Uncovering robust patterns of microRNA co-expression across cancers using Bayesian Relevance Networks.

PubMed

Ramachandran, Parameswaran; Sánchez-Taltavull, Daniel; Perkins, Theodore J

2017-01-01

Co-expression networks have long been used as a tool for investigating the molecular circuitry governing biological systems. However, most algorithms for constructing co-expression networks were developed in the microarray era, before high-throughput sequencing-with its unique statistical properties-became the norm for expression measurement. Here we develop Bayesian Relevance Networks, an algorithm that uses Bayesian reasoning about expression levels to account for the differing levels of uncertainty in expression measurements between highly- and lowly-expressed entities, and between samples with different sequencing depths. It combines data from groups of samples (e.g., replicates) to estimate group expression levels and confidence ranges. It then computes uncertainty-moderated estimates of cross-group correlations between entities, and uses permutation testing to assess their statistical significance. Using large scale miRNA data from The Cancer Genome Atlas, we show that our Bayesian update of the classical Relevance Networks algorithm provides improved reproducibility in co-expression estimates and lower false discovery rates in the resulting co-expression networks. Software is available at www.perkinslab.ca.

A comprehensive analysis on preservation patterns of gene co-expression networks during Alzheimer's disease progression.

PubMed

Ray, Sumanta; Hossain, Sk Md Mosaddek; Khatun, Lutfunnesa; Mukhopadhyay, Anirban

2017-12-20

Alzheimer's disease (AD) is a chronic neuro-degenerative disruption of the brain which involves in large scale transcriptomic variation. The disease does not impact every regions of the brain at the same time, instead it progresses slowly involving somewhat sequential interaction with different regions. Analysis of the expression patterns of the genes in different regions of the brain influenced in AD surely contribute for a enhanced comprehension of AD pathogenesis and shed light on the early characterization of the disease. Here, we have proposed a framework to identify perturbation and preservation characteristics of gene expression patterns across six distinct regions of the brain ("EC", "HIP", "PC", "MTG", "SFG", and "VCX") affected in AD. Co-expression modules were discovered considering a couple of regions at once. These are then analyzed to know the preservation and perturbation characteristics. Different module preservation statistics and a rank aggregation mechanism have been adopted to detect the changes of expression patterns across brain regions. Gene ontology (GO) and pathway based analysis were also carried out to know the biological meaning of preserved and perturbed modules. In this article, we have extensively studied the preservation patterns of co-expressed modules in six distinct brain regions affected in AD. Some modules are emerged as the most preserved while some others are detected as perturbed between a pair of brain regions. Further investigation on the topological properties of preserved and non-preserved modules reveals a substantial association amongst "betweenness centrality" and "degree" of the involved genes. Our findings may render a deeper realization of the preservation characteristics of gene expression patterns in discrete brain regions affected by AD.

Developmental transcriptional profiling reveals key insights into Triticeae reproductive development.

PubMed

Tran, Frances; Penniket, Carolyn; Patel, Rohan V; Provart, Nicholas J; Laroche, André; Rowland, Owen; Robert, Laurian S

2013-06-01

Despite their importance, there remains a paucity of large-scale gene expression-based studies of reproductive development in species belonging to the Triticeae. As a first step to address this deficiency, a gene expression atlas of triticale reproductive development was generated using the 55K Affymetrix GeneChip(®) wheat genome array. The global transcriptional profiles of the anther/pollen, ovary and stigma were analyzed at concurrent developmental stages, and co-expressed as well as preferentially expressed genes were identified. Data analysis revealed both novel and conserved regulatory factors underlying Triticeae floral development and function. This comprehensive resource rests upon detailed gene annotations, and the expression profiles are readily accessible via a web browser. © 2013 Her Majesty the Queen in Right of Canada as represented by the Minister of Agriculture and Agri-Food Canada.

Large-scale production of foot-and-mouth disease virus (serotype Asia1) VLP vaccine in Escherichia coli and protection potency evaluation in cattle.

PubMed

Xiao, Yan; Chen, Hong-Ying; Wang, Yuzhou; Yin, Bo; Lv, Chaochao; Mo, Xiaobing; Yan, He; Xuan, Yajie; Huang, Yuxin; Pang, Wenqiang; Li, Xiangdong; Yuan, Y Adam; Tian, Kegong

2016-07-02

Foot-and-mouth disease (FMD) is an acute, highly contagious disease that infects cloven-hoofed animals. Vaccination is an effective means of preventing and controlling FMD. Compared to conventional inactivated FMDV vaccines, the format of FMDV virus-like particles (VLPs) as a non-replicating particulate vaccine candidate is a promising alternative. In this study, we have developed a co-expression system in E. coli, which drove the expression of FMDV capsid proteins (VP0, VP1, and VP3) in tandem by a single plasmid. The co-expressed FMDV capsid proteins (VP0, VP1, and VP3) were produced in large scale by fermentation at 10 L scale and the chromatographic purified capsid proteins were auto-assembled as VLPs in vitro. Cattle vaccinated with a single dose of the subunit vaccine, comprising in vitro assembled FMDV VLP and adjuvant, developed FMDV-specific antibody response (ELISA antibodies and neutralizing antibodies) with the persistent period of 6 months. Moreover, cattle vaccinated with the subunit vaccine showed the high protection potency with the 50 % bovine protective dose (PD50) reaching 11.75 PD50 per dose. Our data strongly suggest that in vitro assembled recombinant FMDV VLPs produced from E. coli could function as a potent FMDV vaccine candidate against FMDV Asia1 infection. Furthermore, the robust protein expression and purification approaches described here could lead to the development of industrial level large-scale production of E. coli-based VLPs against FMDV infections with different serotypes.

Reconstruction of the genome-scale co-expression network for the Hippo signaling pathway in colorectal cancer.

PubMed

Dehghanian, Fariba; Hojati, Zohreh; Hosseinkhan, Nazanin; Mousavian, Zaynab; Masoudi-Nejad, Ali

2018-05-26

The Hippo signaling pathway (HSP) has been identified as an essential and complex signaling pathway for tumor suppression that coordinates proliferation, differentiation, cell death, cell growth and stemness. In the present study, we conducted a genome-scale co-expression analysis to reconstruct the HSP in colorectal cancer (CRC). Five key modules were detected through network clustering, and a detailed discussion of two modules containing respectively 18 and 13 over and down-regulated members of HSP was provided. Our results suggest new potential regulatory factors in the HSP. The detected modules also suggest novel genes contributing to CRC. Moreover, differential expression analysis confirmed the differential expression pattern of HSP members and new suggested regulatory factors between tumor and normal samples. These findings can further reveal the importance of HSP in CRC. Copyright © 2018 Elsevier Ltd. All rights reserved.

Coexistence trend contingent to Mediterranean oaks with different leaf habits.

PubMed

Di Paola, Arianna; Paquette, Alain; Trabucco, Antonio; Mereu, Simone; Valentini, Riccardo; Paparella, Francesco

2017-05-01

In a previous work we developed a mathematical model to explain the co-occurrence of evergreen and deciduous oak groups in the Mediterranean region, regarded as one of the distinctive features of Mediterranean biodiversity. The mathematical analysis showed that a stabilizing mechanism resulting from niche difference (i.e. different water use and water stress tolerance) between groups allows their coexistence at intermediate values of suitable soil water content. A simple formal derivation of the model expresses this hypothesis in a testable form linked uniquely to the actual evapotranspiration of forests community. In the present work we ascertain whether this simplified conclusion possesses some degree of explanatory power by comparing available data on oaks distributions and remotely sensed evapotranspiration (MODIS product) in a large-scale survey embracing the western Mediterranean area. Our findings confirmed the basic assumptions of model addressed on large scale, but also revealed asymmetric responses to water use and water stress tolerance between evergreen and deciduous oaks that should be taken into account to increase the understating of species interactions and, ultimately, improve the modeling capacity to explain co-occurrence.

Integrated analysis of long non-coding RNAs in human gastric cancer: An in silico study.

PubMed

Han, Weiwei; Zhang, Zhenyu; He, Bangshun; Xu, Yijun; Zhang, Jun; Cao, Weijun

2017-01-01

Accumulating evidence highlights the important role of long non-coding RNAs (lncRNAs) in a large number of biological processes. However, the knowledge of genome scale expression of lncRNAs and their potential biological function in gastric cancer is still lacking. Using RNA-seq data from 420 gastric cancer patients in The Cancer Genome Atlas (TCGA), we identified 1,294 lncRNAs differentially expressed in gastric cancer compared with adjacent normal tissues. We also found 247 lncRNAs differentially expressed between intestinal subtype and diffuse subtype. Survival analysis revealed 33 lncRNAs independently associated with patient overall survival, of which 6 lncRNAs were validated in the internal validation set. There were 181 differentially expressed lncRNAs located in the recurrent somatic copy number alterations (SCNAs) regions and their correlations between copy number and RNA expression level were also analyzed. In addition, we inferred the function of lncRNAs by construction of a co-expression network for mRNAs and lncRNAs. Together, this study presented an integrative analysis of lncRNAs in gastric cancer and provided a valuable resource for further functional research of lncRNAs in gastric cancer.

A Review of Feature Extraction Software for Microarray Gene Expression Data

PubMed Central

Tan, Ching Siang; Ting, Wai Soon; Mohamad, Mohd Saberi; Chan, Weng Howe; Deris, Safaai; Ali Shah, Zuraini

2014-01-01

When gene expression data are too large to be processed, they are transformed into a reduced representation set of genes. Transforming large-scale gene expression data into a set of genes is called feature extraction. If the genes extracted are carefully chosen, this gene set can extract the relevant information from the large-scale gene expression data, allowing further analysis by using this reduced representation instead of the full size data. In this paper, we review numerous software applications that can be used for feature extraction. The software reviewed is mainly for Principal Component Analysis (PCA), Independent Component Analysis (ICA), Partial Least Squares (PLS), and Local Linear Embedding (LLE). A summary and sources of the software are provided in the last section for each feature extraction method. PMID:25250315

Assessing the utility of gene co-expression stability in combination with correlation in the analysis of protein-protein interaction networks

PubMed Central

2011-01-01

Background Gene co-expression, in the form of a correlation coefficient, has been valuable in the analysis, classification and prediction of protein-protein interactions. However, it is susceptible to bias from a few samples having a large effect on the correlation coefficient. Gene co-expression stability is a means of quantifying this bias, with high stability indicating robust, unbiased co-expression correlation coefficients. We assess the utility of gene co-expression stability as an additional measure to support the co-expression correlation in the analysis of protein-protein interaction networks. Results We studied the patterns of co-expression correlation and stability in interacting proteins with respect to their interaction promiscuity, levels of intrinsic disorder, and essentiality or disease-relatedness. Co-expression stability, along with co-expression correlation, acts as a better classifier of hub proteins in interaction networks, than co-expression correlation alone, enabling the identification of a class of hubs that are functionally distinct from the widely accepted transient (date) and obligate (party) hubs. Proteins with high levels of intrinsic disorder have low co-expression correlation and high stability with their interaction partners suggesting their involvement in transient interactions, except for a small group that have high co-expression correlation and are typically subunits of stable complexes. Similar behavior was seen for disease-related and essential genes. Interacting proteins that are both disordered have higher co-expression stability than ordered protein pairs. Using co-expression correlation and stability, we found that transient interactions are more likely to occur between an ordered and a disordered protein while obligate interactions primarily occur between proteins that are either both ordered, or disordered. Conclusions We observe that co-expression stability shows distinct patterns in structurally and functionally different groups of proteins and interactions. We conclude that it is a useful and important measure to be used in concert with gene co-expression correlation for further insights into the characteristics of proteins in the context of their interaction network. PMID:22369639

High-efficiency Agrobacterium-mediated transformation of Norway spruce (Picea abies) and loblolly pine (Pinus taeda)

NASA Technical Reports Server (NTRS)

Wenck, A. R.; Quinn, M.; Whetten, R. W.; Pullman, G.; Sederoff, R.; Brown, C. S. (Principal Investigator)

1999-01-01

Agrobacterium-mediated gene transfer is the method of choice for many plant biotechnology laboratories; however, large-scale use of this organism in conifer transformation has been limited by difficult propagation of explant material, selection efficiencies and low transformation frequency. We have analyzed co-cultivation conditions and different disarmed strains of Agrobacterium to improve transformation. Additional copies of virulence genes were added to three common disarmed strains. These extra virulence genes included either a constitutively active virG or extra copies of virG and virB, both from pTiBo542. In experiments with Norway spruce, we increased transformation efficiencies 1000-fold from initial experiments where little or no transient expression was detected. Over 100 transformed lines expressing the marker gene beta-glucuronidase (GUS) were generated from rapidly dividing embryogenic suspension-cultured cells co-cultivated with Agrobacterium. GUS activity was used to monitor transient expression and to further test lines selected on kanamycin-containing medium. In loblolly pine, transient expression increased 10-fold utilizing modified Agrobacterium strains. Agrobacterium-mediated gene transfer is a useful technique for large-scale generation of transgenic Norway spruce and may prove useful for other conifer species.

Southern Ocean carbon-wind stress feedback

NASA Astrophysics Data System (ADS)

Bronselaer, Ben; Zanna, Laure; Munday, David R.; Lowe, Jason

2018-02-01

The Southern Ocean is the largest sink of anthropogenic carbon in the present-day climate. Here, Southern Ocean pCO2 and its dependence on wind forcing are investigated using an equilibrium mixed layer carbon budget. This budget is used to derive an expression for Southern Ocean pCO2 sensitivity to wind stress. Southern Ocean pCO2 is found to vary as the square root of area-mean wind stress, arising from the dominance of vertical mixing over other processes such as lateral Ekman transport. The expression for pCO2 is validated using idealised coarse-resolution ocean numerical experiments. Additionally, we show that increased (decreased) stratification through surface warming reduces (increases) the sensitivity of the Southern Ocean pCO2 to wind stress. The scaling is then used to estimate the wind-stress induced changes of atmospheric pCO_2 in CMIP5 models using only a handful of parameters. The scaling is further used to model the anthropogenic carbon sink, showing a long-term reversal of the Southern Ocean sink for large wind stress strength.

Bi-Force: large-scale bicluster editing and its application to gene expression data biclustering

PubMed Central

Sun, Peng; Speicher, Nora K.; Röttger, Richard; Guo, Jiong; Baumbach, Jan

2014-01-01

Abstract The explosion of the biological data has dramatically reformed today's biological research. The need to integrate and analyze high-dimensional biological data on a large scale is driving the development of novel bioinformatics approaches. Biclustering, also known as ‘simultaneous clustering’ or ‘co-clustering’, has been successfully utilized to discover local patterns in gene expression data and similar biomedical data types. Here, we contribute a new heuristic: ‘Bi-Force’. It is based on the weighted bicluster editing model, to perform biclustering on arbitrary sets of biological entities, given any kind of pairwise similarities. We first evaluated the power of Bi-Force to solve dedicated bicluster editing problems by comparing Bi-Force with two existing algorithms in the BiCluE software package. We then followed a biclustering evaluation protocol in a recent review paper from Eren et al. (2013) (A comparative analysis of biclustering algorithms for gene expressiondata. Brief. Bioinform., 14:279–292.) and compared Bi-Force against eight existing tools: FABIA, QUBIC, Cheng and Church, Plaid, BiMax, Spectral, xMOTIFs and ISA. To this end, a suite of synthetic datasets as well as nine large gene expression datasets from Gene Expression Omnibus were analyzed. All resulting biclusters were subsequently investigated by Gene Ontology enrichment analysis to evaluate their biological relevance. The distinct theoretical foundation of Bi-Force (bicluster editing) is more powerful than strict biclustering. We thus outperformed existing tools with Bi-Force at least when following the evaluation protocols from Eren et al. Bi-Force is implemented in Java and integrated into the open source software package of BiCluE. The software as well as all used datasets are publicly available at http://biclue.mpi-inf.mpg.de. PMID:24682815

Co-expression network analysis of duplicate genes in maize (Zea mays L.) reveals no subgenome bias.

PubMed

Li, Lin; Briskine, Roman; Schaefer, Robert; Schnable, Patrick S; Myers, Chad L; Flagel, Lex E; Springer, Nathan M; Muehlbauer, Gary J

2016-11-04

Gene duplication is prevalent in many species and can result in coding and regulatory divergence. Gene duplications can be classified as whole genome duplication (WGD), tandem and inserted (non-syntenic). In maize, WGD resulted in the subgenomes maize1 and maize2, of which maize1 is considered the dominant subgenome. However, the landscape of co-expression network divergence of duplicate genes in maize is still largely uncharacterized. To address the consequence of gene duplication on co-expression network divergence, we developed a gene co-expression network from RNA-seq data derived from 64 different tissues/stages of the maize reference inbred-B73. WGD, tandem and inserted gene duplications exhibited distinct regulatory divergence. Inserted duplicate genes were more likely to be singletons in the co-expression networks, while WGD duplicate genes were likely to be co-expressed with other genes. Tandem duplicate genes were enriched in the co-expression pattern where co-expressed genes were nearly identical for the duplicates in the network. Older gene duplications exhibit more extensive co-expression variation than younger duplications. Overall, non-syntenic genes primarily from inserted duplications show more co-expression divergence. Also, such enlarged co-expression divergence is significantly related to duplication age. Moreover, subgenome dominance was not observed in the co-expression networks - maize1 and maize2 exhibit similar levels of intra subgenome correlations. Intriguingly, the level of inter subgenome co-expression was similar to the level of intra subgenome correlations, and genes from specific subgenomes were not likely to be the enriched in co-expression network modules and the hub genes were not predominantly from any specific subgenomes in maize. Our work provides a comprehensive analysis of maize co-expression network divergence for three different types of gene duplications and identifies potential relationships between duplication types, duplication ages and co-expression consequences.

Integrating transient heterogeneity of non-photochemical quenching in shade-grown heterobaric leaves of avocado (Persea americana L.): responses to CO2 concentration, stomatal occlusion, dehydration and relative humidity.

PubMed

Takayama, Kotaro; King, Diana; Robinson, Sharon A; Osmond, Barry

2013-11-01

Long-lived shade leaves of avocado had extremely low rates of photosynthesis. Gas exchange measurements of photosynthesis were of limited use, so we resorted to Chl fluorescence imaging (CFI) and spot measurements to evaluate photosynthetic electron transport rates (ETRs) and non-photochemical quenching (NPQ). Imaging revealed a remarkable transient heterogeneity of NPQ during photosynthetic induction in these hypostomatous, heterobaric leaves, but was adequately integrated by spot measurements, despite long-lasting artifacts from repeated saturating flashes during assays. Major veins (mid-vein, first- and second-order veins) defined areas of more static large-scale heterogeneous NPQ, with more dynamic small-scale heterogeneity most strongly expressed in mesophyll cells between third- and fourth-order veins. Both responded to external CO2 concentration ([CO2]), occlusion of stomata with Vaseline™, leaf dehydration and relative humidity (RH). We interpreted these responses in terms of independent behavior of stomata in adjacent areoles that was largely expressed through CO2-limited photosynthesis. Heterogeneity was most pronounced and prolonged in the absence of net CO2 fixation in 100 p.p.m. [CO2] when respiratory and photorespiratory CO2 cycling constrained the inferred ETR to ~75% of values in 400 or 700 p.p.m. [CO2]. Likewise, sustained higher NPQ under Vaseline™, after dehydration or at low RH, also restricted ETR to ~75% of control values. Low NPQ in chloroplast-containing cells adjacent to major veins but remote from stomata suggested internal sources of high [CO2] in these tissues.

A Gene Co-Expression Network in Whole Blood of Schizophrenia Patients Is Independent of Antipsychotic-Use and Enriched for Brain-Expressed Genes

PubMed Central

de Jong, Simone; Boks, Marco P. M.; Fuller, Tova F.; Strengman, Eric; Janson, Esther; de Kovel, Carolien G. F.; Ori, Anil P. S.; Vi, Nancy; Mulder, Flip; Blom, Jan Dirk; Glenthøj, Birte; Schubart, Chris D.; Cahn, Wiepke; Kahn, René S.; Horvath, Steve; Ophoff, Roel A.

2012-01-01

Despite large-scale genome-wide association studies (GWAS), the underlying genes for schizophrenia are largely unknown. Additional approaches are therefore required to identify the genetic background of this disorder. Here we report findings from a large gene expression study in peripheral blood of schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co-expression modules associated with schizophrenia. Several of these disease related modules are likely to reflect expression changes due to antipsychotic medication. However, two of the disease modules could be replicated in an independent second data set involving antipsychotic-free patients and controls. One of these robustly defined disease modules is significantly enriched with brain-expressed genes and with genetic variants that were implicated in a GWAS study, which could imply a causal role in schizophrenia etiology. The most highly connected intramodular hub gene in this module (ABCF1), is located in, and regulated by the major histocompatibility (MHC) complex, which is intriguing in light of the fact that common allelic variants from the MHC region have been implicated in schizophrenia. This suggests that the MHC increases schizophrenia susceptibility via altered gene expression of regulatory genes in this network. PMID:22761806

State-resolved Thermal/Hyperthermal Dynamics of Atmospheric Species

DTIC Science & Technology

2015-06-23

gas -room temperature ionic liquid (RTIL) interfaces. 2) Large scale trajectory simulations for theoretical analysis of gas - liquid scattering studies...areas: 1) Diode laser and LIF studies of hyperthermal CO2 and NO collisions at the gas -room temperature ionic liquid (RTIL) interfaces. 2) Large...scale trajectory simulations for theoretical analysis of gas - liquid scattering studies, 3) LIF data for state-resolved scattering of hyperthermal NO at

bigSCale: an analytical framework for big-scale single-cell data.

PubMed

Iacono, Giovanni; Mereu, Elisabetta; Guillaumet-Adkins, Amy; Corominas, Roser; Cuscó, Ivon; Rodríguez-Esteban, Gustavo; Gut, Marta; Pérez-Jurado, Luis Alberto; Gut, Ivo; Heyn, Holger

2018-06-01

Single-cell RNA sequencing (scRNA-seq) has significantly deepened our insights into complex tissues, with the latest techniques capable of processing tens of thousands of cells simultaneously. Analyzing increasing numbers of cells, however, generates extremely large data sets, extending processing time and challenging computing resources. Current scRNA-seq analysis tools are not designed to interrogate large data sets and often lack sensitivity to identify marker genes. With bigSCale, we provide a scalable analytical framework to analyze millions of cells, which addresses the challenges associated with large data sets. To handle the noise and sparsity of scRNA-seq data, bigSCale uses large sample sizes to estimate an accurate numerical model of noise. The framework further includes modules for differential expression analysis, cell clustering, and marker identification. A directed convolution strategy allows processing of extremely large data sets, while preserving transcript information from individual cells. We evaluated the performance of bigSCale using both a biological model of aberrant gene expression in patient-derived neuronal progenitor cells and simulated data sets, which underlines the speed and accuracy in differential expression analysis. To test its applicability for large data sets, we applied bigSCale to assess 1.3 million cells from the mouse developing forebrain. Its directed down-sampling strategy accumulates information from single cells into index cell transcriptomes, thereby defining cellular clusters with improved resolution. Accordingly, index cell clusters identified rare populations, such as reelin ( Reln )-positive Cajal-Retzius neurons, for which we report previously unrecognized heterogeneity associated with distinct differentiation stages, spatial organization, and cellular function. Together, bigSCale presents a solution to address future challenges of large single-cell data sets. © 2018 Iacono et al.; Published by Cold Spring Harbor Laboratory Press.

Large-scale transcriptome analysis reveals arabidopsis metabolic pathways are frequently influenced by different pathogens.

PubMed

Jiang, Zhenhong; He, Fei; Zhang, Ziding

2017-07-01

Through large-scale transcriptional data analyses, we highlighted the importance of plant metabolism in plant immunity and identified 26 metabolic pathways that were frequently influenced by the infection of 14 different pathogens. Reprogramming of plant metabolism is a common phenomenon in plant defense responses. Currently, a large number of transcriptional profiles of infected tissues in Arabidopsis (Arabidopsis thaliana) have been deposited in public databases, which provides a great opportunity to understand the expression patterns of metabolic pathways during plant defense responses at the systems level. Here, we performed a large-scale transcriptome analysis based on 135 previously published expression samples, including 14 different pathogens, to explore the expression pattern of Arabidopsis metabolic pathways. Overall, metabolic genes are significantly changed in expression during plant defense responses. Upregulated metabolic genes are enriched on defense responses, and downregulated genes are enriched on photosynthesis, fatty acid and lipid metabolic processes. Gene set enrichment analysis (GSEA) identifies 26 frequently differentially expressed metabolic pathways (FreDE_Paths) that are differentially expressed in more than 60% of infected samples. These pathways are involved in the generation of energy, fatty acid and lipid metabolism as well as secondary metabolite biosynthesis. Clustering analysis based on the expression levels of these 26 metabolic pathways clearly distinguishes infected and control samples, further suggesting the importance of these metabolic pathways in plant defense responses. By comparing with FreDE_Paths from abiotic stresses, we find that the expression patterns of 26 FreDE_Paths from biotic stresses are more consistent across different infected samples. By investigating the expression correlation between transcriptional factors (TFs) and FreDE_Paths, we identify several notable relationships. Collectively, the current study will deepen our understanding of plant metabolism in plant immunity and provide new insights into disease-resistant crop improvement.

Analysis of co-occurrence toponyms in web pages based on complex networks

NASA Astrophysics Data System (ADS)

Zhong, Xiang; Liu, Jiajun; Gao, Yong; Wu, Lun

2017-01-01

A large number of geographical toponyms exist in web pages and other documents, providing abundant geographical resources for GIS. It is very common for toponyms to co-occur in the same documents. To investigate these relations associated with geographic entities, a novel complex network model for co-occurrence toponyms is proposed. Then, 12 toponym co-occurrence networks are constructed from the toponym sets extracted from the People's Daily Paper documents of 2010. It is found that two toponyms have a high co-occurrence probability if they are at the same administrative level or if they possess a part-whole relationship. By applying complex network analysis methods to toponym co-occurrence networks, we find the following characteristics. (1) The navigation vertices of the co-occurrence networks can be found by degree centrality analysis. (2) The networks express strong cluster characteristics, and it takes only several steps to reach one vertex from another one, implying that the networks are small-world graphs. (3) The degree distribution satisfies the power law with an exponent of 1.7, so the networks are free-scale. (4) The networks are disassortative and have similar assortative modes, with assortative exponents of approximately 0.18 and assortative indexes less than 0. (5) The frequency of toponym co-occurrence is weakly negatively correlated with geographic distance, but more strongly negatively correlated with administrative hierarchical distance. Considering the toponym frequencies and co-occurrence relationships, a novel method based on link analysis is presented to extract the core toponyms from web pages. This method is suitable and effective for geographical information retrieval.

Gene Expression Browser: Large-Scale and Cross-Experiment Microarray Data Management, Search & Visualization

USDA-ARS?s Scientific Manuscript database

The amount of microarray gene expression data in public repositories has been increasing exponentially for the last couple of decades. High-throughput microarray data integration and analysis has become a critical step in exploring the large amount of expression data for biological discovery. Howeve...

paraGSEA: a scalable approach for large-scale gene expression profiling

PubMed Central

Peng, Shaoliang; Yang, Shunyun

2017-01-01

Abstract More studies have been conducted using gene expression similarity to identify functional connections among genes, diseases and drugs. Gene Set Enrichment Analysis (GSEA) is a powerful analytical method for interpreting gene expression data. However, due to its enormous computational overhead in the estimation of significance level step and multiple hypothesis testing step, the computation scalability and efficiency are poor on large-scale datasets. We proposed paraGSEA for efficient large-scale transcriptome data analysis. By optimization, the overall time complexity of paraGSEA is reduced from O(mn) to O(m+n), where m is the length of the gene sets and n is the length of the gene expression profiles, which contributes more than 100-fold increase in performance compared with other popular GSEA implementations such as GSEA-P, SAM-GS and GSEA2. By further parallelization, a near-linear speed-up is gained on both workstations and clusters in an efficient manner with high scalability and performance on large-scale datasets. The analysis time of whole LINCS phase I dataset (GSE92742) was reduced to nearly half hour on a 1000 node cluster on Tianhe-2, or within 120 hours on a 96-core workstation. The source code of paraGSEA is licensed under the GPLv3 and available at http://github.com/ysycloud/paraGSEA. PMID:28973463

Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation

PubMed Central

Faria, José P.; Davis, James J.; Edirisinghe, Janaka N.; Taylor, Ronald C.; Weisenhorn, Pamela; Olson, Robert D.; Stevens, Rick L.; Rocha, Miguel; Rocha, Isabel; Best, Aaron A.; DeJongh, Matthew; Tintle, Nathan L.; Parrello, Bruce; Overbeek, Ross; Henry, Christopher S.

2016-01-01

Understanding gene function and regulation is essential for the interpretation, prediction, and ultimate design of cell responses to changes in the environment. An important step toward meeting the challenge of understanding gene function and regulation is the identification of sets of genes that are always co-expressed. These gene sets, Atomic Regulons (ARs), represent fundamental units of function within a cell and could be used to associate genes of unknown function with cellular processes and to enable rational genetic engineering of cellular systems. Here, we describe an approach for inferring ARs that leverages large-scale expression data sets, gene context, and functional relationships among genes. We computed ARs for Escherichia coli based on 907 gene expression experiments and compared our results with gene clusters produced by two prevalent data-driven methods: Hierarchical clustering and k-means clustering. We compared ARs and purely data-driven gene clusters to the curated set of regulatory interactions for E. coli found in RegulonDB, showing that ARs are more consistent with gold standard regulons than are data-driven gene clusters. We further examined the consistency of ARs and data-driven gene clusters in the context of gene interactions predicted by Context Likelihood of Relatedness (CLR) analysis, finding that the ARs show better agreement with CLR predicted interactions. We determined the impact of increasing amounts of expression data on AR construction and find that while more data improve ARs, it is not necessary to use the full set of gene expression experiments available for E. coli to produce high quality ARs. In order to explore the conservation of co-regulated gene sets across different organisms, we computed ARs for Shewanella oneidensis, Pseudomonas aeruginosa, Thermus thermophilus, and Staphylococcus aureus, each of which represents increasing degrees of phylogenetic distance from E. coli. Comparison of the organism-specific ARs showed that the consistency of AR gene membership correlates with phylogenetic distance, but there is clear variability in the regulatory networks of closely related organisms. As large scale expression data sets become increasingly common for model and non-model organisms, comparative analyses of atomic regulons will provide valuable insights into fundamental regulatory modules used across the bacterial domain. PMID:27933038

Genomewide transcriptional reprogramming in the seagrass Cymodocea nodosa under experimental ocean acidification.

PubMed

Ruocco, Miriam; Musacchia, Francesco; Olivé, Irene; Costa, Monya M; Barrote, Isabel; Santos, Rui; Sanges, Remo; Procaccini, Gabriele; Silva, João

2017-08-01

Here, we report the first use of massive-scale RNA-sequencing to explore seagrass response to CO 2 -driven ocean acidification (OA). Large-scale gene expression changes in the seagrass Cymodocea nodosa occurred at CO 2 levels projected by the end of the century. C. nodosa transcriptome was obtained using Illumina RNA-Seq technology and de novo assembly, and differential gene expression was explored in plants exposed to short-term high CO 2 /low pH conditions. At high pCO 2 , there was a significant increased expression of transcripts associated with photosynthesis, including light reaction functions and CO 2 fixation, and also to respiratory pathways, specifically for enzymes involved in glycolysis, in the tricarboxylic acid cycle and in the energy metabolism of the mitochondrial electron transport. The upregulation of respiratory metabolism is probably supported by the increased availability of photosynthates and increased energy demand for biosynthesis and stress-related processes under elevated CO 2 and low pH. The upregulation of several chaperones resembling heat stress-induced changes in gene expression highlighted the positive role these proteins play in tolerance to intracellular acid stress in seagrasses. OA further modifies C. nodosa secondary metabolism inducing the transcription of enzymes related to biosynthesis of carbon-based secondary compounds, in particular the synthesis of polyphenols and isoprenoid compounds that have a variety of biological functions including plant defence. By demonstrating which physiological processes are most sensitive to OA, this research provides a major advance in the understanding of seagrass metabolism in the context of altered seawater chemistry from global climate change. © 2017 John Wiley & Sons Ltd.

Changes in gene expression, cell physiology and toxicity of the harmful cyanobacterium Microcystis aeruginosa at elevated CO2

PubMed Central

Sandrini, Giovanni; Cunsolo, Serena; Schuurmans, J. Merijn; Matthijs, Hans C. P.; Huisman, Jef

2015-01-01

Rising CO2 concentrations may have large effects on aquatic microorganisms. In this study, we investigated how elevated pCO2 affects the harmful freshwater cyanobacterium Microcystis aeruginosa. This species is capable of producing dense blooms and hepatotoxins called microcystins. Strain PCC 7806 was cultured in chemostats that were shifted from low to high pCO2 conditions. This resulted in a transition from a C-limited to a light-limited steady state, with a ~2.7-fold increase of the cyanobacterial biomass and ~2.5-fold more microcystin per cell. Cells increased their chlorophyll a and phycocyanin content, and raised their PSI/PSII ratio at high pCO2. Surprisingly, cells had a lower dry weight and contained less carbohydrates, which might be an adaptation to improve the buoyancy of Microcystis when light becomes more limiting at high pCO2. Only 234 of the 4691 genes responded to elevated pCO2. For instance, expression of the carboxysome, RuBisCO, photosystem and C metabolism genes did not change significantly, and only a few N assimilation genes were expressed differently. The lack of large-scale changes in the transcriptome could suit a buoyant species that lives in eutrophic lakes with strong CO2 fluctuations very well. However, we found major responses in inorganic carbon uptake. At low pCO2, cells were mainly dependent on bicarbonate uptake, whereas at high pCO2 gene expression of the bicarbonate uptake systems was down-regulated and cells shifted to CO2 and low-affinity bicarbonate uptake. These results show that the need for high-affinity bicarbonate uptake systems ceases at elevated CO2. Moreover, the combination of an increased cyanobacterial abundance, improved buoyancy, and higher toxin content per cell indicates that rising atmospheric CO2 levels may increase the problems associated with the harmful cyanobacterium Microcystis in eutrophic lakes. PMID:25999931

Cell-free translational screening of an expression sequence tag library of Clonorchis sinensis for novel antigen discovery.

PubMed

Kasi, Devi; Catherine, Christy; Lee, Seung-Won; Lee, Kyung-Ho; Kim, Yu Jung; Ro Lee, Myeong; Ju, Jung Won; Kim, Dong-Myung

2017-05-01

The rapidly evolving cloning and sequencing technologies have enabled understanding of genomic structure of parasite genomes, opening up new ways of combatting parasite-related diseases. To make the most of the exponentially accumulating genomic data, however, it is crucial to analyze the proteins encoded by these genomic sequences. In this study, we adopted an engineered cell-free protein synthesis system for large-scale expression screening of an expression sequence tag (EST) library of Clonorchis sinensis to identify potential antigens that can be used for diagnosis and treatment of clonorchiasis. To allow high-throughput expression and identification of individual genes comprising the library, a cell-free synthesis reaction was designed such that both the template DNA and the expressed proteins were co-immobilized on the same microbeads, leading to microbead-based linkage of the genotype and phenotype. This reaction configuration allowed streamlined expression, recovery, and analysis of proteins. This approach enabled us to identify 21 antigenic proteins. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:832-837, 2017. © 2017 American Institute of Chemical Engineers.

Large clusters of co-expressed genes in the Drosophila genome.

PubMed

Boutanaev, Alexander M; Kalmykova, Alla I; Shevelyov, Yuri Y; Nurminsky, Dmitry I

2002-12-12

Clustering of co-expressed, non-homologous genes on chromosomes implies their co-regulation. In lower eukaryotes, co-expressed genes are often found in pairs. Clustering of genes that share aspects of transcriptional regulation has also been reported in higher eukaryotes. To advance our understanding of the mode of coordinated gene regulation in multicellular organisms, we performed a genome-wide analysis of the chromosomal distribution of co-expressed genes in Drosophila. We identified a total of 1,661 testes-specific genes, one-third of which are clustered on chromosomes. The number of clusters of three or more genes is much higher than expected by chance. We observed a similar trend for genes upregulated in the embryo and in the adult head, although the expression pattern of individual genes cannot be predicted on the basis of chromosomal position alone. Our data suggest that the prevalent mechanism of transcriptional co-regulation in higher eukaryotes operates with extensive chromatin domains that comprise multiple genes.

Effects of seawater acidification on gene expression: resolving broader-scale trends in sea urchins.

PubMed

Evans, Tyler G; Watson-Wynn, Priscilla

2014-06-01

Sea urchins are ecologically and economically important calcifying organisms threatened by acidification of the global ocean caused by anthropogenic CO2 emissions. Propelled by the sequencing of the purple sea urchin (Strongylocentrotus purpuratus) genome, profiling changes in gene expression during exposure to high pCO2 seawater has emerged as a powerful and increasingly common method to infer the response of urchins to ocean change. However, analyses of gene expression are sensitive to experimental methodology, and comparisons between studies of genes regulated by ocean acidification are most often made in the context of major caveats. Here we perform meta-analyses as a means of minimizing experimental discrepancies and resolving broader-scale trends regarding the effects of ocean acidification on gene expression in urchins. Analyses across eight studies and four urchin species largely support prevailing hypotheses about the impact of ocean acidification on marine calcifiers. The predominant expression pattern involved the down-regulation of genes within energy-producing pathways, a clear indication of metabolic depression. Genes with functions in ion transport were significantly over-represented and are most plausibly contributing to intracellular pH regulation. Expression profiles provided extensive evidence for an impact on biomineralization, epitomized by the down-regulation of seven spicule matrix proteins. In contrast, expression profiles provided limited evidence for CO2-mediated developmental delay or induction of a cellular stress response. Congruence between studies of gene expression and the ocean acidification literature in general validates the accuracy of gene expression in predicting the consequences of ocean change and justifies its continued use in future studies. © 2014 Marine Biological Laboratory.

Bi-Force: large-scale bicluster editing and its application to gene expression data biclustering.

PubMed

Sun, Peng; Speicher, Nora K; Röttger, Richard; Guo, Jiong; Baumbach, Jan

2014-05-01

The explosion of the biological data has dramatically reformed today's biological research. The need to integrate and analyze high-dimensional biological data on a large scale is driving the development of novel bioinformatics approaches. Biclustering, also known as 'simultaneous clustering' or 'co-clustering', has been successfully utilized to discover local patterns in gene expression data and similar biomedical data types. Here, we contribute a new heuristic: 'Bi-Force'. It is based on the weighted bicluster editing model, to perform biclustering on arbitrary sets of biological entities, given any kind of pairwise similarities. We first evaluated the power of Bi-Force to solve dedicated bicluster editing problems by comparing Bi-Force with two existing algorithms in the BiCluE software package. We then followed a biclustering evaluation protocol in a recent review paper from Eren et al. (2013) (A comparative analysis of biclustering algorithms for gene expressiondata. Brief. Bioinform., 14:279-292.) and compared Bi-Force against eight existing tools: FABIA, QUBIC, Cheng and Church, Plaid, BiMax, Spectral, xMOTIFs and ISA. To this end, a suite of synthetic datasets as well as nine large gene expression datasets from Gene Expression Omnibus were analyzed. All resulting biclusters were subsequently investigated by Gene Ontology enrichment analysis to evaluate their biological relevance. The distinct theoretical foundation of Bi-Force (bicluster editing) is more powerful than strict biclustering. We thus outperformed existing tools with Bi-Force at least when following the evaluation protocols from Eren et al. Bi-Force is implemented in Java and integrated into the open source software package of BiCluE. The software as well as all used datasets are publicly available at http://biclue.mpi-inf.mpg.de. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Bridging the Gap between Gene Expression and Metabolic Phenotype via Kinetic Models

DTIC Science & Technology

2013-07-22

construction of large-scale kinetic models of metabolism, namely, the detailed definition of appro- priate reaction rate expressions and the determination...mole of bio- mass precursor, and the summation included only the drain fluxes to biomass. Note that this definition of the biomass growth rate can... 4P G ly co ly si s Glu Pro Arg Lys Glucose-6P Carbohydrates RNA Lipids Acetaldehyde Figure 2 Metabolic network of the central carbon

Identification of rice genes associated with cosmic-ray response via co-expression gene network analysis.

PubMed

Hwang, Sun-Goo; Kim, Dong Sub; Hwang, Jung Eun; Han, A-Reum; Jang, Cheol Seong

2014-05-15

In order to better understand the biological systems that are affected in response to cosmic ray (CR), we conducted weighted gene co-expression network analysis using the module detection method. By using the Pearson's correlation coefficient (PCC) value, we evaluated complex gene-gene functional interactions between 680 CR-responsive probes from integrated microarray data sets, which included large-scale transcriptional profiling of 1000 microarray samples. These probes were divided into 6 distinct modules that contained 20 enriched gene ontology (GO) functions, such as oxidoreductase activity, hydrolase activity, and response to stimulus and stress. In particular, modules 1 and 2 commonly showed enriched annotation categories such as oxidoreductase activity, including enriched cis-regulatory elements known as ROS-specific regulators. These results suggest that the ROS-mediated irradiation response pathway is affected by CR in modules 1 and 2. We found 243 ionizing radiation (IR)-responsive probes that exhibited similarities in expression patterns in various irradiation microarray data sets. The expression patterns of 6 randomly selected IR-responsive genes were evaluated by quantitative reverse transcription polymerase chain reaction following treatment with CR, gamma rays (GR), and ion beam (IB); similar patterns were observed among these genes under these 3 treatments. Moreover, we constructed subnetworks of IR-responsive genes and evaluated the expression levels of their neighboring genes following GR treatment; similar patterns were observed among them. These results of network-based analyses might provide a clue to understanding the complex biological system related to the CR response in plants. Copyright © 2014 Elsevier B.V. All rights reserved.

CrosstalkNet: A Visualization Tool for Differential Co-expression Networks and Communities.

PubMed

Manem, Venkata; Adam, George Alexandru; Gruosso, Tina; Gigoux, Mathieu; Bertos, Nicholas; Park, Morag; Haibe-Kains, Benjamin

2018-04-15

Variations in physiological conditions can rewire molecular interactions between biological compartments, which can yield novel insights into gain or loss of interactions specific to perturbations of interest. Networks are a promising tool to elucidate intercellular interactions, yet exploration of these large-scale networks remains a challenge due to their high dimensionality. To retrieve and mine interactions, we developed CrosstalkNet, a user friendly, web-based network visualization tool that provides a statistical framework to infer condition-specific interactions coupled with a community detection algorithm for bipartite graphs to identify significantly dense subnetworks. As a case study, we used CrosstalkNet to mine a set of 54 and 22 gene-expression profiles from breast tumor and normal samples, respectively, with epithelial and stromal compartments extracted via laser microdissection. We show how CrosstalkNet can be used to explore large-scale co-expression networks and to obtain insights into the biological processes that govern cross-talk between different tumor compartments. Significance: This web application enables researchers to mine complex networks and to decipher novel biological processes in tumor epithelial-stroma cross-talk as well as in other studies of intercompartmental interactions. Cancer Res; 78(8); 2140-3. ©2018 AACR . ©2018 American Association for Cancer Research.

Large-Scale Analysis of Network Bistability for Human Cancers

PubMed Central

Shiraishi, Tetsuya; Matsuyama, Shinako; Kitano, Hiroaki

2010-01-01

Protein–protein interaction and gene regulatory networks are likely to be locked in a state corresponding to a disease by the behavior of one or more bistable circuits exhibiting switch-like behavior. Sets of genes could be over-expressed or repressed when anomalies due to disease appear, and the circuits responsible for this over- or under-expression might persist for as long as the disease state continues. This paper shows how a large-scale analysis of network bistability for various human cancers can identify genes that can potentially serve as drug targets or diagnosis biomarkers. PMID:20628618

Plant RuBisCo assembly in E. coli with five chloroplast chaperones including BSD2.

PubMed

Aigner, H; Wilson, R H; Bracher, A; Calisse, L; Bhat, J Y; Hartl, F U; Hayer-Hartl, M

2017-12-08

Plant RuBisCo, a complex of eight large and eight small subunits, catalyzes the fixation of CO 2 in photosynthesis. The low catalytic efficiency of RuBisCo provides strong motivation to reengineer the enzyme with the goal of increasing crop yields. However, genetic manipulation has been hampered by the failure to express plant RuBisCo in a bacterial host. We achieved the functional expression of Arabidopsis thaliana RuBisCo in Escherichia coli by coexpressing multiple chloroplast chaperones. These include the chaperonins Cpn60/Cpn20, RuBisCo accumulation factors 1 and 2, RbcX, and bundle-sheath defective-2 (BSD2). Our structural and functional analysis revealed the role of BSD2 in stabilizing an end-state assembly intermediate of eight RuBisCo large subunits until the small subunits become available. The ability to produce plant RuBisCo recombinantly will facilitate efforts to improve the enzyme through mutagenesis. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

CoCoNUT: an efficient system for the comparison and analysis of genomes

PubMed Central

2008-01-01

Background Comparative genomics is the analysis and comparison of genomes from different species. This area of research is driven by the large number of sequenced genomes and heavily relies on efficient algorithms and software to perform pairwise and multiple genome comparisons. Results Most of the software tools available are tailored for one specific task. In contrast, we have developed a novel system CoCoNUT (Computational Comparative geNomics Utility Toolkit) that allows solving several different tasks in a unified framework: (1) finding regions of high similarity among multiple genomic sequences and aligning them, (2) comparing two draft or multi-chromosomal genomes, (3) locating large segmental duplications in large genomic sequences, and (4) mapping cDNA/EST to genomic sequences. Conclusion CoCoNUT is competitive with other software tools w.r.t. the quality of the results. The use of state of the art algorithms and data structures allows CoCoNUT to solve comparative genomics tasks more efficiently than previous tools. With the improved user interface (including an interactive visualization component), CoCoNUT provides a unified, versatile, and easy-to-use software tool for large scale studies in comparative genomics. PMID:19014477

Antisense RNA Downregulation of Coenzyme A Transferase Combined with Alcohol-Aldehyde Dehydrogenase Overexpression Leads to Predominantly Alcohologenic Clostridium acetobutylicum Fermentations

PubMed Central

Tummala, Seshu B.; Junne, Stefan G.; Papoutsakis, Eleftherios T.

2003-01-01

Plasmid pAADB1 for the overexpression of the alcohol-aldehyde dehydrogenase (aad) gene and downregulation of the coenzyme A transferase (CoAT) using antisense RNA (asRNA) against ctfB (the second CoAT gene on the polycistronic aad-ctfA-ctfB message) was used in order to increase the butanol/acetone ratio of Clostridium acetobutylicum ATCC 824 fermentations. Acetone and butanol levels were drastically reduced in 824(pCTFB1AS) (expresses only an asRNA against ctfB) compared to 824(pSOS95del) (plasmid control). Compared to strain 824(pCTFB1AS), 824(pAADB1) fermentations exhibited two profound differences. First, butanol levels were ca. 2.8-fold higher in 824(pAADB1) and restored back to plasmid control levels, thus supporting the hypothesis that asRNA downregulation of ctfB leads to degradation of the whole aad-ctfA-ctfB transcript. Second, ethanol titers in 824(pAADB1) were ca. 23-fold higher and the highest (ca. 200 mM) ever reported in C. acetobutylicum. Western blot analysis confirmed that CoAT was downregulated in 824(pAADB1) at nearly the same levels as in strain 824(pCTFB1AS). Butyrate depletion in 824(pAADB1) fermentations suggested that butyryl-CoA was limiting butanol production in 824(pAADB1). This was confirmed by exogenously adding butyric acid to 824(pAADB1) fermentations to increase the butanol/ethanol ratio. DNA microarray analysis showed that aad overexpression profoundly affects the large-scale transcriptional program of the cells. Several classes of genes were differentially expressed [strain 824(pAADB1) versus strain 824(pCTFB1AS)], including genes of the stress response, sporulation, and chemotaxis. The expression patterns of the CoAT genes (ctfA and ctfB) and aad were consistent with the overexpression of aad and asRNA downregulation of ctfB. PMID:12775702

Antisense RNA downregulation of coenzyme A transferase combined with alcohol-aldehyde dehydrogenase overexpression leads to predominantly alcohologenic Clostridium acetobutylicum fermentations.

PubMed

Tummala, Seshu B; Junne, Stefan G; Papoutsakis, Eleftherios T

2003-06-01

Plasmid pAADB1 for the overexpression of the alcohol-aldehyde dehydrogenase (aad) gene and downregulation of the coenzyme A transferase (CoAT) using antisense RNA (asRNA) against ctfB (the second CoAT gene on the polycistronic aad-ctfA-ctfB message) was used in order to increase the butanol/acetone ratio of Clostridium acetobutylicum ATCC 824 fermentations. Acetone and butanol levels were drastically reduced in 824(pCTFB1AS) (expresses only an asRNA against ctfB) compared to 824(pSOS95del) (plasmid control). Compared to strain 824(pCTFB1AS), 824(pAADB1) fermentations exhibited two profound differences. First, butanol levels were ca. 2.8-fold higher in 824(pAADB1) and restored back to plasmid control levels, thus supporting the hypothesis that asRNA downregulation of ctfB leads to degradation of the whole aad-ctfA-ctfB transcript. Second, ethanol titers in 824(pAADB1) were ca. 23-fold higher and the highest (ca. 200 mM) ever reported in C. acetobutylicum. Western blot analysis confirmed that CoAT was downregulated in 824(pAADB1) at nearly the same levels as in strain 824(pCTFB1AS). Butyrate depletion in 824(pAADB1) fermentations suggested that butyryl-CoA was limiting butanol production in 824(pAADB1). This was confirmed by exogenously adding butyric acid to 824(pAADB1) fermentations to increase the butanol/ethanol ratio. DNA microarray analysis showed that aad overexpression profoundly affects the large-scale transcriptional program of the cells. Several classes of genes were differentially expressed [strain 824(pAADB1) versus strain 824(pCTFB1AS)], including genes of the stress response, sporulation, and chemotaxis. The expression patterns of the CoAT genes (ctfA and ctfB) and aad were consistent with the overexpression of aad and asRNA downregulation of ctfB.

Multilevel Analysis of Trachomatous Trichiasis and Corneal Opacity in Nigeria: The Role of Environmental and Climatic Risk Factors on the Distribution of Disease.

PubMed

Smith, Jennifer L; Sivasubramaniam, Selvaraj; Rabiu, Mansur M; Kyari, Fatima; Solomon, Anthony W; Gilbert, Clare

2015-01-01

The distribution of trachoma in Nigeria is spatially heterogeneous, with large-scale trends observed across the country and more local variation within areas. Relative contributions of individual and cluster-level risk factors to the geographic distribution of disease remain largely unknown. The primary aim of this analysis is to assess the relationship between climatic factors and trachomatous trichiasis (TT) and/or corneal opacity (CO) due to trachoma in Nigeria, while accounting for the effects of individual risk factors and spatial correlation. In addition, we explore the relative importance of variation in the risk of trichiasis and/or corneal opacity (TT/CO) at different levels. Data from the 2007 National Blindness and Visual Impairment Survey were used for this analysis, which included a nationally representative sample of adults aged 40 years and above. Complete data were available from 304 clusters selected using a multi-stage stratified cluster-random sampling strategy. All participants (13,543 individuals) were interviewed and examined by an ophthalmologist for the presence or absence of TT and CO. In addition to field-collected data, remotely sensed climatic data were extracted for each cluster and used to fit Bayesian hierarchical logistic models to disease outcome. The risk of TT/CO was associated with factors at both the individual and cluster levels, with approximately 14% of the total variation attributed to the cluster level. Beyond established individual risk factors (age, gender and occupation), there was strong evidence that environmental/climatic factors at the cluster-level (lower precipitation, higher land surface temperature, higher mean annual temperature and rural classification) were also associated with a greater risk of TT/CO. This study establishes the importance of large-scale risk factors in the geographical distribution of TT/CO in Nigeria, supporting anecdotal evidence that environmental conditions are associated with increased risk in this context and highlighting their potential use in improving estimates of disease burden at large scales.

Development of multitissue microfluidic dynamic array for assessing changes in gene expression associated with channel catfish appetite, growth, metabolism, and intestinal health

USDA-ARS?s Scientific Manuscript database

Large-scale, gene expression methods allow for high throughput analysis of physiological pathways at a fraction of the cost of individual gene expression analysis. Systems, such as the Fluidigm quantitative PCR array described here, can provide powerful assessments of the effects of diet, environme...

Cooperative interactions of LPPR family members in membrane localization and alteration of cellular morphology

PubMed Central

Yu, Panpan; Agbaegbu, Chinyere; Malide, Daniela A.; Wu, Xufeng; Katagiri, Yasuhiro; Hammer, John A.; Geller, Herbert M.

2015-01-01

ABSTRACT The lipid phosphate phosphatase-related proteins (LPPRs), also known as plasticity-related genes (PRGs), are classified as a new brain-enriched subclass of the lipid phosphate phosphatase (LPP) superfamily. They induce membrane protrusions, neurite outgrowth or dendritic spine formation in cell lines and primary neurons. However, the exact roles of LPPRs and the mechanisms underlying their effects are not certain. Here, we present the results of a large-scale proteome analysis to determine LPPR1-interacting proteins using co-immunoprecipitation coupled to mass spectrometry. We identified putative LPPR1-binding proteins involved in various biological processes. Most interestingly, we identified the interaction of LPPR1 with its family member LPPR3, LPPR4 and LPPR5. Their interactions were characterized by co-immunoprecipitation and colocalization analysis using confocal and super-resolution microscopy. Moreover, co-expressing two LPPR members mutually elevated their protein levels, facilitated their plasma membrane localization and resulted in an increased induction of membrane protrusions as well as the phosphorylation of S6 ribosomal protein. Taken together, we revealed a new functional cooperation between LPPR family members and discovered for the first time that LPPRs likely exert their function through forming complex with its family members. PMID:26183180

Development of Anti-Insect Microencapsulated Polypropylene Films Using a Large Scale Film Coating System.

PubMed

Song, Ah Young; Choi, Ha Young; Lee, Eun Song; Han, Jaejoon; Min, Sea C

2018-04-01

Films containing microencapsulated cinnamon oil (CO) were developed using a large-scale production system to protect against the Indian meal moth (Plodia interpunctella). CO at concentrations of 0%, 0.8%, or 1.7% (w/w ink mixture) was microencapsulated with polyvinyl alcohol. The microencapsulated CO emulsion was mixed with ink (47% or 59%, w/w) and thinner (20% or 25%, w/w) and coated on polypropylene (PP) films. The PP film was then laminated with a low-density polyethylene (LDPE) film on the coated side. The film with microencapsulated CO at 1.7% repelled P. interpunctella most effectively. Microencapsulation did not negatively affect insect repelling activity. The release rate of cinnamaldehyde, an active repellent, was lower when CO was microencapsulated than that in the absence of microencapsulation. Thermogravimetric analysis exhibited that microencapsulation prevented the volatilization of CO. The tensile strength, percentage elongation at break, elastic modulus, and water vapor permeability of the films indicated that microencapsulation did not affect the tensile and moisture barrier properties (P > 0.05). The results of this study suggest that effective films for the prevention of Indian meal moth invasion can be produced by the microencapsulation of CO using a large-scale film production system. Low-density polyethylene-laminated polypropylene films printed with ink incorporating microencapsulated cinnamon oil using a large-scale film production system effectively repelled Indian meal moth larvae. Without altering the tensile and moisture barrier properties of the film, microencapsulation resulted in the release of an active repellent for extended periods with a high thermal stability of cinnamon oil, enabling commercial film production at high temperatures. This anti-insect film system may have applications to other food-packaging films that use the same ink-printing platform. © 2018 Institute of Food Technologists®.

Network Compression as a Quality Measure for Protein Interaction Networks

PubMed Central

Royer, Loic; Reimann, Matthias; Stewart, A. Francis; Schroeder, Michael

2012-01-01

With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressible when represented as a network. Here we propose that network compression can be used to compare false positive and false negative noise levels in protein interaction networks. We validate this hypothesis by first confirming the detrimental effect of false positives and false negatives. Second, we show that gold standard networks are more compressible. Third, we show that compressibility correlates with co-expression, co-localization, and shared function. Fourth, we also observe correlation with better protein tagging methods, physiological expression in contrast to over-expression of tagged proteins, and smart pooling approaches for yeast two-hybrid screens. Overall, this new measure is a proxy for both sensitivity and specificity and gives complementary information to standard measures such as average degree and clustering coefficients. PMID:22719828

MPIGeneNet: Parallel Calculation of Gene Co-Expression Networks on Multicore Clusters.

PubMed

Gonzalez-Dominguez, Jorge; Martin, Maria J

2017-10-10

In this work we present MPIGeneNet, a parallel tool that applies Pearson's correlation and Random Matrix Theory to construct gene co-expression networks. It is based on the state-of-the-art sequential tool RMTGeneNet, which provides networks with high robustness and sensitivity at the expenses of relatively long runtimes for large scale input datasets. MPIGeneNet returns the same results as RMTGeneNet but improves the memory management, reduces the I/O cost, and accelerates the two most computationally demanding steps of co-expression network construction by exploiting the compute capabilities of common multicore CPU clusters. Our performance evaluation on two different systems using three typical input datasets shows that MPIGeneNet is significantly faster than RMTGeneNet. As an example, our tool is up to 175.41 times faster on a cluster with eight nodes, each one containing two 12-core Intel Haswell processors. Source code of MPIGeneNet, as well as a reference manual, are available at https://sourceforge.net/projects/mpigenenet/.

Immunological metagene signatures derived from immunogenic cancer cell death associate with improved survival of patients with lung, breast or ovarian malignancies: A large-scale meta-analysis

PubMed Central

Garg, Abhishek D.; De Ruysscher, Dirk; Agostinis, Patrizia

2016-01-01

ABSTRACT The emerging role of the cancer cell-immune cell interface in shaping tumorigenesis/anticancer immunotherapy has increased the need to identify prognostic biomarkers. Henceforth, our primary aim was to identify the immunogenic cell death (ICD)-derived metagene signatures in breast, lung and ovarian cancer that associate with improved patient survival. To this end, we analyzed the prognostic impact of differential gene-expression of 33 pre-clinically-validated ICD-parameters through a large-scale meta-analysis involving 3,983 patients (‘discovery’ dataset) across lung (1,432), breast (1,115) and ovarian (1,436) malignancies. The main results were also substantiated in ‘validation’ datasets consisting of 818 patients of same cancer-types (i.e. 285 breast/274 lung/259 ovarian). The ICD-associated parameters exhibited a highly-clustered and largely cancer type-specific prognostic impact. Interestingly, we delineated ICD-derived consensus-metagene signatures that exhibited a positive prognostic impact that was either cancer type-independent or specific. Importantly, most of these ICD-derived consensus-metagenes (acted as attractor-metagenes and thereby) ‘attracted’ highly co-expressing sets of genes or convergent-metagenes. These convergent-metagenes also exhibited positive prognostic impact in respective cancer types. Remarkably, we found that the cancer type-independent consensus-metagene acted as an ‘attractor’ for cancer-specific convergent-metagenes. This reaffirms that the immunological prognostic landscape of cancer tends to segregate between cancer-independent and cancer-type specific gene signatures. Moreover, this prognostic landscape was largely dominated by the classical T cell activity/infiltration/function-related biomarkers. Interestingly, each cancer type tended to associate with biomarkers representing a specific T cell activity or function rather than pan-T cell biomarkers. Thus, our analysis confirms that ICD can serve as a platform for discovery of novel prognostic metagenes. PMID:27057433

Expression Atlas: gene and protein expression across multiple studies and organisms

PubMed Central

Tang, Y Amy; Bazant, Wojciech; Burke, Melissa; Fuentes, Alfonso Muñoz-Pomer; George, Nancy; Koskinen, Satu; Mohammed, Suhaib; Geniza, Matthew; Preece, Justin; Jarnuczak, Andrew F; Huber, Wolfgang; Stegle, Oliver; Brazma, Alvis; Petryszak, Robert

2018-01-01

Abstract Expression Atlas (http://www.ebi.ac.uk/gxa) is an added value database that provides information about gene and protein expression in different species and contexts, such as tissue, developmental stage, disease or cell type. The available public and controlled access data sets from different sources are curated and re-analysed using standardized, open source pipelines and made available for queries, download and visualization. As of August 2017, Expression Atlas holds data from 3,126 studies across 33 different species, including 731 from plants. Data from large-scale RNA sequencing studies including Blueprint, PCAWG, ENCODE, GTEx and HipSci can be visualized next to each other. In Expression Atlas, users can query genes or gene-sets of interest and explore their expression across or within species, tissues, developmental stages in a constitutive or differential context, representing the effects of diseases, conditions or experimental interventions. All processed data matrices are available for direct download in tab-delimited format or as R-data. In addition to the web interface, data sets can now be searched and downloaded through the Expression Atlas R package. Novel features and visualizations include the on-the-fly analysis of gene set overlaps and the option to view gene co-expression in experiments investigating constitutive gene expression across tissues or other conditions. PMID:29165655

NetMiner-an ensemble pipeline for building genome-wide and high-quality gene co-expression network using massive-scale RNA-seq samples.

PubMed

Yu, Hua; Jiao, Bingke; Lu, Lu; Wang, Pengfei; Chen, Shuangcheng; Liang, Chengzhi; Liu, Wei

2018-01-01

Accurately reconstructing gene co-expression network is of great importance for uncovering the genetic architecture underlying complex and various phenotypes. The recent availability of high-throughput RNA-seq sequencing has made genome-wide detecting and quantifying of the novel, rare and low-abundance transcripts practical. However, its potential merits in reconstructing gene co-expression network have still not been well explored. Using massive-scale RNA-seq samples, we have designed an ensemble pipeline, called NetMiner, for building genome-scale and high-quality Gene Co-expression Network (GCN) by integrating three frequently used inference algorithms. We constructed a RNA-seq-based GCN in one species of monocot rice. The quality of network obtained by our method was verified and evaluated by the curated gene functional association data sets, which obviously outperformed each single method. In addition, the powerful capability of network for associating genes with functions and agronomic traits was shown by enrichment analysis and case studies. In particular, we demonstrated the potential value of our proposed method to predict the biological roles of unknown protein-coding genes, long non-coding RNA (lncRNA) genes and circular RNA (circRNA) genes. Our results provided a valuable and highly reliable data source to select key candidate genes for subsequent experimental validation. To facilitate identification of novel genes regulating important biological processes and phenotypes in other plants or animals, we have published the source code of NetMiner, making it freely available at https://github.com/czllab/NetMiner.

Large-Scale Compute-Intensive Analysis via a Combined In-situ and Co-scheduling Workflow Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Messer, Bronson; Sewell, Christopher; Heitmann, Katrin

2015-01-01

Large-scale simulations can produce tens of terabytes of data per analysis cycle, complicating and limiting the efficiency of workflows. Traditionally, outputs are stored on the file system and analyzed in post-processing. With the rapidly increasing size and complexity of simulations, this approach faces an uncertain future. Trending techniques consist of performing the analysis in situ, utilizing the same resources as the simulation, and/or off-loading subsets of the data to a compute-intensive analysis system. We introduce an analysis framework developed for HACC, a cosmological N-body code, that uses both in situ and co-scheduling approaches for handling Petabyte-size outputs. An initial inmore » situ step is used to reduce the amount of data to be analyzed, and to separate out the data-intensive tasks handled off-line. The analysis routines are implemented using the PISTON/VTK-m framework, allowing a single implementation of an algorithm that simultaneously targets a variety of GPU, multi-core, and many-core architectures.« less

Weighted gene co-expression network analysis reveals potential genes involved in early metamorphosis process in sea cucumber Apostichopus japonicus.

PubMed

Li, Yongxin; Kikuchi, Mani; Li, Xueyan; Gao, Qionghua; Xiong, Zijun; Ren, Yandong; Zhao, Ruoping; Mao, Bingyu; Kondo, Mariko; Irie, Naoki; Wang, Wen

2018-01-01

Sea cucumbers, one main class of Echinoderms, have a very fast and drastic metamorphosis process during their development. However, the molecular basis under this process remains largely unknown. Here we systematically examined the gene expression profiles of Japanese common sea cucumber (Apostichopus japonicus) for the first time by RNA sequencing across 16 developmental time points from fertilized egg to juvenile stage. Based on the weighted gene co-expression network analysis (WGCNA), we identified 21 modules. Among them, MEdarkmagenta was highly expressed and correlated with the early metamorphosis process from late auricularia to doliolaria larva. Furthermore, gene enrichment and differentially expressed gene analysis identified several genes in the module that may play key roles in the metamorphosis process. Our results not only provide a molecular basis for experimentally studying the development and morphological complexity of sea cucumber, but also lay a foundation for improving its emergence rate. Copyright © 2017 Elsevier Inc. All rights reserved.

Controlled crystallization and granulation of nano-scale β-Ni(OH) 2 cathode materials for high power Ni-MH batteries

NASA Astrophysics Data System (ADS)

He, Xiangming; Li, Jianjun; Cheng, Hongwei; Jiang, Changyin; Wan, Chunrong

A novel synthesis of controlled crystallization and granulation was attempted to prepare nano-scale β-Ni(OH) 2 cathode materials for high power Ni-MH batteries. Nano-scale β-Ni(OH) 2 and Co(OH) 2 with a diameter of 20 nm were prepared by controlled crystallization, mixed by ball milling, and granulated to form about 5 μm spherical grains by spray drying granulation. Both the addition of nano-scale Co(OH) 2 and granulation significantly enhanced electrochemical performance of nano-scale Ni(OH) 2. The XRD and TEM analysis shown that there were a large amount of defects among the crystal lattice of as-prepared nano-scale Ni(OH) 2, and the DTA-TG analysis shown that it had both lower decomposition temperature and higher decomposition reaction rate, indicating less thermal stability, as compared with conventional micro-scale Ni(OH) 2, and indicating that it had higher electrochemical performance. The granulated grains of nano-scale Ni(OH) 2 mixed with nano-scale Co(OH) 2 at Co/Ni = 1/20 presented the highest specific capacity reaching its theoretical value of 289 mAh g -1 at 1 C, and also exhibited much improved electrochemical performance at high discharge capacity rate up to 10 C. The granulated grains of nano-scale β-Ni(OH) 2 mixed with nano-scale Co(OH) 2 is a promising cathode active material for high power Ni-MH batteries.

Stormbow: A Cloud-Based Tool for Reads Mapping and Expression Quantification in Large-Scale RNA-Seq Studies

PubMed Central

Zhao, Shanrong; Prenger, Kurt; Smith, Lance

2013-01-01

RNA-Seq is becoming a promising replacement to microarrays in transcriptome profiling and differential gene expression study. Technical improvements have decreased sequencing costs and, as a result, the size and number of RNA-Seq datasets have increased rapidly. However, the increasing volume of data from large-scale RNA-Seq studies poses a practical challenge for data analysis in a local environment. To meet this challenge, we developed Stormbow, a cloud-based software package, to process large volumes of RNA-Seq data in parallel. The performance of Stormbow has been tested by practically applying it to analyse 178 RNA-Seq samples in the cloud. In our test, it took 6 to 8 hours to process an RNA-Seq sample with 100 million reads, and the average cost was $3.50 per sample. Utilizing Amazon Web Services as the infrastructure for Stormbow allows us to easily scale up to handle large datasets with on-demand computational resources. Stormbow is a scalable, cost effective, and open-source based tool for large-scale RNA-Seq data analysis. Stormbow can be freely downloaded and can be used out of box to process Illumina RNA-Seq datasets. PMID:25937948

Stormbow: A Cloud-Based Tool for Reads Mapping and Expression Quantification in Large-Scale RNA-Seq Studies.

PubMed

Zhao, Shanrong; Prenger, Kurt; Smith, Lance

2013-01-01

RNA-Seq is becoming a promising replacement to microarrays in transcriptome profiling and differential gene expression study. Technical improvements have decreased sequencing costs and, as a result, the size and number of RNA-Seq datasets have increased rapidly. However, the increasing volume of data from large-scale RNA-Seq studies poses a practical challenge for data analysis in a local environment. To meet this challenge, we developed Stormbow, a cloud-based software package, to process large volumes of RNA-Seq data in parallel. The performance of Stormbow has been tested by practically applying it to analyse 178 RNA-Seq samples in the cloud. In our test, it took 6 to 8 hours to process an RNA-Seq sample with 100 million reads, and the average cost was $3.50 per sample. Utilizing Amazon Web Services as the infrastructure for Stormbow allows us to easily scale up to handle large datasets with on-demand computational resources. Stormbow is a scalable, cost effective, and open-source based tool for large-scale RNA-Seq data analysis. Stormbow can be freely downloaded and can be used out of box to process Illumina RNA-Seq datasets.

oPOSSUM: identification of over-represented transcription factor binding sites in co-expressed genes

PubMed Central

Ho Sui, Shannan J.; Mortimer, James R.; Arenillas, David J.; Brumm, Jochen; Walsh, Christopher J.; Kennedy, Brian P.; Wasserman, Wyeth W.

2005-01-01

Targeted transcript profiling studies can identify sets of co-expressed genes; however, identification of the underlying functional mechanism(s) is a significant challenge. Established methods for the analysis of gene annotations, particularly those based on the Gene Ontology, can identify functional linkages between genes. Similar methods for the identification of over-represented transcription factor binding sites (TFBSs) have been successful in yeast, but extension to human genomics has largely proved ineffective. Creation of a system for the efficient identification of common regulatory mechanisms in a subset of co-expressed human genes promises to break a roadblock in functional genomics research. We have developed an integrated system that searches for evidence of co-regulation by one or more transcription factors (TFs). oPOSSUM combines a pre-computed database of conserved TFBSs in human and mouse promoters with statistical methods for identification of sites over-represented in a set of co-expressed genes. The algorithm successfully identified mediating TFs in control sets of tissue-specific genes and in sets of co-expressed genes from three transcript profiling studies. Simulation studies indicate that oPOSSUM produces few false positives using empirically defined thresholds and can tolerate up to 50% noise in a set of co-expressed genes. PMID:15933209

Atmospheric CO2 Concentrations from Aircraft for 1972-1981, CSIRO Monitoring Program

DOE Data Explorer

Beardsmore, David J. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Victoria, Australia; Pearman, Graeme I. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Victoria, Australia

2012-01-01

From 1972 through 1981, air samples were collected in glass flasks from aircraft at a variety of latitudes and altitudes over Australia, New Zealand, and Antarctica. The samples were analyzed for CO2 concentrations with nondispersive infrared gas analysis. The resulting data contain the sampling dates, type of aircraft, flight number, flask identification number, sampling time, geographic sector, distance in kilometers from the listed distance measuring equipment (DME) station, station number of the radio navigation distance measuring equipment, altitude of the aircraft above mean sea level, sample analysis date, flask pressure, tertiary standards used for the analysis, analyzer used, and CO2 concentration. These data represent the first published record of CO2 concentrations in the Southern Hemisphere expressed in the WMO 1981 CO2 Calibration Scale and provide a precise record of atmospheric CO2 concentrations in the troposphere and lower stratosphere over Australia and New Zealand.

In silico identification and comparative analysis of differentially expressed genes in human and mouse tissues

PubMed Central

Pao, Sheng-Ying; Lin, Win-Li; Hwang, Ming-Jing

2006-01-01

Background Screening for differentially expressed genes on the genomic scale and comparative analysis of the expression profiles of orthologous genes between species to study gene function and regulation are becoming increasingly feasible. Expressed sequence tags (ESTs) are an excellent source of data for such studies using bioinformatic approaches because of the rich libraries and tremendous amount of data now available in the public domain. However, any large-scale EST-based bioinformatics analysis must deal with the heterogeneous, and often ambiguous, tissue and organ terms used to describe EST libraries. Results To deal with the issue of tissue source, in this work, we carefully screened and organized more than 8 million human and mouse ESTs into 157 human and 108 mouse tissue/organ categories, to which we applied an established statistic test using different thresholds of the p value to identify genes differentially expressed in different tissues. Further analysis of the tissue distribution and level of expression of human and mouse orthologous genes showed that tissue-specific orthologs tended to have more similar expression patterns than those lacking significant tissue specificity. On the other hand, a number of orthologs were found to have significant disparity in their expression profiles, hinting at novel functions, divergent regulation, or new ortholog relationships. Conclusion Comprehensive statistics on the tissue-specific expression of human and mouse genes were obtained in this very large-scale, EST-based analysis. These statistical results have been organized into a database, freely accessible at our website , for easy searching of human and mouse tissue-specific genes and for investigating gene expression profiles in the context of comparative genomics. Comparative analysis showed that, although highly tissue-specific genes tend to exhibit similar expression profiles in human and mouse, there are significant exceptions, indicating that orthologous genes, while sharing basic genomic properties, could result in distinct phenotypes. PMID:16626500

The analysis of soil cores polluted with certain metals using the Box-Cox transformation.

PubMed

Meloun, Milan; Sánka, Milan; Nemec, Pavel; Krítková, Sona; Kupka, Karel

2005-09-01

To define the soil properties for a given area or country including the level of pollution, soil survey and inventory programs are essential tools. Soil data transformations enable the expression of the original data on a new scale, more suitable for data analysis. In the computer-aided interactive analysis of large data files of soil characteristics containing outliers, the diagnostic plots of the exploratory data analysis (EDA) often find that the sample distribution is systematically skewed or reject sample homogeneity. Under such circumstances the original data should be transformed. The Box-Cox transformation improves sample symmetry and stabilizes spread. The logarithmic plot of a profile likelihood function enables the optimum transformation parameter to be found. Here, a proposed procedure for data transformation in univariate data analysis is illustrated on a determination of cadmium content in the plough zone of agricultural soils. A typical soil pollution survey concerns the determination of the elements Be (16 544 values available), Cd (40 317 values), Co (22 176 values), Cr (40 318 values), Hg (32 344 values), Ni (34 989 values), Pb (40 344 values), V (20 373 values) and Zn (36 123 values) in large samples.

CO 2 Leakage Into Shallow Aquifers: Modeling CO 2 Gas Evolution and Accumulation at Interfaces of Heterogeneity

DOE PAGES

Porter, Mark L.; Plampin, Michael; Pawar, Rajesh; ...

2014-12-31

The physicochemical processes associated with CO 2 leakage into shallow aquifer systems are complex and span multiple spatial and time scales. Continuum-scale numerical models that faithfully represent the underlying pore-scale physics are required to predict the long-term behavior and aid in risk analysis regarding regulatory and management decisions. This study focuses on benchmarking the numerical simulator, FEHM, with intermediate-scale column experiments of CO 2 gas evolution in homogeneous and heterogeneous sand configurations. Inverse modeling was conducted to calibrate model parameters and determine model sensitivity to the observed steady-state saturation profiles. It is shown that FEHM is a powerful tool thatmore » is capable of capturing the experimentally observed out ow rates and saturation profiles. Moreover, FEHM captures the transition from single- to multi-phase flow and CO 2 gas accumulation at interfaces separating sands. We also derive a simple expression, based on Darcy's law, for the pressure at which CO 2 free phase gas is observed and show that it reliably predicts the location at which single-phase flow transitions to multi-phase flow.« less

Pan- and core- network analysis of co-expression genes in a model plant

DOE PAGES

He, Fei; Maslov, Sergei

2016-12-16

Genome-wide gene expression experiments have been performed using the model plant Arabidopsis during the last decade. Some studies involved construction of coexpression networks, a popular technique used to identify groups of co-regulated genes, to infer unknown gene functions. One approach is to construct a single coexpression network by combining multiple expression datasets generated in different labs. We advocate a complementary approach in which we construct a large collection of 134 coexpression networks based on expression datasets reported in individual publications. To this end we reanalyzed public expression data. To describe this collection of networks we introduced concepts of ‘pan-network’ andmore » ‘core-network’ representing union and intersection between a sizeable fractions of individual networks, respectively. Here, we showed that these two types of networks are different both in terms of their topology and biological function of interacting genes. For example, the modules of the pan-network are enriched in regulatory and signaling functions, while the modules of the core-network tend to include components of large macromolecular complexes such as ribosomes and photosynthetic machinery. Our analysis is aimed to help the plant research community to better explore the information contained within the existing vast collection of gene expression data in Arabidopsis.« less

Pan- and core- network analysis of co-expression genes in a model plant

DOE Office of Scientific and Technical Information (OSTI.GOV)

He, Fei; Maslov, Sergei

Genome-wide gene expression experiments have been performed using the model plant Arabidopsis during the last decade. Some studies involved construction of coexpression networks, a popular technique used to identify groups of co-regulated genes, to infer unknown gene functions. One approach is to construct a single coexpression network by combining multiple expression datasets generated in different labs. We advocate a complementary approach in which we construct a large collection of 134 coexpression networks based on expression datasets reported in individual publications. To this end we reanalyzed public expression data. To describe this collection of networks we introduced concepts of ‘pan-network’ andmore » ‘core-network’ representing union and intersection between a sizeable fractions of individual networks, respectively. Here, we showed that these two types of networks are different both in terms of their topology and biological function of interacting genes. For example, the modules of the pan-network are enriched in regulatory and signaling functions, while the modules of the core-network tend to include components of large macromolecular complexes such as ribosomes and photosynthetic machinery. Our analysis is aimed to help the plant research community to better explore the information contained within the existing vast collection of gene expression data in Arabidopsis.« less

Structural Variation Shapes the Landscape of Recombination in Mouse

PubMed Central

Morgan, Andrew P.; Gatti, Daniel M.; Najarian, Maya L.; Keane, Thomas M.; Galante, Raymond J.; Pack, Allan I.; Mott, Richard; Churchill, Gary A.; de Villena, Fernando Pardo-Manuel

2017-01-01

Meiotic recombination is an essential feature of sexual reproduction that ensures faithful segregation of chromosomes and redistributes genetic variants in populations. Multiparent populations such as the Diversity Outbred (DO) mouse stock accumulate large numbers of crossover (CO) events between founder haplotypes, and thus present a unique opportunity to study the role of genetic variation in shaping the recombination landscape. We obtained high-density genotype data from 6886 DO mice, and localized 2.2 million CO events to intervals with a median size of 28 kb. The resulting sex-averaged genetic map of the DO population is highly concordant with large-scale (order 10 Mb) features of previously reported genetic maps for mouse. To examine fine-scale (order 10 kb) patterns of recombination in the DO, we overlaid putative recombination hotspots onto our CO intervals. We found that CO intervals are enriched in hotspots compared to the genomic background. However, as many as 26% of CO intervals do not overlap any putative hotspots, suggesting that our understanding of hotspots is incomplete. We also identified coldspots encompassing 329 Mb, or 12% of observable genome, in which there is little or no recombination. In contrast to hotspots, which are a few kilobases in size, and widely scattered throughout the genome, coldspots have a median size of 2.1 Mb and are spatially clustered. Coldspots are strongly associated with copy-number variant (CNV) regions, especially multi-allelic clusters, identified from whole-genome sequencing of 228 DO mice. Genes in these regions have reduced expression, and epigenetic features of closed chromatin in male germ cells, which suggests that CNVs may repress recombination by altering chromatin structure in meiosis. Our findings demonstrate how multiparent populations, by bridging the gap between large-scale and fine-scale genetic mapping, can reveal new features of the recombination landscape. PMID:28592499

Structural Variation Shapes the Landscape of Recombination in Mouse.

PubMed

Morgan, Andrew P; Gatti, Daniel M; Najarian, Maya L; Keane, Thomas M; Galante, Raymond J; Pack, Allan I; Mott, Richard; Churchill, Gary A; de Villena, Fernando Pardo-Manuel

2017-06-01

Meiotic recombination is an essential feature of sexual reproduction that ensures faithful segregation of chromosomes and redistributes genetic variants in populations. Multiparent populations such as the Diversity Outbred (DO) mouse stock accumulate large numbers of crossover (CO) events between founder haplotypes, and thus present a unique opportunity to study the role of genetic variation in shaping the recombination landscape. We obtained high-density genotype data from [Formula: see text] DO mice, and localized 2.2 million CO events to intervals with a median size of 28 kb. The resulting sex-averaged genetic map of the DO population is highly concordant with large-scale (order 10 Mb) features of previously reported genetic maps for mouse. To examine fine-scale (order 10 kb) patterns of recombination in the DO, we overlaid putative recombination hotspots onto our CO intervals. We found that CO intervals are enriched in hotspots compared to the genomic background. However, as many as [Formula: see text] of CO intervals do not overlap any putative hotspots, suggesting that our understanding of hotspots is incomplete. We also identified coldspots encompassing 329 Mb, or [Formula: see text] of observable genome, in which there is little or no recombination. In contrast to hotspots, which are a few kilobases in size, and widely scattered throughout the genome, coldspots have a median size of 2.1 Mb and are spatially clustered. Coldspots are strongly associated with copy-number variant (CNV) regions, especially multi-allelic clusters, identified from whole-genome sequencing of 228 DO mice. Genes in these regions have reduced expression, and epigenetic features of closed chromatin in male germ cells, which suggests that CNVs may repress recombination by altering chromatin structure in meiosis. Our findings demonstrate how multiparent populations, by bridging the gap between large-scale and fine-scale genetic mapping, can reveal new features of the recombination landscape. Copyright © 2017 by the Genetics Society of America.

Large Pilot-Scale Carbon Dioxide (CO2) Capture Project Using Aminosilicone Solvent.Final Scientific/Technical Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hancu, Dan

GE Global Research has developed, over the last 8 years, a platform of cost effective CO2 capture technologies based on a non-aqueous aminosilicone solvent (GAP-1m). As demonstrated in previous funded DOE projects (DE-FE0007502 and DEFE0013755), the GAP-1m solvent has increased CO2 working capacity, lower volatility and corrosivity than the benchmark aqueous amine technology. Performance of the GAP-1m solvent was recently demonstrated in a 0.5 MWe pilot at National Carbon Capture Center, AL with real flue gas for over 500 hours of operation using a Steam Stripper Column (SSC). The pilot-scale PSTU engineering data were used to (i) update the techno-economicmore » analysis, and EH&S assessment, (ii) perform technology gap analysis, and (iii) conduct the solvent manufacturability and scale-up study.« less

Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets.

PubMed

Lam, Max; Trampush, Joey W; Yu, Jin; Knowles, Emma; Davies, Gail; Liewald, David C; Starr, John M; Djurovic, Srdjan; Melle, Ingrid; Sundet, Kjetil; Christoforou, Andrea; Reinvang, Ivar; DeRosse, Pamela; Lundervold, Astri J; Steen, Vidar M; Espeseth, Thomas; Räikkönen, Katri; Widen, Elisabeth; Palotie, Aarno; Eriksson, Johan G; Giegling, Ina; Konte, Bettina; Roussos, Panos; Giakoumaki, Stella; Burdick, Katherine E; Payton, Antony; Ollier, William; Chiba-Falek, Ornit; Attix, Deborah K; Need, Anna C; Cirulli, Elizabeth T; Voineskos, Aristotle N; Stefanis, Nikos C; Avramopoulos, Dimitrios; Hatzimanolis, Alex; Arking, Dan E; Smyrnis, Nikolaos; Bilder, Robert M; Freimer, Nelson A; Cannon, Tyrone D; London, Edythe; Poldrack, Russell A; Sabb, Fred W; Congdon, Eliza; Conley, Emily Drabant; Scult, Matthew A; Dickinson, Dwight; Straub, Richard E; Donohoe, Gary; Morris, Derek; Corvin, Aiden; Gill, Michael; Hariri, Ahmad R; Weinberger, Daniel R; Pendleton, Neil; Bitsios, Panos; Rujescu, Dan; Lahti, Jari; Le Hellard, Stephanie; Keller, Matthew C; Andreassen, Ole A; Deary, Ian J; Glahn, David C; Malhotra, Anil K; Lencz, Todd

2017-11-28

Here, we present a large (n = 107,207) genome-wide association study (GWAS) of general cognitive ability ("g"), further enhanced by combining results with a large-scale GWAS of educational attainment. We identified 70 independent genomic loci associated with general cognitive ability. Results showed significant enrichment for genes causing Mendelian disorders with an intellectual disability phenotype. Competitive pathway analysis implicated the biological processes of neurogenesis and synaptic regulation, as well as the gene targets of two pharmacologic agents: cinnarizine, a T-type calcium channel blocker, and LY97241, a potassium channel inhibitor. Transcriptome-wide and epigenome-wide analysis revealed that the implicated loci were enriched for genes expressed across all brain regions (most strongly in the cerebellum). Enrichment was exclusive to genes expressed in neurons but not oligodendrocytes or astrocytes. Finally, we report genetic correlations between cognitive ability and disparate phenotypes including psychiatric disorders, several autoimmune disorders, longevity, and maternal age at first birth. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

mRNA-Seq Analysis of the Pseudoperonospora cubensis Transcriptome During Cucumber (Cucumis sativus L.) Infection

PubMed Central

Hamilton, John P.; Vaillancourt, Brieanne; Buell, C. Robin; Day, Brad

2012-01-01

Pseudoperonospora cubensis, an oomycete, is the causal agent of cucurbit downy mildew, and is responsible for significant losses on cucurbit crops worldwide. While other oomycete plant pathogens have been extensively studied at the molecular level, Ps. cubensis and the molecular basis of its interaction with cucurbit hosts has not been well examined. Here, we present the first large-scale global gene expression analysis of Ps. cubensis infection of a susceptible Cucumis sativus cultivar, ‘Vlaspik’, and identification of genes with putative roles in infection, growth, and pathogenicity. Using high throughput whole transcriptome sequencing, we captured differential expression of 2383 Ps. cubensis genes in sporangia and at 1, 2, 3, 4, 6, and 8 days post-inoculation (dpi). Additionally, comparison of Ps. cubensis expression profiles with expression profiles from an infection time course of the oomycete pathogen Phytophthora infestans on Solanum tuberosum revealed similarities in expression patterns of 1,576–6,806 orthologous genes suggesting a substantial degree of overlap in molecular events in virulence between the biotrophic Ps. cubensis and the hemi-biotrophic P. infestans. Co-expression analyses identified distinct modules of Ps. cubensis genes that were representative of early, intermediate, and late infection stages. Collectively, these expression data have advanced our understanding of key molecular and genetic events in the virulence of Ps. cubensis and thus, provides a foundation for identifying mechanism(s) by which to engineer or effect resistance in the host. PMID:22545137

Transcriptomic Analysis of Paeonia delavayi Wild Population Flowers to Identify Differentially Expressed Genes Involved in Purple-Red and Yellow Petal Pigmentation

PubMed Central

Wang, Yan; Li, Kui; Zheng, Baoqiang; Miao, Kun

2015-01-01

Tree peony (Paeonia suffruticosa Andrews) is a very famous traditional ornamental plant in China. P. delavayi is a species endemic to Southwest China that has aroused great interest from researchers as a precious genetic resource for flower color breeding. However, the current understanding of the molecular mechanisms of flower pigmentation in this plant is limited, hindering the genetic engineering of novel flower color in tree peonies. In this study, we conducted a large-scale transcriptome analysis based on Illumina HiSeq sequencing of cDNA libraries generated from yellow and purple-red P. delavayi petals. A total of 90,202 unigenes were obtained by de novo assembly, with an average length of 721 nt. Using Blastx, 44,811 unigenes (49.68%) were found to have significant similarity to accessions in the NR, NT, and Swiss-Prot databases. We also examined COG, GO and KEGG annotations to better understand the functions of these unigenes. Further analysis of the two digital transcriptomes revealed that 6,855 unigenes were differentially expressed between yellow and purple-red flower petals, with 3,430 up-regulated and 3,425 down-regulated. According to the RNA-Seq data and qRT-PCR analysis, we proposed that four up-regulated key structural genes, including F3H, DFR, ANS and 3GT, might play an important role in purple-red petal pigmentation, while high co-expression of THC2'GT, CHI and FNS II ensures the accumulation of pigments contributing to the yellow color. We also found 50 differentially expressed transcription factors that might be involved in flavonoid biosynthesis. This study is the first to report genetic information for P. delavayi. The large number of gene sequences produced by transcriptome sequencing and the candidate genes identified using pathway mapping and expression profiles will provide a valuable resource for future association studies aimed at better understanding the molecular mechanisms underlying flower pigmentation in tree peonies. PMID:26267644

Dynamic Visualization of Co-expression in Systems Genetics Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

New, Joshua Ryan; Huang, Jian; Chesler, Elissa J

2008-01-01

Biologists hope to address grand scientific challenges by exploring the abundance of data made available through modern microarray technology and other high-throughput techniques. The impact of this data, however, is limited unless researchers can effectively assimilate such complex information and integrate it into their daily research; interactive visualization tools are called for to support the effort. Specifically, typical studies of gene co-expression require novel visualization tools that enable the dynamic formulation and fine-tuning of hypotheses to aid the process of evaluating sensitivity of key parameters. These tools should allow biologists to develop an intuitive understanding of the structure of biologicalmore » networks and discover genes which reside in critical positions in networks and pathways. By using a graph as a universal data representation of correlation in gene expression data, our novel visualization tool employs several techniques that when used in an integrated manner provide innovative analytical capabilities. Our tool for interacting with gene co-expression data integrates techniques such as: graph layout, qualitative subgraph extraction through a novel 2D user interface, quantitative subgraph extraction using graph-theoretic algorithms or by querying an optimized b-tree, dynamic level-of-detail graph abstraction, and template-based fuzzy classification using neural networks. We demonstrate our system using a real-world workflow from a large-scale, systems genetics study of mammalian gene co-expression.« less

Energy: the microfluidic frontier.

PubMed

Sinton, David

2014-09-07

Global energy is largely a fluids problem. It is also large-scale, in stark contrast to microchannels. Microfluidic energy technologies must offer either massive scalability or direct relevance to energy processes already operating at scale. We have to pick our fights. Highlighted here are the exceptional opportunities I see, including some recent successes and areas where much more attention is needed. The most promising directions are those that leverage high surface-to-volume ratios, rapid diffusive transport, capacity for high temperature and high pressure experiments, and length scales characteristic of microbes and fluids (hydrocarbons, CO2) underground. The most immediate areas of application are where information is the product; either fluid sample analysis (e.g. oil analysis); or informing operations (e.g. CO2 transport in microporous media). I'll close with aspects that differentiate energy from traditional microfluidics applications, the uniquely important role of engineering in energy, and some thoughts for the research community forming at the nexus of lab-on-a-chip and energy--a microfluidic frontier.

Modality-Spanning Deficits in Attention-Deficit/Hyperactivity Disorder in Functional Networks, Gray Matter, and White Matter

PubMed Central

Kessler, Daniel; Angstadt, Michael; Welsh, Robert C.

2014-01-01

Previous neuroimaging investigations in attention-deficit/hyperactivity disorder (ADHD) have separately identified distributed structural and functional deficits, but interconnections between these deficits have not been explored. To unite these modalities in a common model, we used joint independent component analysis, a multivariate, multimodal method that identifies cohesive components that span modalities. Based on recent network models of ADHD, we hypothesized that altered relationships between large-scale networks, in particular, default mode network (DMN) and task-positive networks (TPNs), would co-occur with structural abnormalities in cognitive regulation regions. For 756 human participants in the ADHD-200 sample, we produced gray and white matter volume maps with voxel-based morphometry, as well as whole-brain functional connectomes. Joint independent component analysis was performed, and the resulting transmodal components were tested for differential expression in ADHD versus healthy controls. Four components showed greater expression in ADHD. Consistent with our a priori hypothesis, we observed reduced DMN-TPN segregation co-occurring with structural abnormalities in dorsolateral prefrontal cortex and anterior cingulate cortex, two important cognitive control regions. We also observed altered intranetwork connectivity in DMN, dorsal attention network, and visual network, with co-occurring distributed structural deficits. There was strong evidence of spatial correspondence across modalities: For all four components, the impact of the respective component on gray matter at a region strongly predicted the impact on functional connectivity at that region. Overall, our results demonstrate that ADHD involves multiple, cohesive modality spanning deficits, each one of which exhibits strong spatial overlap in the pattern of structural and functional alterations. PMID:25505309

Balloon-borne tropospheric CO2 observations over the equatorial eastern and western Pacific

NASA Astrophysics Data System (ADS)

Inai, Yoichi; Aoki, Shuji; Honda, Hideyuki; Furutani, Hiroshi; Matsumi, Yutaka; Ouchi, Mai; Sugawara, Satoshi; Hasebe, Fumio; Uematsu, Mitsuo; Fujiwara, Masatomo

2018-07-01

Vertical profiles of carbon dioxide (CO2) mixing ratio in the equatorial eastern and western Pacific were measured by newly developed balloon-borne CO2 sondes in February 2012 (two soundings) and February-March 2015 (four soundings), respectively. The 1-10 km vertically averaged CO2 mixing ratios lie between the background surface values in the Northern Hemisphere (NH) and those in the Southern Hemisphere (SH) monitored at ground-based sites during these periods. A backward trajectory analysis, taking account of convective mixing processes using geostationary satellite cloud-image data, is applied to the measured CO2 profiles to estimate the origin of the observed air masses. Air masses originating in the SH show low CO2 mixing ratios that are similar to the background values in the SH. This relationship is confirmed by a positive correlation (∼0.6) between the CO2 mixing ratio and the latitude of air mass origin which is found from trajectory calculations. This result suggests that the CO2 distribution in the troposphere over the equatorial Pacific is controlled by monthly time-scale, large-scale CO2 distribution and weekly time-scale atmospheric transport processes. Furthermore, this study shows that the combination of CO2 sonde measurements and trajectory analysis, taking account of convective mixing, is a useful tool in investigating CO2 transport processes.

Identification of host transcriptional networks showing concentration-dependent regulation by HPV16 E6 and E7 proteins in basal cervical squamous epithelial cells

PubMed Central

Smith, Stephen P.; Scarpini, Cinzia G.; Groves, Ian J.; Odle, Richard I.; Coleman, Nicholas

2016-01-01

Development of cervical squamous cell carcinoma requires increased expression of the major high-risk human-papillomavirus (HPV) oncogenes E6 and E7 in basal cervical epithelial cells. We used a systems biology approach to identify host transcriptional networks in such cells and study the concentration-dependent changes produced by HPV16-E6 and -E7 oncoproteins. We investigated sample sets derived from the W12 model of cervical neoplastic progression, for which high quality phenotype/genotype data were available. We defined a gene co-expression matrix containing a small number of highly-connected hub nodes that controlled large numbers of downstream genes (regulons), indicating the scale-free nature of host gene co-expression in W12. We identified a small number of ‘master regulators’ for which downstream effector genes were significantly associated with protein levels of HPV16 E6 (n = 7) or HPV16 E7 (n = 5). We validated our data by depleting E6/E7 in relevant cells and by functional analysis of selected genes in vitro. We conclude that the network of transcriptional interactions in HPV16-infected basal-type cervical epithelium is regulated in a concentration-dependent manner by E6/E7, via a limited number of central master-regulators. These effects are likely to be significant in cervical carcinogenesis, where there is competitive selection of cells with elevated expression of virus oncoproteins. PMID:27457222

Clustering approaches to identifying gene expression patterns from DNA microarray data.

PubMed

Do, Jin Hwan; Choi, Dong-Kug

2008-04-30

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

Transformation and model choice for RNA-seq co-expression analysis.

PubMed

Rau, Andrea; Maugis-Rabusseau, Cathy

2018-05-01

Although a large number of clustering algorithms have been proposed to identify groups of co-expressed genes from microarray data, the question of if and how such methods may be applied to RNA sequencing (RNA-seq) data remains unaddressed. In this work, we investigate the use of data transformations in conjunction with Gaussian mixture models for RNA-seq co-expression analyses, as well as a penalized model selection criterion to select both an appropriate transformation and number of clusters present in the data. This approach has the advantage of accounting for per-cluster correlation structures among samples, which can be strong in RNA-seq data. In addition, it provides a rigorous statistical framework for parameter estimation, an objective assessment of data transformations and number of clusters and the possibility of performing diagnostic checks on the quality and homogeneity of the identified clusters. We analyze four varied RNA-seq data sets to illustrate the use of transformations and model selection in conjunction with Gaussian mixture models. Finally, we propose a Bioconductor package coseq (co-expression of RNA-seq data) to facilitate implementation and visualization of the recommended RNA-seq co-expression analyses.

A high resolution atlas of gene expression in the domestic sheep (Ovis aries)

PubMed Central

Farquhar, Iseabail L.; Young, Rachel; Lefevre, Lucas; Pridans, Clare; Tsang, Hiu G.; Afrasiabi, Cyrus; Watson, Mick; Whitelaw, C. Bruce; Freeman, Tom C.; Archibald, Alan L.; Hume, David A.

2017-01-01

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of ‘guilt by association’ was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages. PMID:28915238

A high resolution atlas of gene expression in the domestic sheep (Ovis aries).

PubMed

Clark, Emily L; Bush, Stephen J; McCulloch, Mary E B; Farquhar, Iseabail L; Young, Rachel; Lefevre, Lucas; Pridans, Clare; Tsang, Hiu G; Wu, Chunlei; Afrasiabi, Cyrus; Watson, Mick; Whitelaw, C Bruce; Freeman, Tom C; Summers, Kim M; Archibald, Alan L; Hume, David A

2017-09-01

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of 'guilt by association' was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages.

Chaperone-Assisted Soluble Expression of a Humanized Anti-EGFR ScFv Antibody in E. Coli

PubMed Central

Veisi, Kamal; Farajnia, Safar; Zarghami, Nosratollah; Khoram Khorshid, Hamid Reza; Samadi, Nasser; Ahdi Khosroshahi, Shiva; Zarei Jaliani, Hossein

2015-01-01

Purpose: Formation of inclusion bodies is a considerable obstacle threatening the advantages of E. coli expression system to serve as the most common and easiest system in recombinant protein production. To solve this problem, several strategies have been proposed among which application of molecular chaperones is of remarkable consideration. The aim of this study was to evaluate the effects of molecular chaperones on soluble expression of aggregation-prone humanized single chain antibody. Methods: To increase the solubility of a humanized single chain antibody (hscFv), different chaperone plasmids including PG-tf2 (GroES- GroEL- tig), ptf16 (tig) and pGro7 (GroES- GroEL) were co-expressed in BL21 cells containing pET-22b- hscFv construct. The solubility of recombinant hscFv was analyzed by SDS-PAGE. After purification of soluble hscFv by Ni-NTA column, the biological activity and cytotoxicity of the recombinant protein were tested by ELISA and MTT assay, respectively. Results: SDS-PAGE analysis of the hscFv revealed that chaperone utility remarkably increased (up to 50%) the solubility of the protein. ELISA test and MTT assay analyses also confirmed the biological activity of the gained hscFv in reaction with A431 cells (OD value: 2.6) and inhibition of their proliferation, respectively. Conclusion: The results of this study revealed that co-expression of chaperones with hscFv leads to remarkable increase in the solubility of the recombinant hscFv, which could be of great consideration for large scale production of recombinant single chain antibodies. PMID:26793607

Dissolved carbon dioxide determines the productivity of a recombinant hemagglutinin component of an influenza vaccine produced by insect cells.

PubMed

Meghrous, Jamal; Khramtsov, Nikolai; Buckland, Barry C; Cox, Manon M J; Palomares, Laura A; Srivastava, Indresh K

2015-11-01

Dissolved carbon dioxide (dCO2 ) accumulation during cell culture has been recognized as an important parameter that needs to be controlled for successful scale-up of animal cell culture because above a certain concentration there are adverse effects on cell growth performance and protein production. We investigated the effect of accumulation of dCO2 in bioreactor cultures of expresSF+(®) insect cells infected with recombinant baculoviruses expressing recombinant influenza virus hemagglutinins (rHA). Different strategies for bioreactor cultures were used to obtain various ranges of concentrations of dCO2 (<50, 50-100, 100-200, and >200 mmHg) and to determine their effects on recombinant protein production and cell metabolic activity. We show that the accumulation of dCO2 at levels > 100 mmHg resulted in reduced metabolic activity, slowed cell growth, prolonged culture viability after infection, and decreased infection kinetics. The reduced rHA yields were not caused by the decrease in the extracellular pH that resulted from dCO2 accumulation, but were most likely due to the effect of dCO2 accumulation in cells. The results obtained here at the 2 L scale have been used for the design of large-scale processes to manufacture the rHA based recombinant vaccine Flublok™ at the 2500 L scale Biotechnol. Bioeng. 2015;112: 2267-2275. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Correlated motion of protein subdomains and large-scale conformational flexibility of RecA protein filament

NASA Astrophysics Data System (ADS)

Yu, Garmay; A, Shvetsov; D, Karelov; D, Lebedev; A, Radulescu; M, Petukhov; V, Isaev-Ivanov

2012-02-01

Based on X-ray crystallographic data available at Protein Data Bank, we have built molecular dynamics (MD) models of homologous recombinases RecA from E. coli and D. radiodurans. Functional form of RecA enzyme, which is known to be a long helical filament, was approximated by a trimer, simulated in periodic water box. The MD trajectories were analyzed in terms of large-scale conformational motions that could be detectable by neutron and X-ray scattering techniques. The analysis revealed that large-scale RecA monomer dynamics can be described in terms of relative motions of 7 subdomains. Motion of C-terminal domain was the major contributor to the overall dynamics of protein. Principal component analysis (PCA) of the MD trajectories in the atom coordinate space showed that rotation of C-domain is correlated with the conformational changes in the central domain and N-terminal domain, that forms the monomer-monomer interface. Thus, even though C-terminal domain is relatively far from the interface, its orientation is correlated with large-scale filament conformation. PCA of the trajectories in the main chain dihedral angle coordinate space implicates a co-existence of a several different large-scale conformations of the modeled trimer. In order to clarify the relationship of independent domain orientation with large-scale filament conformation, we have performed analysis of independent domain motion and its implications on the filament geometry.

Gene Expression Analysis: Teaching Students to Do 30,000 Experiments at Once with Microarray

ERIC Educational Resources Information Center

Carvalho, Felicia I.; Johns, Christopher; Gillespie, Marc E.

2012-01-01

Genome scale experiments routinely produce large data sets that require computational analysis, yet there are few student-based labs that illustrate the design and execution of these experiments. In order for students to understand and participate in the genomic world, teaching labs must be available where students generate and analyze large data…

A novel method to identify pathways associated with renal cell carcinoma based on a gene co-expression network

PubMed Central

RUAN, XIYUN; LI, HONGYUN; LIU, BO; CHEN, JIE; ZHANG, SHIBAO; SUN, ZEQIANG; LIU, SHUANGQING; SUN, FAHAI; LIU, QINGYONG

2015-01-01

The aim of the present study was to develop a novel method for identifying pathways associated with renal cell carcinoma (RCC) based on a gene co-expression network. A framework was established where a co-expression network was derived from the database as well as various co-expression approaches. First, the backbone of the network based on differentially expressed (DE) genes between RCC patients and normal controls was constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The differentially co-expressed links were detected by Pearson’s correlation, the empirical Bayesian (EB) approach and Weighted Gene Co-expression Network Analysis (WGCNA). The co-expressed gene pairs were merged by a rank-based algorithm. We obtained 842; 371; 2,883 and 1,595 co-expressed gene pairs from the co-expression networks of the STRING database, Pearson’s correlation EB method and WGCNA, respectively. Two hundred and eighty-one differentially co-expressed (DC) gene pairs were obtained from the merged network using this novel method. Pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the network enrichment analysis (NEA) method were performed to verify feasibility of the merged method. Results of the KEGG and NEA pathway analyses showed that the network was associated with RCC. The suggested method was computationally efficient to identify pathways associated with RCC and has been identified as a useful complement to traditional co-expression analysis. PMID:26058425

An Iterative Time Windowed Signature Algorithm for Time Dependent Transcription Module Discovery

PubMed Central

Meng, Jia; Gao, Shou-Jiang; Huang, Yufei

2010-01-01

An algorithm for the discovery of time varying modules using genome-wide expression data is present here. When applied to large-scale time serious data, our method is designed to discover not only the transcription modules but also their timing information, which is rarely annotated by the existing approaches. Rather than assuming commonly defined time constant transcription modules, a module is depicted as a set of genes that are co-regulated during a specific period of time, i.e., a time dependent transcription module (TDTM). A rigorous mathematical definition of TDTM is provided, which is serve as an objective function for retrieving modules. Based on the definition, an effective signature algorithm is proposed that iteratively searches the transcription modules from the time series data. The proposed method was tested on the simulated systems and applied to the human time series microarray data during Kaposi's sarcoma-associated herpesvirus (KSHV) infection. The result has been verified by Expression Analysis Systematic Explorer. PMID:21552463

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seljak, Uroš, E-mail: useljak@berkeley.edu

On large scales a nonlinear transformation of matter density field can be viewed as a biased tracer of the density field itself. A nonlinear transformation also modifies the redshift space distortions in the same limit, giving rise to a velocity bias. In models with primordial nongaussianity a nonlinear transformation generates a scale dependent bias on large scales. We derive analytic expressions for the large scale bias, the velocity bias and the redshift space distortion (RSD) parameter β, as well as the scale dependent bias from primordial nongaussianity for a general nonlinear transformation. These biases can be expressed entirely in termsmore » of the one point distribution function (PDF) of the final field and the parameters of the transformation. The analysis shows that one can view the large scale bias different from unity and primordial nongaussianity bias as a consequence of converting higher order correlations in density into 2-point correlations of its nonlinear transform. Our analysis allows one to devise nonlinear transformations with nearly arbitrary bias properties, which can be used to increase the signal in the large scale clustering limit. We apply the results to the ionizing equilibrium model of Lyman-α forest, in which Lyman-α flux F is related to the density perturbation δ via a nonlinear transformation. Velocity bias can be expressed as an average over the Lyman-α flux PDF. At z = 2.4 we predict the velocity bias of -0.1, compared to the observed value of −0.13±0.03. Bias and primordial nongaussianity bias depend on the parameters of the transformation. Measurements of bias can thus be used to constrain these parameters, and for reasonable values of the ionizing background intensity we can match the predictions to observations. Matching to the observed values we predict the ratio of primordial nongaussianity bias to bias to have the opposite sign and lower magnitude than the corresponding values for the highly biased galaxies, but this depends on the model parameters and can also vanish or change the sign.« less

CO2 deserts: implications of existing CO2 supply limitations for carbon management.

PubMed

Middleton, Richard S; Clarens, Andres F; Liu, Xiaowei; Bielicki, Jeffrey M; Levine, Jonathan S

2014-10-07

Efforts to mitigate the impacts of climate change will require deep reductions in anthropogenic CO2 emissions on the scale of gigatonnes per year. CO2 capture and utilization and/or storage technologies are a class of approaches that can substantially reduce CO2 emissions. Even though examples of this approach, such as CO2-enhanced oil recovery, are already being practiced on a scale >0.05 Gt/year, little attention has been focused on the supply of CO2 for these projects. Here, facility-scale data newly collected by the U.S. Environmental Protection Agency was processed to produce the first comprehensive map of CO2 sources from industrial sectors currently supplying CO2 in the United States. Collectively these sources produce 0.16 Gt/year, but the data reveal the presence of large areas without access to CO2 at an industrially relevant scale (>25 kt/year). Even though some facilities with the capability to capture CO2 are not doing so and in some regions pipeline networks are being built to link CO2 sources and sinks, much of the country exists in "CO2 deserts". A life cycle analysis of the sources reveals that the predominant source of CO2, dedicated wells, has the largest carbon footprint further confounding prospects for rational carbon management strategies.

Species-Specific Responses of Juvenile Rockfish to Elevated pCO2: From Behavior to Genomics

PubMed Central

Hamilton, Scott L.; Logan, Cheryl A.; Fennie, Hamilton W.; Sogard, Susan M.; Barry, James P.; Makukhov, April D.; Tobosa, Lauren R.; Boyer, Kirsten; Lovera, Christopher F.; Bernardi, Giacomo

2017-01-01

In the California Current ecosystem, global climate change is predicted to trigger large-scale changes in ocean chemistry within this century. Ocean acidification—which occurs when increased levels of atmospheric CO2 dissolve into the ocean—is one of the biggest potential threats to marine life. In a coastal upwelling system, we compared the effects of chronic exposure to low pH (elevated pCO2) at four treatment levels (i.e., pCO2 = ambient [500], moderate [750], high [1900], and extreme [2800 μatm]) on behavior, physiology, and patterns of gene expression in white muscle tissue of juvenile rockfish (genus Sebastes), integrating responses from the transcriptome to the whole organism level. Experiments were conducted simultaneously on two closely related species that both inhabit kelp forests, yet differ in early life history traits, to compare high-CO2 tolerance among species. Our findings indicate that these congeners express different sensitivities to elevated CO2 levels. Copper rockfish (S. caurinus) exhibited changes in behavioral lateralization, reduced critical swimming speed, depressed aerobic scope, changes in metabolic enzyme activity, and increases in the expression of transcription factors and regulatory genes at high pCO2 exposure. Blue rockfish (S. mystinus), in contrast, showed no significant changes in behavior, swimming physiology, or aerobic capacity, but did exhibit significant changes in the expression of muscle structural genes as a function of pCO2, indicating acclimatization potential. The capacity of long-lived, late to mature, commercially important fish to acclimatize and adapt to changing ocean chemistry over the next 50–100 years is likely dependent on species-specific physiological tolerances. PMID:28056071

In Situ Gene Expression Responsible for Sulfide Oxidation and CO2 Fixation of an Uncultured Large Sausage-Shaped Aquificae Bacterium in a Sulfidic Hot Spring

PubMed Central

Tamazawa, Satoshi; Yamamoto, Kyosuke; Takasaki, Kazuto; Mitani, Yasuo; Hanada, Satoshi; Kamagata, Yoichi; Tamaki, Hideyuki

2016-01-01

We investigated the in situ gene expression profile of sulfur-turf microbial mats dominated by an uncultured large sausage-shaped Aquificae bacterium, a key metabolic player in sulfur-turfs in sulfidic hot springs. A reverse transcription-PCR analysis revealed that the genes responsible for sulfide, sulfite, and thiosulfate oxidation and carbon fixation via the reductive TCA cycle were continuously expressed in sulfur-turf mats taken at different sampling points, seasons, and years. These results suggest that the uncultured large sausage-shaped bacterium has the ability to grow chemolithoautotrophically and plays key roles as a primary producer in the sulfidic hot spring ecosystem in situ. PMID:27297893

In Situ Gene Expression Responsible for Sulfide Oxidation and CO2 Fixation of an Uncultured Large Sausage-Shaped Aquificae Bacterium in a Sulfidic Hot Spring.

PubMed

Tamazawa, Satoshi; Yamamoto, Kyosuke; Takasaki, Kazuto; Mitani, Yasuo; Hanada, Satoshi; Kamagata, Yoichi; Tamaki, Hideyuki

2016-06-25

We investigated the in situ gene expression profile of sulfur-turf microbial mats dominated by an uncultured large sausage-shaped Aquificae bacterium, a key metabolic player in sulfur-turfs in sulfidic hot springs. A reverse transcription-PCR analysis revealed that the genes responsible for sulfide, sulfite, and thiosulfate oxidation and carbon fixation via the reductive TCA cycle were continuously expressed in sulfur-turf mats taken at different sampling points, seasons, and years. These results suggest that the uncultured large sausage-shaped bacterium has the ability to grow chemolithoautotrophically and plays key roles as a primary producer in the sulfidic hot spring ecosystem in situ.

Proteomic profile of the Bradysia odoriphaga in response to the microbial secondary metabolite benzothiazole.

PubMed

Zhao, Yunhe; Cui, Kaidi; Xu, Chunmei; Wang, Qiuhong; Wang, Yao; Zhang, Zhengqun; Liu, Feng; Mu, Wei

2016-11-24

Benzothiazole, a microbial secondary metabolite, has been demonstrated to possess fumigant activity against Sclerotinia sclerotiorum, Ditylenchus destructor and Bradysia odoriphaga. However, to facilitate the development of novel microbial pesticides, the mode of action of benzothiazole needs to be elucidated. Here, we employed iTRAQ-based quantitative proteomics analysis to investigate the effects of benzothiazole on the proteomic expression of B. odoriphaga. In response to benzothiazole, 92 of 863 identified proteins in B. odoriphaga exhibited altered levels of expression, among which 14 proteins were related to the action mechanism of benzothiazole, 11 proteins were involved in stress responses, and 67 proteins were associated with the adaptation of B. odoriphaga to benzothiazole. Further bioinformatics analysis indicated that the reduction in energy metabolism, inhibition of the detoxification process and interference with DNA and RNA synthesis were potentially associated with the mode of action of benzothiazole. The myosin heavy chain, succinyl-CoA synthetase and Ca + -transporting ATPase proteins may be related to the stress response. Increased expression of proteins involved in carbohydrate metabolism, energy production and conversion pathways was responsible for the adaptive response of B. odoriphaga. The results of this study provide novel insight into the molecular mechanisms of benzothiazole at a large-scale translation level and will facilitate the elucidation of the mechanism of action of benzothiazole.

Overview of Opportunities for Co-Location of Solar Energy Technologies and Vegetation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Macknick, Jordan; Beatty, Brenda; Hill, Graham

2013-12-01

Large-scale solar facilities have the potential to contribute significantly to national electricity production. Many solar installations are large-scale or utility-scale, with a capacity over 1 MW and connected directly to the electric grid. Large-scale solar facilities offer an opportunity to achieve economies of scale in solar deployment, yet there have been concerns about the amount of land required for solar projects and the impact of solar projects on local habitat. During the site preparation phase for utility-scale solar facilities, developers often grade land and remove all vegetation to minimize installation and operational costs, prevent plants from shading panels, and minimizemore » potential fire or wildlife risks. However, the common site preparation practice of removing vegetation can be avoided in certain circumstances, and there have been successful examples where solar facilities have been co-located with agricultural operations or have native vegetation growing beneath the panels. In this study we outline some of the impacts that large-scale solar facilities can have on the local environment, provide examples of installations where impacts have been minimized through co-location with vegetation, characterize the types of co-location, and give an overview of the potential benefits from co-location of solar energy projects and vegetation. The varieties of co-location can be replicated or modified for site-specific use at other solar energy installations around the world. We conclude with opportunities to improve upon our understanding of ways to reduce the environmental impacts of large-scale solar installations.« less

A large-scale analysis of sex differences in facial expressions

PubMed Central

Kodra, Evan; el Kaliouby, Rana; LaFrance, Marianne

2017-01-01

There exists a stereotype that women are more expressive than men; however, research has almost exclusively focused on a single facial behavior, smiling. A large-scale study examines whether women are consistently more expressive than men or whether the effects are dependent on the emotion expressed. Studies of gender differences in expressivity have been somewhat restricted to data collected in lab settings or which required labor-intensive manual coding. In the present study, we analyze gender differences in facial behaviors as over 2,000 viewers watch a set of video advertisements in their home environments. The facial responses were recorded using participants’ own webcams. Using a new automated facial coding technology we coded facial activity. We find that women are not universally more expressive across all facial actions. Nor are they more expressive in all positive valence actions and less expressive in all negative valence actions. It appears that generally women express actions more frequently than men, and in particular express more positive valence actions. However, expressiveness is not greater in women for all negative valence actions and is dependent on the discrete emotional state. PMID:28422963

Transitions from mono- to co- to tri-culture uniquely affect gene expression in breast cancer, stromal, and immune compartments.

PubMed

Regier, Mary C; Maccoux, Lindsey J; Weinberger, Emma M; Regehr, Keil J; Berry, Scott M; Beebe, David J; Alarid, Elaine T

2016-08-01

Heterotypic interactions in cancer microenvironments play important roles in disease initiation, progression, and spread. Co-culture is the predominant approach used in dissecting paracrine interactions between tumor and stromal cells, but functional results from simple co-cultures frequently fail to correlate to in vivo conditions. Though complex heterotypic in vitro models have improved functional relevance, there is little systematic knowledge of how multi-culture parameters influence this recapitulation. We therefore have employed a more iterative approach to investigate the influence of increasing model complexity; increased heterotypic complexity specifically. Here we describe how the compartmentalized and microscale elements of our multi-culture device allowed us to obtain gene expression data from one cell type at a time in a heterotypic culture where cells communicated through paracrine interactions. With our device we generated a large dataset comprised of cell type specific gene-expression patterns for cultures of increasing complexity (three cell types in mono-, co-, or tri-culture) not readily accessible in other systems. Principal component analysis indicated that gene expression was changed in co-culture but was often more strongly altered in tri-culture as compared to mono-culture. Our analysis revealed that cell type identity and the complexity around it (mono-, co-, or tri-culture) influence gene regulation. We also observed evidence of complementary regulation between cell types in the same heterotypic culture. Here we demonstrate the utility of our platform in providing insight into how tumor and stromal cells respond to microenvironments of varying complexities highlighting the expanding importance of heterotypic cultures that go beyond conventional co-culture.

Framing Psychology as a Discipline (1950-1999): A Large-Scale Term Co-Occurrence Analysis of Scientific Literature in Psychology.

PubMed

Flis, Ivan; van Eck, Nees Jan

2017-07-20

This study investigated the structure of psychological literature as represented by a corpus of 676,393 articles in the period from 1950 to 1999. The corpus was extracted from 1,269 journals indexed by PsycINFO. The data in our analysis consisted of the relevant terms mined from the titles and abstracts of all of the articles in the corpus. Based on the co-occurrences of these terms, we developed a series of chronological visualizations using a bibliometric software tool called VOSviewer. These visualizations produced a stable structure through the 5 decades under analysis, and this structure was analyzed as a data-mined proxy for the disciplinary formation of scientific psychology in the second part of the 20th century. Considering the stable structure uncovered by our term co-occurrence analysis and its visualization, we discuss it in the context of Lee Cronbach's "Two Disciplines of Scientific Psychology" (1957) and conventional history of 20th-century psychology's disciplinary formation and history of methods. Our aim was to provide a comprehensive digital humanities perspective on the large-scale structural development of research in English-language psychology from 1950 to 1999. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Pair-barcode high-throughput sequencing for large-scale multiplexed sample analysis

PubMed Central

2012-01-01

Background The multiplexing becomes the major limitation of the next-generation sequencing (NGS) in application to low complexity samples. Physical space segregation allows limited multiplexing, while the existing barcode approach only permits simultaneously analysis of up to several dozen samples. Results Here we introduce pair-barcode sequencing (PBS), an economic and flexible barcoding technique that permits parallel analysis of large-scale multiplexed samples. In two pilot runs using SOLiD sequencer (Applied Biosystems Inc.), 32 independent pair-barcoded miRNA libraries were simultaneously discovered by the combination of 4 unique forward barcodes and 8 unique reverse barcodes. Over 174,000,000 reads were generated and about 64% of them are assigned to both of the barcodes. After mapping all reads to pre-miRNAs in miRBase, different miRNA expression patterns are captured from the two clinical groups. The strong correlation using different barcode pairs and the high consistency of miRNA expression in two independent runs demonstrates that PBS approach is valid. Conclusions By employing PBS approach in NGS, large-scale multiplexed pooled samples could be practically analyzed in parallel so that high-throughput sequencing economically meets the requirements of samples which are low sequencing throughput demand. PMID:22276739

Pair-barcode high-throughput sequencing for large-scale multiplexed sample analysis.

PubMed

Tu, Jing; Ge, Qinyu; Wang, Shengqin; Wang, Lei; Sun, Beili; Yang, Qi; Bai, Yunfei; Lu, Zuhong

2012-01-25

The multiplexing becomes the major limitation of the next-generation sequencing (NGS) in application to low complexity samples. Physical space segregation allows limited multiplexing, while the existing barcode approach only permits simultaneously analysis of up to several dozen samples. Here we introduce pair-barcode sequencing (PBS), an economic and flexible barcoding technique that permits parallel analysis of large-scale multiplexed samples. In two pilot runs using SOLiD sequencer (Applied Biosystems Inc.), 32 independent pair-barcoded miRNA libraries were simultaneously discovered by the combination of 4 unique forward barcodes and 8 unique reverse barcodes. Over 174,000,000 reads were generated and about 64% of them are assigned to both of the barcodes. After mapping all reads to pre-miRNAs in miRBase, different miRNA expression patterns are captured from the two clinical groups. The strong correlation using different barcode pairs and the high consistency of miRNA expression in two independent runs demonstrates that PBS approach is valid. By employing PBS approach in NGS, large-scale multiplexed pooled samples could be practically analyzed in parallel so that high-throughput sequencing economically meets the requirements of samples which are low sequencing throughput demand.

Pore-scale supercritical CO2 dissolution and mass transfer under imbibition conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, Chun; Zhou, Quanlin; Kneafsey, Timothy J.

2016-06-01

In modeling of geological carbon storage, dissolution of supercritical CO2 (scCO2) is often assumed to be instantaneous with equilibrium phase partitioning. In contrast, recent core-scale imbibition experiments have shown a prolonged depletion of residual scCO2 by dissolution, implying a non-equilibrium mechanism. In this study, eight pore-scale scCO2 dissolution experiments in a 2D heterogeneous, sandstone-analogue micromodel were conducted at supercritical conditions (9 MPa and 40 °C). The micromodel was first saturated with deionized (DI) water and drained by injecting scCO2 to establish a stable scCO2 saturation. DI water was then injected at constant flow rates after scCO2 drainage was completed. Highmore » resolution time-lapse images of scCO2 and water distributions were obtained during imbibition and dissolution, aided by a scCO2-soluble fluorescent dye introduced with scCO2 during drainage. These images were used to estimate scCO2 saturations and scCO2 depletion rates. Experimental results show that (1) a time-independent, varying number of water-flow channels are created during imbibition and later dominant dissolution by the random nature of water flow at the micromodel inlet, and (2) a time-dependent number of water-flow channels are created by coupled imbibition and dissolution following completion of dominant imbibition. The number of water-flow paths, constant or transient in nature, greatly affects the overall depletion rate of scCO2 by dissolution. The average mass fraction of dissolved CO2 (dsCO2) in water effluent varies from 0.38% to 2.72% of CO2 solubility, indicating non-equilibrium scCO2 dissolution in the millimeter-scale pore network. In general, the transient depletion rate decreases as trapped, discontinuous scCO2 bubbles and clusters within water-flow paths dissolve, then remains low with dissolution of large bypassed scCO2 clusters at their interfaces with longitudinal water flow, and finally increases with coupled transverse water flow and enhanced dissolution of large scCO2 clusters. The three stages of scCO2 depletion, common to experiments with time-independent water-flow paths, are revealed by zoom-in image analysis of individual scCO2 bubbles and clusters. The measured relative permeability of water, affected by scCO2 dissolution and bi-modal permeability, shows a non-monotonic dependence on saturation. The results for experiments with different injection rates imply that the non-equilibrium nature of scCO2 dissolution becomes less important when water flow is relatively low and the time scale for dissolution is large, and more pronounced when heterogeneity is strong.« less

Rhizospheric fungi and their link with the nitrogen-fixing Frankia harbored in host plant Hippophae rhamnoides L.

PubMed

Zhou, Xue; Tian, Lei; Zhang, Jianfeng; Ma, Lina; Li, Xiujun; Tian, Chunjie

2017-12-01

Sea buckthorn (Hippophae rhamnoides L.) is a pioneer plant used for land reclamation and an appropriate material for studying the interactions of symbiotic microorganisms because of its nitrogen-fixing root nodules and mycorrhiza. We used high-throughput sequencing to reveal the diversities and community structures of rhizospheric fungi and their link with nitrogen-fixing Frankia harbored in sea buckthorn collected along an altitude gradient from the Qinghai Tibet Plateau to interior areas. We found that the fungal diversities and compositions varied between different sites. Ascomycota, Basidiomycota, and Zygomycota were the dominant phyla. The distribution of sea buckthorn rhizospheric fungi was driven by both environmental factors and the geographic distance. Among all examined soil characteristics, altitude, AP, and pH were found to have significant (p < 0.05) effect on the rhizospheric fungal community. The rhizospheric fungal communities became more distinct as the distance increased. Moreover, co-inertia analysis identified significant co-structures between Frankia and AMF communities in the rhizosphere of sea buckthorn. We conclude that at the large scale, there are certain linkages between nitrogen-fixing bacteria and the AMF expressed in the distributional pattern. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Large-scale bioinformatic analysis of the regulation of the disease resistance NBS gene family by microRNAs in Poaceae.

PubMed

Habachi-Houimli, Yosra; Khalfallah, Yosra; Makni, Hanem; Makni, Mohamed; Bouktila, Dhia

2016-01-01

In the present study, we have screened 71, 713, 525, 119 and 241 mature miRNA variants from Hordeum vulgare, Oryza sativa, Brachypodium distachyon, Triticum aestivum, and Sorghum bicolor, respectively, and classified them with respect to their conservation status and expression levels. These Poaceae non-redundant miRNA species (1,669) were distributed over a total of 625 MIR families, among which only 54 were conserved across two or more plant species, confirming the relatively recent evolutionary differentiation of miRNAs in grasses. On the other hand, we have used 257 H. vulgare, 286T. aestivum, 119 B. distachyon, 269 O. sativa, and 139 S. bicolor NBS domains, which were either mined directly from the annotated proteomes, or predicted from whole genome sequence assemblies. The hybridization potential between miRNAs and their putative NBS genes targets was analyzed, revealing that at least 454 NBS genes from all five Poaceae were potentially regulated by 265 distinct miRNA species, most of them expressed in leaves and predominantly co-expressed in additional tissues. Based on gene ontology, we could assign these probable miRNA target genes to 16 functional groups, among which three conferring resistance to bacteria (Rpm1, Xa1 and Rps2), and 13 groups of resistance to fungi (Rpp8,13, Rp3, Tsn1, Lr10, Rps1-k-1, Pm3, Rpg5, and MLA1,6,10,12,13). The results of the present analysis provide a large-scale platform for a better understanding of biological control strategies of disease resistance genes in Poaceae, and will serve as an important starting point for enhancing crop disease resistance improvement by means of transgenic lines with artificial miRNAs. Copyright © 2016 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Analysis of blood-based gene expression in idiopathic Parkinson disease.

PubMed

Shamir, Ron; Klein, Christine; Amar, David; Vollstedt, Eva-Juliane; Bonin, Michael; Usenovic, Marija; Wong, Yvette C; Maver, Ales; Poths, Sven; Safer, Hershel; Corvol, Jean-Christophe; Lesage, Suzanne; Lavi, Ofer; Deuschl, Günther; Kuhlenbaeumer, Gregor; Pawlack, Heike; Ulitsky, Igor; Kasten, Meike; Riess, Olaf; Brice, Alexis; Peterlin, Borut; Krainc, Dimitri

2017-10-17

To examine whether gene expression analysis of a large-scale Parkinson disease (PD) patient cohort produces a robust blood-based PD gene signature compared to previous studies that have used relatively small cohorts (≤220 samples). Whole-blood gene expression profiles were collected from a total of 523 individuals. After preprocessing, the data contained 486 gene profiles (n = 205 PD, n = 233 controls, n = 48 other neurodegenerative diseases) that were partitioned into training, validation, and independent test cohorts to identify and validate a gene signature. Batch-effect reduction and cross-validation were performed to ensure signature reliability. Finally, functional and pathway enrichment analyses were applied to the signature to identify PD-associated gene networks. A gene signature of 100 probes that mapped to 87 genes, corresponding to 64 upregulated and 23 downregulated genes differentiating between patients with idiopathic PD and controls, was identified with the training cohort and successfully replicated in both an independent validation cohort (area under the curve [AUC] = 0.79, p = 7.13E-6) and a subsequent independent test cohort (AUC = 0.74, p = 4.2E-4). Network analysis of the signature revealed gene enrichment in pathways, including metabolism, oxidation, and ubiquitination/proteasomal activity, and misregulation of mitochondria-localized genes, including downregulation of COX4I1 , ATP5A1 , and VDAC3 . We present a large-scale study of PD gene expression profiling. This work identifies a reliable blood-based PD signature and highlights the importance of large-scale patient cohorts in developing potential PD biomarkers. © 2017 American Academy of Neurology.

Evaluating the effects of future climate change and elevated CO2 on the water use efficiency in terrestrial ecosystems of China

USGS Publications Warehouse

Zhu, Q.; Jiang, H.; Peng, C.; Liu, J.; Wei, X.; Fang, X.; Liu, S.; Zhou, G.; Yu, S.

2011-01-01

Water use efficiency (WUE) is an important variable used in climate change and hydrological studies in relation to how it links ecosystem carbon cycles and hydrological cycles together. However, obtaining reliable WUE results based on site-level flux data remains a great challenge when scaling up to larger regional zones. Biophysical, process-based ecosystem models are powerful tools to study WUE at large spatial and temporal scales. The Integrated BIosphere Simulator (IBIS) was used to evaluate the effects of climate change and elevated CO2 concentrations on ecosystem-level WUE (defined as the ratio of gross primary production (GPP) to evapotranspiration (ET)) in relation to terrestrial ecosystems in China for 2009–2099. Climate scenario data (IPCC SRES A2 and SRES B1) generated from the Third Generation Coupled Global Climate Model (CGCM3) was used in the simulations. Seven simulations were implemented according to the assemblage of different elevated CO2 concentrations scenarios and different climate change scenarios. Analysis suggests that (1) further elevated CO2concentrations will significantly enhance the WUE over China by the end of the twenty-first century, especially in forest areas; (2) effects of climate change on WUE will vary for different geographical regions in China with negative effects occurring primarily in southern regions and positive effects occurring primarily in high latitude and altitude regions (Tibetan Plateau); (3) WUE will maintain the current levels for 2009–2099 under the constant climate scenario (i.e. using mean climate condition of 1951–2006 and CO2concentrations of the 2008 level); and (4) WUE will decrease with the increase of water resource restriction (expressed as evaporation ratio) among different ecosystems.

Structural covariance networks are coupled to expression of genes enriched in supragranular layers of the human cortex.

PubMed

Romero-Garcia, Rafael; Whitaker, Kirstie J; Váša, František; Seidlitz, Jakob; Shinn, Maxwell; Fonagy, Peter; Dolan, Raymond J; Jones, Peter B; Goodyer, Ian M; Bullmore, Edward T; Vértes, Petra E

2018-05-01

Complex network topology is characteristic of many biological systems, including anatomical and functional brain networks (connectomes). Here, we first constructed a structural covariance network from MRI measures of cortical thickness on 296 healthy volunteers, aged 14-24 years. Next, we designed a new algorithm for matching sample locations from the Allen Brain Atlas to the nodes of the SCN. Subsequently we used this to define, transcriptomic brain networks by estimating gene co-expression between pairs of cortical regions. Finally, we explored the hypothesis that transcriptional networks and structural MRI connectomes are coupled. A transcriptional brain network (TBN) and a structural covariance network (SCN) were correlated across connection weights and showed qualitatively similar complex topological properties: assortativity, small-worldness, modularity, and a rich-club. In both networks, the weight of an edge was inversely related to the anatomical (Euclidean) distance between regions. There were differences between networks in degree and distance distributions: the transcriptional network had a less fat-tailed degree distribution and a less positively skewed distance distribution than the SCN. However, cortical areas connected to each other within modules of the SCN had significantly higher levels of whole genome co-expression than expected by chance. Nodes connected in the SCN had especially high levels of expression and co-expression of a human supragranular enriched (HSE) gene set that has been specifically located to supragranular layers of human cerebral cortex and is known to be important for large-scale, long-distance cortico-cortical connectivity. This coupling of brain transcriptome and connectome topologies was largely but not entirely accounted for by the common constraint of physical distance on both networks. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

On the use of metabolic control analysis in the optimization of cyanobacterial biosolar cell factories.

PubMed

Angermayr, S Andreas; Hellingwerf, Klaas J

2013-09-26

Oxygenic photosynthesis will have a key role in a sustainable future. It is therefore significant that this process can be engineered in organisms such as cyanobacteria to construct cell factories that catalyze the (sun)light-driven conversion of CO2 and water into products like ethanol, butanol, or other biofuels or lactic acid, a bioplastic precursor, and oxygen as a byproduct. It is of key importance to optimize such cell factories to maximal efficiency. This holds for their light-harvesting capabilities under, for example, circadian illumination in large-scale photobioreactors. However, this also holds for the "dark" reactions of photosynthesis, that is, the conversion of CO2, NADPH, and ATP into a product. Here, we present an analysis, based on metabolic control theory, to estimate the optimal capacity for product formation with which such cyanobacterial cell factories have to be equipped. Engineered l-lactic acid producing Synechocystis sp. PCC6803 strains are used to identify the relation between production rate and enzymatic capacity. The analysis shows that the engineered cell factories for l-lactic acid are fully limited by the metabolic capacity of the product-forming pathway. We attribute this to the fact that currently available promoter systems in cyanobacteria lack the genetic capacity to a provide sufficient expression in single-gene doses.

Analysis of CO2 trapping capacities and long-term migration for geological formations in the Norwegian North Sea using MRST-co2lab

NASA Astrophysics Data System (ADS)

Møll Nilsen, Halvor; Lie, Knut-Andreas; Andersen, Odd

2015-06-01

MRST-co2lab is a collection of open-source computational tools for modeling large-scale and long-time migration of CO2 in conductive aquifers, combining ideas from basin modeling, computational geometry, hydrology, and reservoir simulation. Herein, we employ the methods of MRST-co2lab to study long-term CO2 storage on the scale of hundreds of megatonnes. We consider public data sets of two aquifers from the Norwegian North Sea and use geometrical methods for identifying structural traps, percolation-type methods for identifying potential spill paths, and vertical-equilibrium methods for efficient simulation of structural, residual, and solubility trapping in a thousand-year perspective. In particular, we investigate how data resolution affects estimates of storage capacity and discuss workflows for identifying good injection sites and optimizing injection strategies.

High Throughput, High Content Screening for Novel Pigmentation Regulators Using a Keratinocyte/Melanocyte Co-culture System

PubMed Central

Lee, Ju Hee; Chen, Hongxiang; Kolev, Vihren; Aull, Katherine H.; Jung, Inhee; Wang, Jun; Miyamoto, Shoko; Hosoi, Junichi; Mandinova, Anna; Fisher, David E.

2014-01-01

Skin pigmentation is a complex process including melanogenesis within melanocytes and melanin transfer to the keratinocytes. To develop a comprehensive screening method for novel pigmentation regulators, we used immortalized melanocytes and keratinocytes in co-culture to screen large numbers of compounds. High-throughput screening plates were subjected to digital automated microscopy to quantify the pigmentation via brightfield microscopy. Compounds with pigment suppression were secondarily tested for their effects on expression of MITF and several pigment regulatory genes, and further validated in terms of non-toxicity to keratinocytes/melanocytes and dose dependent activity. The results demonstrate a high-throughput, high-content screening approach, which is applicable to the analysis of large chemical libraries using a co-culture system. We identified candidate pigmentation inhibitors from 4,000 screened compounds including zoxazolamine, 3-methoxycatechol, and alpha-mangostin, which were also shown to modulate expression of MITF and several key pigmentation factors, and are worthy of further evaluation for potential translation to clinical use. PMID:24438532

Basin-Scale Hydrologic Impacts of CO2 Storage: Regulatory and Capacity Implications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Birkholzer, J.T.; Zhou, Q.

Industrial-scale injection of CO{sub 2} into saline sedimentary basins will cause large-scale fluid pressurization and migration of native brines, which may affect valuable groundwater resources overlying the deep sequestration reservoirs. In this paper, we discuss how such basin-scale hydrologic impacts can (1) affect regulation of CO{sub 2} storage projects and (2) may reduce current storage capacity estimates. Our assessment arises from a hypothetical future carbon sequestration scenario in the Illinois Basin, which involves twenty individual CO{sub 2} storage projects in a core injection area suitable for long-term storage. Each project is assumed to inject five million tonnes of CO{sub 2}more » per year for 50 years. A regional-scale three-dimensional simulation model was developed for the Illinois Basin that captures both the local-scale CO{sub 2}-brine flow processes and the large-scale groundwater flow patterns in response to CO{sub 2} storage. The far-field pressure buildup predicted for this selected sequestration scenario suggests that (1) the area that needs to be characterized in a permitting process may comprise a very large region within the basin if reservoir pressurization is considered, and (2) permits cannot be granted on a single-site basis alone because the near- and far-field hydrologic response may be affected by interference between individual sites. Our results also support recent studies in that environmental concerns related to near-field and far-field pressure buildup may be a limiting factor on CO{sub 2} storage capacity. In other words, estimates of storage capacity, if solely based on the effective pore volume available for safe trapping of CO{sub 2}, may have to be revised based on assessments of pressure perturbations and their potential impact on caprock integrity and groundwater resources, respectively. We finally discuss some of the challenges in making reliable predictions of large-scale hydrologic impacts related to CO{sub 2} sequestration projects.« less

Energetic valorization of wood waste: estimation of the reduction in CO2 emissions.

PubMed

Vanneste, J; Van Gerven, T; Vander Putten, E; Van der Bruggen, B; Helsen, L

2011-09-01

This paper investigates the potential CO(2) emission reductions related to a partial switch from fossil fuel-based heat and electricity generation to renewable wood waste-based systems in Flanders. The results show that valorization in large-scale CHP (combined heat and power) systems and co-firing in coal plants have the largest CO(2) reduction per TJ wood waste. However, at current co-firing rates of 10%, the CO(2) reduction per GWh of electricity that can be achieved by co-firing in coal plants is five times lower than the CO(2) reduction per GWh of large-scale CHP. Moreover, analysis of the effect of government support for co-firing of wood waste in coal-fired power plants on the marginal costs of electricity generation plants reveals that the effect of the European Emission Trading Scheme (EU ETS) is effectively counterbalanced. This is due to the fact that biomass integrated gasification combined cycles (BIGCC) are not yet commercially available. An increase of the fraction of coal-based electricity in the total electricity generation from 8 to 10% at the expense of the fraction of gas-based electricity due to the government support for co-firing wood waste, would compensate entirely for the CO(2) reduction by substitution of coal by wood waste. This clearly illustrates the possibility of a 'rebound' effect on the CO(2) reduction due to government support for co-combustion of wood waste in an electricity generation system with large installed capacity of coal- and gas-based power plants, such as the Belgian one. Copyright © 2011 Elsevier B.V. All rights reserved.

Identification of tissue-specific, abiotic stress-responsive gene expression patterns in wine grape (Vitis vinifera L.) based on curation and mining of large-scale EST data sets

PubMed Central

2011-01-01

Background Abiotic stresses, such as water deficit and soil salinity, result in changes in physiology, nutrient use, and vegetative growth in vines, and ultimately, yield and flavor in berries of wine grape, Vitis vinifera L. Large-scale expressed sequence tags (ESTs) were generated, curated, and analyzed to identify major genetic determinants responsible for stress-adaptive responses. Although roots serve as the first site of perception and/or injury for many types of abiotic stress, EST sequencing in root tissues of wine grape exposed to abiotic stresses has been extremely limited to date. To overcome this limitation, large-scale EST sequencing was conducted from root tissues exposed to multiple abiotic stresses. Results A total of 62,236 expressed sequence tags (ESTs) were generated from leaf, berry, and root tissues from vines subjected to abiotic stresses and compared with 32,286 ESTs sequenced from 20 public cDNA libraries. Curation to correct annotation errors, clustering and assembly of the berry and leaf ESTs with currently available V. vinifera full-length transcripts and ESTs yielded a total of 13,278 unique sequences, with 2302 singletons and 10,976 mapped to V. vinifera gene models. Of these, 739 transcripts were found to have significant differential expression in stressed leaves and berries including 250 genes not described previously as being abiotic stress responsive. In a second analysis of 16,452 ESTs from a normalized root cDNA library derived from roots exposed to multiple, short-term, abiotic stresses, 135 genes with root-enriched expression patterns were identified on the basis of their relative EST abundance in roots relative to other tissues. Conclusions The large-scale analysis of relative EST frequency counts among a diverse collection of 23 different cDNA libraries from leaf, berry, and root tissues of wine grape exposed to a variety of abiotic stress conditions revealed distinct, tissue-specific expression patterns, previously unrecognized stress-induced genes, and many novel genes with root-enriched mRNA expression for improving our understanding of root biology and manipulation of rootstock traits in wine grape. mRNA abundance estimates based on EST library-enriched expression patterns showed only modest correlations between microarray and quantitative, real-time reverse transcription-polymerase chain reaction (qRT-PCR) methods highlighting the need for deep-sequencing expression profiling methods. PMID:21592389

The imprint of surface fluxes and transport on variations in total column carbon dioxide

NASA Astrophysics Data System (ADS)

Keppel-Aleks, G.; Wennberg, P. O.; Washenfelder, R. A.; Wunch, D.; Schneider, T.; Toon, G. C.; Andres, R. J.; Blavier, J.-F.; Connor, B.; Davis, K. J.; Desai, A. R.; Messerschmidt, J.; Notholt, J.; Roehl, C. M.; Sherlock, V.; Stephens, B. B.; Vay, S. A.; Wofsy, S. C.

2011-07-01

New observations of the vertically integrated CO2 mixing ratio, ⟨CO2⟩, from ground-based remote sensing show that variations in ⟨CO2⟩ are primarily determined by large-scale flux patterns. They therefore provide fundamentally different information than observations made within the boundary layer, which reflect the combined influence of large scale and local fluxes. Observations of both ⟨CO2⟩ and CO2 concentrations in the free troposphere show that large-scale spatial gradients induce synoptic-scale temporal variations in ⟨CO2⟩ in the Northern Hemisphere midlatitudes through horizontal advection. Rather than obscure the signature of surface fluxes on atmospheric CO2, these synoptic-scale variations provide useful information that can be used to reveal the meridional flux distribution. We estimate the meridional gradient in ⟨CO2⟩ from covariations in ⟨CO2⟩ and potential temperature, θ, a dynamical tracer, on synoptic timescales to evaluate surface flux estimates commonly used in carbon cycle models. We find that Carnegie Ames Stanford Approach (CASA) biospheric fluxes underestimate both the ⟨CO2⟩ seasonal cycle amplitude throughout the Northern Hemisphere midlatitudes as well as the meridional gradient during the growing season. Simulations using CASA net ecosystem exchange (NEE) with increased and phase-shifted boreal fluxes better reflect the observations. Our simulations suggest that boreal growing season NEE (between 45-65° N) is underestimated by ~40 % in CASA. We describe the implications for this large seasonal exchange on inference of the net Northern Hemisphere terrestrial carbon sink.

The imprint of surface fluxes and transport on variations in total column carbon dioxide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keppel-Aleks, G; Wennberg, PO; Washenfelder, RA

2012-01-01

New observations of the vertically integrated CO{sub 2} mixing ratio, , from ground-based remote sensing show that variations in are primarily determined by large-scale flux patterns. They therefore provide fundamentally different information than observations made within the boundary layer, which reflect the combined influence of large-scale and local fluxes. Observations of both and CO{sub 2} concentrations in the free troposphere show that large-scale spatial gradients induce synoptic-scale temporal variations in in the Northern Hemisphere midlatitudes through horizontal advection. Rather than obscure the signature of surface fluxes on atmospheric CO{sub 2}, these synoptic-scale variationsmore » provide useful information that can be used to reveal the meridional flux distribution. We estimate the meridional gradient in from covariations in and potential temperature, {theta}, a dynamical tracer, on synoptic timescales to evaluate surface flux estimates commonly used in carbon cycle models. We find that simulations using Carnegie Ames Stanford Approach (CASA) biospheric fluxes underestimate both the seasonal cycle amplitude throughout the Northern Hemisphere midlatitudes and the meridional gradient during the growing season. Simulations using CASA net ecosystem exchange (NEE) with increased and phase-shifted boreal fluxes better fit the observations. Our simulations suggest that climatological mean CASA fluxes underestimate boreal growing season NEE (between 45-65{sup o} N) by {approx}40%. We describe the implications for this large seasonal exchange on inference of the net Northern Hemisphere terrestrial carbon sink.« less

The imprint of surface fluxes and transport on variations in total column carbon dioxide

NASA Astrophysics Data System (ADS)

Keppel-Aleks, G.; Wennberg, P. O.; Washenfelder, R. A.; Wunch, D.; Schneider, T.; Toon, G. C.; Andres, R. J.; Blavier, J.-F.; Connor, B.; Davis, K. J.; Desai, A. R.; Messerschmidt, J.; Notholt, J.; Roehl, C. M.; Sherlock, V.; Stephens, B. B.; Vay, S. A.; Wofsy, S. C.

2012-03-01

New observations of the vertically integrated CO2 mixing ratio, ⟨CO2⟩, from ground-based remote sensing show that variations in CO2⟩ are primarily determined by large-scale flux patterns. They therefore provide fundamentally different information than observations made within the boundary layer, which reflect the combined influence of large-scale and local fluxes. Observations of both ⟨CO2⟩ and CO2 concentrations in the free troposphere show that large-scale spatial gradients induce synoptic-scale temporal variations in ⟨CO2⟩ in the Northern Hemisphere midlatitudes through horizontal advection. Rather than obscure the signature of surface fluxes on atmospheric CO2, these synoptic-scale variations provide useful information that can be used to reveal the meridional flux distribution. We estimate the meridional gradient in ⟨CO2⟩ from covariations in ⟨CO2⟩ and potential temperature, θ, a dynamical tracer, on synoptic timescales to evaluate surface flux estimates commonly used in carbon cycle models. We find that simulations using Carnegie Ames Stanford Approach (CASA) biospheric fluxes underestimate both the ⟨CO2⟩ seasonal cycle amplitude throughout the Northern Hemisphere midlatitudes and the meridional gradient during the growing season. Simulations using CASA net ecosystem exchange (NEE) with increased and phase-shifted boreal fluxes better fit the observations. Our simulations suggest that climatological mean CASA fluxes underestimate boreal growing season NEE (between 45-65° N) by ~40%. We describe the implications for this large seasonal exchange on inference of the net Northern Hemisphere terrestrial carbon sink.

Genome-wide computational prediction and analysis of core promoter elements across plant monocots and dicots

USDA-ARS?s Scientific Manuscript database

Transcription initiation, essential to gene expression regulation, involves recruitment of basal transcription factors to the core promoter elements (CPEs). The distribution of currently known CPEs across plant genomes is largely unknown. This is the first large scale genome-wide report on the compu...

Reduction of adenovirus E1A mRNA by RNAi results in enhanced recombinant protein expression in transiently transfected HEK293 cells.

PubMed

Hacker, David L; Bertschinger, Martin; Baldi, Lucia; Wurm, Florian M

2004-10-27

Human embryonic kidney 293 (HEK293) cells, a widely used host for large-scale transient expression of recombinant proteins, are transformed with the adenovirus E1A and E1B genes. Because the E1A proteins function as transcriptional activators or repressors, they may have a positive or negative effect on transient transgene expression in this cell line. Suspension cultures of HEK293 EBNA (HEK293E) cells were co-transfected with a reporter plasmid expressing the GFP gene and a plasmid expressing a short hairpin RNA (shRNA) targeting the E1A mRNAs for degradation by RNA interference (RNAi). The presence of the shRNA in HEK293E cells reduced the steady state level of E1A mRNA up to 75% and increased transient GFP expression from either the elongation factor-1alpha (EF-1alpha) promoter or the human cytomegalovirus (HCMV) immediate early promoter up to twofold. E1A mRNA depletion also resulted in a twofold increase in transient expression of a recombinant IgG in both small- and large-scale suspension cultures when the IgG light and heavy chain genes were controlled by the EF-1alpha promoter. Finally, transient IgG expression was enhanced 2.5-fold when the anti-E1A shRNA was expressed from the same vector as the IgG light chain gene. These results demonstrated that E1A has a negative effect on transient gene expression in HEK293E cells, and they established that RNAi can be used to enhance recombinant protein expression in mammalian cells.

Multi-Scale Transport Properties of Fine-Grained Rocks: A Case Study of the Kirtland Formation, San Juan Basin, USA

NASA Astrophysics Data System (ADS)

Heath, J. E.; Dewers, T. A.; McPherson, B. J.; Wilson, T. H.; Flach, T.

2009-12-01

Understanding and characterizing transport properties of fine-grained rocks is critical in development of shale gas plays or assessing retention of CO2 at geologic storage sites. Difficulties arise in that both small scale (i.e., ~ nm) properties of the rock matrix and much larger scale fractures, faults, and sedimentological architecture govern migration of multiphase fluids. We present a multi-scale investigation of sealing and transport properties of the Kirtland Formation, which is a regional aquitard and reservoir seal in the San Juan Basin, USA. Sub-micron dual FIB/SEM imaging and reconstruction of 3D pore networks in core samples reveal a variety of pore types, including slit-shaped pores that are co-located with sedimentary structures and variations in mineralogy. Micron-scale chemical analysis and XRD reveal a mixture of mixed-layer smectite/illite, chlorite, quartz, and feldspar with little organic matter. Analysis of sub-micron digital reconstructions, mercury capillary injection pressure, and gas breakthrough measurements indicate a high quality sealing matrix. Natural full and partially mineralized fractures observed in core and in FMI logs include those formed from early soil-forming processes, differential compaction, and tectonic events. The potential impact of both fracture and matrix properties on large-scale transport is investigated through an analysis of natural helium from core samples, 3D seismic data and poro-elastic modeling. While seismic interpretations suggest considerable fracturing of the Kirtland, large continuous fracture zones and faults extending through the seal to the surface cannot be inferred from the data. Observed Kirtland Formation multi-scale transport properties are included as part of a risk assessment methodology for CO2 storage. Acknowledgements: The authors gratefully acknowledge the U.S. Department of Energy’s (DOE) National Energy Technology Laboratory for sponsoring this project. The DOE’s Basic Energy Science Office funded the dual FIB/SEM analysis. The Kirtland Formation overlies the coal seams of the Fruitland into which CO2 has been injected as a Phase II demonstration of the Southwest Regional Partnership on Carbon Sequestration. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the U.S. Department of Energy under contract DE-ACOC4-94AL85000.

Integrated analysis of transcriptome and lipid profiling reveals the co-influences of inositol-choline and Snf1 in controlling lipid biosynthesis in yeast.

PubMed

Chumnanpuen, Pramote; Zhang, Jie; Nookaew, Intawat; Nielsen, Jens

2012-07-01

In the yeast Saccharomyces cerevisiae many genes involved in lipid biosynthesis are transcriptionally controlled by inositol-choline and the protein kinase Snf1. Here we undertook a global study on how inositol-choline and Snf1 interact in controlling lipid metabolism in yeast. Using both a reference strain (CEN.PK113-7D) and a snf1Δ strain cultured at different nutrient limitations (carbon and nitrogen), at a fixed specific growth rate of 0.1 h(-1), and at different inositol choline concentrations, we quantified the expression of genes involved in lipid biosynthesis and the fluxes towards the different lipid components. Through integrated analysis of the transcriptome, the lipid profiling and the fluxome, it was possible to obtain a high quality, large-scale dataset that could be used to identify correlations and associations between the different components. At the transcription level, Snf1 and inositol-choline interact either directly through the main phospholipid-involving transcription factors (i.e. Ino2, Ino4, and Opi1) or through other transcription factors e.g. Gis1, Mga2, and Hac1. However, there seems to be flux regulation at the enzyme levels of several lipid involving enzymes. The analysis showed the strength of using both transcriptome and lipid profiling analysis for mapping the co-influence of inositol-choline and Snf1 on phospholipid metabolism.

Transitions from mono- to co- to tri-culture uniquely affect gene expression in breast cancer, stromal, and immune compartments

PubMed Central

Weinberger, Emma M.; Regehr, Keil J.; Berry, Scott M.; Beebe, David J.; Alarid, Elaine T.

2016-01-01

Heterotypic interactions in cancer microenvironments play important roles in disease initiation, progression, and spread. Co-culture is the predominant approach used in dissecting paracrine interactions between tumor and stromal cells, but functional results from simple co-cultures frequently fail to correlate to in vivo conditions. Though complex heterotypic in vitro models have improved functional relevance, there is little systematic knowledge of how multi-culture parameters influence this recapitulation. We therefore have employed a more iterative approach to investigate the influence of increasing model complexity; increased heterotypic complexity specifically. Here we describe how the compartmentalized and microscale elements of our multi-culture device allowed us to obtain gene expression data from one cell type at a time in a heterotypic culture where cells communicated through paracrine interactions. With our device we generated a large dataset comprised of cell type specific gene-expression patterns for cultures of increasing complexity (three cell types in mono-, co-, or tri-culture) not readily accessible in other systems. Principal component analysis indicated that gene expression was changed in co-culture but was often more strongly altered in tri-culture as compared to mono-culture. Our analysis revealed that cell type identity and the complexity around it (mono-, co-, or tri-culture) influence gene regulation. We also observed evidence of complementary regulation between cell types in the same heterotypic culture. Here we demonstrate the utility of our platform in providing insight into how tumor and stromal cells respond to microenvironments of varying complexities highlighting the expanding importance of heterotypic cultures that go beyond conventional co-culture. PMID:27432323

Final Report Systems Level Analysis of the Function and Adaptive Responses of Methanogenic Consortia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lovley, Derek R.

The purpose of this research was to determine whether the syntrophic microbial associations that are central to the functioning of methane-producing terrestrial wetlands can be predictively modeled with coupled multi-species genome-scale metabolic models. Such models are important because methane is an important greenhouse gas and there is a need to predictively model how the methane-producing microbial communities will respond to environmental perturbations, such as global climate change. The research discovered that the most prodigious methane-producing microorganisms on earth participate in a previously unrecognized form of energy exchange. The methane-producers Methanosaeta and Methanosarcina forge biological electrical connections with other microbes inmore » order to obtain electrons to reduce carbon dioxide to methane. This direct interspecies electron transfer (DIET) was demonstrated in complex microbial communities as well as in defined co-cultures. For example, metatranscriptomic analysis of gene expression in both natural communities and defined co-cultures demonstrated that Methanosaeta species highly expressed genes for the enzymes for the reduction of carbon dioxide to methane. Furthermore, Methanosaeta’s electron-donating partners highly expressed genes for the biological electrical connections known as microbial nanowires. A series of studies involving transcriptomics, genome resequencing, and analysis of the metabolism of a series of strains with targeted gene deletions, further elucidated the mechanisms and energetics of DIET in methane-producing co-cultures, as well as in a co-culture of Geobacter metallireducens and Geobacter sulfurreducens, which provided a system for studying DIET with two genetically tractable partners. Genome-scale modeling of DIET in the G. metallireducens/G. sulfurreducens co-culture suggested that DIET provides more energy to the electron-donating partner that electron exchange via interspecies hydrogen transfer, but that the performance of DIET may be strongly influenced by environmental factors. These studies have significantly modified conceptual models for carbon and electron flow in methane-producing environments and have developed a computational framework for predictive modeling the influence of environmental perturbations on methane-producing microbial communities. The results have important implications for modeling the response of methane-producing microbial communities to climate change as well as for the bioenergy strategy of converting wastes and biomass to methane.« less

Gene and process level modulation to overcome the bottlenecks of recombinant proteins expression in Pichia pastoris.

PubMed

Prabhu, Ashish A; Boro, Bibari; Bharali, Biju; Chakraborty, Shuchishloka; Dasu, Veeranki V

2017-01-01

Process development involving system metabolic engineering and bioprocess engineering has become one of the major thrust for the development of therapeutic proteins or enzymes. Pichia pastoris has emerged as a prominent host for the production of therapeutic protein or enzymes. Regardless of producing high protein titers, various cellular and process level bottlenecks restrict the expression of recombinant proteins in P. pastoris. In the present review, we have summarized the recent developments in the expression of foreign proteins in P. pastoris. Further, we have discussed various cellular engineering strategies which include codon optimization, pathway engineering, signal peptide processing, development of protease deficient strain and glyco-engineered strains for the high yield protein secretion of recombinant protein. Bioprocess development of recombinant proteins in large-scale bioreactor including medium optimization, optimum feeding strategy and co-substrate feeding in fed-batch as well as continuous cultivation have been described. The recent advances in system and synthetic biology studies including metabolic flux analysis in understanding the phenotypic characteristics of recombinant Pichia and genome editing with CRISPR-CAS system have also been summarized. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Integrated Mid-Continent Carbon Capture, Sequestration & Enhanced Oil Recovery Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brian McPherson

2010-08-31

A consortium of research partners led by the Southwest Regional Partnership on Carbon Sequestration and industry partners, including CAP CO2 LLC, Blue Source LLC, Coffeyville Resources, Nitrogen Fertilizers LLC, Ash Grove Cement Company, Kansas Ethanol LLC, Headwaters Clean Carbon Services, Black & Veatch, and Schlumberger Carbon Services, conducted a feasibility study of a large-scale CCS commercialization project that included large-scale CO{sub 2} sources. The overall objective of this project, entitled the 'Integrated Mid-Continent Carbon Capture, Sequestration and Enhanced Oil Recovery Project' was to design an integrated system of US mid-continent industrial CO{sub 2} sources with CO{sub 2} capture, and geologicmore » sequestration in deep saline formations and in oil field reservoirs with concomitant EOR. Findings of this project suggest that deep saline sequestration in the mid-continent region is not feasible without major financial incentives, such as tax credits or otherwise, that do not exist at this time. However, results of the analysis suggest that enhanced oil recovery with carbon sequestration is indeed feasible and practical for specific types of geologic settings in the Midwestern U.S.« less

Co-evolutionary Analysis of Domains in Interacting Proteins Reveals Insights into Domain–Domain Interactions Mediating Protein–Protein Interactions

PubMed Central

Jothi, Raja; Cherukuri, Praveen F.; Tasneem, Asba; Przytycka, Teresa M.

2006-01-01

Recent advances in functional genomics have helped generate large-scale high-throughput protein interaction data. Such networks, though extremely valuable towards molecular level understanding of cells, do not provide any direct information about the regions (domains) in the proteins that mediate the interaction. Here, we performed co-evolutionary analysis of domains in interacting proteins in order to understand the degree of co-evolution of interacting and non-interacting domains. Using a combination of sequence and structural analysis, we analyzed protein–protein interactions in F1-ATPase, Sec23p/Sec24p, DNA-directed RNA polymerase and nuclear pore complexes, and found that interacting domain pair(s) for a given interaction exhibits higher level of co-evolution than the noninteracting domain pairs. Motivated by this finding, we developed a computational method to test the generality of the observed trend, and to predict large-scale domain–domain interactions. Given a protein–protein interaction, the proposed method predicts the domain pair(s) that is most likely to mediate the protein interaction. We applied this method on the yeast interactome to predict domain–domain interactions, and used known domain–domain interactions found in PDB crystal structures to validate our predictions. Our results show that the prediction accuracy of the proposed method is statistically significant. Comparison of our prediction results with those from two other methods reveals that only a fraction of predictions are shared by all the three methods, indicating that the proposed method can detect known interactions missed by other methods. We believe that the proposed method can be used with other methods to help identify previously unrecognized domain–domain interactions on a genome scale, and could potentially help reduce the search space for identifying interaction sites. PMID:16949097

Application of multivariate analysis and mass transfer principles for refinement of a 3-L bioreactor scale-down model--when shake flasks mimic 15,000-L bioreactors better.

PubMed

Ahuja, Sanjeev; Jain, Shilpa; Ram, Kripa

2015-01-01

Characterization of manufacturing processes is key to understanding the effects of process parameters on process performance and product quality. These studies are generally conducted using small-scale model systems. Because of the importance of the results derived from these studies, the small-scale model should be predictive of large scale. Typically, small-scale bioreactors, which are considered superior to shake flasks in simulating large-scale bioreactors, are used as the scale-down models for characterizing mammalian cell culture processes. In this article, we describe a case study where a cell culture unit operation in bioreactors using one-sided pH control and their satellites (small-scale runs conducted using the same post-inoculation cultures and nutrient feeds) in 3-L bioreactors and shake flasks indicated that shake flasks mimicked the large-scale performance better than 3-L bioreactors. We detail here how multivariate analysis was used to make the pertinent assessment and to generate the hypothesis for refining the existing 3-L scale-down model. Relevant statistical techniques such as principal component analysis, partial least square, orthogonal partial least square, and discriminant analysis were used to identify the outliers and to determine the discriminatory variables responsible for performance differences at different scales. The resulting analysis, in combination with mass transfer principles, led to the hypothesis that observed similarities between 15,000-L and shake flask runs, and differences between 15,000-L and 3-L runs, were due to pCO2 and pH values. This hypothesis was confirmed by changing the aeration strategy at 3-L scale. By reducing the initial sparge rate in 3-L bioreactor, process performance and product quality data moved closer to that of large scale. © 2015 American Institute of Chemical Engineers.

Economic and energetic analysis of capturing CO2 from ambient air

PubMed Central

House, Kurt Zenz; Baclig, Antonio C.; Ranjan, Manya; van Nierop, Ernst A.; Wilcox, Jennifer; Herzog, Howard J.

2011-01-01

Capturing carbon dioxide from the atmosphere (“air capture”) in an industrial process has been proposed as an option for stabilizing global CO2 concentrations. Published analyses suggest these air capture systems may cost a few hundred dollars per tonne of CO2, making it cost competitive with mainstream CO2 mitigation options like renewable energy, nuclear power, and carbon dioxide capture and storage from large CO2 emitting point sources. We investigate the thermodynamic efficiencies of commercial separation systems as well as trace gas removal systems to better understand and constrain the energy requirements and costs of these air capture systems. Our empirical analyses of operating commercial processes suggest that the energetic and financial costs of capturing CO2 from the air are likely to have been underestimated. Specifically, our analysis of existing gas separation systems suggests that, unless air capture significantly outperforms these systems, it is likely to require more than 400 kJ of work per mole of CO2, requiring it to be powered by CO2-neutral power sources in order to be CO2 negative. We estimate that total system costs of an air capture system will be on the order of $1,000 per tonne of CO2, based on experience with as-built large-scale trace gas removal systems. PMID:22143760

Co-expression of mitosis-regulating genes contributes to malignant progression and prognosis in oligodendrogliomas

PubMed Central

Liu, Yanwei; Hu, Huimin; Zhang, Chuanbao; Wang, Haoyuan; Zhang, Wenlong; Wang, Zheng; Li, Mingyang; Zhang, Wei; Zhou, Dabiao; Jiang, Tao

2015-01-01

The clinical prognosis of patients with glioma is determined by tumor grades, but tumors of different subtypes with equal malignancy grade usually have different prognosis that is largely determined by genetic abnormalities. Oligodendrogliomas (ODs) are the second most common type of gliomas. In this study, integrative analyses found that distribution of TCGA transcriptomic subtypes was associated with grade progression in ODs. To identify critical gene(s) associated with tumor grades and TCGA subtypes, we analyzed 34 normal brain tissue (NBT), 146 WHO grade II and 130 grade III ODs by microarray and RNA sequencing, and identified a co-expression network of six genes (AURKA, NDC80,CENPK, KIAA0101, TIMELESS and MELK) that was associated with tumor grades and TCGA subtypes as well as Ki-67 expression. Validation of the six genes was performed by qPCR in additional 28 ODs. Importantly, these genes also were validated in four high-grade recurrent gliomas and the initial lower-grade gliomas resected from the same patients. Finally, the RNA data on two genes with the highest discrimination potential (AURKA and NDC80) and Ki-67 were validated on an independent cohort (5 NBTs and 86 ODs) by immunohistochemistry. Knockdown of AURKA and NDC80 by siRNAs suppressed Ki-67 expression and proliferation of gliomas cells. Survival analysis showed that high expression of the six genes corporately indicated a poor survival outcome. Correlation and protein interaction analysis provided further evidence for this co-expression network. These data suggest that the co-expression of the six mitosis-regulating genes was associated with malignant progression and prognosis in ODs. PMID:26468983

Soybean kinome: functional classification and gene expression patterns

PubMed Central

Liu, Jinyi; Chen, Nana; Grant, Joshua N.; Cheng, Zong-Ming (Max); Stewart, C. Neal; Hewezi, Tarek

2015-01-01

The protein kinase (PK) gene family is one of the largest and most highly conserved gene families in plants and plays a role in nearly all biological functions. While a large number of genes have been predicted to encode PKs in soybean, a comprehensive functional classification and global analysis of expression patterns of this large gene family is lacking. In this study, we identified the entire soybean PK repertoire or kinome, which comprised 2166 putative PK genes, representing 4.67% of all soybean protein-coding genes. The soybean kinome was classified into 19 groups, 81 families, and 122 subfamilies. The receptor-like kinase (RLK) group was remarkably large, containing 1418 genes. Collinearity analysis indicated that whole-genome segmental duplication events may have played a key role in the expansion of the soybean kinome, whereas tandem duplications might have contributed to the expansion of specific subfamilies. Gene structure, subcellular localization prediction, and gene expression patterns indicated extensive functional divergence of PK subfamilies. Global gene expression analysis of soybean PK subfamilies revealed tissue- and stress-specific expression patterns, implying regulatory functions over a wide range of developmental and physiological processes. In addition, tissue and stress co-expression network analysis uncovered specific subfamilies with narrow or wide interconnected relationships, indicative of their association with particular or broad signalling pathways, respectively. Taken together, our analyses provide a foundation for further functional studies to reveal the biological and molecular functions of PKs in soybean. PMID:25614662

Association of HADHA expression with the risk of breast cancer: targeted subset analysis and meta-analysis of microarray data

PubMed Central

2012-01-01

Background The role of n-3 fatty acids in prevention of breast cancer is well recognized, but the underlying molecular mechanisms are still unclear. In view of the growing need for early detection of breast cancer, Graham et al. (2010) studied the microarray gene expression in histologically normal epithelium of subjects with or without breast cancer. We conducted a secondary analysis of this dataset with a focus on the genes (n = 47) involved in fat and lipid metabolism. We used stepwise multivariate logistic regression analyses, volcano plots and false discovery rates for association analyses. We also conducted meta-analyses of other microarray studies using random effects models for three outcomes--risk of breast cancer (380 breast cancer patients and 240 normal subjects), risk of metastasis (430 metastatic compared to 1104 non-metastatic breast cancers) and risk of recurrence (484 recurring versus 890 non-recurring breast cancers). Results The HADHA gene [hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase (trifunctional protein), alpha subunit] was significantly under-expressed in breast cancer; more so in those with estrogen receptor-negative status. Our meta-analysis showed an 18.4%-26% reduction in HADHA expression in breast cancer. Also, there was an inconclusive but consistent under-expression of HADHA in subjects with metastatic and recurring breast cancers. Conclusions Involvement of mitochondria and the mitochondrial trifunctional protein (encoded by HADHA gene) in breast carcinogenesis is known. Our results lend additional support to the possibility of this involvement. Further, our results suggest that targeted subset analysis of large genome-based datasets can provide interesting association signals. PMID:22240105

Evolution of a Cellular Immune Response in Drosophila: A Phenotypic and Genomic Comparative Analysis

PubMed Central

Salazar-Jaramillo, Laura; Paspati, Angeliki; van de Zande, Louis; Vermeulen, Cornelis Joseph; Schwander, Tanja; Wertheim, Bregje

2014-01-01

Understanding the genomic basis of evolutionary adaptation requires insight into the molecular basis underlying phenotypic variation. However, even changes in molecular pathways associated with extreme variation, gains and losses of specific phenotypes, remain largely uncharacterized. Here, we investigate the large interspecific differences in the ability to survive infection by parasitoids across 11 Drosophila species and identify genomic changes associated with gains and losses of parasitoid resistance. We show that a cellular immune defense, encapsulation, and the production of a specialized blood cell, lamellocytes, are restricted to a sublineage of Drosophila, but that encapsulation is absent in one species of this sublineage, Drosophila sechellia. Our comparative analyses of hemopoiesis pathway genes and of genes differentially expressed during the encapsulation response revealed that hemopoiesis-associated genes are highly conserved and present in all species independently of their resistance. In contrast, 11 genes that are differentially expressed during the response to parasitoids are novel genes, specific to the Drosophila sublineage capable of lamellocyte-mediated encapsulation. These novel genes, which are predominantly expressed in hemocytes, arose via duplications, whereby five of them also showed signatures of positive selection, as expected if they were recruited for new functions. Three of these novel genes further showed large-scale and presumably loss-of-function sequence changes in D. sechellia, consistent with the loss of resistance in this species. In combination, these convergent lines of evidence suggest that co-option of duplicated genes in existing pathways and subsequent neofunctionalization are likely to have contributed to the evolution of the lamellocyte-mediated encapsulation in Drosophila. PMID:24443439

Evolution of a cellular immune response in Drosophila: a phenotypic and genomic comparative analysis.

PubMed

Salazar-Jaramillo, Laura; Paspati, Angeliki; van de Zande, Louis; Vermeulen, Cornelis Joseph; Schwander, Tanja; Wertheim, Bregje

2014-02-01

Understanding the genomic basis of evolutionary adaptation requires insight into the molecular basis underlying phenotypic variation. However, even changes in molecular pathways associated with extreme variation, gains and losses of specific phenotypes, remain largely uncharacterized. Here, we investigate the large interspecific differences in the ability to survive infection by parasitoids across 11 Drosophila species and identify genomic changes associated with gains and losses of parasitoid resistance. We show that a cellular immune defense, encapsulation, and the production of a specialized blood cell, lamellocytes, are restricted to a sublineage of Drosophila, but that encapsulation is absent in one species of this sublineage, Drosophila sechellia. Our comparative analyses of hemopoiesis pathway genes and of genes differentially expressed during the encapsulation response revealed that hemopoiesis-associated genes are highly conserved and present in all species independently of their resistance. In contrast, 11 genes that are differentially expressed during the response to parasitoids are novel genes, specific to the Drosophila sublineage capable of lamellocyte-mediated encapsulation. These novel genes, which are predominantly expressed in hemocytes, arose via duplications, whereby five of them also showed signatures of positive selection, as expected if they were recruited for new functions. Three of these novel genes further showed large-scale and presumably loss-of-function sequence changes in D. sechellia, consistent with the loss of resistance in this species. In combination, these convergent lines of evidence suggest that co-option of duplicated genes in existing pathways and subsequent neofunctionalization are likely to have contributed to the evolution of the lamellocyte-mediated encapsulation in Drosophila.

Large scale production of highly-qualified graphene by ultrasonic exfoliation of expanded graphite under the promotion of (NH4)2CO3 decomposition.

PubMed

Wang, Yunwei; Tong, Xili; Guo, Xiaoning; Wang, Yingyong; Jin, Guoqiang; Guo, Xiangyun

2013-11-29

Highly-qualified graphene was prepared by the ultrasonic exfoliation of commercial expanded graphite (EG) under the promotion of (NH4)2CO3 decomposition. The yield of graphene from the first exfoliation is 7 wt%, and it can be increased to more than 65 wt% by repeated exfoliations. Atomic force microscopy, x-ray photoelectron spectroscopy and Raman analysis show that the as-prepared graphene only has a few defects or oxides, and more than 95% of the graphene flakes have a thickness of ~1 nm. The electrochemical performance of the as-prepared graphene is comparable to reduced graphene oxide in the determination of dopamine (DA) from the mixed solution of ascorbic acid, uric acid and DA. These results show that the decomposition of (NH4)2CO3 molecules in the EG layers under ultrasonication promotes the exfoliation of graphite and provides a low-priced route for large scale production of highly-quality graphene.

Large scale production of highly-qualified graphene by ultrasonic exfoliation of expanded graphite under the promotion of (NH4)2CO3 decomposition

NASA Astrophysics Data System (ADS)

Wang, Yunwei; Tong, Xili; Guo, Xiaoning; Wang, Yingyong; Jin, Guoqiang; Guo, Xiangyun

2013-11-01

Highly-qualified graphene was prepared by the ultrasonic exfoliation of commercial expanded graphite (EG) under the promotion of (NH4)2CO3 decomposition. The yield of graphene from the first exfoliation is 7 wt%, and it can be increased to more than 65 wt% by repeated exfoliations. Atomic force microscopy, x-ray photoelectron spectroscopy and Raman analysis show that the as-prepared graphene only has a few defects or oxides, and more than 95% of the graphene flakes have a thickness of ˜1 nm. The electrochemical performance of the as-prepared graphene is comparable to reduced graphene oxide in the determination of dopamine (DA) from the mixed solution of ascorbic acid, uric acid and DA. These results show that the decomposition of (NH4)2CO3 molecules in the EG layers under ultrasonication promotes the exfoliation of graphite and provides a low-priced route for large scale production of highly-quality graphene.

New Approaches to Quantifying Transport Model Error in Atmospheric CO2 Simulations

NASA Technical Reports Server (NTRS)

Ott, L.; Pawson, S.; Zhu, Z.; Nielsen, J. E.; Collatz, G. J.; Gregg, W. W.

2012-01-01

In recent years, much progress has been made in observing CO2 distributions from space. However, the use of these observations to infer source/sink distributions in inversion studies continues to be complicated by difficulty in quantifying atmospheric transport model errors. We will present results from several different experiments designed to quantify different aspects of transport error using the Goddard Earth Observing System, Version 5 (GEOS-5) Atmospheric General Circulation Model (AGCM). In the first set of experiments, an ensemble of simulations is constructed using perturbations to parameters in the model s moist physics and turbulence parameterizations that control sub-grid scale transport of trace gases. Analysis of the ensemble spread and scales of temporal and spatial variability among the simulations allows insight into how parameterized, small-scale transport processes influence simulated CO2 distributions. In the second set of experiments, atmospheric tracers representing model error are constructed using observation minus analysis statistics from NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA). The goal of these simulations is to understand how errors in large scale dynamics are distributed, and how they propagate in space and time, affecting trace gas distributions. These simulations will also be compared to results from NASA's Carbon Monitoring System Flux Pilot Project that quantified the impact of uncertainty in satellite constrained CO2 flux estimates on atmospheric mixing ratios to assess the major factors governing uncertainty in global and regional trace gas distributions.

Mars dayside temperature from airglow limb profiles : comparison with in situ measurements and models

NASA Astrophysics Data System (ADS)

Gérard, Jean-Claude; Bougher, Stephen; Montmessin, Franck; Bertaux, Jean-Loup; Stiepen, A.

The thermal structure of the Mars upper atmosphere is the result of the thermal balance between heating by EUV solar radiation, infrared heating and cooling, conduction and dynamic influences such as gravity waves, planetary waves, and tides. It has been derived from observations performed from different spacecraft. These include in situ measurements of orbital drag whose strength depends on the local gas density. Atmospheric temperatures were determined from the altitude variation of the density measured in situ by the Viking landers and orbital drag measurements. Another method is based on remote sensing measurements of ultraviolet airglow limb profiles obtained over 40 years ago with spectrometers during the Mariner 6 and 7 flybys and from the Mariner 9 orbiter. Comparisons with model calculations indicate that they both reflect the CO_2 scale height from which atmospheric temperatures have been deduced. Upper atmospheric temperatures varying over the wide range 270-445 K, with a mean value of 325 K were deduced from the topside scale height of the airglow vertical profile. We present an analysis of limb profiles of the CO Cameron (a(3) Pi-X(1) Sigma(+) ) and CO_2(+) doublet (B(2) Sigma_u(+) - X(2) PiΠ_g) airglows observed with the SPICAM instrument on board Mars Express. We show that the temperature in the Mars thermosphere is very variable with a mean value of 270 K, but values ranging between 150 and 400 K have been observed. These values are compared to earlier determinations and model predictions. No clear dependence on solar zenith angle, latitude or season is apparent. Similarly, exospheric variations with F10.7 in the SPICAM airglow dataset are small over the solar minimum to moderate conditions sampled by Mars Express since 2005. We conclude that an unidentified process is the cause of the large observed temperature variability, which dominates the other sources of temperature variations.

Inorganic carbon loading as a primary driver of dissolved carbon dioxide concentrations in the lakes and reservoirs of the contiguous United States

USGS Publications Warehouse

McDonald, Cory P.; Stets, Edward; Striegl, Robert G.; Butman, David

2013-01-01

Accurate quantification of CO2 flux across the air-water interface and identification of the mechanisms driving CO2 concentrations in lakes and reservoirs is critical to integrating aquatic systems into large-scale carbon budgets, and to predicting the response of these systems to changes in climate or terrestrial carbon cycling. Large-scale estimates of the role of lakes and reservoirs in the carbon cycle, however, typically must rely on aggregation of spatially and temporally inconsistent data from disparate sources. We performed a spatially comprehensive analysis of CO2 concentration and air-water fluxes in lakes and reservoirs of the contiguous United States using large, consistent data sets, and modeled the relative contribution of inorganic and organic carbon loading to vertical CO2 fluxes. Approximately 70% of lakes and reservoirs are supersaturated with respect to the atmosphere during the summer (June–September). Although there is considerable interregional and intraregional variability, lakes and reservoirs represent a net source of CO2 to the atmosphere of approximately 40 Gg C d–1 during the summer. While in-lake CO2 concentrations correlate with indicators of in-lake net ecosystem productivity, virtually no relationship exists between dissolved organic carbon and pCO2,aq. Modeling suggests that hydrologic dissolved inorganic carbon supports pCO2,aq in most supersaturated systems (to the extent that 12% of supersaturated systems simultaneously exhibit positive net ecosystem productivity), and also supports primary production in most CO2-undersaturated systems. Dissolved inorganic carbon loading appears to be an important determinant of CO2concentrations and fluxes across the air-water interface in the majority of lakes and reservoirs in the contiguous United States.

Subsurface Monitoring of CO2 Sequestration - A Review and Look Forward

NASA Astrophysics Data System (ADS)

Daley, T. M.

2012-12-01

The injection of CO2 into subsurface formations is at least 50 years old with large-scale utilization of CO2 for enhanced oil recovery (CO2-EOR) beginning in the 1970s. Early monitoring efforts had limited measurements in available boreholes. With growing interest in CO2 sequestration beginning in the 1990's, along with growth in geophysical reservoir monitoring, small to mid-size sequestration monitoring projects began to appear. The overall goals of a subsurface monitoring plan are to provide measurement of CO2 induced changes in subsurface properties at a range of spatial and temporal scales. The range of spatial scales allows tracking of the location and saturation of the plume with varying detail, while finer temporal sampling (up to continuous) allows better understanding of dynamic processes (e.g. multi-phase flow) and constraining of reservoir models. Early monitoring of small scale pilots associated with CO2-EOR (e.g., the McElroy field and the Lost Hills field), developed many of the methodologies including tomographic imaging and multi-physics measurements. Large (reservoir) scale sequestration monitoring began with the Sleipner and Weyburn projects. Typically, large scale monitoring, such as 4D surface seismic, has limited temporal sampling due to costs. Smaller scale pilots can allow more frequent measurements as either individual time-lapse 'snapshots' or as continuous monitoring. Pilot monitoring examples include the Frio, Nagaoka and Otway pilots using repeated well logging, crosswell imaging, vertical seismic profiles and CASSM (continuous active-source seismic monitoring). For saline reservoir sequestration projects, there is typically integration of characterization and monitoring, since the sites are not pre-characterized resource developments (oil or gas), which reinforces the need for multi-scale measurements. As we move beyond pilot sites, we need to quantify CO2 plume and reservoir properties (e.g. pressure) over large scales, while still obtaining high resolution. Typically the high-resolution (spatial and temporal) tools are deployed in permanent or semi-permanent borehole installations, where special well design may be necessary, such as non-conductive casing for electrical surveys. Effective utilization of monitoring wells requires an approach of modular borehole monitoring (MBM) were multiple measurements can be made. An example is recent work at the Citronelle pilot injection site where an MBM package with seismic, fluid sampling and distributed fiber sensing was deployed. For future large scale sequestration monitoring, an adaptive borehole-monitoring program is proposed.

Fibroblast extracellular matrix gene expression in response to keratinocyte-releasable stratifin.

PubMed

Ghaffari, Abdi; Li, Yunyaun; Karami, Ali; Ghaffari, Mazyar; Tredget, Edward E; Ghahary, Aziz

2006-05-15

Termination of wound-healing process requires a fine balance between connective tissue deposition and its hydrolysis. Previously, we have demonstrated that keratinocyte-releasable stratifin, also known as 14-3-3 sigma protein, stimulates collagenase (MMP-1) expression in dermal fibroblasts. However, role of extracellular stratifin in regulation of extracellular matrix (ECM) factors and other matrix metalloproteinases (MMPs) in dermal fibroblast remains unexplored. To address this question, large-scale ECM gene expression profile were analyzed in human dermal fibroblasts co-cultured with keratinocytes or treated with recombinant stratifin. Superarray pathway-specific microarrays were utilized to identify upregulation or downregulation of 96 human ECM and adhesion molecule genes. RT-PCR and Western blot were used to validate microarray expression profiles of selected genes. Comparison of gene profiles with the appropriate controls showed a significant (more than twofold) increase in expression of collagenase-1, stromelysin-1 and -2, neutrophil collagenase, and membrane type 5 MMP in dermal fibroblasts treated with stratifin or co-cultured with keratinocytes. Expression of type I collagen and fibronectin genes decreased in the same fibroblasts. The results of a dose-response experiment showed that stratifin stimulates the expression of stromelysin-1 (MMP-3) mRNA by dermal fibroblasts in a concentration-dependent fashion. Furthermore, Western blot analysis of fibroblast-conditioned medium showed a peak in MMP-3 protein levels 48 h following treatment with recombinant stratifin. In a lasting-effect study, MMP-3 protein was detected in fibroblast-condition medium for up to 72 h post removal of stratifin. In conclusion, our results suggest that keratinocyte-releasable stratifin plays a major role in induction of ECM degradation by dermal fibroblasts through stimulation of key MMPs, such as MMP-1 and MMP-3. Therefore, stratifin protein may prove to be a useful target for clinical intervention in controlling excessive wound healing in fibrotic conditions. Copyright 2006 Wiley-Liss, Inc.

Exploring candidate biomarkers for lung and prostate cancers using gene expression and flux variability analysis.

PubMed

Asgari, Yazdan; Khosravi, Pegah; Zabihinpour, Zahra; Habibi, Mahnaz

2018-02-19

Genome-scale metabolic models have provided valuable resources for exploring changes in metabolism under normal and cancer conditions. However, metabolism itself is strongly linked to gene expression, so integration of gene expression data into metabolic models might improve the detection of genes involved in the control of tumor progression. Herein, we considered gene expression data as extra constraints to enhance the predictive powers of metabolic models. We reconstructed genome-scale metabolic models for lung and prostate, under normal and cancer conditions to detect the major genes associated with critical subsystems during tumor development. Furthermore, we utilized gene expression data in combination with an information theory-based approach to reconstruct co-expression networks of the human lung and prostate in both cohorts. Our results revealed 19 genes as candidate biomarkers for lung and prostate cancer cells. This study also revealed that the development of a complementary approach (integration of gene expression and metabolic profiles) could lead to proposing novel biomarkers and suggesting renovated cancer treatment strategies which have not been possible to detect using either of the methods alone.

A Commercialization Roadmap for Carbon-Negative Energy Systems

NASA Astrophysics Data System (ADS)

Sanchez, D.

2016-12-01

The Intergovernmental Panel on Climate Change (IPCC) envisages the need for large-scale deployment of net-negative CO2 emissions technologies by mid-century to meet stringent climate mitigation goals and yield a net drawdown of atmospheric carbon. Yet there are few commercial deployments of BECCS outside of niche markets, creating uncertainty about commercialization pathways and sustainability impacts at scale. This uncertainty is exacerbated by the absence of a strong policy framework, such as high carbon prices and research coordination. Here, we propose a strategy for the potential commercial deployment of BECCS. This roadmap proceeds via three steps: 1) via capture and utilization of biogenic CO2 from existing bioenergy facilities, notably ethanol fermentation, 2) via thermochemical co-conversion of biomass and fossil fuels, particularly coal, and 3) via dedicated, large-scale BECCS. Although biochemical conversion is a proven first market for BECCS, this trajectory alone is unlikely to drive commercialization of BECCS at the gigatonne scale. In contrast to biochemical conversion, thermochemical conversion of coal and biomass enables large-scale production of fuels and electricity with a wide range of carbon intensities, process efficiencies and process scales. Aside from systems integration, primarily technical barriers are involved in large-scale biomass logistics, gasification and gas cleaning. Key uncertainties around large-scale BECCS deployment are not limited to commercialization pathways; rather, they include physical constraints on biomass cultivation or CO2 storage, as well as social barriers, including public acceptance of new technologies and conceptions of renewable and fossil energy, which co-conversion systems confound. Despite sustainability risks, this commercialization strategy presents a pathway where energy suppliers, manufacturers and governments could transition from laggards to leaders in climate change mitigation efforts.

Animal component-free Agrobacterium tumefaciens cultivation media for better GMP-compliance increases biomass yield and pharmaceutical protein expression in Nicotiana benthamiana.

PubMed

Houdelet, Marcel; Galinski, Anna; Holland, Tanja; Wenzel, Kathrin; Schillberg, Stefan; Buyel, Johannes Felix

2017-04-01

Transient expression systems allow the rapid production of recombinant proteins in plants. Such systems can be scaled up to several hundred kilograms of biomass, making them suitable for the production of pharmaceutical proteins required at short notice, such as emergency vaccines. However, large-scale transient expression requires the production of recombinant Agrobacterium tumefaciens strains with the capacity for efficient gene transfer to plant cells. The complex media often used for the cultivation of this species typically include animal-derived ingredients that can contain human pathogens, thus conflicting with the requirements of good manufacturing practice (GMP). We replaced all the animal-derived components in yeast extract broth (YEB) cultivation medium with soybean peptone, and then used a design-of-experiments approach to optimize the medium composition, increasing the biomass yield while maintaining high levels of transient expression in subsequent infiltration experiments. The resulting plant peptone Agrobacterium medium (PAM) achieved a two-fold increase in OD 600 compared to YEB medium during a 4-L batch fermentation lasting 18 h. Furthermore, the yields of the monoclonal antibody 2G12 and the fluorescent protein DsRed were maintained when the cells were cultivated in PAM rather than YEB. We have thus demonstrated a simple, efficient and scalable method for medium optimization that reduces process time and costs. The final optimized medium for the cultivation of A. tumefaciens completely lacks animal-derived components, thus facilitating the GMP-compliant large-scale transient expression of recombinant proteins in plants. © 2017 The Authors. Biotechnology Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Combining peptide recognition specificity and context information for the prediction of the 14-3-3-mediated interactome in S. cerevisiae and H. sapiens.

PubMed

Panni, Simona; Montecchi-Palazzi, Luisa; Kiemer, Lars; Cabibbo, Andrea; Paoluzi, Serena; Santonico, Elena; Landgraf, Christiane; Volkmer-Engert, Rudolf; Bachi, Angela; Castagnoli, Luisa; Cesareni, Gianni

2011-01-01

Large-scale interaction studies contribute the largest fraction of protein interactions information in databases. However, co-purification of non-specific or indirect ligands, often results in data sets that are affected by a considerable number of false positives. For the fraction of interactions mediated by short linear peptides, we present here a combined experimental and computational strategy for ranking the reliability of the inferred partners. We apply this strategy to the family of 14-3-3 domains. We have first characterized the recognition specificity of this domain family, largely confirming the results of previous analyses, while revealing new features of the preferred sequence context of 14-3-3 phospho-peptide partners. Notably, a proline next to the carboxy side of the phospho-amino acid functions as a potent inhibitor of 14-3-3 binding. The position-specific information about residue preference was encoded in a scoring matrix and two regular expressions. The integration of these three features in a single predictive model outperforms publicly available prediction tools. Next we have combined, by a naïve Bayesian approach, these "peptide features" with "protein features", such as protein co-expression and co-localization. Our approach provides an orthogonal reliability assessment and maps with high confidence the 14-3-3 peptide target on the partner proteins. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Reconstruction of an Integrated Genome-Scale Co-Expression Network Reveals Key Modules Involved in Lung Adenocarcinoma

PubMed Central

Hosseini Ashtiani, Saman; Moeini, Ali; Nowzari-Dalini, Abbas; Masoudi-Nejad, Ali

2013-01-01

Our goal of this study was to reconstruct a “genome-scale co-expression network” and find important modules in lung adenocarcinoma so that we could identify the genes involved in lung adenocarcinoma. We integrated gene mutation, GWAS, CGH, array-CGH and SNP array data in order to identify important genes and loci in genome-scale. Afterwards, on the basis of the identified genes a co-expression network was reconstructed from the co-expression data. The reconstructed network was named “genome-scale co-expression network”. As the next step, 23 key modules were disclosed through clustering. In this study a number of genes have been identified for the first time to be implicated in lung adenocarcinoma by analyzing the modules. The genes EGFR, PIK3CA, TAF15, XIAP, VAPB, Appl1, Rab5a, ARF4, CLPTM1L, SP4, ZNF124, LPP, FOXP1, SOX18, MSX2, NFE2L2, SMARCC1, TRA2B, CBX3, PRPF6, ATP6V1C1, MYBBP1A, MACF1, GRM2, TBXA2R, PRKAR2A, PTK2, PGF and MYO10 are among the genes that belong to modules 1 and 22. All these genes, being implicated in at least one of the phenomena, namely cell survival, proliferation and metastasis, have an over-expression pattern similar to that of EGFR. In few modules, the genes such as CCNA2 (Cyclin A2), CCNB2 (Cyclin B2), CDK1, CDK5, CDC27, CDCA5, CDCA8, ASPM, BUB1, KIF15, KIF2C, NEK2, NUSAP1, PRC1, SMC4, SYCE2, TFDP1, CDC42 and ARHGEF9 are present that play a crucial role in cell cycle progression. In addition to the mentioned genes, there are some other genes (i.e. DLGAP5, BIRC5, PSMD2, Src, TTK, SENP2, PSMD2, DOK2, FUS and etc.) in the modules. PMID:23874428

Reconstruction of an integrated genome-scale co-expression network reveals key modules involved in lung adenocarcinoma.

PubMed

Bidkhori, Gholamreza; Narimani, Zahra; Hosseini Ashtiani, Saman; Moeini, Ali; Nowzari-Dalini, Abbas; Masoudi-Nejad, Ali

2013-01-01

Our goal of this study was to reconstruct a "genome-scale co-expression network" and find important modules in lung adenocarcinoma so that we could identify the genes involved in lung adenocarcinoma. We integrated gene mutation, GWAS, CGH, array-CGH and SNP array data in order to identify important genes and loci in genome-scale. Afterwards, on the basis of the identified genes a co-expression network was reconstructed from the co-expression data. The reconstructed network was named "genome-scale co-expression network". As the next step, 23 key modules were disclosed through clustering. In this study a number of genes have been identified for the first time to be implicated in lung adenocarcinoma by analyzing the modules. The genes EGFR, PIK3CA, TAF15, XIAP, VAPB, Appl1, Rab5a, ARF4, CLPTM1L, SP4, ZNF124, LPP, FOXP1, SOX18, MSX2, NFE2L2, SMARCC1, TRA2B, CBX3, PRPF6, ATP6V1C1, MYBBP1A, MACF1, GRM2, TBXA2R, PRKAR2A, PTK2, PGF and MYO10 are among the genes that belong to modules 1 and 22. All these genes, being implicated in at least one of the phenomena, namely cell survival, proliferation and metastasis, have an over-expression pattern similar to that of EGFR. In few modules, the genes such as CCNA2 (Cyclin A2), CCNB2 (Cyclin B2), CDK1, CDK5, CDC27, CDCA5, CDCA8, ASPM, BUB1, KIF15, KIF2C, NEK2, NUSAP1, PRC1, SMC4, SYCE2, TFDP1, CDC42 and ARHGEF9 are present that play a crucial role in cell cycle progression. In addition to the mentioned genes, there are some other genes (i.e. DLGAP5, BIRC5, PSMD2, Src, TTK, SENP2, PSMD2, DOK2, FUS and etc.) in the modules.

Analysis of bHLH coding genes using gene co-expression network approach.

PubMed

Srivastava, Swati; Sanchita; Singh, Garima; Singh, Noopur; Srivastava, Gaurava; Sharma, Ashok

2016-07-01

Network analysis provides a powerful framework for the interpretation of data. It uses novel reference network-based metrices for module evolution. These could be used to identify module of highly connected genes showing variation in co-expression network. In this study, a co-expression network-based approach was used for analyzing the genes from microarray data. Our approach consists of a simple but robust rank-based network construction. The publicly available gene expression data of Solanum tuberosum under cold and heat stresses were considered to create and analyze a gene co-expression network. The analysis provide highly co-expressed module of bHLH coding genes based on correlation values. Our approach was to analyze the variation of genes expression, according to the time period of stress through co-expression network approach. As the result, the seed genes were identified showing multiple connections with other genes in the same cluster. Seed genes were found to be vary in different time periods of stress. These analyzed seed genes may be utilized further as marker genes for developing the stress tolerant plant species.

Co-Option and De Novo Gene Evolution Underlie Molluscan Shell Diversity

PubMed Central

Aguilera, Felipe; McDougall, Carmel

2017-01-01

Abstract Molluscs fabricate shells of incredible diversity and complexity by localized secretions from the dorsal epithelium of the mantle. Although distantly related molluscs express remarkably different secreted gene products, it remains unclear if the evolution of shell structure and pattern is underpinned by the differential co-option of conserved genes or the integration of lineage-specific genes into the mantle regulatory program. To address this, we compare the mantle transcriptomes of 11 bivalves and gastropods of varying relatedness. We find that each species, including four Pinctada (pearl oyster) species that diverged within the last 20 Ma, expresses a unique mantle secretome. Lineage- or species-specific genes comprise a large proportion of each species’ mantle secretome. A majority of these secreted proteins have unique domain architectures that include repetitive, low complexity domains (RLCDs), which evolve rapidly, and have a proclivity to expand, contract and rearrange in the genome. There are also a large number of secretome genes expressed in the mantle that arose before the origin of gastropods and bivalves. Each species expresses a unique set of these more ancient genes consistent with their independent co-option into these mantle gene regulatory networks. From this analysis, we infer lineage-specific secretomes underlie shell diversity, and include both rapidly evolving RLCD-containing proteins, and the continual recruitment and loss of both ancient and recently evolved genes into the periphery of the regulatory network controlling gene expression in the mantle epithelium. PMID:28053006

A Normalization-Free and Nonparametric Method Sharpens Large-Scale Transcriptome Analysis and Reveals Common Gene Alteration Patterns in Cancers.

PubMed

Li, Qi-Gang; He, Yong-Han; Wu, Huan; Yang, Cui-Ping; Pu, Shao-Yan; Fan, Song-Qing; Jiang, Li-Ping; Shen, Qiu-Shuo; Wang, Xiao-Xiong; Chen, Xiao-Qiong; Yu, Qin; Li, Ying; Sun, Chang; Wang, Xiangting; Zhou, Jumin; Li, Hai-Peng; Chen, Yong-Bin; Kong, Qing-Peng

2017-01-01

Heterogeneity in transcriptional data hampers the identification of differentially expressed genes (DEGs) and understanding of cancer, essentially because current methods rely on cross-sample normalization and/or distribution assumption-both sensitive to heterogeneous values. Here, we developed a new method, Cross-Value Association Analysis (CVAA), which overcomes the limitation and is more robust to heterogeneous data than the other methods. Applying CVAA to a more complex pan-cancer dataset containing 5,540 transcriptomes discovered numerous new DEGs and many previously rarely explored pathways/processes; some of them were validated, both in vitro and in vivo , to be crucial in tumorigenesis, e.g., alcohol metabolism ( ADH1B ), chromosome remodeling ( NCAPH ) and complement system ( Adipsin ). Together, we present a sharper tool to navigate large-scale expression data and gain new mechanistic insights into tumorigenesis.

Blazing Signature Filter: a library for fast pairwise similarity comparisons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Joon-Yong; Fujimoto, Grant M.; Wilson, Ryan

Identifying similarities between datasets is a fundamental task in data mining and has become an integral part of modern scientific investigation. Whether the task is to identify co-expressed genes in large-scale expression surveys or to predict combinations of gene knockouts which would elicit a similar phenotype, the underlying computational task is often a multi-dimensional similarity test. As datasets continue to grow, improvements to the efficiency, sensitivity or specificity of such computation will have broad impacts as it allows scientists to more completely explore the wealth of scientific data. A significant practical drawback of large-scale data mining is the vast majoritymore » of pairwise comparisons are unlikely to be relevant, meaning that they do not share a signature of interest. It is therefore essential to efficiently identify these unproductive comparisons as rapidly as possible and exclude them from more time-intensive similarity calculations. The Blazing Signature Filter (BSF) is a highly efficient pairwise similarity algorithm which enables extensive data mining within a reasonable amount of time. The algorithm transforms datasets into binary metrics, allowing it to utilize the computationally efficient bit operators and provide a coarse measure of similarity. As a result, the BSF can scale to high dimensionality and rapidly filter unproductive pairwise comparison. Two bioinformatics applications of the tool are presented to demonstrate the ability to scale to billions of pairwise comparisons and the usefulness of this approach.« less

Automated recognition of cell phenotypes in histology images based on membrane- and nuclei-targeting biomarkers

PubMed Central

Karaçalı, Bilge; Vamvakidou, Alexandra P; Tözeren, Aydın

2007-01-01

Background Three-dimensional in vitro culture of cancer cells are used to predict the effects of prospective anti-cancer drugs in vivo. In this study, we present an automated image analysis protocol for detailed morphological protein marker profiling of tumoroid cross section images. Methods Histologic cross sections of breast tumoroids developed in co-culture suspensions of breast cancer cell lines, stained for E-cadherin and progesterone receptor, were digitized and pixels in these images were classified into five categories using k-means clustering. Automated segmentation was used to identify image regions composed of cells expressing a given biomarker. Synthesized images were created to check the accuracy of the image processing system. Results Accuracy of automated segmentation was over 95% in identifying regions of interest in synthesized images. Image analysis of adjacent histology slides stained, respectively, for Ecad and PR, accurately predicted regions of different cell phenotypes. Image analysis of tumoroid cross sections from different tumoroids obtained under the same co-culture conditions indicated the variation of cellular composition from one tumoroid to another. Variations in the compositions of cross sections obtained from the same tumoroid were established by parallel analysis of Ecad and PR-stained cross section images. Conclusion Proposed image analysis methods offer standardized high throughput profiling of molecular anatomy of tumoroids based on both membrane and nuclei markers that is suitable to rapid large scale investigations of anti-cancer compounds for drug development. PMID:17822559

Architectural Visualization of C/C++ Source Code for Program Comprehension

DOE Office of Scientific and Technical Information (OSTI.GOV)

Panas, T; Epperly, T W; Quinlan, D

2006-09-01

Structural and behavioral visualization of large-scale legacy systems to aid program comprehension is still a major challenge. The challenge is even greater when applications are implemented in flexible and expressive languages such as C and C++. In this paper, we consider visualization of static and dynamic aspects of large-scale scientific C/C++ applications. For our investigation, we reuse and integrate specialized analysis and visualization tools. Furthermore, we present a novel layout algorithm that permits a compressive architectural view of a large-scale software system. Our layout is unique in that it allows traditional program visualizations, i.e., graph structures, to be seen inmore » relation to the application's file structure.« less

An integrated approach to reconstructing genome-scale transcriptional regulatory networks

DOE PAGES

Imam, Saheed; Noguera, Daniel R.; Donohue, Timothy J.; ...

2015-02-27

Transcriptional regulatory networks (TRNs) program cells to dynamically alter their gene expression in response to changing internal or environmental conditions. In this study, we develop a novel workflow for generating large-scale TRN models that integrates comparative genomics data, global gene expression analyses, and intrinsic properties of transcription factors (TFs). An assessment of this workflow using benchmark datasets for the well-studied γ-proteobacterium Escherichia coli showed that it outperforms expression-based inference approaches, having a significantly larger area under the precision-recall curve. Further analysis indicated that this integrated workflow captures different aspects of the E. coli TRN than expression-based approaches, potentially making themmore » highly complementary. We leveraged this new workflow and observations to build a large-scale TRN model for the α-Proteobacterium Rhodobacter sphaeroides that comprises 120 gene clusters, 1211 genes (including 93 TFs), 1858 predicted protein-DNA interactions and 76 DNA binding motifs. We found that ~67% of the predicted gene clusters in this TRN are enriched for functions ranging from photosynthesis or central carbon metabolism to environmental stress responses. We also found that members of many of the predicted gene clusters were consistent with prior knowledge in R. sphaeroides and/or other bacteria. Experimental validation of predictions from this R. sphaeroides TRN model showed that high precision and recall was also obtained for TFs involved in photosynthesis (PpsR), carbon metabolism (RSP_0489) and iron homeostasis (RSP_3341). In addition, this integrative approach enabled generation of TRNs with increased information content relative to R. sphaeroides TRN models built via other approaches. We also show how this approach can be used to simultaneously produce TRN models for each related organism used in the comparative genomics analysis. Our results highlight the advantages of integrating comparative genomics of closely related organisms with gene expression data to assemble large-scale TRN models with high-quality predictions.« less

Statistical Model to Analyze Quantitative Proteomics Data Obtained by 18O/16O Labeling and Linear Ion Trap Mass Spectrometry

PubMed Central

Jorge, Inmaculada; Navarro, Pedro; Martínez-Acedo, Pablo; Núñez, Estefanía; Serrano, Horacio; Alfranca, Arántzazu; Redondo, Juan Miguel; Vázquez, Jesús

2009-01-01

Statistical models for the analysis of protein expression changes by stable isotope labeling are still poorly developed, particularly for data obtained by 16O/18O labeling. Besides large scale test experiments to validate the null hypothesis are lacking. Although the study of mechanisms underlying biological actions promoted by vascular endothelial growth factor (VEGF) on endothelial cells is of considerable interest, quantitative proteomics studies on this subject are scarce and have been performed after exposing cells to the factor for long periods of time. In this work we present the largest quantitative proteomics study to date on the short term effects of VEGF on human umbilical vein endothelial cells by 18O/16O labeling. Current statistical models based on normality and variance homogeneity were found unsuitable to describe the null hypothesis in a large scale test experiment performed on these cells, producing false expression changes. A random effects model was developed including four different sources of variance at the spectrum-fitting, scan, peptide, and protein levels. With the new model the number of outliers at scan and peptide levels was negligible in three large scale experiments, and only one false protein expression change was observed in the test experiment among more than 1000 proteins. The new model allowed the detection of significant protein expression changes upon VEGF stimulation for 4 and 8 h. The consistency of the changes observed at 4 h was confirmed by a replica at a smaller scale and further validated by Western blot analysis of some proteins. Most of the observed changes have not been described previously and are consistent with a pattern of protein expression that dynamically changes over time following the evolution of the angiogenic response. With this statistical model the 18O labeling approach emerges as a very promising and robust alternative to perform quantitative proteomics studies at a depth of several thousand proteins. PMID:19181660

Genomic Organization, Phylogenetic and Expression Analysis of the B-BOX Gene Family in Tomato

PubMed Central

Chu, Zhuannan; Wang, Xin; Li, Ying; Yu, Huiyang; Li, Jinhua; Lu, Yongen; Li, Hanxia; Ouyang, Bo

2016-01-01

The B-BOX (BBX) proteins encode a class of zinc-finger transcription factors possessing one or two B-BOX domains and in some cases an additional CCT (CO, CO-like and TOC1) motif, which play important roles in regulating plant growth, development and stress response. Nevertheless, no systematic study of BBX genes has undertaken in tomato (Solanum lycopersicum). Here we present the results of a genome-wide analysis of the 29 BBX genes in this important vegetable species. Their structures, conserved domains, phylogenetic relationships, subcellular localizations, and promoter cis-regulatory elements were analyzed; their tissue expression profiles and expression patterns under various hormones and stress treatments were also investigated in detail. Tomato BBX genes can be divided into five subfamilies, and twelve of them were found to be segmentally duplicated. Real-time quantitative PCR analysis showed that most BBX genes exhibited different temporal and spatial expression patterns. The expression of most BBX genes can be induced by drought, polyethylene glycol-6000 or heat stress. Some BBX genes were induced strongly by phytohormones such as abscisic acid, gibberellic acid, or ethephon. The majority of tomato BBX proteins was predicted to be located in nuclei, and the transient expression assay using Arabidopsis mesophyll protoplasts demonstrated that all the seven BBX members tested (SlBBX5, 7, 15, 17, 20, 22, and 24) were localized in nucleus. Our analysis of tomato BBX genes on the genome scale would provide valuable information for future functional characterization of specific genes in this family. PMID:27807440

Analysis of the fluctuations of the tumour/host interface

NASA Astrophysics Data System (ADS)

Milotti, Edoardo; Vyshemirsky, Vladislav; Stella, Sabrina; Dogo, Federico; Chignola, Roberto

2017-11-01

In a recent analysis of metabolic scaling in solid tumours we found a scaling law that interpolates between the power laws μ ∝ V and μ ∝V 2 / 3, where μ is the metabolic rate expressed as the glucose absorption rate and V is the tumour volume. The scaling law fits quite well both in vitro and in vivo data, however we also observed marked fluctuations that are associated with the specific biological properties of individual tumours. Here we analyse these fluctuations, in an attempt to find the population-wide distribution of an important parameter (A) which expresses the total extent of the interface between the solid tumour and the non-cancerous environment. Heuristic considerations suggest that the values of the A parameter follow a lognormal distribution, and, allowing for the large uncertainties of the experimental data, our statistical analysis confirms this.

Global Landscape of a Co-Expressed Gene Network in Barley and its Application to Gene Discovery in Triticeae Crops

PubMed Central

Mochida, Keiichi; Uehara-Yamaguchi, Yukiko; Yoshida, Takuhiro; Sakurai, Tetsuya; Shinozaki, Kazuo

2011-01-01

Accumulated transcriptome data can be used to investigate regulatory networks of genes involved in various biological systems. Co-expression analysis data sets generated from comprehensively collected transcriptome data sets now represent efficient resources that are capable of facilitating the discovery of genes with closely correlated expression patterns. In order to construct a co-expression network for barley, we analyzed 45 publicly available experimental series, which are composed of 1,347 sets of GeneChip data for barley. On the basis of a gene-to-gene weighted correlation coefficient, we constructed a global barley co-expression network and classified it into clusters of subnetwork modules. The resulting clusters are candidates for functional regulatory modules in the barley transcriptome. To annotate each of the modules, we performed comparative annotation using genes in Arabidopsis and Brachypodium distachyon. On the basis of a comparative analysis between barley and two model species, we investigated functional properties from the representative distributions of the gene ontology (GO) terms. Modules putatively involved in drought stress response and cellulose biogenesis have been identified. These modules are discussed to demonstrate the effectiveness of the co-expression analysis. Furthermore, we applied the data set of co-expressed genes coupled with comparative analysis in attempts to discover potentially Triticeae-specific network modules. These results demonstrate that analysis of the co-expression network of the barley transcriptome together with comparative analysis should promote the process of gene discovery in barley. Furthermore, the insights obtained should be transferable to investigations of Triticeae plants. The associated data set generated in this analysis is publicly accessible at http://coexpression.psc.riken.jp/barley/. PMID:21441235

Cloud-Scale Genomic Signals Processing for Robust Large-Scale Cancer Genomic Microarray Data Analysis.

PubMed

Harvey, Benjamin Simeon; Ji, Soo-Yeon

2017-01-01

As microarray data available to scientists continues to increase in size and complexity, it has become overwhelmingly important to find multiple ways to bring forth oncological inference to the bioinformatics community through the analysis of large-scale cancer genomic (LSCG) DNA and mRNA microarray data that is useful to scientists. Though there have been many attempts to elucidate the issue of bringing forth biological interpretation by means of wavelet preprocessing and classification, there has not been a research effort that focuses on a cloud-scale distributed parallel (CSDP) separable 1-D wavelet decomposition technique for denoising through differential expression thresholding and classification of LSCG microarray data. This research presents a novel methodology that utilizes a CSDP separable 1-D method for wavelet-based transformation in order to initialize a threshold which will retain significantly expressed genes through the denoising process for robust classification of cancer patients. Additionally, the overall study was implemented and encompassed within CSDP environment. The utilization of cloud computing and wavelet-based thresholding for denoising was used for the classification of samples within the Global Cancer Map, Cancer Cell Line Encyclopedia, and The Cancer Genome Atlas. The results proved that separable 1-D parallel distributed wavelet denoising in the cloud and differential expression thresholding increased the computational performance and enabled the generation of higher quality LSCG microarray datasets, which led to more accurate classification results.

Profiling and Co-expression Network Analysis of Learned Helplessness Regulated mRNAs and lncRNAs in the Mouse Hippocampus

PubMed Central

Li, Chaoqun; Cao, Feifei; Li, Shengli; Huang, Shenglin; Li, Wei; Abumaria, Nashat

2018-01-01

Although studies provide insights into the neurobiology of stress and depression, the exact molecular mechanisms underlying their pathologies remain largely unknown. Long non-coding RNA (lncRNA) has been implicated in brain functions and behavior. A potential link between lncRNA and psychiatric disorders has been proposed. However, it remains undetermined whether IncRNA regulation, in the brain, contributes to stress or depression pathologies. In this study, we used a valid animal model of depression-like symptoms; namely learned helplessness, RNA-seq, Gene Ontology and co-expression network analyses to profile the expression pattern of lncRNA and mRNA in the hippocampus of mice. We identified 6346 differentially expressed transcripts. Among them, 340 lncRNAs and 3559 protein coding mRNAs were differentially expressed in helpless mice in comparison with control and/or non-helpless mice (inescapable stress resilient mice). Gene Ontology and pathway enrichment analyses indicated that induction of helplessness altered expression of mRNAs enriched in fundamental biological functions implicated in stress/depression neurobiology such as synaptic, metabolic, cell survival and proliferation, developmental and chromatin modification functions. To explore the possible regulatory roles of the altered lncRNAs, we constructed co-expression networks composed of the lncRNAs and mRNAs. Among our differentially expressed lncRNAs, 17% showed significant correlation with genes. Functional co-expression analysis linked the identified lncRNAs to several cellular mechanisms implicated in stress/depression neurobiology. Importantly, 57% of the identified regulatory lncRNAs significantly correlated with 18 different synapse-related functions. Thus, the current study identifies for the first time distinct groups of lncRNAs regulated by induction of learned helplessness in the mouse brain. Our results suggest that lncRNA-directed regulatory mechanisms might contribute to stress-induced pathologies; in particular, to inescapable stress-induced synaptic modifications. PMID:29375311

Profiling and Co-expression Network Analysis of Learned Helplessness Regulated mRNAs and lncRNAs in the Mouse Hippocampus.

PubMed

Li, Chaoqun; Cao, Feifei; Li, Shengli; Huang, Shenglin; Li, Wei; Abumaria, Nashat

2017-01-01

Although studies provide insights into the neurobiology of stress and depression, the exact molecular mechanisms underlying their pathologies remain largely unknown. Long non-coding RNA (lncRNA) has been implicated in brain functions and behavior. A potential link between lncRNA and psychiatric disorders has been proposed. However, it remains undetermined whether IncRNA regulation, in the brain, contributes to stress or depression pathologies. In this study, we used a valid animal model of depression-like symptoms; namely learned helplessness, RNA-seq, Gene Ontology and co-expression network analyses to profile the expression pattern of lncRNA and mRNA in the hippocampus of mice. We identified 6346 differentially expressed transcripts. Among them, 340 lncRNAs and 3559 protein coding mRNAs were differentially expressed in helpless mice in comparison with control and/or non-helpless mice (inescapable stress resilient mice). Gene Ontology and pathway enrichment analyses indicated that induction of helplessness altered expression of mRNAs enriched in fundamental biological functions implicated in stress/depression neurobiology such as synaptic, metabolic, cell survival and proliferation, developmental and chromatin modification functions. To explore the possible regulatory roles of the altered lncRNAs, we constructed co-expression networks composed of the lncRNAs and mRNAs. Among our differentially expressed lncRNAs, 17% showed significant correlation with genes. Functional co-expression analysis linked the identified lncRNAs to several cellular mechanisms implicated in stress/depression neurobiology. Importantly, 57% of the identified regulatory lncRNAs significantly correlated with 18 different synapse-related functions. Thus, the current study identifies for the first time distinct groups of lncRNAs regulated by induction of learned helplessness in the mouse brain. Our results suggest that lncRNA-directed regulatory mechanisms might contribute to stress-induced pathologies; in particular, to inescapable stress-induced synaptic modifications.

ALMA IMAGING OF THE CO (6-5) LINE EMISSION IN NGC 7130

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Yinghe; Lu, Nanyao; Xu, C. Kevin

2016-04-01

In this paper, we report our high-resolution (0.″20 × 0.″14 or ∼70 × 49 pc) observations of the CO(6-5) line emission, which probes warm and dense molecular gas, and the 434 μm dust continuum in the nuclear region of NGC 7130, obtained with the Atacama Large Millimeter Array (ALMA). The CO line and dust continuum fluxes detected in our ALMA observations are 1230 ± 74 Jy km s{sup −1} and 814 ± 52 mJy, respectively, which account for 100% and 51% of their total fluxes. We find that the CO(6-5) and dust emissions are generally spatially correlated, but their brightest peaks show an offset of ∼70 pc, suggestingmore » that the gas and dust emissions may start decoupling at this physical scale. The brightest peak of the CO(6-5) emission does not spatially correspond to the radio continuum peak, which is likely dominated by an active galactic nucleus (AGN). This, together with our additional quantitative analysis, suggests that the heating contribution of the AGN to the CO(6-5) emission in NGC 7130 is negligible. The CO(6-5) and the extinction-corrected Pa-α maps display striking differences, suggestive of either a breakdown of the correlation between warm dense gas and star formation at linear scales of <100 pc or a large uncertainty in our extinction correction to the observed Pa-α image. Over a larger scale of ∼2.1 kpc, the double-lobed structure found in the CO(6-5) emission agrees well with the dust lanes in the optical/near-infrared images.« less

Analysis of large-scale gene expression data.

PubMed

Sherlock, G

2000-04-01

The advent of cDNA and oligonucleotide microarray technologies has led to a paradigm shift in biological investigation, such that the bottleneck in research is shifting from data generation to data analysis. Hierarchical clustering, divisive clustering, self-organizing maps and k-means clustering have all been recently used to make sense of this mass of data.

Integrating genome-wide association studies and gene expression data highlights dysregulated multiple sclerosis risk pathways.

PubMed

Liu, Guiyou; Zhang, Fang; Jiang, Yongshuai; Hu, Yang; Gong, Zhongying; Liu, Shoufeng; Chen, Xiuju; Jiang, Qinghua; Hao, Junwei

2017-02-01

Much effort has been expended on identifying the genetic determinants of multiple sclerosis (MS). Existing large-scale genome-wide association study (GWAS) datasets provide strong support for using pathway and network-based analysis methods to investigate the mechanisms underlying MS. However, no shared genetic pathways have been identified to date. We hypothesize that shared genetic pathways may indeed exist in different MS-GWAS datasets. Here, we report results from a three-stage analysis of GWAS and expression datasets. In stage 1, we conducted multiple pathway analyses of two MS-GWAS datasets. In stage 2, we performed a candidate pathway analysis of the large-scale MS-GWAS dataset. In stage 3, we performed a pathway analysis using the dysregulated MS gene list from seven human MS case-control expression datasets. In stage 1, we identified 15 shared pathways. In stage 2, we successfully replicated 14 of these 15 significant pathways. In stage 3, we found that dysregulated MS genes were significantly enriched in 10 of 15 MS risk pathways identified in stages 1 and 2. We report shared genetic pathways in different MS-GWAS datasets and highlight some new MS risk pathways. Our findings provide new insights on the genetic determinants of MS.

ALMA Reveals Molecular Cloud N55 in the Large Magellanic Cloud as a Site of Massive Star Formation

NASA Astrophysics Data System (ADS)

Naslim, N.; Tokuda, K.; Onishi, T.; Kemper, F.; Wong, T.; Morata, O.; Takada, S.; Harada, R.; Kawamura, A.; Saigo, K.; Indebetouw, R.; Madden, S. C.; Hony, S.; Meixner, M.

2018-02-01

We present the molecular cloud properties of N55 in the Large Magellanic Cloud using 12CO(1–0) and 13CO(1–0) observations obtained with Atacama Large Millimeter Array. We have done a detailed study of molecular gas properties, to understand how the cloud properties of N55 differ from Galactic clouds. Most CO emission appears clumpy in N55, and molecular cores that have young stellar objects (YSOs) show larger linewidths and masses. The massive clumps are associated with high and intermediate mass YSOs. The clump masses are determined by local thermodynamic equilibrium and virial analysis of the 12CO and 13CO emissions. These mass estimates lead to the conclusion that (a) the clumps are in self-gravitational virial equilibrium, and (b) the 12CO(1–0)-to-H2 conversion factor, {X}{CO}, is 6.5 × 1020 cm‑2 (K km s‑1)‑1. This CO-to-H2 conversion factor for N55 clumps is measured at a spatial scale of ∼0.67 pc, which is about two times higher than the {X}{CO} value of the Orion cloud at a similar spatial scale. The core mass function of N55 clearly show a turnover below 200 {M}ȯ , separating the low-mass end from the high-mass end. The low-mass end of the 12CO mass spectrum is fitted with a power law of index 0.5 ± 0.1, while for 13CO it is fitted with a power law index 0.6 ± 0.2. In the high-mass end, the core mass spectrum is fitted with a power index of 2.0 ± 0.3 for 12CO, and with 2.5 ± 0.4 for 13CO. This power law behavior of the core mass function in N55 is consistent with many Galactic clouds.

Downregulation of acetyl-CoA synthetase 2 is a metabolic hallmark of tumor progression and aggressiveness in colorectal carcinoma.

PubMed

Bae, Jeong Mo; Kim, Jung Ho; Oh, Hyeon Jeong; Park, Hye Eun; Lee, Tae Hun; Cho, Nam-Yun; Kang, Gyeong Hoon

2017-02-01

Acetyl-CoA synthetase-2 is an emerging key enzyme for cancer metabolism, which supplies acetyl-CoA for tumor cells by capturing acetate as a carbon source under stressed conditions. However, implications of acetyl-CoA synthetase-2 in colorectal carcinoma may differ from other malignancies, because normal colonocytes use short-chain fatty acids as an energy source, which are supplied by fermentation of the intestinal flora. Here we analyzed acetyl-CoA synthetase-2 mRNA expression by reverse-transcription quantitative PCR in paired normal mucosa and tumor tissues of 12 colorectal carcinomas, and subsequently evaluated acetyl-CoA synthetase-2 protein expression by immunohistochemistry in 157 premalignant colorectal lesions, including 60 conventional adenomas and 97 serrated polyps, 1,106 surgically resected primary colorectal carcinomas, and 23 metastatic colorectal carcinomas in the liver. In reverse-transcription quantitative PCR analysis, acetyl-CoA synthetase-2 mRNA expression was significantly decreased in tumor tissues compared with corresponding normal mucosa tissues. In acetyl-CoA synthetase-2 immunohistochemistry analysis, all 157 colorectal polyps showed moderate-to-strong expression of acetyl-CoA synthetase-2. However, cytoplasmic acetyl-CoA synthetase-2 expression was downregulated (acetyl-CoA synthetase-2 low expression) in 771 (69.7%) of 1,106 colorectal carcinomas and 21 (91.3%) of 23 metastatic lesions. The colorectal carcinomas with acetyl-CoA synthetase-2-low expression were significantly associated with advanced TNM stage, poor differentiation, and frequent tumor budding. Regarding the molecular aspect, acetyl-CoA synthetase-2-low expression exhibited a tendency of frequent KRT7 expression and decreased KRT20 and CDX2 expression. In survival analysis, acetyl-CoA synthetase-2-low expression was an independent prognostic factor for poor 5-year progression-free survival (hazard ratio, 1.39; 95% confidence interval, 1.08-1.79; P=0.01). In conclusion, these findings suggest that downregulation of acetyl-CoA synthetase-2 expression is a metabolic hallmark of tumor progression and aggressive behavior in colorectal carcinoma.

Mechanisms of glacial-to-future atmospheric CO2 effects on plant immunity.

PubMed

Williams, Alex; Pétriacq, Pierre; Schwarzenbacher, Roland E; Beerling, David J; Ton, Jurriaan

2018-04-01

The impacts of rising atmospheric CO 2 concentrations on plant disease have received increasing attention, but with little consensus emerging on the direct mechanisms by which CO 2 shapes plant immunity. Furthermore, the impact of sub-ambient CO 2 concentrations, which plants have experienced repeatedly over the past 800 000 yr, has been largely overlooked. A combination of gene expression analysis, phenotypic characterisation of mutants and mass spectrometry-based metabolic profiling was used to determine development-independent effects of sub-ambient CO 2 (saCO 2 ) and elevated CO 2 (eCO 2 ) on Arabidopsis immunity. Resistance to the necrotrophic Plectosphaerella cucumerina (Pc) was repressed at saCO 2 and enhanced at eCO 2 . This CO 2 -dependent resistance was associated with priming of jasmonic acid (JA)-dependent gene expression and required intact JA biosynthesis and signalling. Resistance to the biotrophic oomycete Hyaloperonospora arabidopsidis (Hpa) increased at both eCO 2 and saCO 2 . Although eCO 2 primed salicylic acid (SA)-dependent gene expression, mutations affecting SA signalling only partially suppressed Hpa resistance at eCO 2 , suggesting additional mechanisms are involved. Induced production of intracellular reactive oxygen species (ROS) at saCO 2 corresponded to a loss of resistance in glycolate oxidase mutants and increased transcription of the peroxisomal catalase gene CAT2, unveiling a mechanism by which photorespiration-derived ROS determined Hpa resistance at saCO 2 . By separating indirect developmental impacts from direct immunological effects, we uncover distinct mechanisms by which CO 2 shapes plant immunity and discuss their evolutionary significance. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

Using radiocarbon to investigate soil respiration impacts on atmospheric CO2

NASA Astrophysics Data System (ADS)

Phillips, C. L.; LaFranchi, B. W.; McFarlane, K. J.; Desai, A. R.

2013-12-01

While soil respiration is believed to represent the largest single source of CO2 emissions on a global scale, there are few tools available to measure soil emissions at large spatial scales. We investigated whether radiocarbon (14C) abundance in CO2 could be used to detect and characterize soil emissions in the atmosphere, taking advantage of the fact that 14C abundance in soil carbon is elevated compared to the background atmosphere, a result of thermonuclear weapons testing during the mid-20th Century (i.e. bomb-C). Working in a temperate hardwood forest in Northern Wisconsin during 2011-12, we made semi-high-frequency measurements of CO2 at nested spatial scales from the soil subsurface to 150 m above ground level. These measurements were used to investigate seasonal patterns in respired C sources, and to evaluate whether variability in soil-respired Δ14C could also be detected in atmospheric measurements. In our ground-level measurements we found large seasonal variation in soil-respired 14CO2 that correlated with soil moisture, which was likely related to root activity. Atmospheric measurements of 14CO2 in the forest canopy (2 to 30m) were used to construct Keeling plots, and these provided larger spatial-scale estimates of respired 14CO2 that largely agreed with the soil-level measurements. In collaboration with the NOAA we also examined temporal patterns of 14CO2 at the Park Falls tall-tower (150m), and found elevated 14CO2 levels during summer months that likely resulted from increased respiration from heterotrophic sources. These results demonstrate that a fingerprint from soil-respired CO2 can be detected in the seasonal patterns of atmospheric 14CO2, even at a regionally-integrating spatial scale far from the soil surface.

Molecular clouds and the large-scale structure of the galaxy

NASA Technical Reports Server (NTRS)

Thaddeus, Patrick; Stacy, J. Gregory

1990-01-01

The application of molecular radio astronomy to the study of the large-scale structure of the Galaxy is reviewed and the distribution and characteristic properties of the Galactic population of Giant Molecular Clouds (GMCs), derived primarily from analysis of the Columbia CO survey, and their relation to tracers of Population 1 and major spiral features are described. The properties of the local molecular interstellar gas are summarized. The CO observing programs currently underway with the Center for Astrophysics 1.2 m radio telescope are described, with an emphasis on projects relevant to future comparison with high-energy gamma-ray observations. Several areas are discussed in which high-energy gamma-ray observations by the EGRET (Energetic Gamma-Ray Experiment Telescope) experiment aboard the Gamma Ray Observatory will directly complement radio studies of the Milky Way, with the prospect of significant progress on fundamental issues related to the structure and content of the Galaxy.

Constraining the effects of permeability uncertainty for geologic CO2 sequestration in a basalt reservoir

NASA Astrophysics Data System (ADS)

Jayne, R., Jr.; Pollyea, R.

2016-12-01

Carbon capture and sequestration (CCS) in geologic reservoirs is one strategy for reducing anthropogenic CO2 emissions from large-scale point-source emitters. Recent developments at the CarbFix CCS pilot in Iceland have shown that basalt reservoirs are highly effective for permanent mineral trapping on the basis of CO2-water-rock interactions, which result in the formation of carbonates minerals. In order to advance our understanding of basalt sequestration in large igneous provinces, this research uses numerical simulation to evaluate the feasibility of industrial-scale CO2 injections in the Columbia River Basalt Group (CRBG). Although bulk reservoir properties are well constrained on the basis of field and laboratory testing from the Wallula Basalt Sequestration Pilot Project, there remains significant uncertainty in the spatial distribution of permeability at the scale of individual basalt flows. Geostatistical analysis of hydrologic data from 540 wells illustrates that CRBG reservoirs are reasonably modeled as layered heterogeneous systems on the basis of basalt flow morphology; however, the regional dataset is insufficient to constrain permeability variability at the scale of an individual basalt flow. As a result, permeability distribution for this modeling study is established by centering the lognormal permeability distribution in the regional dataset over the bulk permeability measured at Wallula site, which results in a spatially random permeability distribution within the target reservoir. In order to quantify the effects of this permeability uncertainty, CO2 injections are simulated within 50 equally probable synthetic reservoir domains. Each model domain comprises three-dimensional geometry with 530,000 grid blocks, and fracture-matrix interaction is simulated as interacting continua for the two low permeability layers (flow interiors) bounding the injection zone. Results from this research illustrate that permeability uncertainty at the scale of individual basalt flows may significantly impact both injection pressure accumulation and CO2 distribution.

CoNekT: an open-source framework for comparative genomic and transcriptomic network analyses.

PubMed

Proost, Sebastian; Mutwil, Marek

2018-05-01

The recent accumulation of gene expression data in the form of RNA sequencing creates unprecedented opportunities to study gene regulation and function. Furthermore, comparative analysis of the expression data from multiple species can elucidate which functional gene modules are conserved across species, allowing the study of the evolution of these modules. However, performing such comparative analyses on raw data is not feasible for many biologists. Here, we present CoNekT (Co-expression Network Toolkit), an open source web server, that contains user-friendly tools and interactive visualizations for comparative analyses of gene expression data and co-expression networks. These tools allow analysis and cross-species comparison of (i) gene expression profiles; (ii) co-expression networks; (iii) co-expressed clusters involved in specific biological processes; (iv) tissue-specific gene expression; and (v) expression profiles of gene families. To demonstrate these features, we constructed CoNekT-Plants for green alga, seed plants and flowering plants (Picea abies, Chlamydomonas reinhardtii, Vitis vinifera, Arabidopsis thaliana, Oryza sativa, Zea mays and Solanum lycopersicum) and thus provide a web-tool with the broadest available collection of plant phyla. CoNekT-Plants is freely available from http://conekt.plant.tools, while the CoNekT source code and documentation can be found at https://github.molgen.mpg.de/proost/CoNekT/.

Hypothyroidism leads to increased collagen-based stiffness and re-expression of large cardiac titin isoforms with high compliance.

PubMed

Wu, Yiming; Peng, Jun; Campbell, Kenneth B; Labeit, Siegfried; Granzier, Henk

2007-01-01

Because long-term hypothyroidism results in diastolic dysfunction, we investigated myocardial passive stiffness in hypothyroidism and focused on the possible role of titin, an important determinant of diastolic stiffness. A rat model of hypothyroidism was used, obtained by administering propylthiouracil (PTU) for times that varied from 1 month (short-term) to 4 months (long-term). Titin expression was determined by transcript analysis, gel electrophoresis and immunoelectron microscopy. Diastolic function was measured at the isolated heart, skinned muscle, and cardiac myocyte levels. We found that hypothyroidism resulted in expression of a large titin isoform, the abundance of which gradually increased with time to become the most dominant isoform in long-term hypothyroid rats. This isoform co-migrates on high-resolution gels with fetal cardiac titin. Transcript analysis on myocardium of long-term PTU rats, provided evidence for expression of additional PEVK and Ig domain exons, similar to what has been described in fetal myocardium. Consistent with the expression of a large titin isoform, titin-based restoring and passive forces were significantly reduced in single cardiac myocytes and muscle strips of long-term hypothyroid rats. Overall muscle stiffness and LV diastolic wall stiffness were increased, however, due to increased collagen-based stiffness. We conclude that long term hypothyroidism triggers expression of a large cardiac titin isoform and that the ensuing reduction in titin-based passive stiffness functions as a compensatory mechanism to reduce LV wall stiffness.

Transcriptomic profiles of Clostridium ljungdahlii during lithotrophic growth with syngas or H 2 and CO 2 compared to organotrophic growth with fructose

DOE PAGES

Aklujkar, Muktak; Leang, Ching; Shrestha, Pravin M.; ...

2017-10-13

Clostridium ljungdahlii derives energy by lithotrophic and organotrophic acetogenesis. C. ljungdahlii was grown organotrophically with fructose and also lithotrophically, either with syngas - a gas mixture containing hydrogen (H 2), carbon dioxide (CO 2), and carbon monoxide (CO), or with H 2 and CO 2. Gene expression was compared quantitatively by microarrays using RNA extracted from all three conditions. Gene expression with fructose and with H 2/CO 2 was compared by RNA-Seq. Upregulated genes with both syngas and H 2/CO 2 (compared to fructose) point to the urea cycle, uptake and degradation of peptides and amino acids, response to sulfurmore » starvation, potentially NADPH-producing pathways involving (S)-malate and ornithine, quorum sensing, sporulation, and cell wall remodeling, suggesting a global and multicellular response to lithotrophic conditions. With syngas, the upregulated (R)-lactate dehydrogenase gene represents a route of electron transfer from ferredoxin to NAD. With H 2/CO 2, flavodoxin and histidine biosynthesis genes were upregulated. Downregulated genes corresponded to an intracytoplasmic microcompartment for disposal of methylglyoxal, a toxic byproduct of glycolysis, as 1-propanol. Several cytoplasmic and membrane-associated redox-active protein genes were differentially regulated. In conclusion, the transcriptomic profiles of C. ljungdahlii in lithotrophic and organotrophic growth modes indicate large-scale physiological and metabolic differences, observations that may guide biofuel and commodity chemical production with this species.« less

Transcriptomic profiles of Clostridium ljungdahlii during lithotrophic growth with syngas or H 2 and CO 2 compared to organotrophic growth with fructose

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aklujkar, Muktak; Leang, Ching; Shrestha, Pravin M.

Clostridium ljungdahlii derives energy by lithotrophic and organotrophic acetogenesis. C. ljungdahlii was grown organotrophically with fructose and also lithotrophically, either with syngas - a gas mixture containing hydrogen (H 2), carbon dioxide (CO 2), and carbon monoxide (CO), or with H 2 and CO 2. Gene expression was compared quantitatively by microarrays using RNA extracted from all three conditions. Gene expression with fructose and with H 2/CO 2 was compared by RNA-Seq. Upregulated genes with both syngas and H 2/CO 2 (compared to fructose) point to the urea cycle, uptake and degradation of peptides and amino acids, response to sulfurmore » starvation, potentially NADPH-producing pathways involving (S)-malate and ornithine, quorum sensing, sporulation, and cell wall remodeling, suggesting a global and multicellular response to lithotrophic conditions. With syngas, the upregulated (R)-lactate dehydrogenase gene represents a route of electron transfer from ferredoxin to NAD. With H 2/CO 2, flavodoxin and histidine biosynthesis genes were upregulated. Downregulated genes corresponded to an intracytoplasmic microcompartment for disposal of methylglyoxal, a toxic byproduct of glycolysis, as 1-propanol. Several cytoplasmic and membrane-associated redox-active protein genes were differentially regulated. In conclusion, the transcriptomic profiles of C. ljungdahlii in lithotrophic and organotrophic growth modes indicate large-scale physiological and metabolic differences, observations that may guide biofuel and commodity chemical production with this species.« less

Greenhouse gas exchange over grazed systems

NASA Astrophysics Data System (ADS)

Felber, R.; Ammann, C.; Neftel, A.

2012-04-01

Grasslands act as sinks and sources of greenhouse gases (GHG) and are, in conjunction with livestock production systems, responsible for a large share of GHG emissions. Whereas ecosystem scale flux measurements (eddy covariance) are commonly used to investigate CO2 exchange (and is becoming state-of-the-art for other GHGs, too), GHG emissions from agricultural animals are usually investigated on the scale of individual animals. Therefore eddy covariance technique has to be tested for combined systems (i.e. grazed systems). Our project investigates the ability of field scale flux measurements to reliably quantify the contribution of grazing dairy cows to the net exchange of CO2 and CH4. To quantify the contribution of the animals to the net flux the position, movement, and grazing/rumination activity of each cow are recorded. In combination with a detailed footprint analysis of the eddy covariance fluxes, the animal related CO2 and CH4 emissions are derived and compared to standard emission values derived from respiration chambers. The aim of the project is to test the assumption whether field scale CO2 flux measurements adequately include the respiration of grazing cows and to identify potential errors in ecosystem Greenhouse gas budgets.

Computational, Integrative, and Comparative Methods for the Elucidation of Genetic Coexpression Networks

DOE PAGES

Baldwin, Nicole E.; Chesler, Elissa J.; Kirov, Stefan; ...

2005-01-01

Gene expression microarray data can be used for the assembly of genetic coexpression network graphs. Using mRNA samples obtained from recombinant inbred Mus musculus strains, it is possible to integrate allelic variation with molecular and higher-order phenotypes. The depth of quantitative genetic analysis of microarray data can be vastly enhanced utilizing this mouse resource in combination with powerful computational algorithms, platforms, and data repositories. The resulting network graphs transect many levels of biological scale. This approach is illustrated with the extraction of cliques of putatively co-regulated genes and their annotation using gene ontology analysis and cis -regulatory element discovery. Themore » causal basis for co-regulation is detected through the use of quantitative trait locus mapping.« less

Large-scale gene expression profiling data for the model moss Physcomitrella patens aid understanding of developmental progression, culture and stress conditions.

PubMed

Hiss, Manuel; Laule, Oliver; Meskauskiene, Rasa M; Arif, Muhammad A; Decker, Eva L; Erxleben, Anika; Frank, Wolfgang; Hanke, Sebastian T; Lang, Daniel; Martin, Anja; Neu, Christina; Reski, Ralf; Richardt, Sandra; Schallenberg-Rüdinger, Mareike; Szövényi, Peter; Tiko, Theodhor; Wiedemann, Gertrud; Wolf, Luise; Zimmermann, Philip; Rensing, Stefan A

2014-08-01

The moss Physcomitrella patens is an important model organism for studying plant evolution, development, physiology and biotechnology. Here we have generated microarray gene expression data covering the principal developmental stages, culture forms and some environmental/stress conditions. Example analyses of developmental stages and growth conditions as well as abiotic stress treatments demonstrate that (i) growth stage is dominant over culture conditions, (ii) liquid culture is not stressful for the plant, (iii) low pH might aid protoplastation by reduced expression of cell wall structure genes, (iv) largely the same gene pool mediates response to dehydration and rehydration, and (v) AP2/EREBP transcription factors play important roles in stress response reactions. With regard to the AP2 gene family, phylogenetic analysis and comparison with Arabidopsis thaliana shows commonalities as well as uniquely expressed family members under drought, light perturbations and protoplastation. Gene expression profiles for P. patens are available for the scientific community via the easy-to-use tool at https://www.genevestigator.com. By providing large-scale expression profiles, the usability of this model organism is further enhanced, for example by enabling selection of control genes for quantitative real-time PCR. Now, gene expression levels across a broad range of conditions can be accessed online for P. patens. © 2014 The Authors The Plant Journal © 2014 John Wiley & Sons Ltd.

Small Antisense RNA RblR Positively Regulates RuBisCo in Synechocystis sp. PCC 6803.

PubMed

Hu, Jinlu; Li, Tianpei; Xu, Wen; Zhan, Jiao; Chen, Hui; He, Chenliu; Wang, Qiang

2017-01-01

Small regulatory RNAs (sRNAs) function as transcriptional and post-transcriptional regulators of gene expression in organisms from all domains of life. Cyanobacteria are thought to have developed a complex RNA-based regulatory mechanism. In the current study, by genome-wide analysis of differentially expressed small RNAs in Synechocystis sp. PCC 6803 under high light conditions, we discovered an asRNA (RblR) that is 113nt in length and completely complementary to its target gene rbcL , which encodes the large chain of RuBisCO, the enzyme that catalyzes carbon fixation. Further analysis of the RblR(+)/(-) mutants revealed that RblR acts as a positive regulator of rbcL under various stress conditions; Suppressing RblR adversely affects carbon assimilation and thus the yield, and those phenotypes of both the wild type and the overexpressor could be downgraded to the suppressor level by carbonate depletion, indicated a regulatory role of RblR in CO 2 assimilation. In addition, a real-time expression platform in Escherichia coli was setup and which confirmed that RblR promoted the translation of the rbcL mRNA into the RbcL protein. The present study is the first report of a regulatory RNA that targets RbcL in Synechocystis sp. PCC 6803, and provides strong evidence that RblR regulates photosynthesis by positively modulating rbcL expression in Synechocystis .

Small Antisense RNA RblR Positively Regulates RuBisCo in Synechocystis sp. PCC 6803

PubMed Central

Hu, Jinlu; Li, Tianpei; Xu, Wen; Zhan, Jiao; Chen, Hui; He, Chenliu; Wang, Qiang

2017-01-01

Small regulatory RNAs (sRNAs) function as transcriptional and post-transcriptional regulators of gene expression in organisms from all domains of life. Cyanobacteria are thought to have developed a complex RNA-based regulatory mechanism. In the current study, by genome-wide analysis of differentially expressed small RNAs in Synechocystis sp. PCC 6803 under high light conditions, we discovered an asRNA (RblR) that is 113nt in length and completely complementary to its target gene rbcL, which encodes the large chain of RuBisCO, the enzyme that catalyzes carbon fixation. Further analysis of the RblR(+)/(−) mutants revealed that RblR acts as a positive regulator of rbcL under various stress conditions; Suppressing RblR adversely affects carbon assimilation and thus the yield, and those phenotypes of both the wild type and the overexpressor could be downgraded to the suppressor level by carbonate depletion, indicated a regulatory role of RblR in CO2 assimilation. In addition, a real-time expression platform in Escherichia coli was setup and which confirmed that RblR promoted the translation of the rbcL mRNA into the RbcL protein. The present study is the first report of a regulatory RNA that targets RbcL in Synechocystis sp. PCC 6803, and provides strong evidence that RblR regulates photosynthesis by positively modulating rbcL expression in Synechocystis. PMID:28261186

Scale-space measures for graph topology link protein network architecture to function.

PubMed

Hulsman, Marc; Dimitrakopoulos, Christos; de Ridder, Jeroen

2014-06-15

The network architecture of physical protein interactions is an important determinant for the molecular functions that are carried out within each cell. To study this relation, the network architecture can be characterized by graph topological characteristics such as shortest paths and network hubs. These characteristics have an important shortcoming: they do not take into account that interactions occur across different scales. This is important because some cellular functions may involve a single direct protein interaction (small scale), whereas others require more and/or indirect interactions, such as protein complexes (medium scale) and interactions between large modules of proteins (large scale). In this work, we derive generalized scale-aware versions of known graph topological measures based on diffusion kernels. We apply these to characterize the topology of networks across all scales simultaneously, generating a so-called graph topological scale-space. The comprehensive physical interaction network in yeast is used to show that scale-space based measures consistently give superior performance when distinguishing protein functional categories and three major types of functional interactions-genetic interaction, co-expression and perturbation interactions. Moreover, we demonstrate that graph topological scale spaces capture biologically meaningful features that provide new insights into the link between function and protein network architecture. Matlab(TM) code to calculate the scale-aware topological measures (STMs) is available at http://bioinformatics.tudelft.nl/TSSA © The Author 2014. Published by Oxford University Press.

Efficient Production of Hydroxylated Human-Like Collagen Via the Co-Expression of Three Key Genes in Escherichia coli Origami (DE3).

PubMed

Tang, Yunping; Yang, Xiuliang; Hang, Baojian; Li, Jiangtao; Huang, Lei; Huang, Feng; Xu, Zhinan

2016-04-01

Mature collagen is abundant in human bodies and very valuable for a range of industrial and medical applications. The biosynthesis of mature collagen requires post-translational modifications to increase the stability of collagen triple helix structure. By co-expressing the human-like collagen (HLC) gene with human prolyl 4-hydroxylase (P4H) and D-arabinono-1, 4-lactone oxidase (ALO) in Escherichia coli, we have constructed a prokaryotic expression system to produce the hydroxylated HLC. Then, five different media, as well as the induction conditions were investigated with regard to the soluble expression of such protein. The results indicated that the highest soluble expression level of target HLC obtained in shaking flasks was 49.55 ± 0.36 mg/L, when recombinant cells were grew in MBL medium and induced by 0.1 mM IPTG at the middle stage of exponential growth phase. By adopting the glucose feeding strategy, the expression level of target HLC can be improved up to 260 mg/L in a 10 L bench-top fermentor. Further, HPLC analyses revealed that more than 10 % of proline residues in purified HLC were successfully hydroxylated. The present work has provided a solid base for the large-scale production of hydroxylated HLC in E. coli.

Transcriptome profiles link environmental variation and physiological response of Mytilus californianus between Pacific tides

PubMed Central

Place, Sean P.; Menge, Bruce A.; Hofmann, Gretchen E.

2011-01-01

Summary The marine intertidal zone is characterized by large variation in temperature, pH, dissolved oxygen and the supply of nutrients and food on seasonal and daily time scales. These oceanic fluctuations drive of ecological processes such as recruitment, competition and consumer-prey interactions largely via physiological mehcanisms. Thus, to understand coastal ecosystem dynamics and responses to climate change, it is crucial to understand these mechanisms. Here we utilize transcriptome analysis of the physiological response of the mussel Mytilus californianus at different spatial scales to gain insight into these mechanisms. We used mussels inhabiting different vertical locations within Strawberry Hill on Cape Perpetua, OR and Boiler Bay on Cape Foulweather, OR to study inter- and intra-site variation of gene expression. The results highlight two distinct gene expression signatures related to the cycling of metabolic activity and perturbations to cellular homeostasis. Intermediate spatial scales show a strong influence of oceanographic differences in food and stress environments between sites separated by ~65 km. Together, these new insights into environmental control of gene expression may allow understanding of important physiological drivers within and across populations. PMID:22563136

Optimal consistency in microRNA expression analysis using reference-gene-based normalization.

PubMed

Wang, Xi; Gardiner, Erin J; Cairns, Murray J

2015-05-01

Normalization of high-throughput molecular expression profiles secures differential expression analysis between samples of different phenotypes or biological conditions, and facilitates comparison between experimental batches. While the same general principles apply to microRNA (miRNA) normalization, there is mounting evidence that global shifts in their expression patterns occur in specific circumstances, which pose a challenge for normalizing miRNA expression data. As an alternative to global normalization, which has the propensity to flatten large trends, normalization against constitutively expressed reference genes presents an advantage through their relative independence. Here we investigated the performance of reference-gene-based (RGB) normalization for differential miRNA expression analysis of microarray expression data, and compared the results with other normalization methods, including: quantile, variance stabilization, robust spline, simple scaling, rank invariant, and Loess regression. The comparative analyses were executed using miRNA expression in tissue samples derived from subjects with schizophrenia and non-psychiatric controls. We proposed a consistency criterion for evaluating methods by examining the overlapping of differentially expressed miRNAs detected using different partitions of the whole data. Based on this criterion, we found that RGB normalization generally outperformed global normalization methods. Thus we recommend the application of RGB normalization for miRNA expression data sets, and believe that this will yield a more consistent and useful readout of differentially expressed miRNAs, particularly in biological conditions characterized by large shifts in miRNA expression.

Carbon Sequestration in Unconventional Reservoirs: Geophysical, Geochemical and Geomechanical Considerations

NASA Astrophysics Data System (ADS)

Zakharova, Natalia V.

In the face of the environmental challenges presented by the acceleration of global warming, carbon capture and storage, also called carbon sequestration, may provide a vital option to reduce anthropogenic carbon dioxide emissions, while meeting the world's energy demands. To operate on a global scale, carbon sequestration would require thousands of geologic repositories that could accommodate billions of tons of carbon dioxide per year. In order to reach such capacity, various types of geologic reservoirs should be considered, including unconventional reservoirs such as volcanic rocks, fractured formations, and moderate-permeability aquifers. Unconventional reservoirs, however, are characterized by complex pore structure, high heterogeneity, and intricate feedbacks between physical, chemical and mechanical processes, and their capacity to securely store carbon emissions needs to be confirmed. In this dissertation, I present my contribution toward the understanding of geophysical, geochemical, hydraulic, and geomechanical properties of continental basalts and fractured sedimentary formations in the context of their carbon storage capacity. The data come from two characterization projects, in the Columbia River Flood Basalt in Washington and the Newark Rift Basin in New York, funded by the U.S. Department of Energy through Big Sky Carbon Sequestration Partnerships and TriCarb Consortium for Carbon Sequestration. My work focuses on in situ analysis using borehole geophysical measurements that allow for detailed characterization of formation properties on the reservoir scale and under nearly unaltered subsurface conditions. The immobilization of injected CO2 by mineralization in basaltic rocks offers a critical advantage over sedimentary reservoirs for long-term CO2 storage. Continental flood basalts, such as the Columbia River Basalt Group, possess a suitable structure for CO2 storage, with extensive reservoirs in the interflow zones separated by massive impermeable basalt in flow interiors. Other large igneous provinces and ocean floor basalts could accommodate centuries' worth of world's CO2 emissions. Low-volume basaltic flows and fractured intrusives may potentially serve as smaller-scale CO2 storage targets. However, as illustrated by the example of the Palisade sill in the Newark basin, even densely fractured intrusive basalts are often impermeable, and instead may serve as caprock for underlying formations. Hydraulic properties of fractured formations are very site-specific, but observations and theory suggest that the majority of fractures at depth remain closed. Hydraulic tests in the northern Newark basin indicate that fractures introduce strong anisotropy and heterogeneity to the formation properties, and very few of them augment hydraulic conductivity of these fractured formations. Overall, they are unlikely to provide enough storage capacity for safe CO 2 injection at large scales, but can be suitable for small-scale controlled experiments and pilot injection tests. The risk of inducing earthquakes by underground injection has emerged as one of the primary concerns for large-scale carbon sequestration, especially in fractured and moderately permeable formations. Analysis of in situ stress and distribution of fractures in the subsurface are important steps for evaluating the risks of induced seismicity. Preliminary results from the Newark basin suggest that local stress perturbation may potentially create favorable stress conditions for CO2 sequestration by allowing a considerable pore pressure increase without carrying large risks of fault reactivation. Additional in situ stress data are needed, however, to accurately constrain the magnitude of the minimum horizontal stress, and it is recommended that such tests be conducted at all potential CO 2 storage sites.

Potential large scale production of meningococcal vaccines by stable overexpression of fHbp in the rice seeds.

PubMed

Ma, Jian; Wang, Yunpeng; Xu, Nuo; Jin, Libo; Liu, Jia; Xing, Shaochen; Li, Xiaokun

2018-06-25

Factor H binding protein (fHbp) is the most promising vaccine candidate against serogroup B of Neisseria meningitidis which is a major cause of morbidity and mortality in children. In order to facilitate large scale production of a commercial vaccine, we previously used transgenic Arabidopsis thaliana, but plant-derived fHbp is still far away from a commercial vaccine due to less biomass production. Herein, we presented an alternative route for the production of recombinant fHbp from the seeds of transgenic rice. The OsrfHbp gene encoding recombinant fHbp fused protein was introduced into the genome of rice via Agrobacterium-mediated transformation. The both stable integration and transcription of the foreign OsrfHbp were confirmed by Southern blotting and RT-PCR analysis respectively. Further, the expression of fHbp protein was measured by immunoblotting analysis and quantified by ELISA. The results indicated that fHbp was successfully expressed and the highest yield of fHbp was 0.52 ± 0.03% of TSP in the transgenic rice seeds. The purified fHbp protein showed good antigenicity and immunogenicity in the animal model. The results of this experiment offer a novel approach for large-scale production of plant-derived commercial vaccine fHbp. Copyright © 2018. Published by Elsevier Inc.

Employing conservation of co-expression to improve functional inference

PubMed Central

Daub, Carsten O; Sonnhammer, Erik LL

2008-01-01

Background Observing co-expression between genes suggests that they are functionally coupled. Co-expression of orthologous gene pairs across species may improve function prediction beyond the level achieved in a single species. Results We used orthology between genes of the three different species S. cerevisiae, D. melanogaster, and C. elegans to combine co-expression across two species at a time. This led to increased function prediction accuracy when we incorporated expression data from either of the other two species and even further increased when conservation across both of the two other species was considered at the same time. Employing the conservation across species to incorporate abundant model organism data for the prediction of protein interactions in poorly characterized species constitutes a very powerful annotation method. Conclusion To be able to employ the most suitable co-expression distance measure for our analysis, we evaluated the ability of four popular gene co-expression distance measures to detect biologically relevant interactions between pairs of genes. For the expression datasets employed in our co-expression conservation analysis above, we used the GO and the KEGG PATHWAY databases as gold standards. While the differences between distance measures were small, Spearman correlation showed to give most robust results. PMID:18808668

Analysis of host response to bacterial infection using error model based gene expression microarray experiments

PubMed Central

Stekel, Dov J.; Sarti, Donatella; Trevino, Victor; Zhang, Lihong; Salmon, Mike; Buckley, Chris D.; Stevens, Mark; Pallen, Mark J.; Penn, Charles; Falciani, Francesco

2005-01-01

A key step in the analysis of microarray data is the selection of genes that are differentially expressed. Ideally, such experiments should be properly replicated in order to infer both technical and biological variability, and the data should be subjected to rigorous hypothesis tests to identify the differentially expressed genes. However, in microarray experiments involving the analysis of very large numbers of biological samples, replication is not always practical. Therefore, there is a need for a method to select differentially expressed genes in a rational way from insufficiently replicated data. In this paper, we describe a simple method that uses bootstrapping to generate an error model from a replicated pilot study that can be used to identify differentially expressed genes in subsequent large-scale studies on the same platform, but in which there may be no replicated arrays. The method builds a stratified error model that includes array-to-array variability, feature-to-feature variability and the dependence of error on signal intensity. We apply this model to the characterization of the host response in a model of bacterial infection of human intestinal epithelial cells. We demonstrate the effectiveness of error model based microarray experiments and propose this as a general strategy for a microarray-based screening of large collections of biological samples. PMID:15800204

Jumpstarting commercial-scale CO 2 capture and storage with ethylene production and enhanced oil recovery in the US Gulf

DOE PAGES

Middleton, Richard S.; Levine, Jonathan S.; Bielicki, Jeffrey M.; ...

2015-04-27

CO 2 capture, utilization, and storage (CCUS) technology has yet to be widely deployed at a commercial scale despite multiple high-profile demonstration projects. We suggest that developing a large-scale, visible, and financially viable CCUS network could potentially overcome many barriers to deployment and jumpstart commercial-scale CCUS. To date, substantial effort has focused on technology development to reduce the costs of CO 2 capture from coal-fired power plants. Here, we propose that near-term investment could focus on implementing CO 2 capture on facilities that produce high-value chemicals/products. These facilities can absorb the expected impact of the marginal increase in the costmore » of production on the price of their product, due to the addition of CO 2 capture, more than coal-fired power plants. A financially viable demonstration of a large-scale CCUS network requires offsetting the costs of CO 2 capture by using the CO 2 as an input to the production of market-viable products. As a result, we demonstrate this alternative development path with the example of an integrated CCUS system where CO 2 is captured from ethylene producers and used for enhanced oil recovery in the U.S. Gulf Coast region.« less

T cell subtypes and reciprocal inflammatory mediator expression differentiate P. falciparum memory recall responses in asymptomatic and symptomatic malaria patients in southeastern Haiti

PubMed Central

Campo, Joseph J.; Cicéron, Micheline; Raccurt, Christian P.; Beau De Rochars, Valery E. M.

2017-01-01

Asymptomatic Plasmodium falciparum infection is responsible for maintaining malarial disease within human populations in low transmission countries such as Haiti. Investigating differential host immune responses to the parasite as a potential underlying mechanism could help provide insight into this highly complex phenomenon and possibly identify asymptomatic individuals. We performed a cross-sectional analysis of individuals who were diagnosed with malaria in Sud-Est, Haiti by comparing the cellular and humoral responses of both symptomatic and asymptomatic subjects. Plasma samples were analyzed with a P. falciparum protein microarray, which demonstrated serologic reactivity to 3,877 P. falciparum proteins of known serologic reactivity; however, no antigen-antibody reactions delineating asymptomatics from symptomatics were identified. In contrast, differences in cellular responses were observed. Flow cytometric analysis of patient peripheral blood mononuclear cells co-cultured with P. falciparum infected erythrocytes demonstrated a statistically significant increase in the proportion of T regulatory cells (CD4+ CD25+ CD127-), and increases in unique populations of both NKT-like cells (CD3+ CD8+ CD56+) and CD8mid T cells in asymptomatics compared to symptomatics. Also, CD38+/HLA-DR+ expression on γδ T cells, CD8mid (CD56-) T cells, and CD8mid CD56+ NKT-like cells decreased upon exposure to infected erythrocytes in both groups. Cytometric bead analysis of the co-culture supernatants demonstrated an upregulation of monocyte-activating chemokines/cytokines in asymptomatics, while immunomodulatory soluble factors were elevated in symptomatics. Principal component analysis of these expression values revealed a distinct clustering of individual responses within their respective phenotypic groups. This is the first comprehensive investigation of immune responses to P. falciparum in Haiti, and describes unique cell-mediated immune repertoires that delineate individuals into asymptomatic and symptomatic phenotypes. Future investigations using large scale biological data sets analyzing multiple components of adaptive immunity, could collectively define which cellular responses and molecular correlates of disease outcome are malaria region specific, and which are truly generalizable features of asymptomatic Plasmodium immunity, a research goal of critical priority. PMID:28369062

T cell subtypes and reciprocal inflammatory mediator expression differentiate P. falciparum memory recall responses in asymptomatic and symptomatic malaria patients in southeastern Haiti.

PubMed

Lehmann, Jason S; Campo, Joseph J; Cicéron, Micheline; Raccurt, Christian P; Boncy, Jacques; Beau De Rochars, Valery E M; Cannella, Anthony P

2017-01-01

Asymptomatic Plasmodium falciparum infection is responsible for maintaining malarial disease within human populations in low transmission countries such as Haiti. Investigating differential host immune responses to the parasite as a potential underlying mechanism could help provide insight into this highly complex phenomenon and possibly identify asymptomatic individuals. We performed a cross-sectional analysis of individuals who were diagnosed with malaria in Sud-Est, Haiti by comparing the cellular and humoral responses of both symptomatic and asymptomatic subjects. Plasma samples were analyzed with a P. falciparum protein microarray, which demonstrated serologic reactivity to 3,877 P. falciparum proteins of known serologic reactivity; however, no antigen-antibody reactions delineating asymptomatics from symptomatics were identified. In contrast, differences in cellular responses were observed. Flow cytometric analysis of patient peripheral blood mononuclear cells co-cultured with P. falciparum infected erythrocytes demonstrated a statistically significant increase in the proportion of T regulatory cells (CD4+ CD25+ CD127-), and increases in unique populations of both NKT-like cells (CD3+ CD8+ CD56+) and CD8mid T cells in asymptomatics compared to symptomatics. Also, CD38+/HLA-DR+ expression on γδ T cells, CD8mid (CD56-) T cells, and CD8mid CD56+ NKT-like cells decreased upon exposure to infected erythrocytes in both groups. Cytometric bead analysis of the co-culture supernatants demonstrated an upregulation of monocyte-activating chemokines/cytokines in asymptomatics, while immunomodulatory soluble factors were elevated in symptomatics. Principal component analysis of these expression values revealed a distinct clustering of individual responses within their respective phenotypic groups. This is the first comprehensive investigation of immune responses to P. falciparum in Haiti, and describes unique cell-mediated immune repertoires that delineate individuals into asymptomatic and symptomatic phenotypes. Future investigations using large scale biological data sets analyzing multiple components of adaptive immunity, could collectively define which cellular responses and molecular correlates of disease outcome are malaria region specific, and which are truly generalizable features of asymptomatic Plasmodium immunity, a research goal of critical priority.

Tumour-specific HMG-CoAR is an independent predictor of recurrence free survival in epithelial ovarian cancer.

PubMed

Brennan, Donal J; Brändstedt, Jenny; Rexhepaj, Elton; Foley, Michael; Pontén, Fredrik; Uhlén, Mathias; Gallagher, William M; O'Connor, Darran P; O'Herlihy, Colm; Jirstrom, Karin

2010-04-01

Our group previously reported that tumour-specific expression of the rate-limiting enzyme in the mevalonate pathway, 3-hydroxy-3-methylglutharyl-coenzyme A reductase (HMG-CoAR) is associated with more favourable tumour parameters and a good prognosis in breast cancer. In the present study, the prognostic value of HMG-CoAR expression was examined in tumours from a cohort of patients with primary epithelial ovarian cancer. HMG-CoAR expression was assessed using immunohistochemistry (IHC) on tissue microarrays (TMA) consisting of 76 ovarian cancer cases, analysed using automated algorithms to develop a quantitative scoring model. Kaplan Meier analysis and Cox proportional hazards modelling were used to estimate the risk of recurrence free survival (RFS). Seventy-two tumours were suitable for analysis. Cytoplasmic HMG-CoAR expression was present in 65% (n = 46) of tumours. No relationship was seen between HMG-CoAR and age, histological subtype, grade, disease stage, estrogen receptor or Ki-67 status. Patients with tumours expressing HMG-CoAR had a significantly prolonged RFS (p = 0.012). Multivariate Cox regression analysis revealed that HMG-CoAR expression was an independent predictor of improved RFS (RR = 0.49, 95% CI (0.25-0.93); p = 0.03) when adjusted for established prognostic factors such as residual disease, tumour stage and grade. HMG-CoAR expression is an independent predictor of prolonged RFS in primary ovarian cancer. As HMG-CoAR inhibitors, also known as statins, have demonstrated anti-neoplastic effects in vitro, further studies are required to evaluate HMG-CoAR expression as a surrogate marker of response to statin treatment, especially in conjunction with current chemotherapeutic regimens.

Tumour-specific HMG-CoAR is an independent predictor of recurrence free survival in epithelial ovarian cancer

PubMed Central

2010-01-01

Background Our group previously reported that tumour-specific expression of the rate-limiting enzyme in the mevalonate pathway, 3-hydroxy-3-methylglutharyl-coenzyme A reductase (HMG-CoAR) is associated with more favourable tumour parameters and a good prognosis in breast cancer. In the present study, the prognostic value of HMG-CoAR expression was examined in tumours from a cohort of patients with primary epithelial ovarian cancer. Methods HMG-CoAR expression was assessed using immunohistochemistry (IHC) on tissue microarrays (TMA) consisting of 76 ovarian cancer cases, analysed using automated algorithms to develop a quantitative scoring model. Kaplan Meier analysis and Cox proportional hazards modelling were used to estimate the risk of recurrence free survival (RFS). Results Seventy-two tumours were suitable for analysis. Cytoplasmic HMG-CoAR expression was present in 65% (n = 46) of tumours. No relationship was seen between HMG-CoAR and age, histological subtype, grade, disease stage, estrogen receptor or Ki-67 status. Patients with tumours expressing HMG-CoAR had a significantly prolonged RFS (p = 0.012). Multivariate Cox regression analysis revealed that HMG-CoAR expression was an independent predictor of improved RFS (RR = 0.49, 95% CI (0.25-0.93); p = 0.03) when adjusted for established prognostic factors such as residual disease, tumour stage and grade. Conclusion HMG-CoAR expression is an independent predictor of prolonged RFS in primary ovarian cancer. As HMG-CoAR inhibitors, also known as statins, have demonstrated anti-neoplastic effects in vitro, further studies are required to evaluate HMG-CoAR expression as a surrogate marker of response to statin treatment, especially in conjunction with current chemotherapeutic regimens. PMID:20359358

Identification of potential transcriptomic markers in developing pediatric sepsis: a weighted gene co-expression network analysis and a case-control validation study.

PubMed

Li, Yiping; Li, Yanhong; Bai, Zhenjiang; Pan, Jian; Wang, Jian; Fang, Fang

2017-12-13

Sepsis represents a complex disease with the dysregulated inflammatory response and high mortality rate. The goal of this study was to identify potential transcriptomic markers in developing pediatric sepsis by a co-expression module analysis of the transcriptomic dataset. Using the R software and Bioconductor packages, we performed a weighted gene co-expression network analysis to identify co-expression modules significantly associated with pediatric sepsis. Functional interpretation (gene ontology and pathway analysis) and enrichment analysis with known transcription factors and microRNAs of the identified candidate modules were then performed. In modules significantly associated with sepsis, the intramodular analysis was further performed and "hub genes" were identified and validated by quantitative real-time PCR (qPCR) in this study. 15 co-expression modules in total were detected, and four modules ("midnight blue", "cyan", "brown", and "tan") were most significantly associated with pediatric sepsis and suggested as potential sepsis-associated modules. Gene ontology analysis and pathway analysis revealed that these four modules strongly associated with immune response. Three of the four sepsis-associated modules were also enriched with known transcription factors (false discovery rate-adjusted P < 0.05). Hub genes were identified in each of the four modules. Four of the identified hub genes (MYB proto-oncogene like 1, killer cell lectin like receptor G1, stomatin, and membrane spanning 4-domains A4A) were further validated to be differentially expressed between septic children and controls by qPCR. Four pediatric sepsis-associated co-expression modules were identified in this study. qPCR results suggest that hub genes in these modules are potential transcriptomic markers for pediatric sepsis diagnosis. These results provide novel insights into the pathogenesis of pediatric sepsis and promote the generation of diagnostic gene sets.

Mesoderm Lineage 3D Tissue Constructs Are Produced at Large-Scale in a 3D Stem Cell Bioprocess.

PubMed

Cha, Jae Min; Mantalaris, Athanasios; Jung, Sunyoung; Ji, Yurim; Bang, Oh Young; Bae, Hojae

2017-09-01

Various studies have presented different approaches to direct pluripotent stem cell differentiation such as applying defined sets of exogenous biochemical signals and genetic/epigenetic modifications. Although differentiation to target lineages can be successfully regulated, such conventional methods are often complicated, laborious, and not cost-effective to be employed to the large-scale production of 3D stem cell-based tissue constructs. A 3D-culture platform that could realize the large-scale production of mesoderm lineage tissue constructs from embryonic stem cells (ESCs) is developed. ESCs are cultured using our previously established 3D-bioprocess platform which is amenable to mass-production of 3D ESC-based tissue constructs. Hepatocarcinoma cell line conditioned medium is introduced to the large-scale 3D culture to provide a specific biomolecular microenvironment to mimic in vivo mesoderm formation process. After 5 days of spontaneous differentiation period, the resulting 3D tissue constructs are composed of multipotent mesodermal progenitor cells verified by gene and molecular expression profiles. Subsequently the optimal time points to trigger terminal differentiation towards cardiomyogenesis or osteogenesis from the mesodermal tissue constructs is found. A simple and affordable 3D ESC-bioprocess that can reach the scalable production of mesoderm origin tissues with significantly improved correspondent tissue properties is demonstrated. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Integrative Analysis of Many Weighted Co-Expression Networks Using Tensor Computation

PubMed Central

Li, Wenyuan; Liu, Chun-Chi; Zhang, Tong; Li, Haifeng; Waterman, Michael S.; Zhou, Xianghong Jasmine

2011-01-01

The rapid accumulation of biological networks poses new challenges and calls for powerful integrative analysis tools. Most existing methods capable of simultaneously analyzing a large number of networks were primarily designed for unweighted networks, and cannot easily be extended to weighted networks. However, it is known that transforming weighted into unweighted networks by dichotomizing the edges of weighted networks with a threshold generally leads to information loss. We have developed a novel, tensor-based computational framework for mining recurrent heavy subgraphs in a large set of massive weighted networks. Specifically, we formulate the recurrent heavy subgraph identification problem as a heavy 3D subtensor discovery problem with sparse constraints. We describe an effective approach to solving this problem by designing a multi-stage, convex relaxation protocol, and a non-uniform edge sampling technique. We applied our method to 130 co-expression networks, and identified 11,394 recurrent heavy subgraphs, grouped into 2,810 families. We demonstrated that the identified subgraphs represent meaningful biological modules by validating against a large set of compiled biological knowledge bases. We also showed that the likelihood for a heavy subgraph to be meaningful increases significantly with its recurrence in multiple networks, highlighting the importance of the integrative approach to biological network analysis. Moreover, our approach based on weighted graphs detects many patterns that would be overlooked using unweighted graphs. In addition, we identified a large number of modules that occur predominately under specific phenotypes. This analysis resulted in a genome-wide mapping of gene network modules onto the phenome. Finally, by comparing module activities across many datasets, we discovered high-order dynamic cooperativeness in protein complex networks and transcriptional regulatory networks. PMID:21698123

Participatory design facilitates Person Centred Nursing in service improvement with older people: a secondary directed content analysis.

PubMed

Wolstenholme, Daniel; Ross, Helen; Cobb, Mark; Bowen, Simon

2017-05-01

To explore, using the example of a project working with older people in an outpatient setting in a large UK NHS Teaching hospital, how the constructs of Person Centred Nursing are reflected in interviews from participants in a Co-design led service improvement project. Person Centred Care and Person Centred Nursing are recognised terms in healthcare. Co-design (sometimes called participatory design) is an approach that seeks to involve all stakeholders in a creative process to deliver the best result, be this a product, technology or in this case a service. Co-design practice shares some of the underpinning philosophy of Person Centred Nursing and potentially has methods to aid in Person Centred Nursing implementation. The research design was a qualitative secondary Directed analysis. Seven interview transcripts from nurses and older people who had participated in a Co-design led improvement project in a large teaching hospital were transcribed and analysed. Two researchers analysed the transcripts for codes derived from McCormack & McCance's Person Centred Nursing Framework. The four most expressed codes were as follows: from the pre-requisites: knowing self; from care processes, engagement, working with patient's beliefs and values and shared Decision-making; and from Expected outcomes, involvement in care. This study describes the Co-design theory and practice that the participants responded to in the interviews and look at how the co-design activity facilitated elements of the Person Centred Nursing framework. This study adds to the rich literature about using emancipatory and transformational approaches to Person Centred Nursing development, and is the first study exploring explicitly the potential contribution of Co-design to this area. Methods from Co-design allow older people to contribute as equals in a practice development project, co-design methods can facilitate nursing staff to engage meaningfully with older participants and develop a shared understanding and goals. The co-produced outputs of Co-design projects embody and value the expressed beliefs and values of staff and older people. © 2016 The Authors. Journal of Clinical Nursing Published by John Wiley & Sons Ltd.

Scalable non-negative matrix tri-factorization.

PubMed

Čopar, Andrej; Žitnik, Marinka; Zupan, Blaž

2017-01-01

Matrix factorization is a well established pattern discovery tool that has seen numerous applications in biomedical data analytics, such as gene expression co-clustering, patient stratification, and gene-disease association mining. Matrix factorization learns a latent data model that takes a data matrix and transforms it into a latent feature space enabling generalization, noise removal and feature discovery. However, factorization algorithms are numerically intensive, and hence there is a pressing challenge to scale current algorithms to work with large datasets. Our focus in this paper is matrix tri-factorization, a popular method that is not limited by the assumption of standard matrix factorization about data residing in one latent space. Matrix tri-factorization solves this by inferring a separate latent space for each dimension in a data matrix, and a latent mapping of interactions between the inferred spaces, making the approach particularly suitable for biomedical data mining. We developed a block-wise approach for latent factor learning in matrix tri-factorization. The approach partitions a data matrix into disjoint submatrices that are treated independently and fed into a parallel factorization system. An appealing property of the proposed approach is its mathematical equivalence with serial matrix tri-factorization. In a study on large biomedical datasets we show that our approach scales well on multi-processor and multi-GPU architectures. On a four-GPU system we demonstrate that our approach can be more than 100-times faster than its single-processor counterpart. A general approach for scaling non-negative matrix tri-factorization is proposed. The approach is especially useful parallel matrix factorization implemented in a multi-GPU environment. We expect the new approach will be useful in emerging procedures for latent factor analysis, notably for data integration, where many large data matrices need to be collectively factorized.

Genomic survey, expression profile and co-expression network analysis of OsWD40 family in rice

PubMed Central

2012-01-01

Background WD40 proteins represent a large family in eukaryotes, which have been involved in a broad spectrum of crucial functions. Systematic characterization and co-expression analysis of OsWD40 genes enable us to understand the networks of the WD40 proteins and their biological processes and gene functions in rice. Results In this study, we identify and analyze 200 potential OsWD40 genes in rice, describing their gene structures, genome localizations, and evolutionary relationship of each member. Expression profiles covering the whole life cycle in rice has revealed that transcripts of OsWD40 were accumulated differentially during vegetative and reproductive development and preferentially up or down-regulated in different tissues. Under phytohormone treatments, 25 OsWD40 genes were differentially expressed with treatments of one or more of the phytohormone NAA, KT, or GA3 in rice seedlings. We also used a combined analysis of expression correlation and Gene Ontology annotation to infer the biological role of the OsWD40 genes in rice. The results suggested that OsWD40 genes may perform their diverse functions by complex network, thus were predictive for understanding their biological pathways. The analysis also revealed that OsWD40 genes might interact with each other to take part in metabolic pathways, suggesting a more complex feedback network. Conclusions All of these analyses suggest that the functions of OsWD40 genes are diversified, which provide useful references for selecting candidate genes for further functional studies. PMID:22429805

APPLICATION OF CDNA MICROARRAY TECHNOLOGY TO IN VITRO TOXICOLOGY AND THE SELECTION OF GENES FOR A REAL TIME RT-PCR-BASED SCREEN FOR OXIDATIVE STRESS IN HEP-G2 CELLS

EPA Science Inventory

Large-scale analysis of gene expression using cDNA microarrays promises the
rapid detection of the mode of toxicity for drugs and other chemicals. cDNA
microarrays were used to examine chemically-induced alterations of gene
expression in HepG2 cells exposed to oxidative ...

Pacific-wide contrast highlights resistance of reef calcifiers to ocean acidification.

PubMed

Comeau, S; Carpenter, R C; Nojiri, Y; Putnam, H M; Sakai, K; Edmunds, P J

2014-09-07

Ocean acidification (OA) and its associated decline in calcium carbonate saturation states is one of the major threats that tropical coral reefs face this century. Previous studies of the effect of OA on coral reef calcifiers have described a wide variety of outcomes for studies using comparable partial pressure of CO2 (pCO2) ranges, suggesting that key questions remain unresolved. One unresolved hypothesis posits that heterogeneity in the response of reef calcifiers to high pCO2 is a result of regional-scale variation in the responses to OA. To test this hypothesis, we incubated two coral taxa (Pocillopora damicornis and massive Porites) and two calcified algae (Porolithon onkodes and Halimeda macroloba) under 400, 700 and 1000 μatm pCO2 levels in experiments in Moorea (French Polynesia), Hawaii (USA) and Okinawa (Japan), where environmental conditions differ. Both corals and H. macroloba were insensitive to OA at all three locations, while the effects of OA on P. onkodes were location-specific. In Moorea and Hawaii, calcification of P. onkodes was depressed by high pCO2, but for specimens in Okinawa, there was no effect of OA. Using a study of large geographical scale, we show that resistance to OA of some reef species is a constitutive character expressed across the Pacific. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

In vitro expression of hard metal dust (WC-Co) - responsive genes in human peripheral blood mononucleated cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lombaert, Nooemi; Lison, Dominique; Van Hummelen, Paul

Hard metals consist of tungsten carbide (WC) and metallic cobalt (Co) particles and are important industrial materials produced for their extreme hardness and high wear resistance properties. While occupational exposure to metallic Co alone is apparently not associated with an increased risk of cancer, the WC-Co particle mixture was shown to be carcinogenic in exposed workers. The in vitro mutagenic/apoptogenic potential of WC-Co in human peripheral blood mononucleated cells was previously demonstrated by us. This study aimed at obtaining a broader view of the pathways responsible for WC-Co induced carcinogenicity, and in particular genotoxicity and apoptosis. We analyzed the profilemore » of gene expression induced in vitro by WC-Co versus control (24 h treatment) in human PBMC and monocytes using microarrays. The most significantly up-regulated pathways for WC-Co treated PBMC were apoptosis and stress/defense response; the most down-regulated was immune response. For WC-Co treated monocytes the most significantly up- and down-regulated pathways were nucleosome/chromatin assembly and immune response respectively. Quantitative RT-PCR data for a selection of the most strongly modulated genes (HMOX1, HSPA1A, HSPA1L, BNIP3, BNIP3L, ADORA2B, MT3, PLA2G7, TNFAIP6), and some additionally chosen apoptosis related genes (BCL2, BAX, FAS, FASL, TNF{alpha}), confirmed the microarray data after WC-Co exposure and demonstrated limited differences between the Co-containing compounds. Overall, this study provides the first analysis of gene expression induced by the WC-Co mixture showing a large profile of gene modulation and giving a preliminary indication for a hypoxia mimicking environment induced by WC-Co exposure.« less

An elm EST database for identifying leaf beetle egg-induced defense genes

PubMed Central

2012-01-01

Background Plants can defend themselves against herbivorous insects prior to the onset of larval feeding by responding to the eggs laid on their leaves. In the European field elm (Ulmus minor), egg laying by the elm leaf beetle ( Xanthogaleruca luteola) activates the emission of volatiles that attract specialised egg parasitoids, which in turn kill the eggs. Little is known about the transcriptional changes that insect eggs trigger in plants and how such indirect defense mechanisms are orchestrated in the context of other biological processes. Results Here we present the first large scale study of egg-induced changes in the transcriptional profile of a tree. Five cDNA libraries were generated from leaves of (i) untreated control elms, and elms treated with (ii) egg laying and feeding by elm leaf beetles, (iii) feeding, (iv) artificial transfer of egg clutches, and (v) methyl jasmonate. A total of 361,196 ESTs expressed sequence tags (ESTs) were identified which clustered into 52,823 unique transcripts (Unitrans) and were stored in a database with a public web interface. Among the analyzed Unitrans, 73% could be annotated by homology to known genes in the UniProt (Plant) database, particularly to those from Vitis, Ricinus, Populus and Arabidopsis. Comparative in silico analysis among the different treatments revealed differences in Gene Ontology term abundances. Defense- and stress-related gene transcripts were present in high abundance in leaves after herbivore egg laying, but transcripts involved in photosynthesis showed decreased abundance. Many pathogen-related genes and genes involved in phytohormone signaling were expressed, indicative of jasmonic acid biosynthesis and activation of jasmonic acid responsive genes. Cross-comparisons between different libraries based on expression profiles allowed the identification of genes with a potential relevance in egg-induced defenses, as well as other biological processes, including signal transduction, transport and primary metabolism. Conclusion Here we present a dataset for a large-scale study of the mechanisms of plant defense against insect eggs in a co-evolved, natural ecological plant–insect system. The EST database analysis provided here is a first step in elucidating the transcriptional responses of elm to elm leaf beetle infestation, and adds further to our knowledge on insect egg-induced transcriptomic changes in plants. The sequences identified in our comparative analysis give many hints about novel defense mechanisms directed towards eggs. PMID:22702658

An elm EST database for identifying leaf beetle egg-induced defense genes.

PubMed

Büchel, Kerstin; McDowell, Eric; Nelson, Will; Descour, Anne; Gershenzon, Jonathan; Hilker, Monika; Soderlund, Carol; Gang, David R; Fenning, Trevor; Meiners, Torsten

2012-06-15

Plants can defend themselves against herbivorous insects prior to the onset of larval feeding by responding to the eggs laid on their leaves. In the European field elm (Ulmus minor), egg laying by the elm leaf beetle ( Xanthogaleruca luteola) activates the emission of volatiles that attract specialised egg parasitoids, which in turn kill the eggs. Little is known about the transcriptional changes that insect eggs trigger in plants and how such indirect defense mechanisms are orchestrated in the context of other biological processes. Here we present the first large scale study of egg-induced changes in the transcriptional profile of a tree. Five cDNA libraries were generated from leaves of (i) untreated control elms, and elms treated with (ii) egg laying and feeding by elm leaf beetles, (iii) feeding, (iv) artificial transfer of egg clutches, and (v) methyl jasmonate. A total of 361,196 ESTs expressed sequence tags (ESTs) were identified which clustered into 52,823 unique transcripts (Unitrans) and were stored in a database with a public web interface. Among the analyzed Unitrans, 73% could be annotated by homology to known genes in the UniProt (Plant) database, particularly to those from Vitis, Ricinus, Populus and Arabidopsis. Comparative in silico analysis among the different treatments revealed differences in Gene Ontology term abundances. Defense- and stress-related gene transcripts were present in high abundance in leaves after herbivore egg laying, but transcripts involved in photosynthesis showed decreased abundance. Many pathogen-related genes and genes involved in phytohormone signaling were expressed, indicative of jasmonic acid biosynthesis and activation of jasmonic acid responsive genes. Cross-comparisons between different libraries based on expression profiles allowed the identification of genes with a potential relevance in egg-induced defenses, as well as other biological processes, including signal transduction, transport and primary metabolism. Here we present a dataset for a large-scale study of the mechanisms of plant defense against insect eggs in a co-evolved, natural ecological plant-insect system. The EST database analysis provided here is a first step in elucidating the transcriptional responses of elm to elm leaf beetle infestation, and adds further to our knowledge on insect egg-induced transcriptomic changes in plants. The sequences identified in our comparative analysis give many hints about novel defense mechanisms directed towards eggs.

A Tibetan lake sediment record of Holocene Indian summer monsoon variability

NASA Astrophysics Data System (ADS)

Bird, Broxton W.; Polisar, Pratigya J.; Lei, Yanbin; Thompson, Lonnie G.; Yao, Tandong; Finney, Bruce P.; Bain, Daniel J.; Pompeani, David P.; Steinman, Byron A.

2014-08-01

Sedimentological data and hydrogen isotopic measurements of leaf wax long-chain n-alkanes (δDwax) from an alpine lake sediment archive on the southeastern Tibetan Plateau (Paru Co) provide a Holocene perspective of Indian summer monsoon (ISM) activity. The sedimentological data reflect variations in lake level and erosion related to local ISM rainfall over the Paru Co catchment, whereas δDwax reflects integrated, synoptic-scale ISM dynamics. Our results indicate that maximum ISM rainfall occurred between 10.1 and ˜5.2 ka, during which time there were five century-scale high and low lake stands. After 5.2 ka, the ISM trended toward drier conditions to the present, with the exception of a pluvial event centered at 0.9 ka. The Paru Co results share similarities with paleoclimate records from across the Tibetan Plateau, suggesting millennial-scale ISM dynamics were expressed coherently. These millennial variations largely track gradual decreases in orbital insolation, the southward migration of the Intertropical Convergence Zone (ITCZ), decreasing zonal Pacific sea surface temperature (SST) gradients and cooling surface air temperatures on the Tibetan Plateau. Centennial ISM and lake-level variability at Paru Co closely track reconstructed surface air temperatures on the Tibetan Plateau, but may also reflect Indian Ocean Dipole events, particularly during the early Holocene when ENSO variability was attenuated. Variations in the latitude of the ITCZ during the early and late Holocene also appear to have exerted an influence on centennial ISM rainfall.

Parallel human genome analysis: microarray-based expression monitoring of 1000 genes.

PubMed Central

Schena, M; Shalon, D; Heller, R; Chai, A; Brown, P O; Davis, R W

1996-01-01

Microarrays containing 1046 human cDNAs of unknown sequence were printed on glass with high-speed robotics. These 1.0-cm2 DNA "chips" were used to quantitatively monitor differential expression of the cognate human genes using a highly sensitive two-color hybridization assay. Array elements that displayed differential expression patterns under given experimental conditions were characterized by sequencing. The identification of known and novel heat shock and phorbol ester-regulated genes in human T cells demonstrates the sensitivity of the assay. Parallel gene analysis with microarrays provides a rapid and efficient method for large-scale human gene discovery. Images Fig. 1 Fig. 2 Fig. 3 PMID:8855227

RNA SEQ Analysis Indicates that the AE3 Cl-/HCO3- Exchanger Contributes to Active Transport-Mediated CO2 Disposal in Heart.

PubMed

Vairamani, Kanimozhi; Wang, Hong-Sheng; Medvedovic, Mario; Lorenz, John N; Shull, Gary E

2017-08-04

Loss of the AE3 Cl - /HCO 3 - exchanger (Slc4a3) in mice causes an impaired cardiac force-frequency response and heart failure under some conditions but the mechanisms are not known. To better understand the functions of AE3, we performed RNA Seq analysis of AE3-null and wild-type mouse hearts and evaluated the data with respect to three hypotheses (CO 2 disposal, facilitation of Na + -loading, and recovery from an alkaline load) that have been proposed for its physiological functions. Gene Ontology and PubMatrix analyses of differentially expressed genes revealed a hypoxia response and changes in vasodilation and angiogenesis genes that strongly support the CO 2 disposal hypothesis. Differential expression of energy metabolism genes, which indicated increased glucose utilization and decreased fatty acid utilization, were consistent with adaptive responses to perturbations of O 2 /CO 2 balance in AE3-null myocytes. Given that the myocardium is an obligate aerobic tissue and consumes large amounts of O 2 , the data suggest that loss of AE3, which has the potential to extrude CO 2 in the form of HCO 3 - , impairs O 2 /CO 2 balance in cardiac myocytes. These results support a model in which the AE3 Cl - /HCO 3 - exchanger, coupled with parallel Cl - and H + -extrusion mechanisms and extracellular carbonic anhydrase, is responsible for active transport-mediated disposal of CO 2 .

Molecular signatures in Arabidopsis thaliana in response to insect attack and bacterial infection.

PubMed

Barah, Pankaj; Winge, Per; Kusnierczyk, Anna; Tran, Diem Hong; Bones, Atle M

2013-01-01

Under the threat of global climatic change and food shortages, it is essential to take the initiative to obtain a comprehensive understanding of common and specific defence mechanisms existing in plant systems for protection against different types of biotic invaders. We have implemented an integrated approach to analyse the overall transcriptomic reprogramming and systems-level defence responses in the model plant species Arabidopsis thaliana (A. thaliana henceforth) during insect Brevicoryne brassicae (B. brassicae henceforth) and bacterial Pseudomonas syringae pv. tomato strain DC3000 (P. syringae henceforth) attacks. The main aim of this study was to identify the attacker-specific and general defence response signatures in A. thaliana when attacked by phloem-feeding aphids or pathogenic bacteria. The obtained annotated networks of differentially expressed transcripts indicated that members of transcription factor families, such as WRKY, MYB, ERF, BHLH and bZIP, could be crucial for stress-specific defence regulation in Arabidopsis during aphid and P. syringae attack. The defence response pathways, signalling pathways and metabolic processes associated with aphid attack and P. syringae infection partially overlapped. Components of several important biosynthesis and signalling pathways, such as salicylic acid (SA), jasmonic acid (JA), ethylene (ET) and glucosinolates, were differentially affected during the two the treatments. Several stress-regulated transcription factors were known to be associated with stress-inducible microRNAs. The differentially regulated gene sets included many signature transcription factors, and our co-expression analysis showed that they were also strongly co-expressed during 69 other biotic stress experiments. Defence responses and functional networks that were unique and specific to aphid or P. syringae stresses were identified. Furthermore, our analysis revealed a probable link between biotic stress and microRNAs in Arabidopsis and, thus gives indicates a new direction for conducting large-scale targeted experiments to explore the detailed regulatory links between them. The presented results provide a comparative understanding of Arabidopsis - B. brassicae and Arabidopsis - P. syringae interactions at the transcriptomic level.

Resolving the substructure of molecular clouds in the LMC

NASA Astrophysics Data System (ADS)

Wong, Tony; Hughes, Annie; Tokuda, Kazuki; Indebetouw, Remy; Wojciechowski, Evan; Bandurski, Jeffrey; MC3 Collaboration

2018-01-01

We present recent wide-field CO and 13CO mapping of giant molecular clouds in the Large Magellanic Cloud with ALMA. Our sample exhibits diverse star-formation properties, and reveals comparably diverse molecular cloud properties including surface density and velocity dispersion at a given scale. We first present the results of a recent study comparing two GMCs at the extreme ends of the star formation activity spectrum. Our quiescent cloud exhibits 10 times lower surface density and 5 times lower velocity dispersion than the active 30 Doradus cloud, yet in both clouds we find a wide range of line widths at the smallest resolved scales, spanning nearly the full range of line widths seen at all scales. This suggests an important role for feedback on sub-parsec scales, while the energetics on larger scales are dominated by clump-to-clump relative velocities. We then extend our analysis to four additional clouds that exhibit intermediate levels of star formation activity.

Transcriptomic response of sea urchin larvae Strongylocentrotus purpuratus to CO2-driven seawater acidification.

PubMed

Todgham, Anne E; Hofmann, Gretchen E

2009-08-01

Ocean acidification from the uptake of anthropogenic CO(2) is expected to have deleterious consequences for many calcifying marine animals. Forecasting the vulnerability of these marine organisms to climate change is linked to an understanding of whether species possess the physiological capacity to compensate for the potentially adverse effects of ocean acidification. We carried out a microarray-based transcriptomic analysis of the physiological response of larvae of a calcifying marine invertebrate, the purple sea urchin, Strongylocentrotus purpuratus, to CO(2)-driven seawater acidification. In lab-based cultures, larvae were raised under conditions approximating current ocean pH conditions (pH 8.01) and at projected, more acidic pH conditions (pH 7.96 and 7.88) in seawater aerated with CO(2) gas. Targeting expression of approximately 1000 genes involved in several biological processes, this study captured changes in gene expression patterns that characterize the transcriptomic response to CO(2)-driven seawater acidification of developing sea urchin larvae. In response to both elevated CO(2) scenarios, larvae underwent broad scale decreases in gene expression in four major cellular processes: biomineralization, cellular stress response, metabolism and apoptosis. This study underscores that physiological processes beyond calcification are impacted greatly, suggesting that overall physiological capacity and not just a singular focus on biomineralization processes is essential for forecasting the impact of future CO(2) conditions on marine organisms. Conducted on targeted and vulnerable species, genomics-based studies, such as the one highlighted here, have the potential to identify potential ;weak links' in physiological function that may ultimately determine an organism's capacity to tolerate future ocean conditions.

Co-expression Network Approach to Studying the Effects of Botulinum Neurotoxin-A.

PubMed

Mukund, Kavitha; Ward, Samuel R; Lieber, Richard L; Subramaniam, Shankar

2017-10-16

Botulinum Neurotoxin A (BoNT-A) is a potent neurotoxin with several clinical applications.The goal of this study was to utilize co-expression network theory to analyze temporal transcriptional data from skeletal muscle after BoNT-A treatment. Expression data for 2000 genes (extracted using a ranking heuristic) served as the basis for this analysis. Using weighted gene co-expression network analysis (WGCNA), we identified 19 co-expressed modules, further hierarchically clustered into 5 groups. Quantifying average expression and co-expression patterns across these groups revealed temporal aspects of muscle's response to BoNT-A. Functional analysis revealed enrichment of group 1 with metabolism; group 5 with contradictory functions of atrophy and cellular recovery; and groups 2 and 3 with extracellular matrix (ECM) and non-fast fiber isoforms. Topological positioning of two highly ranked, significantly expressed genes- Dclk1 and Ostalpha within group 5 suggested possible mechanistic roles in recovery from BoNT-A induced atrophy. Phenotypic correlations of groups with titin and myosin protein content further emphasized the effect of BoNT-A on the sarcomeric contraction machinery in early phase of chemodenervation. In summary, our approach revealed a hierarchical functional response to BoNT-A induced paralysis with early metabolic and later ECM responses and identified putative biomarkers associated with chemodenervation. Additionally, our results provide an unbiased validation of the response documented in our previous workBotulinum Neurotoxin A (BoNT-A) is a potent neurotoxin with several clinical applications.The goal of this study was to utilize co-expression network theory to analyze temporal transcriptional data from skeletal muscle after BoNT-A treatment. Expression data for 2000 genes (extracted using a ranking heuristic) served as the basis for this analysis. Using weighted gene co-expression network analysis (WGCNA), we identified 19 co-expressed modules, further hierarchically clustered into 5 groups. Quantifying average expression and co-expression patterns across these groups revealed temporal aspects of muscle's response to BoNT-A. Functional analysis revealed enrichment of group 1 with metabolism; group 5 with contradictory functions of atrophy and cellular recovery; and groups 2 and 3 with extracellular matrix (ECM) and non-fast fiber isoforms. Topological positioning of two highly ranked, significantly expressed genes- Dclk1 and Ostalpha within group 5 suggested possible mechanistic roles in recovery from BoNT-A induced atrophy. Phenotypic correlations of groups with titin and myosin protein content further emphasized the effect of BoNT-A on the sarcomeric contraction machinery in early phase of chemodenervation. In summary, our approach revealed a hierarchical functional response to BoNT-A induced paralysis with early metabolic and later ECM responses and identified putative biomarkers associated with chemodenervation. Additionally, our results provide an unbiased validation of the response documented in our previous work.

Co-governing decentralised water systems: an analytical framework.

PubMed

Yu, C; Brown, R; Morison, P

2012-01-01

Current discourses in urban water management emphasise a diversity of water sources and scales of infrastructure for resilience and adaptability. During the last 2 decades, in particular, various small-scale systems emerged and developed so that the debate has largely moved from centralised versus decentralised water systems toward governing integrated and networked systems of provision and consumption where small-scale technologies are embedded in large-scale centralised infrastructures. However, while centralised systems have established boundaries of ownership and management, decentralised water systems (such as stormwater harvesting technologies for the street, allotment/house scales) do not, therefore the viability for adoption and/or continued use of decentralised water systems is challenged. This paper brings together insights from the literature on public sector governance, co-production and social practices model to develop an analytical framework for co-governing such systems. The framework provides urban water practitioners with guidance when designing co-governance arrangements for decentralised water systems so that these systems continue to exist, and become widely adopted, within the established urban water regime.

Parallel group independent component analysis for massive fMRI data sets.

PubMed

Chen, Shaojie; Huang, Lei; Qiu, Huitong; Nebel, Mary Beth; Mostofsky, Stewart H; Pekar, James J; Lindquist, Martin A; Eloyan, Ani; Caffo, Brian S

2017-01-01

Independent component analysis (ICA) is widely used in the field of functional neuroimaging to decompose data into spatio-temporal patterns of co-activation. In particular, ICA has found wide usage in the analysis of resting state fMRI (rs-fMRI) data. Recently, a number of large-scale data sets have become publicly available that consist of rs-fMRI scans from thousands of subjects. As a result, efficient ICA algorithms that scale well to the increased number of subjects are required. To address this problem, we propose a two-stage likelihood-based algorithm for performing group ICA, which we denote Parallel Group Independent Component Analysis (PGICA). By utilizing the sequential nature of the algorithm and parallel computing techniques, we are able to efficiently analyze data sets from large numbers of subjects. We illustrate the efficacy of PGICA, which has been implemented in R and is freely available through the Comprehensive R Archive Network, through simulation studies and application to rs-fMRI data from two large multi-subject data sets, consisting of 301 and 779 subjects respectively.

Metabolic pathway engineering for fatty acid ethyl ester production in Saccharomyces cerevisiae using stable chromosomal integration.

PubMed

de Jong, Bouke Wim; Shi, Shuobo; Valle-Rodríguez, Juan Octavio; Siewers, Verena; Nielsen, Jens

2015-03-01

Fatty acid ethyl esters are fatty acid derived molecules similar to first generation biodiesel (fatty acid methyl esters; FAMEs) which can be produced in a microbial cell factory. Saccharomyces cerevisiae is a suitable candidate for microbial large scale and long term cultivations, which is the typical industrial production setting for biofuels. It is crucial to conserve the metabolic design of the cell factory during industrial cultivation conditions that require extensive propagation. Genetic modifications therefore have to be introduced in a stable manner. Here, several metabolic engineering strategies for improved production of fatty acid ethyl esters in S. cerevisiae were combined and the genes were stably expressed from the organisms' chromosomes. A wax ester synthase (ws2) was expressed in different yeast strains with an engineered acetyl-CoA and fatty acid metabolism. Thus, we compared expression of ws2 with and without overexpression of alcohol dehydrogenase (ADH2), acetaldehyde dehydrogenase (ALD6) and acetyl-CoA synthetase (acs SE (L641P) ) and further evaluated additional overexpression of a mutant version of acetyl-CoA decarboxylase (ACC1 (S1157A,S659A) ) and the acyl-CoA binding protein (ACB1). The combined engineering efforts of the implementation of ws2, ADH2, ALD6 and acs SE (L641P) , ACC1 (S1157A,S659A) and ACB1 in a S. cerevisiae strain lacking storage lipid formation (are1Δ, are2Δ, dga1Δ and lro1Δ) and β-oxidation (pox1Δ) resulted in a 4.1-fold improvement compared with sole expression of ws2 in S. cerevisiae.

Multiwell CO2 injectivity: impact of boundary conditions and brine extraction on geologic CO2 storage efficiency and pressure buildup.

PubMed

Heath, Jason E; McKenna, Sean A; Dewers, Thomas A; Roach, Jesse D; Kobos, Peter H

2014-01-21

CO2 storage efficiency is a metric that expresses the portion of the pore space of a subsurface geologic formation that is available to store CO2. Estimates of storage efficiency for large-scale geologic CO2 storage depend on a variety of factors including geologic properties and operational design. These factors govern estimates on CO2 storage resources, the longevity of storage sites, and potential pressure buildup in storage reservoirs. This study employs numerical modeling to quantify CO2 injection well numbers, well spacing, and storage efficiency as a function of geologic formation properties, open-versus-closed boundary conditions, and injection with or without brine extraction. The set of modeling runs is important as it allows the comparison of controlling factors on CO2 storage efficiency. Brine extraction in closed domains can result in storage efficiencies that are similar to those of injection in open-boundary domains. Geomechanical constraints on downhole pressure at both injection and extraction wells lower CO2 storage efficiency as compared to the idealized scenario in which the same volumes of CO2 and brine are injected and extracted, respectively. Geomechanical constraints should be taken into account to avoid potential damage to the storage site.

Quantification of CO emissions from the city of Madrid using MOPITT satellite retrievals and WRF simulations

NASA Astrophysics Data System (ADS)

Dekker, Iris N.; Houweling, Sander; Aben, Ilse; Röckmann, Thomas; Krol, Maarten; Martínez-Alonso, Sara; Deeter, Merritt N.; Worden, Helen M.

2017-12-01

The growth of mega-cities leads to air quality problems directly affecting the citizens. Satellite measurements are becoming of higher quality and quantity, which leads to more accurate satellite retrievals of enhanced air pollutant concentrations over large cities. In this paper, we compare and discuss both an existing and a new method for estimating urban-scale trends in CO emissions using multi-year retrievals from the MOPITT satellite instrument. The first method is mainly based on satellite data, and has the advantage of fewer assumptions, but also comes with uncertainties and limitations as shown in this paper. To improve the reliability of urban-to-regional scale emission trend estimation, we simulate MOPITT retrievals using the Weather Research and Forecast model with chemistry core (WRF-Chem). The difference between model and retrieval is used to optimize CO emissions in WRF-Chem, focusing on the city of Madrid, Spain. This method has the advantage over the existing method in that it allows both a trend analysis of CO concentrations and a quantification of CO emissions. Our analysis confirms that MOPITT is capable of detecting CO enhancements over Madrid, although significant differences remain between the yearly averaged model output and satellite measurements (R2 = 0.75) over the city. After optimization, we find Madrid CO emissions to be lower by 48 % for 2002 and by 17 % for 2006 compared with the EdgarV4.2 emission inventory. The MOPITT-derived emission adjustments lead to better agreement with the European emission inventory TNO-MAC-III for both years. This suggests that the downward trend in CO emissions over Madrid is overestimated in EdgarV4.2 and more realistically represented in TNO-MACC-III. However, our satellite and model based emission estimates have large uncertainties, around 20 % for 2002 and 50 % for 2006.

Genomic reconstruction to improve bioethanol and ergosterol production of industrial yeast Saccharomyces cerevisiae.

PubMed

Zhang, Ke; Tong, Mengmeng; Gao, Kehui; Di, Yanan; Wang, Pinmei; Zhang, Chunfang; Wu, Xuechang; Zheng, Daoqiong

2015-02-01

Baker's yeast (Saccharomyces cerevisiae) is the common yeast used in the fields of bread making, brewing, and bioethanol production. Growth rate, stress tolerance, ethanol titer, and byproducts yields are some of the most important agronomic traits of S. cerevisiae for industrial applications. Here, we developed a novel method of constructing S. cerevisiae strains for co-producing bioethanol and ergosterol. The genome of an industrial S. cerevisiae strain, ZTW1, was first reconstructed through treatment with an antimitotic drug followed by sporulation and hybridization. A total of 140 mutants were selected for ethanol fermentation testing, and a significant positive correlation between ergosterol content and ethanol production was observed. The highest performing mutant, ZG27, produced 7.9 % more ethanol and 43.2 % more ergosterol than ZTW1 at the end of fermentation. Chromosomal karyotyping and proteome analysis of ZG27 and ZTW1 suggested that this breeding strategy caused large-scale genome structural variations and global gene expression diversities in the mutants. Genetic manipulation further demonstrated that the altered expression activity of some genes (such as ERG1, ERG9, and ERG11) involved in ergosterol synthesis partly explained the trait improvement in ZG27.

Tomato functional genomics database (TFGD): a comprehensive collection and analysis package for tomato functional genomics

USDA-ARS?s Scientific Manuscript database

Tomato Functional Genomics Database (TFGD; http://ted.bti.cornell.edu) provides a comprehensive systems biology resource to store, mine, analyze, visualize and integrate large-scale tomato functional genomics datasets. The database is expanded from the previously described Tomato Expression Database...

Expression-based clustering of CAZyme-encoding genes of Aspergillus niger.

PubMed

Gruben, Birgit S; Mäkelä, Miia R; Kowalczyk, Joanna E; Zhou, Miaomiao; Benoit-Gelber, Isabelle; De Vries, Ronald P

2017-11-23

The Aspergillus niger genome contains a large repertoire of genes encoding carbohydrate active enzymes (CAZymes) that are targeted to plant polysaccharide degradation enabling A. niger to grow on a wide range of plant biomass substrates. Which genes need to be activated in certain environmental conditions depends on the composition of the available substrate. Previous studies have demonstrated the involvement of a number of transcriptional regulators in plant biomass degradation and have identified sets of target genes for each regulator. In this study, a broad transcriptional analysis was performed of the A. niger genes encoding (putative) plant polysaccharide degrading enzymes. Microarray data focusing on the initial response of A. niger to the presence of plant biomass related carbon sources were analyzed of a wild-type strain N402 that was grown on a large range of carbon sources and of the regulatory mutant strains ΔxlnR, ΔaraR, ΔamyR, ΔrhaR and ΔgalX that were grown on their specific inducing compounds. The cluster analysis of the expression data revealed several groups of co-regulated genes, which goes beyond the traditionally described co-regulated gene sets. Additional putative target genes of the selected regulators were identified, based on their expression profile. Notably, in several cases the expression profile puts questions on the function assignment of uncharacterized genes that was based on homology searches, highlighting the need for more extensive biochemical studies into the substrate specificity of enzymes encoded by these non-characterized genes. The data also revealed sets of genes that were upregulated in the regulatory mutants, suggesting interaction between the regulatory systems and a therefore even more complex overall regulatory network than has been reported so far. Expression profiling on a large number of substrates provides better insight in the complex regulatory systems that drive the conversion of plant biomass by fungi. In addition, the data provides additional evidence in favor of and against the similarity-based functions assigned to uncharacterized genes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Middleton, Richard S.; Levine, Jonathan S.; Bielicki, Jeffrey M.

CO 2 capture, utilization, and storage (CCUS) technology has yet to be widely deployed at a commercial scale despite multiple high-profile demonstration projects. We suggest that developing a large-scale, visible, and financially viable CCUS network could potentially overcome many barriers to deployment and jumpstart commercial-scale CCUS. To date, substantial effort has focused on technology development to reduce the costs of CO 2 capture from coal-fired power plants. Here, we propose that near-term investment could focus on implementing CO 2 capture on facilities that produce high-value chemicals/products. These facilities can absorb the expected impact of the marginal increase in the costmore » of production on the price of their product, due to the addition of CO 2 capture, more than coal-fired power plants. A financially viable demonstration of a large-scale CCUS network requires offsetting the costs of CO 2 capture by using the CO 2 as an input to the production of market-viable products. As a result, we demonstrate this alternative development path with the example of an integrated CCUS system where CO 2 is captured from ethylene producers and used for enhanced oil recovery in the U.S. Gulf Coast region.« less

Multivariate Pattern Classification of Facial Expressions Based on Large-Scale Functional Connectivity.

PubMed

Liang, Yin; Liu, Baolin; Li, Xianglin; Wang, Peiyuan

2018-01-01

It is an important question how human beings achieve efficient recognition of others' facial expressions in cognitive neuroscience, and it has been identified that specific cortical regions show preferential activation to facial expressions in previous studies. However, the potential contributions of the connectivity patterns in the processing of facial expressions remained unclear. The present functional magnetic resonance imaging (fMRI) study explored whether facial expressions could be decoded from the functional connectivity (FC) patterns using multivariate pattern analysis combined with machine learning algorithms (fcMVPA). We employed a block design experiment and collected neural activities while participants viewed facial expressions of six basic emotions (anger, disgust, fear, joy, sadness, and surprise). Both static and dynamic expression stimuli were included in our study. A behavioral experiment after scanning confirmed the validity of the facial stimuli presented during the fMRI experiment with classification accuracies and emotional intensities. We obtained whole-brain FC patterns for each facial expression and found that both static and dynamic facial expressions could be successfully decoded from the FC patterns. Moreover, we identified the expression-discriminative networks for the static and dynamic facial expressions, which span beyond the conventional face-selective areas. Overall, these results reveal that large-scale FC patterns may also contain rich expression information to accurately decode facial expressions, suggesting a novel mechanism, which includes general interactions between distributed brain regions, and that contributes to the human facial expression recognition.

Multivariate Pattern Classification of Facial Expressions Based on Large-Scale Functional Connectivity

PubMed Central

Liang, Yin; Liu, Baolin; Li, Xianglin; Wang, Peiyuan

2018-01-01

It is an important question how human beings achieve efficient recognition of others’ facial expressions in cognitive neuroscience, and it has been identified that specific cortical regions show preferential activation to facial expressions in previous studies. However, the potential contributions of the connectivity patterns in the processing of facial expressions remained unclear. The present functional magnetic resonance imaging (fMRI) study explored whether facial expressions could be decoded from the functional connectivity (FC) patterns using multivariate pattern analysis combined with machine learning algorithms (fcMVPA). We employed a block design experiment and collected neural activities while participants viewed facial expressions of six basic emotions (anger, disgust, fear, joy, sadness, and surprise). Both static and dynamic expression stimuli were included in our study. A behavioral experiment after scanning confirmed the validity of the facial stimuli presented during the fMRI experiment with classification accuracies and emotional intensities. We obtained whole-brain FC patterns for each facial expression and found that both static and dynamic facial expressions could be successfully decoded from the FC patterns. Moreover, we identified the expression-discriminative networks for the static and dynamic facial expressions, which span beyond the conventional face-selective areas. Overall, these results reveal that large-scale FC patterns may also contain rich expression information to accurately decode facial expressions, suggesting a novel mechanism, which includes general interactions between distributed brain regions, and that contributes to the human facial expression recognition. PMID:29615882

Bioinspired Wood Nanotechnology for Functional Materials.

PubMed

Berglund, Lars A; Burgert, Ingo

2018-05-01

It is a challenging task to realize the vision of hierarchically structured nanomaterials for large-scale applications. Herein, the biomaterial wood as a large-scale biotemplate for functionalization at multiple scales is discussed, to provide an increased property range to this renewable and CO 2 -storing bioresource, which is available at low cost and in large quantities. The Progress Report reviews the emerging field of functional wood materials in view of the specific features of the structural template and novel nanotechnological approaches for the development of wood-polymer composites and wood-mineral hybrids for advanced property profiles and new functions. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Evapotranspiration: A process driving mass transport and energy exchange in the soil-plant-atmosphere-climate system

NASA Astrophysics Data System (ADS)

Katul, Gabriel G.; Oren, Ram; Manzoni, Stefano; Higgins, Chad; Parlange, Marc B.

2012-09-01

The role of evapotranspiration (ET) in the global, continental, regional, and local water cycles is reviewed. Elevated atmospheric CO2, air temperature, vapor pressure deficit (D), turbulent transport, radiative transfer, and reduced soil moisture all impact biotic and abiotic processes controlling ET that must be extrapolated to large scales. Suggesting a blueprint to achieve this link is the main compass of this review. Leaf-scale transpiration (fe) as governed by the plant biochemical demand for CO2 is first considered. When this biochemical demand is combined with mass transfer formulations, the problem remains mathematically intractable, requiring additional assumptions. A mathematical "closure" that assumes stomatal aperture is autonomously regulated so as to maximize the leaf carbon gain while minimizing water loss is proposed, which leads to analytical expressions for leaf-scale transpiration. This formulation predicts well the effects of elevated atmospheric CO2 and increases in D on fe. The case of soil moisture stress is then considered using extensive gas exchange measurements collected in drought studies. Upscaling the fe to the canopy is then discussed at multiple time scales. The impact of limited soil water availability within the rooting zone on the upscaled ET as well as some plant strategies to cope with prolonged soil moisture stress are briefly presented. Moving further up in direction and scale, the soil-plant system is then embedded within the atmospheric boundary layer, where the influence of soil moisture on rainfall is outlined. The review concludes by discussing outstanding challenges and how to tackle them by means of novel theoretical, numerical, and experimental approaches.

PFS/Mars Express first results: water vapour and carbon monoxide global distribution

NASA Astrophysics Data System (ADS)

Ignatiev, N. I.; Titov, D. V.; Formisano, V.; Moroz, V. I.; Lellouch, E.; Encrenaz, Th.; Fouchet, T.; Grassi, D.; Giuranna, M.; Atreya, S.; Pfs Team

Planetary Fourier Spectrometer onboard Mars Express, with its wide spectral range (1.2--45 um) and high spectral resolution (1.4 cm-1), makes it possible to study in a self-consistent manner the Martian atmosphere by means of simultaneous analysis of spectral features in several spectral regions. As concerned small species, we observe 30--50, 6.3, 2.56, 1.87 and 1.38 μ m H2O bands, and 4.7 and 2.35 μ m CO bands. The most favourable, with respect to the instrument performance, 2.56 μ m H2O and 4.7 μ m CO bands, are used to study the variations of column abundance of water vapour and carbon monoxide on a global scale from pole to pole. All necessary atmospheric parameters, namely temperature profiles, surface pressure, and dust density are obtained from the same spectra, whenever possible.

Genome-scale approaches to the epigenetics of common human disease

PubMed Central

2011-01-01

Traditionally, the pathology of human disease has been focused on microscopic examination of affected tissues, chemical and biochemical analysis of biopsy samples, other available samples of convenience, such as blood, and noninvasive or invasive imaging of varying complexity, in order to classify disease and illuminate its mechanistic basis. The molecular age has complemented this armamentarium with gene expression arrays and selective analysis of individual genes. However, we are entering a new era of epigenomic profiling, i.e., genome-scale analysis of cell-heritable nonsequence genetic change, such as DNA methylation. The epigenome offers access to stable measurements of cellular state and to biobanked material for large-scale epidemiological studies. Some of these genome-scale technologies are beginning to be applied to create the new field of epigenetic epidemiology. PMID:19844740

Extended local similarity analysis (eLSA) of microbial community and other time series data with replicates.

PubMed

Xia, Li C; Steele, Joshua A; Cram, Jacob A; Cardon, Zoe G; Simmons, Sheri L; Vallino, Joseph J; Fuhrman, Jed A; Sun, Fengzhu

2011-01-01

The increasing availability of time series microbial community data from metagenomics and other molecular biological studies has enabled the analysis of large-scale microbial co-occurrence and association networks. Among the many analytical techniques available, the Local Similarity Analysis (LSA) method is unique in that it captures local and potentially time-delayed co-occurrence and association patterns in time series data that cannot otherwise be identified by ordinary correlation analysis. However LSA, as originally developed, does not consider time series data with replicates, which hinders the full exploitation of available information. With replicates, it is possible to understand the variability of local similarity (LS) score and to obtain its confidence interval. We extended our LSA technique to time series data with replicates and termed it extended LSA, or eLSA. Simulations showed the capability of eLSA to capture subinterval and time-delayed associations. We implemented the eLSA technique into an easy-to-use analytic software package. The software pipeline integrates data normalization, statistical correlation calculation, statistical significance evaluation, and association network construction steps. We applied the eLSA technique to microbial community and gene expression datasets, where unique time-dependent associations were identified. The extended LSA analysis technique was demonstrated to reveal statistically significant local and potentially time-delayed association patterns in replicated time series data beyond that of ordinary correlation analysis. These statistically significant associations can provide insights to the real dynamics of biological systems. The newly designed eLSA software efficiently streamlines the analysis and is freely available from the eLSA homepage, which can be accessed at http://meta.usc.edu/softs/lsa.

Extended local similarity analysis (eLSA) of microbial community and other time series data with replicates

PubMed Central

2011-01-01

Background The increasing availability of time series microbial community data from metagenomics and other molecular biological studies has enabled the analysis of large-scale microbial co-occurrence and association networks. Among the many analytical techniques available, the Local Similarity Analysis (LSA) method is unique in that it captures local and potentially time-delayed co-occurrence and association patterns in time series data that cannot otherwise be identified by ordinary correlation analysis. However LSA, as originally developed, does not consider time series data with replicates, which hinders the full exploitation of available information. With replicates, it is possible to understand the variability of local similarity (LS) score and to obtain its confidence interval. Results We extended our LSA technique to time series data with replicates and termed it extended LSA, or eLSA. Simulations showed the capability of eLSA to capture subinterval and time-delayed associations. We implemented the eLSA technique into an easy-to-use analytic software package. The software pipeline integrates data normalization, statistical correlation calculation, statistical significance evaluation, and association network construction steps. We applied the eLSA technique to microbial community and gene expression datasets, where unique time-dependent associations were identified. Conclusions The extended LSA analysis technique was demonstrated to reveal statistically significant local and potentially time-delayed association patterns in replicated time series data beyond that of ordinary correlation analysis. These statistically significant associations can provide insights to the real dynamics of biological systems. The newly designed eLSA software efficiently streamlines the analysis and is freely available from the eLSA homepage, which can be accessed at http://meta.usc.edu/softs/lsa. PMID:22784572

Dating and functional characterization of duplicated genes in the apple (Malus domestica Borkh.) by analyzing EST data.

PubMed

Sanzol, Javier

2010-05-14

Gene duplication is central to genome evolution. In plants, genes can be duplicated through small-scale events and large-scale duplications often involving polyploidy. The apple belongs to the subtribe Pyrinae (Rosaceae), a diverse lineage that originated via allopolyploidization. Both small-scale duplications and polyploidy may have been important mechanisms shaping the genome of this species. This study evaluates the gene duplication and polyploidy history of the apple by characterizing duplicated genes in this species using EST data. Overall, 68% of the apple genes were clustered into families with a mean copy-number of 4.6. Analysis of the age distribution of gene duplications supported a continuous mode of small-scale duplications, plus two episodes of large-scale duplicates of vastly different ages. The youngest was consistent with the polyploid origin of the Pyrinae 37-48 MYBP, whereas the older may be related to gamma-triplication; an ancient hexapolyploidization previously characterized in the four sequenced eurosid genomes and basal to the eurosid-asterid divergence. Duplicated genes were studied for functional diversification with an emphasis on young paralogs; those originated during or after the formation of the Pyrinae lineage. Unequal assignment of single-copy genes and gene families to Gene Ontology categories suggested functional bias in the pattern of gene retention of paralogs. Young paralogs related to signal transduction, metabolism, and energy pathways have been preferentially retained. Non-random retention of duplicated genes seems to have mediated the expansion of gene families, some of which may have substantially increased their members after the origin of the Pyrinae. The joint analysis of over-duplicated functional categories and phylogenies, allowed evaluation of the role of both polyploidy and small-scale duplications during this process. Finally, gene expression analysis indicated that 82% of duplicated genes, including 80% of young paralogs, showed uncorrelated expression profiles, suggesting extensive subfunctionalization and a role of gene duplication in the acquisition of novel patterns of gene expression. This study reports a genome-wide analysis of the mode of gene duplication in the apple, and provides evidence for its role in genome functional diversification by characterising three major processes: selective retention of paralogs, amplification of gene families, and changes in gene expression.

Neurochemical phenotype of cytoglobin-expressing neurons in the rat hippocampus.

PubMed

Hundahl, Christian Ansgar; Fahrenkrug, Jan; Hannibal, Jens

2014-09-01

Cytoglobin (Cygb), a novel oxygen-binding protein, is expressed in the majority of tissues and has been proposed to function in nitric oxide (NO) metabolism in the vasculature and to have cytoprotective properties. However, the overall functions of Cygb remain elusive. Cygb is also expressed in a subpopulation of brain neurons. Recently, it has been shown that stress upregulates Cygb expression in the brain and the majority of neuronal nitric oxide synthase (nNOS)-positive neurons, an enzyme that produces NO, co-express Cygb. However, there are more neurons expressing Cygb than nNOS, thus a large number of Cygb neurons remain uncharacterized by the neurochemical content. The aim of the present study was to provide an additional and more detailed neurochemical phenotype of Cygb-expressing neurons in the rat hippocampus. The rat hippocampus was chosen due to the abundance of Cygb, as well as this limbic structure being an important target in a number of neurodegenerative diseases. Using triple immunohistochemistry, it was demonstrated that nearly all the parvalbumin- and heme oxygenase 1-positive neurons co-express Cygb and to a large extent, these neuron populations are distinct from the population of Cygb neurons co-expressing nNOS. Furthermore, it was shown that the majority of neurons expressing somastostatin and vasoactive intestinal peptide also co-express Cygb and nNOS. Detailed information regarding the neurochemical phenotype of Cygb neurons in the hippocampus can be a valuable tool in determining the function of Cygb in the brain.

Regional Relationship between CO and O3 in New England

NASA Astrophysics Data System (ADS)

Mao, H.; Talbot, R.

2003-12-01

The seasonality and interannual variability in the mixing ratios of ozone (O3) and carbon monoxide (CO) and their inter-relationship were investigated at the rural low elevation site Thompson Farm (TF) and the hill site Castle Springs (400 m above ground level) in southern New Hampshire using continuous observations (2001-2003) from the Atmospheric Investigation, Regional Modeling, Analysis and Prediction (AIRMAP) program at University of New Hampshire (UNH). Our results show distinct site-dependent characteristics in temporal variations on various time scales in O3 and CO and particularly large interannual variability in fall and winter at both sites. The grouped O3 and CO data, based on wind speed and direction over different time periods of the day, showed largely varying probability distribution functions (PDF). It was found that only 10% of the seasonal observations formed a positive O3-CO linear correlation, leading to an estimate of 370 M moles d-1 for O3 export from the northeastern U.S. This estimate is three times smaller than previous studies. We used a ratio analysis (NO/NOy and NOy/CO) to show that the linear O3-CO relationships were a result of multiple processes rather than simply either photochemical or depositonal loss processes as proposed by previous work. One of the most important features of the O3-CO relationship is the lower CO boundary, for which we attempeted to provide physical and chemical interpretations.

AML1/ETO trans-activates c-KIT expression through the long range interaction between promoter and intronic enhancer.

PubMed

Tian, Ying; Wang, Genjie; Hu, Qingzhu; Xiao, Xichun; Chen, Shuxia

2018-04-01

The AML1/ETO onco-fusion protein is crucial for the genesis of t(8;21) acute myeloid leukemia (AML) and is well documented as a transcriptional repressor through dominant-negative effect. However, little is known about the transactivation mechanism of AML1/ETO. Through large cohort of patient's expression level data analysis and a series of experimental validation, we report here that AML1/ETO transactivates c-KIT expression through directly binding to and mediating the long-range interaction between the promoter and intronic enhancer regions of c-KIT. Gene expression analyses verify that c-KIT expression is significantly high in t(8;21) AML. Further ChIP-seq analysis and motif scanning identify two regulatory regions located in the promoter and intronic enhancer region of c-KIT, respectively. Both regions are enriched by co-factors of AML1/ETO, such as AML1, CEBPe, c-Jun, and c-Fos. Further luciferase reporter assays show that AML1/ETO trans-activates c-KIT promoter activity through directly recognizing the AML1 motif and the co-existence of co-factors. The induction of c-KIT promoter activity is reinforced with the existence of intronic enhancer region. Furthermore, ChIP-3C-qPCR assays verify that AML1/ETO mediates the formation of DNA-looping between the c-KIT promoter and intronic enhancer region through the long-range interaction. Collectively, our data uncover a novel transcriptional activity mechanism of AML1/ETO and enrich our knowledge of the onco-fusion protein mediated transcription regulation. © 2017 Wiley Periodicals, Inc.

Comparisons for ESTA-Task3: ASTEC, CESAM and CLÉS

NASA Astrophysics Data System (ADS)

Christensen-Dalsgaard, J.

The ESTA activity under the CoRoT project aims at testing the tools for computing stellar models and oscillation frequencies that will be used in the analysis of asteroseismic data from CoRoT and other large-scale upcoming asteroseismic projects. Here I report results of comparisons between calculations using the Aarhus code (ASTEC) and two other codes, for models that include diffusion and settling. It is found that there are likely deficiencies, requiring further study, in the ASTEC computation of models including convective cores.

Principles of gene microarray data analysis.

PubMed

Mocellin, Simone; Rossi, Carlo Riccardo

2007-01-01

The development of several gene expression profiling methods, such as comparative genomic hybridization (CGH), differential display, serial analysis of gene expression (SAGE), and gene microarray, together with the sequencing of the human genome, has provided an opportunity to monitor and investigate the complex cascade of molecular events leading to tumor development and progression. The availability of such large amounts of information has shifted the attention of scientists towards a nonreductionist approach to biological phenomena. High throughput technologies can be used to follow changing patterns of gene expression over time. Among them, gene microarray has become prominent because it is easier to use, does not require large-scale DNA sequencing, and allows for the parallel quantification of thousands of genes from multiple samples. Gene microarray technology is rapidly spreading worldwide and has the potential to drastically change the therapeutic approach to patients affected with tumor. Therefore, it is of paramount importance for both researchers and clinicians to know the principles underlying the analysis of the huge amount of data generated with microarray technology.

Cloud-scale genomic signals processing classification analysis for gene expression microarray data.

PubMed

Harvey, Benjamin; Soo-Yeon Ji

2014-01-01

As microarray data available to scientists continues to increase in size and complexity, it has become overwhelmingly important to find multiple ways to bring inference though analysis of DNA/mRNA sequence data that is useful to scientists. Though there have been many attempts to elucidate the issue of bringing forth biological inference by means of wavelet preprocessing and classification, there has not been a research effort that focuses on a cloud-scale classification analysis of microarray data using Wavelet thresholding in a Cloud environment to identify significantly expressed features. This paper proposes a novel methodology that uses Wavelet based Denoising to initialize a threshold for determination of significantly expressed genes for classification. Additionally, this research was implemented and encompassed within cloud-based distributed processing environment. The utilization of Cloud computing and Wavelet thresholding was used for the classification 14 tumor classes from the Global Cancer Map (GCM). The results proved to be more accurate than using a predefined p-value for differential expression classification. This novel methodology analyzed Wavelet based threshold features of gene expression in a Cloud environment, furthermore classifying the expression of samples by analyzing gene patterns, which inform us of biological processes. Moreover, enabling researchers to face the present and forthcoming challenges that may arise in the analysis of data in functional genomics of large microarray datasets.

Streaming fragment assignment for real-time analysis of sequencing experiments

PubMed Central

Roberts, Adam; Pachter, Lior

2013-01-01

We present eXpress, a software package for highly efficient probabilistic assignment of ambiguously mapping sequenced fragments. eXpress uses a streaming algorithm with linear run time and constant memory use. It can determine abundances of sequenced molecules in real time, and can be applied to ChIP-seq, metagenomics and other large-scale sequencing data. We demonstrate its use on RNA-seq data, showing greater efficiency than other quantification methods. PMID:23160280

Hierarchical Engine for Large-scale Infrastructure Co-Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

2017-04-24

HELICS is designed to support very-large-scale (100,000+ federates) cosimulations with off-the-shelf power-system, communication, market, and end-use tools. Other key features include cross platform operating system support, the integration of both event driven (e.g., packetized communication) and time-series (e.g., power flow) simulations, and the ability to co-iterate among federates to ensure physical model convergence at each time step.

Full-length single-cell RNA-seq applied to a viral human cancer: applications to HPV expression and splicing analysis in HeLa S3 cells.

PubMed

Wu, Liang; Zhang, Xiaolong; Zhao, Zhikun; Wang, Ling; Li, Bo; Li, Guibo; Dean, Michael; Yu, Qichao; Wang, Yanhui; Lin, Xinxin; Rao, Weijian; Mei, Zhanlong; Li, Yang; Jiang, Runze; Yang, Huan; Li, Fuqiang; Xie, Guoyun; Xu, Liqin; Wu, Kui; Zhang, Jie; Chen, Jianghao; Wang, Ting; Kristiansen, Karsten; Zhang, Xiuqing; Li, Yingrui; Yang, Huanming; Wang, Jian; Hou, Yong; Xu, Xun

2015-01-01

Viral infection causes multiple forms of human cancer, and HPV infection is the primary factor in cervical carcinomas. Recent single-cell RNA-seq studies highlight the tumor heterogeneity present in most cancers, but virally induced tumors have not been studied. HeLa is a well characterized HPV+ cervical cancer cell line. We developed a new high throughput platform to prepare single-cell RNA on a nanoliter scale based on a customized microwell chip. Using this method, we successfully amplified full-length transcripts of 669 single HeLa S3 cells and 40 of them were randomly selected to perform single-cell RNA sequencing. Based on these data, we obtained a comprehensive understanding of the heterogeneity of HeLa S3 cells in gene expression, alternative splicing and fusions. Furthermore, we identified a high diversity of HPV-18 expression and splicing at the single-cell level. By co-expression analysis we identified 283 E6, E7 co-regulated genes, including CDC25, PCNA, PLK4, BUB1B and IRF1 known to interact with HPV viral proteins. Our results reveal the heterogeneity of a virus-infected cell line. It not only provides a transcriptome characterization of HeLa S3 cells at the single cell level, but is a demonstration of the power of single cell RNA-seq analysis of virally infected cells and cancers.

Gene expression-based detection of radiation exposure in mice after treatment with granulocyte colony-stimulating factor and lipopolysaccharide.

PubMed

Tucker, James D; Grever, William E; Joiner, Michael C; Konski, Andre A; Thomas, Robert A; Smolinski, Joseph M; Divine, George W; Auner, Gregory W

2012-02-01

In a large-scale nuclear incident, many thousands of people may be exposed to a wide range of radiation doses. Rapid biological dosimetry will be required on an individualized basis to estimate the exposures and to make treatment decisions. To ameliorate the adverse effects of exposure, victims may be treated with one or more cytokine growth factors, including granulocyte colony-stimulating factor (G-CSF), which has therapeutic efficacy for treating radiation-induced bone marrow ablation by stimulating granulopoiesis. The existence of infections and the administration of G-CSF each may confound the ability to achieve reliable dosimetry by gene expression analysis. In this study, C57BL/6 mice were used to determine the extent to which G-CSF and lipopolysaccharide (LPS, which simulates infection by gram-negative bacteria) alter the expression of genes that are either radiation-responsive or non-responsive, i.e., show potential for use as endogenous controls. Mice were acutely exposed to (60)Co γ rays at either 0 Gy or 6 Gy. Two hours later the animals were injected with either 0.1 mg/kg of G-CSF or 0.3 mg/kg of LPS. Expression levels of 96 different gene targets were evaluated in peripheral blood after an additional 4 or 24 h using real-time quantitative PCR. The results indicate that the expression levels of some genes are altered by LPS, but altered expression after G-CSF treatment was generally not observed. The expression levels of many genes therefore retain utility for biological dosimetry or as endogenous controls. These data suggest that PCR-based quantitative gene expression analyses may have utility in radiation biodosimetry in humans even in the presence of an infection or after treatment with G-CSF.

Improvement of General Electric’s Chilled Ammonia Process with the use of Membrane Technology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Muraskin, Dave; Dube, Sanjay; Baburao, Barath

General Electric Environmental Control Solutions (formerly Alstom Power Environmental Control Systems) set out to complete the Phase 1 award requirements for a Phase II renewal application for their project selected under DOE-FOA-0001190 “Small and Large Scale Pilots for Reducing the Cost of CO 2 Capture and Compression”. The project focus was to implement several improvement concepts utilizing membrane technology at the recipient’s Chilled Ammonia Process (CAP) CO 2 capture large-scale pilot plant. The goal was to lower the overall cost of technology. During the development of costs for the preliminary techno-economic assessment (TEA), it became clear that the capital andmore » operating costs of this concept were not economically attractive. All work related to a Phase II renewal application at that point was halted as GE made the decision not to submit a Phase II renewal application. Discussions with DOE resulted in a path towards useful information produced from the design and cost work already completed on the project. With the reverse osmosis (RO) unit providing most of the cost issues, GE would provide a sensitivity analysis of the RO unit with respect to project cost. This information would be included with the Techno-Economic Analysis along with the Technology Gap Analysis.« less

SLIDE - a web-based tool for interactive visualization of large-scale -omics data.

PubMed

Ghosh, Soumita; Datta, Abhik; Tan, Kaisen; Choi, Hyungwon

2018-06-28

Data visualization is often regarded as a post hoc step for verifying statistically significant results in the analysis of high-throughput data sets. This common practice leaves a large amount of raw data behind, from which more information can be extracted. However, existing solutions do not provide capabilities to explore large-scale raw datasets using biologically sensible queries, nor do they allow user interaction based real-time customization of graphics. To address these drawbacks, we have designed an open-source, web-based tool called Systems-Level Interactive Data Exploration, or SLIDE to visualize large-scale -omics data interactively. SLIDE's interface makes it easier for scientists to explore quantitative expression data in multiple resolutions in a single screen. SLIDE is publicly available under BSD license both as an online version as well as a stand-alone version at https://github.com/soumitag/SLIDE. Supplementary Information are available at Bioinformatics online.

Predictive model for inflammation grades of chronic hepatitis B: Large-scale analysis of clinical parameters and gene expressions.

PubMed

Zhou, Weichen; Ma, Yanyun; Zhang, Jun; Hu, Jingyi; Zhang, Menghan; Wang, Yi; Li, Yi; Wu, Lijun; Pan, Yida; Zhang, Yitong; Zhang, Xiaonan; Zhang, Xinxin; Zhang, Zhanqing; Zhang, Jiming; Li, Hai; Lu, Lungen; Jin, Li; Wang, Jiucun; Yuan, Zhenghong; Liu, Jie

2017-11-01

Liver biopsy is the gold standard to assess pathological features (eg inflammation grades) for hepatitis B virus-infected patients although it is invasive and traumatic; meanwhile, several gene profiles of chronic hepatitis B (CHB) have been separately described in relatively small hepatitis B virus (HBV)-infected samples. We aimed to analyse correlations among inflammation grades, gene expressions and clinical parameters (serum alanine amino transaminase, aspartate amino transaminase and HBV-DNA) in large-scale CHB samples and to predict inflammation grades by using clinical parameters and/or gene expressions. We analysed gene expressions with three clinical parameters in 122 CHB samples by an improved regression model. Principal component analysis and machine-learning methods including Random Forest, K-nearest neighbour and support vector machine were used for analysis and further diagnosis models. Six normal samples were conducted to validate the predictive model. Significant genes related to clinical parameters were found enriching in the immune system, interferon-stimulated, regulation of cytokine production, anti-apoptosis, and etc. A panel of these genes with clinical parameters can effectively predict binary classifications of inflammation grade (area under the ROC curve [AUC]: 0.88, 95% confidence interval [CI]: 0.77-0.93), validated by normal samples. A panel with only clinical parameters was also valuable (AUC: 0.78, 95% CI: 0.65-0.86), indicating that liquid biopsy method for detecting the pathology of CHB is possible. This is the first study to systematically elucidate the relationships among gene expressions, clinical parameters and pathological inflammation grades in CHB, and to build models predicting inflammation grades by gene expressions and/or clinical parameters as well. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Co-infection with human polyomavirus BK enhances gene expression and replication of human adenovirus.

PubMed

Bil-Lula, Iwona; Woźniak, Mieczysław

2018-03-26

Immunocompromised patients are susceptible to multiple viral infections. Relevant interactions between co-infecting viruses might result from viral regulatory genes which trans-activate or repress the expression of host cell genes as well as the genes of any co-infecting virus. The aim of the current study was to show that the replication of human adenovirus 5 is enhanced by co-infection with BK polyomavirus and is associated with increased expression of proteins including early region 4 open reading frame 1 and both the large tumor antigen and small tumor antigen. Clinical samples of whole blood and urine from 156 hematopoietic stem cell transplant recipients were tested. We also inoculated adenocarcinomic human alveolar basal epithelial cells with both human adenovirus 5 and BK polyomavirus to evaluate if co-infection of viruses affected their replication. Data showed that adenovirus load was significantly higher in the plasma (mean 7.5 x 10 3  ± 8.5 x 10 2 copies/ml) and urine (mean 1.9 x 10 3  ± 8.0 x 10 2 copies/ml) of samples from patients with co-infections, in comparison to samples from patients with isolated adenovirus infection. In vitro co-infection led to an increased (8.6 times) expression of the adenovirus early region 4 open reading frame gene 48 hours post-inoculation. The expression of the early region 4 open reading frame gene positively correlated with the expression of BK polyomavirus large tumor antigen (r = 0.90, p < 0.0001) and small tumor antigen (r = 0.83, p < 0.001) genes. The enhanced expression of the early region 4 open reading frame gene due to co-infection with BK polyomavirus was associated with enhanced adenovirus, but not BK polyomavirus, replication. The current study provides evidence that co-infection of adenovirus and BK polyomavirus contributes to enhanced adenovirus replication. Data obtained from this study may have significant importance in the clinical setting.

It’s about This and That: A Description of Anaphoric Expressions in Clinical Text

PubMed Central

Wang, Yan; Melton, Genevieve B.; Pakhomov, Serguei

2011-01-01

Although anaphoric expressions are very common in biomedical and clinical documents, little work has been done to systematically characterize their use in clinical text. Samples of ‘it’, ‘this’, and ‘that’ expressions occurring in inpatient clinical notes from four metropolitan hospitals were analyzed using a combination of semi-automated and manual annotation techniques. We developed a rule-based approach to filter potential non-referential expressions. A physician then manually annotated 1000 potential referential instances to determine referent status and the antecedent of each referent expression. A distributional analysis of the three referring expressions in the entire corpus of notes demonstrates a high prevalence of anaphora and large variance in distributions of referential expressions with different notes. Our results confirm that anaphoric expressions are common in clinical texts. Effective co-reference resolution with anaphoric expressions remains an important challenge in medical natural language processing research. PMID:22195211

Large-scale atlas of microarray data reveals biological landscape of gene expression in Arabidopsis

USDA-ARS?s Scientific Manuscript database

Transcriptome datasets from thousands of samples of the model plant Arabidopsis thaliana have been collectively generated by multiple individual labs. Although integration and meta-analysis of these samples has become routine in the plant research community, it is often hampered by the lack of metad...

Sequence analysis reveals genomic factors affecting EST-SSR primer performance and polymorphism

USDA-ARS?s Scientific Manuscript database

Search for simple sequence repeat (SSR) motifs and design of flanking primers in expressed sequence tag (EST) sequences can be easily done at a large scale using bioinformatics programs. However, failed amplification and/or detection, along with lack of polymorphism, is often seen among randomly sel...

Improved L-BFGS diagonal preconditioners for a large-scale 4D-Var inversion system: application to CO2 flux constraints and analysis error calculation

NASA Astrophysics Data System (ADS)

Bousserez, Nicolas; Henze, Daven; Bowman, Kevin; Liu, Junjie; Jones, Dylan; Keller, Martin; Deng, Feng

2013-04-01

This work presents improved analysis error estimates for 4D-Var systems. From operational NWP models to top-down constraints on trace gas emissions, many of today's data assimilation and inversion systems in atmospheric science rely on variational approaches. This success is due to both the mathematical clarity of these formulations and the availability of computationally efficient minimization algorithms. However, unlike Kalman Filter-based algorithms, these methods do not provide an estimate of the analysis or forecast error covariance matrices, these error statistics being propagated only implicitly by the system. From both a practical (cycling assimilation) and scientific perspective, assessing uncertainties in the solution of the variational problem is critical. For large-scale linear systems, deterministic or randomization approaches can be considered based on the equivalence between the inverse Hessian of the cost function and the covariance matrix of analysis error. For perfectly quadratic systems, like incremental 4D-Var, Lanczos/Conjugate-Gradient algorithms have proven to be most efficient in generating low-rank approximations of the Hessian matrix during the minimization. For weakly non-linear systems though, the Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS), a quasi-Newton descent algorithm, is usually considered the best method for the minimization. Suitable for large-scale optimization, this method allows one to generate an approximation to the inverse Hessian using the latest m vector/gradient pairs generated during the minimization, m depending upon the available core memory. At each iteration, an initial low-rank approximation to the inverse Hessian has to be provided, which is called preconditioning. The ability of the preconditioner to retain useful information from previous iterations largely determines the efficiency of the algorithm. Here we assess the performance of different preconditioners to estimate the inverse Hessian of a large-scale 4D-Var system. The impact of using the diagonal preconditioners proposed by Gilbert and Le Maréchal (1989) instead of the usual Oren-Spedicato scalar will be first presented. We will also introduce new hybrid methods that combine randomization estimates of the analysis error variance with L-BFGS diagonal updates to improve the inverse Hessian approximation. Results from these new algorithms will be evaluated against standard large ensemble Monte-Carlo simulations. The methods explored here are applied to the problem of inferring global atmospheric CO2 fluxes using remote sensing observations, and are intended to be integrated with the future NASA Carbon Monitoring System.

Building gene co-expression networks using transcriptomics data for systems biology investigations: Comparison of methods using microarray data

PubMed Central

Kadarmideen, Haja N; Watson-haigh, Nathan S

2012-01-01

Gene co-expression networks (GCN), built using high-throughput gene expression data are fundamental aspects of systems biology. The main aims of this study were to compare two popular approaches to building and analysing GCN. We use real ovine microarray transcriptomics datasets representing four different treatments with Metyrapone, an inhibitor of cortisol biosynthesis. We conducted several microarray quality control checks before applying GCN methods to filtered datasets. Then we compared the outputs of two methods using connectivity as a criterion, as it measures how well a node (gene) is connected within a network. The two GCN construction methods used were, Weighted Gene Co-expression Network Analysis (WGCNA) and Partial Correlation and Information Theory (PCIT) methods. Nodes were ranked based on their connectivity measures in each of the four different networks created by WGCNA and PCIT and node ranks in two methods were compared to identify those nodes which are highly differentially ranked (HDR). A total of 1,017 HDR nodes were identified across one or more of four networks. We investigated HDR nodes by gene enrichment analyses in relation to their biological relevance to phenotypes. We observed that, in contrast to WGCNA method, PCIT algorithm removes many of the edges of the most highly interconnected nodes. Removal of edges of most highly connected nodes or hub genes will have consequences for downstream analyses and biological interpretations. In general, for large GCN construction (with > 20000 genes) access to large computer clusters, particularly those with larger amounts of shared memory is recommended. PMID:23144540

Combined cistrome and transcriptome analysis of SKI in AML cells identifies SKI as a co-repressor for RUNX1

PubMed Central

Feld, Christine; Sahu, Peeyush; Frech, Miriam; Finkernagel, Florian; Nist, Andrea; Stiewe, Thorsten; Bauer, Uta-Maria; Neubauer, Andreas

2018-01-01

Abstract SKI is a transcriptional co-regulator and overexpressed in various human tumors, for example in acute myeloid leukemia (AML). SKI contributes to the origin and maintenance of the leukemic phenotype. Here, we use ChIP-seq and RNA-seq analysis to identify the epigenetic alterations induced by SKI overexpression in AML cells. We show that approximately two thirds of differentially expressed genes are up-regulated upon SKI deletion, of which >40% harbor SKI binding sites in their proximity, primarily in enhancer regions. Gene ontology analysis reveals that many of the differentially expressed genes are annotated to hematopoietic cell differentiation and inflammatory response, corroborating our finding that SKI contributes to a myeloid differentiation block in HL60 cells. We find that SKI peaks are enriched for RUNX1 consensus motifs, particularly in up-regulated SKI targets upon SKI deletion. RUNX1 ChIP-seq displays that nearly 70% of RUNX1 binding sites overlap with SKI peaks, mainly at enhancer regions. SKI and RUNX1 occupy the same genomic sites and cooperate in gene silencing. Our work demonstrates for the first time the predominant co-repressive function of SKI in AML cells on a genome-wide scale and uncovers the transcription factor RUNX1 as an important mediator of SKI-dependent transcriptional repression. PMID:29471413

Correlation set analysis: detecting active regulators in disease populations using prior causal knowledge

PubMed Central

2012-01-01

Background Identification of active causal regulators is a crucial problem in understanding mechanism of diseases or finding drug targets. Methods that infer causal regulators directly from primary data have been proposed and successfully validated in some cases. These methods necessarily require very large sample sizes or a mix of different data types. Recent studies have shown that prior biological knowledge can successfully boost a method's ability to find regulators. Results We present a simple data-driven method, Correlation Set Analysis (CSA), for comprehensively detecting active regulators in disease populations by integrating co-expression analysis and a specific type of literature-derived causal relationships. Instead of investigating the co-expression level between regulators and their regulatees, we focus on coherence of regulatees of a regulator. Using simulated datasets we show that our method performs very well at recovering even weak regulatory relationships with a low false discovery rate. Using three separate real biological datasets we were able to recover well known and as yet undescribed, active regulators for each disease population. The results are represented as a rank-ordered list of regulators, and reveals both single and higher-order regulatory relationships. Conclusions CSA is an intuitive data-driven way of selecting directed perturbation experiments that are relevant to a disease population of interest and represent a starting point for further investigation. Our findings demonstrate that combining co-expression analysis on regulatee sets with a literature-derived network can successfully identify causal regulators and help develop possible hypothesis to explain disease progression. PMID:22443377

CO 2 Storage and Enhanced Oil Recovery: Bald Unit Test Site, Mumford Hills Oil Field, Posey County, Indiana

DOE Office of Scientific and Technical Information (OSTI.GOV)

Frailey, Scott M.; Krapac, Ivan G.; Damico, James R.

2012-03-30

The Midwest Geological Sequestration Consortium (MGSC) carried out a small-scale carbon dioxide (CO 2) injection test in a sandstone within the Clore Formation (Mississippian System, Chesterian Series) in order to gauge the large-scale CO 2 storage that might be realized from enhanced oil recovery (EOR) of mature Illinois Basin oil fields via miscible liquid CO 2 flooding.

An efficient procedure for the expression and purification of HIV-1 protease from inclusion bodies.

PubMed

Nguyen, Hong-Loan Thi; Nguyen, Thuy Thi; Vu, Quy Thi; Le, Hang Thi; Pham, Yen; Trinh, Phuong Le; Bui, Thuan Phuong; Phan, Tuan-Nghia

2015-12-01

Several studies have focused on HIV-1 protease for developing drugs for treating AIDS. Recombinant HIV-1 protease is used to screen new drugs from synthetic compounds or natural substances. However, large-scale expression and purification of this enzyme is difficult mainly because of its low expression and solubility. In this study, we constructed 9 recombinant plasmids containing a sequence encoding HIV-1 protease along with different fusion tags and examined the expression of the enzyme from these plasmids. Of the 9 plasmids, pET32a(+) plasmid containing the HIV-1 protease-encoding sequence along with sequences encoding an autocleavage site GTVSFNF at the N-terminus and TEV plus 6× His tag at the C-terminus showed the highest expression of the enzyme and was selected for further analysis. The recombinant protein was isolated from inclusion bodies by using 2 tandem Q- and Ni-Sepharose columns. SDS-PAGE of the obtained HIV-1 protease produced a single band of approximately 13 kDa. The enzyme was recovered efficiently (4 mg protein/L of cell culture) and had high specific activity of 1190 nmol min(-1) mg(-1) at an optimal pH of 4.7 and optimal temperature of 37 °C. This procedure for expressing and purifying HIV-1 protease is now being scaled up to produce the enzyme on a large scale for its application. Copyright © 2015 Elsevier Inc. All rights reserved.

Demonstrating microbial co-occurrence pattern analyses within and between ecosystems

PubMed Central

Williams, Ryan J.; Howe, Adina; Hofmockel, Kirsten S.

2014-01-01

Co-occurrence patterns are used in ecology to explore interactions between organisms and environmental effects on coexistence within biological communities. Analysis of co-occurrence patterns among microbial communities has ranged from simple pairwise comparisons between all community members to direct hypothesis testing between focal species. However, co-occurrence patterns are rarely studied across multiple ecosystems or multiple scales of biological organization within the same study. Here we outline an approach to produce co-occurrence analyses that are focused at three different scales: co-occurrence patterns between ecosystems at the community scale, modules of co-occurring microorganisms within communities, and co-occurring pairs within modules that are nested within microbial communities. To demonstrate our co-occurrence analysis approach, we gathered publicly available 16S rRNA amplicon datasets to compare and contrast microbial co-occurrence at different taxonomic levels across different ecosystems. We found differences in community composition and co-occurrence that reflect environmental filtering at the community scale and consistent pairwise occurrences that may be used to infer ecological traits about poorly understood microbial taxa. However, we also found that conclusions derived from applying network statistics to microbial relationships can vary depending on the taxonomic level chosen and criteria used to build co-occurrence networks. We present our statistical analysis and code for public use in analysis of co-occurrence patterns across microbial communities. PMID:25101065

Computerized image analysis for quantitative neuronal phenotyping in zebrafish.

PubMed

Liu, Tianming; Lu, Jianfeng; Wang, Ye; Campbell, William A; Huang, Ling; Zhu, Jinmin; Xia, Weiming; Wong, Stephen T C

2006-06-15

An integrated microscope image analysis pipeline is developed for automatic analysis and quantification of phenotypes in zebrafish with altered expression of Alzheimer's disease (AD)-linked genes. We hypothesize that a slight impairment of neuronal integrity in a large number of zebrafish carrying the mutant genotype can be detected through the computerized image analysis method. Key functionalities of our zebrafish image processing pipeline include quantification of neuron loss in zebrafish embryos due to knockdown of AD-linked genes, automatic detection of defective somites, and quantitative measurement of gene expression levels in zebrafish with altered expression of AD-linked genes or treatment with a chemical compound. These quantitative measurements enable the archival of analyzed results and relevant meta-data. The structured database is organized for statistical analysis and data modeling to better understand neuronal integrity and phenotypic changes of zebrafish under different perturbations. Our results show that the computerized analysis is comparable to manual counting with equivalent accuracy and improved efficacy and consistency. Development of such an automated data analysis pipeline represents a significant step forward to achieve accurate and reproducible quantification of neuronal phenotypes in large scale or high-throughput zebrafish imaging studies.

Design of high-activity single-atom catalysts via n-p codoping

NASA Astrophysics Data System (ADS)

Wang, Xiaonan; Zhou, Haiyan; Zhang, Xiaoyang; Jia, Jianfeng; Wu, Haishun

2018-03-01

The large-scale synthesis of stable single-atom catalysts (SACs) in experiments remains a significant challenge due to high surface free energy of metal atom. Here, we propose a concise n-p codoping approach, and find it can not only disperse the relatively inexpensive metal, copper (Cu), onto boron (B)-doped graphene, but also result in high-activity SACs. We use CO oxidation on B/Cu codoped graphene as a prototype example, and demonstrate that: (1) a stable SAC can be formed by stronger electrostatic attraction between the metal atom (n-type Cu) and support (p-type B-doped graphene). (2) the energy barrier of the prototype CO oxidation on B/Cu codoped graphene is 0.536 eV by the Eley-Rideal mechanism. Further analysis shows that the spin selection rule can provide well theoretical insight into high activity of our suggested SAC. The concept of n-p codoping may lead to new strategy in large-scale synthesis of stable single-atom catalysts.

A gene encoding maize caffeoyl-CoA O-methyltransferase confers quantitative resistance to multiple pathogens.

PubMed

Yang, Qin; He, Yijian; Kabahuma, Mercy; Chaya, Timothy; Kelly, Amy; Borrego, Eli; Bian, Yang; El Kasmi, Farid; Yang, Li; Teixeira, Paulo; Kolkman, Judith; Nelson, Rebecca; Kolomiets, Michael; L Dangl, Jeffery; Wisser, Randall; Caplan, Jeffrey; Li, Xu; Lauter, Nick; Balint-Kurti, Peter

2017-09-01

Alleles that confer multiple disease resistance (MDR) are valuable in crop improvement, although the molecular mechanisms underlying their functions remain largely unknown. A quantitative trait locus, qMdr 9.02 , associated with resistance to three important foliar maize diseases-southern leaf blight, gray leaf spot and northern leaf blight-has been identified on maize chromosome 9. Through fine-mapping, association analysis, expression analysis, insertional mutagenesis and transgenic validation, we demonstrate that ZmCCoAOMT2, which encodes a caffeoyl-CoA O-methyltransferase associated with the phenylpropanoid pathway and lignin production, is the gene within qMdr 9.02 conferring quantitative resistance to both southern leaf blight and gray leaf spot. We suggest that resistance might be caused by allelic variation at the level of both gene expression and amino acid sequence, thus resulting in differences in levels of lignin and other metabolites of the phenylpropanoid pathway and regulation of programmed cell death.

Proteomic profiling of halloysite clay nanotube exposure in intestinal cell co-culture

PubMed Central

Lai, Xianyin; Agarwal, Mangilal; Lvov, Yuri M.; Pachpande, Chetan; Varahramyan, Kody; Witzmann, Frank A.

2013-01-01

Halloysite is aluminosilicate clay with a hollow tubular structure with nanoscale internal and external diameters. Assessment of halloysite biocompatibility has gained importance in view of its potential application in oral drug delivery. To investigate the effect of halloysite nanotubes on an in vitro model of the large intestine, Caco-2/HT29-MTX cells in monolayer co-culture were exposed to nanotubes for toxicity tests and proteomic analysis. Results indicate that halloysite exhibits a high degree of biocompatibility characterized by an absence of cytotoxicity, in spite of elevated pro-inflammatory cytokine release. Exposure-specific changes in expression were observed among 4081 proteins analyzed. Bioinformatic analysis of differentially expressed protein profiles suggest that halloysite stimulates processes related to cell growth and proliferation, subtle responses to cell infection, irritation and injury, enhanced antioxidant capability, and an overall adaptive response to exposure. These potentially relevant functional effects warrant further investigation in in vivo models and suggest that chronic or bolus occupational exposure to halloysite nanotubes may have unintended outcomes. PMID:23606564

Skin Transcriptomes of common bottlenose dolphins (Tursiops truncatus) from the northern Gulf of Mexico and southeastern U.S. Atlantic coasts.

PubMed

Neely, Marion G; Morey, Jeanine S; Anderson, Paul; Balmer, Brian C; Ylitalo, Gina M; Zolman, Eric S; Speakman, Todd R; Sinclair, Carrie; Bachman, Melannie J; Huncik, Kevin; Kucklick, John; Rosel, Patricia E; Mullin, Keith D; Rowles, Teri K; Schwacke, Lori H; Van Dolah, Frances M

2018-04-01

Common bottlenose dolphins serve as sentinels for the health of their coastal environments as they are susceptible to health impacts from anthropogenic inputs through both direct exposure and food web magnification. Remote biopsy samples have been widely used to reveal contaminant burdens in free-ranging bottlenose dolphins, but do not address the health consequences of this exposure. To gain insight into whether remote biopsies can also identify health impacts associated with contaminant burdens, we employed RNA sequencing (RNA-seq) to interrogate the transcriptomes of remote skin biopsies from 116 bottlenose dolphins from the northern Gulf of Mexico and southeastern U.S. Atlantic coasts. Gene expression was analyzed using principal component analysis, differential expression testing, and gene co-expression networks, and the results correlated to season, location, and contaminant burden. Season had a significant impact, with over 60% of genes differentially expressed between spring/summer and winter months. Geographic location exhibited lesser effects on the transcriptome, with 23.5% of genes differentially expressed between the northern Gulf of Mexico and the southeastern U.S. Atlantic locations. Despite a large overlap between the seasonal and geographical gene sets, the pathways altered in the observed gene expression profiles were somewhat distinct. Co-regulated gene modules and differential expression analysis both identified epidermal development and cellular architecture pathways to be expressed at lower levels in animals from the northern Gulf of Mexico. Although contaminant burdens measured were not significantly different between regions, some correlation with contaminant loads in individuals was observed among co-expressed gene modules, but these did not include classical detoxification pathways. Instead, this study identified other, possibly downstream pathways, including those involved in cellular architecture, immune response, and oxidative stress, that may prove to be contaminant responsive markers in bottlenose dolphin skin. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Biological mechanism analysis of acute renal allograft rejection: integrated of mRNA and microRNA expression profiles.

PubMed

Huang, Shi-Ming; Zhao, Xia; Zhao, Xue-Mei; Wang, Xiao-Ying; Li, Shan-Shan; Zhu, Yu-Hui

2014-01-01

Renal transplantation is the preferred method for most patients with end-stage renal disease, however, acute renal allograft rejection is still a major risk factor for recipients leading to renal injury. To improve the early diagnosis and treatment of acute rejection, study on the molecular mechanism of it is urgent. MicroRNA (miRNA) expression profile and mRNA expression profile of acute renal allograft rejection and well-functioning allograft downloaded from ArrayExpress database were applied to identify differentially expressed (DE) miRNAs and DE mRNAs. DE miRNAs targets were predicted by combining five algorithm. By overlapping the DE mRNAs and DE miRNAs targets, common genes were obtained. Differentially co-expressed genes (DCGs) were identified by differential co-expression profile (DCp) and differential co-expression enrichment (DCe) methods in Differentially Co-expressed Genes and Links (DCGL) package. Then, co-expression network of DCGs and the cluster analysis were performed. Functional enrichment analysis for DCGs was undergone. A total of 1270 miRNA targets were predicted and 698 DE mRNAs were obtained. While overlapping miRNA targets and DE mRNAs, 59 common genes were gained. We obtained 103 DCGs and 5 transcription factors (TFs) based on regulatory impact factors (RIF), then built the regulation network of miRNA targets and DE mRNAs. By clustering the co-expression network, 5 modules were obtained. Thereinto, module 1 had the highest degree and module 2 showed the most number of DCGs and common genes. TF CEBPB and several common genes, such as RXRA, BASP1 and AKAP10, were mapped on the co-expression network. C1R showed the highest degree in the network. These genes might be associated with human acute renal allograft rejection. We conducted biological analysis on integration of DE mRNA and DE miRNA in acute renal allograft rejection, displayed gene expression patterns and screened out genes and TFs that may be related to acute renal allograft rejection.

Biological mechanism analysis of acute renal allograft rejection: integrated of mRNA and microRNA expression profiles

PubMed Central

Huang, Shi-Ming; Zhao, Xia; Zhao, Xue-Mei; Wang, Xiao-Ying; Li, Shan-Shan; Zhu, Yu-Hui

2014-01-01

Objectives: Renal transplantation is the preferred method for most patients with end-stage renal disease, however, acute renal allograft rejection is still a major risk factor for recipients leading to renal injury. To improve the early diagnosis and treatment of acute rejection, study on the molecular mechanism of it is urgent. Methods: MicroRNA (miRNA) expression profile and mRNA expression profile of acute renal allograft rejection and well-functioning allograft downloaded from ArrayExpress database were applied to identify differentially expressed (DE) miRNAs and DE mRNAs. DE miRNAs targets were predicted by combining five algorithm. By overlapping the DE mRNAs and DE miRNAs targets, common genes were obtained. Differentially co-expressed genes (DCGs) were identified by differential co-expression profile (DCp) and differential co-expression enrichment (DCe) methods in Differentially Co-expressed Genes and Links (DCGL) package. Then, co-expression network of DCGs and the cluster analysis were performed. Functional enrichment analysis for DCGs was undergone. Results: A total of 1270 miRNA targets were predicted and 698 DE mRNAs were obtained. While overlapping miRNA targets and DE mRNAs, 59 common genes were gained. We obtained 103 DCGs and 5 transcription factors (TFs) based on regulatory impact factors (RIF), then built the regulation network of miRNA targets and DE mRNAs. By clustering the co-expression network, 5 modules were obtained. Thereinto, module 1 had the highest degree and module 2 showed the most number of DCGs and common genes. TF CEBPB and several common genes, such as RXRA, BASP1 and AKAP10, were mapped on the co-expression network. C1R showed the highest degree in the network. These genes might be associated with human acute renal allograft rejection. Conclusions: We conducted biological analysis on integration of DE mRNA and DE miRNA in acute renal allograft rejection, displayed gene expression patterns and screened out genes and TFs that may be related to acute renal allograft rejection. PMID:25664019

Open-source framework for power system transmission and distribution dynamics co-simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Renke; Fan, Rui; Daily, Jeff

The promise of the smart grid entails more interactions between the transmission and distribution networks, and there is an immediate need for tools to provide the comprehensive modelling and simulation required to integrate operations at both transmission and distribution levels. Existing electromagnetic transient simulators can perform simulations with integration of transmission and distribution systems, but the computational burden is high for large-scale system analysis. For transient stability analysis, currently there are only separate tools for simulating transient dynamics of the transmission and distribution systems. In this paper, we introduce an open source co-simulation framework “Framework for Network Co-Simulation” (FNCS), togethermore » with the decoupled simulation approach that links existing transmission and distribution dynamic simulators through FNCS. FNCS is a middleware interface and framework that manages the interaction and synchronization of the transmission and distribution simulators. Preliminary testing results show the validity and capability of the proposed open-source co-simulation framework and the decoupled co-simulation methodology.« less

Intermediate-Scale Investigation of Capillary and Dissolution Trapping during CO2 Injection and Post-Injection in Heterogeneous Geological Formations

NASA Astrophysics Data System (ADS)

Cihan, A.; Illangasekare, T. H.; Zhou, Q.; Birkholzer, J. T.; Rodriguez, D.

2010-12-01

The capillary and dissolution trapping processes are believed to be major trapping mechanisms during CO2 injection and post-injection in heterogeneous subsurface environments. These processes are important at relatively shorter time periods compared to mineralization and have a strong impact on storage capacity and leakage risks, and they are suitable to investigate at reasonable times in the laboratory. The objectives of the research presented is to investigate the effect of the texture transitions and variability in heterogeneous field formations on the effective capillary and dissolution trapping at the field scale through multistage analysis comprising of experimental and modeling studies. A series of controlled experiments in intermediate-scale test tanks are proposed to investigate the key processes involving (1) viscous fingering of free-phase CO2 along high-permeability (or high-K) fast flow pathways, (2) dynamic intrusion of CO2 from high-K zones into low-K zones by capillarity (as well as buoyancy), (3) diffusive transport of dissolved CO2 into low-K zones across large interface areas, and (4) density-driven convective mass transfer into CO2-free regions. The test tanks contain liquid sampling ports to measure spatial and temporal changes in concentration of dissolved fluid as the injected fluid migrates. In addition to visualization and capturing images through digital photography, X-ray and gamma attenuation methods are used to measure phase saturations. Heterogeneous packing configurations are created with tightly packed sands ranging from very fine to medium fine to mimic sedimentary rocks at potential storage formations. Effect of formation type, injection pressure and injection rate on trapped fluid fraction are quantified. Macroscopic variables such as saturation, pressure and concentration that are measured will be used for testing the existing macroscopic models. The applicability of multiphase flow theories will be evaluated by comparing with the experimental data. Existing upscaling methodologies will be tested using experimental data for accurately estimating parameters of the large-scale heterogeneous porous media. This paper presents preliminary results from the initial-stage experiments and the modeling analysis. In the future, we will design and conduct a comprehensive set of experiments for improving the fundamental understanding of the processes, and refine and calibrate the models simulating the effective capillary and dissolution trapping with an ultimate goal to design efficient and safe storage schemes.

Measurements and modeling of CO 2 concentration and isotopes to improve process-level understanding of Arctic and boreal carbon cycling. Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keeling, Ralph F.

The major goal of this project was to improve understanding of processes that control the exchanges of CO 2 between the atmosphere and the land biosphere on decadal and longer time scales. The approach involves measuring the changes in atmospheric CO 2 concentration and the isotopes of CO 2 ( 13C/ 12C and 18O/ 16O) at background stations and uses these and other datasets to challenge and improve numerical models of the earth system. The project particularly emphasized the use of these data to improve understanding of changes occurring in boreal and arctic ecosystems over the past 50 years andmore » to seek from these data improved understanding of large-scale processes impacting carbon cycling, such as the responses to warming, CO 2 fertilization, and disturbance. The project also led to advances in the understanding of changes in water-use efficiency of land ecosystems globally based on trends in 13C/ 12C. The core element of this project was providing partial support for continuing measurements of CO 2 concentrations and isotopes from the Scripps CO 2 program, initiated by C. D. Keeling in the 1960s. The measurements included analysis of flasks collected at an array of ten stations distributed from the Arctic to the Antarctic. The project also supported modeling studies and interpretive work to help understand the origins of the large ~50% increase in the amplitude of the atmospheric CO 2 cycle detected at high northern latitudes between 1960 and present and to understand the long-term trend in carbon 13C/ 12C of CO 2. The seasonal cycle work was advanced through collaborations with colleagues at MPI Jena and Imperial College« less

Resolving stem and progenitor cells in the adult mouse incisor through gene co-expression analysis

PubMed Central

Seidel, Kerstin; Marangoni, Pauline; Tang, Cynthia; Houshmand, Bahar; Du, Wen; Maas, Richard L; Murray, Steven; Oldham, Michael C; Klein, Ophir D

2017-01-01

Investigations into stem cell-fueled renewal of an organ benefit from an inventory of cell type-specific markers and a deep understanding of the cellular diversity within stem cell niches. Using the adult mouse incisor as a model for a continuously renewing organ, we performed an unbiased analysis of gene co-expression relationships to identify modules of co-expressed genes that represent differentiated cells, transit-amplifying cells, and residents of stem cell niches. Through in vivo lineage tracing, we demonstrated the power of this approach by showing that co-expression module members Lrig1 and Igfbp5 define populations of incisor epithelial and mesenchymal stem cells. We further discovered that two adjacent mesenchymal tissues, the periodontium and dental pulp, are maintained by distinct pools of stem cells. These findings reveal novel mechanisms of incisor renewal and illustrate how gene co-expression analysis of intact biological systems can provide insights into the transcriptional basis of cellular identity. DOI: http://dx.doi.org/10.7554/eLife.24712.001 PMID:28475038

Large Scale Cross Drive Correlation Of Digital Media

DTIC Science & Technology

2016-03-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS LARGE SCALE CROSS-DRIVE CORRELATION OF DIGITAL MEDIA by Joseph Van Bruaene March 2016 Thesis Co...CROSS-DRIVE CORRELATION OF DIGITAL MEDIA 5. FUNDING NUMBERS 6. AUTHOR(S) Joseph Van Bruaene 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval...the ability to make large scale cross-drive correlations among a large corpus of digital media becomes increasingly important. We propose a

Expression of the fructose receptor BmGr9 and its involvement in the promotion of feeding, suggested by its co-expression with neuropeptide F1 in Bombyx mori.

PubMed

Mang, Dingze; Shu, Min; Tanaka, Shiho; Nagata, Shinji; Takada, Tomoyuki; Endo, Haruka; Kikuta, Shingo; Tabunoki, Hiroko; Iwabuchi, Kikuo; Sato, Ryoichi

2016-08-01

Insect gustatory receptors (Grs) are members of a large family of proteins with seven transmembrane domains that provide insects with the ability to detect chemical signals critical for feeding, mating, and oviposition. To date, 69 Bombyx mori Grs (BmGrs) genes have been identified via genome studies. BmGr9 has been shown to respond specifically to fructose and to function as a ligand-gated ion channel selectively activated by fructose. However, the sites where this Gr are expressed remain unclear. We demonstrated using reverse transcription (RT)-PCR that BmGr9 is widely expressed in the central nervous system (CNS), as well as oral sensory organs. Additionally, immunohistochemistry was performed using anti-BmGr9 antiserum to show that BmGr9 is expressed in cells of the oral sensory organs, including the maxillary galea, maxillary palps, labrum, and labium, as well as in putative neurosecretory cells of the CNS. Furthermore, double immunohistochemical analysis showed that most BmGr9-expressing cells co-localized with putative neuropeptide F1-expressing cells in the brain, suggesting that BmGr9 is involved in the promotion of feeding behaviors. In addition, a portion of BmGr9-expressing cells in the brain co-localized with cells expressing BmGr6, a molecule of the sugar receptor clade, suggesting that sugars other than fructose are involved in the regulation of feeding behaviors in B. mori larvae. Copyright © 2016 Elsevier Ltd. All rights reserved.

Systems biology of embryonic development: Prospects for a complete understanding of the Caenorhabditis elegans embryo.

PubMed

Murray, John Isaac

2018-05-01

The convergence of developmental biology and modern genomics tools brings the potential for a comprehensive understanding of developmental systems. This is especially true for the Caenorhabditis elegans embryo because its small size, invariant developmental lineage, and powerful genetic and genomic tools provide the prospect of a cellular resolution understanding of messenger RNA (mRNA) expression and regulation across the organism. We describe here how a systems biology framework might allow large-scale determination of the embryonic regulatory relationships encoded in the C. elegans genome. This framework consists of two broad steps: (a) defining the "parts list"-all genes expressed in all cells at each time during development and (b) iterative steps of computational modeling and refinement of these models by experimental perturbation. Substantial progress has been made towards defining the parts list through imaging methods such as large-scale green fluorescent protein (GFP) reporter analysis. Imaging results are now being augmented by high-resolution transcriptome methods such as single-cell RNA sequencing, and it is likely the complete expression patterns of all genes across the embryo will be known within the next few years. In contrast, the modeling and perturbation experiments performed so far have focused largely on individual cell types or genes, and improved methods will be needed to expand them to the full genome and organism. This emerging comprehensive map of embryonic expression and regulatory function will provide a powerful resource for developmental biologists, and would also allow scientists to ask questions not accessible without a comprehensive picture. This article is categorized under: Invertebrate Organogenesis > Worms Technologies > Analysis of the Transcriptome Gene Expression and Transcriptional Hierarchies > Gene Networks and Genomics. © 2018 Wiley Periodicals, Inc.

An integrated bioinformatics approach to improve two-color microarray quality-control: impact on biological conclusions.

PubMed

van Haaften, Rachel I M; Luceri, Cristina; van Erk, Arie; Evelo, Chris T A

2009-06-01

Omics technology used for large-scale measurements of gene expression is rapidly evolving. This work pointed out the need of an extensive bioinformatics analyses for array quality assessment before and after gene expression clustering and pathway analysis. A study focused on the effect of red wine polyphenols on rat colon mucosa was used to test the impact of quality control and normalisation steps on the biological conclusions. The integration of data visualization, pathway analysis and clustering revealed an artifact problem that was solved with an adapted normalisation. We propose a possible point to point standard analysis procedure, based on a combination of clustering and data visualization for the analysis of microarray data.

Comparisons between Arabidopsis thaliana and Drosophila melanogaster in relation to Coding and Noncoding Sequence Length and Gene Expression

PubMed Central

Caldwell, Rachel; Lin, Yan-Xia; Zhang, Ren

2015-01-01

There is a continuing interest in the analysis of gene architecture and gene expression to determine the relationship that may exist. Advances in high-quality sequencing technologies and large-scale resource datasets have increased the understanding of relationships and cross-referencing of expression data to the large genome data. Although a negative correlation between expression level and gene (especially transcript) length has been generally accepted, there have been some conflicting results arising from the literature concerning the impacts of different regions of genes, and the underlying reason is not well understood. The research aims to apply quantile regression techniques for statistical analysis of coding and noncoding sequence length and gene expression data in the plant, Arabidopsis thaliana, and fruit fly, Drosophila melanogaster, to determine if a relationship exists and if there is any variation or similarities between these species. The quantile regression analysis found that the coding sequence length and gene expression correlations varied, and similarities emerged for the noncoding sequence length (5′ and 3′ UTRs) between animal and plant species. In conclusion, the information described in this study provides the basis for further exploration into gene regulation with regard to coding and noncoding sequence length. PMID:26114098

Comparative proteomic analysis of differentially expressed proteins in β-aminobutyric acid enhanced Arabidopsis thaliana tolerance to simulated acid rain.

PubMed

Liu, Tingwu; Jiang, Xinwu; Shi, Wuliang; Chen, Juan; Pei, Zhenming; Zheng, Hailei

2011-05-01

Acid rain is a worldwide environmental issue that has seriously destroyed forest ecosystems. As a highly effective and broad-spectrum plant resistance-inducing agent, β-aminobutyric acid could elevate the tolerance of Arabidopsis when subjected to simulated acid rain. Using comparative proteomic strategies, we analyzed 203 significantly varied proteins of which 175 proteins were identified responding to β-aminobutyric acid in the absence and presence of simulated acid rain. They could be divided into ten groups according to their biological functions. Among them, the majority was cell rescue, development and defense-related proteins, followed by transcription, protein synthesis, folding, modification and destination-associated proteins. Our conclusion is β-aminobutyric acid can lead to a large-scale primary metabolism change and simultaneously activate antioxidant system and salicylic acid, jasmonic acid, abscisic acid signaling pathways. In addition, β-aminobutyric acid can reinforce physical barriers to defend simulated acid rain stress. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Oncoprotein HBXIP enhances HOXB13 acetylation and co-activates HOXB13 to confer tamoxifen resistance in breast cancer.

PubMed

Liu, Bowen; Wang, Tianjiao; Wang, Huawei; Zhang, Lu; Xu, Feifei; Fang, Runping; Li, Leilei; Cai, Xiaoli; Wu, Yue; Zhang, Weiying; Ye, Lihong

2018-02-23

Resistance to tamoxifen (TAM) frequently occurs in the treatment of estrogen receptor positive (ER+) breast cancer. Accumulating evidences indicate that transcription factor HOXB13 is of great significance in TAM resistance. However, the regulation of HOXB13 in TAM-resistant breast cancer remains largely unexplored. Here, we were interested in the potential effect of HBXIP, an oncoprotein involved in the acceleration of cancer progression, on the modulation of HOXB13 in TAM resistance of breast cancer. The Kaplan-Meier plotter cancer database and GEO dataset were used to analyze the association between HBXIP expression and relapse-free survival. The correlation of HBXIP and HOXB13 in ER+ breast cancer was assessed by human tissue microarray. Immunoblotting analysis, qRT-PCR assay, immunofluorescence staining, Co-IP assay, ChIP assay, luciferase reporter gene assay, cell viability assay, and colony formation assay were performed to explore the possible molecular mechanism by which HBXIP modulates HOXB13. Cell viability assay, xenograft assay, and immunohistochemistry staining analysis were utilized to evaluate the effect of the HBXIP/HOXB13 axis on the facilitation of TAM resistance in vitro and in vivo. The analysis of the Kaplan-Meier plotter and the GEO dataset showed that mono-TAM-treated breast cancer patients with higher HBXIP expression levels had shorter relapse-free survivals than patients with lower HBXIP expression levels. Overexpression of HBXIP induced TAM resistance in ER+ breast cancer cells. The tissue microarray analysis revealed a positive association between the expression levels of HBXIP and HOXB13 in ER+ breast cancer patients. HBXIP elevated HOXB13 protein level in breast cancer cells. Mechanistically, HBXIP prevented chaperone-mediated autophagy (CMA)-dependent degradation of HOXB13 via enhancement of HOXB13 acetylation at the lysine 277 residue, causing the accumulation of HOXB13. Moreover, HBXIP was able to act as a co-activator of HOXB13 to stimulate interleukin (IL)-6 transcription in the promotion of TAM resistance. Interestingly, aspirin (ASA) suppressed the HBXIP/HOXB13 axis by decreasing HBXIP expression, overcoming TAM resistance in vitro and in vivo. Our study highlights that HBXIP enhances HOXB13 acetylation to prevent HOXB13 degradation and co-activates HOXB13 in the promotion of TAM resistance of breast cancer. Therapeutically, ASA can serve as a potential candidate for reversing TAM resistance by inhibiting HBXIP expression.

Generation and analysis of expressed sequence tags from the bone marrow of Chinese Sika deer.

PubMed

Yao, Baojin; Zhao, Yu; Zhang, Mei; Li, Juan

2012-03-01

Sika deer is one of the best-known and highly valued animals of China. Despite its economic, cultural, and biological importance, there has not been a large-scale sequencing project for Sika deer to date. With the ultimate goal of sequencing the complete genome of this organism, we first established a bone marrow cDNA library for Sika deer and generated a total of 2,025 reads. After processing the sequences, 2,017 high-quality expressed sequence tags (ESTs) were obtained. These ESTs were assembled into 1,157 unigenes, including 238 contigs and 919 singletons. Comparative analyses indicated that 888 (76.75%) of the unigenes had significant matches to sequences in the non-redundant protein database, In addition to highly expressed genes, such as stearoyl-CoA desaturase, cytochrome c oxidase, adipocyte-type fatty acid-binding protein, adiponectin and thymosin beta-4, we also obtained vascular endothelial growth factor-A and heparin-binding growth-associated molecule, both of which are of great importance for angiogenesis research. There were 244 (21.09%) unigenes with no significant match to any sequence in current protein or nucleotide databases, and these sequences may represent genes with unknown function in Sika deer. Open reading frame analysis of the sequences was performed using the getorf program. In addition, the sequences were functionally classified using the gene ontology hierarchy, clusters of orthologous groups of proteins and Kyoto encyclopedia of genes and genomes databases. Analysis of ESTs described in this paper provides an important resource for the transcriptome exploration of Sika deer, and will also facilitate further studies on functional genomics, gene discovery and genome annotation of Sika deer.

Microarray analysis and scale-free gene networks identify candidate regulators in drought-stressed roots of loblolly pine (P. taeda L.)

PubMed Central

2011-01-01

Background Global transcriptional analysis of loblolly pine (Pinus taeda L.) is challenging due to limited molecular tools. PtGen2, a 26,496 feature cDNA microarray, was fabricated and used to assess drought-induced gene expression in loblolly pine propagule roots. Statistical analysis of differential expression and weighted gene correlation network analysis were used to identify drought-responsive genes and further characterize the molecular basis of drought tolerance in loblolly pine. Results Microarrays were used to interrogate root cDNA populations obtained from 12 genotype × treatment combinations (four genotypes, three watering regimes). Comparison of drought-stressed roots with roots from the control treatment identified 2445 genes displaying at least a 1.5-fold expression difference (false discovery rate = 0.01). Genes commonly associated with drought response in pine and other plant species, as well as a number of abiotic and biotic stress-related genes, were up-regulated in drought-stressed roots. Only 76 genes were identified as differentially expressed in drought-recovered roots, indicating that the transcript population can return to the pre-drought state within 48 hours. Gene correlation analysis predicts a scale-free network topology and identifies eleven co-expression modules that ranged in size from 34 to 938 members. Network topological parameters identified a number of central nodes (hubs) including those with significant homology (E-values ≤ 2 × 10-30) to 9-cis-epoxycarotenoid dioxygenase, zeatin O-glucosyltransferase, and ABA-responsive protein. Identified hubs also include genes that have been associated previously with osmotic stress, phytohormones, enzymes that detoxify reactive oxygen species, and several genes of unknown function. Conclusion PtGen2 was used to evaluate transcriptome responses in loblolly pine and was leveraged to identify 2445 differentially expressed genes responding to severe drought stress in roots. Many of the genes identified are known to be up-regulated in response to osmotic stress in pine and other plant species and encode proteins involved in both signal transduction and stress tolerance. Gene expression levels returned to control values within a 48-hour recovery period in all but 76 transcripts. Correlation network analysis indicates a scale-free network topology for the pine root transcriptome and identifies central nodes that may serve as drivers of drought-responsive transcriptome dynamics in the roots of loblolly pine. PMID:21609476

Interpretation and evaluation of combined measurement techniques for soil CO2 efflux: Discrete surface chambers and continuous soil CO2 concentration probes

Treesearch

Diego A. Riveros-Iregui; Brian L. McGlynn; Howard E. Epstein; Daniel L. Welsch

2008-01-01

Soil CO2 efflux is a large respiratory flux from terrestrial ecosystems and a critical component of the global carbon (C) cycle. Lack of process understanding of the spatiotemporal controls on soil CO2 efflux limits our ability to extrapolate from fluxes measured at point scales to scales useful for corroboration with other ecosystem level measures of C exchange....

DEXTER: Disease-Expression Relation Extraction from Text.

PubMed

Gupta, Samir; Dingerdissen, Hayley; Ross, Karen E; Hu, Yu; Wu, Cathy H; Mazumder, Raja; Vijay-Shanker, K

2018-01-01

Gene expression levels affect biological processes and play a key role in many diseases. Characterizing expression profiles is useful for clinical research, and diagnostics and prognostics of diseases. There are currently several high-quality databases that capture gene expression information, obtained mostly from large-scale studies, such as microarray and next-generation sequencing technologies, in the context of disease. The scientific literature is another rich source of information on gene expression-disease relationships that not only have been captured from large-scale studies but have also been observed in thousands of small-scale studies. Expression information obtained from literature through manual curation can extend expression databases. While many of the existing databases include information from literature, they are limited by the time-consuming nature of manual curation and have difficulty keeping up with the explosion of publications in the biomedical field. In this work, we describe an automated text-mining tool, Disease-Expression Relation Extraction from Text (DEXTER) to extract information from literature on gene and microRNA expression in the context of disease. One of the motivations in developing DEXTER was to extend the BioXpress database, a cancer-focused gene expression database that includes data derived from large-scale experiments and manual curation of publications. The literature-based portion of BioXpress lags behind significantly compared to expression information obtained from large-scale studies and can benefit from our text-mined results. We have conducted two different evaluations to measure the accuracy of our text-mining tool and achieved average F-scores of 88.51 and 81.81% for the two evaluations, respectively. Also, to demonstrate the ability to extract rich expression information in different disease-related scenarios, we used DEXTER to extract information on differential expression information for 2024 genes in lung cancer, 115 glycosyltransferases in 62 cancers and 826 microRNA in 171 cancers. All extractions using DEXTER are integrated in the literature-based portion of BioXpress.Database URL: http://biotm.cis.udel.edu/DEXTER.

Synthesis and characterization of α-cobalt hydroxide nanobelts

NASA Astrophysics Data System (ADS)

Tian, L.; Zhu, J. L.; Chen, L.; An, B.; Liu, Q. Q.; Huang, K. L.

2011-08-01

α-Cobalt hydroxide was synthesized by a facile hydrothermal process from Co(Ac)2 and NH3·H2O in the presence of 1,3-propanediol. The large-scale-prepared cobalt hydroxide has a uniform nanobelt morphology with a considerably high aspect-ratio more than 20 which may be advantageous for exploration of their physicochemical properties. This synthetic method is convenient, economical, and controllable. The samples were characterized by powder X-ray diffraction, energy dispersive spectrum, scanning electron microscopy, transmission electron microscopy, Fourier transform infrared spectroscopy, CHN element analysis, thermogravimetric and differential-thermogravimetric analysis, which revealed the compound is lamellar structural cobalt organic-inorganic hybrid with the chemical formula of Co(OH)1.49(NH3)0.01(CO3 2-)0.22(Ac-)0.07(H2O)0.11 and single-crystalline.

Cogena, a novel tool for co-expressed gene-set enrichment analysis, applied to drug repositioning and drug mode of action discovery.

PubMed

Jia, Zhilong; Liu, Ying; Guan, Naiyang; Bo, Xiaochen; Luo, Zhigang; Barnes, Michael R

2016-05-27

Drug repositioning, finding new indications for existing drugs, has gained much recent attention as a potentially efficient and economical strategy for accelerating new therapies into the clinic. Although improvement in the sensitivity of computational drug repositioning methods has identified numerous credible repositioning opportunities, few have been progressed. Arguably the "black box" nature of drug action in a new indication is one of the main blocks to progression, highlighting the need for methods that inform on the broader target mechanism in the disease context. We demonstrate that the analysis of co-expressed genes may be a critical first step towards illumination of both disease pathology and mode of drug action. We achieve this using a novel framework, co-expressed gene-set enrichment analysis (cogena) for co-expression analysis of gene expression signatures and gene set enrichment analysis of co-expressed genes. The cogena framework enables simultaneous, pathway driven, disease and drug repositioning analysis. Cogena can be used to illuminate coordinated changes within disease transcriptomes and identify drugs acting mechanistically within this framework. We illustrate this using a psoriatic skin transcriptome, as an exemplar, and recover two widely used Psoriasis drugs (Methotrexate and Ciclosporin) with distinct modes of action. Cogena out-performs the results of Connectivity Map and NFFinder webservers in similar disease transcriptome analyses. Furthermore, we investigated the literature support for the other top-ranked compounds to treat psoriasis and showed how the outputs of cogena analysis can contribute new insight to support the progression of drugs into the clinic. We have made cogena freely available within Bioconductor or https://github.com/zhilongjia/cogena . In conclusion, by targeting co-expressed genes within disease transcriptomes, cogena offers novel biological insight, which can be effectively harnessed for drug discovery and repositioning, allowing the grouping and prioritisation of drug repositioning candidates on the basis of putative mode of action.

Model Selection for Monitoring CO2 Plume during Sequestration

DOE Office of Scientific and Technical Information (OSTI.GOV)

2014-12-31

The model selection method developed as part of this project mainly includes four steps: (1) assessing the connectivity/dynamic characteristics of a large prior ensemble of models, (2) model clustering using multidimensional scaling coupled with k-mean clustering, (3) model selection using the Bayes' rule in the reduced model space, (4) model expansion using iterative resampling of the posterior models. The fourth step expresses one of the advantages of the method: it provides a built-in means of quantifying the uncertainty in predictions made with the selected models. In our application to plume monitoring, by expanding the posterior space of models, the finalmore » ensemble of representations of geological model can be used to assess the uncertainty in predicting the future displacement of the CO2 plume. The software implementation of this approach is attached here.« less

BFDCA: A Comprehensive Tool of Using Bayes Factor for Differential Co-Expression Analysis.

PubMed

Wang, Duolin; Wang, Juexin; Jiang, Yuexu; Liang, Yanchun; Xu, Dong

2017-02-03

Comparing the gene-expression profiles between biological conditions is useful for understanding gene regulation underlying complex phenotypes. Along this line, analysis of differential co-expression (DC) has gained attention in the recent years, where genes under one condition have different co-expression patterns compared with another. We developed an R package Bayes Factor approach for Differential Co-expression Analysis (BFDCA) for DC analysis. BFDCA is unique in integrating various aspects of DC patterns (including Shift, Cross, and Re-wiring) into one uniform Bayes factor. We tested BFDCA using simulation data and experimental data. Simulation results indicate that BFDCA outperforms existing methods in accuracy and robustness of detecting DC pairs and DC modules. Results of using experimental data suggest that BFDCA can cluster disease-related genes into functional DC subunits and estimate the regulatory impact of disease-related genes well. BFDCA also achieves high accuracy in predicting case-control phenotypes by using significant DC gene pairs as markers. BFDCA is publicly available at http://dx.doi.org/10.17632/jdz4vtvnm3.1. Copyright © 2016 Elsevier Ltd. All rights reserved.

Genetic Approaches to Study Meiosis and Meiosis-Specific Gene Expression in Saccharomyces cerevisiae.

PubMed

Kassir, Yona; Stuart, David T

2017-01-01

The budding yeast Saccharomyces cerevisiae has a long history as a model organism for studies of meiosis and the cell cycle. The popularity of this yeast as a model is in large part due to the variety of genetic and cytological approaches that can be effectively performed with the cells. Cultures of the cells can be induced to synchronously progress through meiosis and sporulation allowing large-scale gene expression and biochemical studies to be performed. Additionally, the spore tetrads resulting from meiosis make it possible to characterize the haploid products of meiosis allowing investigation of meiotic recombination and chromosome segregation. Here we describe genetic methods for analysis progression of S. cerevisiae through meiosis and sporulation with an emphasis on strategies for the genetic analysis of regulators of meiosis-specific genes.

Cell-free protein synthesis: applications in proteomics and biotechnology.

PubMed

He, Mingyue

2008-01-01

Protein production is one of the key steps in biotechnology and functional proteomics. Expression of proteins in heterologous hosts (such as in E. coli) is generally lengthy and costly. Cell-free protein synthesis is thus emerging as an attractive alternative. In addition to the simplicity and speed for protein production, cell-free expression allows generation of functional proteins that are difficult to produce by in vivo systems. Recent exploitation of cell-free systems enables novel development of technologies for rapid discovery of proteins with desirable properties from very large libraries. This article reviews the recent development in cell-free systems and their application in the large scale protein analysis.

GEM2Net: from gene expression modeling to -omics networks, a new CATdb module to investigate Arabidopsis thaliana genes involved in stress response.

PubMed

Zaag, Rim; Tamby, Jean Philippe; Guichard, Cécile; Tariq, Zakia; Rigaill, Guillem; Delannoy, Etienne; Renou, Jean-Pierre; Balzergue, Sandrine; Mary-Huard, Tristan; Aubourg, Sébastien; Martin-Magniette, Marie-Laure; Brunaud, Véronique

2015-01-01

CATdb (http://urgv.evry.inra.fr/CATdb) is a database providing a public access to a large collection of transcriptomic data, mainly for Arabidopsis but also for other plants. This resource has the rare advantage to contain several thousands of microarray experiments obtained with the same technical protocol and analyzed by the same statistical pipelines. In this paper, we present GEM2Net, a new module of CATdb that takes advantage of this homogeneous dataset to mine co-expression units and decipher Arabidopsis gene functions. GEM2Net explores 387 stress conditions organized into 18 biotic and abiotic stress categories. For each one, a model-based clustering is applied on expression differences to identify clusters of co-expressed genes. To characterize functions associated with these clusters, various resources are analyzed and integrated: Gene Ontology, subcellular localization of proteins, Hormone Families, Transcription Factor Families and a refined stress-related gene list associated to publications. Exploiting protein-protein interactions and transcription factors-targets interactions enables to display gene networks. GEM2Net presents the analysis of the 18 stress categories, in which 17,264 genes are involved and organized within 681 co-expression clusters. The meta-data analyses were stored and organized to compose a dynamic Web resource. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Concordant integrative gene set enrichment analysis of multiple large-scale two-sample expression data sets.

PubMed

Lai, Yinglei; Zhang, Fanni; Nayak, Tapan K; Modarres, Reza; Lee, Norman H; McCaffrey, Timothy A

2014-01-01

Gene set enrichment analysis (GSEA) is an important approach to the analysis of coordinate expression changes at a pathway level. Although many statistical and computational methods have been proposed for GSEA, the issue of a concordant integrative GSEA of multiple expression data sets has not been well addressed. Among different related data sets collected for the same or similar study purposes, it is important to identify pathways or gene sets with concordant enrichment. We categorize the underlying true states of differential expression into three representative categories: no change, positive change and negative change. Due to data noise, what we observe from experiments may not indicate the underlying truth. Although these categories are not observed in practice, they can be considered in a mixture model framework. Then, we define the mathematical concept of concordant gene set enrichment and calculate its related probability based on a three-component multivariate normal mixture model. The related false discovery rate can be calculated and used to rank different gene sets. We used three published lung cancer microarray gene expression data sets to illustrate our proposed method. One analysis based on the first two data sets was conducted to compare our result with a previous published result based on a GSEA conducted separately for each individual data set. This comparison illustrates the advantage of our proposed concordant integrative gene set enrichment analysis. Then, with a relatively new and larger pathway collection, we used our method to conduct an integrative analysis of the first two data sets and also all three data sets. Both results showed that many gene sets could be identified with low false discovery rates. A consistency between both results was also observed. A further exploration based on the KEGG cancer pathway collection showed that a majority of these pathways could be identified by our proposed method. This study illustrates that we can improve detection power and discovery consistency through a concordant integrative analysis of multiple large-scale two-sample gene expression data sets.

Study on γH2AX Expression of Lymphocytes as a Biomarker In Radiation Biodosimetry

PubMed Central

Pan, Yan; Gao, Gang; Ruan, Jian Lei; Liu, Jian Xiang

2016-01-01

Flow cytometry analysis was used to detect the changes of γH2AX protein expression in human peripheral blood lymphocytes. In the dose-effect study, the expression of γH2AX was detected 1 h after irradiation with 60Co γ-rays at doses of 0, 0.5, 1, 2, 4, and 6 Gy. Blood was cultivated for 0, 1, 2, 4, 6, 12, and 24 h after 4 Gy 60Co γ-rays irradiation for the time-effect study. At the same time, the blood was divided into four treatment groups (ultraviolet [UV] irradiation, 60Co γ-rays irradiation, UV plus 60Co γ-rays irradiation, and control group) to detect the changes of protein expression of γH2AX. The results showed that the γH2AX protein expression was in dose-effect and time-effect relationship with 60Co γ-rays. The peak expression of γH2AX was at 1 h after 60Co γ-ray irradiation and began to decrease quickly. Compared to irradiation with 60Co γ-rays alone, the expression of γH2AX was not significantly changed after irradiation with 60Co γ-rays plus UV. Dose rate did not significantly change the expression of γH2AX. The expression of γH2AX induced by 60Co γ-rays was basically consistent with the mice in vivo and in vitro. The results revealed that the detection of γH2AX protein expression changes in peripheral blood lymphocyte by flow cytometry analysis is reasonable and may be useful for biodosimetry. PMID:28217286

Large- and Very-Large-Scale Motions in Katabatic Flows Over Steep Slopes

NASA Astrophysics Data System (ADS)

Giometto, M. G.; Fang, J.; Salesky, S.; Parlange, M. B.

2016-12-01

Evidence of large- and very-large-scale motions populating the boundary layer in katabatic flows over steep slopes is presented via direct numerical simulations (DNSs). DNSs are performed at a modified Reynolds number (Rem = 967), considering four sloping angles (α = 60°, 70°, 80° and 90°). Large coherent structures prove to be strongly dependent on the inclination of the underlying surface. Spectra and co-spectra consistently show signatures of large-scale motions (LSMs), with streamwise extension on the order of the boundary layer thickness. A second low-wavenumber mode characterizes pre-multiplied spectra and co-spectra when the slope angle is below 70°, indicative of very-large-scale motions (VLSMs). In addition, conditional sampling and averaging shows how LSMs and VLSMs are induced by counter-rotating roll modes, in agreement with findings from canonical wall-bounded flows. VLSMs contribute to the stream-wise velocity variance and shear stress in the above-jet regions up to 30% and 45% respectively, whereas both LSMs and VLSMs are inactive in the near-wall regions.

Transcriptional analysis of the Arabidopsis ovule by massively parallel signature sequencing

PubMed Central

Sánchez-León, Nidia; Arteaga-Vázquez, Mario; Alvarez-Mejía, César; Mendiola-Soto, Javier; Durán-Figueroa, Noé; Rodríguez-Leal, Daniel; Rodríguez-Arévalo, Isaac; García-Campayo, Vicenta; García-Aguilar, Marcelina; Olmedo-Monfil, Vianey; Arteaga-Sánchez, Mario; Martínez de la Vega, Octavio; Nobuta, Kan; Vemaraju, Kalyan; Meyers, Blake C.; Vielle-Calzada, Jean-Philippe

2012-01-01

The life cycle of flowering plants alternates between a predominant sporophytic (diploid) and an ephemeral gametophytic (haploid) generation that only occurs in reproductive organs. In Arabidopsis thaliana, the female gametophyte is deeply embedded within the ovule, complicating the study of the genetic and molecular interactions involved in the sporophytic to gametophytic transition. Massively parallel signature sequencing (MPSS) was used to conduct a quantitative large-scale transcriptional analysis of the fully differentiated Arabidopsis ovule prior to fertilization. The expression of 9775 genes was quantified in wild-type ovules, additionally detecting >2200 new transcripts mapping to antisense or intergenic regions. A quantitative comparison of global expression in wild-type and sporocyteless (spl) individuals resulted in 1301 genes showing 25-fold reduced or null activity in ovules lacking a female gametophyte, including those encoding 92 signalling proteins, 75 transcription factors, and 72 RNA-binding proteins not reported in previous studies based on microarray profiling. A combination of independent genetic and molecular strategies confirmed the differential expression of 28 of them, showing that they are either preferentially active in the female gametophyte, or dependent on the presence of a female gametophyte to be expressed in sporophytic cells of the ovule. Among 18 genes encoding pentatricopeptide-repeat proteins (PPRs) that show transcriptional activity in wild-type but not spl ovules, CIHUATEOTL (At4g38150) is specifically expressed in the female gametophyte and necessary for female gametogenesis. These results expand the nature of the transcriptional universe present in the ovule of Arabidopsis, and offer a large-scale quantitative reference of global expression for future genomic and developmental studies. PMID:22442422

Transcriptional analysis of the Arabidopsis ovule by massively parallel signature sequencing.

PubMed

Sánchez-León, Nidia; Arteaga-Vázquez, Mario; Alvarez-Mejía, César; Mendiola-Soto, Javier; Durán-Figueroa, Noé; Rodríguez-Leal, Daniel; Rodríguez-Arévalo, Isaac; García-Campayo, Vicenta; García-Aguilar, Marcelina; Olmedo-Monfil, Vianey; Arteaga-Sánchez, Mario; de la Vega, Octavio Martínez; Nobuta, Kan; Vemaraju, Kalyan; Meyers, Blake C; Vielle-Calzada, Jean-Philippe

2012-06-01

The life cycle of flowering plants alternates between a predominant sporophytic (diploid) and an ephemeral gametophytic (haploid) generation that only occurs in reproductive organs. In Arabidopsis thaliana, the female gametophyte is deeply embedded within the ovule, complicating the study of the genetic and molecular interactions involved in the sporophytic to gametophytic transition. Massively parallel signature sequencing (MPSS) was used to conduct a quantitative large-scale transcriptional analysis of the fully differentiated Arabidopsis ovule prior to fertilization. The expression of 9775 genes was quantified in wild-type ovules, additionally detecting >2200 new transcripts mapping to antisense or intergenic regions. A quantitative comparison of global expression in wild-type and sporocyteless (spl) individuals resulted in 1301 genes showing 25-fold reduced or null activity in ovules lacking a female gametophyte, including those encoding 92 signalling proteins, 75 transcription factors, and 72 RNA-binding proteins not reported in previous studies based on microarray profiling. A combination of independent genetic and molecular strategies confirmed the differential expression of 28 of them, showing that they are either preferentially active in the female gametophyte, or dependent on the presence of a female gametophyte to be expressed in sporophytic cells of the ovule. Among 18 genes encoding pentatricopeptide-repeat proteins (PPRs) that show transcriptional activity in wild-type but not spl ovules, CIHUATEOTL (At4g38150) is specifically expressed in the female gametophyte and necessary for female gametogenesis. These results expand the nature of the transcriptional universe present in the ovule of Arabidopsis, and offer a large-scale quantitative reference of global expression for future genomic and developmental studies.

Large-scale derived flood frequency analysis based on continuous simulation

NASA Astrophysics Data System (ADS)

Dung Nguyen, Viet; Hundecha, Yeshewatesfa; Guse, Björn; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

There is an increasing need for spatially consistent flood risk assessments at the regional scale (several 100.000 km2), in particular in the insurance industry and for national risk reduction strategies. However, most large-scale flood risk assessments are composed of smaller-scale assessments and show spatial inconsistencies. To overcome this deficit, a large-scale flood model composed of a weather generator and catchments models was developed reflecting the spatially inherent heterogeneity. The weather generator is a multisite and multivariate stochastic model capable of generating synthetic meteorological fields (precipitation, temperature, etc.) at daily resolution for the regional scale. These fields respect the observed autocorrelation, spatial correlation and co-variance between the variables. They are used as input into catchment models. A long-term simulation of this combined system enables to derive very long discharge series at many catchment locations serving as a basic for spatially consistent flood risk estimates at the regional scale. This combined model was set up and validated for major river catchments in Germany. The weather generator was trained by 53-year observation data at 528 stations covering not only the complete Germany but also parts of France, Switzerland, Czech Republic and Australia with the aggregated spatial scale of 443,931 km2. 10.000 years of daily meteorological fields for the study area were generated. Likewise, rainfall-runoff simulations with SWIM were performed for the entire Elbe, Rhine, Weser, Donau and Ems catchments. The validation results illustrate a good performance of the combined system, as the simulated flood magnitudes and frequencies agree well with the observed flood data. Based on continuous simulation this model chain is then used to estimate flood quantiles for the whole Germany including upstream headwater catchments in neighbouring countries. This continuous large scale approach overcomes the several drawbacks reported in traditional approaches for the derived flood frequency analysis and therefore is recommended for large scale flood risk case studies.

Development and reliability testing of a self-report instrument to measure the office layout as a correlate of occupational sitting.

PubMed

Duncan, Mitch J; Rashid, Mahbub; Vandelanotte, Corneel; Cutumisu, Nicoleta; Plotnikoff, Ronald C

2013-02-04

Spatial configurations of office environments assessed by Space Syntax methodologies are related to employee movement patterns. These methods require analysis of floors plans which are not readily available in large population-based studies or otherwise unavailable. Therefore a self-report instrument to assess spatial configurations of office environments using four scales was developed. The scales are: local connectivity (16 items), overall connectivity (11 items), visibility of co-workers (10 items), and proximity of co-workers (5 items). A panel cohort (N = 1154) completed an online survey, only data from individuals employed in office-based occupations (n = 307) were used to assess scale measurement properties. To assess test-retest reliability a separate sample of 37 office-based workers completed the survey on two occasions 7.7 (±3.2) days apart. Redundant scale items were eliminated using factor analysis; Chronbach's α was used to evaluate internal consistency and test re-test reliability (retest-ICC). ANOVA was employed to examine differences between office types (Private, Shared, Open) as a measure of construct validity. Generalized Linear Models were used to examine relationships between spatial configuration scales and the duration of and frequency of breaks in occupational sitting. The number of items on all scales were reduced, Chronbach's α and ICCs indicated good scale internal consistency and test re-test reliability: local connectivity (5 items; α = 0.70; retest-ICC = 0.84), overall connectivity (6 items; α = 0.86; retest-ICC = 0.87), visibility of co-workers (4 items; α = 0.78; retest-ICC = 0.86), and proximity of co-workers (3 items; α = 0.85; retest-ICC = 0.70). Significant (p ≤ 0.001) differences, in theoretically expected directions, were observed for all scales between office types, except overall connectivity. Significant associations were observed between all scales and occupational sitting behaviour (p ≤ 0.05). All scales have good measurement properties indicating the instrument may be a useful alternative to Space Syntax to examine environmental correlates of occupational sitting in population surveys.

Development and reliability testing of a self-report instrument to measure the office layout as a correlate of occupational sitting

PubMed Central

2013-01-01

Background Spatial configurations of office environments assessed by Space Syntax methodologies are related to employee movement patterns. These methods require analysis of floors plans which are not readily available in large population-based studies or otherwise unavailable. Therefore a self-report instrument to assess spatial configurations of office environments using four scales was developed. Methods The scales are: local connectivity (16 items), overall connectivity (11 items), visibility of co-workers (10 items), and proximity of co-workers (5 items). A panel cohort (N = 1154) completed an online survey, only data from individuals employed in office-based occupations (n = 307) were used to assess scale measurement properties. To assess test-retest reliability a separate sample of 37 office-based workers completed the survey on two occasions 7.7 (±3.2) days apart. Redundant scale items were eliminated using factor analysis; Chronbach’s α was used to evaluate internal consistency and test re-test reliability (retest-ICC). ANOVA was employed to examine differences between office types (Private, Shared, Open) as a measure of construct validity. Generalized Linear Models were used to examine relationships between spatial configuration scales and the duration of and frequency of breaks in occupational sitting. Results The number of items on all scales were reduced, Chronbach’s α and ICCs indicated good scale internal consistency and test re-test reliability: local connectivity (5 items; α = 0.70; retest-ICC = 0.84), overall connectivity (6 items; α = 0.86; retest-ICC = 0.87), visibility of co-workers (4 items; α = 0.78; retest-ICC = 0.86), and proximity of co-workers (3 items; α = 0.85; retest-ICC = 0.70). Significant (p ≤ 0.001) differences, in theoretically expected directions, were observed for all scales between office types, except overall connectivity. Significant associations were observed between all scales and occupational sitting behaviour (p ≤ 0.05). Conclusion All scales have good measurement properties indicating the instrument may be a useful alternative to Space Syntax to examine environmental correlates of occupational sitting in population surveys. PMID:23379485

GECKO: a complete large-scale gene expression analysis platform.

PubMed

Theilhaber, Joachim; Ulyanov, Anatoly; Malanthara, Anish; Cole, Jack; Xu, Dapeng; Nahf, Robert; Heuer, Michael; Brockel, Christoph; Bushnell, Steven

2004-12-10

Gecko (Gene Expression: Computation and Knowledge Organization) is a complete, high-capacity centralized gene expression analysis system, developed in response to the needs of a distributed user community. Based on a client-server architecture, with a centralized repository of typically many tens of thousands of Affymetrix scans, Gecko includes automatic processing pipelines for uploading data from remote sites, a data base, a computational engine implementing approximately 50 different analysis tools, and a client application. Among available analysis tools are clustering methods, principal component analysis, supervised classification including feature selection and cross-validation, multi-factorial ANOVA, statistical contrast calculations, and various post-processing tools for extracting data at given error rates or significance levels. On account of its open architecture, Gecko also allows for the integration of new algorithms. The Gecko framework is very general: non-Affymetrix and non-gene expression data can be analyzed as well. A unique feature of the Gecko architecture is the concept of the Analysis Tree (actually, a directed acyclic graph), in which all successive results in ongoing analyses are saved. This approach has proven invaluable in allowing a large (approximately 100 users) and distributed community to share results, and to repeatedly return over a span of years to older and potentially very complex analyses of gene expression data. The Gecko system is being made publicly available as free software http://sourceforge.net/projects/geckoe. In totality or in parts, the Gecko framework should prove useful to users and system developers with a broad range of analysis needs.

Identification and Characterization of Genomic Amplifications in Ovarian Serous Carcinoma

DTIC Science & Technology

2009-07-01

oncogenes, Rsf1 and Notch3, which were up-regulated in both genomic DNA and transcript levels in ovarian cancer. In a large- scale FISH analysis, Rsf1...associated with worse disease outcome, suggesting that Rsf1 could be potentially used as a prognostic marker in the future (Appendix #1). For the...over- expressed in a recurrent carcinoma. Although the follow-up study in a larger- scale sample size did not demonstrate clear amplification in NAC1

Long non-coding RNAs are associated with spatiotemporal gene expression profiles in the marine gastropod Tegula atra.

PubMed

Détrée, Camille; Núñez-Acuña, Gustavo; Tapia, Fabian; Gallardo-Escárate, Cristian

2017-06-01

Increasing evidence suggests that long non-coding RNAs (lncRNAs) play diverse roles in cellular processes, including in the regulation of embryogenesis and growth. However, little is known about the role of lncRNAs in marine invertebrates inhabiting changing environments. Therefore, the aim of this study was to present the first characterization of lncRNAs in an intertidal marine gastropod. Specifically, Tegula atra individuals were sampled in four sites of the central-northern Chilean coastline (28-31°) during summer and winter. A pipeline was constructed, and 3524 putative lncRNAs were identified from transcriptome databases specific to T. atra. These lncRNAs exhibited characteristics common to known lncRNAs, including a length shorter than coding sequences, low GC-content, and low sequence conservation. Expression analyses revealed that lncRNAs varied more in the summer. Furthermore, a majority of the differentially expressed lncRNAs were found in the southernmost population, the seasonal temperatures of which varied the greatest among all groups. Additionally, co-expression analysis found some lncRNAs strongly correlated with coding genes involved in the environmental stress response, such as heat shock proteins and metalloproteins. In contrast, other lncRNA expressions were strongly uncorrelated with genes involved in lipid/carbohydrates metabolism and cell-cell communication. This study provides the first large-scale characterization of lncRNAs in a marine gastropod, with results suggesting a putative role of lncRNAs in thermal tolerance, as well as an association with molecular mechanisms involved in the local adaptations of marine invertebrate populations. Copyright © 2017 Elsevier B.V. All rights reserved.

Potential Regulators Driving the Transition in Nonalcoholic Fatty Liver Disease: a Stage-Based View.

PubMed

Lou, Yi; Chen, Yi-Dan; Sun, Fu-Rong; Shi, Jun-Ping; Song, Yu; Yang, Jin

2017-01-01

The incidence of nonalcoholic fatty liver disease (NAFLD), ranging from mild steatosis to hepatocellular injury and inflammation, increases with the rise of obesity. However, the implications of transcription factors network in progressive NAFLD remain to be determined. A co-regulatory network approach by combining gene expression and transcription influence was utilized to dissect transcriptional regulators in different NAFLD stages. In vivo, mice models of NAFLD were used to investigate whether dysregulated expression be undertaken by transcriptional regulators. Through constructing a large-scale co-regulatory network, sample-specific regulator activity was estimated. The combinations of active regulators that drive the progression of NAFLD were identified. Next, top regulators in each stage of NAFLD were determined, and the results were validated using the different experiments and bariatric surgical samples. In particular, Adipocyte enhancer-binding protein 1 (AEBP1) showed increased transcription activity in nonalcoholic steatohepatitis (NASH). Further characterization of the AEBP1 related transcription program defined its co-regulators, targeted genes, and functional organization. The dynamics of AEBP1 and its potential targets were verified in an animal model of NAFLD. This study identifies putative functions for several transcription factors in the pathogenesis of NAFLD and may thus point to potential targets for therapeutic interventions. © 2017 The Author(s) Published by S. Karger AG, Basel.

RNA sequencing: current and prospective uses in metabolic research.

PubMed

Vikman, Petter; Fadista, Joao; Oskolkov, Nikolay

2014-10-01

Previous global RNA analysis was restricted to known transcripts in species with a defined transcriptome. Next generation sequencing has transformed transcriptomics by making it possible to analyse expressed genes with an exon level resolution from any tissue in any species without any a priori knowledge of which genes that are being expressed, splice patterns or their nucleotide sequence. In addition, RNA sequencing is a more sensitive technique compared with microarrays with a larger dynamic range, and it also allows for investigation of imprinting and allele-specific expression. This can be done for a cost that is able to compete with that of a microarray, making RNA sequencing a technique available to most researchers. Therefore RNA sequencing has recently become the state of the art with regards to large-scale RNA investigations and has to a large extent replaced microarrays. The only drawback is the large data amounts produced, which together with the complexity of the data can make a researcher spend far more time on analysis than performing the actual experiment. © 2014 Society for Endocrinology.

Predicting injection related changes in seismic properties at Kevin Dome, north central Montana, using well logs and laboratory measurements

NASA Astrophysics Data System (ADS)

Saltiel, S.; Bonner, B. P.; Ajo Franklin, J. B.

2014-12-01

Time-lapse seismic monitoring (4D) is currently the primary technique available for tracking sequestered CO2 in a geologic storage reservoir away from monitoring wells. The main seismic responses to injection are those due to direct fluid substitution, changes in differential pressure, and chemical interactions with reservoir rocks; the importance of each depends on reservoir/injection properties and temporal/spatial scales of interest. As part of the Big Sky Carbon Sequestration Partnership, we are monitoring the upcoming large scale (1 million ton+) CO2 injection in Kevin Dome, north central Montana. As part of this research, we predict the relative significance of these three effects, as an aid in design of field surveys. Analysis is undertaken using existing open-hole well log data and cores from wells drilled at producer and injector pads as well as core experiments. For this demonstration site, CO2 will be produced from a natural reservoir and re-injected down dip, where the formation is saturated with brine. Effective medium models based on borehole seismic velocity measurements predict relatively small effects (less than 40 m/s change in V¬p) due to the injection of more compressible supercritical CO2. This is due to the stiff dolomite reservoir rock, with high seismic velocities (Vp~6000 m/s, Vs~3000 m/s) and fairly low porosity (<10%). Assuming pure dolomite mineralogy, these models predict a slight increase in Vp during CO2 injection. This velocity increase is due to the lower density of CO2 relative to brine; which outweighs the small change in modulus compared to the stiff reservoir rock. We present both room pressure and in-situ P/T ultrasonic experiments using core samples obtained from the reservoir; such measurements are undertaken to access the expected seismic velocities under pressurized injection. The reservoir appears to have fairly low permeability. Large-volume injection is expected to produce large local pore pressure increases, which may have the largest immediate effect on seismic velocities. Increasing pore pressure lowers the differential pressure due to confining stress, which decreases seismic velocities by opening cracks. The magnitude of this effect depends both on rock microstructure and fracture at the field scale; core scale measurements will help separate these effects.

A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress

USDA-ARS?s Scientific Manuscript database

Functional annotations of large plant genome projects mostly provide information on gene function and gene families based on the presence of protein domains and gene homology, but not necessarily in association with gene expression or metabolic and regulatory networks. These additional annotations a...

Large-scale analysis of antisense transcription in wheat using the Affymetrix GeneChip Wheat Genome Array

USDA-ARS?s Scientific Manuscript database

Natural antisense transcripts (NATs) are transcripts of the opposite DNA strand to the sense-strand either at the same locus (cis-encoded) or a different locus (trans-encoded). They can affect gene expression at multiple stages including transcription, RNA processing and transport, and translation....

ICA model order selection of task co-activation networks.

PubMed

Ray, Kimberly L; McKay, D Reese; Fox, Peter M; Riedel, Michael C; Uecker, Angela M; Beckmann, Christian F; Smith, Stephen M; Fox, Peter T; Laird, Angela R

2013-01-01

Independent component analysis (ICA) has become a widely used method for extracting functional networks in the brain during rest and task. Historically, preferred ICA dimensionality has widely varied within the neuroimaging community, but typically varies between 20 and 100 components. This can be problematic when comparing results across multiple studies because of the impact ICA dimensionality has on the topology of its resultant components. Recent studies have demonstrated that ICA can be applied to peak activation coordinates archived in a large neuroimaging database (i.e., BrainMap Database) to yield whole-brain task-based co-activation networks. A strength of applying ICA to BrainMap data is that the vast amount of metadata in BrainMap can be used to quantitatively assess tasks and cognitive processes contributing to each component. In this study, we investigated the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components. Our findings suggest dimensionality of 20 for low model order ICA to examine large-scale brain networks, and dimensionality of 70 to provide insight into how large-scale networks fractionate into sub-networks. We also provide a functional and organizational assessment of visual, motor, emotion, and interoceptive task co-activation networks as they fractionate from low to high model-orders.

ICA model order selection of task co-activation networks

PubMed Central

Ray, Kimberly L.; McKay, D. Reese; Fox, Peter M.; Riedel, Michael C.; Uecker, Angela M.; Beckmann, Christian F.; Smith, Stephen M.; Fox, Peter T.; Laird, Angela R.

2013-01-01

Independent component analysis (ICA) has become a widely used method for extracting functional networks in the brain during rest and task. Historically, preferred ICA dimensionality has widely varied within the neuroimaging community, but typically varies between 20 and 100 components. This can be problematic when comparing results across multiple studies because of the impact ICA dimensionality has on the topology of its resultant components. Recent studies have demonstrated that ICA can be applied to peak activation coordinates archived in a large neuroimaging database (i.e., BrainMap Database) to yield whole-brain task-based co-activation networks. A strength of applying ICA to BrainMap data is that the vast amount of metadata in BrainMap can be used to quantitatively assess tasks and cognitive processes contributing to each component. In this study, we investigated the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components. Our findings suggest dimensionality of 20 for low model order ICA to examine large-scale brain networks, and dimensionality of 70 to provide insight into how large-scale networks fractionate into sub-networks. We also provide a functional and organizational assessment of visual, motor, emotion, and interoceptive task co-activation networks as they fractionate from low to high model-orders. PMID:24339802

Vertical structure of the phytoplankton community associated with a coastal plume in the Gulf of Mexico

USGS Publications Warehouse

Wawrik, B.; Paul, J.H.; Campbell, L.; Griffin, D.; Houchin, L.; Fuentes-Ortega, A.; Muller-Karger, F.

2003-01-01

Low salinity plumes of coastal origin are occasionally found far offshore, where they display a distinct color signature detectable by satellites. The impact of such plumes on carbon fixation and phytoplankton community structure in vertical profiles and on basin wide scales is poorly understood. On a research cruise in June 1999, ocean-color satellite-images (Sea-viewing Wide Field-of-view Sensor, SeaWiFS) were used in locating a Mississippi River plume in the eastern Gulf of Mexico. Profiles sampled within and outside of the plume were analyzed using flow cytometry, HPLC pigment analysis and primary production using 14C incorporation. Additionally, RubisCO large subunit (rbcL) gene expression was measured by hybridization of extracted RNA using 3 full-length RNA gene probes specific for individual phytoplankton clades. We also used a combination of RT-PCR/PCR and TA cloning in order to generate cDNA and DNA rbcL clone libraries from samples taken in the plume. Primary productivity was greatest in the low salinity surface layer of the plume. The plume was also associated with high Synechococcus counts and a strong peak in Form IA rbcL expression. Form IB rbcL (green algal) mRNA was abundant at the subsurface chlorophyll maximum (SCM), whereas Form ID rbcL (chromophytic) expression showed little vertical structure. Phylogenetic analysis of cDNA libraries demonstrated the presence of Form IA rbcL Synechococcus phylotypes in the plume. Below the plume, 2 spatially separated and genetically distinct rbcL clades of Prochlorococcus were observed. This indicated the presence of the high- and low-light adapted clades of Prochlorococcus. A large and very diverse clade of Prymnesiophytes was distributed throughout the water column, whereas a clade of closely related prasinophytes may have dominated at the SCM. These data indicate that the Mississippi river plume may dramatically alter the surface picoplankton composition of the Gulf of Mexico, with Synechococcus displacing Prochlorococcus in the surface waters.

Identification of the transcriptional regulators by expression profiling infected with hepatitis B virus.

PubMed

Chai, Xiaoqiang; Han, Yanan; Yang, Jian; Zhao, Xianxian; Liu, Yewang; Hou, Xugang; Tang, Yiheng; Zhao, Shirong; Li, Xiao

2016-02-01

The molecular pathogenesis of infection by hepatitis B virus with human is extremely complex and heterogeneous. To date the molecular information is not clearly defined despite intensive research efforts. Thus, studies aimed at transcription and regulation during virus infection or combined researches of those already known to be beneficial are needed. With the purpose of identifying the transcriptional regulators related to infection of hepatitis B virus in gene level, the gene expression profiles from some normal individuals and hepatitis B patients were analyzed in our study. In this work, the differential expressed genes were selected primarily. The several genes among those were validated in an independent set by qRT-PCR. Then the differentially co-expression analysis was conducted to identify differentially co-expressed links and differential co-expressed genes. Next, the analysis of the regulatory impact factors was performed through mapping the links and regulatory data. In order to give a further insight to these regulators, the co-expression gene modules were identified using a threshold-based hierarchical clustering method. Incidentally, the construction of the regulatory network was generated using the computer software. A total of 137,284 differentially co-expressed links and 780 differential co-expressed genes were identified. These co-expressed genes were significantly enriched inflammatory response. The results of regulatory impact factors revealed several crucial regulators related to hepatocellular carcinoma and other high-rank regulators. Meanwhile, more than one hundred co-expression gene modules were identified using clustering method. In our study, some important transcriptional regulators were identified using a computational method, which may enhance the understanding of disease mechanisms and lead to an improved treatment of hepatitis B. However, further experimental studies are required to confirm these findings. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

[Outbreak of carbon monoxide poisoning in the Ile-de-France region during the spring 2016 Seine flooding].

PubMed

Dufayet, Laurène; Médernach, Chantal; Bassi, Clément; Garnier, Robert; Langrand, Jérôme

2017-01-01

Heavy rainfall in May 2016 caused large-scale flooding of the Seine and its tributaries. Analysis of this unusual event showed that it could recur on an even larger scale. The sanitary consequences were less frequently assessed in this analysis, particularly the risk of accidental collective carbon monoxide (CO) poisoning caused by the use of combustion engine drainage pumps. We retrospectively reviewed all cases of acute accidental carbon monoxide exposure observed in the Ile-de-France region, related to the use of drainage pumps in spring and summer 2016 and notified to the Ile-de-France CO poisoning surveillance network. Five events were identified, including 45 people exposed to carbon monoxide. Thirty-four of these people were poisoned, 5 were not poisoned and insufficient data were available for 6 people. Three people showed signs of severity and 2 were treated by hyperbaric oxygen therapy. The other poisoned individuals were managed in hospital and treated by oxygen therapy. All were cured. Collective CO poisonings are common sanitary events during flooding and can be potentially severe. They can occur during the event or over the following days. Preventive measures may help to reduce the risk of CO poisoning, such as increased awareness among professionals, better information of individuals who rent these types of devices or even the use of CO detectors during their use.

DOE Office of Scientific and Technical Information (OSTI.GOV)

John, David E.; Wang, Zhaohui A.; Liu, Xuewu

River plumes deliver large quantities of nutrients to oligotrophic oceans, often resulting in significant CO 2 drawdown. To determine the relationship between expression of the major gene in carbon fixation (large subunit of ribulose-1,5-bisphosphate carboxylase/oxygenase, RuBisCO) and CO 2 dynamics, we evaluated rbcL mRNA abundance using novel quantitative PCR assays, phytoplankton cell analyses, photophysiological parameters, and pCO 2 in and around the Mississippi River plume (MRP) in the Gulf of Mexico. Lower salinity (30–32) stations were dominated by rbcL mRNA concentrations from heterokonts, such as diatoms and pelagophytes, which were at least an order of magnitude greater than haptophytes, alpha-Synechococcusmore » or high-light Prochlorococcus. However, rbcL transcript abundances were similar among these groups at oligotrophic stations (salinity 34–36). Diatom cell counts and heterokont rbcL RNA showed a strong negative correlation to seawater pCO 2. While Prochlorococcus cells did not exhibit a large difference between low and high pCO 2 water, Prochlorococcus rbcL RNA concentrations had a strong positive correlation to pCO 2, suggesting a very low level of RuBisCO RNA transcription among Prochlorococcus in the plume waters, possibly due to their relatively poor carbon concentrating mechanisms (CCMs). These results provide molecular evidence that diatom/pelagophyte productivity is largely responsible for the large CO 2 drawdown occurring in the MRP, based on the co-occurrence of elevated RuBisCO gene transcript concentrations from this group and reduced seawater pCO 2 levels. This may partly be due to efficient CCMs that enable heterokont eukaryotes such as diatoms to continue fixing CO 2 in the face of strong CO 2 drawdown. Finally, our work represents the first attempt to relate in situ microbial gene expression to contemporaneous CO 2 flux measurements in the ocean.« less

Scalable methodology for large scale building energy improvement: Relevance of calibration in model-based retrofit analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heo, Yeonsook; Augenbroe, Godfried; Graziano, Diane

2015-05-01

The increasing interest in retrofitting of existing buildings is motivated by the need to make a major contribution to enhancing building energy efficiency and reducing energy consumption and CO2 emission by the built environment. This paper examines the relevance of calibration in model-based analysis to support decision-making for energy and carbon efficiency retrofits of individual buildings and portfolios of buildings. The authors formulate a set of real retrofit decision-making situations and evaluate the role of calibration by using a case study that compares predictions and decisions from an uncalibrated model with those of a calibrated model. The case study illustratesmore » both the mechanics and outcomes of a practical alternative to the expert- and time-intense application of dynamic energy simulation models for large-scale retrofit decision-making under uncertainty.« less

Control of developmentally primed erythroid genes by combinatorial co-repressor actions

PubMed Central

Stadhouders, Ralph; Cico, Alba; Stephen, Tharshana; Thongjuea, Supat; Kolovos, Petros; Baymaz, H. Irem; Yu, Xiao; Demmers, Jeroen; Bezstarosti, Karel; Maas, Alex; Barroca, Vilma; Kockx, Christel; Ozgur, Zeliha; van Ijcken, Wilfred; Arcangeli, Marie-Laure; Andrieu-Soler, Charlotte; Lenhard, Boris; Grosveld, Frank; Soler, Eric

2015-01-01

How transcription factors (TFs) cooperate within large protein complexes to allow rapid modulation of gene expression during development is still largely unknown. Here we show that the key haematopoietic LIM-domain-binding protein-1 (LDB1) TF complex contains several activator and repressor components that together maintain an erythroid-specific gene expression programme primed for rapid activation until differentiation is induced. A combination of proteomics, functional genomics and in vivo studies presented here identifies known and novel co-repressors, most notably the ETO2 and IRF2BP2 proteins, involved in maintaining this primed state. The ETO2–IRF2BP2 axis, interacting with the NCOR1/SMRT co-repressor complex, suppresses the expression of the vast majority of archetypical erythroid genes and pathways until its decommissioning at the onset of terminal erythroid differentiation. Our experiments demonstrate that multimeric regulatory complexes feature a dynamic interplay between activating and repressing components that determines lineage-specific gene expression and cellular differentiation. PMID:26593974

Crowdsourcing scoring of immunohistochemistry images: Evaluating Performance of the Crowd and an Automated Computational Method

NASA Astrophysics Data System (ADS)

Irshad, Humayun; Oh, Eun-Yeong; Schmolze, Daniel; Quintana, Liza M.; Collins, Laura; Tamimi, Rulla M.; Beck, Andrew H.

2017-02-01

The assessment of protein expression in immunohistochemistry (IHC) images provides important diagnostic, prognostic and predictive information for guiding cancer diagnosis and therapy. Manual scoring of IHC images represents a logistical challenge, as the process is labor intensive and time consuming. Since the last decade, computational methods have been developed to enable the application of quantitative methods for the analysis and interpretation of protein expression in IHC images. These methods have not yet replaced manual scoring for the assessment of IHC in the majority of diagnostic laboratories and in many large-scale research studies. An alternative approach is crowdsourcing the quantification of IHC images to an undefined crowd. The aim of this study is to quantify IHC images for labeling of ER status with two different crowdsourcing approaches, image-labeling and nuclei-labeling, and compare their performance with automated methods. Crowdsourcing- derived scores obtained greater concordance with the pathologist interpretations for both image-labeling and nuclei-labeling tasks (83% and 87%), as compared to the pathologist concordance achieved by the automated method (81%) on 5,338 TMA images from 1,853 breast cancer patients. This analysis shows that crowdsourcing the scoring of protein expression in IHC images is a promising new approach for large scale cancer molecular pathology studies.

DCGL v2.0: an R package for unveiling differential regulation from differential co-expression.

PubMed

Yang, Jing; Yu, Hui; Liu, Bao-Hong; Zhao, Zhongming; Liu, Lei; Ma, Liang-Xiao; Li, Yi-Xue; Li, Yuan-Yuan

2013-01-01

Differential co-expression analysis (DCEA) has emerged in recent years as a novel, systematic investigation into gene expression data. While most DCEA studies or tools focus on the co-expression relationships among genes, some are developing a potentially more promising research domain, differential regulation analysis (DRA). In our previously proposed R package DCGL v1.0, we provided functions to facilitate basic differential co-expression analyses; however, the output from DCGL v1.0 could not be translated into differential regulation mechanisms in a straightforward manner. To advance from DCEA to DRA, we upgraded the DCGL package from v1.0 to v2.0. A new module named "Differential Regulation Analysis" (DRA) was designed, which consists of three major functions: DRsort, DRplot, and DRrank. DRsort selects differentially regulated genes (DRGs) and differentially regulated links (DRLs) according to the transcription factor (TF)-to-target information. DRrank prioritizes the TFs in terms of their potential relevance to the phenotype of interest. DRplot graphically visualizes differentially co-expressed links (DCLs) and/or TF-to-target links in a network context. In addition to these new modules, we streamlined the codes from v1.0. The evaluation results proved that our differential regulation analysis is able to capture the regulators relevant to the biological subject. With ample functions to facilitate differential regulation analysis, DCGL v2.0 was upgraded from a DCEA tool to a DRA tool, which may unveil the underlying differential regulation from the observed differential co-expression. DCGL v2.0 can be applied to a wide range of gene expression data in order to systematically identify novel regulators that have not yet been documented as critical. DCGL v2.0 package is available at http://cran.r-project.org/web/packages/DCGL/index.html or at our project home page http://lifecenter.sgst.cn/main/en/dcgl.jsp.

ON THE HORSESHOE DRAG OF A LOW-MASS PLANET. II. MIGRATION IN ADIABATIC DISKS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Masset, F. S.; Casoli, J., E-mail: frederic.masset@cea.f, E-mail: jules.casoli@cea.f, E-mail: frederic.masset@cea.f

2009-09-20

We evaluate the horseshoe drag exerted on a low-mass planet embedded in a gaseous disk, assuming the disk's flow in the co-orbital region to be adiabatic. We restrict this analysis to the case of a planet on a circular orbit, and we assume a steady flow in the corotating frame. We also assume that the corotational flow upstream of the U-turns is unperturbed, so that we discard saturation effects. In addition to the classical expression for the horseshoe drag in barotropic disks, which features the vortensity gradient across corotation, we find an additional term which scales with the entropy gradient,more » and whose amplitude depends on the perturbed pressure at the stagnation point of the horseshoe separatrices. This additional torque is exerted by evanescent waves launched at the horseshoe separatrices, as a consequence of an asymmetry of the horseshoe region. It has a steep dependence on the potential's softening length, suggesting that the effect can be extremely strong in the three-dimensional case. We describe the main properties of the co-orbital region (the production of vortensity during the U-turns, the appearance of vorticity sheets at the downstream separatrices, and the pressure response), and we give torque expressions suitable to this regime of migration. Side results include a weak, negative feedback on migration, due to the dependence of the location of the stagnation point on the migration rate, and a mild enhancement of the vortensity-related torque at a large entropy gradient.« less

Diurnal Transcriptome and Gene Network Represented through Sparse Modeling in Brachypodium distachyon.

PubMed

Koda, Satoru; Onda, Yoshihiko; Matsui, Hidetoshi; Takahagi, Kotaro; Yamaguchi-Uehara, Yukiko; Shimizu, Minami; Inoue, Komaki; Yoshida, Takuhiro; Sakurai, Tetsuya; Honda, Hiroshi; Eguchi, Shinto; Nishii, Ryuei; Mochida, Keiichi

2017-01-01

We report the comprehensive identification of periodic genes and their network inference, based on a gene co-expression analysis and an Auto-Regressive eXogenous (ARX) model with a group smoothly clipped absolute deviation (SCAD) method using a time-series transcriptome dataset in a model grass, Brachypodium distachyon . To reveal the diurnal changes in the transcriptome in B. distachyon , we performed RNA-seq analysis of its leaves sampled through a diurnal cycle of over 48 h at 4 h intervals using three biological replications, and identified 3,621 periodic genes through our wavelet analysis. The expression data are feasible to infer network sparsity based on ARX models. We found that genes involved in biological processes such as transcriptional regulation, protein degradation, and post-transcriptional modification and photosynthesis are significantly enriched in the periodic genes, suggesting that these processes might be regulated by circadian rhythm in B. distachyon . On the basis of the time-series expression patterns of the periodic genes, we constructed a chronological gene co-expression network and identified putative transcription factors encoding genes that might be involved in the time-specific regulatory transcriptional network. Moreover, we inferred a transcriptional network composed of the periodic genes in B. distachyon , aiming to identify genes associated with other genes through variable selection by grouping time points for each gene. Based on the ARX model with the group SCAD regularization using our time-series expression datasets of the periodic genes, we constructed gene networks and found that the networks represent typical scale-free structure. Our findings demonstrate that the diurnal changes in the transcriptome in B. distachyon leaves have a sparse network structure, demonstrating the spatiotemporal gene regulatory network over the cyclic phase transitions in B. distachyon diurnal growth.

Diffusion of CO2 in Large Crystals of Cu-BTC MOF.

PubMed

Tovar, Trenton M; Zhao, Junjie; Nunn, William T; Barton, Heather F; Peterson, Gregory W; Parsons, Gregory N; LeVan, M Douglas

2016-09-14

Carbon dioxide adsorption in metal-organic frameworks has been widely studied for applications in carbon capture and sequestration. A critical component that has been largely overlooked is the measurement of diffusion rates. This paper describes a new reproducible procedure to synthesize millimeter-scale Cu-BTC single crystals using concentrated reactants and an acetic acid modulator. Microscopic images, X-ray diffraction patterns, Brunauer-Emmett-Teller surface areas, and thermogravimetric analysis results all confirm the high quality of these Cu-BTC single crystals. The large crystal size aids in the accurate measurement of micropore diffusion coefficients. Concentration-swing frequency response performed at varying gas-phase concentrations gives diffusion coefficients that show very little dependence on the loading up to pressures of 0.1 bar. The measured micropore diffusion coefficient for CO2 in Cu-BTC is 1.7 × 10(-9) m(2)/s.

Mass production of somatic embryos expressing Escherichia coli heat-labile enterotoxin B subunit in Siberian ginseng.

PubMed

Kang, Tae-Jin; Lee, Won-Seok; Choi, Eun-Gyung; Kim, Jae-Whune; Kim, Bang-Geul; Yang, Moon-Sik

2006-01-24

The B subunit of Escherichia coli heat-labile toxin (LTB) is a potent mucosal immunogen and immunoadjuvant for co-administered antigens. In order to produce large scale of LTB for the development of edible vaccine, we used transgenic somatic embryos of Siberian ginseng, which is known as medicinal plant. When transgenic somatic embryos were cultured in 130L air-lift type bioreactor, they were developed to mature somatic embryos through somatic embryogenesis and contained approximately 0.36% LTB of the total soluble protein. Enzyme-linked immunosorbent assay indicated that the somatic embryo-synthesized LTB protein bound specifically to GM1-ganglioside, suggesting the LTB subunits formed active pentamers. Therefore, the use of the bioreactor system for expression of LTB proteins in somatic embryos allows for continuous mass production in a short-term period.

Using noble gas tracers to estimate residual CO2 saturation in the field: results from the CO2CRC Otway residual saturation and dissolution test

NASA Astrophysics Data System (ADS)

LaForce, T.; Ennis-King, J.; Paterson, L.

2013-12-01

Residual CO2 saturation is a critically important parameter in CO2 storage as it can have a large impact on the available secure storage volume and post-injection CO2 migration. A suite of single-well tests to measure residual trapping was conducted at the Otway test site in Victoria, Australia during 2011. One or more of these tests could be conducted at a prospective CO2 storage site before large-scale injection. The test involved injection of 150 tonnes of pure carbon dioxide followed by 454 tonnes of CO2-saturated formation water to drive the carbon dioxide to residual saturation. This work presents a brief overview of the full test sequence, followed by the analysis and interpretation of the tests using noble gas tracers. Prior to CO2 injection krypton (Kr) and xenon (Xe) tracers were injected and back-produced to characterise the aquifer under single-phase conditions. After CO2 had been driven to residual the two tracers were injected and produced again. The noble gases act as non-partitioning aqueous-phase tracers in the undisturbed aquifer and as partitioning tracers in the presence of residual CO2. To estimate residual saturation from the tracer test data a one-dimensional radial model of the near-well region is used. In the model there are only two independent parameters: the apparent dispersivity of each tracer and the residual CO2 saturation. Independent analysis of the Kr and Xe tracer production curves gives the same estimate of residual saturation to within the accuracy of the method. Furthermore the residual from the noble gas tracer tests is consistent with other measurements in the sequence of tests.

Systemic bioinformatics analysis of skeletal muscle gene expression profiles of sepsis

PubMed Central

Yang, Fang; Wang, Yumei

2018-01-01

Sepsis is a type of systemic inflammatory response syndrome with high morbidity and mortality. Skeletal muscle dysfunction is one of the major complications of sepsis that may also influence the outcome of sepsis. The aim of the present study was to explore and identify potential mechanisms and therapeutic targets of sepsis. Systemic bioinformatics analysis of skeletal muscle gene expression profiles from the Gene Expression Omnibus was performed. Differentially expressed genes (DEGs) in samples from patients with sepsis and control samples were screened out using the limma package. Differential co-expression and coregulation (DCE and DCR, respectively) analysis was performed based on the Differential Co-expression Analysis package to identify differences in gene co-expression and coregulation patterns between the control and sepsis groups. Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways of DEGs were identified using the Database for Annotation, Visualization and Integrated Discovery, and inflammatory, cancer and skeletal muscle development-associated biological processes and pathways were identified. DCE and DCR analysis revealed several potential therapeutic targets for sepsis, including genes and transcription factors. The results of the present study may provide a basis for the development of novel therapeutic targets and treatment methods for sepsis. PMID:29805480

IRAM 30 m large scale survey of {sup 12}CO(2-1) and {sup 13}CO(2-1) emission in the Orion molecular cloud

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berné, O.; Cernicharo, J.; Marcelino, N., E-mail: olivier.berne@irap.omp.eu

2014-11-01

Using the IRAM 30 m telescope, we have surveyed a 1 × 0.°8 part of the Orion molecular cloud in the {sup 12}CO and {sup 13}CO (2-1) lines with a maximal spatial resolution of ∼11'' and spectral resolution of ∼0.4 km s{sup –1}. The cloud appears filamentary, clumpy, and with a complex kinematical structure. We derive an estimated mass of the cloud of 7700 M {sub ☉} (half of which is found in regions with visual extinctions A{sub V} below ∼10) and a dynamical age for the nebula of the order of 0.2 Myr. The energy balance suggests that magneticmore » fields play an important role in supporting the cloud, at large and small scales. According to our analysis, the turbulent kinetic energy in the molecular gas due to outflows is comparable to turbulent kinetic energy resulting from the interaction of the cloud with the H II region. This latter feedback appears negative, i.e., the triggering of star formation by the H II region is inefficient in Orion. The reduced data as well as additional products such as the column density map are made available online (http://userpages.irap.omp.eu/∼oberne/Olivier{sub B}erne/Data).« less

Fitting a Point Cloud to a 3d Polyhedral Surface

NASA Astrophysics Data System (ADS)

Popov, E. V.; Rotkov, S. I.

2017-05-01

The ability to measure parameters of large-scale objects in a contactless fashion has a tremendous potential in a number of industrial applications. However, this problem is usually associated with an ambiguous task to compare two data sets specified in two different co-ordinate systems. This paper deals with the study of fitting a set of unorganized points to a polyhedral surface. The developed approach uses Principal Component Analysis (PCA) and Stretched grid method (SGM) to substitute a non-linear problem solution with several linear steps. The squared distance (SD) is a general criterion to control the process of convergence of a set of points to a target surface. The described numerical experiment concerns the remote measurement of a large-scale aerial in the form of a frame with a parabolic shape. The experiment shows that the fitting process of a point cloud to a target surface converges in several linear steps. The method is applicable to the geometry remote measurement of large-scale objects in a contactless fashion.

Comparative sequence analysis of the complete set of 40S ribosomal proteins in the Senegalese sole (Solea senegalensis Kaup) and Atlantic halibut (Hippoglossus hippoglossus L.) (Teleostei: Pleuronectiformes): phylogeny and tissue- and development-specific expression.

PubMed

Manchado, Manuel; Infante, Carlos; Asensio, Esther; Cañavate, Jose Pedro; Douglas, Susan E

2007-07-03

Ribosomal proteins (RPs) are key components of ribosomes, the cellular organelle responsible for protein biosynthesis in cells. Their levels can vary as a function of organism growth and development; however, some RPs have been associated with other cellular processes or extraribosomal functions. Their high representation in cDNA libraries has resulted in the increase of RP sequences available from different organisms and their proposal as appropriate molecular markers for phylogenetic analysis. The development of large-scale genomics of Senegalese sole (Solea senegalensis) and Atlantic halibut (Hippoglossus hippoglossus), two commercially important flatfish species, has made possible the identification and systematic analysis of the complete set of RP sequences for the small (40S) ribosome subunit. Amino acid sequence comparisons showed a high similarity both between these two flatfish species and with respect to other fish and human. EST analysis revealed the existence of two and four RPS27 genes in Senegalese sole and Atlantic halibut, respectively. Phylogenetic analysis clustered RPS27 in two separate clades with their fish and mammalian counterparts. Steady-state transcript levels for eight RPs (RPS2, RPS3a, RPS15, RPS27-1, RPS27-2, RPS27a, RPS28, and RPS29) in sole were quantitated during larval development and in tissues, using a real-time PCR approach. All eight RPs exhibited different expression patterns in tissues with the lowest levels in brain. On the contrary, RP transcripts increased co-ordinately after first larval feeding reducing progressively during the metamorphic process. The genomic resources and knowledge developed in this survey will provide new insights into the evolution of Pleuronectiformes. Expression data will contribute to a better understanding of RP functions in fish, especially the mechanisms that govern growth and development in larvae, with implications in aquaculture.

The opportunities and challenges of large-scale molecular approaches to songbird neurobiology

PubMed Central

Mello, C.V.; Clayton, D.F.

2014-01-01

High-through put methods for analyzing genome structure and function are having a large impact in song-bird neurobiology. Methods include genome sequencing and annotation, comparative genomics, DNA microarrays and transcriptomics, and the development of a brain atlas of gene expression. Key emerging findings include the identification of complex transcriptional programs active during singing, the robust brain expression of non-coding RNAs, evidence of profound variations in gene expression across brain regions, and the identification of molecular specializations within song production and learning circuits. Current challenges include the statistical analysis of large datasets, effective genome curations, the efficient localization of gene expression changes to specific neuronal circuits and cells, and the dissection of behavioral and environmental factors that influence brain gene expression. The field requires efficient methods for comparisons with organisms like chicken, which offer important anatomical, functional and behavioral contrasts. As sequencing costs plummet, opportunities emerge for comparative approaches that may help reveal evolutionary transitions contributing to vocal learning, social behavior and other properties that make songbirds such compelling research subjects. PMID:25280907

Co-expression of midkine and pleiotrophin predicts poor survival in human glioma.

PubMed

Ma, Jinyang; Lang, Bojuan; Wang, Xiongwei; Wang, Lei; Dong, Yuanxun; Hu, Huojun

2014-11-01

The aim of this study was to investigate whether co-expression of midkine (MK) and pleiotrophin (PTN) has prognostic relevance in human gliomas. Immunohistochemistry was used to investigate the expression of MK and PTN proteins in 168 patients with gliomas. The levels of MK and PTN mRNA in glioma tissues and paratumor tissues were evaluated in 45 paired cases by quantitative real-time polymerase chain reaction (qRT-PCR). Kaplan-Meier survival analysis was performed to assess prognostic significance. The expression levels of MK and PTN proteins in glioma tissue were both significantly higher (both p<0.001) than those in paratumor tissues on immunohistochemistry analysis, which was confirmed by qRT-PCR analysis. Additionally, the overexpression of either MK or PTN was significantly associated with the World Health Organization Grade (p=0.001 and 0.034, respectively), low Karnofsky Performance Status (KPS) score (p=0.022 and 0.001, respectively), time to recurrence (p=0.043 and 0.011, respectively) and poor overall survival (p=0.018 and 0.001, respectively). Multivariate Cox proportional-hazards regression analysis revealed that increased expressions of MK and PTN were both independent prognostic factors for poor overall survival (p=0.030 and 0.022, respectively). Furthermore, the co-expression of MK and PTN was more significantly (p=0.003) associated with adverse prognosis in patients with gliomas than the respective expression of MK or PTN alone. To our knowledge, these findings are the first to indicate that the co-expression of MK and PTN is significantly correlated with prognosis in glioma patients, suggesting that the co-expression of these proteins may be used as both an early diagnostic and independent prognostic marker. Copyright © 2014 Elsevier Ltd. All rights reserved.

Co-expression of COX-2 and 5-LO in primary glioblastoma is associated with poor prognosis.

PubMed

Wang, Xingfu; Chen, Yupeng; Zhang, Sheng; Zhang, Lifeng; Liu, Xueyong; Zhang, Li; Li, Xiaoling; Chen, Dayang

2015-11-01

Cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LO) are important factors in tumorigenesis and malignant progression; however, studies of their roles in glioblastoma have produced conflicting results. To define the frequencies of COX-2 and 5-LO expression and their correlation with clinicopathological features and prognosis, tumor tissues from 76 cases of newly diagnosed primary ordinary glioblastoma were examined for COX-2 and 5-LO expression by immunohistochemistry. The expression levels of COX-2 and 5-LO and the relationships between the co-expression of COX-2/5-LO and patient age and gender, edema index (EI), Karnofsky Performance Scale and overall survival (OS) were analyzed. COX-2 and 5-LO were expressed in 73.7 % (56/76) and 92.1 % (70/76) of the samples, respectively. Among the clinicopathological characteristics, only age (>60 years) exhibited a significant association with the high expression of COX-2. No statistically significant correlations were found in the 5-LO cohort. A significant positive correlation was revealed between the COX-2 and 5-LO scores (r = 0.374; p = 0.001). The elevated co-expression of COX-2 and 5-LO was observed primarily in the patients over the age of 60 years. Patients with a high expression of COX-2 had a significantly shorter OS (p < 0.01), whereas the immunoexpression of 5-LO was not associated with the OS of patients with glioblastoma. Survival analysis indicated that simultaneous high levels of COX-2 and 5-LO expression were significantly correlated with poor OS and, conversely, that a low/low expression pattern of these two proteins was significantly associated with better OS (p < 0.05). Moreover, the Cox multivariable proportional hazard model showed that a high expression of COX-2, high co-expression of COX-2 and 5-LO, and a high Ki-67 index were significant predictors of shorter OS in primary glioblastoma, independent of age, gender, EI, 5-LO expression and p53 status. The hazard ratios for OS were 2.347 (95 % CI 1.30-4.25, p = 0.005), 1.900 (95 % CI 1.30-2.78, p = 0.001), and 2.210 (95 % CI 1.19-4.09, p = 0.011), respectively. These results suggest that COX-2 and 5-LO play roles in tumorigenesis and the progression of primary glioblastoma and that the co-expression pattern of COX-2/5-LO may be used as an independent prognostic factor in this disease.

Directed module detection in a large-scale expression compendium.

PubMed

Fu, Qiang; Lemmens, Karen; Sanchez-Rodriguez, Aminael; Thijs, Inge M; Meysman, Pieter; Sun, Hong; Fierro, Ana Carolina; Engelen, Kristof; Marchal, Kathleen

2012-01-01

Public online microarray databases contain tremendous amounts of expression data. Mining these data sources can provide a wealth of information on the underlying transcriptional networks. In this chapter, we illustrate how the web services COLOMBOS and DISTILLER can be used to identify condition-dependent coexpression modules by exploring compendia of public expression data. COLOMBOS is designed for user-specified query-driven analysis, whereas DISTILLER generates a global regulatory network overview. The user is guided through both web services by means of a case study in which condition-dependent coexpression modules comprising a gene of interest (i.e., "directed") are identified.

Metatranscriptome Analysis of Aquifer Samples Reveals Unexpected Metabolic Lifestyles Relevant to Active Biogeochemical Cycling

NASA Astrophysics Data System (ADS)

Beller, H. R.; Jewell, T. N. M.; Karaoz, U.; Banfield, J. F.; Brodie, E.; Williams, K. H.

2015-12-01

Modern molecular ecology techniques are revealing the metabolic potential of uncultivated microorganisms, but there is still much to be learned about the actual biogeochemical roles of microbes that have cultivated relatives. Here, we present metatranscriptomic and metagenomic data from a field study that provides evidence of coupled redox processes that have not been documented in cultivated relatives and, indeed, represent strains with metabolic traits that are novel with respect to closely related isolates. The data come from omics analysis of groundwater samples collected during an experiment in which nitrate (a native electron acceptor) was injected into a perennially suboxic aquifer in Rifle (CO). Transcriptional data indicated that just two groups of chemolithoautotrophic bacteria accounted for a very large portion (~80%) of overall community gene expression: (1) members of the Fe(II)-oxidizing Gallionellaceae family and (2) strains of the S-oxidizing species, Sulfurimonas denitrificans. Metabolic lifestyles for Gallionellaceae strains that were novel compared to cultivated representatives included nitrate-dependent Fe(II) oxidation and S oxidation. Evidence for these metabolisms included highly correlated temporal expression in binned data of nitrate reductase (e.g., narGHI) genes (which have never been reported in Gallionellaceae genomes) and Fe(II) oxidation genes (e.g., mtoA) or S oxidation genes (e.g., dsrE, aprA). Of the two most active strains of S. denitrificans, only one showed strong expression of S oxidation genes, whereas the other was apparently using an unexpected (as-yet unidentified) primary electron donor. Transcriptional data added considerable interpretive value to this study, as (1) metagenomic data would not have highlighted these organisms, which had a disproportionately large role in community metabolism relative to their populations, and (2) co-expression of coupled pathway genes could not be predicted based solely on metagenomic data.

Combining classifiers to predict gene function in Arabidopsis thaliana using large-scale gene expression measurements.

PubMed

Lan, Hui; Carson, Rachel; Provart, Nicholas J; Bonner, Anthony J

2007-09-21

Arabidopsis thaliana is the model species of current plant genomic research with a genome size of 125 Mb and approximately 28,000 genes. The function of half of these genes is currently unknown. The purpose of this study is to infer gene function in Arabidopsis using machine-learning algorithms applied to large-scale gene expression data sets, with the goal of identifying genes that are potentially involved in plant response to abiotic stress. Using in house and publicly available data, we assembled a large set of gene expression measurements for A. thaliana. Using those genes of known function, we first evaluated and compared the ability of basic machine-learning algorithms to predict which genes respond to stress. Predictive accuracy was measured using ROC50 and precision curves derived through cross validation. To improve accuracy, we developed a method for combining these classifiers using a weighted-voting scheme. The combined classifier was then trained on genes of known function and applied to genes of unknown function, identifying genes that potentially respond to stress. Visual evidence corroborating the predictions was obtained using electronic Northern analysis. Three of the predicted genes were chosen for biological validation. Gene knockout experiments confirmed that all three are involved in a variety of stress responses. The biological analysis of one of these genes (At1g16850) is presented here, where it is shown to be necessary for the normal response to temperature and NaCl. Supervised learning methods applied to large-scale gene expression measurements can be used to predict gene function. However, the ability of basic learning methods to predict stress response varies widely and depends heavily on how much dimensionality reduction is used. Our method of combining classifiers can improve the accuracy of such predictions - in this case, predictions of genes involved in stress response in plants - and it effectively chooses the appropriate amount of dimensionality reduction automatically. The method provides a useful means of identifying genes in A. thaliana that potentially respond to stress, and we expect it would be useful in other organisms and for other gene functions.

IKKε and TBK1 expression in gastric cancer.

PubMed

Lee, Seung Eun; Hong, Mineui; Cho, Junhun; Lee, Jeeyun; Kim, Kyoung-Mee

2017-03-07

Inhibitor of kappa B kinase epsilon (IKKε) and TANK-binding kinase 1 (TBK1) are non-canonical IKKs. IKKε and TBK1 share the kinase domain and are similar in their ability to activate the nuclear factor-kappa B signaling pathway. IKKε and TBK1 are overexpressed through multiple mechanisms in various human cancers. However, the expression of IKKε and TBK1 in gastric cancer and their role in prognosis have not been studied.To investigate overexpression of the IKKε and TBK1 proteins in gastric cancer and their relationship with clinicopathologic factors, we performed immunohistochemical staining using a tissue microarray. Tissue microarray samples were obtained from 1,107 gastric cancer patients who underwent R0 gastrectomy with extensive lymph node dissection and adjuvant chemotherapy.We identified expression of IKKε in 150 (13.6%) and TBK1 in 38 (3.4%) gastric cancers. Furthermore, co-expression of IKKε and TBK1 was identified in 1.5% of cases. Co-expression of IKKε and TBK1 was associated with differentiated intestinal histology and earlier T stage. In a multivariate binary logistic regression model, intestinal histologic type by Lauren classification and early AJCC stage were significant predictors for expression of IKKε and TBK1 proteins in gastric cancer. Changes in IKKε and TBK1 expression may be involved in the development of intestinal-type gastric cancer. The overexpression of IKKε and TBK1 should be considered in selected patients with intestinal-type gastric cancer.In conclusion, this is the first large-scale study investigating the relationships between expression of IKKε and TBK1 and clinicopathologic features of gastric cancer. The role of IKKε and TBK1 in intestinal-type gastric cancer pathogenesis should be elucidated by further investigation.

Large scale systematic proteomic quantification from non-metastatic to metastatic colorectal cancer

NASA Astrophysics Data System (ADS)

Yin, Xuefei; Zhang, Yang; Guo, Shaowen; Jin, Hong; Wang, Wenhai; Yang, Pengyuan

2015-07-01

A systematic proteomic quantification of formalin-fixed, paraffin-embedded (FFPE) colorectal cancer tissues from stage I to stage IIIC was performed in large scale. 1017 proteins were identified with 338 proteins in quantitative changes by label free method, while 341 proteins were quantified with significant expression changes among 6294 proteins by iTRAQ method. We found that proteins related to migration expression increased and those for binding and adherent decreased during the colorectal cancer development according to the gene ontology (GO) annotation and ingenuity pathway analysis (IPA). The integrin alpha 5 (ITA5) in integrin family was focused, which was consistent with the metastasis related pathway. The expression level of ITA5 decreased in metastasis tissues and the result has been further verified by Western blotting. Another two cell migration related proteins vitronectin (VTN) and actin-related protein (ARP3) were also proved to be up-regulated by both mass spectrometry (MS) based quantification results and Western blotting. Up to now, our result shows one of the largest dataset in colorectal cancer proteomics research. Our strategy reveals a disease driven omics-pattern for the metastasis colorectal cancer.

Data processing of Martian topographic information obtained from ground-based radar and spectroscopy and from Mariners 6 and 7. Martian topography elevations: Data processing

NASA Technical Reports Server (NTRS)

Anderson, K. A.

1974-01-01

Papers are presented which were published as a result of a project involving the preparation of a topographical elevation contour map of Mars from all data sources available through 1969, as well as the observation of Mars by spectroscopic methods in 1971 to provide additional pressure data for topographic information. Topics of the papers include: the analysis of large-scale Martian topography variations - data preparation from earth based radar, earth based CO2 spectroscopy, and Mariners 6 and 7 CO2 spectroscopy; the analysis of water content in observed Martian white clouds; and Martian, lunar, and terrestrial crusts - a three-dimensional exercise in comparative geophysics.

Genome-wide transcriptomic analysis of the effects of sub-ambient atmospheric oxygen and elevated atmospheric carbon dioxide levels on gametophytes of the moss, Physcomitrella patens

PubMed Central

Shinde, Suhas; Behpouri, Ali; McElwain, Jennifer C.; Ng, Carl K.-Y.

2015-01-01

It is widely accepted that atmospheric O2 has played a key role in the development of life on Earth, as evident from the coincidence between the rise of atmospheric O2 concentrations in the Precambrian and biological evolution. Additionally, it has also been suggested that low atmospheric O2 is one of the major drivers for at least two of the five mass-extinction events in the Phanerozoic. At the molecular level, our understanding of the responses of plants to sub-ambient O2 concentrations is largely confined to studies of the responses of underground organs, e.g. roots to hypoxic conditions. Oxygen deprivation often results in elevated CO2 levels, particularly under waterlogged conditions, due to slower gas diffusion in water compared to air. In this study, changes in the transcriptome of gametophytes of the moss Physcomitrella patens arising from exposure to sub-ambient O2 of 13% (oxygen deprivation) and elevated CO2 (1500 ppmV) were examined to further our understanding of the responses of lower plants to changes in atmospheric gaseous composition. Microarray analyses revealed that the expression of a large number of genes was affected under elevated CO2 (814 genes) and sub-ambient O2 conditions (576 genes). Intriguingly, the expression of comparatively fewer numbers of genes (411 genes) was affected under a combination of both sub-ambient O2 and elevated CO2 condition (low O2–high CO2). Overall, the results point towards the effects of atmospheric changes in CO2 and O2 on transcriptional reprogramming, photosynthetic regulation, carbon metabolism, and stress responses. PMID:25948702

Genome-wide transcriptomic analysis of the effects of sub-ambient atmospheric oxygen and elevated atmospheric carbon dioxide levels on gametophytes of the moss, Physcomitrella patens.

PubMed

Shinde, Suhas; Behpouri, Ali; McElwain, Jennifer C; Ng, Carl K-Y

2015-07-01

It is widely accepted that atmospheric O2 has played a key role in the development of life on Earth, as evident from the coincidence between the rise of atmospheric O2 concentrations in the Precambrian and biological evolution. Additionally, it has also been suggested that low atmospheric O2 is one of the major drivers for at least two of the five mass-extinction events in the Phanerozoic. At the molecular level, our understanding of the responses of plants to sub-ambient O2 concentrations is largely confined to studies of the responses of underground organs, e.g. roots to hypoxic conditions. Oxygen deprivation often results in elevated CO2 levels, particularly under waterlogged conditions, due to slower gas diffusion in water compared to air. In this study, changes in the transcriptome of gametophytes of the moss Physcomitrella patens arising from exposure to sub-ambient O2 of 13% (oxygen deprivation) and elevated CO2 (1500 ppmV) were examined to further our understanding of the responses of lower plants to changes in atmospheric gaseous composition. Microarray analyses revealed that the expression of a large number of genes was affected under elevated CO2 (814 genes) and sub-ambient O2 conditions (576 genes). Intriguingly, the expression of comparatively fewer numbers of genes (411 genes) was affected under a combination of both sub-ambient O2 and elevated CO2 condition (low O2-high CO2). Overall, the results point towards the effects of atmospheric changes in CO2 and O2 on transcriptional reprogramming, photosynthetic regulation, carbon metabolism, and stress responses. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Purification and properties of insulin receptor ectodomain from large-scale mammalian cell culture.

PubMed

Cosgrove, L; Lovrecz, G O; Verkuylen, A; Cavaleri, L; Black, L A; Bentley, J D; Howlett, G J; Gray, P P; Ward, C W; McKern, N M

1995-12-01

Ectodomain of the exon 11+ form of the human insulin receptor (hIR) was expressed in the mammalian cell secretion vector pEE6.HCMV-GS, containing the glutamine synthetase gene. Following transfection of the hIR ectodomain gene into Chinese hamster ovary (CHO-K1) cells, clones were isolated by selecting for glutamine synthetase expression with methionine sulphoximine. The expression levels of ectodomain were subsequently increased by gene amplification. Production was scaled up using a 40-liter airlift fermenter in which the transfected CHO-K1 cells were cultured on microcarrier beads, initially in medium containing 10% fetal calf serum (FCS). By continuous perfusion of serum-free medium into the bioreactor, cell viability was maintained during reduction of FCS, which enabled soluble hIR ectodomain to be harvested for at least 22 days. Harvests were concentrated 20-fold by anion-exchange chromatography. Optimal recovery of ectodomain from early harvests containing large quantities of serum proteins was achieved by insulin-affinity chromatography, whereas in later harvests purification was achieved by multistep chromatography. Analysis of the purified hIR ectodomain showed that it had a molecular weight by sedimentation equilibrium analysis of 269,500. Amino-terminal amino acid sequence analysis showed that the ectodomain was correctly processed to alpha and beta chains and that glycosylation characteristics were similar to those of native hIR. The integrity of the ectodomain was demonstrated by the recognition of conformation-dependent anti-hIR antibodies and by its binding of insulin (Kd approximately 2 x 10(-9) M). These results demonstrate the successful production and purification of hIR ectodomain by processes amenable to scale-up and in a form appropriate for structure/function studies of the ligand-binding domain of the receptor.

Characterization and functional assay of a fatty acyl-CoA reductase gene in the scale insect, Ericerus pela Chavannes (Hemiptera: Coccoidae).

PubMed

Hu, Yan-Hong; Chen, Xiao-Ming; Yang, Pu; Ding, Wei-Feng

2018-04-01

Ericerus pela Chavannes (Hemiptera: Coccoidae) is an economically important scale insect because the second instar males secrete a harvestable wax-like substance. In this study, we report the molecular cloning of a fatty acyl-CoA reductase gene (EpFAR) of E. pela. We predicted a 520-aa protein with the FAR family features from the deduced amino acid sequence. The EpFAR mRNA was expressed in five tested tissues, testis, alimentary canal, fat body, Malpighian tubules, and mostly in cuticle. The EpFAR protein was localized by immunofluorescence only in the wax glands and testis. EpFAR expression in High Five insect cells documented the recombinant EpFAR reduced 26-0:(S) CoA and to its corresponding alcohol. The data illuminate the molecular mechanism for fatty alcohol biosynthesis in a beneficial insect, E. pela. © 2017 Wiley Periodicals, Inc.

Large-scale patterns in summer diffusive CH4 fluxes across boreal lakes, and contribution to diffusive C emissions.

PubMed

Rasilo, Terhi; Prairie, Yves T; Del Giorgio, Paul A

2015-03-01

Lakes are a major component of boreal landscapes, and whereas lake CO2 emissions are recognized as a major component of regional C budgets, there is still much uncertainty associated to lake CH4 fluxes. Here, we present a large-scale study of the magnitude and regulation of boreal lake summer diffusive CH4 fluxes, and their contribution to total lake carbon (C) emissions, based on in situ measurements of concentration and fluxes of CH4 and CO2 in 224 lakes across a wide range of lake type and environmental gradients in Québec. The diffusive CH4 flux was highly variable (mean 11.6 ± 26.4 SD mg m(-2)  d(-1) ), and it was positively correlated with temperature and lake nutrient status, and negatively correlated with lake area and colored dissolved organic matter (CDOM). The relationship between CH4 and CO2 concentrations fluxes was weak, suggesting major differences in their respective sources and/or regulation. For example, increasing water temperature leads to higher CH4 flux but does not significantly affect CO2 flux, whereas increasing CDOM concentration leads to higher CO2 flux but lower CH4 flux. CH4 contributed to 8 ± 23% to the total lake C emissions (CH4  + CO2 ), but 18 ± 25% to the total flux in terms of atmospheric warming potential, expressed as CO2 -equivalents. The incorporation of ebullition and plant-mediated CH4 fluxes would further increase the importance of lake CH4 . The average Q10 of CH4 flux was 3.7, once other covarying factors were accounted for, but this apparent Q10 varied with lake morphometry and was higher for shallow lakes. We conclude that global climate change and the resulting shifts in temperature will strongly influence lake CH4 fluxes across the boreal biome, but these climate effects may be altered by regional patterns in lake morphometry, nutrient status, and browning. © 2014 John Wiley & Sons Ltd.

Analysis of Pacific oyster larval proteome and its response to high-CO2.

PubMed

Dineshram, R; Wong, Kelvin K W; Xiao, Shu; Yu, Ziniu; Qian, Pei Yuan; Thiyagarajan, Vengatesen

2012-10-01

Most calcifying organisms show depressed metabolic, growth and calcification rates as symptoms to high-CO(2) due to ocean acidification (OA) process. Analysis of the global expression pattern of proteins (proteome analysis) represents a powerful tool to examine these physiological symptoms at molecular level, but its applications are inadequate. To address this knowledge gap, 2-DE coupled with mass spectrophotometer was used to compare the global protein expression pattern of oyster larvae exposed to ambient and to high-CO(2). Exposure to OA resulted in marked reduction of global protein expression with a decrease or loss of 71 proteins (18% of the expressed proteins in control), indicating a wide-spread depression of metabolic genes expression in larvae reared under OA. This is, to our knowledge, the first proteome analysis that provides insights into the link between physiological suppression and protein down-regulation under OA in oyster larvae. Copyright © 2012 Elsevier Ltd. All rights reserved.

Search for Local Variations of Atmospheric H2O and CO on Mars with PFS/Mars Express

NASA Astrophysics Data System (ADS)

Lellouch, E.; Encrenaz, T.; Fouchet, T.; Billebaud, F.; Formisano, V.; Atreya, S.; Ignatiev, N.; Moroz, V.; Maturilli, A.; Grassi, D.; Pfs Team

Spectra recorded by the PFS instrument onboard Mars Express include clear spectral signatures due to CO at 4.7 and 2.3 micron, and H2O at 1.38, 2.6 and 30-50 micron. These features can be used to determine the horizontal distribution of these species on global and local scales and to monitor it with time. Here we investigate the local variations of H2O and CO, focussing on the regions of high-altitude volcanoes. Preliminary results suggest a significant decrease of the CO mixing ratio in these regions, as was found from ISM/Phobos observations (Rosenqvist et al. Icarus 98, 254, 1992).

SARS-CoV envelope protein palmitoylation or nucleocapid association is not required for promoting virus-like particle production.

PubMed

Tseng, Ying-Tzu; Wang, Shiu-Mei; Huang, Kuo-Jung; Wang, Chin-Tien

2014-04-27

Coronavirus membrane (M) proteins are capable of interacting with nucleocapsid (N) and envelope (E) proteins. Severe acute respiratory syndrome coronavirus (SARS-CoV) M co-expression with either N or E is sufficient for producing virus-like particles (VLPs), although at a lower level compared to M, N and E co-expression. Whether E can release from cells or E/N interaction exists so as to contribute to enhanced VLP production is unknown. It also remains to be determined whether E palmitoylation or disulfide bond formation plays a role in SARS-CoV virus assembly. SARS-CoV N is released from cells through an association with E protein-containing vesicles. Further analysis suggests that domains involved in E/N interaction are largely located in both carboxyl-terminal regions. Changing all three E cysteine residues to alanines did not exert negative effects on E release, E association with N, or E enhancement of VLP production, suggesting that E palmitoylation modification or disulfide bond formation is not required for SARS-CoV virus assembly. We found that removal of the last E carboxyl-terminal residue markedly affected E release, N association, and VLP incorporation, but did not significantly compromise the contribution of E to efficient VLP production. The independence of the SARS-CoV E enhancement effect on VLP production from its viral packaging capacity suggests a distinct SARS-CoV E role in virus assembly.

SARS-CoV envelope protein palmitoylation or nucleocapid association is not required for promoting virus-like particle production

PubMed Central

2014-01-01

Background Coronavirus membrane (M) proteins are capable of interacting with nucleocapsid (N) and envelope (E) proteins. Severe acute respiratory syndrome coronavirus (SARS-CoV) M co-expression with either N or E is sufficient for producing virus-like particles (VLPs), although at a lower level compared to M, N and E co-expression. Whether E can release from cells or E/N interaction exists so as to contribute to enhanced VLP production is unknown. It also remains to be determined whether E palmitoylation or disulfide bond formation plays a role in SARS-CoV virus assembly. Results SARS-CoV N is released from cells through an association with E protein-containing vesicles. Further analysis suggests that domains involved in E/N interaction are largely located in both carboxyl-terminal regions. Changing all three E cysteine residues to alanines did not exert negative effects on E release, E association with N, or E enhancement of VLP production, suggesting that E palmitoylation modification or disulfide bond formation is not required for SARS-CoV virus assembly. We found that removal of the last E carboxyl-terminal residue markedly affected E release, N association, and VLP incorporation, but did not significantly compromise the contribution of E to efficient VLP production. Conclusions The independence of the SARS-CoV E enhancement effect on VLP production from its viral packaging capacity suggests a distinct SARS-CoV E role in virus assembly. PMID:24766657

Large-Scale Covariability Between Aerosol and Precipitation Over the 7-SEAS Region: Observations and Simulations

NASA Technical Reports Server (NTRS)

Huang, Jingfeng; Hsu, N. Christina; Tsay, Si-Chee; Zhang, Chidong; Jeong, Myeong Jae; Gautam, Ritesh; Bettenhausen, Corey; Sayer, Andrew M.; Hansell, Richard A.; Liu, Xiaohong;

Large CO 2 effluxes at night and during synoptic weather events significantly contribute to CO 2 emissions from a reservoir

DOE PAGES

Liu, Heping; Zhang, Qianyu; Katul, Gabriel G.; ...

2016-05-24

CO 2 emissions from inland waters are commonly determined by indirect methods that are based on the product of a gas transfer coefficient and the concentration gradient at the air water interface (e.g., wind-based gas transfer models). The measurements of concentration gradient are typically collected during the day in fair weather throughout the course of a year. Direct measurements of eddy covariance CO 2 fluxes from a large inland water body (Ross Barnett reservoir, Mississippi, USA) show that CO 2 effluxes at night are approximately 70% greater than those during the day. At longer time scales, frequent synoptic weather eventsmore » associated with extratropical cyclones induce CO 2 flux pulses, resulting in further increase in annual CO 2 effluxes by 16%. Therefore, CO 2 emission rates from this reservoir, if these diel and synoptic processes are under-sampled, are likely to be underestimated by approximately 40%. Our results also indicate that the CO 2 emission rates from global inland waters reported in the literature, when based on indirect methods, are likely underestimated. Field samplings and indirect modeling frameworks that estimate CO 2 emissions should account for both daytime-nighttime efflux difference and enhanced emissions during synoptic weather events. Furthermore, the analysis here can guide carbon emission sampling to improve regional carbon estimates.« less

Large CO 2 effluxes at night and during synoptic weather events significantly contribute to CO 2 emissions from a reservoir

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Heping; Zhang, Qianyu; Katul, Gabriel G.

CO 2 emissions from inland waters are commonly determined by indirect methods that are based on the product of a gas transfer coefficient and the concentration gradient at the air water interface (e.g., wind-based gas transfer models). The measurements of concentration gradient are typically collected during the day in fair weather throughout the course of a year. Direct measurements of eddy covariance CO 2 fluxes from a large inland water body (Ross Barnett reservoir, Mississippi, USA) show that CO 2 effluxes at night are approximately 70% greater than those during the day. At longer time scales, frequent synoptic weather eventsmore » associated with extratropical cyclones induce CO 2 flux pulses, resulting in further increase in annual CO 2 effluxes by 16%. Therefore, CO 2 emission rates from this reservoir, if these diel and synoptic processes are under-sampled, are likely to be underestimated by approximately 40%. Our results also indicate that the CO 2 emission rates from global inland waters reported in the literature, when based on indirect methods, are likely underestimated. Field samplings and indirect modeling frameworks that estimate CO 2 emissions should account for both daytime-nighttime efflux difference and enhanced emissions during synoptic weather events. Furthermore, the analysis here can guide carbon emission sampling to improve regional carbon estimates.« less

Comparison of gene co-networks reveals the molecular mechanisms of the rice (Oryza sativa L.) response to Rhizoctonia solani AG1 IA infection.

PubMed

Zhang, Jinfeng; Zhao, Wenjuan; Fu, Rong; Fu, Chenglin; Wang, Lingxia; Liu, Huainian; Li, Shuangcheng; Deng, Qiming; Wang, Shiquan; Zhu, Jun; Liang, Yueyang; Li, Ping; Zheng, Aiping

2018-05-05

Rhizoctonia solani causes rice sheath blight, an important disease affecting the growth of rice (Oryza sativa L.). Attempts to control the disease have met with little success. Based on transcriptional profiling, we previously identified more than 11,947 common differentially expressed genes (TPM > 10) between the rice genotypes TeQing and Lemont. In the current study, we extended these findings by focusing on an analysis of gene co-expression in response to R. solani AG1 IA and identified gene modules within the networks through weighted gene co-expression network analysis (WGCNA). We compared the different genes assigned to each module and the biological interpretations of gene co-expression networks at early and later modules in the two rice genotypes to reveal differential responses to AG1 IA. Our results show that different changes occurred in the two rice genotypes and that the modules in the two groups contain a number of candidate genes possibly involved in pathogenesis, such as the VQ protein. Furthermore, these gene co-expression networks provide comprehensive transcriptional information regarding gene expression in rice in response to AG1 IA. The co-expression networks derived from our data offer ideas for follow-up experimentation that will help advance our understanding of the translational regulation of rice gene expression changes in response to AG1 IA.

Constraints on High Northern Photosynthesis Increase Using Earth System Models and a Set of Independent Observations

NASA Astrophysics Data System (ADS)

Winkler, A. J.; Brovkin, V.; Myneni, R.; Alexandrov, G.

2017-12-01

Plant growth in the northern high latitudes benefits from increasing temperature (radiative effect) and CO2 fertilization as a consequence of rising atmospheric CO2 concentration. This enhanced gross primary production (GPP) is evident in large scale increase in summer time greening over the 36-year record of satellite observations. In this time period also various global ecosystem models simulate a greening trend in terms of increasing leaf area index (LAI). We also found a persistent greening trend analyzing historical simulations of Earth system models (ESM) participating in Phase 5 of the Coupled Model Intercomparison Project (CMIP5). However, these models span a large range in strength of the LAI trend, expressed as sensitivity to both key environmental factors, temperature and CO2 concentration. There is also a wide spread in magnitude of the associated increase of terrestrial GPP among the ESMs, which contributes to pronounced uncertainties in projections of future climate change. Here we demonstrate that there is a linear relationship across the CMIP5 model ensemble between projected GPP changes and historical LAI sensitivity, which allows using the observed LAI sensitivity as an "emerging constraint" on GPP estimation at future CO2 concentration. This constrained estimate of future GPP is substantially higher than the traditional multi-model mean suggesting that the majority of current ESMs may be significantly underestimating carbon fixation by vegetation in NHL. We provide three independent lines of evidence in analyzing observed and simulated CO2 amplitude as well as atmospheric CO2 inversion products to arrive at the same conclusion.

The relationship between CO emission and visual extinction traced by dust emission in the Magellanic Clouds

NASA Astrophysics Data System (ADS)

Lee, Cheoljong; Leroy, Adam K.; Schnee, Scott; Wong, Tony; Bolatto, Alberto D.; Indebetouw, Remy; Rubio, Monica

2015-07-01

To test the theoretical understanding that finding bright CO emission depends primarily on dust shielding, we investigate the relationship between CO emission (ICO) and the amount of dust (estimated from infrared emission and expressed as `AV') across the Large Magellanic Cloud (LMC), the Small Magellanic Cloud, and the Milky Way. We show that at our common resolution of 10 pc scales, ICO given a fixed line of sight AV is similar across all three systems despite the difference in metallicity. We find some evidence for a secondary dependence of ICO on radiation field; in the LMC, ICO at a given AV is smaller in regions of high Tdust, perhaps because of an increased photodissociating radiation field. We suggest a simple but useful picture in which the CO-to-H2 conversion factor (XCO) depends on two separable factors: (1) the distribution of gas column densities, which maps to an extinction distribution via a dust-to-gas ratio; and (2) the dependence of ICO on AV. Assuming that the probability distribution function (PDF) of local Milky Way clouds is universal, this approach predicts a dependence of {X_CO} on Z between Z-1 and Z-2 above about a third solar metallicity. Below this metallicity, CO emerges from only the high column density parts of the cloud and so depends very sensitively on the adopted PDF and the H2/H I prescription. The PDF of low-metallicity clouds is thus of considerable interest and the uncertainty associated with even an ideal prescription for XCO at very low metallicity will be large.

Genome-wide transcriptional changes of ramie (Boehmeria nivea L. Gaud) in response to root-lesion nematode infection.

PubMed

Zhu, Siyuan; Tang, Shouwei; Tang, Qingming; Liu, Touming

2014-11-15

Ramie fiber extracted from stem bark is one of the most important natural fibers. The root-lesion nematode (RLN) Pratylenchus coffeae is a major ramie pest and causes large fiber yield losses in China annually. The response mechanism of ramie to RLN infection is poorly understood. In this study, we identified genes that are potentially involved in the RLN-resistance in ramie using Illumina pair-end sequencing in two RLN-infected plants (Inf1 and Inf2) and two control plants (CO1 and CO2). Approximately 56.3, 51.7, 43.4, and 45.0 million sequencing reads were generated from the libraries of CO1, CO2, Inf1, and Inf2, respectively. De novo assembly for these 196 million reads yielded 50,486 unigenes with an average length of 853.3bp. A total of 24,820 (49.2%) genes were annotated for their function. Comparison of gene expression levels between CO and Inf ramie revealed 777 differentially expressed genes (DEGs). The expression levels of 12 DEGs were further confirmed by real-time quantitative PCR (qRT-PCR). Pathway enrichment analysis showed that three pathways (phenylalanine metabolism, carotenoid biosynthesis, and phenylpropanoid biosynthesis) were strongly influenced by RLN infection. A series of candidate genes and pathways that may contribute to the defense response against RLN in ramie will be helpful for further improving resistance to RLN infection. Copyright © 2014. Published by Elsevier B.V.

Steps Towards Understanding Large-scale Deformation of Gas Hydrate-bearing Sediments

NASA Astrophysics Data System (ADS)

Gupta, S.; Deusner, C.; Haeckel, M.; Kossel, E.

2016-12-01

Marine sediments bearing gas hydrates are typically characterized by heterogeneity in the gas hydrate distribution and anisotropy in the sediment-gas hydrate fabric properties. Gas hydrates also contribute to the strength and stiffness of the marine sediment, and any disturbance in the thermodynamic stability of the gas hydrates is likely to affect the geomechanical stability of the sediment. Understanding mechanisms and triggers of large-strain deformation and failure of marine gas hydrate-bearing sediments is an area of extensive research, particularly in the context of marine slope-stability and industrial gas production. The ultimate objective is to predict severe deformation events such as regional-scale slope failure or excessive sand production by using numerical simulation tools. The development of such tools essentially requires a careful analysis of thermo-hydro-chemo-mechanical behavior of gas hydrate-bearing sediments at lab-scale, and its stepwise integration into reservoir-scale simulators through definition of effective variables, use of suitable constitutive relations, and application of scaling laws. One of the focus areas of our research is to understand the bulk coupled behavior of marine gas hydrate systems with contributions from micro-scale characteristics, transport-reaction dynamics, and structural heterogeneity through experimental flow-through studies using high-pressure triaxial test systems and advanced tomographical tools (CT, ERT, MRI). We combine these studies to develop mathematical model and numerical simulation tools which could be used to predict the coupled hydro-geomechanical behavior of marine gas hydrate reservoirs in a large-strain framework. Here we will present some of our recent results from closely co-ordinated experimental and numerical simulation studies with an objective to capture the large-deformation behavior relevant to different gas production scenarios. We will also report on a variety of mechanically relevant test scenarios focusing on effects of dynamic changes in gas hydrate saturation, highly uneven gas hydrate distributions, focused fluid migration and gas hydrate production through depressurization and CO2 injection.

Genome-Wide Identification and Expression Analysis of the Mitogen-Activated Protein Kinase Gene Family in Cassava

PubMed Central

Yan, Yan; Wang, Lianzhe; Ding, Zehong; Tie, Weiwei; Ding, Xupo; Zeng, Changying; Wei, Yunxie; Zhao, Hongliang; Peng, Ming; Hu, Wei

2016-01-01

Mitogen-activated protein kinases (MAPKs) play central roles in plant developmental processes, hormone signaling transduction, and responses to abiotic stress. However, no data are currently available about the MAPK family in cassava, an important tropical crop. Herein, 21 MeMAPK genes were identified from cassava. Phylogenetic analysis indicated that MeMAPKs could be classified into four subfamilies. Gene structure analysis demonstrated that the number of introns in MeMAPK genes ranged from 1 to 10, suggesting large variation among cassava MAPK genes. Conserved motif analysis indicated that all MeMAPKs had typical protein kinase domains. Transcriptomic analysis suggested that MeMAPK genes showed differential expression patterns in distinct tissues and in response to drought stress between wild subspecies and cultivated varieties. Interaction networks and co-expression analyses revealed that crucial pathways controlled by MeMAPK networks may be involved in the differential response to drought stress in different accessions of cassava. Expression of nine selected MAPK genes showed that these genes could comprehensively respond to osmotic, salt, cold, oxidative stressors, and abscisic acid (ABA) signaling. These findings yield new insights into the transcriptional control of MAPK gene expression, provide an improved understanding of abiotic stress responses and signaling transduction in cassava, and lead to potential applications in the genetic improvement of cassava cultivars. PMID:27625666

Maximizing capture of gene co-expression relationships through pre-clustering of input expression samples: an Arabidopsis case study.

PubMed

Feltus, F Alex; Ficklin, Stephen P; Gibson, Scott M; Smith, Melissa C

2013-06-05

In genomics, highly relevant gene interaction (co-expression) networks have been constructed by finding significant pair-wise correlations between genes in expression datasets. These networks are then mined to elucidate biological function at the polygenic level. In some cases networks may be constructed from input samples that measure gene expression under a variety of different conditions, such as for different genotypes, environments, disease states and tissues. When large sets of samples are obtained from public repositories it is often unmanageable to associate samples into condition-specific groups, and combining samples from various conditions has a negative effect on network size. A fixed significance threshold is often applied also limiting the size of the final network. Therefore, we propose pre-clustering of input expression samples to approximate condition-specific grouping of samples and individual network construction of each group as a means for dynamic significance thresholding. The net effect is increase sensitivity thus maximizing the total co-expression relationships in the final co-expression network compendium. A total of 86 Arabidopsis thaliana co-expression networks were constructed after k-means partitioning of 7,105 publicly available ATH1 Affymetrix microarray samples. We term each pre-sorted network a Gene Interaction Layer (GIL). Random Matrix Theory (RMT), an un-supervised thresholding method, was used to threshold each of the 86 networks independently, effectively providing a dynamic (non-global) threshold for the network. The overall gene count across all GILs reached 19,588 genes (94.7% measured gene coverage) and 558,022 unique co-expression relationships. In comparison, network construction without pre-sorting of input samples yielded only 3,297 genes (15.9%) and 129,134 relationships. in the global network. Here we show that pre-clustering of microarray samples helps approximate condition-specific networks and allows for dynamic thresholding using un-supervised methods. Because RMT ensures only highly significant interactions are kept, the GIL compendium consists of 558,022 unique high quality A. thaliana co-expression relationships across almost all of the measurable genes on the ATH1 array. For A. thaliana, these networks represent the largest compendium to date of significant gene co-expression relationships, and are a means to explore complex pathway, polygenic, and pleiotropic relationships for this focal model plant. The networks can be explored at sysbio.genome.clemson.edu. Finally, this method is applicable to any large expression profile collection for any organism and is best suited where a knowledge-independent network construction method is desired.

Maximizing capture of gene co-expression relationships through pre-clustering of input expression samples: an Arabidopsis case study

PubMed Central

2013-01-01

Background In genomics, highly relevant gene interaction (co-expression) networks have been constructed by finding significant pair-wise correlations between genes in expression datasets. These networks are then mined to elucidate biological function at the polygenic level. In some cases networks may be constructed from input samples that measure gene expression under a variety of different conditions, such as for different genotypes, environments, disease states and tissues. When large sets of samples are obtained from public repositories it is often unmanageable to associate samples into condition-specific groups, and combining samples from various conditions has a negative effect on network size. A fixed significance threshold is often applied also limiting the size of the final network. Therefore, we propose pre-clustering of input expression samples to approximate condition-specific grouping of samples and individual network construction of each group as a means for dynamic significance thresholding. The net effect is increase sensitivity thus maximizing the total co-expression relationships in the final co-expression network compendium. Results A total of 86 Arabidopsis thaliana co-expression networks were constructed after k-means partitioning of 7,105 publicly available ATH1 Affymetrix microarray samples. We term each pre-sorted network a Gene Interaction Layer (GIL). Random Matrix Theory (RMT), an un-supervised thresholding method, was used to threshold each of the 86 networks independently, effectively providing a dynamic (non-global) threshold for the network. The overall gene count across all GILs reached 19,588 genes (94.7% measured gene coverage) and 558,022 unique co-expression relationships. In comparison, network construction without pre-sorting of input samples yielded only 3,297 genes (15.9%) and 129,134 relationships. in the global network. Conclusions Here we show that pre-clustering of microarray samples helps approximate condition-specific networks and allows for dynamic thresholding using un-supervised methods. Because RMT ensures only highly significant interactions are kept, the GIL compendium consists of 558,022 unique high quality A. thaliana co-expression relationships across almost all of the measurable genes on the ATH1 array. For A. thaliana, these networks represent the largest compendium to date of significant gene co-expression relationships, and are a means to explore complex pathway, polygenic, and pleiotropic relationships for this focal model plant. The networks can be explored at sysbio.genome.clemson.edu. Finally, this method is applicable to any large expression profile collection for any organism and is best suited where a knowledge-independent network construction method is desired. PMID:23738693

Co-expression modules construction by WGCNA and identify potential prognostic markers of uveal melanoma.

PubMed

Wan, Qi; Tang, Jing; Han, Yu; Wang, Dan

2018-01-01

Uveal melanoma is an aggressive cancer which has a high percentage recurrence and with a worse prognosis. Identify the potential prognostic markers of uveal melanoma may provide information for early detection of recurrence and treatment. RNA sequence data of uveal melanoma and patient clinic traits were obtained from The Cancer Genome Atlas (TCGA) database. Co-expression modules were built by weighted gene co -expression network analysis (WGCNA) and applied to investigate the relationship underlying modules and clinic traits. Besides, functional enrichment analysis was performed on these co-expression genes from interested modules. First, using WGCNA, identified 21 co-expression modules were constructed by the 10975 genes from the 80 human uveal melanoma samples. The number of genes in these modules ranged from 42 to 5091. Found four co -expression modules significantly correlated with three clinic traits (status, recurrence and recurrence Time). Module red, and purple positively correlated with patient's life status and recurrence Time. Module green positively correlates with recurrence. The result of functional enrichment analysis showed that the module magenta was mainly enriched genetic material assemble processes, the purple module was mainly enriched in tissue homeostasis and melanosome membrane and the module red was mainly enriched metastasis of cell, suggesting its critical role in the recurrence and development of the disease. Additionally, identified the hug gene (top connectivity with other genes) in each module. The hub gene SLC17A7, NTRK2, ABTB1 and ADPRHL1 might play a vital role in recurrence of uveal melanoma. Our findings provided the framework of co-expression gene modules of uveal melanoma and identified some prognostic markers might be detection of recurrence and treatment for uveal melanoma. Copyright © 2017 Elsevier Ltd. All rights reserved.

The co-evolution of social institutions, demography, and large-scale human cooperation.

PubMed

Powers, Simon T; Lehmann, Laurent

2013-11-01

Human cooperation is typically coordinated by institutions, which determine the outcome structure of the social interactions individuals engage in. Explaining the Neolithic transition from small- to large-scale societies involves understanding how these institutions co-evolve with demography. We study this using a demographically explicit model of institution formation in a patch-structured population. Each patch supports both social and asocial niches. Social individuals create an institution, at a cost to themselves, by negotiating how much of the costly public good provided by cooperators is invested into sanctioning defectors. The remainder of their public good is invested in technology that increases carrying capacity, such as irrigation systems. We show that social individuals can invade a population of asocials, and form institutions that support high levels of cooperation. We then demonstrate conditions where the co-evolution of cooperation, institutions, and demographic carrying capacity creates a transition from small- to large-scale social groups. © 2013 John Wiley & Sons Ltd/CNRS.

Statistical Analysis of Big Data on Pharmacogenomics

PubMed Central

Fan, Jianqing; Liu, Han

2013-01-01

This paper discusses statistical methods for estimating complex correlation structure from large pharmacogenomic datasets. We selectively review several prominent statistical methods for estimating large covariance matrix for understanding correlation structure, inverse covariance matrix for network modeling, large-scale simultaneous tests for selecting significantly differently expressed genes and proteins and genetic markers for complex diseases, and high dimensional variable selection for identifying important molecules for understanding molecule mechanisms in pharmacogenomics. Their applications to gene network estimation and biomarker selection are used to illustrate the methodological power. Several new challenges of Big data analysis, including complex data distribution, missing data, measurement error, spurious correlation, endogeneity, and the need for robust statistical methods, are also discussed. PMID:23602905

CO 2 Sequestration and Enhanced Oil Recovery at Depleted Oil/Gas Reservoirs

DOE PAGES

Dai, Zhenxue; Viswanathan, Hari; Xiao, Ting; ...

2017-08-18

This study presents a quantitative evaluation of the operational and technical risks of an active CO 2-EOR project. A set of risk factor metrics is defined to post-process the Monte Carlo (MC) simulations for statistical analysis. The risk factors are expressed as measurable quantities that can be used to gain insight into project risk (e.g. environmental and economic risks) without the need to generate a rigorous consequence structure, which include (a) CO 2 injection rate, (b) net CO 2 injection rate, (c) cumulative CO 2 storage, (d) cumulative water injection, (e) oil production rate, (f) cumulative oil production, (g) cumulativemore » CH 4 production, and (h) CO 2 breakthrough time. The Morrow reservoir at the Farnsworth Unit (FWU) site, Texas, is used as an example for studying the multi-scale statistical approach for CO 2 accounting and risk analysis. A set of geostatistical-based MC simulations of CO 2-oil/gas-water flow and transport in the Morrow formation are conducted for evaluating the risk metrics. A response-surface-based economic model has been derived to calculate the CO 2-EOR profitability for the FWU site with a current oil price, which suggests that approximately 31% of the 1000 realizations can be profitable. If government carbon-tax credits are available, or the oil price goes up or CO 2 capture and operating expenses reduce, more realizations would be profitable.« less

CO 2 Sequestration and Enhanced Oil Recovery at Depleted Oil/Gas Reservoirs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, Zhenxue; Viswanathan, Hari; Xiao, Ting

This study presents a quantitative evaluation of the operational and technical risks of an active CO 2-EOR project. A set of risk factor metrics is defined to post-process the Monte Carlo (MC) simulations for statistical analysis. The risk factors are expressed as measurable quantities that can be used to gain insight into project risk (e.g. environmental and economic risks) without the need to generate a rigorous consequence structure, which include (a) CO 2 injection rate, (b) net CO 2 injection rate, (c) cumulative CO 2 storage, (d) cumulative water injection, (e) oil production rate, (f) cumulative oil production, (g) cumulativemore » CH 4 production, and (h) CO 2 breakthrough time. The Morrow reservoir at the Farnsworth Unit (FWU) site, Texas, is used as an example for studying the multi-scale statistical approach for CO 2 accounting and risk analysis. A set of geostatistical-based MC simulations of CO 2-oil/gas-water flow and transport in the Morrow formation are conducted for evaluating the risk metrics. A response-surface-based economic model has been derived to calculate the CO 2-EOR profitability for the FWU site with a current oil price, which suggests that approximately 31% of the 1000 realizations can be profitable. If government carbon-tax credits are available, or the oil price goes up or CO 2 capture and operating expenses reduce, more realizations would be profitable.« less

Epigenomic reprogramming during pancreatic cancer progression links anabolic glucose metabolism to distant metastasis.

PubMed

McDonald, Oliver G; Li, Xin; Saunders, Tyler; Tryggvadottir, Rakel; Mentch, Samantha J; Warmoes, Marc O; Word, Anna E; Carrer, Alessandro; Salz, Tal H; Natsume, Sonoko; Stauffer, Kimberly M; Makohon-Moore, Alvin; Zhong, Yi; Wu, Hao; Wellen, Kathryn E; Locasale, Jason W; Iacobuzio-Donahue, Christine A; Feinberg, Andrew P

2017-03-01

During the progression of pancreatic ductal adenocarcinoma (PDAC), heterogeneous subclonal populations emerge that drive primary tumor growth, regional spread, distant metastasis, and patient death. However, the genetics of metastases largely reflects that of the primary tumor in untreated patients, and PDAC driver mutations are shared by all subclones. This raises the possibility that an epigenetic process might operate during metastasis. Here we report large-scale reprogramming of chromatin modifications during the natural evolution of distant metastasis. Changes were targeted to thousands of large chromatin domains across the genome that collectively specified malignant traits, including euchromatin and large organized chromatin histone H3 lysine 9 (H3K9)-modified (LOCK) heterochromatin. Remarkably, distant metastases co-evolved a dependence on the oxidative branch of the pentose phosphate pathway (oxPPP), and oxPPP inhibition selectively reversed reprogrammed chromatin, malignant gene expression programs, and tumorigenesis. These findings suggest a model whereby linked metabolic-epigenetic programs are selected for enhanced tumorigenic fitness during the evolution of distant metastasis.

FastGCN: A GPU Accelerated Tool for Fast Gene Co-Expression Networks

PubMed Central

Liang, Meimei; Zhang, Futao; Jin, Gulei; Zhu, Jun

2015-01-01

Gene co-expression networks comprise one type of valuable biological networks. Many methods and tools have been published to construct gene co-expression networks; however, most of these tools and methods are inconvenient and time consuming for large datasets. We have developed a user-friendly, accelerated and optimized tool for constructing gene co-expression networks that can fully harness the parallel nature of GPU (Graphic Processing Unit) architectures. Genetic entropies were exploited to filter out genes with no or small expression changes in the raw data preprocessing step. Pearson correlation coefficients were then calculated. After that, we normalized these coefficients and employed the False Discovery Rate to control the multiple tests. At last, modules identification was conducted to construct the co-expression networks. All of these calculations were implemented on a GPU. We also compressed the coefficient matrix to save space. We compared the performance of the GPU implementation with those of multi-core CPU implementations with 16 CPU threads, single-thread C/C++ implementation and single-thread R implementation. Our results show that GPU implementation largely outperforms single-thread C/C++ implementation and single-thread R implementation, and GPU implementation outperforms multi-core CPU implementation when the number of genes increases. With the test dataset containing 16,000 genes and 590 individuals, we can achieve greater than 63 times the speed using a GPU implementation compared with a single-thread R implementation when 50 percent of genes were filtered out and about 80 times the speed when no genes were filtered out. PMID:25602758

FastGCN: a GPU accelerated tool for fast gene co-expression networks.

PubMed

Liang, Meimei; Zhang, Futao; Jin, Gulei; Zhu, Jun

2015-01-01

Gene co-expression networks comprise one type of valuable biological networks. Many methods and tools have been published to construct gene co-expression networks; however, most of these tools and methods are inconvenient and time consuming for large datasets. We have developed a user-friendly, accelerated and optimized tool for constructing gene co-expression networks that can fully harness the parallel nature of GPU (Graphic Processing Unit) architectures. Genetic entropies were exploited to filter out genes with no or small expression changes in the raw data preprocessing step. Pearson correlation coefficients were then calculated. After that, we normalized these coefficients and employed the False Discovery Rate to control the multiple tests. At last, modules identification was conducted to construct the co-expression networks. All of these calculations were implemented on a GPU. We also compressed the coefficient matrix to save space. We compared the performance of the GPU implementation with those of multi-core CPU implementations with 16 CPU threads, single-thread C/C++ implementation and single-thread R implementation. Our results show that GPU implementation largely outperforms single-thread C/C++ implementation and single-thread R implementation, and GPU implementation outperforms multi-core CPU implementation when the number of genes increases. With the test dataset containing 16,000 genes and 590 individuals, we can achieve greater than 63 times the speed using a GPU implementation compared with a single-thread R implementation when 50 percent of genes were filtered out and about 80 times the speed when no genes were filtered out.

An numerical analysis of high-temperature helium reactor power plant for co-production of hydrogen and electricity

NASA Astrophysics Data System (ADS)

Dudek, M.; Podsadna, J.; Jaszczur, M.

2016-09-01

In the present work, the feasibility of using a high temperature gas cooled nuclear reactor (HTR) for electricity generation and hydrogen production are analysed. The HTR is combined with a steam and a gas turbine, as well as with the system for heat delivery for medium temperature hydrogen production. Industrial-scale hydrogen production using copper-chlorine (Cu-Cl) thermochemical cycle is considered and compared with high temperature electrolysis. Presented cycle shows a very promising route for continuous, efficient, large-scale and environmentally benign hydrogen production without CO2 emissions. The results show that the integration of a high temperature helium reactor, with a combined cycle for electric power generation and hydrogen production, may reach very high efficiency and could possibly lead to a significant decrease of hydrogen production costs.

Revealing the Hidden Relationship by Sparse Modules in Complex Networks with a Large-Scale Analysis

PubMed Central

Jiao, Qing-Ju; Huang, Yan; Liu, Wei; Wang, Xiao-Fan; Chen, Xiao-Shuang; Shen, Hong-Bin

2013-01-01

One of the remarkable features of networks is module that can provide useful insights into not only network organizations but also functional behaviors between their components. Comprehensive efforts have been devoted to investigating cohesive modules in the past decade. However, it is still not clear whether there are important structural characteristics of the nodes that do not belong to any cohesive module. In order to answer this question, we performed a large-scale analysis on 25 complex networks with different types and scales using our recently developed BTS (bintree seeking) algorithm, which is able to detect both cohesive and sparse modules in the network. Our results reveal that the sparse modules composed by the cohesively isolated nodes widely co-exist with the cohesive modules. Detailed analysis shows that both types of modules provide better characterization for the division of a network into functional units than merely cohesive modules, because the sparse modules possibly re-organize the nodes in the so-called cohesive modules, which lack obvious modular significance, into meaningful groups. Compared with cohesive modules, the sizes of sparse ones are generally smaller. Sparse modules are also found to have preferences in social and biological networks than others. PMID:23762457

Experimental Quantification of Pore-Scale Flow Phenomena in 2D Heterogeneous Porous Micromodels: Multiphase Flow Towards Coupled Solid-Liquid Interactions

NASA Astrophysics Data System (ADS)

Li, Y.; Kazemifar, F.; Blois, G.; Christensen, K. T.

2017-12-01

Geological sequestration of CO2 within saline aquifers is a viable technology for reducing CO2 emissions. Central to this goal is accurately predicting both the fidelity of candidate sites pre-injection of CO2 and its post-injection migration. Moreover, local fluid pressure buildup may cause activation of small pre-existing unidentified faults, leading to micro-seismic events, which could prove disastrous for societal acceptance of CCS, and possibly compromise seal integrity. Recent evidence shows that large-scale events are coupled with pore-scale phenomena, which necessitates the representation of pore-scale stress, strain, and multiphase flow processes in large-scale modeling. To this end, the pore-scale flow of water and liquid/supercritical CO2 is investigated under reservoir-relevant conditions, over a range of wettability conditions in 2D heterogeneous micromodels that reflect the complexity of a real sandstone. High-speed fluorescent microscopy, complemented by a fast differential pressure transmitter, allows for simultaneous measurement of the flow field within and the instantaneous pressure drop across the micromodels. A flexible micromodel is also designed and fabricated, to be used in conjunction with the micro-PIV technique, enabling the quantification of coupled solid-liquid interactions.

Formation of Molecular Networks: Tailored Quantum Boxes and Behavior of Adsorbed CO in Them

NASA Astrophysics Data System (ADS)

Wyrick, Jon; Sun, Dezheng; Kim, Dae-Ho; Cheng, Zhihai; Lu, Wenhao; Zhu, Yeming; Luo, Miaomiao; Kim, Yong Su; Rotenberg, Eli; Kim, Kwangmoo; Einstein, T. L.; Bartels, Ludwig

2011-03-01

We show that the behavior of CO adsorbed into the pores of large regular networks on Cu(111) is significantly affected by their nano-scale lateral confinement and that formation of the networks themselves is directed by the Shockley surface state. Saturation coverages of CO are found to exhibit persistent dislocation lines; at lower coverages their mobility increases. Individual CO within the pores titrate the surface state, providing crucial information for understanding formation of the network as a result of optimization of the number N of electrons bound within each pore. Determination of N is based on quinone-coverage-dependent UPS data and an analysis of states of particles in a pore-shaped box (verified by CO's titration); a wide range of possible pore shapes and sizes has been considered. Work at UCR supported by NSF CHE 07-49949; at UMD by NSF CHE 07-50334 & UMD NSF-MRSEC DMR 05-20471.

Predicting the ultimate potential of natural gas SOFC power cycles with CO2 capture - Part B: Applications

NASA Astrophysics Data System (ADS)

Campanari, Stefano; Mastropasqua, Luca; Gazzani, Matteo; Chiesa, Paolo; Romano, Matteo C.

2016-09-01

An important advantage of solid oxide fuel cells (SOFC) as future systems for large scale power generation is the possibility of being efficiently integrated with processes for CO2 capture. Focusing on natural gas power generation, Part A of this work assessed the performances of advanced pressurised and atmospheric plant configurations (SOFC + GT and SOFC + ST, with fuel cell integration within a gas turbine or a steam turbine cycle) without CO2 separation. This Part B paper investigates such kind of power cycles when applied to CO2 capture, proposing two ultra-high efficiency plant configurations based on advanced intermediate-temperature SOFCs with internal reforming and low temperature CO2 separation process. The power plants are simulated at the 100 MW scale with a set of realistic assumptions about FC performances, main components and auxiliaries, and show the capability of exceeding 70% LHV efficiency with high CO2 capture (above 80%) and a low specific primary energy consumption for the CO2 avoided (1.1-2.4 MJ kg-1). Detailed results are presented in terms of energy and material balances, and a sensitivity analysis of plant performance is developed vs. FC voltage and fuel utilisation to investigate possible long-term improvements. Options for further improvement of the CO2 capture efficiency are also addressed.

Application of a fluidized bed reactor charged with aragonite for control of alkalinity, pH and carbon dioxide in marine recirculating aquaculture systems

USGS Publications Warehouse

Paul S Wills, PhD; Pfeiffer, Timothy; Baptiste, Richard; Watten, Barnaby J.

2016-01-01

Control of alkalinity, dissolved carbon dioxide (dCO2), and pH are critical in marine recirculating aquaculture systems (RAS) in order to maintain health and maximize growth. A small-scale prototype aragonite sand filled fluidized bed reactor was tested under varying conditions of alkalinity and dCO2 to develop and model the response of dCO2 across the reactor. A large-scale reactor was then incorporated into an operating marine recirculating aquaculture system to observe the reactor as the system moved toward equilibrium. The relationship between alkalinity dCO2, and pH across the reactor are described by multiple regression equations. The change in dCO2 across the small-scale reactor indicated a strong likelihood that an equilibrium alkalinity would be maintained by using a fluidized bed aragonite reactor. The large-scale reactor verified this observation and established equilibrium at an alkalinity of approximately 135 mg/L as CaCO3, dCO2 of 9 mg/L, and a pH of 7.0 within 4 days that was stable during a 14 day test period. The fluidized bed aragonite reactor has the potential to simplify alkalinity and pH control, and aid in dCO2 control in RAS design and operation. Aragonite sand, purchased in bulk, is less expensive than sodium bicarbonate and could reduce overall operating production costs.

BECCS capability of dedicated bioenergy crops under a future land-use scenario targeting net negative carbon emissions

NASA Astrophysics Data System (ADS)

Kato, E.; Yamagata, Y.

2014-12-01

Bioenergy with Carbon Capture and Storage (BECCS) is a key component of mitigation strategies in future socio-economic scenarios that aim to keep mean global temperature rise below 2°C above pre-industrial, which would require net negative carbon emissions in the end of the 21st century. Because of the additional need for land, developing sustainable low-carbon scenarios requires careful consideration of the land-use implications of deploying large-scale BECCS. We evaluated the feasibility of the large-scale BECCS in RCP2.6, which is a scenario with net negative emissions aiming to keep the 2°C temperature target, with a top-down analysis of required yields and a bottom-up evaluation of BECCS potential using a process-based global crop model. Land-use change carbon emissions related to the land expansion were examined using a global terrestrial biogeochemical cycle model. Our analysis reveals that first-generation bioenergy crops would not meet the required BECCS of the RCP2.6 scenario even with a high fertilizer and irrigation application. Using second-generation bioenergy crops can marginally fulfill the required BECCS only if a technology of full post-process combustion CO2 capture is deployed with a high fertilizer application in the crop production. If such an assumed technological improvement does not occur in the future, more than doubling the area for bioenergy production for BECCS around 2050 assumed in RCP2.6 would be required, however, such scenarios implicitly induce large-scale land-use changes that would cancel half of the assumed CO2 sequestration by BECCS. Otherwise a conflict of land-use with food production is inevitable.

BECCS capability of dedicated bioenergy crops under a future land-use scenario targeting net negative carbon emissions

NASA Astrophysics Data System (ADS)

Kato, Etsushi; Yamagata, Yoshiki

2014-09-01

Bioenergy with Carbon Capture and Storage (BECCS) is a key component of mitigation strategies in future socioeconomic scenarios that aim to keep mean global temperature rise below 2°C above preindustrial, which would require net negative carbon emissions in the end of the 21st century. Because of the additional need for land, developing sustainable low-carbon scenarios requires careful consideration of the land-use implications of deploying large scale BECCS. We evaluated the feasibility of the large-scale BECCS in RCP2.6, which is a scenario with net negative emissions aiming to keep the 2°C temperature target, with a top-down analysis of required yields and a bottom-up evaluation of BECCS potential using a process-based global crop model. Land-use change carbon emissions related to the land expansion were examined using a global terrestrial biogeochemical cycle model. Our analysis reveals that first-generation bioenergy crops would not meet the required BECCS of the RCP2.6 scenario even with a high-fertilizer and irrigation application. Using second-generation bioenergy crops can marginally fulfill the required BECCS only if a technology of full postprocess combustion CO2 capture is deployed with a high-fertilizer application in the crop production. If such an assumed technological improvement does not occur in the future, more than doubling the area for bioenergy production for BECCS around 2050 assumed in RCP2.6 would be required; however, such scenarios implicitly induce large-scale land-use changes that would cancel half of the assumed CO2 sequestration by BECCS. Otherwise, a conflict of land use with food production is inevitable.

SPECTRAL LINE DE-CONFUSION IN AN INTENSITY MAPPING SURVEY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cheng, Yun-Ting; Bock, James; Bradford, C. Matt

2016-12-01

Spectral line intensity mapping (LIM) has been proposed as a promising tool to efficiently probe the cosmic reionization and the large-scale structure. Without detecting individual sources, LIM makes use of all available photons and measures the integrated light in the source confusion limit to efficiently map the three-dimensional matter distribution on large scales as traced by a given emission line. One particular challenge is the separation of desired signals from astrophysical continuum foregrounds and line interlopers. Here we present a technique to extract large-scale structure information traced by emission lines from different redshifts, embedded in a three-dimensional intensity mapping data cube.more » The line redshifts are distinguished by the anisotropic shape of the power spectra when projected onto a common coordinate frame. We consider the case where high-redshift [C ii] lines are confused with multiple low-redshift CO rotational lines. We present a semi-analytic model for [C ii] and CO line estimates based on the cosmic infrared background measurements, and show that with a modest instrumental noise level and survey geometry, the large-scale [C ii] and CO power spectrum amplitudes can be successfully extracted from a confusion-limited data set, without external information. We discuss the implications and limits of this technique for possible LIM experiments.« less

Large-scale phase separation with nano-twin domains in manganite spinel (Co,Fe,Mn){sub 3}O{sub 4}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Horibe, Y., E-mail: horibe@post.matsc.kyutech.ac.jp; Takeyama, S.; Mori, S.

The effect of Mn concentration on the formation of nano-domain structures in the spinel oxide (Co,Fe,Mn){sub 3}O{sub 4} was investigated by electron diffraction, bright-, and dark-field imaging technique with transmission electron microscopy. Large scale phase separation with nano-twin domains was observed in Co{sub 0.6}Fe{sub 1.0}Mn{sub 1.4}O{sub 4}, in contrast to the highly aligned checkerboard nano-domains in Co{sub 0.6}Fe{sub 0.9}Mn{sub 1.5}O{sub 4}. Diffusion of the Mn{sup 3+} ions with the Jahn-Teller distortions is suggested to play an important role in the formation of checkerboard nano-domain structure.

Proteomic profiling of halloysite clay nanotube exposure in intestinal cell co-culture.

PubMed

Lai, Xianyin; Agarwal, Mangilal; Lvov, Yuri M; Pachpande, Chetan; Varahramyan, Kody; Witzmann, Frank A

2013-11-01

Halloysite is aluminosilicate clay with a hollow tubular structure with nanoscale internal and external diameters. Assessment of halloysite biocompatibility has gained importance in view of its potential application in oral drug delivery. To investigate the effect of halloysite nanotubes on an in vitro model of the large intestine, Caco-2/HT29-MTX cells in monolayer co-culture were exposed to nanotubes for toxicity tests and proteomic analysis. Results indicate that halloysite exhibits a high degree of biocompatibility characterized by an absence of cytotoxicity, in spite of elevated pro-inflammatory cytokine release. Exposure-specific changes in expression were observed among 4081 proteins analyzed. Bioinformatic analysis of differentially expressed protein profiles suggest that halloysite stimulates processes related to cell growth and proliferation, subtle responses to cell infection, irritation and injury, enhanced antioxidant capability, and an overall adaptive response to exposure. These potentially relevant functional effects warrant further investigation in in vivo models and suggest that chronic or bolus occupational exposure to halloysite nanotubes may have unintended outcomes. Copyright © 2013 John Wiley & Sons, Ltd.

Genome-wide screen identifies a novel prognostic signature for breast cancer survival

DOE PAGES

Mao, Xuan Y.; Lee, Matthew J.; Zhu, Jeffrey; ...

2017-01-21

Large genomic datasets in combination with clinical data can be used as an unbiased tool to identify genes important in patient survival and discover potential therapeutic targets. We used a genome-wide screen to identify 587 genes significantly and robustly deregulated across four independent breast cancer (BC) datasets compared to normal breast tissue. Gene expression of 381 genes was significantly associated with relapse-free survival (RFS) in BC patients. We used a gene co-expression network approach to visualize the genetic architecture in normal breast and BCs. In normal breast tissue, co-expression cliques were identified enriched for cell cycle, gene transcription, cell adhesion,more » cytoskeletal organization and metabolism. In contrast, in BC, only two major co-expression cliques were identified enriched for cell cycle-related processes or blood vessel development, cell adhesion and mammary gland development processes. Interestingly, gene expression levels of 7 genes were found to be negatively correlated with many cell cycle related genes, highlighting these genes as potential tumor suppressors and novel therapeutic targets. A forward-conditional Cox regression analysis was used to identify a 12-gene signature associated with RFS. A prognostic scoring system was created based on the 12-gene signature. This scoring system robustly predicted BC patient RFS in 60 sampling test sets and was further validated in TCGA and METABRIC BC data. Our integrated study identified a 12-gene prognostic signature that could guide adjuvant therapy for BC patients and includes novel potential molecular targets for therapy.« less

Genome-wide screen identifies a novel prognostic signature for breast cancer survival

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mao, Xuan Y.; Lee, Matthew J.; Zhu, Jeffrey

Large genomic datasets in combination with clinical data can be used as an unbiased tool to identify genes important in patient survival and discover potential therapeutic targets. We used a genome-wide screen to identify 587 genes significantly and robustly deregulated across four independent breast cancer (BC) datasets compared to normal breast tissue. Gene expression of 381 genes was significantly associated with relapse-free survival (RFS) in BC patients. We used a gene co-expression network approach to visualize the genetic architecture in normal breast and BCs. In normal breast tissue, co-expression cliques were identified enriched for cell cycle, gene transcription, cell adhesion,more » cytoskeletal organization and metabolism. In contrast, in BC, only two major co-expression cliques were identified enriched for cell cycle-related processes or blood vessel development, cell adhesion and mammary gland development processes. Interestingly, gene expression levels of 7 genes were found to be negatively correlated with many cell cycle related genes, highlighting these genes as potential tumor suppressors and novel therapeutic targets. A forward-conditional Cox regression analysis was used to identify a 12-gene signature associated with RFS. A prognostic scoring system was created based on the 12-gene signature. This scoring system robustly predicted BC patient RFS in 60 sampling test sets and was further validated in TCGA and METABRIC BC data. Our integrated study identified a 12-gene prognostic signature that could guide adjuvant therapy for BC patients and includes novel potential molecular targets for therapy.« less

Molecular phenotype of zebrafish ovarian follicle by serial analysis of gene expression and proteomic profiling, and comparison with the transcriptomes of other animals

PubMed Central

Knoll-Gellida, Anja; André, Michèle; Gattegno, Tamar; Forgue, Jean; Admon, Arie; Babin, Patrick J

2006-01-01

Background The ability of an oocyte to develop into a viable embryo depends on the accumulation of specific maternal information and molecules, such as RNAs and proteins. A serial analysis of gene expression (SAGE) was carried out in parallel with proteomic analysis on fully-grown ovarian follicles from zebrafish (Danio rerio). The data obtained were compared with ovary/follicle/egg molecular phenotypes of other animals, published or available in public sequence databases. Results Sequencing of 27,486 SAGE tags identified 11,399 different ones, including 3,329 tags with an occurrence superior to one. Fifty-eight genes were expressed at over 0.15% of the total population and represented 17.34% of the mRNA population identified. The three most expressed transcripts were a rhamnose-binding lectin, beta-actin 2, and a transcribed locus similar to the H2B histone family. Comparison with the large-scale expressed sequence tags sequencing approach revealed highly expressed transcripts that were not previously known to be expressed at high levels in fish ovaries, like the short-sized polarized metallothionein 2 transcript. A higher sensitivity for the detection of transcripts with a characterized maternal genetic contribution was also demonstrated compared to large-scale sequencing of cDNA libraries. Ferritin heavy polypeptide 1, heat shock protein 90-beta, lactate dehydrogenase B4, beta-actin isoforms, tubulin beta 2, ATP synthase subunit 9, together with 40 S ribosomal protein S27a, were common highly-expressed transcripts of vertebrate ovary/unfertilized egg. Comparison of transcriptome and proteome data revealed that transcript levels provide little predictive value with respect to the extent of protein abundance. All the proteins identified by proteomic analysis of fully-grown zebrafish follicles had at least one transcript counterpart, with two exceptions: eosinophil chemotactic cytokine and nothepsin. Conclusion This study provides a complete sequence data set of maternal mRNA stored in zebrafish germ cells at the end of oogenesis. This catalogue contains highly-expressed transcripts that are part of a vertebrate ovarian expressed gene signature. Comparison of transcriptome and proteome data identified downregulated transcripts or proteins potentially incorporated in the oocyte by endocytosis. The molecular phenotype described provides groundwork for future experimental approaches aimed at identifying functionally important stored maternal transcripts and proteins involved in oogenesis and early stages of embryo development. PMID:16526958

Discovery and mapping of a new expressed sequence tag-single nucleotide polymorphism and simple sequence repeat panel for large-scale genetic studies and breeding of Theobroma cacao L.

PubMed Central

Allegre, Mathilde; Argout, Xavier; Boccara, Michel; Fouet, Olivier; Roguet, Yolande; Bérard, Aurélie; Thévenin, Jean Marc; Chauveau, Aurélie; Rivallan, Ronan; Clement, Didier; Courtois, Brigitte; Gramacho, Karina; Boland-Augé, Anne; Tahi, Mathias; Umaharan, Pathmanathan; Brunel, Dominique; Lanaud, Claire

2012-01-01

Theobroma cacao is an economically important tree of several tropical countries. Its genetic improvement is essential to provide protection against major diseases and improve chocolate quality. We discovered and mapped new expressed sequence tag-single nucleotide polymorphism (EST-SNP) and simple sequence repeat (SSR) markers and constructed a high-density genetic map. By screening 149 650 ESTs, 5246 SNPs were detected in silico, of which 1536 corresponded to genes with a putative function, while 851 had a clear polymorphic pattern across a collection of genetic resources. In addition, 409 new SSR markers were detected on the Criollo genome. Lastly, 681 new EST-SNPs and 163 new SSRs were added to the pre-existing 418 co-dominant markers to construct a large consensus genetic map. This high-density map and the set of new genetic markers identified in this study are a milestone in cocoa genomics and for marker-assisted breeding. The data are available at http://tropgenedb.cirad.fr. PMID:22210604

Large Scale Bacterial Colony Screening of Diversified FRET Biosensors

PubMed Central

Litzlbauer, Julia; Schifferer, Martina; Ng, David; Fabritius, Arne; Thestrup, Thomas; Griesbeck, Oliver

2015-01-01

Biosensors based on Förster Resonance Energy Transfer (FRET) between fluorescent protein mutants have started to revolutionize physiology and biochemistry. However, many types of FRET biosensors show relatively small FRET changes, making measurements with these probes challenging when used under sub-optimal experimental conditions. Thus, a major effort in the field currently lies in designing new optimization strategies for these types of sensors. Here we describe procedures for optimizing FRET changes by large scale screening of mutant biosensor libraries in bacterial colonies. We describe optimization of biosensor expression, permeabilization of bacteria, software tools for analysis, and screening conditions. The procedures reported here may help in improving FRET changes in multiple suitable classes of biosensors. PMID:26061878

Biocatalysis of a Paclitaxel Analogue: Conversion of Baccatin III to N-Debenzoyl-N-(2-furoyl)paclitaxel and Characterization of an Amino Phenylpropanoyl CoA Transferase.

PubMed

Thornburg, Chelsea K; Walter, Tyler; Walker, Kevin D

2017-11-07

In this study, we demonstrate an enzyme cascade reaction using a benzoate CoA ligase (BadA), a modified nonribosomal peptide synthase (PheAT), a phenylpropanoyltransferase (BAPT), and a benzoyltransferase (NDTNBT) to produce an anticancer paclitaxel analogue and its precursor from the commercially available biosynthetic intermediate baccatin III. BAPT and NDTNBT are acyltransferases on the biosynthetic pathway to the antineoplastic drug paclitaxel in Taxus plants. For this study, we addressed the recalcitrant expression of BAPT by expressing it as a soluble maltose binding protein fusion (MBP-BAPT). Further, the preparative-scale in vitro biocatalysis of phenylisoserinyl CoA using PheAT enabled thorough kinetic analysis of MBP-BAPT, for the first time, with the cosubstrate baccatin III. The turnover rate of MBP-BAPT was calculated for the product N-debenzoylpaclitaxel, a key intermediate to various bioactive paclitaxel analogues. MBP-BAPT also converted, albeit more slowly, 10-deacetylbaccatin III to N-deacyldocetaxel, a precursor of the pharmaceutical docetaxel. With PheAT available to make phenylisoserinyl CoA and kinetic characterization of MBP-BAPT, we used Michaelis-Menten parameters of the four enzymes to adjust catalyst and substrate loads in a 200-μL one-pot reaction. This multienzyme network produced a paclitaxel analogue N-debenzoyl-N-(2-furoyl)paclitaxel (230 ng) that is more cytotoxic than paclitaxel against certain macrophage cell types. Also in this pilot reaction, the versatile N-debenzoylpaclitaxel intermediate was made at an amount 20-fold greater than the N-(2-furoyl) product. This reaction network has great potential for optimization to scale-up production and is attractive in its regioselective O- and N-acylation steps that remove protecting group manipulations used in paclitaxel analogue synthesis.

FOXP2-positive diffuse large B-cell lymphomas exhibit a poor response to R-CHOP therapy and distinct biological signatures

PubMed Central

Wong, Kah Keng; Gascoyne, Duncan M.; Soilleux, Elizabeth J.; Lyne, Linden; Spearman, Hayley; Roncador, Giovanna; Pedersen, Lars M.; Møller, Michael B.; Green, Tina M.; Banham, Alison H.

2016-01-01

FOXP2 shares partially overlapping normal tissue expression and functionality with FOXP1; an established diffuse large B-cell lymphoma (DLBCL) oncogene and marker of poor prognosis. FOXP2 is expressed in the plasma cell malignancy multiple myeloma but has not been studied in DLBCL, where a poor prognosis activated B-cell (ABC)-like subtype display partially blocked plasma cell differentiation. FOXP2 protein expression was detected in ABC-DLBCL cell lines, and in primary DLBCL samples tumoral FOXP2 protein expression was detected in both germinal center B-cell-like (GCB) and non-GCB DLBCL. In biopsies from DLBCL patients treated with immunochemotherapy (R-CHOP), ≥ 20% nuclear tumoral FOXP2-positivity (n = 24/158) correlated with significantly inferior overall survival (OS: P = 0.0017) and progression-free survival (PFS: P = 0.0096). This remained significant in multivariate analysis against either the international prognostic index score or the non-GCB DLBCL phenotype (P < 0.05 for both OS and PFS). Expression of BLIMP1, a marker of plasmacytic differentiation that is commonly inactivated in ABC-DLBCL, did not correlate with patient outcome or FOXP2 expression in this series. Increased frequency of FOXP2 expression significantly correlated with FOXP1-positivity (P = 0.0187), and FOXP1 co-immunoprecipitated FOXP2 from ABC-DLBCL cells indicating that these proteins can co-localize in a multi-protein complex. FOXP2-positive DLBCL had reduced expression of HIP1R (P = 0.0348), which is directly repressed by FOXP1, and exhibited distinct patterns of gene expression. Specifically in ABC-DLBCL these were associated with lower expression of immune response and T-cell receptor signaling pathways. Further studies are warranted to investigate the potential functional cooperativity between FOXP1 and FOXP2 in repressing immune responses during the pathogenesis of high-risk DLBCL. PMID:27224915

FOXP2-positive diffuse large B-cell lymphomas exhibit a poor response to R-CHOP therapy and distinct biological signatures.

PubMed

Wong, Kah Keng; Gascoyne, Duncan M; Soilleux, Elizabeth J; Lyne, Linden; Spearman, Hayley; Roncador, Giovanna; Pedersen, Lars M; Møller, Michael B; Green, Tina M; Banham, Alison H

2016-08-16

FOXP2 shares partially overlapping normal tissue expression and functionality with FOXP1; an established diffuse large B-cell lymphoma (DLBCL) oncogene and marker of poor prognosis. FOXP2 is expressed in the plasma cell malignancy multiple myeloma but has not been studied in DLBCL, where a poor prognosis activated B-cell (ABC)-like subtype display partially blocked plasma cell differentiation. FOXP2 protein expression was detected in ABC-DLBCL cell lines, and in primary DLBCL samples tumoral FOXP2 protein expression was detected in both germinal center B-cell-like (GCB) and non-GCB DLBCL. In biopsies from DLBCL patients treated with immunochemotherapy (R-CHOP), ≥ 20% nuclear tumoral FOXP2-positivity (n = 24/158) correlated with significantly inferior overall survival (OS: P = 0.0017) and progression-free survival (PFS: P = 0.0096). This remained significant in multivariate analysis against either the international prognostic index score or the non-GCB DLBCL phenotype (P < 0.05 for both OS and PFS). Expression of BLIMP1, a marker of plasmacytic differentiation that is commonly inactivated in ABC-DLBCL, did not correlate with patient outcome or FOXP2 expression in this series. Increased frequency of FOXP2 expression significantly correlated with FOXP1-positivity (P = 0.0187), and FOXP1 co-immunoprecipitated FOXP2 from ABC-DLBCL cells indicating that these proteins can co-localize in a multi-protein complex. FOXP2-positive DLBCL had reduced expression of HIP1R (P = 0.0348), which is directly repressed by FOXP1, and exhibited distinct patterns of gene expression. Specifically in ABC-DLBCL these were associated with lower expression of immune response and T-cell receptor signaling pathways. Further studies are warranted to investigate the potential functional cooperativity between FOXP1 and FOXP2 in repressing immune responses during the pathogenesis of high-risk DLBCL.

A regulation probability model-based meta-analysis of multiple transcriptomics data sets for cancer biomarker identification.

PubMed

Xie, Xin-Ping; Xie, Yu-Feng; Wang, Hong-Qiang

2017-08-23

Large-scale accumulation of omics data poses a pressing challenge of integrative analysis of multiple data sets in bioinformatics. An open question of such integrative analysis is how to pinpoint consistent but subtle gene activity patterns across studies. Study heterogeneity needs to be addressed carefully for this goal. This paper proposes a regulation probability model-based meta-analysis, jGRP, for identifying differentially expressed genes (DEGs). The method integrates multiple transcriptomics data sets in a gene regulatory space instead of in a gene expression space, which makes it easy to capture and manage data heterogeneity across studies from different laboratories or platforms. Specifically, we transform gene expression profiles into a united gene regulation profile across studies by mathematically defining two gene regulation events between two conditions and estimating their occurring probabilities in a sample. Finally, a novel differential expression statistic is established based on the gene regulation profiles, realizing accurate and flexible identification of DEGs in gene regulation space. We evaluated the proposed method on simulation data and real-world cancer datasets and showed the effectiveness and efficiency of jGRP in identifying DEGs identification in the context of meta-analysis. Data heterogeneity largely influences the performance of meta-analysis of DEGs identification. Existing different meta-analysis methods were revealed to exhibit very different degrees of sensitivity to study heterogeneity. The proposed method, jGRP, can be a standalone tool due to its united framework and controllable way to deal with study heterogeneity.

Regulation of gene expression is associated with tolerance of the Arctic copepod Calanus glacialis to CO2-acidified sea water.

PubMed

Bailey, Allison; De Wit, Pierre; Thor, Peter; Browman, Howard I; Bjelland, Reidun; Shema, Steven; Fields, David M; Runge, Jeffrey A; Thompson, Cameron; Hop, Haakon

2017-09-01

Ocean acidification is the increase in seawater p CO 2 due to the uptake of atmospheric anthropogenic CO 2 , with the largest changes predicted to occur in the Arctic seas. For some marine organisms, this change in p CO 2 , and associated decrease in pH, represents a climate change-related stressor. In this study, we investigated the gene expression patterns of nauplii of the Arctic copepod Calanus glacialis cultured at low pH levels. We have previously shown that organismal-level performance (development, growth, respiration) of C. glacialis nauplii is unaffected by low pH. Here, we investigated the molecular-level response to lowered pH in order to elucidate the physiological processes involved in this tolerance. Nauplii from wild-caught C. glacialis were cultured at four pH levels (8.05, 7.9, 7.7, 7.5). At stage N6, mRNA was extracted and sequenced using RNA-seq. The physiological functionality of the proteins identified was categorized using Gene Ontology and KEGG pathways. We found that the expression of 151 contigs varied significantly with pH on a continuous scale (93% downregulated with decreasing pH). Gene set enrichment analysis revealed that, of the processes downregulated, many were components of the universal cellular stress response, including DNA repair, redox regulation, protein folding, and proteolysis. Sodium:proton antiporters were among the processes significantly upregulated, indicating that these ion pumps were involved in maintaining cellular pH homeostasis. C. glacialis significantly alters its gene expression at low pH, although they maintain normal larval development. Understanding what confers tolerance to some species will support our ability to predict the effects of future ocean acidification on marine organisms.

A phase-field lattice Boltzmann model for simulating multiphase flows in porous media: Application and comparison to experiments of CO2 sequestration at pore scale

NASA Astrophysics Data System (ADS)

Fakhari, Abbas; Li, Yaofa; Bolster, Diogo; Christensen, Kenneth T.

2018-04-01

We implement a phase-field based lattice-Boltzmann (LB) method for numerical simulation of multiphase flows in heterogeneous porous media at pore scales with wettability effects. The present method can handle large density and viscosity ratios, pertinent to many practical problems. As a practical application, we study multiphase flow in a micromodel representative of CO2 invading a water-saturated porous medium at reservoir conditions, both numerically and experimentally. We focus on two flow cases with (i) a crossover from capillary fingering to viscous fingering at a relatively small capillary number, and (ii) viscous fingering at a relatively moderate capillary number. Qualitative and quantitative comparisons are made between numerical results and experimental data for temporal and spatial CO2 saturation profiles, and good agreement is found. In particular, a correlation analysis shows that any differences between simulations and results are comparable to intra-experimental differences from replicate experiments. A key conclusion of this work is that system behavior is highly sensitive to boundary conditions, particularly inlet and outlet ones. We finish with a discussion on small-scale flow features, such as the emergence of strong recirculation zones as well as flow in which the residual phase is trapped, including a close look at the detailed formation of a water cone. Overall, the proposed model yields useful information, such as the spatiotemporal evolution of the CO2 front and instantaneous velocity fields, which are valuable for understanding the mechanisms of CO2 infiltration at the pore scale.

The stability and change of etiological influences on depression, anxiety symptoms and their co-occurrence across adolescence and young adulthood.

PubMed

Waszczuk, M A; Zavos, H M S; Gregory, A M; Eley, T C

2016-01-01

Depression and anxiety persist within and across diagnostic boundaries. The manner in which common v. disorder-specific genetic and environmental influences operate across development to maintain internalizing disorders and their co-morbidity is unclear. This paper investigates the stability and change of etiological influences on depression, panic, generalized, separation and social anxiety symptoms, and their co-occurrence, across adolescence and young adulthood. A total of 2619 twins/siblings prospectively reported symptoms of depression and anxiety at mean ages 15, 17 and 20 years. Each symptom scale showed a similar pattern of moderate continuity across development, largely underpinned by genetic stability. New genetic influences contributing to change in the developmental course of the symptoms emerged at each time point. All symptom scales correlated moderately with one another over time. Genetic influences, both stable and time-specific, overlapped considerably between the scales. Non-shared environmental influences were largely time- and symptom-specific, but some contributed moderately to the stability of depression and anxiety symptom scales. These stable, longitudinal environmental influences were highly correlated between the symptoms. The results highlight both stable and dynamic etiology of depression and anxiety symptom scales. They provide preliminary evidence that stable as well as newly emerging genes contribute to the co-morbidity between depression and anxiety across adolescence and young adulthood. Conversely, environmental influences are largely time-specific and contribute to change in symptoms over time. The results inform molecular genetics research and transdiagnostic treatment and prevention approaches.

An intersection network based on combining SNP co-association and RNA co-expression networks for feed utilization traits in Japanese Black cattle.

PubMed

Okada, D; Endo, S; Matsuda, H; Ogawa, S; Taniguchi, Y; Katsuta, T; Watanabe, T; Iwaisaki, H

2018-05-12

Genome-wide association studies (GWAS) of quantitative traits have detected numerous genetic associations, but they encounter difficulties in pinpointing prominent candidate genes and inferring gene networks. The present study used a systems genetics approach integrating GWAS results with external RNA-expression data to detect candidate gene networks in feed utilization and growth traits of Japanese Black cattle, which are matters of concern. A SNP co-association network was derived from significant correlations between SNPs with effects estimated by GWAS across seven phenotypic traits. The resulting network genes contained significant numbers of annotations related to the traits. Using bovine transcriptome data from a public database, an RNA co-expression network was inferred based on the similarity of expression patterns across different tissues. An intersection network was then generated by superimposing the SNP and RNA networks and extracting shared interactions. This intersection network contained four tissue-specific modules: nervous system, reproductive system, muscular system, and glands. To characterize the structure (topographical properties) of the three networks, their scale-free properties were evaluated, which revealed that the intersection network was the most scale-free. In the sub-network containing the most connected transcription factors (URI1, ROCK2 and ETV6), most genes were widely expressed across tissues, and genes previously shown to be involved in the traits were found. Results indicated that the current approach might be used to construct a gene network that better reflects biological information, providing encouragement for the genetic dissection of economically important quantitative traits.

Thermal oxidation of nuclear graphite: A large scale waste treatment option.

PubMed

Theodosiou, Alex; Jones, Abbie N; Marsden, Barry J

2017-01-01

This study has investigated the laboratory scale thermal oxidation of nuclear graphite, as a proof-of-concept for the treatment and decommissioning of reactor cores on a larger industrial scale. If showed to be effective, this technology could have promising international significance with a considerable impact on the nuclear waste management problem currently facing many countries worldwide. The use of thermal treatment of such graphite waste is seen as advantageous since it will decouple the need for an operational Geological Disposal Facility (GDF). Particulate samples of Magnox Reactor Pile Grade-A (PGA) graphite, were oxidised in both air and 60% O2, over the temperature range 400-1200°C. Oxidation rates were found to increase with temperature, with a particular rise between 700-800°C, suggesting a change in oxidation mechanism. A second increase in oxidation rate was observed between 1000-1200°C and was found to correspond to a large increase in the CO/CO2 ratio, as confirmed through gas analysis. Increasing the oxidant flow rate gave a linear increase in oxidation rate, up to a certain point, and maximum rates of 23.3 and 69.6 mg / min for air and 60% O2 respectively were achieved at a flow of 250 ml / min and temperature of 1000°C. These promising results show that large-scale thermal treatment could be a potential option for the decommissioning of graphite cores, although the design of the plant would need careful consideration in order to achieve optimum efficiency and throughput.

Thermal oxidation of nuclear graphite: A large scale waste treatment option

PubMed Central

Jones, Abbie N.; Marsden, Barry J.

2017-01-01

This study has investigated the laboratory scale thermal oxidation of nuclear graphite, as a proof-of-concept for the treatment and decommissioning of reactor cores on a larger industrial scale. If showed to be effective, this technology could have promising international significance with a considerable impact on the nuclear waste management problem currently facing many countries worldwide. The use of thermal treatment of such graphite waste is seen as advantageous since it will decouple the need for an operational Geological Disposal Facility (GDF). Particulate samples of Magnox Reactor Pile Grade-A (PGA) graphite, were oxidised in both air and 60% O2, over the temperature range 400–1200°C. Oxidation rates were found to increase with temperature, with a particular rise between 700–800°C, suggesting a change in oxidation mechanism. A second increase in oxidation rate was observed between 1000–1200°C and was found to correspond to a large increase in the CO/CO2 ratio, as confirmed through gas analysis. Increasing the oxidant flow rate gave a linear increase in oxidation rate, up to a certain point, and maximum rates of 23.3 and 69.6 mg / min for air and 60% O2 respectively were achieved at a flow of 250 ml / min and temperature of 1000°C. These promising results show that large-scale thermal treatment could be a potential option for the decommissioning of graphite cores, although the design of the plant would need careful consideration in order to achieve optimum efficiency and throughput. PMID:28793326

Systems analysis of transcriptome data provides new hypotheses about Arabidopsis root response to nitrate treatments

PubMed Central

Canales, Javier; Moyano, Tomás C.; Villarroel, Eva; Gutiérrez, Rodrigo A.

2014-01-01

Nitrogen (N) is an essential macronutrient for plant growth and development. Plants adapt to changes in N availability partly by changes in global gene expression. We integrated publicly available root microarray data under contrasting nitrate conditions to identify new genes and functions important for adaptive nitrate responses in Arabidopsis thaliana roots. Overall, more than 2000 genes exhibited changes in expression in response to nitrate treatments in Arabidopsis thaliana root organs. Global regulation of gene expression by nitrate depends largely on the experimental context. However, despite significant differences from experiment to experiment in the identity of regulated genes, there is a robust nitrate response of specific biological functions. Integrative gene network analysis uncovered relationships between nitrate-responsive genes and 11 highly co-expressed gene clusters (modules). Four of these gene network modules have robust nitrate responsive functions such as transport, signaling, and metabolism. Network analysis hypothesized G2-like transcription factors are key regulatory factors controlling transport and signaling functions. Our meta-analysis highlights the role of biological processes not studied before in the context of the nitrate response such as root hair development and provides testable hypothesis to advance our understanding of nitrate responses in plants. PMID:24570678

Thymidylate synthase (TS) gene expression in primary lung cancer patients: a large-scale study in Japanese population.

PubMed

Tanaka, F; Wada, H; Fukui, Y; Fukushima, M

2011-08-01

Previous small-sized studies showed lower thymidylate synthase (TS) expression in adenocarcinoma of the lung, which may explain higher antitumor activity of TS-inhibiting agents such as pemetrexed. To quantitatively measure TS gene expression in a large-scale Japanese population (n = 2621) with primary lung cancer, laser-captured microdissected sections were cut from primary tumors, surrounding normal lung tissues and involved nodes. TS gene expression level in primary tumor was significantly higher than that in normal lung tissue (mean TS/β-actin, 3.4 and 1.0, respectively; P < 0.01), and TS gene expression level was further higher in involved node (mean TS/β-actin, 7.7; P < 0.01). Analyses of TS gene expression levels in primary tumor according to histologic cell type revealed that small-cell carcinoma showed highest TS expression (mean TS/β-actin, 13.8) and that squamous cell carcinoma showed higher TS expression as compared with adenocarcinoma (mean TS/β-actin, 4.3 and 2.3, respectively; P < 0.01); TS gene expression was significantly increased along with a decrease in the grade of tumor cell differentiation. There was no significant difference in TS gene expression according to any other patient characteristics including tumor progression. Lower TS expression in adenocarcinoma of the lung was confirmed in a large-scale study.

Material Characterization for the Analysis of Skin/Stiffener Separation

NASA Technical Reports Server (NTRS)

Davila, Carlos G.; Leone, Frank A.; Song, Kyongchan; Ratcliffe, James G.; Rose, Cheryl A.

2017-01-01

Test results show that separation failure in co-cured skin/stiffener interfaces is characterized by dense networks of interacting cracks and crack path migrations that are not present in standard characterization tests for delamination. These crack networks result in measurable large-scale and sub-ply-scale R curve toughening mechanisms, such as fiber bridging, crack migration, and crack delving. Consequently, a number of unknown issues exist regarding the level of analysis detail that is required for sufficient predictive fidelity. The objective of the present paper is to examine some of the difficulties associated with modeling separation failure in stiffened composite structures. A procedure to characterize the interfacial material properties is proposed and the use of simplified models based on empirical interface properties is evaluated.

A Multi-scale Approach for CO2 Accounting and Risk Analysis in CO2 Enhanced Oil Recovery Sites

NASA Astrophysics Data System (ADS)

Dai, Z.; Viswanathan, H. S.; Middleton, R. S.; Pan, F.; Ampomah, W.; Yang, C.; Jia, W.; Lee, S. Y.; McPherson, B. J. O. L.; Grigg, R.; White, M. D.

2015-12-01

Using carbon dioxide in enhanced oil recovery (CO2-EOR) is a promising technology for emissions management because CO2-EOR can dramatically reduce carbon sequestration costs in the absence of greenhouse gas emissions policies that include incentives for carbon capture and storage. This study develops a multi-scale approach to perform CO2 accounting and risk analysis for understanding CO2 storage potential within an EOR environment at the Farnsworth Unit of the Anadarko Basin in northern Texas. A set of geostatistical-based Monte Carlo simulations of CO2-oil-water flow and transport in the Marrow formation are conducted for global sensitivity and statistical analysis of the major risk metrics: CO2 injection rate, CO2 first breakthrough time, CO2 production rate, cumulative net CO2 storage, cumulative oil and CH4 production, and water injection and production rates. A global sensitivity analysis indicates that reservoir permeability, porosity, and thickness are the major intrinsic reservoir parameters that control net CO2 injection/storage and oil/CH4 recovery rates. The well spacing (the distance between the injection and production wells) and the sequence of alternating CO2 and water injection are the major operational parameters for designing an effective five-spot CO2-EOR pattern. The response surface analysis shows that net CO2 injection rate increases with the increasing reservoir thickness, permeability, and porosity. The oil/CH4 production rates are positively correlated to reservoir permeability, porosity and thickness, but negatively correlated to the initial water saturation. The mean and confidence intervals are estimated for quantifying the uncertainty ranges of the risk metrics. The results from this study provide useful insights for understanding the CO2 storage potential and the corresponding risks of commercial-scale CO2-EOR fields.

Engineering of Baeyer-Villiger monooxygenase-based Escherichia coli biocatalyst for large scale biotransformation of ricinoleic acid into (Z)-11-(heptanoyloxy)undec-9-enoic acid

PubMed Central

Seo, Joo-Hyun; Kim, Hwan-Hee; Jeon, Eun-Yeong; Song, Young-Ha; Shin, Chul-Soo; Park, Jin-Byung

2016-01-01

Baeyer-Villiger monooxygenases (BVMOs) are able to catalyze regiospecific Baeyer-Villiger oxygenation of a variety of cyclic and linear ketones to generate the corresponding lactones and esters, respectively. However, the enzymes are usually difficult to express in a functional form in microbial cells and are rather unstable under process conditions hindering their large-scale applications. Thereby, we investigated engineering of the BVMO from Pseudomonas putida KT2440 and the gene expression system to improve its activity and stability for large-scale biotransformation of ricinoleic acid (1) into the ester (i.e., (Z)-11-(heptanoyloxy)undec-9-enoic acid) (3), which can be hydrolyzed into 11-hydroxyundec-9-enoic acid (5) (i.e., a precursor of polyamide-11) and n-heptanoic acid (4). The polyionic tag-based fusion engineering of the BVMO and the use of a synthetic promoter for constitutive enzyme expression allowed the recombinant Escherichia coli expressing the BVMO and the secondary alcohol dehydrogenase of Micrococcus luteus to produce the ester (3) to 85 mM (26.6 g/L) within 5 h. The 5 L scale biotransformation process was then successfully scaled up to a 70 L bioreactor; 3 was produced to over 70 mM (21.9 g/L) in the culture medium 6 h after biotransformation. This study demonstrated that the BVMO-based whole-cell reactions can be applied for large-scale biotransformations. PMID:27311560

Techno-economic analysis of horseradish peroxidase production using a transient expression system in Nicotiana benthamiana.

PubMed

Walwyn, David Richard; Huddy, Suzanne M; Rybicki, Edward P

2015-01-01

Despite the advantages of plant-based transient expression systems relative to microbial or mammalian cell systems, the commercial production of recombinant proteins using plants has not yet been achieved to any significant extent. One of the challenges has been the lack of published data on the costs of manufacture for products other than biopharmaceuticals. In this study, we report on the techno-economic analysis of the production of a standard commercial enzyme, namely, horseradish peroxidase (HRP), using a transient expression system in Nicotiana benthamiana. Based on the proven plant yield of 240 mg HRP/kg biomass, a biomass productivity of 15-kg biomass/m(2)/year and a process yield of 54 % (mg HRP product/mg HRP in biomass), it is apparent that HRP can be manufactured economically via transient expression in plants in a large-scale facility (>5 kg HRP/year). At this level, the process is competitive versus the existing technology (extraction of the enzyme from horseradish), and the product is of comparable or improved activity, containing only the preferred isoenzyme C. Production scale, protein yield and biomass productivity are found to be the most important determinants of overall viability.

Large-scale adenovirus and poxvirus-vectored vaccine manufacturing to enable clinical trials.

PubMed

Kallel, Héla; Kamen, Amine A

2015-05-01

Efforts to make vaccines against infectious diseases and immunotherapies for cancer have evolved to utilize a variety of heterologous expression systems such as viral vectors. These vectors are often attenuated or engineered to safely deliver genes encoding antigens of different pathogens. Adenovirus and poxvirus vectors are among the viral vectors that are most frequently used to develop prophylactic vaccines against infectious diseases as well as therapeutic cancer vaccines. This mini-review describes the trends and processes in large-scale production of adenovirus and poxvirus vectors to meet the needs of clinical applications. We briefly describe the general principles for the production and purification of adenovirus and poxvirus viral vectors. Currently, adenovirus and poxvirus vector manufacturing methods rely on well-established cell culture technologies. Several improvements have been evaluated to increase the yield and to reduce the overall manufacturing cost, such as cultivation at high cell densities and continuous downstream processing. Additionally, advancements in vector characterization will greatly facilitate the development of novel vectored vaccine candidates. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Vectors for co-expression of an unrestricted number of proteins

PubMed Central

Scheich, Christoph; Kümmel, Daniel; Soumailakakis, Dimitri; Heinemann, Udo; Büssow, Konrad

2007-01-01

A vector system is presented that allows generation of E. coli co-expression clones by a standardized, robust cloning procedure. The number of co-expressed proteins is not limited. Five ‘pQLink’ vectors for expression of His-tag and GST-tag fusion proteins as well as untagged proteins and for cloning by restriction enzymes or Gateway cloning were generated. The vectors allow proteins to be expressed individually; to achieve co-expression, two pQLink plasmids are combined by ligation-independent cloning. pQLink co-expression plasmids can accept an unrestricted number of genes. As an example, the co-expression of a heterotetrameric human transport protein particle (TRAPP) complex from a single plasmid, its isolation and analysis of its stoichiometry are shown. pQLink clones can be used directly for pull-down experiments if the proteins are expressed with different tags. We demonstrate pull-down experiments of human valosin-containing protein (VCP) with fragments of the autocrine motility factor receptor (AMFR). The cloning method avoids PCR or gel isolation of restriction fragments, and a single resistance marker and origin of replication are used, allowing over-expression of rare tRNAs from a second plasmid. It is expected that applications are not restricted to bacteria, but could include co-expression in other hosts such as Bacluovirus/insect cells. PMID:17311810

Glutamate 338 is an electrostatic facilitator of C–Co bond breakage in a dynamic/electrostatic model of catalysis by ornithine aminomutase

PubMed Central

Menon, Binuraj R K; Menon, Navya; Fisher, Karl; Rigby, Stephen E J; Leys, David; Scrutton, Nigel S

2015-01-01

How cobalamin-dependent enzymes promote C–Co homolysis to initiate radical catalysis has been debated extensively. For the pyridoxal 5′-phosphate and cobalamin-dependent enzymes lysine 5,6-aminomutase and ornithine 4,5-aminomutase (OAM), large-scale re-orientation of the cobalamin-binding domain linked to C–Co bond breakage has been proposed. In these models, substrate binding triggers dynamic sampling of the B12-binding Rossmann domain to achieve a catalytically competent ‘closed’ conformational state. In ‘closed’ conformations of OAM, Glu338 is thought to facilitate C–Co bond breakage by close association with the cobalamin adenosyl group. We investigated this using stopped-flow continuous-wave photolysis, viscosity dependence kinetic measurements, and electron paramagnetic resonance spectroscopy of a series of Glu338 variants. We found that substrate-induced C–Co bond homolysis is compromised in Glu388 variant forms of OAM, although photolysis of the C–Co bond is not affected by the identity of residue 338. Electrostatic interactions of Glu338 with the 5′-deoxyadenosyl group of B12 potentiate C–Co bond homolysis in ‘closed’ conformations only; these conformations are unlocked by substrate binding. Our studies extend earlier models that identified a requirement for large-scale motion of the cobalamin domain. Our findings indicate that large-scale motion is required to pre-organize the active site by enabling transient formation of ‘closed’ conformations of OAM. In ‘closed’ conformations, Glu338 interacts with the 5′-deoxyadenosyl group of cobalamin. This interaction is required to potentiate C–Co homolysis, and is a crucial component of the approximately 1012 rate enhancement achieved by cobalamin-dependent enzymes for C–Co bond homolysis. PMID:25627283

Genetic engineering of Synechocystis PCC6803 for the photoautotrophic production of the sweetener erythritol.

PubMed

van der Woude, Aniek D; Perez Gallego, Ruth; Vreugdenhil, Angie; Puthan Veetil, Vinod; Chroumpi, Tania; Hellingwerf, Klaas J

2016-04-08

Erythritol is a polyol that is used in the food and beverage industry. Due to its non-caloric and non-cariogenic properties, the popularity of this sweetener is increasing. Large scale production of erythritol is currently based on conversion of glucose by selected fungi. In this study, we describe a biotechnological process to produce erythritol from light and CO2, using engineered Synechocystis sp. PCC6803. By functionally expressing codon-optimized genes encoding the erythrose-4-phosphate phosphatase TM1254 and the erythrose reductase Gcy1p, or GLD1, this cyanobacterium can directly convert the Calvin cycle intermediate erythrose-4-phosphate into erythritol via a two-step process and release the polyol sugar in the extracellular medium. Further modifications targeted enzyme expression and pathway intermediates. After several optimization steps, the best strain, SEP024, produced up to 2.1 mM (256 mg/l) erythritol, excreted in the medium.

CGDV: a webtool for circular visualization of genomics and transcriptomics data.

PubMed

Jha, Vineet; Singh, Gulzar; Kumar, Shiva; Sonawane, Amol; Jere, Abhay; Anamika, Krishanpal

2017-10-24

Interpretation of large-scale data is very challenging and currently there is scarcity of web tools which support automated visualization of a variety of high throughput genomics and transcriptomics data and for a wide variety of model organisms along with user defined karyotypes. Circular plot provides holistic visualization of high throughput large scale data but it is very complex and challenging to generate as most of the available tools need informatics expertise to install and run them. We have developed CGDV (Circos for Genomics and Transcriptomics Data Visualization), a webtool based on Circos, for seamless and automated visualization of a variety of large scale genomics and transcriptomics data. CGDV takes output of analyzed genomics or transcriptomics data of different formats, such as vcf, bed, xls, tab limited matrix text file, CNVnator raw output and Gene fusion raw output, to plot circular view of the sample data. CGDV take cares of generating intermediate files required for circos. CGDV is freely available at https://cgdv-upload.persistent.co.in/cgdv/ . The circular plot for each data type is tailored to gain best biological insights into the data. The inter-relationship between data points, homologous sequences, genes involved in fusion events, differential expression pattern, sequencing depth, types and size of variations and enrichment of DNA binding proteins can be seen using CGDV. CGDV thus helps biologists and bioinformaticians to visualize a variety of genomics and transcriptomics data seamlessly.

Functional regression method for whole genome eQTL epistasis analysis with sequencing data.

PubMed

Xu, Kelin; Jin, Li; Xiong, Momiao

2017-05-18

Epistasis plays an essential rule in understanding the regulation mechanisms and is an essential component of the genetic architecture of the gene expressions. However, interaction analysis of gene expressions remains fundamentally unexplored due to great computational challenges and data availability. Due to variation in splicing, transcription start sites, polyadenylation sites, post-transcriptional RNA editing across the entire gene, and transcription rates of the cells, RNA-seq measurements generate large expression variability and collectively create the observed position level read count curves. A single number for measuring gene expression which is widely used for microarray measured gene expression analysis is highly unlikely to sufficiently account for large expression variation across the gene. Simultaneously analyzing epistatic architecture using the RNA-seq and whole genome sequencing (WGS) data poses enormous challenges. We develop a nonlinear functional regression model (FRGM) with functional responses where the position-level read counts within a gene are taken as a function of genomic position, and functional predictors where genotype profiles are viewed as a function of genomic position, for epistasis analysis with RNA-seq data. Instead of testing the interaction of all possible pair-wises SNPs, the FRGM takes a gene as a basic unit for epistasis analysis, which tests for the interaction of all possible pairs of genes and use all the information that can be accessed to collectively test interaction between all possible pairs of SNPs within two genome regions. By large-scale simulations, we demonstrate that the proposed FRGM for epistasis analysis can achieve the correct type 1 error and has higher power to detect the interactions between genes than the existing methods. The proposed methods are applied to the RNA-seq and WGS data from the 1000 Genome Project. The numbers of pairs of significantly interacting genes after Bonferroni correction identified using FRGM, RPKM and DESeq were 16,2361, 260 and 51, respectively, from the 350 European samples. The proposed FRGM for epistasis analysis of RNA-seq can capture isoform and position-level information and will have a broad application. Both simulations and real data analysis highlight the potential for the FRGM to be a good choice of the epistatic analysis with sequencing data.

Effects of threshold on the topology of gene co-expression networks.

PubMed

Couto, Cynthia Martins Villar; Comin, César Henrique; Costa, Luciano da Fontoura

2017-09-26

Several developments regarding the analysis of gene co-expression profiles using complex network theory have been reported recently. Such approaches usually start with the construction of an unweighted gene co-expression network, therefore requiring the selection of a suitable threshold defining which pairs of vertices will be connected. We aimed at addressing such an important problem by suggesting and comparing five different approaches for threshold selection. Each of the methods considers a respective biologically-motivated criterion for electing a potentially suitable threshold. A set of 21 microarray experiments from different biological groups was used to investigate the effect of applying the five proposed criteria to several biological situations. For each experiment, we used the Pearson correlation coefficient to measure the relationship between each gene pair, and the resulting weight matrices were thresholded considering several values, generating respective adjacency matrices (co-expression networks). Each of the five proposed criteria was then applied in order to select the respective threshold value. The effects of these thresholding approaches on the topology of the resulting networks were compared by using several measurements, and we verified that, depending on the database, the impact on the topological properties can be large. However, a group of databases was verified to be similarly affected by most of the considered criteria. Based on such results, it can be suggested that when the generated networks present similar measurements, the thresholding method can be chosen with greater freedom. If the generated networks are markedly different, the thresholding method that better suits the interests of each specific research study represents a reasonable choice.

Evaluation of Kirkwood-Buff integrals via finite size scaling: a large scale molecular dynamics study

NASA Astrophysics Data System (ADS)

Dednam, W.; Botha, A. E.

2015-01-01

Solvation of bio-molecules in water is severely affected by the presence of co-solvent within the hydration shell of the solute structure. Furthermore, since solute molecules can range from small molecules, such as methane, to very large protein structures, it is imperative to understand the detailed structure-function relationship on the microscopic level. For example, it is useful know the conformational transitions that occur in protein structures. Although such an understanding can be obtained through large-scale molecular dynamic simulations, it is often the case that such simulations would require excessively large simulation times. In this context, Kirkwood-Buff theory, which connects the microscopic pair-wise molecular distributions to global thermodynamic properties, together with the recently developed technique, called finite size scaling, may provide a better method to reduce system sizes, and hence also the computational times. In this paper, we present molecular dynamics trial simulations of biologically relevant low-concentration solvents, solvated by aqueous co-solvent solutions. In particular we compare two different methods of calculating the relevant Kirkwood-Buff integrals. The first (traditional) method computes running integrals over the radial distribution functions, which must be obtained from large system-size NVT or NpT simulations. The second, newer method, employs finite size scaling to obtain the Kirkwood-Buff integrals directly by counting the particle number fluctuations in small, open sub-volumes embedded within a larger reservoir that can be well approximated by a much smaller simulation cell. In agreement with previous studies, which made a similar comparison for aqueous co-solvent solutions, without the additional solvent, we conclude that the finite size scaling method is also applicable to the present case, since it can produce computationally more efficient results which are equivalent to the more costly radial distribution function method.

A Drosophila Toolkit for the Visualization and Quantification of Viral Replication Launched from Transgenic Genomes

PubMed Central

Wernet, Mathias F.; Klovstad, Martha; Clandinin, Thomas R.

2014-01-01

Arthropod RNA viruses pose a serious threat to human health, yet many aspects of their replication cycle remain incompletely understood. Here we describe a versatile Drosophila toolkit of transgenic, self-replicating genomes (‘replicons’) from Sindbis virus that allow rapid visualization and quantification of viral replication in vivo. We generated replicons expressing Luciferase for the quantification of viral replication, serving as useful new tools for large-scale genetic screens for identifying cellular pathways that influence viral replication. We also present a new binary system in which replication-deficient viral genomes can be activated ‘in trans’, through co-expression of an intact replicon contributing an RNA-dependent RNA polymerase. The utility of this toolkit for studying virus biology is demonstrated by the observation of stochastic exclusion between replicons expressing different fluorescent proteins, when co-expressed under control of the same cellular promoter. This process is analogous to ‘superinfection exclusion’ between virus particles in cell culture, a process that is incompletely understood. We show that viral polymerases strongly prefer to replicate the genome that encoded them, and that almost invariably only a single virus genome is stochastically chosen for replication in each cell. Our in vivo system now makes this process amenable to detailed genetic dissection. Thus, this toolkit allows the cell-type specific, quantitative study of viral replication in a genetic model organism, opening new avenues for molecular, genetic and pharmacological dissection of virus biology and tool development. PMID:25386852

Immortalized porcine mesenchymal cells derived from nasal mucosa, lungs, lymph nodes, spleen and bone marrow retain their stemness properties and trigger the expression of siglec-1 in co-cultured blood monocytic cells

PubMed Central

Garba, Abubakar; Desmarets, Lowiese M. B.; Acar, Delphine D.; Devriendt, Bert; Nauwynck, Hans J.

2017-01-01

Mesenchymal stromal cells have been isolated from different sources. They are multipotent cells capable of differentiating into many different cell types, including osteocytes, chondrocytes and adipocytes. They possess a therapeutic potential in the management of immune disorders and the repair of damaged tissues. Previous work in our laboratory showed an increase of the percentages of CD172a+, CD14+, CD163+, Siglec-1+, CD4+ and CD8+ hematopoietic cells, when co-cultured with immortalized mesenchymal cells derived from bone marrow. The present work aimed to demonstrate the stemness properties of SV40-immortalized mesenchymal cells derived from nasal mucosa, lungs, spleen, lymph nodes and red bone marrow and their immunomodulatory effect on blood monocytes. Mesenchymal cells from nasal mucosa, lungs, spleen, lymph nodes and red bone marrow were isolated and successfully immortalized using simian virus 40 large T antigen (SV40LT) and later, co-cultured with blood monocytes, in order to examine their differentiation stage (expression of Siglec-1). Flow cytometric analysis revealed that the five mesenchymal cell lines were positive for mesenchymal cell markers CD105, CD44, CD90 and CD29, but lacked the expression of myeloid cell markers CD16 and CD11b. Growth analysis of the cells demonstrated that bone marrow derived-mesenchymal cells proliferated faster compared with those derived from the other tissues. All five mesenchymal cell lines co-cultured with blood monocytes for 1, 2 and 7 days triggered the expression of siglec-1 in the monocytes. In contrast, no siglec-1+ cells were observed in monocyte cultures without mesenchymal cell lines. Mesenchymal cells isolated from nasal mucosa, lungs, spleen, lymph nodes and bone marrow were successfully immortalized and these cell lines retained their stemness properties and displayed immunomodulatory effects on blood monocytes. PMID:29036224

Immortalized porcine mesenchymal cells derived from nasal mucosa, lungs, lymph nodes, spleen and bone marrow retain their stemness properties and trigger the expression of siglec-1 in co-cultured blood monocytic cells.

PubMed

Garba, Abubakar; Desmarets, Lowiese M B; Acar, Delphine D; Devriendt, Bert; Nauwynck, Hans J

2017-01-01

Mesenchymal stromal cells have been isolated from different sources. They are multipotent cells capable of differentiating into many different cell types, including osteocytes, chondrocytes and adipocytes. They possess a therapeutic potential in the management of immune disorders and the repair of damaged tissues. Previous work in our laboratory showed an increase of the percentages of CD172a+, CD14+, CD163+, Siglec-1+, CD4+ and CD8+ hematopoietic cells, when co-cultured with immortalized mesenchymal cells derived from bone marrow. The present work aimed to demonstrate the stemness properties of SV40-immortalized mesenchymal cells derived from nasal mucosa, lungs, spleen, lymph nodes and red bone marrow and their immunomodulatory effect on blood monocytes. Mesenchymal cells from nasal mucosa, lungs, spleen, lymph nodes and red bone marrow were isolated and successfully immortalized using simian virus 40 large T antigen (SV40LT) and later, co-cultured with blood monocytes, in order to examine their differentiation stage (expression of Siglec-1). Flow cytometric analysis revealed that the five mesenchymal cell lines were positive for mesenchymal cell markers CD105, CD44, CD90 and CD29, but lacked the expression of myeloid cell markers CD16 and CD11b. Growth analysis of the cells demonstrated that bone marrow derived-mesenchymal cells proliferated faster compared with those derived from the other tissues. All five mesenchymal cell lines co-cultured with blood monocytes for 1, 2 and 7 days triggered the expression of siglec-1 in the monocytes. In contrast, no siglec-1+ cells were observed in monocyte cultures without mesenchymal cell lines. Mesenchymal cells isolated from nasal mucosa, lungs, spleen, lymph nodes and bone marrow were successfully immortalized and these cell lines retained their stemness properties and displayed immunomodulatory effects on blood monocytes.

Authentic Research Experience and “Big Data” Analysis in the Classroom: Maize Response to Abiotic Stress

PubMed Central

Makarevitch, Irina; Frechette, Cameo; Wiatros, Natalia

2015-01-01

Integration of inquiry-based approaches into curriculum is transforming the way science is taught and studied in undergraduate classrooms. Incorporating quantitative reasoning and mathematical skills into authentic biology undergraduate research projects has been shown to benefit students in developing various skills necessary for future scientists and to attract students to science, technology, engineering, and mathematics disciplines. While large-scale data analysis became an essential part of modern biological research, students have few opportunities to engage in analysis of large biological data sets. RNA-seq analysis, a tool that allows precise measurement of the level of gene expression for all genes in a genome, revolutionized molecular biology and provides ample opportunities for engaging students in authentic research. We developed, implemented, and assessed a series of authentic research laboratory exercises incorporating a large data RNA-seq analysis into an introductory undergraduate classroom. Our laboratory series is focused on analyzing gene expression changes in response to abiotic stress in maize seedlings; however, it could be easily adapted to the analysis of any other biological system with available RNA-seq data. Objective and subjective assessment of student learning demonstrated gains in understanding important biological concepts and in skills related to the process of science. PMID:26163561

Interdisciplinary Team Science in Cell Biology.

PubMed

Horwitz, Rick

2016-11-01

The cell is complex. With its multitude of components, spatial-temporal character, and gene expression diversity, it is challenging to comprehend the cell as an integrated system and to develop models that predict its behaviors. I suggest an approach to address this issue, involving system level data analysis, large scale team science, and philanthropy. Copyright © 2016 Elsevier Ltd. All rights reserved.

VLSI Microsystem for Rapid Bioinformatic Pattern Recognition

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi; Lue, Jaw-Chyng

2009-01-01

A system comprising very-large-scale integrated (VLSI) circuits is being developed as a means of bioinformatics-oriented analysis and recognition of patterns of fluorescence generated in a microarray in an advanced, highly miniaturized, portable genetic-expression-assay instrument. Such an instrument implements an on-chip combination of polymerase chain reactions and electrochemical transduction for amplification and detection of deoxyribonucleic acid (DNA).

Pore-scale simulation of CO2-water-rock interactions

NASA Astrophysics Data System (ADS)

Deng, H.; Molins, S.; Steefel, C. I.; DePaolo, D. J.

2017-12-01

In Geologic Carbon Storage (GCS) systems, the migration of scCO2 versus CO2-acidifed brine ultimately determines the extent of mineral trapping and caprock integrity, i.e. the long-term storage efficiency and security. While continuum scale multiphase reactive transport models are valuable for large scale investigations, they typically (over-)simplify pore-scale dynamics and cannot capture local heterogeneities that may be important. Therefore, pore-scale models are needed in order to provide mechanistic understanding of how fine scale structural variations and heterogeneous processes influence the transport and geochemistry in the context of multiphase flow, and to inform parameterization of continuum scale modeling. In this study, we investigate the interplay of different processes at pore scale (e.g. diffusion, reactions, and multiphase flow) through the coupling of a well-developed multiphase flow simulator with a sophisticated reactive transport code. The objectives are to understand where brine displaced by scCO2 will reside in a rough pore/fracture, and how the CO2-water-rock interactions may affect the redistribution of different phases. In addition, the coupled code will provide a platform for model testing in pore-scale multiphase reactive transport problems.

Prospective CO 2 saline resource estimation methodology: Refinement of existing US-DOE-NETL methods based on data availability

DOE PAGES

Goodman, Angela; Sanguinito, Sean; Levine, Jonathan S.

2016-09-28

Carbon storage resource estimation in subsurface saline formations plays an important role in establishing the scale of carbon capture and storage activities for governmental policy and commercial project decision-making. Prospective CO 2 resource estimation of large regions or subregions, such as a basin, occurs at the initial screening stages of a project using only limited publicly available geophysical data, i.e. prior to project-specific site selection data generation. As the scale of investigation is narrowed and selected areas and formations are identified, prospective CO 2 resource estimation can be refined and uncertainty narrowed when site-specific geophysical data are available. Here, wemore » refine the United States Department of Energy – National Energy Technology Laboratory (US-DOE-NETL) methodology as the scale of investigation is narrowed from very large regional assessments down to selected areas and formations that may be developed for commercial storage. In addition, we present a new notation that explicitly identifies differences between data availability and data sources used for geologic parameters and efficiency factors as the scale of investigation is narrowed. This CO 2 resource estimation method is available for screening formations in a tool called CO 2-SCREEN.« less

Prospective CO 2 saline resource estimation methodology: Refinement of existing US-DOE-NETL methods based on data availability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goodman, Angela; Sanguinito, Sean; Levine, Jonathan S.

Carbon storage resource estimation in subsurface saline formations plays an important role in establishing the scale of carbon capture and storage activities for governmental policy and commercial project decision-making. Prospective CO 2 resource estimation of large regions or subregions, such as a basin, occurs at the initial screening stages of a project using only limited publicly available geophysical data, i.e. prior to project-specific site selection data generation. As the scale of investigation is narrowed and selected areas and formations are identified, prospective CO 2 resource estimation can be refined and uncertainty narrowed when site-specific geophysical data are available. Here, wemore » refine the United States Department of Energy – National Energy Technology Laboratory (US-DOE-NETL) methodology as the scale of investigation is narrowed from very large regional assessments down to selected areas and formations that may be developed for commercial storage. In addition, we present a new notation that explicitly identifies differences between data availability and data sources used for geologic parameters and efficiency factors as the scale of investigation is narrowed. This CO 2 resource estimation method is available for screening formations in a tool called CO 2-SCREEN.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jahnke, Fred C.

FuelCell Energy with support from the Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) has investigated the production of low-cost, low CO2 hydrogen using a molten carbonate fuel cell operating as an electrolyzer. We confirmed the feasibility of the technology by testing a large-scale short stack. Economic analysis was done with the assistance of the National Fuel Cell Center at the University of California, Irvine and we found the technology to be attractive, especially for distributed hydrogen. We explored the performance under various operating parameters and developed an accurate model for further analysis and development calculations. Wemore » achieved the expected results, meeting all program goals. We identified additional uses of the technology such as for CO2 capture, power storage, and power load leveling.« less

Jejunal long noncoding RNAs are associated with glycemic control via gut-brain axis after bariatric surgery in diabetic mice.

PubMed

Liang, Yongjun; Yu, Bo; Wang, Yueqian; Qiao, Zhengdong; Cao, Ting; Zhang, Peng

2018-06-01

Metabolic and bariatric surgery is effective in ameliorating type 2 diabetes, although its underlying mechanisms are largely unknown. Our previous study indicated that the distinctly expressed duodenal long noncoding RNAs (lncRNAs) induced by the duodenal-jejunal bypass (DJB) might play a role in improving glycemic control via the enteropancreatic axis. Therefore, the physiologic role of the jejunum in metabolic regulation after DJB requires investigation. To investigate the alterations in the jejunal Roux limb lncRNA expression signatures after DJB and analyze the functional pathways associated with metabolic improvement on a genome-wide scale in high-fat diet-induced diabetic mice. University medical center. Diabetic mice induced by high-fat diet were randomly assigned into 2 groups undergoing either DJB or sham surgery. The lncRNA and messenger (m)RNA expression profiles of the Roux limb segment of the jejunum in both groups were investigated using microarray. To identify the functional characteristics of the distinctly expressed lncRNAs, gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis were conducted. The lncRNA-mRNA and lncRNA-transcription factor interaction networks were constructed based on Pearson correlation analysis. Compared with the sham group, 827 dysregulated (fold change ≥2.0) jejunal lncRNAs were identified in the DJB group. Both Kyoto Encyclopedia of Genes and Genomes pathway and gene ontology enrichment analysis revealed that 601 lncRNA-co-expressed mRNAs (fold change ≥2.0) were associated with neuromodulation-related pathways or biological processes, including serotonergic, glutamatergic, and dopaminergic synapses. In addition, hormonal regulation-related pathways, especially steroid biosynthesis, were also enriched. The results were further confirmed by bioinformatic analysis of target genes or transcription factors predicted on the basis of dysregulated jejunal lncRNAs. Furthermore, the NONMMUT023781 lncRNA may simultaneously target the Adcy8 mRNA both in cis and in trans and participate in neuromodulation and hormonal regulation. Alterations of jejunal Roux limb lncRNA and mRNA expression profiles trigger both neuromodulation and endocrine-related pathways, which play a critical role in type 2 diabetes remission after metabolic and bariatric surgery via the gut-brain axis. NONMMTU023781 and Adcy8 were identified as potential targets, which warrant further research. Copyright © 2018 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

Comprehensive analysis of coding-lncRNA gene co-expression network uncovers conserved functional lncRNAs in zebrafish.

PubMed

Chen, Wen; Zhang, Xuan; Li, Jing; Huang, Shulan; Xiang, Shuanglin; Hu, Xiang; Liu, Changning

2018-05-09

Zebrafish is a full-developed model system for studying development processes and human disease. Recent studies of deep sequencing had discovered a large number of long non-coding RNAs (lncRNAs) in zebrafish. However, only few of them had been functionally characterized. Therefore, how to take advantage of the mature zebrafish system to deeply investigate the lncRNAs' function and conservation is really intriguing. We systematically collected and analyzed a series of zebrafish RNA-seq data, then combined them with resources from known database and literatures. As a result, we obtained by far the most complete dataset of zebrafish lncRNAs, containing 13,604 lncRNA genes (21,128 transcripts) in total. Based on that, a co-expression network upon zebrafish coding and lncRNA genes was constructed and analyzed, and used to predict the Gene Ontology (GO) and the KEGG annotation of lncRNA. Meanwhile, we made a conservation analysis on zebrafish lncRNA, identifying 1828 conserved zebrafish lncRNA genes (1890 transcripts) that have their putative mammalian orthologs. We also found that zebrafish lncRNAs play important roles in regulation of the development and function of nervous system; these conserved lncRNAs present a significant sequential and functional conservation, with their mammalian counterparts. By integrative data analysis and construction of coding-lncRNA gene co-expression network, we gained the most comprehensive dataset of zebrafish lncRNAs up to present, as well as their systematic annotations and comprehensive analyses on function and conservation. Our study provides a reliable zebrafish-based platform to deeply explore lncRNA function and mechanism, as well as the lncRNA commonality between zebrafish and human.

A combinatorial code for pattern formation in Drosophila oogenesis.

PubMed

Yakoby, Nir; Bristow, Christopher A; Gong, Danielle; Schafer, Xenia; Lembong, Jessica; Zartman, Jeremiah J; Halfon, Marc S; Schüpbach, Trudi; Shvartsman, Stanislav Y

2008-11-01

Two-dimensional patterning of the follicular epithelium in Drosophila oogenesis is required for the formation of three-dimensional eggshell structures. Our analysis of a large number of published gene expression patterns in the follicle cells suggests that they follow a simple combinatorial code based on six spatial building blocks and the operations of union, difference, intersection, and addition. The building blocks are related to the distribution of inductive signals, provided by the highly conserved epidermal growth factor receptor and bone morphogenetic protein signaling pathways. We demonstrate the validity of the code by testing it against a set of patterns obtained in a large-scale transcriptional profiling experiment. Using the proposed code, we distinguish 36 distinct patterns for 81 genes expressed in the follicular epithelium and characterize their joint dynamics over four stages of oogenesis. The proposed combinatorial framework allows systematic analysis of the diversity and dynamics of two-dimensional transcriptional patterns and guides future studies of gene regulation.

Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression

DOE PAGES

Ma, Ding; Yang, Laurence; Fleming, Ronan M. T.; ...

2017-01-18

Currently, Constraint-Based Reconstruction and Analysis (COBRA) is the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many orders of magnitude. Data values also have greatly varying magnitudes. Furthermore, standard double-precision solvers may return inaccurate solutions or report that no solution exists. Exact simplex solvers based on rational arithmetic require a near-optimal warm start to be practical on large problems (current ME models have 70,000 constraints and variables and will grow larger). We also developed a quadrupleprecision version of ourmore » linear and nonlinear optimizer MINOS, and a solution procedure (DQQ) involving Double and Quad MINOS that achieves reliability and efficiency for ME models and other challenging problems tested here. DQQ will enable extensive use of large linear and nonlinear models in systems biology and other applications involving multiscale data.« less

Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, Ding; Yang, Laurence; Fleming, Ronan M. T.

Currently, Constraint-Based Reconstruction and Analysis (COBRA) is the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many orders of magnitude. Data values also have greatly varying magnitudes. Furthermore, standard double-precision solvers may return inaccurate solutions or report that no solution exists. Exact simplex solvers based on rational arithmetic require a near-optimal warm start to be practical on large problems (current ME models have 70,000 constraints and variables and will grow larger). We also developed a quadrupleprecision version of ourmore » linear and nonlinear optimizer MINOS, and a solution procedure (DQQ) involving Double and Quad MINOS that achieves reliability and efficiency for ME models and other challenging problems tested here. DQQ will enable extensive use of large linear and nonlinear models in systems biology and other applications involving multiscale data.« less

Production of transgenic cattle highly expressing human serum albumin in milk by phiC31 integrase-mediated gene delivery.

PubMed

Luo, Yan; Wang, Yongsheng; Liu, Jun; Lan, Hui; Shao, Minghao; Yu, Yuan; Quan, Fusheng; Zhang, Yong

2015-10-01

Transgenic cattle expressing high levels of recombinant human serum albumin (HSA) in their milk may as an alternative source for commercial production. Our objective was to produce transgenic cattle highly expressing HSA in milk by using phiC31 integrase system and somatic cell nuclear transfer (SCNT). The mammary-specific expression plasmid pIACH(-), containing the attB recognition site for phiC31 integrase, were co-transfected with integrase expression plasmid pCMVInt into bovine fetal fibroblast cells (BFFs). PhiC31 integrase-mediated integrations in genome of BFFs were screened by nested inverse PCR. After analysis of sequence of the PCR products, 46.0% (23/50) of the both attB-genome junction sites (attL and attR) were confirmed, and four pseudo attP sites were identified. The integration rates in BF3, BF11, BF19 and BF4 sites were 4.0% (2/50), 6.0% (3/50), 16.0% (8/50) and 20.0% (10/50), respectively. BF3 is located in the bovine chromosome 3 collagen alpha-3 (VI) chain isomer 2 gene, while the other three sites are located in the non-coding region. The transgenic cell lines from BF11, BF19 and BF4 sites were used as donors for SCNT. Two calves from transgenic cells BF19 were born, one died within a few hours after birth, and another calf survived healthy. PCR and Southern blot analysis revealed integration of the transgene in the genome of cloned calves. The nested reverse PCR confirmed that the integration site in cloned calves was identical to the donor cells. The western blotting assessment indicated that recombinant HSA was expressed in the milk of transgenic cattle and the expression level was about 4-8 mg/mL. The present study demonstrated that phiC31 integrase system was an efficient and safety gene delivery tool for producing HSA transgenic cattle. The production of recombinant HSA in the milk of cattle may provide a large-scale and cost-effective resource.

On the Role of Multi-Scale Processes in CO2 Storage Security and Integrity

NASA Astrophysics Data System (ADS)

Pruess, K.; Kneafsey, T. J.

2008-12-01

Consideration of multiple scales in subsurface processes is usually referred to the spatial domain, where we may attempt to relate process descriptions and parameters from pore and bench (Darcy) scale to much larger field and regional scales. However, multiple scales occur also in the time domain, and processes extending over a broad range of time scales may be very relevant to CO2 storage and containment. In some cases, such as in the convective instability induced by CO2 dissolution in saline waters, space and time scales are coupled in the sense that perturbations induced by CO2 injection will grow concurrently over many orders of magnitude in both space and time. In other cases, CO2 injection may induce processes that occur on short time scales, yet may affect large regions. Possible examples include seismicity that may be triggered by CO2 injection, or hypothetical release events such as "pneumatic eruptions" that may discharge substantial amounts of CO2 over a short time period. This paper will present recent advances in our experimental and modeling studies of multi-scale processes. Specific examples that will be discussed include (1) the process of CO2 dissolution-diffusion-convection (DDC), that can greatly accelerate the rate at which free-phase CO2 is stored as aqueous solute; (2) self- enhancing and self-limiting processes during CO2 leakage through faults, fractures, or improperly abandoned wells; and (3) porosity and permeability reduction from salt precipitation near CO2 injection wells, and mitigation of corresponding injectivity loss. This work was supported by the Office of Basic Energy Sciences and by the Zero Emission Research and Technology project (ZERT) under Contract No. DE-AC02-05CH11231 with the U.S. Department of Energy.

Coalescence computations for large samples drawn from populations of time-varying sizes

PubMed Central

Polanski, Andrzej; Szczesna, Agnieszka; Garbulowski, Mateusz; Kimmel, Marek

2017-01-01

We present new results concerning probability distributions of times in the coalescence tree and expected allele frequencies for coalescent with large sample size. The obtained results are based on computational methodologies, which involve combining coalescence time scale changes with techniques of integral transformations and using analytical formulae for infinite products. We show applications of the proposed methodologies for computing probability distributions of times in the coalescence tree and their limits, for evaluation of accuracy of approximate expressions for times in the coalescence tree and expected allele frequencies, and for analysis of large human mitochondrial DNA dataset. PMID:28170404

Effect of the temperature and the CO2 concentration on the behaviour of the citric acid as a scale inhibitor of CaCO3

NASA Astrophysics Data System (ADS)

Blanco, K.; Aponte, H.; Vera, E.

2017-12-01

For all Industrial sector is important to extend the useful life of the materials that they use in their process, the scales of CaCO3 are common in situation where fluids are handled with high concentration of ions and besides this temperatures and CO2 concentration dissolved, that scale generates large annual losses because there is a reduction in the process efficiency or corrosion damage under deposit, among other. In order to find new alternatives to this problem, the citric acid was evaluated as scale of calcium carbonate inhibition in critical condition of temperature and concentration of CO2 dissolved. Once the results are obtained it was carried out the statistical evaluation in order to generate an equation that allow to see that behaviour, giving as result, a good efficiency of inhibition to the conditions evaluated the scales of products obtained were characterized through scanning electron microscopy.

Why does high pressure destroy co-non-solvency of PNIPAm in aqueous methanol?

PubMed

de Oliveira, Tiago E; Netz, Paulo A; Mukherji, Debashish; Kremer, Kurt

2015-11-28

It is well known that poly(N-isopropylacrylamide) (PNIPAm) exhibits an interesting, yet puzzling, phenomenon of co-non-solvency. Co-non-solvency occurs when two competing good solvents for PNIPAm, such as water and alcohol, are mixed together. As a result, the same PNIPAm collapses within intermediate mixing ratios. This complex conformational transition is driven by preferential binding of methanol with PNIPAm. Interestingly, co-non-solvency can be destroyed when applying high hydrostatic pressures. In this work, using a large scale molecular dynamics simulation employing high pressures, we propose a microscopic picture behind the suppression of the co-non-solvency phenomenon. Based on thermodynamic and structural analysis, our results suggest that the preferential binding of methanol with PNIPAm gets partially lost at high pressures, making the background fluid reasonably homogeneous for the polymer. This is consistent with the hypothesis that the co-non-solvency phenomenon is driven by preferential binding and is not based on depletion effects.

A Synthesized Model-Observation Approach to Constraining Gross Urban CO2 Fluxes Using 14CO2 and carbonyl sulfide

NASA Astrophysics Data System (ADS)

LaFranchi, B. W.; Campbell, J. E.; Cameron-Smith, P. J.; Bambha, R.; Michelsen, H. A.

2013-12-01

Urbanized regions are responsible for a disproportionately large percentage (30-40%) of global anthropogenic greenhouse gas (GHG) emissions, despite covering only 2% of the Earth's surface area [Satterthwaite, 2008]. As a result, policies enacted at the local level in these urban areas can, in aggregate, have a large global impact, both positive and negative. In order to address the scientific questions that are required to drive these policy decisions, methods are needed that resolve gross CO2 flux components from the net flux. Recent work suggests that the critical knowledge gaps in CO2 surface fluxes could be addressed through the combined analysis of atmospheric carbonyl sulfide (COS) and radiocarbon in atmospheric CO2 (14CO2) [e.g. Campbell et al., 2008; Graven et al., 2009]. The 14CO2 approach relies on mass balance assumptions about atmospheric CO2 and the large differences in 14CO2 abundance between fossil and natural sources of CO2 [Levin et al., 2003]. COS, meanwhile, is a potentially transformative tracer of photosynthesis because its variability in the atmosphere has been found to be influenced primarily by vegetative uptake, scaling linearly will gross primary production (GPP) [Kettle et al., 20027]. Taken together, these two observations provide constraints on two of the three main components of the CO2 budget at the urban scale: photosynthesis and fossil fuel emissions. The third component, respiration, can then be determined by difference if the net flux is known. Here we present a general overview of our synthesized model-observation approach for improving surface flux estimates of CO2 for the upwind fetch of a ~30m tower located in Livermore, CA, USA, a suburb (pop. ~80,000) at the eastern edge of the San Francisco Bay Area. Additionally, we will present initial results from a one week observational intensive, which includes continuous CO2, CH4, CO, SO2, NOx, and O3 observations in addition to measurements of 14CO2 and COS from air samples collected every ~1-3 hours during this time period. References Campbell, J. E., et. al., Science, 322, 1085-1088, 2008. Graven, H. D., et al., Tellus B, 61, 536-546, 2009. Kettle, A. J., et al., J. Geophys. Res.-Atmos., 107, 2002. Levin, I., et al., Geophys. Res. Lett., 30, 2003. Satterthwaite, D., Environment and Urbanization, 20, 539-549, 2008.

Efficient production of human acidic fibroblast growth factor in pea (Pisum sativum L.) plants by agroinfection of germinated seeds

PubMed Central

2011-01-01

Background For efficient and large scale production of recombinant proteins in plants transient expression by agroinfection has a number of advantages over stable transformation. Simple manipulation, rapid analysis and high expression efficiency are possible. In pea, Pisum sativum, a Virus Induced Gene Silencing System using the pea early browning virus has been converted into an efficient agroinfection system by converting the two RNA genomes of the virus into binary expression vectors for Agrobacterium transformation. Results By vacuum infiltration (0.08 Mpa, 1 min) of germinating pea seeds with 2-3 cm roots with Agrobacteria carrying the binary vectors, expression of the gene for Green Fluorescent Protein as marker and the gene for the human acidic fibroblast growth factor (aFGF) was obtained in 80% of the infiltrated developing seedlings. Maximal production of the recombinant proteins was achieved 12-15 days after infiltration. Conclusions Compared to the leaf injection method vacuum infiltration of germinated seeds is highly efficient allowing large scale production of plants transiently expressing recombinant proteins. The production cycle of plants for harvesting the recombinant protein was shortened from 30 days for leaf injection to 15 days by applying vacuum infiltration. The synthesized aFGF was purified by heparin-affinity chromatography and its mitogenic activity on NIH 3T3 cells confirmed to be similar to a commercial product. PMID:21548923

Catalytic reduction of CO 2 by H 2 for synthesis of CO, methanol and hydrocarbons: challenges and opportunities

DOE PAGES

Porosoff, Marc D.; Yan, Binhang; Chen, Jingguang G.

2015-10-22

Ocean acidification and climate change are expected to be two of the most difficult scientific challenges of the 21st century. Converting CO 2 into valuable chemicals and fuels is one of the most practical routes for reducing CO 2 emissions while fossil fuels continue to dominate the energy sector. Reducing CO 2 by H 2 using heterogeneous catalysis has been studied extensively, but there are still significant challenges in developing active, selective and stable catalysts suitable for large-scale commercialization. We study the catalytic reduction of CO 2 by H 2 can lead to the formation of three types of products:more » CO through the reverse water–gas shift (RWGS) reaction, methanol via selective hydrogenation, and hydrocarbons through combination of CO 2 reduction with Fischer–Tropsch (FT) reactions. In addition, investigations into these routes reveal that the stabilization of key reaction intermediates is critically important for controlling catalytic selectivity. Furthermore, viability of these processes is contingent on the development of a CO 2-free H 2 source on a large enough scale to significantly reduce CO 2 emissions.« less

Multi-scale modeling of Arabidopsis thaliana response to different CO2 conditions: From gene expression to metabolic flux.

PubMed

Liu, Lin; Shen, Fangzhou; Xin, Changpeng; Wang, Zhuo

2016-01-01

Multi-scale investigation from gene transcript level to metabolic activity is important to uncover plant response to environment perturbation. Here we integrated a genome-scale constraint-based metabolic model with transcriptome data to explore Arabidopsis thaliana response to both elevated and low CO2 conditions. The four condition-specific models from low to high CO2 concentrations show differences in active reaction sets, enriched pathways for increased/decreased fluxes, and putative post-transcriptional regulation, which indicates that condition-specific models are necessary to reflect physiological metabolic states. The simulated CO2 fixation flux at different CO2 concentrations is consistent with the measured Assimilation-CO2intercellular curve. Interestingly, we found that reactions in primary metabolism are affected most significantly by CO2 perturbation, whereas secondary metabolic reactions are not influenced a lot. The changes predicted in key pathways are consistent with existing knowledge. Another interesting point is that Arabidopsis is required to make stronger adjustment on metabolism to adapt to the more severe low CO2 stress than elevated CO2 . The challenges of identifying post-transcriptional regulation could also be addressed by the integrative model. In conclusion, this innovative application of multi-scale modeling in plants demonstrates potential to uncover the mechanisms of metabolic response to different conditions. © 2015 Institute of Botany, Chinese Academy of Sciences.

Reverse engineering and analysis of large genome-scale gene networks

PubMed Central

Aluru, Maneesha; Zola, Jaroslaw; Nettleton, Dan; Aluru, Srinivas

2013-01-01

Reverse engineering the whole-genome networks of complex multicellular organisms continues to remain a challenge. While simpler models easily scale to large number of genes and gene expression datasets, more accurate models are compute intensive limiting their scale of applicability. To enable fast and accurate reconstruction of large networks, we developed Tool for Inferring Network of Genes (TINGe), a parallel mutual information (MI)-based program. The novel features of our approach include: (i) B-spline-based formulation for linear-time computation of MI, (ii) a novel algorithm for direct permutation testing and (iii) development of parallel algorithms to reduce run-time and facilitate construction of large networks. We assess the quality of our method by comparison with ARACNe (Algorithm for the Reconstruction of Accurate Cellular Networks) and GeneNet and demonstrate its unique capability by reverse engineering the whole-genome network of Arabidopsis thaliana from 3137 Affymetrix ATH1 GeneChips in just 9 min on a 1024-core cluster. We further report on the development of a new software Gene Network Analyzer (GeNA) for extracting context-specific subnetworks from a given set of seed genes. Using TINGe and GeNA, we performed analysis of 241 Arabidopsis AraCyc 8.0 pathways, and the results are made available through the web. PMID:23042249

Eurasian continental background and regionally polluted levels of ozone and CO observed in northeast Asia

NASA Astrophysics Data System (ADS)

Pochanart, Pakpong; Kato, Shungo; Katsuno, Takao; Akimoto, Hajime

The roles of Eurasian/Siberian continental air masses transport and the impact of large-scale East Asian anthropogenic emissions on tropospheric ozone and carbon monoxide levels in northeast Asia were investigated. Seasonal behaviors of O 3 and CO mixing ratios in background continental (BC) air masses and regionally polluted continental (RPC) air masses were identified using trajectory analyses of Eurasian continental air masses and multi-year O 3 and CO data observed at Happo, a mountain site in Japan. RPC air masses show significantly higher O 3 and CO mixing ratios (annual average of 53.9±6.0 and 200±41 ppb, respectively) than BC air masses (44.4±3.6 and 167±17 ppb, respectively). Large scale anthropogenic emissions in East Asia are suggested to contribute about 10 ppb of photochemical O 3 and 32 ppb of CO at Happo. A comparative study of O 3 and CO observed at other sites, i.e., Oki Islands and Mondy in northeast Asia, showed similarities suggesting that O 3 mixing ratios in BC air masses at Happo could be representative for remote northeast Asia. However, CO mixing ratios in BC air masses at Happo are higher than the background level in Siberia. The overestimate is probably related to an increase in the CO baseline gradient between Siberia and the East Asia Pacific rim, and perturbations by sub-grid scale pollution transport and regional-scale boreal forest fires in Siberia when the background continental air masses are transported to Japan.

Carbon Cycle Model Linkage Project (CCMLP): Evaluating Biogeochemical Process Models with Atmospheric Measurements and Field Experiments

NASA Astrophysics Data System (ADS)

Heimann, M.; Prentice, I. C.; Foley, J.; Hickler, T.; Kicklighter, D. W.; McGuire, A. D.; Melillo, J. M.; Ramankutty, N.; Sitch, S.

2001-12-01

Models of biophysical and biogeochemical proceses are being used -either offline or in coupled climate-carbon cycle (C4) models-to assess climate- and CO2-induced feedbacks on atmospheric CO2. Observations of atmospheric CO2 concentration, and supplementary tracers including O2 concentrations and isotopes, offer unique opportunities to evaluate the large-scale behaviour of models. Global patterns, temporal trends, and interannual variability of the atmospheric CO2 concentration and its seasonal cycle provide crucial benchmarks for simulations of regionally-integrated net ecosystem exchange; flux measurements by eddy correlation allow a far more demanding model test at the ecosystem scale than conventional indicators, such as measurements of annual net primary production; and large-scale manipulations, such as the Duke Forest Free Air Carbon Enrichment (FACE) experiment, give a standard to evaluate modelled phenomena such as ecosystem-level CO2 fertilization. Model runs including historical changes of CO2, climate and land use allow comparison with regional-scale monthly CO2 balances as inferred from atmospheric measurements. Such comparisons are providing grounds for some confidence in current models, while pointing to processes that may still be inadequately treated. Current plans focus on (1) continued benchmarking of land process models against flux measurements across ecosystems and experimental findings on the ecosystem-level effects of enhanced CO2, reactive N inputs and temperature; (2) improved representation of land use, forest management and crop metabolism in models; and (3) a strategy for the evaluation of C4 models in a historical observational context.

Uncovering a facile large-scale synthesis of LiNi1/3Co1/3Mn1/3O2 nanoflowers for high power lithium-ion batteries

NASA Astrophysics Data System (ADS)

Hua, Wei-Bo; Guo, Xiao-Dong; Zheng, Zhuo; Wang, Yan-Jie; Zhong, Ben-He; Fang, Baizeng; Wang, Jia-Zhao; Chou, Shu-Lei; Liu, Heng

2015-02-01

Developing advanced electrode materials that deliver high energy at ultra-fast charge and discharge rates are very crucial to meet an increasing large-scale market demand for high power lithium ion batteries (LIBs). A three-dimensional (3D) nanoflower structure is successfully developed in the large-scale synthesis of LiNi1/3Co1/3Mn1/3O2 material for the first time. The fast co-precipitation is the key technique to prepare the nanoflower structure in our method. After heat treatment, the obtained LiNi1/3Co1/3Mn1/3O2 nanoflowers (NL333) pronouncedly present a pristine flower-like nano-architecture and provide fast pathways for the transport of Li-ions and electrons. As a cathode material in a LIB, the prepared NL333 electrode demonstrates an outstanding high-rate capability. Particularly, in a narrow voltage range of 2.7-4.3 V, the discharge capacity at an ultra-fast charge-discharge rate (20C) is up to 126 mAh g-1, which reaches 78% of that at 0.2C, and is much higher than that (i.e., 44.17%) of the traditional bulk LiNi1/3Co1/3Mn1/3O2.

Design of a large-scale femtoliter droplet array for single-cell analysis of drug-tolerant and drug-resistant bacteria.

PubMed

Iino, Ryota; Matsumoto, Yoshimi; Nishino, Kunihiko; Yamaguchi, Akihito; Noji, Hiroyuki

2013-01-01

Single-cell analysis is a powerful method to assess the heterogeneity among individual cells, enabling the identification of very rare cells with properties that differ from those of the majority. In this Methods Article, we describe the use of a large-scale femtoliter droplet array to enclose, isolate, and analyze individual bacterial cells. As a first example, we describe the single-cell detection of drug-tolerant persisters of Pseudomonas aeruginosa treated with the antibiotic carbenicillin. As a second example, this method was applied to the single-cell evaluation of drug efflux activity, which causes acquired antibiotic resistance of bacteria. The activity of the MexAB-OprM multidrug efflux pump system from Pseudomonas aeruginosa was expressed in Escherichia coli and the effect of an inhibitor D13-9001 were assessed at the single cell level.

Evolution of Synonymous Codon Usage in Neurospora tetrasperma and Neurospora discreta

PubMed Central

Whittle, C. A.; Sun, Y.; Johannesson, H.

2011-01-01

Neurospora comprises a primary model system for the study of fungal genetics and biology. In spite of this, little is known about genome evolution in Neurospora. For example, the evolution of synonymous codon usage is largely unknown in this genus. In the present investigation, we conducted a comprehensive analysis of synonymous codon usage and its relationship to gene expression and gene length (GL) in Neurospora tetrasperma and Neurospora discreta. For our analysis, we examined codon usage among 2,079 genes per organism and assessed gene expression using large-scale expressed sequenced tag (EST) data sets (279,323 and 453,559 ESTs for N. tetrasperma and N. discreta, respectively). Data on relative synonymous codon usage revealed 24 codons (and two putative codons) that are more frequently used in genes with high than with low expression and thus were defined as optimal codons. Although codon-usage bias was highly correlated with gene expression, it was independent of selectively neutral base composition (introns); thus demonstrating that translational selection drives synonymous codon usage in these genomes. We also report that GL (coding sequences [CDS]) was inversely associated with optimal codon usage at each gene expression level, with highly expressed short genes having the greatest frequency of optimal codons. Optimal codon frequency was moderately higher in N. tetrasperma than in N. discreta, which might be due to variation in selective pressures and/or mating systems. PMID:21402862

Computational design of RNA parts, devices, and transcripts with kinetic folding algorithms implemented on multiprocessor clusters.

PubMed

Thimmaiah, Tim; Voje, William E; Carothers, James M

2015-01-01

With progress toward inexpensive, large-scale DNA assembly, the demand for simulation tools that allow the rapid construction of synthetic biological devices with predictable behaviors continues to increase. By combining engineered transcript components, such as ribosome binding sites, transcriptional terminators, ligand-binding aptamers, catalytic ribozymes, and aptamer-controlled ribozymes (aptazymes), gene expression in bacteria can be fine-tuned, with many corollaries and applications in yeast and mammalian cells. The successful design of genetic constructs that implement these kinds of RNA-based control mechanisms requires modeling and analyzing kinetically determined co-transcriptional folding pathways. Transcript design methods using stochastic kinetic folding simulations to search spacer sequence libraries for motifs enabling the assembly of RNA component parts into static ribozyme- and dynamic aptazyme-regulated expression devices with quantitatively predictable functions (rREDs and aREDs, respectively) have been described (Carothers et al., Science 334:1716-1719, 2011). Here, we provide a detailed practical procedure for computational transcript design by illustrating a high throughput, multiprocessor approach for evaluating spacer sequences and generating functional rREDs. This chapter is written as a tutorial, complete with pseudo-code and step-by-step instructions for setting up a computational cluster with an Amazon, Inc. web server and performing the large numbers of kinefold-based stochastic kinetic co-transcriptional folding simulations needed to design functional rREDs and aREDs. The method described here should be broadly applicable for designing and analyzing a variety of synthetic RNA parts, devices and transcripts.

High-throughput method for the quantitation of metabolites and co-factors from homocysteine-methionine cycle for nutritional status assessment.

PubMed

Da Silva, Laeticia; Collino, Sebastiano; Cominetti, Ornella; Martin, Francois-Pierre; Montoliu, Ivan; Moreno, Sergio Oller; Corthesy, John; Kaput, Jim; Kussmann, Martin; Monteiro, Jacqueline Pontes; Guiraud, Seu Ping

2016-09-01

There is increasing interest in the profiling and quantitation of methionine pathway metabolites for health management research. Currently, several analytical approaches are required to cover metabolites and co-factors. We report the development and the validation of a method for the simultaneous detection and quantitation of 13 metabolites in red blood cells. The method, validated in a cohort of healthy human volunteers, shows a high level of accuracy and reproducibility. This high-throughput protocol provides a robust coverage of central metabolites and co-factors in one single analysis and in a high-throughput fashion. In large-scale clinical settings, the use of such an approach will significantly advance the field of nutritional research in health and disease.

Biomass logistics analysis for large scale biofuel production: case study of loblolly pine and switchgrass.

PubMed

Lu, Xiaoming; Withers, Mitch R; Seifkar, Navid; Field, Randall P; Barrett, Steven R H; Herzog, Howard J

2015-05-01

The objective of this study was to assess the costs, energy consumption and greenhouse gas (GHG) emissions throughout the biomass supply chain for large scale biofuel production. Two types of energy crop were considered, switchgrass and loblolly pine, as representative of herbaceous and woody biomass. A biomass logistics model has been developed to estimate the feedstock supply system from biomass production through transportation. Biomass in the form of woodchip, bale and pellet was investigated with road, railway and waterway transportation options. Our analysis indicated that the farm or forest gate cost is lowest for loblolly pine whole tree woodchip at $39.7/dry tonne and highest for switchgrass round bale at $72.3/dry tonne. Switchgrass farm gate GHG emissions is approximately 146kgCO2e/dry tonne, about 4 times higher than loblolly pine. The optimum biomass transportation mode and delivered form are determined by the tradeoff between fixed and variable costs for feedstock shipment. Copyright © 2015 Elsevier Ltd. All rights reserved.

3-Dimensional Root Cause Diagnosis via Co-analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, Ziming; Lan, Zhiling; Yu, Li

2012-01-01

With the growth of system size and complexity, reliability has become a major concern for large-scale systems. Upon the occurrence of failure, system administrators typically trace the events in Reliability, Availability, and Serviceability (RAS) logs for root cause diagnosis. However, RAS log only contains limited diagnosis information. Moreover, the manual processing is time-consuming, error-prone, and not scalable. To address the problem, in this paper we present an automated root cause diagnosis mechanism for large-scale HPC systems. Our mechanism examines multiple logs to provide a 3-D fine-grained root cause analysis. Here, 3-D means that our analysis will pinpoint the failure layer,more » the time, and the location of the event that causes the problem. We evaluate our mechanism by means of real logs collected from a production IBM Blue Gene/P system at Oak Ridge National Laboratory. It successfully identifies failure layer information for 219 failures during 23-month period. Furthermore, it effectively identifies the triggering events with time and location information, even when the triggering events occur hundreds of hours before the resulting failures.« less

A sensitivity analysis on seismic tomography data with respect to CO2 saturation of a CO2 geological sequestration field

NASA Astrophysics Data System (ADS)

Park, Chanho; Nguyen, Phung K. T.; Nam, Myung Jin; Kim, Jongwook

2013-04-01

Monitoring CO2 migration and storage in geological formations is important not only for the stability of geological sequestration of CO2 but also for efficient management of CO2 injection. Especially, geophysical methods can make in situ observation of CO2 to assess the potential leakage of CO2 and to improve reservoir description as well to monitor development of geologic discontinuity (i.e., fault, crack, joint, etc.). Geophysical monitoring can be based on wireline logging or surface surveys for well-scale monitoring (high resolution and nallow area of investigation) or basin-scale monitoring (low resolution and wide area of investigation). In the meantime, crosswell tomography can make reservoir-scale monitoring to bridge the resolution gap between well logs and surface measurements. This study focuses on reservoir-scale monitoring based on crosswell seismic tomography aiming describe details of reservoir structure and monitoring migration of reservoir fluid (water and CO2). For the monitoring, we first make a sensitivity analysis on crosswell seismic tomography data with respect to CO2 saturation. For the sensitivity analysis, Rock Physics Models (RPMs) are constructed by calculating the values of density and P and S-wave velocities of a virtual CO2 injection reservoir. Since the seismic velocity of the reservoir accordingly changes as CO2 saturation changes when the CO2 saturation is less than about 20%, while when the CO2 saturation is larger than 20%, the seismic velocity is insensitive to the change, sensitivity analysis is mainly made when CO2 saturation is less than 20%. For precise simulation of seismic tomography responses for constructed RPMs, we developed a time-domain 2D elastic modeling based on finite difference method with a staggered grid employing a boundary condition of a convolutional perfectly matched layer. We further make comparison between sensitivities of seismic tomography and surface measurements for RPMs to analysis resolution difference between them. Moreover, assuming a similar reservoir situation to the CO2 storage site in Nagaoka, Japan, we generate time-lapse tomographic data sets for the corresponding CO2 injection process, and make a preliminary interpretation of the data sets.

Comparative transcriptome analysis of the CO2 sensing pathway via differential expression of carbonic anhydrase in Cryptococcus neoformans.

PubMed

Kim, Min Su; Ko, Young-Joon; Maeng, Shinae; Floyd, Anna; Heitman, Joseph; Bahn, Yong-Sun

2010-08-01

Carbon dioxide (CO(2)) sensing and metabolism via carbonic anhydrases (CAs) play pivotal roles in survival and proliferation of pathogenic fungi infecting human hosts from natural environments due to the drastic difference in CO(2) levels. In Cryptococcus neoformans, which causes fatal fungal meningoencephalitis, the Can2 CA plays essential roles during both cellular growth in air and sexual differentiation of the pathogen. However the signaling networks downstream of Can2 are largely unknown. To address this question, the present study employed comparative transcriptome DNA microarray analysis of a C. neoformans strain in which CAN2 expression is artificially controlled by the CTR4 (copper transporter) promoter. The P(CTR4)CAN2 strain showed growth defects in a CO(2)-dependent manner when CAN2 was repressed but resumed normal growth when CAN2 was overexpressed. The Can2-dependent genes identified by the transcriptome analysis include FAS1 (fatty acid synthase 1) and GPB1 (G-protein beta subunit), supporting the roles of Can2 in fatty acid biosynthesis and sexual differentiation. Cas3, a capsular structure designer protein, was also discovered to be Can2-dependent and yet was not involved in CO(2)-mediated capsule induction. Most notably, a majority of Can2-dependent genes were environmental stress-regulated (ESR) genes. Supporting this, the CAN2 overexpression strain was hypersensitive to oxidative and genotoxic stress as well as antifungal drugs, such as polyene and azole drugs, potentially due to defective membrane integrity. Finally, an oxidative stress-responsive Atf1 transcription factor was also found to be Can2-dependent. Atf1 not only plays an important role in diverse stress responses, including thermotolerance and antifungal drug resistance, but also represses melanin and capsule production in C. neoformans. In conclusion, this study provides insights into the comprehensive signaling networks orchestrated by CA/CO(2)-sensing pathways in pathogenic fungi.

Gene co-expression network analysis in Rhodobacter capsulatus and application to comparative expression analysis of Rhodobacter sphaeroides

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pena-Castillo, Lourdes; Mercer, Ryan; Gurinovich, Anastasia

2014-08-28

The genus Rhodobacter contains purple nonsulfur bacteria found mostly in freshwater environments. Representative strains of two Rhodobacter species, R. capsulatus and R. sphaeroides, have had their genomes fully sequenced and both have been the subject of transcriptional profiling studies. Gene co-expression networks can be used to identify modules of genes with similar expression profiles. Functional analysis of gene modules can then associate co-expressed genes with biological pathways, and network statistics can determine the degree of module preservation in related networks. In this paper, we constructed an R. capsulatus gene co-expression network, performed functional analysis of identified gene modules, and investigatedmore » preservation of these modules in R. capsulatus proteomics data and in R. sphaeroides transcriptomics data. Results: The analysis identified 40 gene co-expression modules in R. capsulatus. Investigation of the module gene contents and expression profiles revealed patterns that were validated based on previous studies supporting the biological relevance of these modules. We identified two R. capsulatus gene modules preserved in the protein abundance data. We also identified several gene modules preserved between both Rhodobacter species, which indicate that these cellular processes are conserved between the species and are candidates for functional information transfer between species. Many gene modules were non-preserved, providing insight into processes that differentiate the two species. In addition, using Local Network Similarity (LNS), a recently proposed metric for expression divergence, we assessed the expression conservation of between-species pairs of orthologs, and within-species gene-protein expression profiles. Conclusions: Our analyses provide new sources of information for functional annotation in R. capsulatus because uncharacterized genes in modules are now connected with groups of genes that constitute a joint functional annotation. We identified R. capsulatus modules enriched with genes for ribosomal proteins, porphyrin and bacteriochlorophyll anabolism, and biosynthesis of secondary metabolites to be preserved in R. sphaeroides whereas modules related to RcGTA production and signalling showed lack of preservation in R. sphaeroides. In addition, we demonstrated that network statistics may also be applied within-species to identify congruence between mRNA expression and protein abundance data for which simple correlation measurements have previously had mixed results.« less

The MIND PALACE: A Multi-Spectral Imaging and Spectroscopy Database for Planetary Science

NASA Astrophysics Data System (ADS)

Eshelman, E.; Doloboff, I.; Hara, E. K.; Uckert, K.; Sapers, H. M.; Abbey, W.; Beegle, L. W.; Bhartia, R.

2017-12-01

The Multi-Instrument Database (MIND) is the web-based home to a well-characterized set of analytical data collected by a suite of deep-UV fluorescence/Raman instruments built at the Jet Propulsion Laboratory (JPL). Samples derive from a growing body of planetary surface analogs, mineral and microbial standards, meteorites, spacecraft materials, and other astrobiologically relevant materials. In addition to deep-UV spectroscopy, datasets stored in MIND are obtained from a variety of analytical techniques obtained over multiple spatial and spectral scales including electron microscopy, optical microscopy, infrared spectroscopy, X-ray fluorescence, and direct fluorescence imaging. Multivariate statistical analysis techniques, primarily Principal Component Analysis (PCA), are used to guide interpretation of these large multi-analytical spectral datasets. Spatial co-referencing of integrated spectral/visual maps is performed using QGIS (geographic information system software). Georeferencing techniques transform individual instrument data maps into a layered co-registered data cube for analysis across spectral and spatial scales. The body of data in MIND is intended to serve as a permanent, reliable, and expanding database of deep-UV spectroscopy datasets generated by this unique suite of JPL-based instruments on samples of broad planetary science interest.

CPTAC researchers report first large-scale integrated proteomic and genomic analysis of a human cancer | Office of Cancer Clinical Proteomics Research

Cancer.gov

Investigators from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) who comprehensively analyzed 95 human colorectal tumor samples, have determined how gene alterations identified in previous analyses of the same samples are expressed at the protein level. The integration of proteomic and genomic data, or proteogenomics, provides a more comprehensive view of the biological features that drive cancer than genomic analysis alone and may help identify the most important targets for cancer detection and intervention.

Soil organic matter composition from correlated thermal analysis and nuclear magnetic resonance data in Australian national inventory of agricultural soils

NASA Astrophysics Data System (ADS)

Moore, T. S.; Sanderman, J.; Baldock, J.; Plante, A. F.

2016-12-01

National-scale inventories typically include soil organic carbon (SOC) content, but not chemical composition or biogeochemical stability. Australia's Soil Carbon Research Programme (SCaRP) represents a national inventory of SOC content and composition in agricultural systems. The program used physical fractionation followed by 13C nuclear magnetic resonance (NMR) spectroscopy. While these techniques are highly effective, they are typically too expensive and time consuming for use in large-scale SOC monitoring. We seek to understand if analytical thermal analysis is a viable alternative. Coupled differential scanning calorimetry (DSC) and evolved gas analysis (CO2- and H2O-EGA) yields valuable data on SOC composition and stability via ramped combustion. The technique requires little training to use, and does not require fractionation or other sample pre-treatment. We analyzed 300 agricultural samples collected by SCaRP, divided into four fractions: whole soil, coarse particulates (POM), untreated mineral associated (HUM), and hydrofluoric acid (HF)-treated HUM. All samples were analyzed by DSC-EGA, but only the POM and HF-HUM fractions were analyzed by NMR. Multivariate statistical analyses were used to explore natural clustering in SOC composition and stability based on DSC-EGA data. A partial least-squares regression (PLSR) model was used to explore correlations among the NMR and DSC-EGA data. Correlations demonstrated regions of combustion attributable to specific functional groups, which may relate to SOC stability. We are increasingly challenged with developing an efficient technique to assess SOC composition and stability at large spatial and temporal scales. Correlations between NMR and DSC-EGA may demonstrate the viability of using thermal analysis in lieu of more demanding methods in future large-scale surveys, and may provide data that goes beyond chemical composition to better approach quantification of biogeochemical stability.

Recent variations in Amazon carbon balance driven by climate anomalies

NASA Astrophysics Data System (ADS)

Miller, J. B.

2015-12-01

Understanding tropical rainforest response to heat and drought is critical for quantifying the effects of climate change on tropical ecosystems, including global climate-carbon feedbacks. Of particular importance for the global carbon budget is net ecosystem exchange of CO2 with the atmosphere (NEE), a metric that represents the total integrated signal of carbon fluxes into and out of ecosystems. Sub-annual and sub-basin NEE estimates have previously been derived from process-based biosphere models, despite often disagreeing with plot-scale observations. Our analysis of airborne CO2 and CO measurements reveals monthly, sub-Basin scale (~106 km2) NEE variations in a framework that is largely independent of bottom-up estimates. As such, our approach provides new insights about tropical forest response to climate. We find acute sensitivity of NEE to daily and monthly climate extremes. In particular, increased central-Amazon NEE was associated with wet-season heat and dry-season drought in 2010. We analyze satellite proxies for photosynthesis and find that suppression of photosynthesis may have contributed to increased carbon loss in the 2010 drought, consistent with recent analysis of plot-scale measurements. In the eastern Amazon, pulses of increased NEE (i.e. net respiration) persisted through 2011, suggesting legacy effects of the drought that occurred in 2010. Regional differences in post-drought recovery in 2011 and 2012 appear related to long-term water availability. These results provide novel evidence of the vulnerability of Amazon carbon stocks to short-term temperature and moisture extremes.

Bioremediation of trace cobalt from simulated spent decontamination solutions of nuclear power reactors using E. coli expressing NiCoT genes.

PubMed

Raghu, G; Balaji, V; Venkateswaran, G; Rodrigue, A; Maruthi Mohan, P

2008-12-01

Removal of radioactive cobalt at trace levels (approximately nM) in the presence of large excess (10(6)-fold) of corrosion product ions of complexed Fe, Cr, and Ni in spent chemical decontamination formulations (simulated effluent) of nuclear reactors is currently done by using synthetic organic ion exchangers. A large volume of solid waste is generated due to the nonspecific nature of ion sorption. Our earlier work using various fungi and bacteria, with the aim of nuclear waste volume reduction, realized up to 30% of Co removal with specific capacities calculated up to 1 microg/g in 6-24 h. In the present study using engineered Escherichia coli expressing NiCoT genes from Rhodopseudomonas palustris CGA009 (RP) and Novosphingobium aromaticivorans F-199 (NA), we report a significant increase in the specific capacity for Co removal (12 microg/g) in 1-h exposure to simulated effluent. About 85% of Co removal was achieved in a two-cycle treatment with the cloned bacteria. Expression of NiCoT genes in the E. coli knockout mutant of NiCoT efflux gene (rcnA) was more efficient as compared to expression in wild-type E. coli MC4100, JM109 and BL21 (DE3) hosts. The viability of the E. coli strains in the formulation as well as at different doses of gamma rays exposure and the effect of gamma dose on their cobalt removal capacity are determined. The potential application scheme of the above process of bioremediation of cobalt from nuclear power reactor chemical decontamination effluents is discussed.

FunRich proteomics software analysis, let the fun begin!

PubMed

Benito-Martin, Alberto; Peinado, Héctor

2015-08-01

Protein MS analysis is the preferred method for unbiased protein identification. It is normally applied to a large number of both small-scale and high-throughput studies. However, user-friendly computational tools for protein analysis are still needed. In this issue, Mathivanan and colleagues (Proteomics 2015, 15, 2597-2601) report the development of FunRich software, an open-access software that facilitates the analysis of proteomics data, providing tools for functional enrichment and interaction network analysis of genes and proteins. FunRich is a reinterpretation of proteomic software, a standalone tool combining ease of use with customizable databases, free access, and graphical representations. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Bioenergy production from perennial energy crops: a consequential LCA of 12 bioenergy scenarios including land use changes.

PubMed

Tonini, Davide; Hamelin, Lorie; Wenzel, Henrik; Astrup, Thomas

2012-12-18

In the endeavor of optimizing the sustainability of bioenergy production in Denmark, this consequential life cycle assessment (LCA) evaluated the environmental impacts associated with the production of heat and electricity from one hectare of Danish arable land cultivated with three perennial crops: ryegrass (Lolium perenne), willow (Salix viminalis) and Miscanthus giganteus. For each, four conversion pathways were assessed against a fossil fuel reference: (I) anaerobic co-digestion with manure, (II) gasification, (III) combustion in small-to-medium scale biomass combined heat and power (CHP) plants and IV) co-firing in large scale coal-fired CHP plants. Soil carbon changes, direct and indirect land use changes as well as uncertainty analysis (sensitivity, MonteCarlo) were included in the LCA. Results showed that global warming was the bottleneck impact, where only two scenarios, namely willow and Miscanthus co-firing, allowed for an improvement as compared with the reference (-82 and -45 t CO₂-eq. ha⁻¹, respectively). The indirect land use changes impact was quantified as 310 ± 170 t CO₂-eq. ha⁻¹, representing a paramount average of 41% of the induced greenhouse gas emissions. The uncertainty analysis confirmed the results robustness and highlighted the indirect land use changes uncertainty as the only uncertainty that can significantly change the outcome of the LCA results.

Differential co-expression analysis reveals a novel prognostic gene module in ovarian cancer.

PubMed

Gov, Esra; Arga, Kazim Yalcin

2017-07-10

Ovarian cancer is one of the most significant disease among gynecological disorders that women suffered from over the centuries. However, disease-specific and effective biomarkers were still not available, since studies have focused on individual genes associated with ovarian cancer, ignoring the interactions and associations among the gene products. Here, ovarian cancer differential co-expression networks were reconstructed via meta-analysis of gene expression data and co-expressed gene modules were identified in epithelial cells from ovarian tumor and healthy ovarian surface epithelial samples to propose ovarian cancer associated genes and their interactions. We propose a novel, highly interconnected, differentially co-expressed, and co-regulated gene module in ovarian cancer consisting of 84 prognostic genes. Furthermore, the specificity of the module to ovarian cancer was shown through analyses of datasets in nine other cancers. These observations underscore the importance of transcriptome based systems biomarkers research in deciphering the elusive pathophysiology of ovarian cancer, and here, we present reciprocal interplay between candidate ovarian cancer genes and their transcriptional regulatory dynamics. The corresponding gene module might provide new insights on ovarian cancer prognosis and treatment strategies that continue to place a significant burden on global health.

Traits and causes of environmental loss-related chemical accidents in China based on co-word analysis.

PubMed

Wu, Desheng; Song, Yu; Xie, Kefan; Zhang, Baofeng

2018-04-25

Chemical accidents are major causes of environmental losses and have been debated due to the potential threat to human beings and environment. Compared with the single statistical analysis, co-word analysis of chemical accidents illustrates significant traits at various levels and presents data into a visual network. This study utilizes a co-word analysis of the keywords extracted from the Web crawling texts of environmental loss-related chemical accidents and uses the Pearson's correlation coefficient to examine the internal attributes. To visualize the keywords of the accidents, this study carries out a multidimensional scaling analysis applying PROXSCAL and centrality identification. The research results show that an enormous environmental cost is exacted, especially given the expected environmental loss-related chemical accidents with geographical features. Meanwhile, each event often brings more than one environmental impact. Large number of chemical substances are released in the form of solid, liquid, and gas, leading to serious results. Eight clusters that represent the traits of these accidents are formed, including "leakage," "poisoning," "explosion," "pipeline crack," "river pollution," "dust pollution," "emission," and "industrial effluent." "Explosion" and "gas" possess a strong correlation with "poisoning," located at the center of visualization map.

Correlated mRNAs and miRNAs from co-expression and regulatory networks affect porcine muscle and finally meat properties.

PubMed

Ponsuksili, Siriluck; Du, Yang; Hadlich, Frieder; Siengdee, Puntita; Murani, Eduard; Schwerin, Manfred; Wimmers, Klaus

2013-08-05

Physiological processes aiding the conversion of muscle to meat involve many genes associated with muscle structure and metabolic processes. MicroRNAs regulate networks of genes to orchestrate cellular functions, in turn regulating phenotypes. We applied weighted gene co-expression network analysis to identify co-expression modules that correlated to meat quality phenotypes and were highly enriched for genes involved in glucose metabolism, response to wounding, mitochondrial ribosome, mitochondrion, and extracellular matrix. Negative correlation of miRNA with mRNA and target prediction were used to select transcripts out of the modules of trait-associated mRNAs to further identify those genes that are correlated with post mortem traits. Porcine muscle co-expression transcript networks that correlated to post mortem traits were identified. The integration of miRNA and mRNA expression analyses, as well as network analysis, enabled us to interpret the differentially-regulated genes from a systems perspective. Linking co-expression networks of transcripts and hierarchically organized pairs of miRNAs and mRNAs to meat properties yields new insight into several biological pathways underlying phenotype differences. These pathways may also be diagnostic for many myopathies, which are accompanied by deficient nutrient and oxygen supply of muscle fibers.

Ubiquitous LEA29Y Expression Blocks T Cell Co-Stimulation but Permits Sexual Reproduction in Genetically Modified Pigs.

PubMed

Bähr, Andrea; Käser, Tobias; Kemter, Elisabeth; Gerner, Wilhelm; Kurome, Mayuko; Baars, Wiebke; Herbach, Nadja; Witter, Kirsti; Wünsch, Annegret; Talker, Stephanie C; Kessler, Barbara; Nagashima, Hiroshi; Saalmüller, Armin; Schwinzer, Reinhard; Wolf, Eckhard; Klymiuk, Nikolai

2016-01-01

We have successfully established and characterized a genetically modified pig line with ubiquitous expression of LEA29Y, a human CTLA4-Ig derivate. LEA29Y binds human B7.1/CD80 and B7.2/CD86 with high affinity and is thus a potent inhibitor of T cell co-stimulation via this pathway. We have characterized the expression pattern and the biological function of the transgene as well as its impact on the porcine immune system and have evaluated the potential of these transgenic pigs to propagate via assisted breeding methods. The analysis of LEA29Y expression in serum and multiple organs of CAG-LEA transgenic pigs revealed that these animals produce a biologically active transgenic product at a considerable level. They present with an immune system affected by transgene expression, but can be maintained until sexual maturity and propagated by assisted reproduction techniques. Based on previous experience with pancreatic islets expressing LEA29Y, tissues from CAG-LEA29Y transgenic pigs should be protected against rejection by human T cells. Furthermore, their immune-compromised phenotype makes CAG-LEA29Y transgenic pigs an interesting large animal model for testing human cell therapies and will provide an important tool for further clarifying the LEA29Y mode of action.

Massive-scale gene co-expression network construction and robustness testing using random matrix theory.

PubMed

Gibson, Scott M; Ficklin, Stephen P; Isaacson, Sven; Luo, Feng; Feltus, Frank A; Smith, Melissa C

2013-01-01

The study of gene relationships and their effect on biological function and phenotype is a focal point in systems biology. Gene co-expression networks built using microarray expression profiles are one technique for discovering and interpreting gene relationships. A knowledge-independent thresholding technique, such as Random Matrix Theory (RMT), is useful for identifying meaningful relationships. Highly connected genes in the thresholded network are then grouped into modules that provide insight into their collective functionality. While it has been shown that co-expression networks are biologically relevant, it has not been determined to what extent any given network is functionally robust given perturbations in the input sample set. For such a test, hundreds of networks are needed and hence a tool to rapidly construct these networks. To examine functional robustness of networks with varying input, we enhanced an existing RMT implementation for improved scalability and tested functional robustness of human (Homo sapiens), rice (Oryza sativa) and budding yeast (Saccharomyces cerevisiae). We demonstrate dramatic decrease in network construction time and computational requirements and show that despite some variation in global properties between networks, functional similarity remains high. Moreover, the biological function captured by co-expression networks thresholded by RMT is highly robust.

Prognostic value of the MicroRNA regulators Dicer and Drosha in non-small-cell lung cancer: co-expression of Drosha and miR-126 predicts poor survival.

PubMed

Lønvik, Kenneth; Sørbye, Sveinung W; Nilsen, Marit N; Paulssen, Ruth H

2014-01-01

Dicer and Drosha are important enzymes for processing microRNAs. Recent studies have exhibited possible links between expression of different miRNAs, levels of miRNA processing enzymes, and cancer prognosis. We have investigated the prognostic impact of Dicer and Drosha and their correlation with miR-126 expression in a large cohort of non-small cell lung cancer (NSCLC) patients. We aimed to find patient groups within the cohort that might have an advantage of receiving adjunctive therapies. Dicer expression in the cytoplasm and Drosha expression in the nucleus were evaluated by manual immunohistochemistry of tissue microarrays (TMAs), including tumor tissue samples from 335 patients with resected stages I to IIIA NSCLC. In addition, in situ hybridizations of TMAs for visualization of miR-126 were performed. Kaplan-Meier analysis was performed, and the log-rank test via SPSS v.22 was used for estimating significance levels. In patients with normal performance status (ECOG = 0, n = 197), high Dicer expression entailed a significantly better prognosis than low Dicer expression (P = 0.024). Dicer had no significant prognostic value in patients with reduced performance status (ECOG = 1-2, n = 138). High Drosha expression was significantly correlated with high levels of the microRNA 126 (miR-126) (P = 0.004). Drosha/miR-126 co-expression had a significant negative impact on the disease-specific survival (DSS) rate (P < 0.001). Multivariate analyses revealed that the interaction Dicer*Histology (P = 0.049) and Drosha/miR-126 co-expression (P = 0.033) were independent prognostic factors. In NSCLC patients with normal performance status, Dicer is a positive prognostic factor. The importance of Drosha as a prognostic factor in our material seems to be related to miR-126 and possibly other microRNAs.

On the relationship between ecosystem-scale hyperspectral reflectance and CO2 exchange in European mountain grasslands

NASA Astrophysics Data System (ADS)

Balzarolo, M.; Vescovo, L.; Hammerle, A.; Gianelle, D.; Papale, D.; Tomelleri, E.; Wohlfahrt, G.

2015-05-01

In this paper we explore the skill of hyperspectral reflectance measurements and vegetation indices (VIs) derived from these in estimating carbon dioxide (CO2) fluxes of grasslands. Hyperspectral reflectance data, CO2 fluxes and biophysical parameters were measured at three grassland sites located in European mountain regions using standardized protocols. The relationships between CO2 fluxes, ecophysiological variables, traditional VIs and VIs derived using all two-band combinations of wavelengths available from the whole hyperspectral data space were analysed. We found that VIs derived from hyperspectral data generally explained a large fraction of the variability in the investigated dependent variables but differed in their ability to estimate midday and daily average CO2 fluxes and various derived ecophysiological parameters. Relationships between VIs and CO2 fluxes and ecophysiological parameters were site-specific, likely due to differences in soils, vegetation parameters and environmental conditions. Chlorophyll and water-content-related VIs explained the largest fraction of variability in most of the dependent variables. Band selection based on a combination of a genetic algorithm with random forests (GA-rF) confirmed that it is difficult to select a universal band region suitable across the investigated ecosystems. Our findings have major implications for upscaling terrestrial CO2 fluxes to larger regions and for remote- and proximal-sensing sampling and analysis strategies and call for more cross-site synthesis studies linking ground-based spectral reflectance with ecosystem-scale CO2 fluxes.

Assessing Greenhouse Gas emissions in the Greater Toronto Area using atmospheric observations (Invited)

NASA Astrophysics Data System (ADS)

Vogel, F. R.; Chan, E.; Huang, L.; Levin, I.; Worthy, D.

2013-12-01

Urban areas are said to be responsible for approximately 75% of anthropogenic Greenhouse Gases (GHGs) emissions while comprising only two percent of the land area [1]. This limited spatial expansion should facilitate a monitoring of anthropogenic GHGs from atmospheric observations. As major sources of emissions, cities also have a huge potential to drive emissions reductions. To effectively manage emissions, cities must however, first measure and report these publicly [2]. Modelling studies and measurements of CO2 from fossil fuel burning (FFCO2) in densely populated areas does, however, pose several challenges: Besides continuous in-situ observations, i.e. finding an adequate atmospheric transport model, a sufficiently fine-grained FFCO2 emission model and the proper background reference observations to distinguish the large-scale from the local/urban contributions to the observed FFCO2 concentration offsets ( ΔFFCO2) are required. Pilot studies which include the data from two 'sister sites*' in the vicinity of Toronto, Canada helped to derive flux estimates for Non-CO2 GHGs [3] and improve our understanding of urban FFCO2 emissions. Our 13CO2 observations reveal that the contribution of natural gas burning (mostly due to domestic heating) account for 80%×7% of FFCO2 emissions in the Greater Toronto Area (GTA) during winter. Our 14CO2 observations in the GTA, furthermore, show that the local offset of CO2 (ΔCO2) between our two sister sites can be largely attributed to urban FFCO2 emissions. The seasonal cycle of the observed ΔFFCO2 in Toronto, combined with high-resolution atmospheric modeling, helps to independently assess the contribution from different emission sectors (transportation, primary energy and industry, domestic heating) as predicted by a dedicated city-scale emission inventory, which deviates from a UNFCCC-based inventory. [1] D. Dodman. 2009. Blaming cities for climate change? An analysis of urban greenhouse gas emissions inventories. Environment and Urbanization, 21,185. [2] Arikan Y., Desaim R., Bhatia P. and W. K. Fong, 2012 Global Protocol for Community-Scale Greenhouse Gas Emissions (GPC), C40 Cities Climate Leadership group, available at: http://www.c40.org [3] Vogel, F. R., Ishizawa, M., Chan, E., Chan, D., Hammer, S., Levin, I., & Worthy, D. E. J. (2012). Regional non-CO2 greenhouse gas fluxes inferred from atmospheric measurements in Ontario, Canada. Journal of Integrative Environmental Sciences, 9(1), 41-55. *The term 'sister sites' refers to sites that share a common background signal (i.e. common large scale influence), while significantly differing sensitivities to urban GHG emissions. In our case: Egbert, Ontario and Downsview, Toronto, Ontario.

How cosmic microwave background correlations at large angles relate to mass autocorrelations in space

NASA Technical Reports Server (NTRS)

Blumenthal, George R.; Johnston, Kathryn V.

1994-01-01

The Sachs-Wolfe effect is known to produce large angular scale fluctuations in the cosmic microwave background radiation (CMBR) due to gravitational potential fluctuations. We show how the angular correlation function of the CMBR can be expressed explicitly in terms of the mass autocorrelation function xi(r) in the universe. We derive analytic expressions for the angular correlation function and its multipole moments in terms of integrals over xi(r) or its second moment, J(sub 3)(r), which does not need to satisfy the sort of integral constraint that xi(r) must. We derive similar expressions for bulk flow velocity in terms of xi and J(sub 3). One interesting result that emerges directly from this analysis is that, for all angles theta, there is a substantial contribution to the correlation function from a wide range of distance r and that radial shape of this contribution does not vary greatly with angle.

Transport properties and pinning analysis for Co-doped BaFe2As2 thin films on metal tapes

NASA Astrophysics Data System (ADS)

Xu, Zhongtang; Yuan, Pusheng; Fan, Fan; Chen, Yimin; Ma, Yanwei

2018-05-01

We report on the transport properties and pinning analysis of BaFe1.84Co0.16As2 (Ba122:Co) thin films on metal tapes by pulsed laser deposition. The thin films exhibit a large in-plane misorientation of 5.6°, close to that of the buffer layer SrTiO3 (5.9°). Activation energy U 0(H) analysis reveals a power law relationship with field, having three different exponents at different field regions, indicative of variation from single-vortex pinning to a collective flux creep regime. The Ba122:Co coated conductors present {{T}{{c}}}{{onset}} = 20.2 K and {{T}{{c}}}{{zero}} = 19.0 K along with a self-field J c of 1.14 MA cm‑2 and an in-field J c as high as 0.98 and 0.86 MA cm‑2 up to 9 T at 4.2 K for both major crystallographic directions of the applied field, promising for high field applications. Pinning force analysis indicates a significant enhancement compared with similar Ba122:Co coated conductors. By using the anisotropic scaling approach, intrinsic pinning associated with coupling between superconducting blocks can be identified as the pinning source in the vicinity of H//ab, while for H//c random point defects are likely to play a role but correlated defects start to be active at high temperatures.

Scaling laws for perturbations in the ocean-atmosphere system following large CO2 emissions

NASA Astrophysics Data System (ADS)

Towles, N.; Olson, P.; Gnanadesikan, A.

2015-01-01

Scaling relationships are derived for the perturbations to atmosphere and ocean variables from large transient CO2 emissions. Using the carbon cycle model LOSCAR (Zeebe et al., 2009; Zeebe, 2012b) we calculate perturbations to atmosphere temperature and total carbon, ocean temperature, total ocean carbon, pH, and alkalinity, marine sediment carbon, plus carbon-13 isotope anomalies in the ocean and atmosphere resulting from idealized CO2 emission events. The peak perturbations in the atmosphere and ocean variables are then fit to power law functions of the form γDαEbeta, where D is the event duration, E is its total carbon emission, and γ is a coefficient. Good power law fits are obtained for most system variables for E up to 50 000 PgC and D up to 100 kyr. However, these power laws deviate substantially from predictions based on simplified equilibrium considerations. For example, although all of the peak perturbations increase with emission rate E/D, we find no evidence of emission rate-only scaling α + β =0, a prediction of the long-term equilibrium between CO2 input by volcanism and CO2 removal by silicate weathering. Instead, our scaling yields α + β ≃ 1 for total ocean and atmosphere carbon and 0< α + β < 1 for most of the other system variables. The deviations in these scaling laws from equilibrium predictions are mainly due to the multitude and diversity of time scales that govern the exchange of carbon between marine sediments, the ocean, and the atmosphere.

Co-expression analysis reveals key gene modules and pathway of human coronary heart disease.

PubMed

Tang, Yu; Ke, Zun-Ping; Peng, Yi-Gen; Cai, Ping-Tai

2018-02-01

Coronary heart disease is a kind of disease which causes great injury to people world-widely. Although gene expression analyses had been performed previously, to our best knowledge, systemic co-expression analysis for this disease is still lacking to date. Microarray data of coronary heart disease was downloaded from NCBI with the accession number of GSE20681. Co-expression modules were constructed by WGCNA. Besides, the connectivity degree of eigengenes was analyzed. Furthermore, GO and KEGG enrichment analysis was performed on these eigengenes in these constructed modules. A total of 11 co-expression modules were constructed by the 3000 up-regulated genes from the 99 samples with coronary heart disease. The average number of genes in these modules was 270. The interaction analysis indicated the relative independence of gene expression in these modules. The functional enrichment analysis showed that there was a significant difference in the enriched terms and degree among these 11 modules. The results showed that modules 9 and 10 played critical roles in the occurrence of coronary disease. Pathways of hsa00190 (oxidative phosphorylation) and (hsa01130: biosynthesis of antibiotics) were thought to be closely related to the occurrence and development of coronary heart disease. Our result demonstrated that modules 9 and 10 were the most critical modules in the occurrence of coronary heart disease. Pathways as hsa00190 (oxidative phosphorylation) and (hsa01130: biosynthesis of antibiotics) had the potential to serve as the prognostic and predictive marker of coronary heart disease. © 2017 Wiley Periodicals, Inc.

Metatranscriptomic insights on gene expression and regulatory controls in Candidatus Accumulibacter phosphatis

DOE PAGES

Oyserman, Ben O.; Noguera, Daniel R.; del Rio, Tijana Glavina; ...

2015-11-10

Previous studies on enhanced biological phosphorus removal (EBPR) have focused on reconstructing genomic blueprints for the model polyphosphate-accumulating organism Candidatus Accumulibacter phosphatis. Here, a time series metatranscriptome generated from enrichment cultures of Accumulibacter was used to gain insight into anerobic/aerobic metabolism and regulatory mechanisms within an EBPR cycle. Co-expressed gene clusters were identified displaying ecologically relevant trends consistent with batch cycle phases. Transcripts displaying increased abundance during anerobic acetate contact were functionally enriched in energy production and conversion, including upregulation of both cytoplasmic and membrane-bound hydrogenases demonstrating the importance of transcriptional regulation to manage energy and electron flux during anerobicmore » acetate contact. We hypothesized and demonstrated hydrogen production after anerobic acetate contact, a previously unknown strategy for Accumulibacter to maintain redox balance. Genes involved in anerobic glycine utilization were identified and phosphorus release after anerobic glycine contact demonstrated, suggesting that Accumulibacter routes diverse carbon sources to acetyl-CoA formation via previously unrecognized pathways. A comparative genomics analysis of sequences upstream of co-expressed genes identified two statistically significant putative regulatory motifs. One palindromic motif was identified upstream of genes involved in PHA synthesis and acetate activation and is hypothesized to be a phaR binding site, hence representing a hypothetical PHA modulon. A second motif was identified ~35 base pairs (bp) upstream of a large and diverse array of genes and hence may represent a sigma factor binding site. As a result, this analysis provides a basis and framework for further investigations into Accumulibacter metabolism and the reconstruction of regulatory networks in uncultured organisms.« less

Metatranscriptomic insights on gene expression and regulatory controls in Candidatus Accumulibacter phosphatis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oyserman, Ben O.; Noguera, Daniel R.; del Rio, Tijana Glavina

Previous studies on enhanced biological phosphorus removal (EBPR) have focused on reconstructing genomic blueprints for the model polyphosphate-accumulating organism Candidatus Accumulibacter phosphatis. Here, a time series metatranscriptome generated from enrichment cultures of Accumulibacter was used to gain insight into anerobic/aerobic metabolism and regulatory mechanisms within an EBPR cycle. Co-expressed gene clusters were identified displaying ecologically relevant trends consistent with batch cycle phases. Transcripts displaying increased abundance during anerobic acetate contact were functionally enriched in energy production and conversion, including upregulation of both cytoplasmic and membrane-bound hydrogenases demonstrating the importance of transcriptional regulation to manage energy and electron flux during anerobicmore » acetate contact. We hypothesized and demonstrated hydrogen production after anerobic acetate contact, a previously unknown strategy for Accumulibacter to maintain redox balance. Genes involved in anerobic glycine utilization were identified and phosphorus release after anerobic glycine contact demonstrated, suggesting that Accumulibacter routes diverse carbon sources to acetyl-CoA formation via previously unrecognized pathways. A comparative genomics analysis of sequences upstream of co-expressed genes identified two statistically significant putative regulatory motifs. One palindromic motif was identified upstream of genes involved in PHA synthesis and acetate activation and is hypothesized to be a phaR binding site, hence representing a hypothetical PHA modulon. A second motif was identified ~35 base pairs (bp) upstream of a large and diverse array of genes and hence may represent a sigma factor binding site. As a result, this analysis provides a basis and framework for further investigations into Accumulibacter metabolism and the reconstruction of regulatory networks in uncultured organisms.« less

SMILE, a new orphan nuclear receptor SHP-interacting protein, regulates SHP-repressed estrogen receptor transactivation.

PubMed

Xie, Yuan-Bin; Lee, Ok-Hee; Nedumaran, Balachandar; Seong, Hyun-A; Lee, Kyeong-Min; Ha, Hyunjung; Lee, In-Kyu; Yun, Yungdae; Choi, Hueng-Sik

2008-12-15

SHP (small heterodimer partner) is a well-known NR (nuclear receptor) co-regulator. In the present study, we have identified a new SHP-interacting protein, termed SMILE (SHP-interacting leucine zipper protein), which was previously designated as ZF (Zhangfei) via a yeast two-hybrid system. We have determined that the SMILE gene generates two isoforms [SMILE-L (long isoform of SMILE) and SMILE-S (short isoform of SMILE)]. Mutational analysis has demonstrated that the SMILE isoforms arise from the alternative usage of initiation codons. We have confirmed the in vivo interaction and co-localization of the SMILE isoforms and SHP. Domain-mapping analysis indicates that the entire N-terminus of SHP and the middle region of SMILE-L are involved in this interaction. Interestingly, the SMILE isoforms counteract the SHP repressive effect on the transactivation of ERs (estrogen receptors) in HEK-293T cells (human embryonic kidney cells expressing the large T-antigen of simian virus 40), but enhance the SHP-repressive effect in MCF-7, T47D and MDA-MB-435 cells. Knockdown of SMILE gene expression using siRNA (small interfering RNA) in MCF-7 cells increases ER-mediated transcriptional activity. Moreover, adenovirus-mediated overexpression of SMILE and SHP down-regulates estrogen-induced mRNA expression of the critical cell-cycle regulator E2F1. Collectively, these results indicate that SMILE isoforms regulate the inhibition of ER transactivation by SHP in a cell-type-specific manner and act as a novel transcriptional co-regulator in ER signalling.

Disentangling degenerate solutions from primary transit and secondary eclipse spectroscopy of exoplanets.

PubMed

Griffith, Caitlin A

2014-04-28

Infrared transmission and emission spectroscopy of exoplanets, recorded from primary transit and secondary eclipse measurements, indicate the presence of the most abundant carbon and oxygen molecular species (H2O, CH4, CO and CO2) in a few exoplanets. However, efforts to constrain the molecular abundances to within several orders of magnitude are thwarted by the broad range of degenerate solutions that fit the data. Here, we explore, with radiative transfer models and analytical approximations, the nature of the degenerate solution sets resulting from the sparse measurements of 'hot Jupiter' exoplanets. As demonstrated with simple analytical expressions, primary transit measurements probe roughly four atmospheric scale heights at each wavelength band. Derived mixing ratios from these data are highly sensitive to errors in the radius of the planet at a reference pressure. For example, an uncertainty of 1% in the radius of a 1000 K and H2-based exoplanet with Jupiter's radius and mass causes an uncertainty of a factor of approximately 100-10,000 in the derived gas mixing ratios. The degree of sensitivity depends on how the line strength increases with the optical depth (i.e. the curve of growth) and the atmospheric scale height. Temperature degeneracies in the solutions of the primary transit data, which manifest their effects through the scale height and absorption coefficients, are smaller. We argue that these challenges can be partially surmounted by a combination of selected wavelength sampling of optical and infrared measurements and, when possible, the joint analysis of transit and secondary eclipse data of exoplanets. However, additional work is needed to constrain other effects, such as those owing to planetary clouds and star spots. Given the current range of open questions in the field, both observations and theory, there is a need for detailed measurements with space-based large mirror platforms (e.g. James web space telescope) and smaller broad survey telescopes as well as ground-based efforts.

Microarray analysis identifies candidate genes for key roles in coral development

PubMed Central

Grasso, Lauretta C; Maindonald, John; Rudd, Stephen; Hayward, David C; Saint, Robert; Miller, David J; Ball, Eldon E

2008-01-01

Background Anthozoan cnidarians are amongst the simplest animals at the tissue level of organization, but are surprisingly complex and vertebrate-like in terms of gene repertoire. As major components of tropical reef ecosystems, the stony corals are anthozoans of particular ecological significance. To better understand the molecular bases of both cnidarian development in general and coral-specific processes such as skeletogenesis and symbiont acquisition, microarray analysis was carried out through the period of early development – when skeletogenesis is initiated, and symbionts are first acquired. Results Of 5081 unique peptide coding genes, 1084 were differentially expressed (P ≤ 0.05) in comparisons between four different stages of coral development, spanning key developmental transitions. Genes of likely relevance to the processes of settlement, metamorphosis, calcification and interaction with symbionts were characterised further and their spatial expression patterns investigated using whole-mount in situ hybridization. Conclusion This study is the first large-scale investigation of developmental gene expression for any cnidarian, and has provided candidate genes for key roles in many aspects of coral biology, including calcification, metamorphosis and symbiont uptake. One surprising finding is that some of these genes have clear counterparts in higher animals but are not present in the closely-related sea anemone Nematostella. Secondly, coral-specific processes (i.e. traits which distinguish corals from their close relatives) may be analogous to similar processes in distantly related organisms. This first large-scale application of microarray analysis demonstrates the potential of this approach for investigating many aspects of coral biology, including the effects of stress and disease. PMID:19014561

One-Health: a Safe, Efficient, Dual-Use Vaccine for Humans and Animals against Middle East Respiratory Syndrome Coronavirus and Rabies Virus.

PubMed

Wirblich, Christoph; Coleman, Christopher M; Kurup, Drishya; Abraham, Tara S; Bernbaum, John G; Jahrling, Peter B; Hensley, Lisa E; Johnson, Reed F; Frieman, Matthew B; Schnell, Matthias J

2017-01-15

Middle East respiratory syndrome coronavirus (MERS-CoV) emerged in 2012 and is a highly pathogenic respiratory virus. There are no treatment options against MERS-CoV for humans or animals, and there are no large-scale clinical trials for therapies against MERS-CoV. To address this need, we developed an inactivated rabies virus (RABV) that contains the MERS-CoV spike (S) protein expressed on its surface. Our initial recombinant vaccine, BNSP333-S, expresses a full-length wild-type MERS-CoV S protein; however, it showed significantly reduced viral titers compared to those of the parental RABV strain and only low-level incorporation of full-length MERS-CoV S into RABV particles. Therefore, we developed a RABV-MERS vector that contained the MERS-CoV S1 domain of the MERS-CoV S protein fused to the RABV G protein C terminus (BNSP333-S1). BNSP333-S1 grew to titers similar to those of the parental vaccine vector BNSP333, and the RABV G-MERS-CoV S1 fusion protein was efficiently expressed and incorporated into RABV particles. When we vaccinated mice, chemically inactivated BNSP333-S1 induced high-titer neutralizing antibodies. Next, we challenged both vaccinated mice and control mice with MERS-CoV after adenovirus transduction of the human dipeptidyl peptidase 4 (hDPP4) receptor and then analyzed the ability of mice to control MERS-CoV infection. Our results demonstrated that vaccinated mice were fully protected from the MERS-CoV challenge, as indicated by the significantly lower MERS-CoV titers and MERS-CoV and mRNA levels in challenged mice than those in unvaccinated controls. These data establish that an inactivated RABV-MERS S-based vaccine may be effective for use in animals and humans in areas where MERS-CoV is endemic. Rabies virus-based vectors have been proven to be efficient dual vaccines against rabies and emergent infectious diseases such as Ebola virus. Here we show that inactivated rabies virus particles containing the MERS-CoV S1 protein induce potent immune responses against MERS-CoV and RABV. This novel vaccine is easy to produce and may be useful to protect target animals, such as camels, as well as humans from deadly MERS-CoV and RABV infections. Our results indicate that this vaccine approach can prevent disease, and the RABV-based vaccine platform may be a valuable tool for timely vaccine development against emerging infectious diseases. Copyright © 2017 American Society for Microbiology.

Integrative Exploratory Analysis of Two or More Genomic Datasets.

PubMed

Meng, Chen; Culhane, Aedin

2016-01-01

Exploratory analysis is an essential step in the analysis of high throughput data. Multivariate approaches such as correspondence analysis (CA), principal component analysis, and multidimensional scaling are widely used in the exploratory analysis of single dataset. Modern biological studies often assay multiple types of biological molecules (e.g., mRNA, protein, phosphoproteins) on a same set of biological samples, thereby creating multiple different types of omics data or multiassay data. Integrative exploratory analysis of these multiple omics data is required to leverage the potential of multiple omics studies. In this chapter, we describe the application of co-inertia analysis (CIA; for analyzing two datasets) and multiple co-inertia analysis (MCIA; for three or more datasets) to address this problem. These methods are powerful yet simple multivariate approaches that represent samples using a lower number of variables, allowing a more easily identification of the correlated structure in and between multiple high dimensional datasets. Graphical representations can be employed to this purpose. In addition, the methods simultaneously project samples and variables (genes, proteins) onto the same lower dimensional space, so the most variant variables from each dataset can be selected and associated with samples, which can be further used to facilitate biological interpretation and pathway analysis. We applied CIA to explore the concordance between mRNA and protein expression in a panel of 60 tumor cell lines from the National Cancer Institute. In the same 60 cell lines, we used MCIA to perform a cross-platform comparison of mRNA gene expression profiles obtained on four different microarray platforms. Last, as an example of integrative analysis of multiassay or multi-omics data we analyzed transcriptomic, proteomic, and phosphoproteomic data from pluripotent (iPS) and embryonic stem (ES) cell lines.

Lightweight and Statistical Techniques for Petascale Debugging: Correctness on Petascale Systems (CoPS) Preliminry Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

de Supinski, B R; Miller, B P; Liblit, B

2011-09-13

Petascale platforms with O(10{sup 5}) and O(10{sup 6}) processing cores are driving advancements in a wide range of scientific disciplines. These large systems create unprecedented application development challenges. Scalable correctness tools are critical to shorten the time-to-solution on these systems. Currently, many DOE application developers use primitive manual debugging based on printf or traditional debuggers such as TotalView or DDT. This paradigm breaks down beyond a few thousand cores, yet bugs often arise above that scale. Programmers must reproduce problems in smaller runs to analyze them with traditional tools, or else perform repeated runs at scale using only primitive techniques.more » Even when traditional tools run at scale, the approach wastes substantial effort and computation cycles. Continued scientific progress demands new paradigms for debugging large-scale applications. The Correctness on Petascale Systems (CoPS) project is developing a revolutionary debugging scheme that will reduce the debugging problem to a scale that human developers can comprehend. The scheme can provide precise diagnoses of the root causes of failure, including suggestions of the location and the type of errors down to the level of code regions or even a single execution point. Our fundamentally new strategy combines and expands three relatively new complementary debugging approaches. The Stack Trace Analysis Tool (STAT), a 2011 R&D 100 Award Winner, identifies behavior equivalence classes in MPI jobs and highlights behavior when elements of the class demonstrate divergent behavior, often the first indicator of an error. The Cooperative Bug Isolation (CBI) project has developed statistical techniques for isolating programming errors in widely deployed code that we will adapt to large-scale parallel applications. Finally, we are developing a new approach to parallelizing expensive correctness analyses, such as analysis of memory usage in the Memgrind tool. In the first two years of the project, we have successfully extended STAT to determine the relative progress of different MPI processes. We have shown that the STAT, which is now included in the debugging tools distributed by Cray with their large-scale systems, substantially reduces the scale at which traditional debugging techniques are applied. We have extended CBI to large-scale systems and developed new compiler based analyses that reduce its instrumentation overhead. Our results demonstrate that CBI can identify the source of errors in large-scale applications. Finally, we have developed MPIecho, a new technique that will reduce the time required to perform key correctness analyses, such as the detection of writes to unallocated memory. Overall, our research results are the foundations for new debugging paradigms that will improve application scientist productivity by reducing the time to determine which package or module contains the root cause of a problem that arises at all scales of our high end systems. While we have made substantial progress in the first two years of CoPS research, significant work remains. While STAT provides scalable debugging assistance for incorrect application runs, we could apply its techniques to assertions in order to observe deviations from expected behavior. Further, we must continue to refine STAT's techniques to represent behavioral equivalence classes efficiently as we expect systems with millions of threads in the next year. We are exploring new CBI techniques that can assess the likelihood that execution deviations from past behavior are the source of erroneous execution. Finally, we must develop usable correctness analyses that apply the MPIecho parallelization strategy in order to locate coding errors. We expect to make substantial progress on these directions in the next year but anticipate that significant work will remain to provide usable, scalable debugging paradigms.« less

Single-nucleotide polymorphism-gene intermixed networking reveals co-linkers connected to multiple gene expression phenotypes

PubMed Central

Gong, Bin-Sheng; Zhang, Qing-Pu; Zhang, Guang-Mei; Zhang, Shao-Jun; Zhang, Wei; Lv, Hong-Chao; Zhang, Fan; Lv, Sa-Li; Li, Chuan-Xing; Rao, Shao-Qi; Li, Xia

2007-01-01

Gene expression profiles and single-nucleotide polymorphism (SNP) profiles are modern data for genetic analysis. It is possible to use the two types of information to analyze the relationships among genes by some genetical genomics approaches. In this study, gene expression profiles were used as expression traits. And relationships among the genes, which were co-linked to a common SNP(s), were identified by integrating the two types of information. Further research on the co-expressions among the co-linked genes was carried out after the gene-SNP relationships were established using the Haseman-Elston sib-pair regression. The results showed that the co-expressions among the co-linked genes were significantly higher if the number of connections between the genes and a SNP(s) was more than six. Then, the genes were interconnected via one or more SNP co-linkers to construct a gene-SNP intermixed network. The genes sharing more SNPs tended to have a stronger correlation. Finally, a gene-gene network was constructed with their intensities of relationships (the number of SNP co-linkers shared) as the weights for the edges. PMID:18466544

DNA microarray analysis of Methanosarcina mazei Gö1 reveals adaptation to different methanogenic substrates.

PubMed

Hovey, Raymond; Lentes, Sabine; Ehrenreich, Armin; Salmon, Kirsty; Saba, Karla; Gottschalk, Gerhard; Gunsalus, Robert P; Deppenmeier, Uwe

2005-05-01

Methansarcina mazei Gö1 DNA arrays were constructed and used to evaluate the genomic expression patterns of cells grown on either of two alternative methanogenic substrates, acetate or methanol, as sole carbon and energy source. Analysis of differential transcription across the genome revealed two functionally grouped sets of genes that parallel the central biochemical pathways in, and reflect many known features of, acetate and methanol metabolism. These include the acetate-induced genes encoding acetate activating enzymes, acetyl-CoA synthase/CO dehydrogenase, and carbonic anhydrase. Interestingly, additional genes expressed at significantly higher levels during growth on acetate included two energy-conserving complexes (the Ech hydrogenase, and the A1A0-type ATP synthase). Many previously unknown features included the induction by acetate of genes coding for ferredoxins and flavoproteins, an aldehyde:ferredoxin oxidoreductase, enzymes for the synthesis of aromatic amino acids, and components of iron, cobalt and oligopeptide uptake systems. In contrast, methanol-grown cells exhibited elevated expression of genes assigned to the methylotrophic pathway of methanogenesis. Expression of genes for components of the translation apparatus was also elevated in cells grown in the methanol medium relative to acetate, and was correlated with the faster growth rate observed on the former substrate. These experiments provide the first comprehensive insight into substrate-dependent gene expression in a methanogenic archaeon. This genome-wide approach, coupled with the complementary molecular and biochemical tools, should greatly accelerate the exploration of Methanosarcina cell physiology, given the present modest level of our knowledge of these large archaeal genomes.

Expression and purification of soluble porcine CTLA-4 in yeast Pichia pastoris

PubMed Central

Peraino, Jaclyn; Zhang, Huiping; Hermanrud, Christina E.; Li, Guoying; Sachs, David H.; Huang, Christene A.; Wang, Zhirui

2012-01-01

Co-stimulation blockade can be used to modulate the immune response for induction of organ transplantation tolerance, treatment of autoimmune disease as well as cancer treatment. Cytotoxic T-Lymphocyte Antigen-4 (CTLA-4), also known as CD152, is an important co-stimulatory molecule which serves as a negative regulator for T cell proliferation and differentiation. CTLA-4/CD28-CD80/CD86 pathway is a critical co-stimulatory pathway for adaptive immune response. T cell activation through the T cell receptor and CD28 leads to increased expression of CTLA-4, an inhibitory receptor for CD80 and CD86. MGH MHC-defined miniature swine provide a unique large animal model useful for preclinical studies of transplantation tolerance and immune regulation. In this study, we have expressed the codon-optimized soluble porcine CTLA-4 in the yeast Pichia pastoris system. The secreted porcine CTLA-4 was captured using Ni-Sepharose 6 fast flow resin and further purified using strong anion exchange resin Poros 50HQ. Glycosylation analysis using PNGase F demonstrated the N-linked glycosylation on Pichia pastoris expressed soluble porcine CTLA-4. To improve the expression level and facilitate the downstream purification we mutated the two potential N-linked glycosylation sites with non-polarized alanines by site-directed mutagenesis. Removal of the two N-glycosylation sites significantly improved the production level from ~2 mg/L to ~8 mg/L. Biotinylated glycosylated and non-N-glycosylated soluble porcine CTLA-4 both bind to a porcine CD80-expressing B-cell lymphoma cell line (KD = 13 nM) and competitively inhibit the binding of an anti-CD80 monoclonal antibody. The availability of soluble porcine CTLA-4, especially the non-N-glycosylated CTLA-4, will provide a very valuable tool for assessing co-stimulatory blockade treatment for translational studies in the clinically relevant porcine model. PMID:22326797

Revised Distances to 21 Supernova Remnants

NASA Astrophysics Data System (ADS)

Ranasinghe, S.; Leahy, D. A.

2018-05-01

We carry out a comprehensive study of H I 21 cm line observations and 13CO line observations of 21 supernova remnants (SNRs). The aim of the study is to search for H I absorption features to obtain kinematic distances in a consistent manner. The 21 SNRs are in the region of sky covered by the Very Large Array Galactic Plane Survey (H I 21 cm observations) and Galactic Ring Survey (13CO line observations). We obtain revised distances for 10 SNRs based on new evidence in the H I and 13CO observations. We revise distances for the other 11 SNRs based on an updated rotation curve and new error analysis. The mean change in distance for the 21 SNRs is ≃25%, i.e., a change of 1.5 kpc compared to a mean distance for the sample of 6.4 kpc. This has a significant impact on interpretation of the physical state of these SNRs. For example, using a Sedov model, age and explosion energy scale as the square of distance, and inferred ISM density scales as distance.

Exploring root symbiotic programs in the model legume Medicago truncatula using EST analysis.

PubMed

Journet, Etienne-Pascal; van Tuinen, Diederik; Gouzy, Jérome; Crespeau, Hervé; Carreau, Véronique; Farmer, Mary-Jo; Niebel, Andreas; Schiex, Thomas; Jaillon, Olivier; Chatagnier, Odile; Godiard, Laurence; Micheli, Fabienne; Kahn, Daniel; Gianinazzi-Pearson, Vivienne; Gamas, Pascal

2002-12-15

We report on a large-scale expressed sequence tag (EST) sequencing and analysis program aimed at characterizing the sets of genes expressed in roots of the model legume Medicago truncatula during interactions with either of two microsymbionts, the nitrogen-fixing bacterium Sinorhizobium meliloti or the arbuscular mycorrhizal fungus Glomus intraradices. We have designed specific tools for in silico analysis of EST data, in relation to chimeric cDNA detection, EST clustering, encoded protein prediction, and detection of differential expression. Our 21 473 5'- and 3'-ESTs could be grouped into 6359 EST clusters, corresponding to distinct virtual genes, along with 52 498 other M.truncatula ESTs available in the dbEST (NCBI) database that were recruited in the process. These clusters were manually annotated, using a specifically developed annotation interface. Analysis of EST cluster distribution in various M.truncatula cDNA libraries, supported by a refined R test to evaluate statistical significance and by 'electronic northern' representation, enabled us to identify a large number of novel genes predicted to be up- or down-regulated during either symbiotic root interaction. These in silico analyses provide a first global view of the genetic programs for root symbioses in M.truncatula. A searchable database has been built and can be accessed through a public interface.

Lidar Measurements of Atmospheric CO2 From Regional to Global Scales

NASA Technical Reports Server (NTRS)

Lin, Bing; Harrison, F. Wallace; Nehrir, Amin; Browell, Edward; Dobler, Jeremy; Campbell, Joel; Meadows, Byron; Obland, Michael; Ismail, Syed; Kooi, Susan;

NEUROTROPHIN SELECTIVITY IN ORGANIZING TOPOGRAPHIC REGENERATION OF NOCICEPTIVE AFFERENTS

PubMed Central

Kelamangalath, Lakshmi; Tang, Xiaoqing; Bezik, Kathleen; Sterling, Noelle; Son, Young-Jin; Smith, George M.

2015-01-01

Neurotrophins represent some of the best candidates to enhance regeneration. In the current study, we investigated the effects of artemin, a member of the glial derived neurotrophic factor (GDNF) family, on sensory axon regeneration following a lumbar dorsal root injury and compared these effects with that observed after either NGF or GDNF expression in the rat spinal cord. Unlike previously published data, artemin failed to induce regeneration of large-diameter myelinated sensory afferents when expressed within either the spinal cord or DRG. However, artemin or NGF induced regeneration of calcitonin gene related peptide positive (CGRP+) axons only when expressed within the spinal cord. Accordingly, artemin or NGF enhanced recovery of only nociceptive behavior and showed a cFos distribution similar to the topography of regenerating axons. Artemin and GDNF signaling requires binding to different co-receptors (GFRα3 or GFRα1, respectively) prior to binding to the signaling receptor, cRet. Approximately 70% of DRG neurons express cRet, but only 35% express either co-receptor. To enhance artemin-induced regeneration, we co-expressed artemin with either GFRα3 or GDNF. Co-expression of artemin and GFRα3 only slightly enhanced regeneration of IB4+ non-peptidergic nociceptive axons, but not myelinated axons. Interestingly, this co-expression also disrupted the ability of artemin to produce topographic targeting and lead to significant increases in cFos immunoreactivity within the deep dorsal laminae. This study failed to demonstrate artemin-induced regeneration of myelinated axons, even with co-expression of GFR-α3, which only promoted mistargeted regeneration. PMID:26054884

Neurotrophin selectivity in organizing topographic regeneration of nociceptive afferents.

PubMed

Kelamangalath, Lakshmi; Tang, Xiaoqing; Bezik, Kathleen; Sterling, Noelle; Son, Young-Jin; Smith, George M

2015-09-01

Neurotrophins represent some of the best candidates to enhance regeneration. In the current study, we investigated the effects of artemin, a member of the glial derived neurotrophic factor (GDNF) family, on sensory axon regeneration following a lumbar dorsal root injury and compared these effects with that observed after either NGF or GDNF expression in the rat spinal cord. Unlike previously published data, artemin failed to induce regeneration of large-diameter myelinated sensory afferents when expressed within either the spinal cord or DRG. However, artemin or NGF induced regeneration of calcitonin gene related peptide positive (CGRP(+)) axons only when expressed within the spinal cord. Accordingly, artemin or NGF enhanced recovery of only nociceptive behavior and showed a cFos distribution similar to the topography of regenerating axons. Artemin and GDNF signaling requires binding to different co-receptors (GFRα3 or GFRα1, respectively) prior to binding to the signaling receptor, cRet. Approximately 70% of DRG neurons express cRet, but only 35% express either co-receptor. To enhance artemin-induced regeneration, we co-expressed artemin with either GFRα3 or GDNF. Co-expression of artemin and GFRα3 only slightly enhanced regeneration of IB4(+) non-peptidergic nociceptive axons, but not myelinated axons. Interestingly, this co-expression also disrupted the ability of artemin to produce topographic targeting and lead to significant increases in cFos immunoreactivity within the deep dorsal laminae. This study failed to demonstrate artemin-induced regeneration of myelinated axons, even with co-expression of GFRα3, which only promoted mistargeted regeneration. Copyright © 2015 Elsevier Inc. All rights reserved.

Prostate-specific membrane antigen PET/MRI validation of MR textural analysis for detection of transition zone prostate cancer.

PubMed

Bates, Anthony; Miles, Kenneth

2017-12-01

To validate MR textural analysis (MRTA) for detection of transition zone (TZ) prostate cancer through comparison with co-registered prostate-specific membrane antigen (PSMA) PET-MR. Retrospective analysis was performed for 30 men who underwent simultaneous PSMA PET-MR imaging for staging of prostate cancer. Thirty texture features were derived from each manually contoured T2-weighted, transaxial, prostatic TZ using texture analysis software that applies a spatial band-pass filter and quantifies texture through histogram analysis. Texture features of the TZ were compared to PSMA expression on the corresponding PET images. The Benjamini-Hochberg correction controlled the false discovery rate at <5%. Eighty-eight T2-weighted images in 18 patients demonstrated abnormal PSMA expression within the TZ on PET-MR. 123 images were PSMA negative. Based on the corrected p-value of 0.005, significant differences between PSMA positive and negative slices were found for 16 texture parameters: Standard deviation and mean of positive pixels for all spatial filters (p = <0.0001 for both at all spatial scaling factor (SSF) values) and mean intensity following filtration for SSF 3-6 mm (p = 0.0002-0.0018). Abnormal expression of PSMA within the TZ is associated with altered texture on T2-weighted MR, providing validation of MRTA for the detection of TZ prostate cancer. • Prostate transition zone (TZ) MR texture analysis may assist in prostate cancer detection. • Abnormal transition zone PSMA expression correlates with altered texture on T2-weighted MR. • TZ with abnormal PSMA expression demonstrates significantly reduced MI, SD and MPP.

Large-Scale Ocean Circulation-Cloud Interactions Reduce the Pace of Transient Climate Change

NASA Technical Reports Server (NTRS)

Trossman, D. S.; Palter, J. B.; Merlis, T. M.; Huang, Y.; Xia, Y.

2016-01-01

Changes to the large scale oceanic circulation are thought to slow the pace of transient climate change due, in part, to their influence on radiative feedbacks. Here we evaluate the interactions between CO2-forced perturbations to the large-scale ocean circulation and the radiative cloud feedback in a climate model. Both the change of the ocean circulation and the radiative cloud feedback strongly influence the magnitude and spatial pattern of surface and ocean warming. Changes in the ocean circulation reduce the amount of transient global warming caused by the radiative cloud feedback by helping to maintain low cloud coverage in the face of global warming. The radiative cloud feedback is key in affecting atmospheric meridional heat transport changes and is the dominant radiative feedback mechanism that responds to ocean circulation change. Uncertainty in the simulated ocean circulation changes due to CO2 forcing may contribute a large share of the spread in the radiative cloud feedback among climate models.

Real-time monitoring of CO2 storage sites: Application to Illinois Basin-Decatur Project

USGS Publications Warehouse

Picard, G.; Berard, T.; Chabora, E.; Marsteller, S.; Greenberg, S.; Finley, R.J.; Rinck, U.; Greenaway, R.; Champagnon, C.; Davard, J.

2011-01-01

Optimization of carbon dioxide (CO2) storage operations for efficiency and safety requires use of monitoring techniques and implementation of control protocols. The monitoring techniques consist of permanent sensors and tools deployed for measurement campaigns. Large amounts of data are thus generated. These data must be managed and integrated for interpretation at different time scales. A fast interpretation loop involves combining continuous measurements from permanent sensors as they are collected to enable a rapid response to detected events; a slower loop requires combining large datasets gathered over longer operational periods from all techniques. The purpose of this paper is twofold. First, it presents an analysis of the monitoring objectives to be performed in the slow and fast interpretation loops. Second, it describes the implementation of the fast interpretation loop with a real-time monitoring system at the Illinois Basin-Decatur Project (IBDP) in Illinois, USA. ?? 2011 Published by Elsevier Ltd.

Analysis of DNA replication associated chromatin decondensation: in vivo assay for understanding chromatin remodeling mechanisms of selected proteins.

PubMed

Borysov, Sergiy; Bryant, Victoria L; Alexandrow, Mark G

2015-01-01

Of critical importance to many of the events underlying transcriptional control of gene expression are modifications to core and linker histones that regulate the accessibility of trans-acting factors to the DNA substrate within the context of chromatin. Likewise, control over the initiation of DNA replication, as well as the ability of the replication machinery to proceed during elongation through the multiple levels of chromatin condensation that are likely to be encountered, is known to involve the creation of chromatin accessibility. In the latter case, chromatin access will likely need to be a transient event so as to prevent total genomic unraveling of the chromatin that would be deleterious to cells. While there are many molecular and biochemical approaches in use to study histone changes and their relationship to transcription and chromatin accessibility, few techniques exist that allow a molecular dissection of the events underlying DNA replication control as it pertains to chromatin changes and accessibility. Here, we outline a novel experimental strategy for addressing the ability of specific proteins to induce large-scale chromatin unfolding (decondensation) in vivo upon site-specific targeting to an engineered locus. Our laboratory has used this powerful system in novel ways to directly address the ability of DNA replication proteins to create chromatin accessibility, and have incorporated modifications to the basic approach that allow for a molecular genetic analysis of the mechanisms and associated factors involved in causing chromatin decondensation by a protein of interest. Alternative approaches involving co-expression of other proteins (competitors or stimulators), concurrent drug treatments, and analysis of co-localizing histone modifications are also addressed, all of which are illustrative of the utility of this experimental system for extending basic findings to physiologically relevant mechanisms. Although used by our group to analyze mechanisms underlying DNA replication associated chromatin accessibility, this unique and powerful experimental system has the propensity to be a valuable tool for understanding chromatin remodeling mechanisms orchestrated by other cellular processes such as DNA repair, recombination, mitotic chromosome condensation, or other chromosome dynamics involving chromatin alterations and accessibility.

A distributed microcomputer-controlled system for data acquisition and power spectral analysis of EEG.

PubMed

Vo, T D; Dwyer, G; Szeto, H H

1986-04-01

A relatively powerful and inexpensive microcomputer-based system for the spectral analysis of the EEG is presented. High resolution and speed is achieved with the use of recently available large-scale integrated circuit technology with enhanced functionality (INTEL Math co-processors 8087) which can perform transcendental functions rapidly. The versatility of the system is achieved with a hardware organization that has distributed data acquisition capability performed by the use of a microprocessor-based analog to digital converter with large resident memory (Cyborg ISAAC-2000). Compiled BASIC programs and assembly language subroutines perform on-line or off-line the fast Fourier transform and spectral analysis of the EEG which is stored as soft as well as hard copy. Some results obtained from test application of the entire system in animal studies are presented.

[The value of alpha-methylacyl-CoA racemase expression in the progression of colonic carcinoma].

PubMed

López-Valdivia, Cecilia M; González-Matea, Manuel; Mayordomo, Empar; Hervás, David; Ramos, David

Alpha-methylacyl-CoA racemase (AMACR) expression has been demonstrated in several normal tissues and in diverse types of carcinoma. Our aim was to analyze the immunohistochemical expression of AMACR in the sequence-progression of colonic cancer. We studied 237 cases, including samples of normal mucosa of the colon, adenomas with different degrees of dysplasia, colonic carcinomas, lymph nodes and liver metastases of colonic carcinomas. A scale of intensity and percentage of expression was used to analyze the AMACR immunohistochemical profile. The expression was nearly absent in samples of normal mucosa, increased in both adenomas and carcinomas, decreased in lymph node metastases but was significantly increased in liver metastases. Copyright © 2016 Sociedad Española de Anatomía Patológica. Publicado por Elsevier España, S.L.U. All rights reserved.

The detailed 3D multi-loop aggregate/rosette chromatin architecture and functional dynamic organization of the human and mouse genomes.

PubMed

Knoch, Tobias A; Wachsmuth, Malte; Kepper, Nick; Lesnussa, Michael; Abuseiris, Anis; Ali Imam, A M; Kolovos, Petros; Zuin, Jessica; Kockx, Christel E M; Brouwer, Rutger W W; van de Werken, Harmen J G; van IJcken, Wilfred F J; Wendt, Kerstin S; Grosveld, Frank G

2016-01-01

The dynamic three-dimensional chromatin architecture of genomes and its co-evolutionary connection to its function-the storage, expression, and replication of genetic information-is still one of the central issues in biology. Here, we describe the much debated 3D architecture of the human and mouse genomes from the nucleosomal to the megabase pair level by a novel approach combining selective high-throughput high-resolution chromosomal interaction capture ( T2C ), polymer simulations, and scaling analysis of the 3D architecture and the DNA sequence. The genome is compacted into a chromatin quasi-fibre with ~5 ± 1 nucleosomes/11 nm, folded into stable ~30-100 kbp loops forming stable loop aggregates/rosettes connected by similar sized linkers. Minor but significant variations in the architecture are seen between cell types and functional states. The architecture and the DNA sequence show very similar fine-structured multi-scaling behaviour confirming their co-evolution and the above. This architecture, its dynamics, and accessibility, balance stability and flexibility ensuring genome integrity and variation enabling gene expression/regulation by self-organization of (in)active units already in proximity. Our results agree with the heuristics of the field and allow "architectural sequencing" at a genome mechanics level to understand the inseparable systems genomic properties.

Large-scale expansion of Wharton's jelly-derived mesenchymal stem cells on gelatin microbeads, with retention of self-renewal and multipotency characteristics and the capacity for enhancing skin wound healing.

PubMed

Zhao, Guifang; Liu, Feilin; Lan, Shaowei; Li, Pengdong; Wang, Li; Kou, Junna; Qi, Xiaojuan; Fan, Ruirui; Hao, Deshun; Wu, Chunling; Bai, Tingting; Li, Yulin; Liu, Jin Yu

2015-03-19

Successful stem cell therapy relies on large-scale generation of stem cells and their maintenance in a proliferative multipotent state. This study aimed to establish a three-dimension culture system for large-scale generation of hWJ-MSC and investigated the self-renewal activity, genomic stability and multi-lineage differentiation potential of such hWJ-MSC in enhancing skin wound healing. hWJ-MSC were seeded on gelatin microbeads and cultured in spinning bottles (3D). Cell proliferation, karyotype analysis, surface marker expression, multipotent differentiation (adipogenic, chondrogenic, and osteogenic potentials), and expression of core transcription factors (OCT4, SOX2, NANOG, and C-MYC), as well as their efficacy in accelerating skin wound healing, were investigated and compared with those of hWJ-MSC derived from plate cultres (2D), using in vivo and in vitro experiments. hWJ-MSC attached to and proliferated on gelatin microbeads in 3D cultures reaching a maximum of 1.1-1.30×10(7) cells on 0.5 g of microbeads by days 8-14; in contrast, hWJ-MSC derived from 2D cultures reached a maximum of 6.5 -11.5×10(5) cells per well in a 24-well plate by days 6-10. hWJ-MSC derived by 3D culture incorporated significantly more EdU (P<0.05) and had a significantly higher proliferation index (P<0.05) than those derived from 2D culture. Immunofluorescence staining, real-time PCR, flow cytometry analysis, and multipotency assays showed that hWJ-MSC derived from 3D culture retained MSC surface markers and multipotency potential similar to 2D culture-derived cells. 3D culture-derived hWJ-MSC also retained the expression of core transcription factors at levels comparable to their 2D culture counterparts. Direct injection of hWJ-MSC derived from 3D or 2D cultures into animals exhibited similar efficacy in enhancing skin wound healing. Thus, hWJ-MSC can be expanded markedly in gelatin microbeads, while retaining MSC surface marker expression, multipotent differential potential, and expression of core transcription factors. These cells also efficiently enhanced skin wound healing in vivo, in a manner comparable to that of hWJ-MSC obtained from 2D culture.

Identification and Successful Negotiation of a Metabolic Checkpoint in Direct Neuronal Reprogramming.

PubMed

Gascón, Sergio; Murenu, Elisa; Masserdotti, Giacomo; Ortega, Felipe; Russo, Gianluca L; Petrik, David; Deshpande, Aditi; Heinrich, Christophe; Karow, Marisa; Robertson, Stephen P; Schroeder, Timm; Beckers, Johannes; Irmler, Martin; Berndt, Carsten; Angeli, José P Friedmann; Conrad, Marcus; Berninger, Benedikt; Götz, Magdalena

2016-03-03

Despite the widespread interest in direct neuronal reprogramming, the mechanisms underpinning fate conversion remain largely unknown. Our study revealed a critical time point after which cells either successfully convert into neurons or succumb to cell death. Co-transduction with Bcl-2 greatly improved negotiation of this critical point by faster neuronal differentiation. Surprisingly, mutants with reduced or no affinity for Bax demonstrated that Bcl-2 exerts this effect by an apoptosis-independent mechanism. Consistent with a caspase-independent role, ferroptosis inhibitors potently increased neuronal reprogramming by inhibiting lipid peroxidation occurring during fate conversion. Genome-wide expression analysis confirmed that treatments promoting neuronal reprogramming elicit an anti-oxidative stress response. Importantly, co-expression of Bcl-2 and anti-oxidative treatments leads to an unprecedented improvement in glial-to-neuron conversion after traumatic brain injury in vivo, underscoring the relevance of these pathways in cellular reprograming irrespective of cell type in vitro and in vivo. Copyright © 2016 Elsevier Inc. All rights reserved.

Evolution and expression analysis of the grape (Vitis vinifera L.) WRKY gene family.

PubMed

Guo, Chunlei; Guo, Rongrong; Xu, Xiaozhao; Gao, Min; Li, Xiaoqin; Song, Junyang; Zheng, Yi; Wang, Xiping

2014-04-01

WRKY proteins comprise a large family of transcription factors that play important roles in plant defence regulatory networks, including responses to various biotic and abiotic stresses. To date, no large-scale study of WRKY genes has been undertaken in grape (Vitis vinifera L.). In this study, a total of 59 putative grape WRKY genes (VvWRKY) were identified and renamed on the basis of their respective chromosome distribution. A multiple sequence alignment analysis using all predicted grape WRKY genes coding sequences, together with those from Arabidopsis thaliana and tomato (Solanum lycopersicum), indicated that the 59 VvWRKY genes can be classified into three main groups (I-III). An evaluation of the duplication events suggested that several WRKY genes arose before the divergence of the grape and Arabidopsis lineages. Moreover, expression profiles derived from semiquantitative PCR and real-time quantitative PCR analyses showed distinct expression patterns in various tissues and in response to different treatments. Four VvWRKY genes showed a significantly higher expression in roots or leaves, 55 responded to varying degrees to at least one abiotic stress treatment, and the expression of 38 were altered following powdery mildew (Erysiphe necator) infection. Most VvWRKY genes were downregulated in response to abscisic acid or salicylic acid treatments, while the expression of a subset was upregulated by methyl jasmonate or ethylene treatments.

Evolution and expression analysis of the grape (Vitis vinifera L.) WRKY gene family

PubMed Central

Guo, Chunlei; Guo, Rongrong; Wang, Xiping

2014-01-01

WRKY proteins comprise a large family of transcription factors that play important roles in plant defence regulatory networks, including responses to various biotic and abiotic stresses. To date, no large-scale study of WRKY genes has been undertaken in grape (Vitis vinifera L.). In this study, a total of 59 putative grape WRKY genes (VvWRKY) were identified and renamed on the basis of their respective chromosome distribution. A multiple sequence alignment analysis using all predicted grape WRKY genes coding sequences, together with those from Arabidopsis thaliana and tomato (Solanum lycopersicum), indicated that the 59 VvWRKY genes can be classified into three main groups (I–III). An evaluation of the duplication events suggested that several WRKY genes arose before the divergence of the grape and Arabidopsis lineages. Moreover, expression profiles derived from semiquantitative PCR and real-time quantitative PCR analyses showed distinct expression patterns in various tissues and in response to different treatments. Four VvWRKY genes showed a significantly higher expression in roots or leaves, 55 responded to varying degrees to at least one abiotic stress treatment, and the expression of 38 were altered following powdery mildew (Erysiphe necator) infection. Most VvWRKY genes were downregulated in response to abscisic acid or salicylic acid treatments, while the expression of a subset was upregulated by methyl jasmonate or ethylene treatments. PMID:24510937

Large-scale protein-protein interaction analysis in Arabidopsis mesophyll protoplasts by split firefly luciferase complementation.

PubMed

Li, Jian-Feng; Bush, Jenifer; Xiong, Yan; Li, Lei; McCormack, Matthew

2011-01-01

Protein-protein interactions (PPIs) constitute the regulatory network that coordinates diverse cellular functions. There are growing needs in plant research for creating protein interaction maps behind complex cellular processes and at a systems biology level. However, only a few approaches have been successfully used for large-scale surveys of PPIs in plants, each having advantages and disadvantages. Here we present split firefly luciferase complementation (SFLC) as a highly sensitive and noninvasive technique for in planta PPI investigation. In this assay, the separate halves of a firefly luciferase can come into close proximity and transiently restore its catalytic activity only when their fusion partners, namely the two proteins of interest, interact with each other. This assay was conferred with quantitativeness and high throughput potential when the Arabidopsis mesophyll protoplast system and a microplate luminometer were employed for protein expression and luciferase measurement, respectively. Using the SFLC assay, we could monitor the dynamics of rapamycin-induced and ascomycin-disrupted interaction between Arabidopsis FRB and human FKBP proteins in a near real-time manner. As a proof of concept for large-scale PPI survey, we further applied the SFLC assay to testing 132 binary PPIs among 8 auxin response factors (ARFs) and 12 Aux/IAA proteins from Arabidopsis. Our results demonstrated that the SFLC assay is ideal for in vivo quantitative PPI analysis in plant cells and is particularly powerful for large-scale binary PPI screens.

Dynamic genome wide expression profiling of Drosophila head development reveals a novel role of Hunchback in retinal glia cell development and blood-brain barrier integrity

PubMed Central

Torres-Oliva, Montserrat; Schneider, Julia; Wiegleb, Gordon

2018-01-01

Drosophila melanogaster head development represents a valuable process to study the developmental control of various organs, such as the antennae, the dorsal ocelli and the compound eyes from a common precursor, the eye-antennal imaginal disc. While the gene regulatory network underlying compound eye development has been extensively studied, the key transcription factors regulating the formation of other head structures from the same imaginal disc are largely unknown. We obtained the developmental transcriptome of the eye-antennal discs covering late patterning processes at the late 2nd larval instar stage to the onset and progression of differentiation at the end of larval development. We revealed the expression profiles of all genes expressed during eye-antennal disc development and we determined temporally co-expressed genes by hierarchical clustering. Since co-expressed genes may be regulated by common transcriptional regulators, we combined our transcriptome dataset with publicly available ChIP-seq data to identify central transcription factors that co-regulate genes during head development. Besides the identification of already known and well-described transcription factors, we show that the transcription factor Hunchback (Hb) regulates a significant number of genes that are expressed during late differentiation stages. We confirm that hb is expressed in two polyploid subperineurial glia cells (carpet cells) and a thorough functional analysis shows that loss of Hb function results in a loss of carpet cells in the eye-antennal disc. Additionally, we provide for the first time functional data indicating that carpet cells are an integral part of the blood-brain barrier. Eventually, we combined our expression data with a de novo Hb motif search to reveal stage specific putative target genes of which we find a significant number indeed expressed in carpet cells. PMID:29360820

Intense laser beams; Proceedings of the Meeting, Los Angeles, CA, Jan. 23, 24, 1992

NASA Technical Reports Server (NTRS)

Wade, Richard C. (Editor); Ulrich, Peter B. (Editor)

1992-01-01

Various papers on intense laser beams are presented. Individual topics addressed include: novel methods of copper vapor laser excitation, UCLA IR FEL, lasing characteristics of a large-bore copper vapor laser (CVL), copper density measurement of a large-bore CVL, high-power XeCl excimer laser, solid state direct-drive circuit for pumping gas lasers, united energy model for FELs, intensity and frequency instabilities in double-mode CO2 lasers, comparison of output power stabilities of CO and CO2 lasers, increasing efficiency of sealed-off CO lasers, thermal effects in singlet delta oxygen generation, optical extraction from the chemical oxygen-iodine laser medium, generation and laser diagnostic analysis of bismuth fluoride. Also discussed are: high-Q resonator design for an HF overtone chemical lasers, improved coatings for HF overtone lasers, scaled atmospheric blooming experiment, simulation on producing conjugate field using deformable mirrors, paraxial theory of amplitude correction, potential capabilities of adaptive optical systems in the atmosphere, power beaming research at NASA, system evaluations of laser power beaming options, performance projections for laser beam power to space, independent assessment of laser power beaming options, removal of atmospheric CFCs by lasers, efficiency of vaporization cutting by CVL.

ISM Properties of a Massive Dusty Star-forming Galaxy Discovered at z ˜ 7

NASA Astrophysics Data System (ADS)

Strandet, M. L.; Weiss, A.; De Breuck, C.; Marrone, D. P.; Vieira, J. D.; Aravena, M.; Ashby, M. L. N.; Béthermin, M.; Bothwell, M. S.; Bradford, C. M.; Carlstrom, J. E.; Chapman, S. C.; Cunningham, D. J. M.; Chen, Chian-Chou; Fassnacht, C. D.; Gonzalez, A. H.; Greve, T. R.; Gullberg, B.; Hayward, C. C.; Hezaveh, Y.; Litke, K.; Ma, J.; Malkan, M.; Menten, K. M.; Miller, T.; Murphy, E. J.; Narayanan, D.; Phadke, K. A.; Rotermund, K. M.; Spilker, J. S.; Sreevani, J.

2017-06-01

We report the discovery and constrain the physical conditions of the interstellar medium of the highest-redshift millimeter-selected dusty star-forming galaxy to date, SPT-S J031132-5823.4 (hereafter SPT0311-58), at z=6.900+/- 0.002. SPT0311-58 was discovered via its 1.4 mm thermal dust continuum emission in the South Pole Telescope (SPT)-SZ survey. The spectroscopic redshift was determined through an Atacama Large Millimeter/submillimeter Array 3 mm frequency scan that detected CO(6-5), CO(7-6), and [{{C}} {{I}}](2-1), and subsequently was confirmed by detections of CO(3-2) with the Australia Telescope Compact Array and [{{C}} {{II}}] with APEX. We constrain the properties of the ISM in SPT0311-58 with a radiative transfer analysis of the dust continuum photometry and the CO and [{{C}} {{I}}] line emission. This allows us to determine the gas content without ad hoc assumptions about gas mass scaling factors. SPT0311-58 is extremely massive, with an intrinsic gas mass of {M}{gas}=3.3+/- 1.9× {10}11 {M}⊙ . Its large mass and intense star formation is very rare for a source well into the epoch of reionization.

Strain-resolved Metatranscriptomic Analysis Reveals Unexpectedly Diverse Heterotrophic and Lithoautotrophic Microbial Metabolism in Naturally Reduced Aquifer Sediments

NASA Astrophysics Data System (ADS)

Beller, H. R.; Jewell, T. N. M.; Karaoz, U.; Bill, M.; Chakraborty, R.; Brodie, E.; Williams, K. H.

2016-12-01

In this study, we sought to better understand how natural organic matter fuels microbial communities in the anoxic subsurface at the Rifle (CO) site. We conducted a 20-day microcosm experiment with naturally reduced zone (NRZ) sediments and collected samples every 5 days for omics (metagenome and metatranscriptome) and geochemical measurements. No electron donors were added other than the NRZ sediment, which is enriched in buried woody plant material. The microcosms were constructed and incubated under anaerobic conditions in serum bottles with a N2 headspace. Biogeochemical measurements indicated that the decomposition of native organic matter occurred in different phases, including mineralization of dissolved organic carbon (DOC) to CO2 during the first week of incubation, followed by a pulse of acetogenesis that dominated carbon flux after 2 weeks. The depletion of DOC over time was strongly correlated with increases in expression of many genes associated with heterotrophy (e.g., amino acid, fatty acid, and carbohydrate metabolism) belonging to a Hydrogenophaga strain that accounted for a relatively large percentage ( 8%) of the metatranscriptome. This Hydrogenophaga strain also expressed genes indicative of chemolithoautotrophy, including CO2 fixation (RubisCO), H2 oxidation, S-compound oxidation, and denitrification. The pulse of acetogenesis appears to have been collectively catalyzed by a number of different organisms and metabolisms, most prominently pyruvate:ferredoxin oxidoreductase. Unexpected genes were identified among the most highly expressed (>98th percentile) transcripts, including acetone carboxylase and cell wall-associated hydrolases, some of which are known to act on peptidoglycan. Many of the most highly expressed hydrolases belonged to a Ca. Bathyarchaeota strain and may have been associated with scavenging of bacterial biomass. Overall, observed metabolism ranged far beyond the expected fermentation of plant-derived organic matter.

Does network topology influence systemic risk contribution? A perspective from the industry indices in Chinese stock market.

PubMed

Long, Haiming; Zhang, Ji; Tang, Nengyu

2017-01-01

This study considers the effect of an industry's network topology on its systemic risk contribution to the stock market using data from the CSI 300 two-tier industry indices from the Chinese stock market. We first measure industry's conditional-value-at-risk (CoVaR) and the systemic risk contribution (ΔCoVaR) using the fitted time-varying t-copula function. The network of the stock industry is established based on dynamic conditional correlations with the minimum spanning tree. Then, we investigate the connection characteristics and topology of the network. Finally, we utilize seemingly unrelated regression estimation (SUR) of panel data to analyze the relationship between network topology of the stock industry and the industry's systemic risk contribution. The results show that the systemic risk contribution of small-scale industries such as real estate, food and beverage, software services, and durable goods and clothing, is higher than that of large-scale industries, such as banking, insurance and energy. Industries with large betweenness centrality, closeness centrality, and clustering coefficient and small node occupancy layer are associated with greater systemic risk contribution. In addition, further analysis using a threshold model confirms that the results are robust.

Genome-wide identification and functional prediction of nitrogen-responsive intergenic and intronic long non-coding RNAs in maize (Zea mays L.).

PubMed

Lv, Yuanda; Liang, Zhikai; Ge, Min; Qi, Weicong; Zhang, Tifu; Lin, Feng; Peng, Zhaohua; Zhao, Han

2016-05-11

Nitrogen (N) is an essential and often limiting nutrient to plant growth and development. Previous studies have shown that the mRNA expressions of numerous genes are regulated by nitrogen supplies; however, little is known about the expressed non-coding elements, for example long non-coding RNAs (lncRNAs) that control the response of maize (Zea mays L.) to nitrogen. LncRNAs are a class of non-coding RNAs larger than 200 bp, which have emerged as key regulators in gene expression. In this study, we surveyed the intergenic/intronic lncRNAs in maize B73 leaves at the V7 stage under conditions of N-deficiency and N-sufficiency using ribosomal RNA depletion and ultra-deep total RNA sequencing approaches. By integration with mRNA expression profiles and physiological evaluations, 7245 lncRNAs and 637 nitrogen-responsive lncRNAs were identified that exhibited unique expression patterns. Co-expression network analysis showed that the nitrogen-responsive lncRNAs were enriched mainly in one of the three co-expressed modules. The genes in the enriched module are mainly involved in NADH dehydrogenase activity, oxidative phosphorylation and the nitrogen compounds metabolic process. We identified a large number of lncRNAs in maize and illustrated their potential regulatory roles in response to N stress. The results lay the foundation for further in-depth understanding of the molecular mechanisms of lncRNAs' role in response to nitrogen stresses.

Combining CO2 sequestration and CH4 production by means of guest exchange in a gas hydrate reservoir: two pilot scale experiments

NASA Astrophysics Data System (ADS)

Heeschen, Katja U.; Spangenberg, Erik; Schicks, Judith M.; Deusner, Christian; Priegnitz, Mike; Strauch, Bettina; Bigalke, Nikolaus; Luzi-Helbing, Manja; Kossel, Elke; Haeckel, Matthias; Wang, Yi

2017-04-01

Methane (CH4) hydrates are considered as a player in the field of energy supply and - if applied as such - as a possible sink for the greenhouse gas carbon dioxide (CO2). Next to the more conventional production methods depressurization and thermal stimulation, an extraction of CH4 by means of CO2 injection is investigated. The method is based on the chemical potential gradient between the CH4 hydrate phase and the injected CO2 phase. Results from small-scale laboratory experiments on the replacement method indicate recovery ratios of up to 66% CH4 but also encounter major discrepancies in conversion rates. So far it has not been demonstrated with certainty that the process rates are sufficient for an energy and cost effective production of CH4 with a concurrent sequestration of CO2. In a co-operation of GFZ and GEOMAR we used LARS (Large Scale Reservoir Simulator) to investigate the CO2-CH4-replacement method combined with thermal stimulation. LARS accommodates a sample volume of 210 l and allows for the simulation of in situ conditions typically found in gas hydrate reservoirs. Based on the sample size, diverse transport mechanisms could be simulated, which are assumed to significantly alter process yields. Temperature and pressure data complemented by a high resolution electrical resistivity tomography (ERT), gas chromatography, and flow measurements serve to interpret the experiments. In two experiments 50 kg heated CO2 was injected into sediments with CH4 hydrate saturations of 50%. While in the first experiment the CO2 was injected discontinuously in a so called "huff'n puff" manner, the second experiment saw a continuous injection. Conditions within LARS were set to 13 MPa and 8˚ C, which allow for stability of pure CO2 and CH4 hydrates as well as mixed hydrates. The CO2 was heated and entered the sediment sample with temperatures of approximately 30˚ C. In this presentation we will discuss the results from the large-scale experiments and compare them with data from small-scale experiments.

A transgenic plant cell-suspension system for expression of epitopes on chimeric Bamboo mosaic virus particles.

PubMed

Muthamilselvan, Thangarasu; Lee, Chin-Wei; Cho, Yu-Hsin; Wu, Feng-Chao; Hu, Chung-Chi; Liang, Yu-Chuan; Lin, Na-Sheng; Hsu, Yau-Heiu

2016-01-01

We describe a novel strategy to produce vaccine antigens using a plant cell-suspension culture system in lieu of the conventional bacterial or animal cell-culture systems. We generated transgenic cell-suspension cultures from Nicotiana benthamiana leaves carrying wild-type or chimeric Bamboo mosaic virus (BaMV) expression constructs encoding the viral protein 1 (VP1) epitope of foot-and-mouth disease virus (FMDV). Antigens accumulated to high levels in BdT38 and BdT19 transgenic cell lines co-expressing silencing suppressor protein P38 or P19. BaMV chimeric virus particles (CVPs) were subsequently purified from the respective cell lines (1.5 and 2.1 mg CVPs/20 g fresh weight of suspended biomass, respectively), and the resulting CVPs displayed VP1 epitope on the surfaces. Guinea pigs vaccinated with purified CVPs produced humoral antibodies. This study represents an important advance in the large-scale production of immunopeptide vaccines in a cost-effective manner using a plant cell-suspension culture system. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Grid-Enabled Quantitative Analysis of Breast Cancer

DTIC Science & Technology

2010-10-01

large-scale, multi-modality computerized image analysis . The central hypothesis of this research is that large-scale image analysis for breast cancer...research, we designed a pilot study utilizing large scale parallel Grid computing harnessing nationwide infrastructure for medical image analysis . Also

VTCdb: a gene co-expression database for the crop species Vitis vinifera (grapevine).

PubMed

Wong, Darren C J; Sweetman, Crystal; Drew, Damian P; Ford, Christopher M

2013-12-16

Gene expression datasets in model plants such as Arabidopsis have contributed to our understanding of gene function and how a single underlying biological process can be governed by a diverse network of genes. The accumulation of publicly available microarray data encompassing a wide range of biological and environmental conditions has enabled the development of additional capabilities including gene co-expression analysis (GCA). GCA is based on the understanding that genes encoding proteins involved in similar and/or related biological processes may exhibit comparable expression patterns over a range of experimental conditions, developmental stages and tissues. We present an open access database for the investigation of gene co-expression networks within the cultivated grapevine, Vitis vinifera. The new gene co-expression database, VTCdb (http://vtcdb.adelaide.edu.au/Home.aspx), offers an online platform for transcriptional regulatory inference in the cultivated grapevine. Using condition-independent and condition-dependent approaches, grapevine co-expression networks were constructed using the latest publicly available microarray datasets from diverse experimental series, utilising the Affymetrix Vitis vinifera GeneChip (16 K) and the NimbleGen Grape Whole-genome microarray chip (29 K), thus making it possible to profile approximately 29,000 genes (95% of the predicted grapevine transcriptome). Applications available with the online platform include the use of gene names, probesets, modules or biological processes to query the co-expression networks, with the option to choose between Affymetrix or Nimblegen datasets and between multiple co-expression measures. Alternatively, the user can browse existing network modules using interactive network visualisation and analysis via CytoscapeWeb. To demonstrate the utility of the database, we present examples from three fundamental biological processes (berry development, photosynthesis and flavonoid biosynthesis) whereby the recovered sub-networks reconfirm established plant gene functions and also identify novel associations. Together, we present valuable insights into grapevine transcriptional regulation by developing network models applicable to researchers in their prioritisation of gene candidates, for on-going study of biological processes related to grapevine development, metabolism and stress responses.

Large-scale multiplex absolute protein quantification of drug-metabolizing enzymes and transporters in human intestine, liver, and kidney microsomes by SWATH-MS: Comparison with MRM/SRM and HR-MRM/PRM.

PubMed

Nakamura, Kenji; Hirayama-Kurogi, Mio; Ito, Shingo; Kuno, Takuya; Yoneyama, Toshihiro; Obuchi, Wataru; Terasaki, Tetsuya; Ohtsuki, Sumio

2016-08-01

The purpose of the present study was to examine simultaneously the absolute protein amounts of 152 membrane and membrane-associated proteins, including 30 metabolizing enzymes and 107 transporters, in pooled microsomal fractions of human liver, kidney, and intestine by means of SWATH-MS with stable isotope-labeled internal standard peptides, and to compare the results with those obtained by MRM/SRM and high resolution (HR)-MRM/PRM. The protein expression levels of 27 metabolizing enzymes, 54 transporters, and six other membrane proteins were quantitated by SWATH-MS; other targets were below the lower limits of quantitation. Most of the values determined by SWATH-MS differed by less than 50% from those obtained by MRM/SRM or HR-MRM/PRM. Various metabolizing enzymes were expressed in liver microsomes more abundantly than in other microsomes. Ten, 13, and eight transporters listed as important for drugs by International Transporter Consortium were quantified in liver, kidney, and intestinal microsomes, respectively. Our results indicate that SWATH-MS enables large-scale multiplex absolute protein quantification while retaining similar quantitative capability to MRM/SRM or HR-MRM/PRM. SWATH-MS is expected to be useful methodology in the context of drug development for elucidating the molecular mechanisms of drug absorption, metabolism, and excretion in the human body based on protein profile information. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High yield bacterial expression, purification and characterisation of bioactive Human Tousled-like Kinase 1B involved in cancer.

PubMed

Bhoir, Siddhant; Shaik, Althaf; Thiruvenkatam, Vijay; Kirubakaran, Sivapriya

2018-03-19

Human Tousled-like kinases (TLKs) are highly conserved serine/threonine protein kinases responsible for cell proliferation, DNA repair, and genome surveillance. Their possible involvement in cancer via efficient DNA repair mechanisms have made them clinically relevant molecular targets for anticancer therapy. Innovative approaches in chemical biology have played a key role in validating the importance of kinases as molecular targets. However, the detailed understanding of the protein structure and the mechanisms of protein-drug interaction through biochemical and biophysical techniques demands a method for the production of an active protein of exceptional stability and purity on a large scale. We have designed a bacterial expression system to express and purify biologically active, wild-type Human Tousled-like Kinase 1B (hTLK1B) by co-expression with the protein phosphatase from bacteriophage λ. We have obtained remarkably high amounts of the soluble and homogeneously dephosphorylated form of biologically active hTLK1B with our unique, custom-built vector design strategy. The recombinant hTLK1B can be used for the structural studies and may further facilitate the development of new TLK inhibitors for anti-cancer therapy using a structure-based drug design approach.

The Reliability of the OWLS Written Expression Scale with ESL Kindergarten Students

ERIC Educational Resources Information Center

Harrison, Gina L.; Ogle, Keira C.; Keilty, Megan

2011-01-01

A reliability analysis was conducted on the Written Expression Scale from the Oral and Written Language Scales, (OWLS, Carrow-Woolfolk, 1996), with 68 ESL and 56 non-ESL kindergarten students. Interrater and internal consistency estimates for the Written Expression Scale were examined separately for each language group. Despite lower oral English…

Climatic effects of large-scale deforestation in Earth System Models

NASA Astrophysics Data System (ADS)

Brovkin, V.; Boysen, L.; Pongratz, J.

2017-12-01

Processes in terrestrial ecosystems, to a large extent, are controlled by climate and CO2 concentration. In turn, geographical distribution of vegetation cover strongly affects heat, moisture, and momentum fluxes between land surface and atmosphere (biogeophysical effects). Anthropogenic land use and land cover changes (LULCC) are now included into Earth System Models (ESMs) in the form of historical and hypothetical future scenarios as a forcing in the Coupled Model Intercomparison project, phase 6 (CMIP6). A propagation of climatic effects from land to the ocean in ESMs allows to investigate a global climate response to LULCC in addition to analysis of local effects over deforested land. One complication in the analysis of global climatic effects of historical and future LULCC scenarios is their relatively small amplitude. To increase the signal-to-noise ratio, the Land Use Model Intercomparison Project (LUMIP) suggested an idealized deforestation simulation following a prototype of 1%-CO2 increase experiment commonly used in CMIPs. The idealized experiment allows to investigate - in a harmonized way across models - a response of land surface biophysics and climate to a large-scale deforestation of 20 million km2 distributed over the most forested parts of globe. The forest is removed linearly over a period of 50 years, with an additional 30 years with no specified change in forest cover. Boundary conditions such as CO2 concentration and other forcings are kept at the pre-industrial level. We will present results of idealized deforestation experiments and other sensitivity runs with the CMIP6-version of MPI-ESM, which will be part of the later multi-model comparison. A special focus will be put on less well investigated aspects of LULCC that the idealized setup is particularly well suited for studying, such as non-linearities of the model response to the deforestation forcing and detectability of the signal over time.

Spatiotemporal dynamics of carbon dioxide and methane fluxes from agricultural and restored wetlands in the California Delta

NASA Astrophysics Data System (ADS)

Hatala, Jaclyn Anne

The Sacramento-San Joaquin Delta in California was drained for agriculture and human settlement over a century ago, resulting in extreme rates of soil subsidence and release of CO2 to the atmosphere from peat oxidation. Because of this century-long ecosystem carbon imbalance where heterotrophic respiration exceeded net primary productivity, most of the land surface in the Delta is now up to 8 meters below sea level. To potentially reverse this trend of chronic carbon loss from Delta ecosystems, land managers have begun converting drained lands back to flooded ecosystems, but at the cost of increased production of CH4, a much more potent greenhouse gas than CO2. To evaluate the impacts of inundation on the biosphere-atmophere exchange of CO2 and CH4 in the Delta, I first measured and analyzed net fluxes of CO2 and CH4 for two continuous years with the eddy covariance technique in a drained peatland pasture and a recently re-flooded rice paddy. This analysis demonstrated that the drained pasture was a consistent large source of CO2 and small source of CH 4, whereas the rice paddy was a mild sink for CO2 and a mild source of CH4. However more importantly, this first analysis revealed nuanced complexities for measuring and interpreting patterns in CO2 and CH4 fluxes through time and space. CO2 and CH4 fluxes are inextricably linked in flooded ecosystems, as plant carbon serves as the primary substrate for the production of CH4 and wetland plants also provide the primary transport pathway of CH4 flux to the atmosphere. At the spatially homogeneous rice paddy during the summer growing season, I investigated rapid temporal coupling between CO2 and CH4 fluxes. Through wavelet Granger-causality analysis, I demonstrated that daily fluctuations in growing season gross ecosystem productivity (photosynthesis) exert a stronger control than temperature on the diurnal pattern in CH4 flux from rice. At a spatially heterogeneous restored wetland site, I analyzed the spatial coupling between net CO2 and CH4 fluxes by characterizing two-dimensional patterns of emergent vegetation within eddy covariance flux footprints. I combined net CO2 and CH4 fluxes from three eddy flux towers with high-resolution remote sensing imagery classified for emergent vegetation and an analytical 2-D flux footprint model to assess the impact of vegetation fractal pattern and abundance on the measured flux. Both emergent vegetation abundance and fractal complexity are important metrics for constraining variability within CO2 and CH4 flux in this complex landscape. Scaling between carbon flux measurements at individual sites and regional scales depends on the connection to remote sensing metrics that can be broadly applied. In the final chapter of this dissertation, I analyzed a long term dataset of hyperspectral ground reflectance measurements collected within the flux tower footprints of three structurally similar yet functionally diverse ecosystems: an annual grassland, a degraded pepperweed pasture, and a rice paddy. The normalized difference vegetation index (NDVI) was highly correlated with landscape-scale photosynthesis across all sites, however this work also revealed new potential spectral indices with high correlation to both net and partitioned CO2 fluxes. This analysis within this dissertation serves as a framework for considering the impacts of temporal and spatial heterogeneity on measured landscape-scale fluxes of CO2 and CH4. Scaling measurements through time and space is especially critical for interpreting fluxes of trace gases with a high degree of temporal heterogeneity, like CH4 and N 2O, from landscapes that have a high degree of spatial heterogeneity, like wetlands. This work articulates a strong mechanistic connection between CO2 and CH4 fluxes in wetland ecosystems, and provides important management considerations for implementing and monitoring inundated land-use conversion as an effective carbon management strategy in the California Delta.

Tissue and cell-type co-expression networks of transcription factors and wood component genes in Populus trichocarpa.

PubMed

Shi, Rui; Wang, Jack P; Lin, Ying-Chung; Li, Quanzi; Sun, Ying-Hsuan; Chen, Hao; Sederoff, Ronald R; Chiang, Vincent L

2017-05-01

Co-expression networks based on transcriptomes of Populus trichocarpa major tissues and specific cell types suggest redundant control of cell wall component biosynthetic genes by transcription factors in wood formation. We analyzed the transcriptomes of five tissues (xylem, phloem, shoot, leaf, and root) and two wood forming cell types (fiber and vessel) of Populus trichocarpa to assemble gene co-expression subnetworks associated with wood formation. We identified 165 transcription factors (TFs) that showed xylem-, fiber-, and vessel-specific expression. Of these 165 TFs, 101 co-expressed (correlation coefficient, r > 0.7) with the 45 secondary cell wall cellulose, hemicellulose, and lignin biosynthetic genes. Each cell wall component gene co-expressed on average with 34 TFs, suggesting redundant control of the cell wall component gene expression. Co-expression analysis showed that the 101 TFs and the 45 cell wall component genes each has two distinct groups (groups 1 and 2), based on their co-expression patterns. The group 1 TFs (44 members) are predominantly xylem and fiber specific, and are all highly positively co-expressed with the group 1 cell wall component genes (30 members), suggesting their roles as major wood formation regulators. Group 1 TFs include a lateral organ boundary domain gene (LBD) that has the highest number of positively correlated cell wall component genes (36) and TFs (47). The group 2 TFs have 57 members, including 14 vessel-specific TFs, and are generally less correlated with the cell wall component genes. An exception is a vessel-specific basic helix-loop-helix (bHLH) gene that negatively correlates with 20 cell wall component genes, and may function as a key transcriptional suppressor. The co-expression networks revealed here suggest a well-structured transcriptional homeostasis for cell wall component biosynthesis during wood formation.