Advances in Omics and Bioinformatics Tools for Systems Analyses of Plant Functions

PubMed Central

Mochida, Keiichi; Shinozaki, Kazuo

2011-01-01

Omics and bioinformatics are essential to understanding the molecular systems that underlie various plant functions. Recent game-changing sequencing technologies have revitalized sequencing approaches in genomics and have produced opportunities for various emerging analytical applications. Driven by technological advances, several new omics layers such as the interactome, epigenome and hormonome have emerged. Furthermore, in several plant species, the development of omics resources has progressed to address particular biological properties of individual species. Integration of knowledge from omics-based research is an emerging issue as researchers seek to identify significance, gain biological insights and promote translational research. From these perspectives, we provide this review of the emerging aspects of plant systems research based on omics and bioinformatics analyses together with their associated resources and technological advances. PMID:22156726

Optimal network alignment with graphlet degree vectors.

PubMed

Milenković, Tijana; Ng, Weng Leong; Hayes, Wayne; Przulj, Natasa

2010-06-30

Important biological information is encoded in the topology of biological networks. Comparative analyses of biological networks are proving to be valuable, as they can lead to transfer of knowledge between species and give deeper insights into biological function, disease, and evolution. We introduce a new method that uses the Hungarian algorithm to produce optimal global alignment between two networks using any cost function. We design a cost function based solely on network topology and use it in our network alignment. Our method can be applied to any two networks, not just biological ones, since it is based only on network topology. We use our new method to align protein-protein interaction networks of two eukaryotic species and demonstrate that our alignment exposes large and topologically complex regions of network similarity. At the same time, our alignment is biologically valid, since many of the aligned protein pairs perform the same biological function. From the alignment, we predict function of yet unannotated proteins, many of which we validate in the literature. Also, we apply our method to find topological similarities between metabolic networks of different species and build phylogenetic trees based on our network alignment score. The phylogenetic trees obtained in this way bear a striking resemblance to the ones obtained by sequence alignments. Our method detects topologically similar regions in large networks that are statistically significant. It does this independent of protein sequence or any other information external to network topology.

B. F. Skinner and G. H. Mead: on biological science and social science.

PubMed Central

Blackman, D E

1991-01-01

Skinner's contributions to psychology provide a unique bridge between psychology conceptualized as a biological science and psychology conceptualized as a social science. Skinner focused on behavior as a naturally occurring biological phenomenon of interest in its own right, functionally related to surrounding events and, in particular (like phylogenesis), subject to selection by its consequences. This essentially biological orientation was further enhanced by Skinner's emphasis on the empirical foundations provided by laboratory-based experimental analyses of behavior, often with nonhuman subjects. Skinner's theoretical writings, however, also have affinity with the traditions of constructionist social science. The verbal behavior of humans is said to be subject, like other behavior, to functional analyses in terms of its environment, in this case its social context. Verbal behavior in turn makes it possible for us to relate to private events, a process that ultimately allows for the development of consciousness, which is thus said to be a social product. Such ideas make contact with aspects of G. H. Mead's social behaviorism and, perhaps of more contemporary impact in psychology, L. Vygotsky's general genetic law of cultural development. Failure to articulate both the biological and the social science aspects of Skinner's theoretical approach to psychology does a disservice to his unique contribution to a discipline that remains fragmented between two intellectual traditions. PMID:2037828

Clinical, Functional, and Biological Correlates of Cognitive Dimensions in Major Depressive Disorder – Rationale, Design, and Characteristics of the Cognitive Function and Mood Study (CoFaM-Study)

PubMed Central

Baune, Bernhard T.; Air, Tracy

2016-01-01

Cross-sectional and longitudinal studies exploring clinical, functional, and biological correlates of major depressive disorder are frequent. In this type of research, depression is most commonly defined as a categorical diagnosis based on studies using diagnostic instruments. Given the phenotypic and biological heterogeneity of depression, we chose to focus the phenotypic assessments on three cognitive dimensions of depression including (a) cognitive performance, (b) emotion processing, and (c) social cognitive functioning. Hence, the overall aim of the study is to investigate the long-term clinical course of these cognitive dimensions in depression and its functional (psychosocial) correlates. We also aim to identify biological “genomic” correlates of these three cognitive dimensions of depression. To address the above overall aim, we created the Cognition and Mood Study (CoFaMS) with the key objective to investigate the clinical, functional, and biological correlates of cognitive dimensions of depression by employing a prospective study design and including a healthy control group. The study commenced in April 2015, including patients with a primary diagnosis of a major depressive episode of major depressive disorder or bipolar disorder according to DSM-IV-TR criteria. The assessments cover the three cognitive dimensions of depression (cognitive performance, emotion processing, and social cognition), cognitive function screening instrument, plus functional scales to assess general, work place, and psychosocial function, depression symptom scales, and clinical course of illness. Blood is collected for comprehensive genomic discovery analyses of biological correlates of cognitive dimensions of depression. The CoFaM-Study represents an innovative approach focusing on cognitive dimensions of depression and its functional and biological “genomic” correlates. The CoFaMS team welcomes collaborations with both national and international researchers. PMID:27616997

Clinical, Functional, and Biological Correlates of Cognitive Dimensions in Major Depressive Disorder - Rationale, Design, and Characteristics of the Cognitive Function and Mood Study (CoFaM-Study).

PubMed

Baune, Bernhard T; Air, Tracy

2016-01-01

Cross-sectional and longitudinal studies exploring clinical, functional, and biological correlates of major depressive disorder are frequent. In this type of research, depression is most commonly defined as a categorical diagnosis based on studies using diagnostic instruments. Given the phenotypic and biological heterogeneity of depression, we chose to focus the phenotypic assessments on three cognitive dimensions of depression including (a) cognitive performance, (b) emotion processing, and (c) social cognitive functioning. Hence, the overall aim of the study is to investigate the long-term clinical course of these cognitive dimensions in depression and its functional (psychosocial) correlates. We also aim to identify biological "genomic" correlates of these three cognitive dimensions of depression. To address the above overall aim, we created the Cognition and Mood Study (CoFaMS) with the key objective to investigate the clinical, functional, and biological correlates of cognitive dimensions of depression by employing a prospective study design and including a healthy control group. The study commenced in April 2015, including patients with a primary diagnosis of a major depressive episode of major depressive disorder or bipolar disorder according to DSM-IV-TR criteria. The assessments cover the three cognitive dimensions of depression (cognitive performance, emotion processing, and social cognition), cognitive function screening instrument, plus functional scales to assess general, work place, and psychosocial function, depression symptom scales, and clinical course of illness. Blood is collected for comprehensive genomic discovery analyses of biological correlates of cognitive dimensions of depression. The CoFaM-Study represents an innovative approach focusing on cognitive dimensions of depression and its functional and biological "genomic" correlates. The CoFaMS team welcomes collaborations with both national and international researchers.

IBIS integrated biological imaging system: electron micrograph image-processing software running on Unix workstations.

PubMed

Flifla, M J; Garreau, M; Rolland, J P; Coatrieux, J L; Thomas, D

1992-12-01

'IBIS' is a set of computer programs concerned with the processing of electron micrographs, with particular emphasis on the requirements for structural analyses of biological macromolecules. The software is written in FORTRAN 77 and runs on Unix workstations. A description of the various functions and the implementation mode is given. Some examples illustrate the user interface.

Identification of SNPs associated with muscle yield and quality traits using allelic-imbalance analysis analyses of pooled RNA-Seq samples in rainbow trout

USDA-ARS?s Scientific Manuscript database

Coding/functional SNPs change the biological function of a gene and, therefore, could serve as “large-effect” genetic markers. In this study, we used two bioinformatics pipelines, GATK and SAMtools, for discovering coding/functional SNPs with allelic-imbalances associated with total body weight, mus...

Integrative analyses of miRNA and proteomics identify potential biological pathways associated with onset of pulmonary fibrosis in the bleomycin rat model

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

Fukunaga, Satoki; Environmental Health Science Laboratory, Sumitomo Chemical Co., Ltd., 3-1-98 Kasugade-Naka, Konohana-ku, Osaka 554-8558; Kakehashi, Anna

To determine miRNAs and their predicted target proteins regulatory networks which are potentially involved in onset of pulmonary fibrosis in the bleomycin rat model, we conducted integrative miRNA microarray and iTRAQ-coupled LC-MS/MS proteomic analyses, and evaluated the significance of altered biological functions and pathways. We observed that alterations of miRNAs and proteins are associated with the early phase of bleomycin-induced pulmonary fibrosis, and identified potential target pairs by using ingenuity pathway analysis. Using the data set of these alterations, it was demonstrated that those miRNAs, in association with their predicted target proteins, are potentially involved in canonical pathways reflective ofmore » initial epithelial injury and fibrogenic processes, and biofunctions related to induction of cellular development, movement, growth, and proliferation. Prediction of activated functions suggested that lung cells acquire proliferative, migratory, and invasive capabilities, and resistance to cell death especially in the very early phase of bleomycin-induced pulmonary fibrosis. The present study will provide new insights for understanding the molecular pathogenesis of idiopathic pulmonary fibrosis. - Highlights: • We analyzed bleomycin-induced pulmonary fibrosis in the rat. • Integrative analyses of miRNA microarray and proteomics were conducted. • We determined the alterations of miRNAs and their potential target proteins. • The alterations may control biological functions and pathways in pulmonary fibrosis. • Our result may provide new insights of pulmonary fibrosis.« less

DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures

PubMed Central

2013-01-01

Background The use of Gene Ontology (GO) data in protein analyses have largely contributed to the improved outcomes of these analyses. Several GO semantic similarity measures have been proposed in recent years and provide tools that allow the integration of biological knowledge embedded in the GO structure into different biological analyses. There is a need for a unified tool that provides the scientific community with the opportunity to explore these different GO similarity measure approaches and their biological applications. Results We have developed DaGO-Fun, an online tool available at http://web.cbio.uct.ac.za/ITGOM, which incorporates many different GO similarity measures for exploring, analyzing and comparing GO terms and proteins within the context of GO. It uses GO data and UniProt proteins with their GO annotations as provided by the Gene Ontology Annotation (GOA) project to precompute GO term information content (IC), enabling rapid response to user queries. Conclusions The DaGO-Fun online tool presents the advantage of integrating all the relevant IC-based GO similarity measures, including topology- and annotation-based approaches to facilitate effective exploration of these measures, thus enabling users to choose the most relevant approach for their application. Furthermore, this tool includes several biological applications related to GO semantic similarity scores, including the retrieval of genes based on their GO annotations, the clustering of functionally related genes within a set, and term enrichment analysis. PMID:24067102

Functional Abstraction as a Method to Discover Knowledge in Gene Ontologies

PubMed Central

Ultsch, Alfred; Lötsch, Jörn

2014-01-01

Computational analyses of functions of gene sets obtained in microarray analyses or by topical database searches are increasingly important in biology. To understand their functions, the sets are usually mapped to Gene Ontology knowledge bases by means of over-representation analysis (ORA). Its result represents the specific knowledge of the functionality of the gene set. However, the specific ontology typically consists of many terms and relationships, hindering the understanding of the ‘main story’. We developed a methodology to identify a comprehensibly small number of GO terms as “headlines” of the specific ontology allowing to understand all central aspects of the roles of the involved genes. The Functional Abstraction method finds a set of headlines that is specific enough to cover all details of a specific ontology and is abstract enough for human comprehension. This method exceeds the classical approaches at ORA abstraction and by focusing on information rather than decorrelation of GO terms, it directly targets human comprehension. Functional abstraction provides, with a maximum of certainty, information value, coverage and conciseness, a representation of the biological functions in a gene set plays a role. This is the necessary means to interpret complex Gene Ontology results thus strengthening the role of functional genomics in biomarker and drug discovery. PMID:24587272

Frontotemporal dementia: insights into the biological underpinnings of disease through gene co-expression network analysis.

PubMed

Ferrari, Raffaele; Forabosco, Paola; Vandrovcova, Jana; Botía, Juan A; Guelfi, Sebastian; Warren, Jason D; Momeni, Parastoo; Weale, Michael E; Ryten, Mina; Hardy, John

2016-02-24

In frontotemporal dementia (FTD) there is a critical lack in the understanding of biological and molecular mechanisms involved in disease pathogenesis. The heterogeneous genetic features associated with FTD suggest that multiple disease-mechanisms are likely to contribute to the development of this neurodegenerative condition. We here present a systems biology approach with the scope of i) shedding light on the biological processes potentially implicated in the pathogenesis of FTD and ii) identifying novel potential risk factors for FTD. We performed a gene co-expression network analysis of microarray expression data from 101 individuals without neurodegenerative diseases to explore regional-specific co-expression patterns in the frontal and temporal cortices for 12 genes (MAPT, GRN, CHMP2B, CTSC, HLA-DRA, TMEM106B, C9orf72, VCP, UBQLN2, OPTN, TARDBP and FUS) associated with FTD and we then carried out gene set enrichment and pathway analyses, and investigated known protein-protein interactors (PPIs) of FTD-genes products. Gene co-expression networks revealed that several FTD-genes (such as MAPT and GRN, CTSC and HLA-DRA, TMEM106B, and C9orf72, VCP, UBQLN2 and OPTN) were clustering in modules of relevance in the frontal and temporal cortices. Functional annotation and pathway analyses of such modules indicated enrichment for: i) DNA metabolism, i.e. transcription regulation, DNA protection and chromatin remodelling (MAPT and GRN modules); ii) immune and lysosomal processes (CTSC and HLA-DRA modules), and; iii) protein meta/catabolism (C9orf72, VCP, UBQLN2 and OPTN, and TMEM106B modules). PPI analysis supported the results of the functional annotation and pathway analyses. This work further characterizes known FTD-genes and elaborates on their biological relevance to disease: not only do we indicate likely impacted regional-specific biological processes driven by FTD-genes containing modules, but also do we suggest novel potential risk factors among the FTD-genes interactors as targets for further mechanistic characterization in hypothesis driven cell biology work.

Integrated Network Analyses for Functional Genomic Studies in Cancer

PubMed Central

Wilson, Jennifer L.; Hemann, Michael T.; Fraenkel, Ernest; Lauffenburger, Douglas A.

2013-01-01

RNA-interference (RNAi) studies hold great promise for functional investigation of the significance of genetic variations and mutations, as well as potential synthetic lethalities, for understanding and treatment of cancer, yet technical and conceptual issues currently diminish the potential power of this approach. While numerous research groups are usefully employing this kind of functional genomic methodology to identify molecular mediators of disease severity, response, and resistance to treatment, findings are generally confounded by “off-target” effects. These effects arise from a variety of issues beyond non-specific reagent behavior, such as biological cross-talk and feedback processes so thus can occur even with specific perturbation. Interpreting RNAi results in a network framework instead of merely as individual “hits” or “targets” leverages contributions from all hit/target contributions to pathways via their relationships with other network nodes. This interpretation can ameliorate dependence on individual reagent performance and increase confidence in biological validation. Here we provide background on RNAi studies in cancer applications, review key challenges with functional genomics, and motivate the use of network models grounded in pathway analyses. PMID:23811269

Integrated omics for the identification of key functionalities in biological wastewater treatment microbial communities.

PubMed

Narayanasamy, Shaman; Muller, Emilie E L; Sheik, Abdul R; Wilmes, Paul

2015-05-01

Biological wastewater treatment plants harbour diverse and complex microbial communities which prominently serve as models for microbial ecology and mixed culture biotechnological processes. Integrated omic analyses (combined metagenomics, metatranscriptomics, metaproteomics and metabolomics) are currently gaining momentum towards providing enhanced understanding of community structure, function and dynamics in situ as well as offering the potential to discover novel biological functionalities within the framework of Eco-Systems Biology. The integration of information from genome to metabolome allows the establishment of associations between genetic potential and final phenotype, a feature not realizable by only considering single 'omes'. Therefore, in our opinion, integrated omics will become the future standard for large-scale characterization of microbial consortia including those underpinning biological wastewater treatment processes. Systematically obtained time and space-resolved omic datasets will allow deconvolution of structure-function relationships by identifying key members and functions. Such knowledge will form the foundation for discovering novel genes on a much larger scale compared with previous efforts. In general, these insights will allow us to optimize microbial biotechnological processes either through better control of mixed culture processes or by use of more efficient enzymes in bioengineering applications. © 2015 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Impact of ontology evolution on functional analyses.

PubMed

Groß, Anika; Hartung, Michael; Prüfer, Kay; Kelso, Janet; Rahm, Erhard

2012-10-15

Ontologies are used in the annotation and analysis of biological data. As knowledge accumulates, ontologies and annotation undergo constant modifications to reflect this new knowledge. These modifications may influence the results of statistical applications such as functional enrichment analyses that describe experimental data in terms of ontological groupings. Here, we investigate to what degree modifications of the Gene Ontology (GO) impact these statistical analyses for both experimental and simulated data. The analysis is based on new measures for the stability of result sets and considers different ontology and annotation changes. Our results show that past changes in the GO are non-uniformly distributed over different branches of the ontology. Considering the semantic relatedness of significant categories in analysis results allows a more realistic stability assessment for functional enrichment studies. We observe that the results of term-enrichment analyses tend to be surprisingly stable despite changes in ontology and annotation.

Systems biology approach to late-onset Alzheimer's disease genome-wide association study identifies novel candidate genes validated using brain expression data and Caenorhabditis elegans experiments.

PubMed

Mukherjee, Shubhabrata; Russell, Joshua C; Carr, Daniel T; Burgess, Jeremy D; Allen, Mariet; Serie, Daniel J; Boehme, Kevin L; Kauwe, John S K; Naj, Adam C; Fardo, David W; Dickson, Dennis W; Montine, Thomas J; Ertekin-Taner, Nilufer; Kaeberlein, Matt R; Crane, Paul K

2017-10-01

We sought to determine whether a systems biology approach may identify novel late-onset Alzheimer's disease (LOAD) loci. We performed gene-wide association analyses and integrated results with human protein-protein interaction data using network analyses. We performed functional validation on novel genes using a transgenic Caenorhabditis elegans Aβ proteotoxicity model and evaluated novel genes using brain expression data from people with LOAD and other neurodegenerative conditions. We identified 13 novel candidate LOAD genes outside chromosome 19. Of those, RNA interference knockdowns of the C. elegans orthologs of UBC, NDUFS3, EGR1, and ATP5H were associated with Aβ toxicity, and NDUFS3, SLC25A11, ATP5H, and APP were differentially expressed in the temporal cortex. Network analyses identified novel LOAD candidate genes. We demonstrated a functional role for four of these in a C. elegans model and found enrichment of differentially expressed genes in the temporal cortex. Copyright © 2017 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Molecular Mechanics and Dynamics Characterization of an "in silico" Mutated Protein: A Stand-Alone Lab Module or Support Activity for "in vivo" and "in vitro" Analyses of Targeted Proteins

ERIC Educational Resources Information Center

Chiang, Harry; Robinson, Lucy C.; Brame, Cynthia J.; Messina, Troy C.

2013-01-01

Over the past 20 years, the biological sciences have increasingly incorporated chemistry, physics, computer science, and mathematics to aid in the development and use of mathematical models. Such combined approaches have been used to address problems from protein structure-function relationships to the workings of complex biological systems.…

Functional Analyses of the Crohn's Disease Risk Gene LACC1.

PubMed

Assadi, Ghazaleh; Vesterlund, Liselotte; Bonfiglio, Ferdinando; Mazzurana, Luca; Cordeddu, Lina; Schepis, Danika; Mjösberg, Jenny; Ruhrmann, Sabrina; Fabbri, Alessia; Vukojevic, Vladana; Percipalle, Piergiorgio; Salomons, Florian A; Laurencikiene, Jurga; Törkvist, Leif; Halfvarson, Jonas; D'Amato, Mauro

2016-01-01

Genetic variation in the Laccase (multicopper oxidoreductase) domain-containing 1 (LACC1) gene has been shown to affect the risk of Crohn's disease, leprosy and, more recently, ulcerative colitis and juvenile idiopathic arthritis. LACC1 function appears to promote fatty-acid oxidation, with concomitant inflammasome activation, reactive oxygen species production, and anti-bacterial responses in macrophages. We sought to contribute to elucidating LACC1 biological function by extensive characterization of its expression in human tissues and cells, and through preliminary analyses of the regulatory mechanisms driving such expression. We implemented Western blot, quantitative real-time PCR, immunofluorescence microscopy, and flow cytometry analyses to investigate fatty acid metabolism-immune nexus (FAMIN; the LACC1 encoded protein) expression in subcellular compartments, cell lines and relevant human tissues. Gene-set enrichment analyses were performed to initially investigate modulatory mechanisms of LACC1 expression. A small-interference RNA knockdown in vitro model system was used to study the effect of FAMIN depletion on peroxisome function. FAMIN expression was detected in macrophage-differentiated THP-1 cells and several human tissues, being highest in neutrophils, monocytes/macrophages, myeloid and plasmacytoid dendritic cells among peripheral blood cells. Subcellular co-localization was exclusively confined to peroxisomes, with some additional positivity for organelle endomembrane structures. LACC1 co-expression signatures were enriched for genes involved in peroxisome proliferator-activated receptors (PPAR) signaling pathways, and PPAR ligands downregulated FAMIN expression in in vitro model systems. FAMIN is a peroxisome-associated protein with primary role(s) in macrophages and other immune cells, where its metabolic functions may be modulated by PPAR signaling events. However, the precise molecular mechanisms through which FAMIN exerts its biological effects in immune cells remain to be elucidated.

Integrated data analysis for genome-wide research.

PubMed

Steinfath, Matthias; Repsilber, Dirk; Scholz, Matthias; Walther, Dirk; Selbig, Joachim

2007-01-01

Integrated data analysis is introduced as the intermediate level of a systems biology approach to analyse different 'omics' datasets, i.e., genome-wide measurements of transcripts, protein levels or protein-protein interactions, and metabolite levels aiming at generating a coherent understanding of biological function. In this chapter we focus on different methods of correlation analyses ranging from simple pairwise correlation to kernel canonical correlation which were recently applied in molecular biology. Several examples are presented to illustrate their application. The input data for this analysis frequently originate from different experimental platforms. Therefore, preprocessing steps such as data normalisation and missing value estimation are inherent to this approach. The corresponding procedures, potential pitfalls and biases, and available software solutions are reviewed. The multiplicity of observations obtained in omics-profiling experiments necessitates the application of multiple testing correction techniques.

Mining for Micropeptides.

PubMed

Makarewich, Catherine A; Olson, Eric N

2017-09-01

Advances in computational biology and large-scale transcriptome analyses have revealed that a much larger portion of the genome is transcribed than was previously recognized, resulting in the production of a diverse population of RNA molecules with both protein-coding and noncoding potential. Emerging evidence indicates that several RNA molecules have been mis-annotated as noncoding and in fact harbor short open reading frames (sORFs) that encode functional peptides and that have evaded detection until now due to their small size. sORF-encoded peptides (SEPs), or micropeptides, have been shown to have important roles in fundamental biological processes and in the maintenance of cellular homeostasis. These small proteins can act independently, for example as ligands or signaling molecules, or they can exert their biological functions by engaging with and modulating larger regulatory proteins. Given their small size, micropeptides may be uniquely suited to fine-tune complex biological systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

A data mining paradigm for identifying key factors in biological processes using gene expression data.

PubMed

Li, Jin; Zheng, Le; Uchiyama, Akihiko; Bin, Lianghua; Mauro, Theodora M; Elias, Peter M; Pawelczyk, Tadeusz; Sakowicz-Burkiewicz, Monika; Trzeciak, Magdalena; Leung, Donald Y M; Morasso, Maria I; Yu, Peng

2018-06-13

A large volume of biological data is being generated for studying mechanisms of various biological processes. These precious data enable large-scale computational analyses to gain biological insights. However, it remains a challenge to mine the data efficiently for knowledge discovery. The heterogeneity of these data makes it difficult to consistently integrate them, slowing down the process of biological discovery. We introduce a data processing paradigm to identify key factors in biological processes via systematic collection of gene expression datasets, primary analysis of data, and evaluation of consistent signals. To demonstrate its effectiveness, our paradigm was applied to epidermal development and identified many genes that play a potential role in this process. Besides the known epidermal development genes, a substantial proportion of the identified genes are still not supported by gain- or loss-of-function studies, yielding many novel genes for future studies. Among them, we selected a top gene for loss-of-function experimental validation and confirmed its function in epidermal differentiation, proving the ability of this paradigm to identify new factors in biological processes. In addition, this paradigm revealed many key genes in cold-induced thermogenesis using data from cold-challenged tissues, demonstrating its generalizability. This paradigm can lead to fruitful results for studying molecular mechanisms in an era of explosive accumulation of publicly available biological data.

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws.

PubMed

Xiao, Xiao; White, Ethan P; Hooten, Mevin B; Durham, Susan L

2011-10-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain.

Network news: prime time for systems biology of the plant circadian clock.

PubMed

McClung, C Robertson; Gutiérrez, Rodrigo A

2010-12-01

Whole-transcriptome analyses have established that the plant circadian clock regulates virtually every plant biological process and most prominently hormonal and stress response pathways. Systems biology efforts have successfully modeled the plant central clock machinery and an iterative process of model refinement and experimental validation has contributed significantly to the current view of the central clock machinery. The challenge now is to connect this central clock to the output pathways for understanding how the plant circadian clock contributes to plant growth and fitness in a changing environment. Undoubtedly, systems approaches will be needed to integrate and model the vastly increased volume of experimental data in order to extract meaningful biological information. Thus, we have entered an era of systems modeling, experimental testing, and refinement. This approach, coupled with advances from the genetic and biochemical analyses of clock function, is accelerating our progress towards a comprehensive understanding of the plant circadian clock network. Copyright © 2010 Elsevier Ltd. All rights reserved.

Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways.

PubMed

Scott, Robert A; Lagou, Vasiliki; Welch, Ryan P; Wheeler, Eleanor; Montasser, May E; Luan, Jian'an; Mägi, Reedik; Strawbridge, Rona J; Rehnberg, Emil; Gustafsson, Stefan; Kanoni, Stavroula; Rasmussen-Torvik, Laura J; Yengo, Loïc; Lecoeur, Cecile; Shungin, Dmitry; Sanna, Serena; Sidore, Carlo; Johnson, Paul C D; Jukema, J Wouter; Johnson, Toby; Mahajan, Anubha; Verweij, Niek; Thorleifsson, Gudmar; Hottenga, Jouke-Jan; Shah, Sonia; Smith, Albert V; Sennblad, Bengt; Gieger, Christian; Salo, Perttu; Perola, Markus; Timpson, Nicholas J; Evans, David M; Pourcain, Beate St; Wu, Ying; Andrews, Jeanette S; Hui, Jennie; Bielak, Lawrence F; Zhao, Wei; Horikoshi, Momoko; Navarro, Pau; Isaacs, Aaron; O'Connell, Jeffrey R; Stirrups, Kathleen; Vitart, Veronique; Hayward, Caroline; Esko, Tõnu; Mihailov, Evelin; Fraser, Ross M; Fall, Tove; Voight, Benjamin F; Raychaudhuri, Soumya; Chen, Han; Lindgren, Cecilia M; Morris, Andrew P; Rayner, Nigel W; Robertson, Neil; Rybin, Denis; Liu, Ching-Ti; Beckmann, Jacques S; Willems, Sara M; Chines, Peter S; Jackson, Anne U; Kang, Hyun Min; Stringham, Heather M; Song, Kijoung; Tanaka, Toshiko; Peden, John F; Goel, Anuj; Hicks, Andrew A; An, Ping; Müller-Nurasyid, Martina; Franco-Cereceda, Anders; Folkersen, Lasse; Marullo, Letizia; Jansen, Hanneke; Oldehinkel, Albertine J; Bruinenberg, Marcel; Pankow, James S; North, Kari E; Forouhi, Nita G; Loos, Ruth J F; Edkins, Sarah; Varga, Tibor V; Hallmans, Göran; Oksa, Heikki; Antonella, Mulas; Nagaraja, Ramaiah; Trompet, Stella; Ford, Ian; Bakker, Stephan J L; Kong, Augustine; Kumari, Meena; Gigante, Bruna; Herder, Christian; Munroe, Patricia B; Caulfield, Mark; Antti, Jula; Mangino, Massimo; Small, Kerrin; Miljkovic, Iva; Liu, Yongmei; Atalay, Mustafa; Kiess, Wieland; James, Alan L; Rivadeneira, Fernando; Uitterlinden, Andre G; Palmer, Colin N A; Doney, Alex S F; Willemsen, Gonneke; Smit, Johannes H; Campbell, Susan; Polasek, Ozren; Bonnycastle, Lori L; Hercberg, Serge; Dimitriou, Maria; Bolton, Jennifer L; Fowkes, Gerard R; Kovacs, Peter; Lindström, Jaana; Zemunik, Tatijana; Bandinelli, Stefania; Wild, Sarah H; Basart, Hanneke V; Rathmann, Wolfgang; Grallert, Harald; Maerz, Winfried; Kleber, Marcus E; Boehm, Bernhard O; Peters, Annette; Pramstaller, Peter P; Province, Michael A; Borecki, Ingrid B; Hastie, Nicholas D; Rudan, Igor; Campbell, Harry; Watkins, Hugh; Farrall, Martin; Stumvoll, Michael; Ferrucci, Luigi; Waterworth, Dawn M; Bergman, Richard N; Collins, Francis S; Tuomilehto, Jaakko; Watanabe, Richard M; de Geus, Eco J C; Penninx, Brenda W; Hofman, Albert; Oostra, Ben A; Psaty, Bruce M; Vollenweider, Peter; Wilson, James F; Wright, Alan F; Hovingh, G Kees; Metspalu, Andres; Uusitupa, Matti; Magnusson, Patrik K E; Kyvik, Kirsten O; Kaprio, Jaakko; Price, Jackie F; Dedoussis, George V; Deloukas, Panos; Meneton, Pierre; Lind, Lars; Boehnke, Michael; Shuldiner, Alan R; van Duijn, Cornelia M; Morris, Andrew D; Toenjes, Anke; Peyser, Patricia A; Beilby, John P; Körner, Antje; Kuusisto, Johanna; Laakso, Markku; Bornstein, Stefan R; Schwarz, Peter E H; Lakka, Timo A; Rauramaa, Rainer; Adair, Linda S; Smith, George Davey; Spector, Tim D; Illig, Thomas; de Faire, Ulf; Hamsten, Anders; Gudnason, Vilmundur; Kivimaki, Mika; Hingorani, Aroon; Keinanen-Kiukaanniemi, Sirkka M; Saaristo, Timo E; Boomsma, Dorret I; Stefansson, Kari; van der Harst, Pim; Dupuis, Josée; Pedersen, Nancy L; Sattar, Naveed; Harris, Tamara B; Cucca, Francesco; Ripatti, Samuli; Salomaa, Veikko; Mohlke, Karen L; Balkau, Beverley; Froguel, Philippe; Pouta, Anneli; Jarvelin, Marjo-Riitta; Wareham, Nicholas J; Bouatia-Naji, Nabila; McCarthy, Mark I; Franks, Paul W; Meigs, James B; Teslovich, Tanya M; Florez, Jose C; Langenberg, Claudia; Ingelsson, Erik; Prokopenko, Inga; Barroso, Inês

2012-09-01

Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.

Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

PubMed Central

Scott, Robert A; Lagou, Vasiliki; Welch, Ryan P; Wheeler, Eleanor; Montasser, May E; Luan, Jian’an; Mägi, Reedik; Strawbridge, Rona J; Rehnberg, Emil; Gustafsson, Stefan; Kanoni, Stavroula; Rasmussen-Torvik, Laura J; Yengo, Loïc; Lecoeur, Cecile; Shungin, Dmitry; Sanna, Serena; Sidore, Carlo; Johnson, Paul C D; Jukema, J Wouter; Johnson, Toby; Mahajan, Anubha; Verweij, Niek; Thorleifsson, Gudmar; Hottenga, Jouke-Jan; Shah, Sonia; Smith, Albert V; Sennblad, Bengt; Gieger, Christian; Salo, Perttu; Perola, Markus; Timpson, Nicholas J; Evans, David M; Pourcain, Beate St; Wu, Ying; Andrews, Jeanette S; Hui, Jennie; Bielak, Lawrence F; Zhao, Wei; Horikoshi, Momoko; Navarro, Pau; Isaacs, Aaron; O’Connell, Jeffrey R; Stirrups, Kathleen; Vitart, Veronique; Hayward, Caroline; Esko, Tönu; Mihailov, Evelin; Fraser, Ross M; Fall, Tove; Voight, Benjamin F; Raychaudhuri, Soumya; Chen, Han; Lindgren, Cecilia M; Morris, Andrew P; Rayner, Nigel W; Robertson, Neil; Rybin, Denis; Liu, Ching-Ti; Beckmann, Jacques S; Willems, Sara M; Chines, Peter S; Jackson, Anne U; Kang, Hyun Min; Stringham, Heather M; Song, Kijoung; Tanaka, Toshiko; Peden, John F; Goel, Anuj; Hicks, Andrew A; An, Ping; Müller-Nurasyid, Martina; Franco-Cereceda, Anders; Folkersen, Lasse; Marullo, Letizia; Jansen, Hanneke; Oldehinkel, Albertine J; Bruinenberg, Marcel; Pankow, James S; North, Kari E; Forouhi, Nita G; Loos, Ruth J F; Edkins, Sarah; Varga, Tibor V; Hallmans, Göran; Oksa, Heikki; Antonella, Mulas; Nagaraja, Ramaiah; Trompet, Stella; Ford, Ian; Bakker, Stephan J L; Kong, Augustine; Kumari, Meena; Gigante, Bruna; Herder, Christian; Munroe, Patricia B; Caulfield, Mark; Antti, Jula; Mangino, Massimo; Small, Kerrin; Miljkovic, Iva; Liu, Yongmei; Atalay, Mustafa; Kiess, Wieland; James, Alan L; Rivadeneira, Fernando; Uitterlinden, Andre G; Palmer, Colin N A; Doney, Alex S F; Willemsen, Gonneke; Smit, Johannes H; Campbell, Susan; Polasek, Ozren; Bonnycastle, Lori L; Hercberg, Serge; Dimitriou, Maria; Bolton, Jennifer L; Fowkes, Gerard R; Kovacs, Peter; Lindström, Jaana; Zemunik, Tatijana; Bandinelli, Stefania; Wild, Sarah H; Basart, Hanneke V; Rathmann, Wolfgang; Grallert, Harald; Maerz, Winfried; Kleber, Marcus E; Boehm, Bernhard O; Peters, Annette; Pramstaller, Peter P; Province, Michael A; Borecki, Ingrid B; Hastie, Nicholas D; Rudan, Igor; Campbell, Harry; Watkins, Hugh; Farrall, Martin; Stumvoll, Michael; Ferrucci, Luigi; Waterworth, Dawn M; Bergman, Richard N; Collins, Francis S; Tuomilehto, Jaakko; Watanabe, Richard M; de Geus, Eco J C; Penninx, Brenda W; Hofman, Albert; Oostra, Ben A; Psaty, Bruce M; Vollenweider, Peter; Wilson, James F; Wright, Alan F; Hovingh, G Kees; Metspalu, Andres; Uusitupa, Matti; Magnusson, Patrik K E; Kyvik, Kirsten O; Kaprio, Jaakko; Price, Jackie F; Dedoussis, George V; Deloukas, Panos; Meneton, Pierre; Lind, Lars; Boehnke, Michael; Shuldiner, Alan R; van Duijn, Cornelia M; Morris, Andrew D; Toenjes, Anke; Peyser, Patricia A; Beilby, John P; Körner, Antje; Kuusisto, Johanna; Laakso, Markku; Bornstein, Stefan R; Schwarz, Peter E H; Lakka, Timo A; Rauramaa, Rainer; Adair, Linda S; Smith, George Davey; Spector, Tim D; Illig, Thomas; de Faire, Ulf; Hamsten, Anders; Gudnason, Vilmundur; Kivimaki, Mika; Hingorani, Aroon; Keinanen-Kiukaanniemi, Sirkka M; Saaristo, Timo E; Boomsma, Dorret I; Stefansson, Kari; van der Harst, Pim; Dupuis, Josée; Pedersen, Nancy L; Sattar, Naveed; Harris, Tamara B; Cucca, Francesco; Ripatti, Samuli; Salomaa, Veikko; Mohlke, Karen L; Balkau, Beverley; Froguel, Philippe; Pouta, Anneli; Jarvelin, Marjo-Riitta; Wareham, Nicholas J; Bouatia-Naji, Nabila; McCarthy, Mark I; Franks, Paul W; Meigs, James B; Teslovich, Tanya M; Florez, Jose C; Langenberg, Claudia; Ingelsson, Erik; Prokopenko, Inga; Barroso, Inês

2012-01-01

Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have raised the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional follow-up of these newly discovered loci will further improve our understanding of glycemic control. PMID:22885924

Prokaryotic regulatory systems biology: Common principles governing the functional architectures of Bacillus subtilis and Escherichia coli unveiled by the natural decomposition approach.

PubMed

Freyre-González, Julio A; Treviño-Quintanilla, Luis G; Valtierra-Gutiérrez, Ilse A; Gutiérrez-Ríos, Rosa María; Alonso-Pavón, José A

2012-10-31

Escherichia coli and Bacillus subtilis are two of the best-studied prokaryotic model organisms. Previous analyses of their transcriptional regulatory networks have shown that they exhibit high plasticity during evolution and suggested that both converge to scale-free-like structures. Nevertheless, beyond this suggestion, no analyses have been carried out to identify the common systems-level components and principles governing these organisms. Here we show that these two phylogenetically distant organisms follow a set of common novel biologically consistent systems principles revealed by the mathematically and biologically founded natural decomposition approach. The discovered common functional architecture is a diamond-shaped, matryoshka-like, three-layer (coordination, processing, and integration) hierarchy exhibiting feedback, which is shaped by four systems-level components: global transcription factors (global TFs), locally autonomous modules, basal machinery and intermodular genes. The first mathematical criterion to identify global TFs, the κ-value, was reassessed on B. subtilis and confirmed its high predictive power by identifying all the previously reported, plus three potential, master regulators and eight sigma factors. The functionally conserved cores of modules, basal cell machinery, and a set of non-orthologous common physiological global responses were identified via both orthologous genes and non-orthologous conserved functions. This study reveals novel common systems principles maintained between two phylogenetically distant organisms and provides a comparison of their lifestyle adaptations. Our results shed new light on the systems-level principles and the fundamental functions required by bacteria to sustain life. Copyright © 2012 Elsevier B.V. All rights reserved.

The function and evolution of male and female genitalia in Phyllophaga Harris scarab beetles (Coleoptera: Scarabaeidae).

PubMed

Richmond, M P; Park, J; Henry, C S

2016-11-01

Genitalia diversity in insects continues to fuel investigation of the function and evolution of these dynamic structures. Whereas most studies have focused on variation in male genitalia, an increasing number of studies on female genitalia have uncovered comparable diversity among females, but often at a much finer morphological scale. In this study, we analysed the function and evolution of male and female genitalia in Phyllophaga scarab beetles, a group in which both sexes exhibit genitalic diversity. To document the interaction between male and female structures during mating, we dissected flash-frozen mating pairs from three Phyllophaga species and investigated fine-scale morphology using SEM. We then reconstructed ancestral character states using a species tree inferred from mitochondrial and nuclear loci to elucidate and compare the evolutionary history of male and female genitalia. Our dissections revealed an interlocking mechanism of the female pubic process and male parameres that appears to improve the mechanical fit of the copulatory position. The comparative analyses, however, did not support coevolution of male and female structures and showed more erratic evolution of the female genitalia relative to males. By studying a group that exhibits obvious female genitalic diversity, we were able to demonstrate the relevance of female reproductive morphology in studies of male genital diversity. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Integrative Transcriptomic Analysis Uncovers Novel Gene Modules That Underlie the Sulfate Response in Arabidopsis thaliana

PubMed Central

Henríquez-Valencia, Carlos; Arenas-M, Anita; Medina, Joaquín; Canales, Javier

2018-01-01

Sulfur is an essential nutrient for plant growth and development. Sulfur is a constituent of proteins, the plasma membrane and cell walls, among other important cellular components. To obtain new insights into the gene regulatory networks underlying the sulfate response, we performed an integrative meta-analysis of transcriptomic data from five different sulfate experiments available in public databases. This bioinformatic approach allowed us to identify a robust set of genes whose expression depends only on sulfate availability, indicating that those genes play an important role in the sulfate response. In relation to sulfate metabolism, the biological function of approximately 45% of these genes is currently unknown. Moreover, we found several consistent Gene Ontology terms related to biological processes that have not been extensively studied in the context of the sulfate response; these processes include cell wall organization, carbohydrate metabolism, nitrogen compound transport, and the regulation of proteolysis. Gene co-expression network analyses revealed relationships between the sulfate-responsive genes that were distributed among seven function-specific co-expression modules. The most connected genes in the sulfate co-expression network belong to a module related to the carbon response, suggesting that this biological function plays an important role in the control of the sulfate response. Temporal analyses of the network suggest that sulfate starvation generates a biphasic response, which involves that major changes in gene expression occur during both the early and late responses. Network analyses predicted that the sulfate response is regulated by a limited number of transcription factors, including MYBs, bZIPs, and NF-YAs. In conclusion, our analysis identified new candidate genes and provided new hypotheses to advance our understanding of the transcriptional regulation of sulfate metabolism in plants. PMID:29692794

Integrative Transcriptomic Analysis Uncovers Novel Gene Modules That Underlie the Sulfate Response in Arabidopsis thaliana.

PubMed

Henríquez-Valencia, Carlos; Arenas-M, Anita; Medina, Joaquín; Canales, Javier

2018-01-01

Sulfur is an essential nutrient for plant growth and development. Sulfur is a constituent of proteins, the plasma membrane and cell walls, among other important cellular components. To obtain new insights into the gene regulatory networks underlying the sulfate response, we performed an integrative meta-analysis of transcriptomic data from five different sulfate experiments available in public databases. This bioinformatic approach allowed us to identify a robust set of genes whose expression depends only on sulfate availability, indicating that those genes play an important role in the sulfate response. In relation to sulfate metabolism, the biological function of approximately 45% of these genes is currently unknown. Moreover, we found several consistent Gene Ontology terms related to biological processes that have not been extensively studied in the context of the sulfate response; these processes include cell wall organization, carbohydrate metabolism, nitrogen compound transport, and the regulation of proteolysis. Gene co-expression network analyses revealed relationships between the sulfate-responsive genes that were distributed among seven function-specific co-expression modules. The most connected genes in the sulfate co-expression network belong to a module related to the carbon response, suggesting that this biological function plays an important role in the control of the sulfate response. Temporal analyses of the network suggest that sulfate starvation generates a biphasic response, which involves that major changes in gene expression occur during both the early and late responses. Network analyses predicted that the sulfate response is regulated by a limited number of transcription factors, including MYBs, bZIPs, and NF-YAs. In conclusion, our analysis identified new candidate genes and provided new hypotheses to advance our understanding of the transcriptional regulation of sulfate metabolism in plants.

Characteristics of genomic signatures derived using univariate methods and mechanistically anchored functional descriptors for predicting drug- and xenobiotic-induced nephrotoxicity.

PubMed

Shi, Weiwei; Bugrim, Andrej; Nikolsky, Yuri; Nikolskya, Tatiana; Brennan, Richard J

2008-01-01

ABSTRACT The ideal toxicity biomarker is composed of the properties of prediction (is detected prior to traditional pathological signs of injury), accuracy (high sensitivity and specificity), and mechanistic relationships to the endpoint measured (biological relevance). Gene expression-based toxicity biomarkers ("signatures") have shown good predictive power and accuracy, but are difficult to interpret biologically. We have compared different statistical methods of feature selection with knowledge-based approaches, using GeneGo's database of canonical pathway maps, to generate gene sets for the classification of renal tubule toxicity. The gene set selection algorithms include four univariate analyses: t-statistics, fold-change, B-statistics, and RankProd, and their combination and overlap for the identification of differentially expressed probes. Enrichment analysis following the results of the four univariate analyses, Hotelling T-square test, and, finally out-of-bag selection, a variant of cross-validation, were used to identify canonical pathway maps-sets of genes coordinately involved in key biological processes-with classification power. Differentially expressed genes identified by the different statistical univariate analyses all generated reasonably performing classifiers of tubule toxicity. Maps identified by enrichment analysis or Hotelling T-square had lower classification power, but highlighted perturbed lipid homeostasis as a common discriminator of nephrotoxic treatments. The out-of-bag method yielded the best functionally integrated classifier. The map "ephrins signaling" performed comparably to a classifier derived using sparse linear programming, a machine learning algorithm, and represents a signaling network specifically involved in renal tubule development and integrity. Such functional descriptors of toxicity promise to better integrate predictive toxicogenomics with mechanistic analysis, facilitating the interpretation and risk assessment of predictive genomic investigations.

Assessment of self-organizing maps to analyze sole-carbon source utilization profiles.

PubMed

Leflaive, Joséphine; Céréghino, Régis; Danger, Michaël; Lacroix, Gérard; Ten-Hage, Loïc

2005-07-01

The use of community-level physiological profiles obtained with Biolog microplates is widely employed to consider the functional diversity of bacterial communities. Biolog produces a great amount of data which analysis has been the subject of many studies. In most cases, after some transformations, these data were investigated with classical multivariate analyses. Here we provided an alternative to this method, that is the use of an artificial intelligence technique, the Self-Organizing Maps (SOM, unsupervised neural network). We used data from a microcosm study of algae-associated bacterial communities placed in various nutritive conditions. Analyses were carried out on the net absorbances at two incubation times for each substrates and on the chemical guild categorization of the total bacterial activity. Compared to Principal Components Analysis and cluster analysis, SOM appeared as a valuable tool for community classification, and to establish clear relationships between clusters of bacterial communities and sole-carbon sources utilization. Specifically, SOM offered a clear bidimensional projection of a relatively large volume of data and were easier to interpret than plots commonly obtained with multivariate analyses. They would be recommended to pattern the temporal evolution of communities' functional diversity.

The genetics of feed conversion efficiency traits in a commercial broiler line

PubMed Central

Reyer, Henry; Hawken, Rachel; Murani, Eduard; Ponsuksili, Siriluck; Wimmers, Klaus

2015-01-01

Individual feed conversion efficiency (FCE) is a major trait that influences the usage of energy resources and the ecological footprint of livestock production. The underlying biological processes of FCE are complex and are influenced by factors as diverse as climate, feed properties, gut microbiota, and individual genetic predisposition. To gain an insight to the genetic relationships with FCE traits and to contribute to the improvement of FCE in commercial chicken lines, a genome-wide association study was conducted using a commercial broiler population (n = 859) tested for FCE and weight traits during the finisher period from 39 to 46 days of age. Both single-marker (generalized linear model) and multi-marker (Bayesian approach) analyses were applied to the dataset to detect genes associated with the variability in FCE. The separate analyses revealed 22 quantitative trait loci (QTL) regions on 13 different chromosomes; the integration of both approaches resulted in 7 overlapping QTL regions. The analyses pointed to acylglycerol kinase (AGK) and general transcription factor 2-I (GTF2I) as positional and functional candidate genes. Non-synonymous polymorphisms of both candidate genes revealed evidence for a functional importance of these genes by influencing different biological aspects of FCE. PMID:26552583

Computational analyses in cognitive neuroscience: in defense of biological implausibility.

PubMed

Dror, I E; Gallogly, D P

1999-06-01

Because cognitive neuroscience researchers attempt to understand the human mind by bridging behavior and brain, they expect computational analyses to be biologically plausible. In this paper, biologically implausible computational analyses are shown to have critical and essential roles in the various stages and domains of cognitive neuroscience research. Specifically, biologically implausible computational analyses can contribute to (1) understanding and characterizing the problem that is being studied, (2) examining the availability of information and its representation, and (3) evaluating and understanding the neuronal solution. In the context of the distinct types of contributions made by certain computational analyses, the biological plausibility of those analyses is altogether irrelevant. These biologically implausible models are nevertheless relevant and important for biologically driven research.

Proximal soil sensing and sensor fusion for soil health assessment

USDA-ARS?s Scientific Manuscript database

Assessment of soil health involves determining how well a soil is performing its biological, chemical, and physical functions relative to its inherent potential. Due to high costs, labor requirements, and soil disturbance, traditional laboratory analyses cannot provide high resolution soil health da...

ESEA: Discovering the Dysregulated Pathways based on Edge Set Enrichment Analysis

PubMed Central

Han, Junwei; Shi, Xinrui; Zhang, Yunpeng; Xu, Yanjun; Jiang, Ying; Zhang, Chunlong; Feng, Li; Yang, Haixiu; Shang, Desi; Sun, Zeguo; Su, Fei; Li, Chunquan; Li, Xia

2015-01-01

Pathway analyses are playing an increasingly important role in understanding biological mechanism, cellular function and disease states. Current pathway-identification methods generally focus on only the changes of gene expression levels; however, the biological relationships among genes are also the fundamental components of pathways, and the dysregulated relationships may also alter the pathway activities. We propose a powerful computational method, Edge Set Enrichment Analysis (ESEA), for the identification of dysregulated pathways. This provides a novel way of pathway analysis by investigating the changes of biological relationships of pathways in the context of gene expression data. Simulation studies illustrate the power and performance of ESEA under various simulated conditions. Using real datasets from p53 mutation, Type 2 diabetes and lung cancer, we validate effectiveness of ESEA in identifying dysregulated pathways. We further compare our results with five other pathway enrichment analysis methods. With these analyses, we show that ESEA is able to help uncover dysregulated biological pathways underlying complex traits and human diseases via specific use of the dysregulated biological relationships. We develop a freely available R-based tool of ESEA. Currently, ESEA can support pathway analysis of the seven public databases (KEGG; Reactome; Biocarta; NCI; SPIKE; HumanCyc; Panther). PMID:26267116

Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding loci†

PubMed Central

Kirsten, Holger; Al-Hasani, Hoor; Holdt, Lesca; Gross, Arnd; Beutner, Frank; Krohn, Knut; Horn, Katrin; Ahnert, Peter; Burkhardt, Ralph; Reiche, Kristin; Hackermüller, Jörg; Löffler, Markus; Teupser, Daniel; Thiery, Joachim; Scholz, Markus

2015-01-01

Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait-associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters and enrichment of co-localized functional elements. We found eQTLs for about 85% of analysed genes, and 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs; however, our data suggest that most cis-heritability of these transcripts seems explained. Dissection of co-localized functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene expression, pathways and disease-related processes. PMID:26019233

Reverse engineering and identification in systems biology: strategies, perspectives and challenges.

PubMed

Villaverde, Alejandro F; Banga, Julio R

2014-02-06

The interplay of mathematical modelling with experiments is one of the central elements in systems biology. The aim of reverse engineering is to infer, analyse and understand, through this interplay, the functional and regulatory mechanisms of biological systems. Reverse engineering is not exclusive of systems biology and has been studied in different areas, such as inverse problem theory, machine learning, nonlinear physics, (bio)chemical kinetics, control theory and optimization, among others. However, it seems that many of these areas have been relatively closed to outsiders. In this contribution, we aim to compare and highlight the different perspectives and contributions from these fields, with emphasis on two key questions: (i) why are reverse engineering problems so hard to solve, and (ii) what methods are available for the particular problems arising from systems biology?

A versatile petri net based architecture for modeling and simulation of complex biological processes.

PubMed

Nagasaki, Masao; Doi, Atsushi; Matsuno, Hiroshi; Miyano, Satoru

2004-01-01

The research on modeling and simulation of complex biological systems is getting more important in Systems Biology. In this respect, we have developed Hybrid Function Petri net (HFPN) that was newly developed from existing Petri net because of their intuitive graphical representation and their capabilities for mathematical analyses. However, in the process of modeling metabolic, gene regulatory or signal transduction pathways with the architecture, we have realized three extensions of HFPN, (i) an entity should be extended to contain more than one value, (ii) an entity should be extended to handle other primitive types, e.g. boolean, string, (iii) an entity should be extended to handle more advanced type called object that consists of variables and methods, are necessary for modeling biological systems with Petri net based architecture. To deal with it, we define a new enhanced Petri net called hybrid functional Petri net with extension (HFPNe). To demonstrate the effectiveness of the enhancements, we model and simulate with HFPNe four biological processes that are diffcult to represent with the previous architecture HFPN.

Web-based applications for building, managing and analysing kinetic models of biological systems.

PubMed

Lee, Dong-Yup; Saha, Rajib; Yusufi, Faraaz Noor Khan; Park, Wonjun; Karimi, Iftekhar A

2009-01-01

Mathematical modelling and computational analysis play an essential role in improving our capability to elucidate the functions and characteristics of complex biological systems such as metabolic, regulatory and cell signalling pathways. The modelling and concomitant simulation render it possible to predict the cellular behaviour of systems under various genetically and/or environmentally perturbed conditions. This motivates systems biologists/bioengineers/bioinformaticians to develop new tools and applications, allowing non-experts to easily conduct such modelling and analysis. However, among a multitude of systems biology tools developed to date, only a handful of projects have adopted a web-based approach to kinetic modelling. In this report, we evaluate the capabilities and characteristics of current web-based tools in systems biology and identify desirable features, limitations and bottlenecks for further improvements in terms of usability and functionality. A short discussion on software architecture issues involved in web-based applications and the approaches taken by existing tools is included for those interested in developing their own simulation applications.

Application of metagenomics technologies for antimicrobial resistance and food safety research and beyond

USDA-ARS?s Scientific Manuscript database

Current developments in the field of metagenomics in biological sciences have demonstrated the need and potential usefulness of taxonomical and functional analyses of meta-omics data generated by genomics, transcriptomics, proteomics, and metabolomics. This review will provide a general overview of...

Nitrification inhibition as measured by RNA- and DNA-based function-specific assays and microbial community structure analyses

EPA Science Inventory

Abstract: The biological removal of ammonia in conventional wastewater treatment plants (WWTPs) is performed by promoting nitrification, which transforms ammonia into nitrate, which in turn is converted into nitrogen gas by denitrifying bacteria. The first step in nitrification, ...

CARBOHYDRATE USE AND ASSIMILATION BY LITTER AND SOIL FUNGI ASSESSED BY CARBON ISOTOPES AND BIOLOG ASSAYS

EPA Science Inventory

Soil fungi are integral to decomposition in forests, yet identification of probable functional roles of different taxa is problematic. Here, we compared carbohydrate assimilation patterns derived from stable isotope analyses on cultures with those produced from cultures on Biolo...

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws

USGS Publications Warehouse

Xiao, X.; White, E.P.; Hooten, M.B.; Durham, S.L.

2011-01-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain. ?? 2011 by the Ecological Society of America.

In the swim of things: recent insights to neurogenetic disorders from zebrafish.

PubMed

Kabashi, Edor; Champagne, Nathalie; Brustein, Edna; Drapeau, Pierre

2010-08-01

The advantage of zebrafish as a model to study human pathologies lies in the ease of manipulating gene expression in vivo. Here we focus on recent progress in our understanding of motor neuron diseases and neurodevelopmental disorders and discuss how novel technologies will permit further disease models to be developed. Together these advances set the stage for this simple functional model, with particular advantages for transgenesis, multigenic analyses and chemical biology, to become uniquely suited for advancing the functional genomics of neurological and possibly psychiatric diseases - from understanding the genetics and cell biology of degenerative and developmental disorders to the discovery of therapeutics. Copyright 2010 Elsevier Ltd. All rights reserved.

Convex reformulation of biologically-based multi-criteria intensity-modulated radiation therapy optimization including fractionation effects

NASA Astrophysics Data System (ADS)

Hoffmann, Aswin L.; den Hertog, Dick; Siem, Alex Y. D.; Kaanders, Johannes H. A. M.; Huizenga, Henk

2008-11-01

Finding fluence maps for intensity-modulated radiation therapy (IMRT) can be formulated as a multi-criteria optimization problem for which Pareto optimal treatment plans exist. To account for the dose-per-fraction effect of fractionated IMRT, it is desirable to exploit radiobiological treatment plan evaluation criteria based on the linear-quadratic (LQ) cell survival model as a means to balance the radiation benefits and risks in terms of biologic response. Unfortunately, the LQ-model-based radiobiological criteria are nonconvex functions, which make the optimization problem hard to solve. We apply the framework proposed by Romeijn et al (2004 Phys. Med. Biol. 49 1991-2013) to find transformations of LQ-model-based radiobiological functions and establish conditions under which transformed functions result in equivalent convex criteria that do not change the set of Pareto optimal treatment plans. The functions analysed are: the LQ-Poisson-based model for tumour control probability (TCP) with and without inter-patient heterogeneity in radiation sensitivity, the LQ-Poisson-based relative seriality s-model for normal tissue complication probability (NTCP), the equivalent uniform dose (EUD) under the LQ-Poisson model and the fractionation-corrected Probit-based model for NTCP according to Lyman, Kutcher and Burman. These functions differ from those analysed before in that they cannot be decomposed into elementary EUD or generalized-EUD functions. In addition, we show that applying increasing and concave transformations to the convexified functions is beneficial for the piecewise approximation of the Pareto efficient frontier.

BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine.

PubMed

Liu, Zhongyang; Guo, Feifei; Wang, Yong; Li, Chun; Zhang, Xinlei; Li, Honglei; Diao, Lihong; Gu, Jiangyong; Wang, Wei; Li, Dong; He, Fuchu

2016-02-16

Traditional Chinese Medicine (TCM), with a history of thousands of years of clinical practice, is gaining more and more attention and application worldwide. And TCM-based new drug development, especially for the treatment of complex diseases is promising. However, owing to the TCM's diverse ingredients and their complex interaction with human body, it is still quite difficult to uncover its molecular mechanism, which greatly hinders the TCM modernization and internationalization. Here we developed the first online Bioinformatics Analysis Tool for Molecular mechANism of TCM (BATMAN-TCM). Its main functions include 1) TCM ingredients' target prediction; 2) functional analyses of targets including biological pathway, Gene Ontology functional term and disease enrichment analyses; 3) the visualization of ingredient-target-pathway/disease association network and KEGG biological pathway with highlighted targets; 4) comparison analysis of multiple TCMs. Finally, we applied BATMAN-TCM to Qishen Yiqi dripping Pill (QSYQ) and combined with subsequent experimental validation to reveal the functions of renin-angiotensin system responsible for QSYQ's cardioprotective effects for the first time. BATMAN-TCM will contribute to the understanding of the "multi-component, multi-target and multi-pathway" combinational therapeutic mechanism of TCM, and provide valuable clues for subsequent experimental validation, accelerating the elucidation of TCM's molecular mechanism. BATMAN-TCM is available at http://bionet.ncpsb.org/batman-tcm.

From Genomes to Protein Models and Back

NASA Astrophysics Data System (ADS)

Tramontano, Anna; Giorgetti, Alejandro; Orsini, Massimiliano; Raimondo, Domenico

2007-12-01

The alternative splicing mechanism allows genes to generate more than one product. When the splicing events occur within protein coding regions they can modify the biological function of the protein. Alternative splicing has been suggested as one way for explaining the discrepancy between the number of human genes and functional complexity. We analysed the putative structure of the alternatively spliced gene products annotated in the ENCODE pilot project and discovered that many of the potential alternative gene products will be unlikely to produce stable functional proteins.

Early post-stroke cognition in stroke rehabilitation patients predicts functional outcome at 13 months.

PubMed

Wagle, Jørgen; Farner, Lasse; Flekkøy, Kjell; Bruun Wyller, Torgeir; Sandvik, Leiv; Fure, Brynjar; Stensrød, Brynhild; Engedal, Knut

2011-01-01

To identify prognostic factors associated with functional outcome at 13 months in a sample of stroke rehabilitation patients. Specifically, we hypothesized that cognitive functioning early after stroke would predict long-term functional outcome independently of other factors. 163 stroke rehabilitation patients underwent a structured neuropsychological examination 2-3 weeks after hospital admittance, and their functional status was subsequently evaluated 13 months later with the modified Rankin Scale (mRS) as outcome measure. Three predictive models were built using linear regression analyses: a biological model (sociodemographics, apolipoprotein E genotype, prestroke vascular factors, lesion characteristics and neurological stroke-related impairment); a functional model (pre- and early post-stroke cognitive functioning, personal and instrumental activities of daily living, ADL, and depressive symptoms), and a combined model (including significant variables, with p value <0.05, from the biological and functional models). A combined model of 4 variables best predicted long-term functional outcome with explained variance of 49%: neurological impairment (National Institute of Health Stroke Scale; β = 0.402, p < 0.001), age (β = 0.233, p = 0.001), post-stroke cognitive functioning (Repeatable Battery of Neuropsychological Status, RBANS; β = -0.248, p = 0.001) and prestroke personal ADL (Barthel Index; β = -0.217, p = 0.002). Further linear regression analyses of which RBANS indexes and subtests best predicted long-term functional outcome showed that Coding (β = -0.484, p < 0.001) and Figure Copy (β = -0.233, p = 0.002) raw scores at baseline explained 42% of the variance in mRS scores at follow-up. Early post-stroke cognitive functioning as measured by the RBANS is a significant and independent predictor of long-term functional post-stroke outcome. Copyright © 2011 S. Karger AG, Basel.

Ontology- and graph-based similarity assessment in biological networks.

PubMed

Wang, Haiying; Zheng, Huiru; Azuaje, Francisco

2010-10-15

A standard systems-based approach to biomarker and drug target discovery consists of placing putative biomarkers in the context of a network of biological interactions, followed by different 'guilt-by-association' analyses. The latter is typically done based on network structural features. Here, an alternative analysis approach in which the networks are analyzed on a 'semantic similarity' space is reported. Such information is extracted from ontology-based functional annotations. We present SimTrek, a Cytoscape plugin for ontology-based similarity assessment in biological networks. http://rosalind.infj.ulst.ac.uk/SimTrek.html francisco.azuaje@crp-sante.lu Supplementary data are available at Bioinformatics online.

Plant peptide hormone signalling.

PubMed

Motomitsu, Ayane; Sawa, Shinichiro; Ishida, Takashi

2015-01-01

The ligand-receptor-based cell-to-cell communication system is one of the most important molecular bases for the establishment of complex multicellular organisms. Plants have evolved highly complex intercellular communication systems. Historical studies have identified several molecules, designated phytohormones, that function in these processes. Recent advances in molecular biological analyses have identified phytohormone receptors and signalling mediators, and have led to the discovery of numerous peptide-based signalling molecules. Subsequent analyses have revealed the involvement in and contribution of these peptides to multiple aspects of the plant life cycle, including development and environmental responses, similar to the functions of canonical phytohormones. On the basis of this knowledge, the view that these peptide hormones are pivotal regulators in plants is becoming increasingly accepted. Peptide hormones are transcribed from the genome and translated into peptides. However, these peptides generally undergo further post-translational modifications to enable them to exert their function. Peptide hormones are expressed in and secreted from specific cells or tissues. Apoplastic peptides are perceived by specialized receptors that are located at the surface of target cells. Peptide hormone-receptor complexes activate intracellular signalling through downstream molecules, including kinases and transcription factors, which then trigger cellular events. In this chapter we provide a comprehensive summary of the biological functions of peptide hormones, focusing on how they mature and the ways in which they modulate plant functions. © 2015 Authors; published by Portland Press Limited.

ProbFAST: Probabilistic functional analysis system tool.

PubMed

Silva, Israel T; Vêncio, Ricardo Z N; Oliveira, Thiago Y K; Molfetta, Greice A; Silva, Wilson A

2010-03-30

The post-genomic era has brought new challenges regarding the understanding of the organization and function of the human genome. Many of these challenges are centered on the meaning of differential gene regulation under distinct biological conditions and can be performed by analyzing the Multiple Differential Expression (MDE) of genes associated with normal and abnormal biological processes. Currently MDE analyses are limited to usual methods of differential expression initially designed for paired analysis. We proposed a web platform named ProbFAST for MDE analysis which uses Bayesian inference to identify key genes that are intuitively prioritized by means of probabilities. A simulated study revealed that our method gives a better performance when compared to other approaches and when applied to public expression data, we demonstrated its flexibility to obtain relevant genes biologically associated with normal and abnormal biological processes. ProbFAST is a free accessible web-based application that enables MDE analysis on a global scale. It offers an efficient methodological approach for MDE analysis of a set of genes that are turned on and off related to functional information during the evolution of a tumor or tissue differentiation. ProbFAST server can be accessed at http://gdm.fmrp.usp.br/probfast.

ProbFAST: Probabilistic Functional Analysis System Tool

PubMed Central

2010-01-01

Background The post-genomic era has brought new challenges regarding the understanding of the organization and function of the human genome. Many of these challenges are centered on the meaning of differential gene regulation under distinct biological conditions and can be performed by analyzing the Multiple Differential Expression (MDE) of genes associated with normal and abnormal biological processes. Currently MDE analyses are limited to usual methods of differential expression initially designed for paired analysis. Results We proposed a web platform named ProbFAST for MDE analysis which uses Bayesian inference to identify key genes that are intuitively prioritized by means of probabilities. A simulated study revealed that our method gives a better performance when compared to other approaches and when applied to public expression data, we demonstrated its flexibility to obtain relevant genes biologically associated with normal and abnormal biological processes. Conclusions ProbFAST is a free accessible web-based application that enables MDE analysis on a global scale. It offers an efficient methodological approach for MDE analysis of a set of genes that are turned on and off related to functional information during the evolution of a tumor or tissue differentiation. ProbFAST server can be accessed at http://gdm.fmrp.usp.br/probfast. PMID:20353576

Isolation, characterization, and expression analyses of tryptophan

USDA-ARS?s Scientific Manuscript database

The dek18 mutant of maize has decreased auxin content in kernels. Molecular and functional characterization of this mutant line offers the possibility to better understand auxin biology in maize seed development. Seeds of the dek18 mutants are smaller compared to wild type seeds and the vegetative d...

Genetic regulation of gene expression in the lung identifies CST3 and CD22 as potential causal genes for airflow obstruction.

PubMed

Lamontagne, Maxime; Timens, Wim; Hao, Ke; Bossé, Yohan; Laviolette, Michel; Steiling, Katrina; Campbell, Joshua D; Couture, Christian; Conti, Massimo; Sherwood, Karen; Hogg, James C; Brandsma, Corry-Anke; van den Berge, Maarten; Sandford, Andrew; Lam, Stephen; Lenburg, Marc E; Spira, Avrum; Paré, Peter D; Nickle, David; Sin, Don D; Postma, Dirkje S

2014-11-01

COPD is a complex chronic disease with poorly understood pathogenesis. Integrative genomic approaches have the potential to elucidate the biological networks underlying COPD and lung function. We recently combined genome-wide genotyping and gene expression in 1111 human lung specimens to map expression quantitative trait loci (eQTL). To determine causal associations between COPD and lung function-associated single nucleotide polymorphisms (SNPs) and lung tissue gene expression changes in our lung eQTL dataset. We evaluated causality between SNPs and gene expression for three COPD phenotypes: FEV(1)% predicted, FEV(1)/FVC and COPD as a categorical variable. Different models were assessed in the three cohorts independently and in a meta-analysis. SNPs associated with a COPD phenotype and gene expression were subjected to causal pathway modelling and manual curation. In silico analyses evaluated functional enrichment of biological pathways among newly identified causal genes. Biologically relevant causal genes were validated in two separate gene expression datasets of lung tissues and bronchial airway brushings. High reliability causal relations were found in SNP-mRNA-phenotype triplets for FEV(1)% predicted (n=169) and FEV(1)/FVC (n=80). Several genes of potential biological relevance for COPD were revealed. eQTL-SNPs upregulating cystatin C (CST3) and CD22 were associated with worse lung function. Signalling pathways enriched with causal genes included xenobiotic metabolism, apoptosis, protease-antiprotease and oxidant-antioxidant balance. By using integrative genomics and analysing the relationships of COPD phenotypes with SNPs and gene expression in lung tissue, we identified CST3 and CD22 as potential causal genes for airflow obstruction. This study also augmented the understanding of previously described COPD pathways. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Clinical, functional, behavioural and epigenomic biomarkers of obesity.

PubMed

Lafortuna, Claudio L; Tovar, Armando R; Rastelli, Fabio; Tabozzi, Sarah A; Caramenti, Martina; Orozco-Ruiz, Ximena; Aguilar-Lopez, Miriam; Guevara-Cruz, Martha; Avila-Nava, Azalia; Torres, Nimbe; Bertoli, Gloria

2017-06-01

Overweight and obesity are highly prevalent conditions worldwide, linked to an increased risk for death, disability and disease due to metabolic and biochemical abnormalities affecting the biological human system throughout different domains. Biomarkers, defined as indicators of biological processes in health and disease, relevant for body mass excess management have been identified according to different criteria, including anthropometric and molecular indexes, as well as physiological and behavioural aspects. Analysing these different biomarkers, we identified their potential role in diagnosis, prognosis and treatment. Epigenetic biomarkers, cellular mediators of inflammation and factors related to microbiota-host interactions may be considered to have a theranostic value. Though, the molecular processes responsible for the biological phenomenology detected by the other analysed markers, is not clear yet. Nevertheless, these biomarkers possess valuable diagnostic and prognostic power. A new frontier for theranostic biomarkers can be foreseen in the exploitation of parameters defining behaviours and lifestyles linked to the risk of obesity, capable to describe the effects of interventions for obesity prevention and treatment which include also behaviour change strategies.

Morphometry, geometry, function, and the future.

PubMed

Mcnulty, Kieran P; Vinyard, Christopher J

2015-01-01

The proliferation of geometric morphometrics (GM) in biological anthropology and more broadly throughout the biological sciences has resulted in a multitude of studies that adopt landmark-based approaches for addressing a variety of questions in evolutionary morphology. In some cases, particularly in the realm of systematics, the fit between research question and analytical design is quite good. Functional-adaptive studies, however, do not readily conform to the methods available in the GM toolkit. The symposium organized by Terhune and Cooke entitled "Assessing function via shape: What is the place of GM in functional morphology?" held at the 2013 meetings of the American Association of Physical Anthropologists was designed specifically to explore this relationship between landmark-based methods and analyses of functional morphology, and the articles in this special issue, which stem in large part from this symposium, provide numerous examples of how the two approaches can complement and contrast each other. Here, we underscore some of the major difficulties in interpreting GM results within a functional regime. In combination with other contributions in this issue, we identify emerging areas of research that will help bridge the gap between multivariate morphometry and functional-adaptive analysis. Ultimately, neither geometric nor functional morphometric approaches is sufficient to elaborate the adaptive pathways that explain morphological evolution through natural selection. These perspectives must be further integrated with research from physiology, developmental biology, genomics, and ecology. © 2014 Wiley Periodicals, Inc.

Chemical roots of biological evolution: the origins of life as a process of development of autonomous functional systems

PubMed Central

Ruiz-Mirazo, Kepa; Briones, Carlos

2017-01-01

In recent years, an extension of the Darwinian framework is being considered for the study of prebiotic chemical evolution, shifting the attention from homogeneous populations of naked molecular species to populations of heterogeneous, compartmentalized and functionally integrated assemblies of molecules. Several implications of this shift of perspective are analysed in this critical review, both in terms of the individual units, which require an adequate characterization as self-maintaining systems with an internal organization, and also in relation to their collective and long-term evolutionary dynamics, based on competition, collaboration and selection processes among those complex individuals. On these lines, a concrete proposal for the set of molecular control mechanisms that must be coupled to bring about autonomous functional systems, at the interface between chemistry and biology, is provided. PMID:28446711

Chemical roots of biological evolution: the origins of life as a process of development of autonomous functional systems.

PubMed

Ruiz-Mirazo, Kepa; Briones, Carlos; de la Escosura, Andrés

2017-04-01

In recent years, an extension of the Darwinian framework is being considered for the study of prebiotic chemical evolution, shifting the attention from homogeneous populations of naked molecular species to populations of heterogeneous, compartmentalized and functionally integrated assemblies of molecules. Several implications of this shift of perspective are analysed in this critical review, both in terms of the individual units, which require an adequate characterization as self-maintaining systems with an internal organization, and also in relation to their collective and long-term evolutionary dynamics, based on competition, collaboration and selection processes among those complex individuals. On these lines, a concrete proposal for the set of molecular control mechanisms that must be coupled to bring about autonomous functional systems, at the interface between chemistry and biology, is provided. © 2017 The Authors.

Reverse engineering and identification in systems biology: strategies, perspectives and challenges

PubMed Central

Villaverde, Alejandro F.; Banga, Julio R.

2014-01-01

The interplay of mathematical modelling with experiments is one of the central elements in systems biology. The aim of reverse engineering is to infer, analyse and understand, through this interplay, the functional and regulatory mechanisms of biological systems. Reverse engineering is not exclusive of systems biology and has been studied in different areas, such as inverse problem theory, machine learning, nonlinear physics, (bio)chemical kinetics, control theory and optimization, among others. However, it seems that many of these areas have been relatively closed to outsiders. In this contribution, we aim to compare and highlight the different perspectives and contributions from these fields, with emphasis on two key questions: (i) why are reverse engineering problems so hard to solve, and (ii) what methods are available for the particular problems arising from systems biology? PMID:24307566

Plant Abiotic Stress Proteomics: The Major Factors Determining Alterations in Cellular Proteome

PubMed Central

Kosová, Klára; Vítámvás, Pavel; Urban, Milan O.; Prášil, Ilja T.; Renaut, Jenny

2018-01-01

HIGHLIGHTS: Major environmental and genetic factors determining stress-related protein abundance are discussed.Major aspects of protein biological function including protein isoforms and PTMs, cellular localization and protein interactions are discussed.Functional diversity of protein isoforms and PTMs is discussed. Abiotic stresses reveal profound impacts on plant proteomes including alterations in protein relative abundance, cellular localization, post-transcriptional and post-translational modifications (PTMs), protein interactions with other protein partners, and, finally, protein biological functions. The main aim of the present review is to discuss the major factors determining stress-related protein accumulation and their final biological functions. A dynamics of stress response including stress acclimation to altered ambient conditions and recovery after the stress treatment is discussed. The results of proteomic studies aimed at a comparison of stress response in plant genotypes differing in stress adaptability reveal constitutively enhanced levels of several stress-related proteins (protective proteins, chaperones, ROS scavenging- and detoxification-related enzymes) in the tolerant genotypes with respect to the susceptible ones. Tolerant genotypes can efficiently adjust energy metabolism to enhanced needs during stress acclimation. Stress tolerance vs. stress susceptibility are relative terms which can reflect different stress-coping strategies depending on the given stress treatment. The role of differential protein isoforms and PTMs with respect to their biological functions in different physiological constraints (cellular compartments and interacting partners) is discussed. The importance of protein functional studies following high-throughput proteome analyses is presented in a broader context of plant biology. In summary, the manuscript tries to provide an overview of the major factors which have to be considered when interpreting data from proteomic studies on stress-treated plants. PMID:29472941

Evolving Relevance of Neuroproteomics in Alzheimer's Disease.

PubMed

Lista, Simone; Zetterberg, Henrik; O'Bryant, Sid E; Blennow, Kaj; Hampel, Harald

2017-01-01

Substantial progress in the understanding of the biology of Alzheimer's disease (AD) has been achieved over the past decades. The early detection and diagnosis of AD and other age-related neurodegenerative diseases, however, remain a challenging scientific frontier. Therefore, the comprehensive discovery (relating to all individual, converging or diverging biochemical disease mechanisms), development, validation, and qualification of standardized biological markers with diagnostic and prognostic functions with a precise performance profile regarding specificity, sensitivity, and positive and negative predictive value are warranted.Methodological innovations in the area of exploratory high-throughput technologies, such as sequencing, microarrays, and mass spectrometry-based analyses of proteins/peptides, have led to the generation of large global molecular datasets from a multiplicity of biological systems, such as biological fluids, cells, tissues, and organs. Such methodological progress has shifted the attention to the execution of hypothesis-independent comprehensive exploratory analyses (opposed to the classical hypothesis-driven candidate approach), with the aim of fully understanding the biological systems in physiology and disease as a whole. The systems biology paradigm integrates experimental biology with accurate and rigorous computational modelling to describe and foresee the dynamic features of biological systems. The use of dynamically evolving technological platforms, including mass spectrometry, in the area of proteomics has enabled to rush the process of biomarker discovery and validation for refining significantly the diagnosis of AD. Currently, proteomics-which is part of the systems biology paradigm-is designated as one of the dominant matured sciences needed for the effective exploratory discovery of prospective biomarker candidates expected to play an effective role in aiding the early detection, diagnosis, prognosis, and therapy development in AD.

Computation of forces from deformed visco-elastic biological tissues

NASA Astrophysics Data System (ADS)

Muñoz, José J.; Amat, David; Conte, Vito

2018-04-01

We present a least-squares based inverse analysis of visco-elastic biological tissues. The proposed method computes the set of contractile forces (dipoles) at the cell boundaries that induce the observed and quantified deformations. We show that the computation of these forces requires the regularisation of the problem functional for some load configurations that we study here. The functional measures the error of the dynamic problem being discretised in time with a second-order implicit time-stepping and in space with standard finite elements. We analyse the uniqueness of the inverse problem and estimate the regularisation parameter by means of an L-curved criterion. We apply the methodology to a simple toy problem and to an in vivo set of morphogenetic deformations of the Drosophila embryo.

Homology and phylogeny and their automated inference

NASA Astrophysics Data System (ADS)

Fuellen, Georg

2008-06-01

The analysis of the ever-increasing amount of biological and biomedical data can be pushed forward by comparing the data within and among species. For example, an integrative analysis of data from the genome sequencing projects for various species traces the evolution of the genomes and identifies conserved and innovative parts. Here, I review the foundations and advantages of this “historical” approach and evaluate recent attempts at automating such analyses. Biological data is comparable if a common origin exists (homology), as is the case for members of a gene family originating via duplication of an ancestral gene. If the family has relatives in other species, we can assume that the ancestral gene was present in the ancestral species from which all the other species evolved. In particular, describing the relationships among the duplicated biological sequences found in the various species is often possible by a phylogeny, which is more informative than homology statements. Detecting and elaborating on common origins may answer how certain biological sequences developed, and predict what sequences are in a particular species and what their function is. Such knowledge transfer from sequences in one species to the homologous sequences of the other is based on the principle of ‘my closest relative looks and behaves like I do’, often referred to as ‘guilt by association’. To enable knowledge transfer on a large scale, several automated ‘phylogenomics pipelines’ have been developed in recent years, and seven of these will be described and compared. Overall, the examples in this review demonstrate that homology and phylogeny analyses, done on a large (and automated) scale, can give insights into function in biology and biomedicine.

Global Dynamics of Proteins: Bridging Between Structure and Function

PubMed Central

Bahar, Ivet; Lezon, Timothy R.; Yang, Lee-Wei; Eyal, Eran

2010-01-01

Biomolecular systems possess unique, structure-encoded dynamic properties that underlie their biological functions. Recent studies indicate that these dynamic properties are determined to a large extent by the topology of native contacts. In recent years, elastic network models used in conjunction with normal mode analyses have proven to be useful for elucidating the collective dynamics intrinsically accessible under native state conditions, including in particular the global modes of motions that are robustly defined by the overall architecture. With increasing availability of structural data for well-studied proteins in different forms (liganded, complexed, or free), there is increasing evidence in support of the correspondence between functional changes in structures observed in experiments and the global motions predicted by these coarse-grained analyses. These observed correlations suggest that computational methods may be advantageously employed for assessing functional changes in structure and allosteric mechanisms intrinsically favored by the native fold. PMID:20192781

Global dynamics of proteins: bridging between structure and function.

PubMed

Bahar, Ivet; Lezon, Timothy R; Yang, Lee-Wei; Eyal, Eran

2010-01-01

Biomolecular systems possess unique, structure-encoded dynamic properties that underlie their biological functions. Recent studies indicate that these dynamic properties are determined to a large extent by the topology of native contacts. In recent years, elastic network models used in conjunction with normal mode analyses have proven to be useful for elucidating the collective dynamics intrinsically accessible under native state conditions, including in particular the global modes of motions that are robustly defined by the overall architecture. With increasing availability of structural data for well-studied proteins in different forms (liganded, complexed, or free), there is increasing evidence in support of the correspondence between functional changes in structures observed in experiments and the global motions predicted by these coarse-grained analyses. These observed correlations suggest that computational methods may be advantageously employed for assessing functional changes in structure and allosteric mechanisms intrinsically favored by the native fold.

Automatically visualise and analyse data on pathways using PathVisioRPC from any programming environment.

PubMed

Bohler, Anwesha; Eijssen, Lars M T; van Iersel, Martijn P; Leemans, Christ; Willighagen, Egon L; Kutmon, Martina; Jaillard, Magali; Evelo, Chris T

2015-08-23

Biological pathways are descriptive diagrams of biological processes widely used for functional analysis of differentially expressed genes or proteins. Primary data analysis, such as quality control, normalisation, and statistical analysis, is often performed in scripting languages like R, Perl, and Python. Subsequent pathway analysis is usually performed using dedicated external applications. Workflows involving manual use of multiple environments are time consuming and error prone. Therefore, tools are needed that enable pathway analysis directly within the same scripting languages used for primary data analyses. Existing tools have limited capability in terms of available pathway content, pathway editing and visualisation options, and export file formats. Consequently, making the full-fledged pathway analysis tool PathVisio available from various scripting languages will benefit researchers. We developed PathVisioRPC, an XMLRPC interface for the pathway analysis software PathVisio. PathVisioRPC enables creating and editing biological pathways, visualising data on pathways, performing pathway statistics, and exporting results in several image formats in multiple programming environments. We demonstrate PathVisioRPC functionalities using examples in Python. Subsequently, we analyse a publicly available NCBI GEO gene expression dataset studying tumour bearing mice treated with cyclophosphamide in R. The R scripts demonstrate how calls to existing R packages for data processing and calls to PathVisioRPC can directly work together. To further support R users, we have created RPathVisio simplifying the use of PathVisioRPC in this environment. We have also created a pathway module for the microarray data analysis portal ArrayAnalysis.org that calls the PathVisioRPC interface to perform pathway analysis. This module allows users to use PathVisio functionality online without having to download and install the software and exemplifies how the PathVisioRPC interface can be used by data analysis pipelines for functional analysis of processed genomics data. PathVisioRPC enables data visualisation and pathway analysis directly from within various analytical environments used for preliminary analyses. It supports the use of existing pathways from WikiPathways or pathways created using the RPC itself. It also enables automation of tasks performed using PathVisio, making it useful to PathVisio users performing repeated visualisation and analysis tasks. PathVisioRPC is freely available for academic and commercial use at http://projects.bigcat.unimaas.nl/pathvisiorpc.

Integrated in silico analyses of regulatory and metabolic networks of Synechococcus sp. PCC 7002 reveal relationships between gene centrality and essentiality

DOE PAGES

Song, Hyun-Seob; McClure, Ryan S.; Bernstein, Hans C.; ...

2015-03-27

Cyanobacteria dynamically relay environmental inputs to intracellular adaptations through a coordinated adjustment of photosynthetic efficiency and carbon processing rates. The output of such adaptations is reflected through changes in transcriptional patterns and metabolic flux distributions that ultimately define growth strategy. To address interrelationships between metabolism and regulation, we performed integrative analyses of metabolic and gene co-expression networks in a model cyanobacterium, Synechococcus sp. PCC 7002. Centrality analyses using the gene co-expression network identified a set of key genes, which were defined here as ‘topologically important.’ Parallel in silico gene knock-out simulations, using the genome-scale metabolic network, classified what we termedmore » as ‘functionally important’ genes, deletion of which affected growth or metabolism. A strong positive correlation was observed between topologically and functionally important genes. Functionally important genes exhibited variable levels of topological centrality; however, the majority of topologically central genes were found to be functionally essential for growth. Subsequent functional enrichment analysis revealed that both functionally and topologically important genes in Synechococcus sp. PCC 7002 are predominantly associated with translation and energy metabolism, two cellular processes critical for growth. This research demonstrates how synergistic network-level analyses can be used for reconciliation of metabolic and gene expression data to uncover fundamental biological principles.« less

Integrated in silico analyses of regulatory and metabolic networks of Synechococcus sp. PCC 7002 reveal relationships between gene centrality and essentiality

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

Song, Hyun-Seob; McClure, Ryan S.; Bernstein, Hans C.

Cyanobacteria dynamically relay environmental inputs to intracellular adaptations through a coordinated adjustment of photosynthetic efficiency and carbon processing rates. The output of such adaptations is reflected through changes in transcriptional patterns and metabolic flux distributions that ultimately define growth strategy. To address interrelationships between metabolism and regulation, we performed integrative analyses of metabolic and gene co-expression networks in a model cyanobacterium, Synechococcus sp. PCC 7002. Centrality analyses using the gene co-expression network identified a set of key genes, which were defined here as ‘topologically important.’ Parallel in silico gene knock-out simulations, using the genome-scale metabolic network, classified what we termedmore » as ‘functionally important’ genes, deletion of which affected growth or metabolism. A strong positive correlation was observed between topologically and functionally important genes. Functionally important genes exhibited variable levels of topological centrality; however, the majority of topologically central genes were found to be functionally essential for growth. Subsequent functional enrichment analysis revealed that both functionally and topologically important genes in Synechococcus sp. PCC 7002 are predominantly associated with translation and energy metabolism, two cellular processes critical for growth. This research demonstrates how synergistic network-level analyses can be used for reconciliation of metabolic and gene expression data to uncover fundamental biological principles.« less

A promising future for integrative biodiversity research: an increased role of scale-dependency and functional biology.

PubMed

Price, S A; Schmitz, L

2016-04-05

Studies into the complex interaction between an organism and changes to its biotic and abiotic environment are fundamental to understanding what regulates biodiversity. These investigations occur at many phylogenetic, temporal and spatial scales and within a variety of biological and geological disciplines but often in relative isolation. This issue focuses on what can be achieved when ecological mechanisms are integrated into analyses of deep-time biodiversity patterns through the union of fossil and extant data and methods. We expand upon this perspective to argue that, given its direct relevance to the current biodiversity crisis, greater integration is needed across biodiversity research. We focus on the need to understand scaling effects, how lower-level ecological and evolutionary processes scale up and vice versa, and the importance of incorporating functional biology. Placing function at the core of biodiversity research is fundamental, as it establishes how an organism interacts with its abiotic and biotic environment and it is functional diversity that ultimately determines important ecosystem processes. To achieve full integration, concerted and ongoing efforts are needed to build a united and interactive community of biodiversity researchers, with education and interdisciplinary training at its heart. © 2016 The Author(s).

A promising future for integrative biodiversity research: an increased role of scale-dependency and functional biology

PubMed Central

Schmitz, L.

2016-01-01

Studies into the complex interaction between an organism and changes to its biotic and abiotic environment are fundamental to understanding what regulates biodiversity. These investigations occur at many phylogenetic, temporal and spatial scales and within a variety of biological and geological disciplines but often in relative isolation. This issue focuses on what can be achieved when ecological mechanisms are integrated into analyses of deep-time biodiversity patterns through the union of fossil and extant data and methods. We expand upon this perspective to argue that, given its direct relevance to the current biodiversity crisis, greater integration is needed across biodiversity research. We focus on the need to understand scaling effects, how lower-level ecological and evolutionary processes scale up and vice versa, and the importance of incorporating functional biology. Placing function at the core of biodiversity research is fundamental, as it establishes how an organism interacts with its abiotic and biotic environment and it is functional diversity that ultimately determines important ecosystem processes. To achieve full integration, concerted and ongoing efforts are needed to build a united and interactive community of biodiversity researchers, with education and interdisciplinary training at its heart. PMID:26977068

Evolution of optimal Hill coefficients in nonlinear public goods games.

PubMed

Archetti, Marco; Scheuring, István

2016-10-07

In evolutionary game theory, the effect of public goods like diffusible molecules has been modelled using linear, concave, sigmoid and step functions. The observation that biological systems are often sigmoid input-output functions, as described by the Hill equation, suggests that a sigmoid function is more realistic. The Michaelis-Menten model of enzyme kinetics, however, predicts a concave function, and while mechanistic explanations of sigmoid kinetics exist, we lack an adaptive explanation: what is the evolutionary advantage of a sigmoid benefit function? We analyse public goods games in which the shape of the benefit function can evolve, in order to determine the optimal and evolutionarily stable Hill coefficients. We find that, while the dynamics depends on whether output is controlled at the level of the individual or the population, intermediate or high Hill coefficients often evolve, leading to sigmoid input-output functions that for some parameters are so steep to resemble a step function (an on-off switch). Our results suggest that, even when the shape of the benefit function is unknown, biological public goods should be modelled using a sigmoid or step function rather than a linear or concave function. Copyright © 2016 Elsevier Ltd. All rights reserved.

The W22 genome: a foundation for maize functional genomics and transposon biology

USDA-ARS?s Scientific Manuscript database

The maize W22 inbred has served as a platform for maize genetics since the mid twentieth century. To streamline maize genome analyses, we have sequenced and de novo assembled a W22 reference genome using small-read sequencing technologies. We show that significant structural heterogeneity exists in ...

Expanding the horizons of microRNA bioinformatics.

PubMed

Huntley, Rachael P; Kramarz, Barbara; Sawford, Tony; Umrao, Zara; Kalea, Anastasia Z; Acquaah, Vanessa; Martin, Maria-Jesus; Mayr, Manuel; Lovering, Ruth C

2018-06-05

MicroRNA regulation of key biological and developmental pathways is a rapidly expanding area of research, accompanied by vast amounts of experimental data. This data, however, is not widely available in bioinformatic resources, making it difficult for researchers to find and analyse microRNA-related experimental data and define further research projects. We are addressing this problem by providing two new bioinformatics datasets that contain experimentally verified functional information for mammalian microRNAs involved in cardiovascular-relevant, and other, processes. To date, our resource provides over 3,900 Gene Ontology annotations associated with almost 500 miRNAs from human, mouse and rat and over 2,200 experimentally validated miRNA:target interactions. We illustrate how this resource can be used to create miRNA-focused interaction networks with a biological context using the known biological role of miRNAs and the mRNAs they regulate, enabling discovery of associations between gene products, biological pathways and, ultimately, diseases. This data will be crucial in advancing the field of microRNA bioinformatics and will establish consistent datasets for reproducible functional analysis of microRNAs across all biological research areas. Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Peroxisome Biogenesis and Function

PubMed Central

Kaur, Navneet; Reumann, Sigrun; Hu, Jianping

2009-01-01

Peroxisomes are small and single membrane-delimited organelles that execute numerous metabolic reactions and have pivotal roles in plant growth and development. In recent years, forward and reverse genetic studies along with biochemical and cell biological analyses in Arabidopsis have enabled researchers to identify many peroxisome proteins and elucidate their functions. This review focuses on the advances in our understanding of peroxisome biogenesis and metabolism, and further explores the contribution of large-scale analysis, such as in sillco predictions and proteomics, in augmenting our knowledge of peroxisome function In Arabidopsis. PMID:22303249

Introduction to bioinformatics.

PubMed

Can, Tolga

2014-01-01

Bioinformatics is an interdisciplinary field mainly involving molecular biology and genetics, computer science, mathematics, and statistics. Data intensive, large-scale biological problems are addressed from a computational point of view. The most common problems are modeling biological processes at the molecular level and making inferences from collected data. A bioinformatics solution usually involves the following steps: Collect statistics from biological data. Build a computational model. Solve a computational modeling problem. Test and evaluate a computational algorithm. This chapter gives a brief introduction to bioinformatics by first providing an introduction to biological terminology and then discussing some classical bioinformatics problems organized by the types of data sources. Sequence analysis is the analysis of DNA and protein sequences for clues regarding function and includes subproblems such as identification of homologs, multiple sequence alignment, searching sequence patterns, and evolutionary analyses. Protein structures are three-dimensional data and the associated problems are structure prediction (secondary and tertiary), analysis of protein structures for clues regarding function, and structural alignment. Gene expression data is usually represented as matrices and analysis of microarray data mostly involves statistics analysis, classification, and clustering approaches. Biological networks such as gene regulatory networks, metabolic pathways, and protein-protein interaction networks are usually modeled as graphs and graph theoretic approaches are used to solve associated problems such as construction and analysis of large-scale networks.

BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine

NASA Astrophysics Data System (ADS)

Liu, Zhongyang; Guo, Feifei; Wang, Yong; Li, Chun; Zhang, Xinlei; Li, Honglei; Diao, Lihong; Gu, Jiangyong; Wang, Wei; Li, Dong; He, Fuchu

2016-02-01

Traditional Chinese Medicine (TCM), with a history of thousands of years of clinical practice, is gaining more and more attention and application worldwide. And TCM-based new drug development, especially for the treatment of complex diseases is promising. However, owing to the TCM’s diverse ingredients and their complex interaction with human body, it is still quite difficult to uncover its molecular mechanism, which greatly hinders the TCM modernization and internationalization. Here we developed the first online Bioinformatics Analysis Tool for Molecular mechANism of TCM (BATMAN-TCM). Its main functions include 1) TCM ingredients’ target prediction; 2) functional analyses of targets including biological pathway, Gene Ontology functional term and disease enrichment analyses; 3) the visualization of ingredient-target-pathway/disease association network and KEGG biological pathway with highlighted targets; 4) comparison analysis of multiple TCMs. Finally, we applied BATMAN-TCM to Qishen Yiqi dripping Pill (QSYQ) and combined with subsequent experimental validation to reveal the functions of renin-angiotensin system responsible for QSYQ’s cardioprotective effects for the first time. BATMAN-TCM will contribute to the understanding of the “multi-component, multi-target and multi-pathway” combinational therapeutic mechanism of TCM, and provide valuable clues for subsequent experimental validation, accelerating the elucidation of TCM’s molecular mechanism. BATMAN-TCM is available at http://bionet.ncpsb.org/batman-tcm.

BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine

PubMed Central

Liu, Zhongyang; Guo, Feifei; Wang, Yong; Li, Chun; Zhang, Xinlei; Li, Honglei; Diao, Lihong; Gu, Jiangyong; Wang, Wei; Li, Dong; He, Fuchu

2016-01-01

Traditional Chinese Medicine (TCM), with a history of thousands of years of clinical practice, is gaining more and more attention and application worldwide. And TCM-based new drug development, especially for the treatment of complex diseases is promising. However, owing to the TCM’s diverse ingredients and their complex interaction with human body, it is still quite difficult to uncover its molecular mechanism, which greatly hinders the TCM modernization and internationalization. Here we developed the first online Bioinformatics Analysis Tool for Molecular mechANism of TCM (BATMAN-TCM). Its main functions include 1) TCM ingredients’ target prediction; 2) functional analyses of targets including biological pathway, Gene Ontology functional term and disease enrichment analyses; 3) the visualization of ingredient-target-pathway/disease association network and KEGG biological pathway with highlighted targets; 4) comparison analysis of multiple TCMs. Finally, we applied BATMAN-TCM to Qishen Yiqi dripping Pill (QSYQ) and combined with subsequent experimental validation to reveal the functions of renin-angiotensin system responsible for QSYQ’s cardioprotective effects for the first time. BATMAN-TCM will contribute to the understanding of the “multi-component, multi-target and multi-pathway” combinational therapeutic mechanism of TCM, and provide valuable clues for subsequent experimental validation, accelerating the elucidation of TCM’s molecular mechanism. BATMAN-TCM is available at http://bionet.ncpsb.org/batman-tcm. PMID:26879404

MetalPDB in 2018: a database of metal sites in biological macromolecular structures.

PubMed

Putignano, Valeria; Rosato, Antonio; Banci, Lucia; Andreini, Claudia

2018-01-04

MetalPDB (http://metalweb.cerm.unifi.it/) is a database providing information on metal-binding sites detected in the three-dimensional (3D) structures of biological macromolecules. MetalPDB represents such sites as 3D templates, called Minimal Functional Sites (MFSs), which describe the local environment around the metal(s) independently of the larger context of the macromolecular structure. The 2018 update of MetalPDB includes new contents and tools. A major extension is the inclusion of proteins whose structures do not contain metal ions although their sequences potentially contain a known MFS. In addition, MetalPDB now provides extensive statistical analyses addressing several aspects of general metal usage within the PDB, across protein families and in catalysis. Users can also query MetalPDB to extract statistical information on structural aspects associated with individual metals, such as preferred coordination geometries or aminoacidic environment. A further major improvement is the functional annotation of MFSs; the annotation is manually performed via a password-protected annotator interface. At present, ∼50% of all MFSs have such a functional annotation. Other noteworthy improvements are bulk query functionality, through the upload of a list of PDB identifiers, and ftp access to MetalPDB contents, allowing users to carry out in-depth analyses on their own computational infrastructure. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Biodiversity Meets Neuroscience: From the Sequencing Ship (Ship-Seq) to Deciphering Parallel Evolution of Neural Systems in Omic's Era.

PubMed

Moroz, Leonid L

2015-12-01

The origins of neural systems and centralized brains are one of the major transitions in evolution. These events might occur more than once over 570-600 million years. The convergent evolution of neural circuits is evident from a diversity of unique adaptive strategies implemented by ctenophores, cnidarians, acoels, molluscs, and basal deuterostomes. But, further integration of biodiversity research and neuroscience is required to decipher critical events leading to development of complex integrative and cognitive functions. Here, we outline reference species and interdisciplinary approaches in reconstructing the evolution of nervous systems. In the "omic" era, it is now possible to establish fully functional genomics laboratories aboard of oceanic ships and perform sequencing and real-time analyses of data at any oceanic location (named here as Ship-Seq). In doing so, fragile, rare, cryptic, and planktonic organisms, or even entire marine ecosystems, are becoming accessible directly to experimental and physiological analyses by modern analytical tools. Thus, we are now in a position to take full advantages from countless "experiments" Nature performed for us in the course of 3.5 billion years of biological evolution. Together with progress in computational and comparative genomics, evolutionary neuroscience, proteomic and developmental biology, a new surprising picture is emerging that reveals many ways of how nervous systems evolved. As a result, this symposium provides a unique opportunity to revisit old questions about the origins of biological complexity. © The Author 2015. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Application of proteomics to ecology and population biology.

PubMed

Karr, T L

2008-02-01

Proteomics is a relatively new scientific discipline that merges protein biochemistry, genome biology and bioinformatics to determine the spatial and temporal expression of proteins in cells, tissues and whole organisms. There has been very little application of proteomics to the fields of behavioral genetics, evolution, ecology and population dynamics, and has only recently been effectively applied to the closely allied fields of molecular evolution and genetics. However, there exists considerable potential for proteomics to impact in areas related to functional ecology; this review will introduce the general concepts and methodologies that define the field of proteomics and compare and contrast the advantages and disadvantages with other methods. Examples of how proteomics can aid, complement and indeed extend the study of functional ecology will be discussed including the main tool of ecological studies, population genetics with an emphasis on metapopulation structure analysis. Because proteomic analyses provide a direct measure of gene expression, it obviates some of the limitations associated with other genomic approaches, such as microarray and EST analyses. Likewise, in conjunction with associated bioinformatics and molecular evolutionary tools, proteomics can provide the foundation of a systems-level integration approach that can enhance ecological studies. It can be envisioned that proteomics will provide important new information on issues specific to metapopulation biology and adaptive processes in nature. A specific example of the application of proteomics to sperm ageing is provided to illustrate the potential utility of the approach.

related: an R package for analysing pairwise relatedness from codominant molecular markers.

PubMed

Pew, Jack; Muir, Paul H; Wang, Jinliang; Frasier, Timothy R

2015-05-01

Analyses of pairwise relatedness represent a key component to addressing many topics in biology. However, such analyses have been limited because most available programs provide a means to estimate relatedness based on only a single estimator, making comparison across estimators difficult. Second, all programs to date have been platform specific, working only on a specific operating system. This has the undesirable outcome of making choice of relatedness estimator limited by operating system preference, rather than being based on scientific rationale. Here, we present a new R package, called related, that can calculate relatedness based on seven estimators, can account for genotyping errors, missing data and inbreeding, and can estimate 95% confidence intervals. Moreover, simulation functions are provided that allow for easy comparison of the performance of different estimators and for analyses of how much resolution to expect from a given data set. Because this package works in R, it is platform independent. Combined, this functionality should allow for more appropriate analyses and interpretation of pairwise relatedness and will also allow for the integration of relatedness data into larger R workflows. © 2014 John Wiley & Sons Ltd.

Using Cluster Analysis to Compartmentalize a Large Managed Wetland Based on Physical, Biological, and Climatic Geospatial Attributes.

PubMed

Hahus, Ian; Migliaccio, Kati; Douglas-Mankin, Kyle; Klarenberg, Geraldine; Muñoz-Carpena, Rafael

2018-04-27

Hierarchical and partitional cluster analyses were used to compartmentalize Water Conservation Area 1, a managed wetland within the Arthur R. Marshall Loxahatchee National Wildlife Refuge in southeast Florida, USA, based on physical, biological, and climatic geospatial attributes. Single, complete, average, and Ward's linkages were tested during the hierarchical cluster analyses, with average linkage providing the best results. In general, the partitional method, partitioning around medoids, found clusters that were more evenly sized and more spatially aggregated than those resulting from the hierarchical analyses. However, hierarchical analysis appeared to be better suited to identify outlier regions that were significantly different from other areas. The clusters identified by geospatial attributes were similar to clusters developed for the interior marsh in a separate study using water quality attributes, suggesting that similar factors have influenced variations in both the set of physical, biological, and climatic attributes selected in this study and water quality parameters. However, geospatial data allowed further subdivision of several interior marsh clusters identified from the water quality data, potentially indicating zones with important differences in function. Identification of these zones can be useful to managers and modelers by informing the distribution of monitoring equipment and personnel as well as delineating regions that may respond similarly to future changes in management or climate.

Bile acids: analysis in biological fluids and tissues

PubMed Central

Griffiths, William J.; Sjövall, Jan

2010-01-01

The formation of bile acids/bile alcohols is of major importance for the maintenance of cholesterol homeostasis. Besides their functions in lipid absorption, bile acids/bile alcohols are regulatory molecules for a number of metabolic processes. Their effects are structure-dependent, and numerous metabolic conversions result in a complex mixture of biologically active and inactive forms. Advanced methods are required to characterize and quantify individual bile acids in these mixtures. A combination of such analyses with analyses of the proteome will be required for a better understanding of mechanisms of action and nature of endogenous ligands. Mass spectrometry is the basic detection technique for effluents from chromatographic columns. Capillary liquid chromatography-mass spectrometry with electrospray ionization provides the highest sensitivity in metabolome analysis. Classical gas chromatography-mass spectrometry is less sensitive but offers extensive structure-dependent fragmentation increasing the specificity in analyses of isobaric isomers of unconjugated bile acids. Depending on the nature of the bile acid/bile alcohol mixture and the range of concentration of individuals, different sample preparation sequences, from simple extractions to group separations and derivatizations, are applicable. We review the methods currently available for the analysis of bile acids in biological fluids and tissues, with emphasis on the combination of liquid and gas phase chromatography with mass spectrometry. PMID:20008121

COMPADRE: an R and web resource for pathway activity analysis by component decompositions.

PubMed

Ramos-Rodriguez, Roberto-Rafael; Cuevas-Diaz-Duran, Raquel; Falciani, Francesco; Tamez-Peña, Jose-Gerardo; Trevino, Victor

2012-10-15

The analysis of biological networks has become essential to study functional genomic data. Compadre is a tool to estimate pathway/gene sets activity indexes using sub-matrix decompositions for biological networks analyses. The Compadre pipeline also includes one of the direct uses of activity indexes to detect altered gene sets. For this, the gene expression sub-matrix of a gene set is decomposed into components, which are used to test differences between groups of samples. This procedure is performed with and without differentially expressed genes to decrease false calls. During this process, Compadre also performs an over-representation test. Compadre already implements four decomposition methods [principal component analysis (PCA), Isomaps, independent component analysis (ICA) and non-negative matrix factorization (NMF)], six statistical tests (t- and f-test, SAM, Kruskal-Wallis, Welch and Brown-Forsythe), several gene sets (KEGG, BioCarta, Reactome, GO and MsigDB) and can be easily expanded. Our simulation results shown in Supplementary Information suggest that Compadre detects more pathways than over-representation tools like David, Babelomics and Webgestalt and less false positives than PLAGE. The output is composed of results from decomposition and over-representation analyses providing a more complete biological picture. Examples provided in Supplementary Information show the utility, versatility and simplicity of Compadre for analyses of biological networks. Compadre is freely available at http://bioinformatica.mty.itesm.mx:8080/compadre. The R package is also available at https://sourceforge.net/p/compadre.

Synthetic biology in the German press: how implications of metaphors shape representations of morality and responsibility.

PubMed

Döring, Martin

2018-06-24

Synthetic biology (SynBio) represents a relatively young field of research which has developed into an important scientific endeavour. Characterised by a high degree of interdisciplinary work crossing disciplinary boundaries, such as biology, mathematics and engineering, SynBio has been, since its beginning, devoted to creating new biological functions, metabolic pathways or even minimal organisms. Although its often-articulated aim of developing new forms of life has so far not been archived, SynBio nowadays represents a well-established biotechnological approach and it has also attracted public concern, especially since Craig Venter's work on Mycoplasma Mycoides JCVI-syn1.0. Taking these developments as a starting point, the paper empirically investigates the metaphorical representations of SynBio in two leading German media publications, the daily newspaper Die Frankfurter Allgemeine Zeitung and the weekly magazine Der Spiegel between 2000 and 2010. Using a novel combination of metaphor and co-occurrence analysis, the paper engages in a systematic examination of implicit moral implications inherent in linguistic images permeating this news coverage. It demonstrates a method of how media-metaphorical representations and their moral implications of SynBio could analytically be revealed and analysed. In doing so, it aims at contributing to empirical ethical analyses of the news coverage on SynBio in particular and offers an approach that methodologically adds to literature on responsible language use, which is emerging in science and technology studies and ethical analyses of new technologies.

Isolation, characterization, and expression analyses of tryptophan aminotransferase genes in a maize dek18 mutant

USDA-ARS?s Scientific Manuscript database

The dek18 mutant of maize has decreased auxin content in kernels. Molecular and functional characterization of this mutant line offers the possibility to better understand auxin biology in maize seed development. Seeds of the dek18 mutants are smaller compared to wild type seeds and the vegetative d...

Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding loci†.

PubMed

Kirsten, Holger; Al-Hasani, Hoor; Holdt, Lesca; Gross, Arnd; Beutner, Frank; Krohn, Knut; Horn, Katrin; Ahnert, Peter; Burkhardt, Ralph; Reiche, Kristin; Hackermüller, Jörg; Löffler, Markus; Teupser, Daniel; Thiery, Joachim; Scholz, Markus

2015-08-15

Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait-associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters and enrichment of co-localized functional elements. We found eQTLs for about 85% of analysed genes, and 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs; however, our data suggest that most cis-heritability of these transcripts seems explained. Dissection of co-localized functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene expression, pathways and disease-related processes. © The Author 2015. Published by Oxford University Press.

Genome-wide investigation and expression analyses of WD40 protein family in the model plant foxtail millet (Setaria italica L.).

PubMed

Mishra, Awdhesh Kumar; Muthamilarasan, Mehanathan; Khan, Yusuf; Parida, Swarup Kumar; Prasad, Manoj

2014-01-01

WD40 proteins play a crucial role in diverse protein-protein interactions by acting as scaffolding molecules and thus assisting in the proper activity of proteins. Hence, systematic characterization and expression profiling of these WD40 genes in foxtail millet would enable us to understand the networks of WD40 proteins and their biological processes and gene functions. In the present study, a genome-wide survey was conducted and 225 potential WD40 genes were identified. Phylogenetic analysis categorized the WD40 proteins into 5 distinct sub-families (I-V). Gene Ontology annotation revealed the biological roles of the WD40 proteins along with its cellular components and molecular functions. In silico comparative mapping with sorghum, maize and rice demonstrated the orthologous relationships and chromosomal rearrangements including duplication, inversion and deletion of WD40 genes. Estimation of synonymous and non-synonymous substitution rates revealed its evolutionary significance in terms of gene-duplication and divergence. Expression profiling against abiotic stresses provided novel insights into specific and/or overlapping expression patterns of SiWD40 genes. Homology modeling enabled three-dimensional structure prediction was performed to understand the molecular functions of WD40 proteins. Although, recent findings had shown the importance of WD40 domains in acting as hubs for cellular networks during many biological processes, it has invited a lesser research attention unlike other common domains. Being a most promiscuous interactors, WD40 domains are versatile in mediating critical cellular functions and hence this genome-wide study especially in the model crop foxtail millet would serve as a blue-print for functional characterization of WD40s in millets and bioenergy grass species. In addition, the present analyses would also assist the research community in choosing the candidate WD40s for comprehensive studies towards crop improvement of millets and biofuel grasses.

Genome-Wide Investigation and Expression Analyses of WD40 Protein Family in the Model Plant Foxtail Millet (Setaria italica L.)

PubMed Central

Mishra, Awdhesh Kumar; Muthamilarasan, Mehanathan; Khan, Yusuf; Parida, Swarup Kumar; Prasad, Manoj

2014-01-01

WD40 proteins play a crucial role in diverse protein-protein interactions by acting as scaffolding molecules and thus assisting in the proper activity of proteins. Hence, systematic characterization and expression profiling of these WD40 genes in foxtail millet would enable us to understand the networks of WD40 proteins and their biological processes and gene functions. In the present study, a genome-wide survey was conducted and 225 potential WD40 genes were identified. Phylogenetic analysis categorized the WD40 proteins into 5 distinct sub-families (I–V). Gene Ontology annotation revealed the biological roles of the WD40 proteins along with its cellular components and molecular functions. In silico comparative mapping with sorghum, maize and rice demonstrated the orthologous relationships and chromosomal rearrangements including duplication, inversion and deletion of WD40 genes. Estimation of synonymous and non-synonymous substitution rates revealed its evolutionary significance in terms of gene-duplication and divergence. Expression profiling against abiotic stresses provided novel insights into specific and/or overlapping expression patterns of SiWD40 genes. Homology modeling enabled three-dimensional structure prediction was performed to understand the molecular functions of WD40 proteins. Although, recent findings had shown the importance of WD40 domains in acting as hubs for cellular networks during many biological processes, it has invited a lesser research attention unlike other common domains. Being a most promiscuous interactors, WD40 domains are versatile in mediating critical cellular functions and hence this genome-wide study especially in the model crop foxtail millet would serve as a blue-print for functional characterization of WD40s in millets and bioenergy grass species. In addition, the present analyses would also assist the research community in choosing the candidate WD40s for comprehensive studies towards crop improvement of millets and biofuel grasses. PMID:24466268

An interactive web-tool for molecular analyses links naturally occurring mutation data with three-dimensional structures of the rhodopsin-like glycoprotein hormone receptors.

PubMed

Kleinau, Gunnar; Kreuchwig, Annika; Worth, Catherine L; Krause, Gerd

2010-06-01

The collection, description and molecular analysis of naturally occurring (pathogenic) mutations are important for understanding the functional mechanisms and malfunctions of biological units such as proteins. Numerous databases collate a huge amount of functional data or descriptions of mutations, but tools to analyse the molecular effects of genetic variations are as yet poorly provided. The goal of this work was therefore to develop a translational web-application that facilitates the interactive linkage of functional and structural data and which helps improve our understanding of the molecular basis of naturally occurring gain- or loss- of function mutations. Here we focus on the human glycoprotein hormone receptors (GPHRs), for which a huge number of mutations are known to cause diseases. We describe new options for interactive data analyses within three-dimensional structures, which enable the assignment of molecular relationships between structure and function. Strikingly, as the functional data are converted into relational percentage values, the system allows the comparison and classification of data from different GPHR subtypes and different experimental approaches. Our new application has been incorporated into a freely available database and website for the GPHRs (http://www.ssfa-gphr.de), but the principle development would also be applicable to other macromolecules.

A Biomechanical Analysis Of Craniofacial Form And Function

NASA Astrophysics Data System (ADS)

Oyen, Ordean J.

1989-04-01

In vivo measures of bite force and bone strain obtained in growing African green monkeys (Cercopeithecus aethiops) are being used to study skull biology and geometry. Strain values and distributional patterns seen in association with forceful jaw elevation are inconsistent with conventional explanations linking upper facial morphology with masticatory function and/or using beam models of craniofacial architecture. These results mandate careful use of notions about skeletal geometry based on static analyses that have not been experimentally verified using in vivo procedures.

Relating genes to function: identifying enriched transcription factors using the ENCODE ChIP-Seq significance tool.

PubMed

Auerbach, Raymond K; Chen, Bin; Butte, Atul J

2013-08-01

Biological analysis has shifted from identifying genes and transcripts to mapping these genes and transcripts to biological functions. The ENCODE Project has generated hundreds of ChIP-Seq experiments spanning multiple transcription factors and cell lines for public use, but tools for a biomedical scientist to analyze these data are either non-existent or tailored to narrow biological questions. We present the ENCODE ChIP-Seq Significance Tool, a flexible web application leveraging public ENCODE data to identify enriched transcription factors in a gene or transcript list for comparative analyses. The ENCODE ChIP-Seq Significance Tool is written in JavaScript on the client side and has been tested on Google Chrome, Apple Safari and Mozilla Firefox browsers. Server-side scripts are written in PHP and leverage R and a MySQL database. The tool is available at http://encodeqt.stanford.edu. abutte@stanford.edu Supplementary material is available at Bioinformatics online.

ISAAC - InterSpecies Analysing Application using Containers.

PubMed

Baier, Herbert; Schultz, Jörg

2014-01-15

Information about genes, transcripts and proteins is spread over a wide variety of databases. Different tools have been developed using these databases to identify biological signals in gene lists from large scale analysis. Mostly, they search for enrichments of specific features. But, these tools do not allow an explorative walk through different views and to change the gene lists according to newly upcoming stories. To fill this niche, we have developed ISAAC, the InterSpecies Analysing Application using Containers. The central idea of this web based tool is to enable the analysis of sets of genes, transcripts and proteins under different biological viewpoints and to interactively modify these sets at any point of the analysis. Detailed history and snapshot information allows tracing each action. Furthermore, one can easily switch back to previous states and perform new analyses. Currently, sets can be viewed in the context of genomes, protein functions, protein interactions, pathways, regulation, diseases and drugs. Additionally, users can switch between species with an automatic, orthology based translation of existing gene sets. As todays research usually is performed in larger teams and consortia, ISAAC provides group based functionalities. Here, sets as well as results of analyses can be exchanged between members of groups. ISAAC fills the gap between primary databases and tools for the analysis of large gene lists. With its highly modular, JavaEE based design, the implementation of new modules is straight forward. Furthermore, ISAAC comes with an extensive web-based administration interface including tools for the integration of third party data. Thus, a local installation is easily feasible. In summary, ISAAC is tailor made for highly explorative interactive analyses of gene, transcript and protein sets in a collaborative environment.

Potential biomarkers of ageing.

PubMed

Simm, Andreas; Nass, Norbert; Bartling, Babett; Hofmann, Britt; Silber, Rolf-Edgar; Navarrete Santos, Alexander

2008-03-01

Life span in individual humans is very heterogeneous.Thus, the ageing rate, measured as the decline of functional capacity and stress resistance, is different in every individual. There have been attempts made to analyse this individual age, the so-called biological age, in comparison to chronological age. Biomarkers of ageing should help to characterise this biological age and, as age is a major risk factor in many degenerative diseases,could be subsequently used to identify individuals at high risk of developing age-associated diseases or disabilities. Markers based on oxidative stress, protein glycation,inflammation, cellular senescence and hormonal deregulation are discussed.

Functional Proteomic Analysis of Human NucleolusD⃞

PubMed Central

Scherl, Alexander; Couté, Yohann; Déon, Catherine; Callé, Aleth; Kindbeiter, Karine; Sanchez, Jean-Charles; Greco, Anna; Hochstrasser, Denis; Diaz, Jean-Jacques

2002-01-01

The notion of a “plurifunctional” nucleolus is now well established. However, molecular mechanisms underlying the biological processes occurring within this nuclear domain remain only partially understood. As a first step in elucidating these mechanisms we have carried out a proteomic analysis to draw up a list of proteins present within nucleoli of HeLa cells. This analysis allowed the identification of 213 different nucleolar proteins. This catalog complements that of the 271 proteins obtained recently by others, giving a total of ∼350 different nucleolar proteins. Functional classification of these proteins allowed outlining several biological processes taking place within nucleoli. Bioinformatic analyses permitted the assignment of hypothetical functions for 43 proteins for which no functional information is available. Notably, a role in ribosome biogenesis was proposed for 31 proteins. More generally, this functional classification reinforces the plurifunctional nature of nucleoli and provides convincing evidence that nucleoli may play a central role in the control of gene expression. Finally, this analysis supports the recent demonstration of a coupling of transcription and translation in higher eukaryotes. PMID:12429849

Genomewide effects of peroxisome proliferator-activated receptor gamma in macrophages and dendritic cells--revealing complexity through systems biology.

PubMed

Cuaranta-Monroy, Ixchelt; Kiss, Mate; Simandi, Zoltan; Nagy, Laszlo

2015-09-01

Systems biology approaches have become indispensable tools in biomedical and basic research. These data integrating bioinformatic methods gained prominence after high-throughput technologies became available to investigate complex cellular processes, such as transcriptional regulation and protein-protein interactions, on a scale that had not been studied before. Immunology is one of the medical fields that systems biology impacted profoundly due to the plasticity of cell types involved and the accessibility of a wide range of experimental models. In this review, we summarize the most important recent genomewide studies exploring the function of peroxisome proliferator-activated receptor γ in macrophages and dendritic cells. PPARγ ChIP-seq experiments were performed in adipocytes derived from embryonic stem cells to complement the existing data sets and to provide comparators to macrophage data. Finally, lists of regulated genes generated from such experiments were analysed with bioinformatics and system biology approaches. We show that genomewide studies utilizing high-throughput data acquisition methods made it possible to gain deeper insights into the role of PPARγ in these immune cell types. We also demonstrate that analysis and visualization of data using network-based approaches can be used to identify novel genes and functions regulated by the receptor. The example of PPARγ in macrophages and dendritic cells highlights the crucial importance of systems biology approaches in establishing novel cellular functions for long-known signaling pathways. © 2015 Stichting European Society for Clinical Investigation Journal Foundation.

Multiple Multi-Copper Oxidase Gene Families in Basidiomycetes – What for?

PubMed Central

Kües, Ursula; Rühl, Martin

2011-01-01

Genome analyses revealed in various basidiomycetes the existence of multiple genes for blue multi-copper oxidases (MCOs). Whole genomes are now available from saprotrophs, white rot and brown rot species, plant and animal pathogens and ectomycorrhizal species. Total numbers (from 1 to 17) and types of mco genes differ between analyzed species with no easy to recognize connection of gene distribution to fungal life styles. Types of mco genes might be present in one and absent in another fungus. Distinct types of genes have been multiplied at speciation in different organisms. Phylogenetic analysis defined different subfamilies of laccases sensu stricto (specific to Agaricomycetes), classical Fe2+-oxidizing Fet3-like ferroxidases, potential ferroxidases/laccases exhibiting either one or both of these enzymatic functions, enzymes clustering with pigment MCOs and putative ascorbate oxidases. Biochemically best described are laccases sensu stricto due to their proposed roles in degradation of wood, straw and plant litter and due to the large interest in these enzymes in biotechnology. However, biological functions of laccases and other MCOs are generally little addressed. Functions in substrate degradation, symbiontic and pathogenic intercations, development, pigmentation and copper homeostasis have been put forward. Evidences for biological functions are in most instances rather circumstantial by correlations of expression. Multiple factors impede research on biological functions such as difficulties of defining suitable biological systems for molecular research, the broad and overlapping substrate spectrum multi-copper oxidases usually possess, the low existent knowledge on their natural substrates, difficulties imposed by low expression or expression of multiple enzymes, and difficulties in expressing enzymes heterologously. PMID:21966246

SorghumFDB: sorghum functional genomics database with multidimensional network analysis.

PubMed

Tian, Tian; You, Qi; Zhang, Liwei; Yi, Xin; Yan, Hengyu; Xu, Wenying; Su, Zhen

2016-01-01

Sorghum (Sorghum bicolor [L.] Moench) has excellent agronomic traits and biological properties, such as heat and drought-tolerance. It is a C4 grass and potential bioenergy-producing plant, which makes it an important crop worldwide. With the sorghum genome sequence released, it is essential to establish a sorghum functional genomics data mining platform. We collected genomic data and some functional annotations to construct a sorghum functional genomics database (SorghumFDB). SorghumFDB integrated knowledge of sorghum gene family classifications (transcription regulators/factors, carbohydrate-active enzymes, protein kinases, ubiquitins, cytochrome P450, monolignol biosynthesis related enzymes, R-genes and organelle-genes), detailed gene annotations, miRNA and target gene information, orthologous pairs in the model plants Arabidopsis, rice and maize, gene loci conversions and a genome browser. We further constructed a dynamic network of multidimensional biological relationships, comprised of the co-expression data, protein-protein interactions and miRNA-target pairs. We took effective measures to combine the network, gene set enrichment and motif analyses to determine the key regulators that participate in related metabolic pathways, such as the lignin pathway, which is a major biological process in bioenergy-producing plants.Database URL: http://structuralbiology.cau.edu.cn/sorghum/index.html. © The Author(s) 2016. Published by Oxford University Press.

Biological roles and functional mechanisms of arenavirus Z protein in viral replication.

PubMed

Wang, Jialong; Danzy, Shamika; Kumar, Naveen; Ly, Hinh; Liang, Yuying

2012-09-01

Arenaviruses can cause severe hemorrhagic fever diseases in humans, with limited prophylactic or therapeutic measures. A small RING-domain viral protein Z has been shown to mediate the formation of virus-like particles and to inhibit viral RNA synthesis, although its biological roles in an infectious viral life cycle have not been directly addressed. By taking advantage of the available reverse genetics system for a model arenavirus, Pichinde virus (PICV), we provide the direct evidence for the essential biological roles of the Z protein's conserved residues, including the G2 myristylation site, the conserved C and H residues of RING domain, and the poorly characterized C-terminal L79 and P80 residues. Dicodon substitutions within the late (L) domain (PSAPPYEP) of the PICV Z protein, although producing viable mutant viruses, have significantly reduced virus growth, a finding suggestive of an important role for the intact L domain in viral replication. Further structure-function analyses of both PICV and Lassa fever virus Z proteins suggest that arenavirus Z proteins have similar molecular mechanisms in mediating their multiple functions, with some interesting variations, such as the role of the G2 residue in blocking viral RNA synthesis. In summary, our studies have characterized the biological roles of the Z protein in an infectious arenavirus system and have shed important light on the distinct functions of its domains in virus budding and viral RNA regulation, the knowledge of which may lead to the development of novel antiviral drugs.

Molecular phenology in plants: in natura systems biology for the comprehensive understanding of seasonal responses under natural environments.

PubMed

Kudoh, Hiroshi

2016-04-01

Phenology refers to the study of seasonal schedules of organisms. Molecular phenology is defined here as the study of the seasonal patterns of organisms captured by molecular biology techniques. The history of molecular phenology is reviewed briefly in relation to advances in the quantification technology of gene expression. High-resolution molecular phenology (HMP) data have enabled us to study phenology with an approach of in natura systems biology. I review recent analyses of FLOWERING LOCUS C (FLC), a temperature-responsive repressor of flowering, along the six steps in the typical flow of in natura systems biology. The extensive studies of the regulation of FLC have made this example a successful case in which a comprehensive understanding of gene functions has been progressing. The FLC-mediated long-term memory of past temperatures creates time lags with other seasonal signals, such as photoperiod and short-term temperature. Major signals that control flowering time have a phase lag between them under natural conditions, and hypothetical phase lag calendars are proposed as mechanisms of season detection in plants. Transcriptomic HMP brings a novel strategy to the study of molecular phenology, because it provides a comprehensive representation of plant functions. I discuss future perspectives of molecular phenology from the standpoints of molecular biology, evolutionary biology and ecology. © 2015 The Author. New Phytologist © 2015 New Phytologist Trust.

Event-based text mining for biology and functional genomics

PubMed Central

Thompson, Paul; Nawaz, Raheel; McNaught, John; Kell, Douglas B.

2015-01-01

The assessment of genome function requires a mapping between genome-derived entities and biochemical reactions, and the biomedical literature represents a rich source of information about reactions between biological components. However, the increasingly rapid growth in the volume of literature provides both a challenge and an opportunity for researchers to isolate information about reactions of interest in a timely and efficient manner. In response, recent text mining research in the biology domain has been largely focused on the identification and extraction of ‘events’, i.e. categorised, structured representations of relationships between biochemical entities, from the literature. Functional genomics analyses necessarily encompass events as so defined. Automatic event extraction systems facilitate the development of sophisticated semantic search applications, allowing researchers to formulate structured queries over extracted events, so as to specify the exact types of reactions to be retrieved. This article provides an overview of recent research into event extraction. We cover annotated corpora on which systems are trained, systems that achieve state-of-the-art performance and details of the community shared tasks that have been instrumental in increasing the quality, coverage and scalability of recent systems. Finally, several concrete applications of event extraction are covered, together with emerging directions of research. PMID:24907365

DNA Hypomethylation Affects Cancer-Related Biological Functions and Genes Relevant in Neuroblastoma Pathogenesis

PubMed Central

Mayol, Gemma; Martín-Subero, José I.; Ríos, José; Queiros, Ana; Kulis, Marta; Suñol, Mariona; Esteller, Manel; Gómez, Soledad; Garcia, Idoia; de Torres, Carmen; Rodríguez, Eva; Galván, Patricia; Mora, Jaume; Lavarino, Cinzia

2012-01-01

Neuroblastoma (NB) pathogenesis has been reported to be closely associated with numerous genetic alterations. However, underlying DNA methylation patterns have not been extensively studied in this developmental malignancy. Here, we generated microarray-based DNA methylation profiles of primary neuroblastic tumors. Stringent supervised differential methylation analyses allowed us to identify epigenetic changes characteristic for NB tumors as well as for clinical and biological subtypes of NB. We observed that gene-specific loss of DNA methylation is more prevalent than promoter hypermethylation. Remarkably, such hypomethylation affected cancer-related biological functions and genes relevant to NB pathogenesis such as CCND1, SPRR3, BTC, EGF and FGF6. In particular, differential methylation in CCND1 affected mostly an evolutionary conserved functionally relevant 3′ untranslated region, suggesting that hypomethylation outside promoter regions may play a role in NB pathogenesis. Hypermethylation targeted genes involved in cell development and proliferation such as RASSF1A, POU2F2 or HOXD3, among others. The results derived from this study provide new candidate epigenetic biomarkers associated with NB as well as insights into the molecular pathogenesis of this tumor, which involves a marked gene-specific hypomethylation. PMID:23144874

The Center for Computational Biology: resources, achievements, and challenges

PubMed Central

Dinov, Ivo D; Thompson, Paul M; Woods, Roger P; Van Horn, John D; Shattuck, David W; Parker, D Stott

2011-01-01

The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains. PMID:22081221

The Center for Computational Biology: resources, achievements, and challenges.

PubMed

Toga, Arthur W; Dinov, Ivo D; Thompson, Paul M; Woods, Roger P; Van Horn, John D; Shattuck, David W; Parker, D Stott

2012-01-01

The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains.

Identifying gene networks underlying the neurobiology of ethanol and alcoholism.

PubMed

Wolen, Aaron R; Miles, Michael F

2012-01-01

For complex disorders such as alcoholism, identifying the genes linked to these diseases and their specific roles is difficult. Traditional genetic approaches, such as genetic association studies (including genome-wide association studies) and analyses of quantitative trait loci (QTLs) in both humans and laboratory animals already have helped identify some candidate genes. However, because of technical obstacles, such as the small impact of any individual gene, these approaches only have limited effectiveness in identifying specific genes that contribute to complex diseases. The emerging field of systems biology, which allows for analyses of entire gene networks, may help researchers better elucidate the genetic basis of alcoholism, both in humans and in animal models. Such networks can be identified using approaches such as high-throughput molecular profiling (e.g., through microarray-based gene expression analyses) or strategies referred to as genetical genomics, such as the mapping of expression QTLs (eQTLs). Characterization of gene networks can shed light on the biological pathways underlying complex traits and provide the functional context for identifying those genes that contribute to disease development.

Phylogeny and evolution of plant cyclic nucleotide-gated ion channel (CNGC) gene family and functional analyses of tomato CNGCs

PubMed Central

Saand, Mumtaz Ali; Xu, You-Ping; Munyampundu, Jean-Pierre; Li, Wen; Zhang, Xuan-Rui; Cai, Xin-Zhong

2015-01-01

Cyclic nucleotide-gated ion channels (CNGCs) are calcium-permeable channels that are involved in various biological functions. Nevertheless, phylogeny and function of plant CNGCs are not well understood. In this study, 333 CNGC genes from 15 plant species were identified using comprehensive bioinformatics approaches. Extensive bioinformatics analyses demonstrated that CNGCs of Group IVa were distinct to those of other groups in gene structure and amino acid sequence of cyclic nucleotide-binding domain. A CNGC-specific motif that recognizes all identified plant CNGCs was generated. Phylogenetic analysis indicated that CNGC proteins of flowering plant species formed five groups. However, CNGCs of the non-vascular plant Physcomitrella patens clustered only in two groups (IVa and IVb), while those of the vascular non-flowering plant Selaginella moellendorffii gathered in four (IVa, IVb, I and II). These data suggest that Group IV CNGCs are most ancient and Group III CNGCs are most recently evolved in flowering plants. Furthermore, silencing analyses revealed that a set of CNGC genes might be involved in disease resistance and abiotic stress responses in tomato and function of SlCNGCs does not correlate with the group that they are belonging to. Our results indicate that Group IVa CNGCs are structurally but not functionally unique among plant CNGCs. PMID:26546226

'PACLIMS': a component LIM system for high-throughput functional genomic analysis.

PubMed

Donofrio, Nicole; Rajagopalon, Ravi; Brown, Douglas; Diener, Stephen; Windham, Donald; Nolin, Shelly; Floyd, Anna; Mitchell, Thomas; Galadima, Natalia; Tucker, Sara; Orbach, Marc J; Patel, Gayatri; Farman, Mark; Pampanwar, Vishal; Soderlund, Cari; Lee, Yong-Hwan; Dean, Ralph A

2005-04-12

Recent advances in sequencing techniques leading to cost reduction have resulted in the generation of a growing number of sequenced eukaryotic genomes. Computational tools greatly assist in defining open reading frames and assigning tentative annotations. However, gene functions cannot be asserted without biological support through, among other things, mutational analysis. In taking a genome-wide approach to functionally annotate an entire organism, in this application the approximately 11,000 predicted genes in the rice blast fungus (Magnaporthe grisea), an effective platform for tracking and storing both the biological materials created and the data produced across several participating institutions was required. The platform designed, named PACLIMS, was built to support our high throughput pipeline for generating 50,000 random insertion mutants of Magnaporthe grisea. To be a useful tool for materials and data tracking and storage, PACLIMS was designed to be simple to use, modifiable to accommodate refinement of research protocols, and cost-efficient. Data entry into PACLIMS was simplified through the use of barcodes and scanners, thus reducing the potential human error, time constraints, and labor. This platform was designed in concert with our experimental protocol so that it leads the researchers through each step of the process from mutant generation through phenotypic assays, thus ensuring that every mutant produced is handled in an identical manner and all necessary data is captured. Many sequenced eukaryotes have reached the point where computational analyses are no longer sufficient and require biological support for their predicted genes. Consequently, there is an increasing need for platforms that support high throughput genome-wide mutational analyses. While PACLIMS was designed specifically for this project, the source and ideas present in its implementation can be used as a model for other high throughput mutational endeavors.

'PACLIMS': A component LIM system for high-throughput functional genomic analysis

PubMed Central

Donofrio, Nicole; Rajagopalon, Ravi; Brown, Douglas; Diener, Stephen; Windham, Donald; Nolin, Shelly; Floyd, Anna; Mitchell, Thomas; Galadima, Natalia; Tucker, Sara; Orbach, Marc J; Patel, Gayatri; Farman, Mark; Pampanwar, Vishal; Soderlund, Cari; Lee, Yong-Hwan; Dean, Ralph A

2005-01-01

Background Recent advances in sequencing techniques leading to cost reduction have resulted in the generation of a growing number of sequenced eukaryotic genomes. Computational tools greatly assist in defining open reading frames and assigning tentative annotations. However, gene functions cannot be asserted without biological support through, among other things, mutational analysis. In taking a genome-wide approach to functionally annotate an entire organism, in this application the ~11,000 predicted genes in the rice blast fungus (Magnaporthe grisea), an effective platform for tracking and storing both the biological materials created and the data produced across several participating institutions was required. Results The platform designed, named PACLIMS, was built to support our high throughput pipeline for generating 50,000 random insertion mutants of Magnaporthe grisea. To be a useful tool for materials and data tracking and storage, PACLIMS was designed to be simple to use, modifiable to accommodate refinement of research protocols, and cost-efficient. Data entry into PACLIMS was simplified through the use of barcodes and scanners, thus reducing the potential human error, time constraints, and labor. This platform was designed in concert with our experimental protocol so that it leads the researchers through each step of the process from mutant generation through phenotypic assays, thus ensuring that every mutant produced is handled in an identical manner and all necessary data is captured. Conclusion Many sequenced eukaryotes have reached the point where computational analyses are no longer sufficient and require biological support for their predicted genes. Consequently, there is an increasing need for platforms that support high throughput genome-wide mutational analyses. While PACLIMS was designed specifically for this project, the source and ideas present in its implementation can be used as a model for other high throughput mutational endeavors. PMID:15826298

A toolbox for discrete modelling of cell signalling dynamics.

PubMed

Paterson, Yasmin Z; Shorthouse, David; Pleijzier, Markus W; Piterman, Nir; Bendtsen, Claus; Hall, Benjamin A; Fisher, Jasmin

2018-06-18

In an age where the volume of data regarding biological systems exceeds our ability to analyse it, many researchers are looking towards systems biology and computational modelling to help unravel the complexities of gene and protein regulatory networks. In particular, the use of discrete modelling allows generation of signalling networks in the absence of full quantitative descriptions of systems, which are necessary for ordinary differential equation (ODE) models. In order to make such techniques more accessible to mainstream researchers, tools such as the BioModelAnalyzer (BMA) have been developed to provide a user-friendly graphical interface for discrete modelling of biological systems. Here we use the BMA to build a library of discrete target functions of known canonical molecular interactions, translated from ordinary differential equations (ODEs). We then show that these BMA target functions can be used to reconstruct complex networks, which can correctly predict many known genetic perturbations. This new library supports the accessibility ethos behind the creation of BMA, providing a toolbox for the construction of complex cell signalling models without the need for extensive experience in computer programming or mathematical modelling, and allows for construction and simulation of complex biological systems with only small amounts of quantitative data.

A-DaGO-Fun: an adaptable Gene Ontology semantic similarity-based functional analysis tool.

PubMed

Mazandu, Gaston K; Chimusa, Emile R; Mbiyavanga, Mamana; Mulder, Nicola J

2016-02-01

Gene Ontology (GO) semantic similarity measures are being used for biological knowledge discovery based on GO annotations by integrating biological information contained in the GO structure into data analyses. To empower users to quickly compute, manipulate and explore these measures, we introduce A-DaGO-Fun (ADaptable Gene Ontology semantic similarity-based Functional analysis). It is a portable software package integrating all known GO information content-based semantic similarity measures and relevant biological applications associated with these measures. A-DaGO-Fun has the advantage not only of handling datasets from the current high-throughput genome-wide applications, but also allowing users to choose the most relevant semantic similarity approach for their biological applications and to adapt a given module to their needs. A-DaGO-Fun is freely available to the research community at http://web.cbio.uct.ac.za/ITGOM/adagofun. It is implemented in Linux using Python under free software (GNU General Public Licence). gmazandu@cbio.uct.ac.za or Nicola.Mulder@uct.ac.za Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Evolving Concepts and Translational Relevance of Enteroendocrine Cell Biology.

PubMed

Drucker, Daniel J

2016-03-01

Classical enteroenteroendocrine cell (EEC) biology evolved historically from identification of scattered hormone-producing endocrine cells within the epithelial mucosa of the stomach, small and large intestine. Purification of functional EEC hormones from intestinal extracts, coupled with molecular cloning of cDNAs and genes expressed within EECs has greatly expanded the complexity of EEC endocrinology, with implications for understanding the contribution of EECs to disease pathophysiology. Pubmed searches identified manuscripts highlighting new concepts illuminating the molecular biology, classification and functional role(s) of EECs and their hormonal products. Molecular interrogation of EECs has been transformed over the past decade, raising multiple new questions that challenge historical concepts of EEC biology. Evidence for evolution of the EEC from a unihormonal cell type with classical endocrine actions, to a complex plurihormonal dynamic cell with pleiotropic interactive functional networks within the gastrointestinal mucosa is critically assessed. We discuss gaps in understanding how EECs sense and respond to nutrients, cytokines, toxins, pathogens, the microbiota, and the microbial metabolome, and highlight the expanding translational relevance of EECs in the pathophysiology and therapy of metabolic and inflammatory disorders. The EEC system represents the largest specialized endocrine network in human physiology, integrating environmental and nutrient cues, enabling neural and hormonal control of metabolic homeostasis. Updating EEC classification systems will enable more accurate comparative analyses of EEC subpopulations and endocrine networks in multiple regions of the gastrointestinal tract.

Bio-logging of physiological parameters in higher marine vertebrates

NASA Astrophysics Data System (ADS)

Ponganis, Paul J.

2007-02-01

Bio-logging of physiological parameters in higher marine vertebrates had its origins in the field of bio-telemetry in the 1960s and 1970s. The development of microprocessor technology allowed its first application to bio-logging investigations of Weddell seal diving physiology in the early 1980s. Since that time, with the use of increased memory capacity, new sensor technology, and novel data processing techniques, investigators have examined heart rate, temperature, swim speed, stroke frequency, stomach function (gastric pH and motility), heat flux, muscle oxygenation, respiratory rate, diving air volume, and oxygen partial pressure (P) during diving. Swim speed, heart rate, and body temperature have been the most commonly studied parameters. Bio-logging investigation of pressure effects has only been conducted with the use of blood samplers and nitrogen analyses on animals diving at isolated dive holes. The advantages/disadvantages and limitations of recording techniques, probe placement, calibration techniques, and study conditions are reviewed.

Perception of Life as Stressful, not Biological Response to Stress, is Associated with Greater Social Disability in Adults with Autism Spectrum Disorder

PubMed Central

Bishop-Fitzpatrick, Lauren; Minshew, Nancy J.; Mazefsky, Carla A.; Eack, Shaun M.

2016-01-01

This study examined differences between adults with autism spectrum disorder (ASD; N=40) and typical community volunteers (N=25) on measures of stressful life events, perceived stress, and biological stress response (cardiovascular and cortisol reactivity) during a novel social stress task. Additional analyses examined the relationship between stress and social functioning as measured by the Social Adjustment Scale-II and the Waisman Activities of Daily Living scale. Results indicated that adults with ASD experienced significantly more stressful life events and perceived stress, and greater systolic blood pressure reactivity than typical community volunteers. Results also indicated that perceived stress and stressful life events were significantly associated with social disability. Interventions targeting stress management might improve social function in adults with ASD. PMID:27696184

Perception of Life as Stressful, Not Biological Response to Stress, is Associated with Greater Social Disability in Adults with Autism Spectrum Disorder.

PubMed

Bishop-Fitzpatrick, Lauren; Minshew, Nancy J; Mazefsky, Carla A; Eack, Shaun M

2017-01-01

This study examined differences between adults with autism spectrum disorder (ASD; N = 40) and typical community volunteers (N = 25) on measures of stressful life events, perceived stress, and biological stress response (cardiovascular and cortisol reactivity) during a novel social stress task. Additional analyses examined the relationship between stress and social functioning as measured by the Social Adjustment Scale-II and the Waisman Activities of Daily Living scale. Results indicated that adults with ASD experienced significantly more stressful life events and perceived stress, and greater systolic blood pressure reactivity than typical community volunteers. Results also indicated that perceived stress and stressful life events were significantly associated with social disability. Interventions targeting stress management might improve social function in adults with ASD.

Using coordinate-based meta-analyses to explore structural imaging genetics.

PubMed

Janouschek, Hildegard; Eickhoff, Claudia R; Mühleisen, Thomas W; Eickhoff, Simon B; Nickl-Jockschat, Thomas

2018-05-05

Imaging genetics has become a highly popular approach in the field of schizophrenia research. A frequently reported finding is that effects from common genetic variation are associated with a schizophrenia-related structural endophenotype. Genetic contributions to a structural endophenotype may be easier to delineate, when referring to biological rather than diagnostic criteria. We used coordinate-based meta-analyses, namely the anatomical likelihood estimation (ALE) algorithm on 30 schizophrenia-related imaging genetics studies, representing 44 single-nucleotide polymorphisms at 26 gene loci investigated in 4682 subjects. To test whether analyses based on biological information would improve the convergence of results, gene ontology (GO) terms were used to group the findings from the published studies. We did not find any significant results for the main contrast. However, our analysis enrolling studies on genotype × diagnosis interaction yielded two clusters in the left temporal lobe and the medial orbitofrontal cortex. All other subanalyses did not yield any significant results. To gain insight into possible biological relationships between the genes implicated by these clusters, we mapped five of them to GO terms of the category "biological process" (AKT1, CNNM2, DISC1, DTNBP1, VAV3), then five to "cellular component" terms (AKT1, CNNM2, DISC1, DTNBP1, VAV3), and three to "molecular function" terms (AKT1, VAV3, ZNF804A). A subsequent cluster analysis identified representative, non-redundant subsets of semantically similar terms that aided a further interpretation. We regard this approach as a new option to systematically explore the richness of the literature in imaging genetics.

Biodiversity Meets Neuroscience: From the Sequencing Ship (Ship-Seq) to Deciphering Parallel Evolution of Neural Systems in Omic’s Era

PubMed Central

Moroz, Leonid L.

2015-01-01

The origins of neural systems and centralized brains are one of the major transitions in evolution. These events might occur more than once over 570–600 million years. The convergent evolution of neural circuits is evident from a diversity of unique adaptive strategies implemented by ctenophores, cnidarians, acoels, molluscs, and basal deuterostomes. But, further integration of biodiversity research and neuroscience is required to decipher critical events leading to development of complex integrative and cognitive functions. Here, we outline reference species and interdisciplinary approaches in reconstructing the evolution of nervous systems. In the “omic” era, it is now possible to establish fully functional genomics laboratories aboard of oceanic ships and perform sequencing and real-time analyses of data at any oceanic location (named here as Ship-Seq). In doing so, fragile, rare, cryptic, and planktonic organisms, or even entire marine ecosystems, are becoming accessible directly to experimental and physiological analyses by modern analytical tools. Thus, we are now in a position to take full advantages from countless “experiments” Nature performed for us in the course of 3.5 billion years of biological evolution. Together with progress in computational and comparative genomics, evolutionary neuroscience, proteomic and developmental biology, a new surprising picture is emerging that reveals many ways of how nervous systems evolved. As a result, this symposium provides a unique opportunity to revisit old questions about the origins of biological complexity. PMID:26163680

Molecular mechanics and dynamics characterization of an in silico mutated protein: a stand-alone lab module or support activity for in vivo and in vitro analyses of targeted proteins.

PubMed

Chiang, Harry; Robinson, Lucy C; Brame, Cynthia J; Messina, Troy C

2013-01-01

Over the past 20 years, the biological sciences have increasingly incorporated chemistry, physics, computer science, and mathematics to aid in the development and use of mathematical models. Such combined approaches have been used to address problems from protein structure-function relationships to the workings of complex biological systems. Computer simulations of molecular events can now be accomplished quickly and with standard computer technology. Also, simulation software is freely available for most computing platforms, and online support for the novice user is ample. We have therefore created a molecular dynamics laboratory module to enhance undergraduate student understanding of molecular events underlying organismal phenotype. This module builds on a previously described project in which students use site-directed mutagenesis to investigate functions of conserved sequence features in members of a eukaryotic protein kinase family. In this report, we detail the laboratory activities of a MD module that provide a complement to phenotypic outcomes by providing a hypothesis-driven and quantifiable measure of predicted structural changes caused by targeted mutations. We also present examples of analyses students may perform. These laboratory activities can be integrated with genetics or biochemistry experiments as described, but could also be used independently in any course that would benefit from a quantitative approach to protein structure-function relationships. Copyright © 2013 Wiley Periodicals, Inc.

An insight into cyanobacterial genomics--a perspective.

PubMed

Lakshmi, Palaniswamy Thanga Velan

2007-05-20

At the turn of the millennium, cyanobacteria deserve attention to be reviewed to understand the past, present and future. The advent of post genomic research, which encompasses functional genomics, structural genomics, transcriptomics, pharmacogenomics, proteomics and metabolomics that allows a systematic wide approach for biological system studies. Thus by exploiting genomic and associated protein information through computational analyses, the fledging information that are generated by biotechnological analyses, could be well extrapolated to fill in the lacuna of scarce information on cyanobacteria and as an effort this paper attempts to highlights the perspectives available and awakens researcher to concentrate in the field of cyanobacterial informatics.

Resource recovery from wastewater: application of meta-omics to phosphorus and carbon management.

PubMed

Sales, Christopher M; Lee, Patrick K H

2015-06-01

A growing trend at wastewater treatment plants is the recovery of resources and energy from wastewater. Enhanced biological phosphorus removal and anaerobic digestion are two established biotechnology approaches for the recovery of phosphorus and carbon, respectively. Meta-omics approaches (meta-genomics, transcriptomics, proteomics, and metabolomics) are providing novel biological insights into these complex biological systems. In particular, genome-centric metagenomics analyses are revealing the function and physiology of individual community members. Querying transcripts, proteins and metabolites are emerging techniques that can inform the cellular responses under different conditions. Overall, meta-omics approaches are shedding light into complex microbial communities once regarded as 'blackboxes', but challenges remain to integrate information from meta-omics into engineering design and operation guidelines. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cerebro-cerebellar Resting-State Functional Connectivity in Children and Adolescents with Autism Spectrum Disorder.

PubMed

Khan, Amanda J; Nair, Aarti; Keown, Christopher L; Datko, Michael C; Lincoln, Alan J; Müller, Ralph-Axel

2015-11-01

The cerebellum plays important roles in sensori-motor and supramodal cognitive functions. Cellular, volumetric, and functional abnormalities of the cerebellum have been found in autism spectrum disorders (ASD), but no comprehensive investigation of cerebro-cerebellar connectivity in ASD is available. We used resting-state functional connectivity magnetic resonance imaging in 56 children and adolescents (28 subjects with ASD, 28 typically developing subjects) 8-17 years old. Partial and total correlation analyses were performed for unilateral regions of interest (ROIs), distinguished in two broad domains as sensori-motor (premotor/primary motor, somatosensory, superior temporal, and occipital) and supramodal (prefrontal, posterior parietal, and inferior and middle temporal). There were three main findings: 1) Total correlation analyses showed predominant cerebro-cerebellar functional overconnectivity in the ASD group; 2) partial correlation analyses that emphasized domain specificity (sensori-motor vs. supramodal) indicated a pattern of robustly increased connectivity in the ASD group (compared with the typically developing group) for sensori-motor ROIs but predominantly reduced connectivity for supramodal ROIs; and 3) this atypical pattern of connectivity was supported by significantly increased noncanonical connections (between sensori-motor cerebral and supramodal cerebellar ROIs and vice versa) in the ASD group. Our findings indicate that sensori-motor intrinsic functional connectivity is atypically increased in ASD, at the expense of connectivity supporting cerebellar participation in supramodal cognition. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Generation of Rab-based transgenic lines for in vivo studies of endosome biology in zebrafish

PubMed Central

Clark, Brian S.; Winter, Mark; Cohen, Andrew R.; Link, Brian A.

2011-01-01

The Rab family of small GTPases function as molecular switches regulating membrane and protein trafficking. Individual Rab isoforms define and are required for specific endosomal compartments. To facilitate in vivo investigation of specific Rab proteins, and endosome biology in general, we have generated transgenic zebrafish lines to mark and manipulate Rab proteins. We also developed software to track and quantify endosome dynamics within time-lapse movies. The established transgenic lines ubiquitously express EGFP fusions of Rab5c (early endosomes), Rab11a (recycling endosomes), and Rab7 (late endosomes) to study localization and dynamics during development. Additionally, we generated UAS-based transgenic lines expressing constitutive active (CA) and dominant negative (DN) versions for each of these Rab proteins. Predicted localization and functional consequences for each line were verified through a variety of assays, including lipophilic dye uptake and Crumbs2a localization. In summary, we have established a toolset for in vivo analyses of endosome dynamics and functions. PMID:21976318

Genetic and Environmental Influences on Longitudinal Trajectories of Functional Biological Age: Comparisons Across Gender.

PubMed

Finkel, Deborah; Sternäng, Ola; Wahlin, Åke

2017-07-01

We used an alternate age variable, functional biological age (fBioAge), which was based on performance on functional body measures. The aim was to examine development of fBioAge across the adult life span, and to also examine potential gender differences and genetic and environmental influences on change with age. We used longitudinal data (n = 740; chronological age (ChronAge) range 45-85 at baseline) from the Swedish Adoption/Twin Study of Aging. The rate of increase in fBioAge was twice as fast after ChronAge 75 than before. fBioAge was higher in women than in men. fBioAge was fairly equally influenced by genetic and environmental factors. Whereas the rate of ChronAge cannot vary across time, gender, or individual, our analyses demonstrate that fBioAge does capture these within and between individual differences in aging, providing advantages for fBioAge in the study of aging effects.

Explorative solid-phase extraction (E-SPE) for accelerated microbial natural product discovery, dereplication, and purification.

PubMed

Månsson, Maria; Phipps, Richard K; Gram, Lone; Munro, Murray H G; Larsen, Thomas O; Nielsen, Kristian F

2010-06-25

Microbial natural products (NP) cover a high chemical diversity, and in consequence extracts from microorganisms are often complex to analyze and purify. A distribution analysis of calculated pK(a) values from the 34390 records in Antibase2008 revealed that within pH 2-11, 44% of all included compounds had an acidic functionality, 17% a basic functionality, and 9% both. This showed a great potential for using ion-exchange chromatography as an integral part of the separation procedure, orthogonal to the classic reversed-phase strategy. Thus, we investigated the use of an "explorative solid-phase extraction" (E-SPE) protocol using SAX, Oasis MAX, SCX, and LH-20 columns for targeted exploitation of chemical functionalities. E-SPE provides a minimum of fractions (15) for chemical and biological analyses and implicates development into a preparative scale methodology. Overall, this allows fast extract prioritization, easier dereplication, mapping of biological activities, and formulation of a purification strategy.

CORUM: the comprehensive resource of mammalian protein complexes

PubMed Central

Ruepp, Andreas; Brauner, Barbara; Dunger-Kaltenbach, Irmtraud; Frishman, Goar; Montrone, Corinna; Stransky, Michael; Waegele, Brigitte; Schmidt, Thorsten; Doudieu, Octave Noubibou; Stümpflen, Volker; Mewes, H. Werner

2008-01-01

Protein complexes are key molecular entities that integrate multiple gene products to perform cellular functions. The CORUM (http://mips.gsf.de/genre/proj/corum/index.html) database is a collection of experimentally verified mammalian protein complexes. Information is manually derived by critical reading of the scientific literature from expert annotators. Information about protein complexes includes protein complex names, subunits, literature references as well as the function of the complexes. For functional annotation, we use the FunCat catalogue that enables to organize the protein complex space into biologically meaningful subsets. The database contains more than 1750 protein complexes that are built from 2400 different genes, thus representing 12% of the protein-coding genes in human. A web-based system is available to query, view and download the data. CORUM provides a comprehensive dataset of protein complexes for discoveries in systems biology, analyses of protein networks and protein complex-associated diseases. Comparable to the MIPS reference dataset of protein complexes from yeast, CORUM intends to serve as a reference for mammalian protein complexes. PMID:17965090

Determinants of the rate of protein sequence evolution

PubMed Central

Zhang, Jianzhi; Yang, Jian-Rong

2015-01-01

The rate and mechanism of protein sequence evolution have been central questions in evolutionary biology since the 1960s. Although the rate of protein sequence evolution depends primarily on the level of functional constraint, exactly what constitutes functional constraint has remained unclear. The increasing availability of genomic data has allowed for much needed empirical examinations on the nature of functional constraint. These studies found that the evolutionary rate of a protein is predominantly influenced by its expression level rather than functional importance. A combination of theoretical and empirical analyses have identified multiple mechanisms behind these observations and demonstrated a prominent role that selection against errors in molecular and cellular processes plays in protein evolution. PMID:26055156

Proteomics in investigation of cancer metastasis: functional and clinical consequences and methodological challenges.

PubMed

Maryáš, Josef; Faktor, Jakub; Dvořáková, Monika; Struhárová, Iva; Grell, Peter; Bouchal, Pavel

2014-03-01

Metastases are responsible for most of the cases of death in patients with solid tumors. There is thus an urgent clinical need of better understanding the exact molecular mechanisms and finding novel therapeutics targets and biomarkers of metastatic disease of various tumors. Metastases are formed in a complicated biological process called metastatic cascade. Up to now, proteomics has enabled the identification of number of metastasis-associated proteins and potential biomarkers in cancer tissues, microdissected cells, model systems, and secretomes. Expression profiles and biological role of key proteins were confirmed in verification and functional experiments. This communication reviews these observations and analyses the methodological aspects of the proteomics approaches used. Moreover, it reviews contribution of current proteomics in the field of functional characterization and interactome analysis of proteins involved in various events in metastatic cascade. It is evident that ongoing technical progress will further increase proteome coverage and sample capacity of proteomics technologies, giving complex answers to clinical and functional questions asked. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Reconstructing temperatures from lake sediments in northern Europe: what do the biological proxies really tell us?

NASA Astrophysics Data System (ADS)

Cunningham, Laura; Holmes, Naomi; Bigler, Christian; Dadal, Anna; Bergman, Jonas; Eriksson, Lars; Brooks, Stephen; Langdon, Pete; Caseldine, Chris

2010-05-01

Over the past two decades considerable effort has been devoted to quantitatively reconstructing temperatures from biological proxies preserved in lake sediments, via transfer functions. Such transfer functions typically consist of modern sediment samples, collected over a broad environmental gradient. Correlations between the biological communities and environmental parameters observed over these broad gradients are assumed to be equally valid temporally. The predictive ability of such spatially based transfer functions has traditionally been assessed by comparisons of measured and inferred temperatures within the calibration sets, with little validation against historical data. Although statistical techniques such as bootstrapping may improve error estimation, this approach remains partly a circular argument. This raises the question of how reliable such reconstructions are for inferring past changes in temperature? In order to address this question, we used transfer functions to reconstruct July temperatures from diatoms and chironomids from several locations across northern Europe. The transfer functions used showed good internal calibration statistics (r2 = 0.66 - 0.91). The diatom and chironomid inferred July air temperatures were compared to local observational records. As the sediment records were non-annual, all data were first smoothed using a 15 yr moving average filter. None of the five biologically-inferred temperature records were correlated with the local meteorological records. Furthermore, diatom inferred temperatures did not agree with chironomid inferred temperatures from the same cores from the same sites. In an attempt to understand this poor performance the biological proxy data was compressed using principal component analysis (PCA), and the PCA axes compared to the local meteorological data. These analyses clearly demonstrated that July temperatures were not correlated with the biological data at these locations. Some correlations were observed between the biological proxies and autumn and spring temperatures, although this varied slightly between sites and proxies. For example, chironomid data from Iceland was most strongly correlated with temperatures in February, March and April whilst in northern Sweden, the chironomid data was most strongly correlated with temperatures in March, April and May. It is suggested that the biological data at these sites may be responding to changes in the length of the ice-free period or hydrological regimes (including snow melt), rather than temperature per se. Our findings demonstrate the need to validate inferred temperatures against local meteorological data. Where such validation cannot be undertaken, inferred temperature reconstructions should be treated cautiously.

Structural Bioinformatics of the Interactome

PubMed Central

Petrey, Donald; Honig, Barry

2014-01-01

The last decade has seen a dramatic expansion in the number and range of techniques available to obtain genome-wide information, and to analyze this information so as to infer both the function of individual molecules and how they interact to modulate the behavior of biological systems. Here we review these techniques, focusing on the construction of physical protein-protein interaction networks, and highlighting approaches that incorporate protein structure which is becoming an increasingly important component of systems-level computational techniques. We also discuss how network analyses are being applied to enhance the basic understanding of biological systems and their disregulation, and how they are being applied in drug development. PMID:24895853

Linear control theory for gene network modeling.

PubMed

Shin, Yong-Jun; Bleris, Leonidas

2010-09-16

Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain) and linear state-space (time domain) can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.

Review of the fundamental theories behind small angle X-ray scattering, molecular dynamics simulations, and relevant integrated application.

PubMed

Boldon, Lauren; Laliberte, Fallon; Liu, Li

2015-01-01

In this paper, the fundamental concepts and equations necessary for performing small angle X-ray scattering (SAXS) experiments, molecular dynamics (MD) simulations, and MD-SAXS analyses were reviewed. Furthermore, several key biological and non-biological applications for SAXS, MD, and MD-SAXS are presented in this review; however, this article does not cover all possible applications. SAXS is an experimental technique used for the analysis of a wide variety of biological and non-biological structures. SAXS utilizes spherical averaging to produce one- or two-dimensional intensity profiles, from which structural data may be extracted. MD simulation is a computer simulation technique that is used to model complex biological and non-biological systems at the atomic level. MD simulations apply classical Newtonian mechanics' equations of motion to perform force calculations and to predict the theoretical physical properties of the system. This review presents several applications that highlight the ability of both SAXS and MD to study protein folding and function in addition to non-biological applications, such as the study of mechanical, electrical, and structural properties of non-biological nanoparticles. Lastly, the potential benefits of combining SAXS and MD simulations for the study of both biological and non-biological systems are demonstrated through the presentation of several examples that combine the two techniques.

Purification of Plant Receptor Kinases from Plant Plasma Membranes.

PubMed

Lee, Jin Suk

2017-01-01

Receptor kinases play a central role in various biological processes, but due to their low abundance and highly hydrophobic and dynamic nature, only a few of them have been functionally characterized, and their partners and ligands remain unidentified. Receptor protein extraction and purification from plant tissues is one of the most challenging steps for the success of various biochemical analyses to characterize their function. Immunoprecipitation is a widely used and selective method for enriching or purifying a specific protein. Here we describe two different optimized protein purification protocols, batch and on-chip immunoprecipitation, which efficiently isolate plant membrane receptor kinases for functional analysis.

Evolution and Conservation of Plant NLR Functions

PubMed Central

Jacob, Florence; Vernaldi, Saskia; Maekawa, Takaki

2013-01-01

In plants and animals, nucleotide-binding domain and leucine-rich repeats (NLR)-containing proteins play pivotal roles in innate immunity. Despite their similar biological functions and protein architecture, comparative genome-wide analyses of NLRs and genes encoding NLR-like proteins suggest that plant and animal NLRs have independently arisen in evolution. Furthermore, the demonstration of interfamily transfer of plant NLR functions from their original species to phylogenetically distant species implies evolutionary conservation of the underlying immune principle across plant taxonomy. In this review we discuss plant NLR evolution and summarize recent insights into plant NLR-signaling mechanisms, which might constitute evolutionarily conserved NLR-mediated immune mechanisms. PMID:24093022

Functional networks inference from rule-based machine learning models.

PubMed

Lazzarini, Nicola; Widera, Paweł; Williamson, Stuart; Heer, Rakesh; Krasnogor, Natalio; Bacardit, Jaume

2016-01-01

Functional networks play an important role in the analysis of biological processes and systems. The inference of these networks from high-throughput (-omics) data is an area of intense research. So far, the similarity-based inference paradigm (e.g. gene co-expression) has been the most popular approach. It assumes a functional relationship between genes which are expressed at similar levels across different samples. An alternative to this paradigm is the inference of relationships from the structure of machine learning models. These models are able to capture complex relationships between variables, that often are different/complementary to the similarity-based methods. We propose a protocol to infer functional networks from machine learning models, called FuNeL. It assumes, that genes used together within a rule-based machine learning model to classify the samples, might also be functionally related at a biological level. The protocol is first tested on synthetic datasets and then evaluated on a test suite of 8 real-world datasets related to human cancer. The networks inferred from the real-world data are compared against gene co-expression networks of equal size, generated with 3 different methods. The comparison is performed from two different points of view. We analyse the enriched biological terms in the set of network nodes and the relationships between known disease-associated genes in a context of the network topology. The comparison confirms both the biological relevance and the complementary character of the knowledge captured by the FuNeL networks in relation to similarity-based methods and demonstrates its potential to identify known disease associations as core elements of the network. Finally, using a prostate cancer dataset as a case study, we confirm that the biological knowledge captured by our method is relevant to the disease and consistent with the specialised literature and with an independent dataset not used in the inference process. The implementation of our network inference protocol is available at: http://ico2s.org/software/funel.html.

Multidimensional approaches for studying plant defence against insects: from ecology to omics and synthetic biology.

PubMed

Barah, Pankaj; Bones, Atle M

2015-02-01

The biggest challenge for modern biology is to integrate multidisciplinary approaches towards understanding the organizational and functional complexity of biological systems at different hierarchies, starting from the subcellular molecular mechanisms (microscopic) to the functional interactions of ecological communities (macroscopic). The plant-insect interaction is a good model for this purpose with the availability of an enormous amount of information at the molecular and the ecosystem levels. Changing global climatic conditions are abruptly resetting plant-insect interactions. Integration of discretely located heterogeneous information from the ecosystem to genes and pathways will be an advantage to understand the complexity of plant-insect interactions. This review will present the recent developments in omics-based high-throughput experimental approaches, with particular emphasis on studying plant defence responses against insect attack. The review highlights the importance of using integrative systems approaches to study plant-insect interactions from the macroscopic to the microscopic level. We analyse the current efforts in generating, integrating and modelling multiomics data to understand plant-insect interaction at a systems level. As a future prospect, we highlight the growing interest in utilizing the synthetic biology platform for engineering insect-resistant plants. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Global analysis of the rat and human platelet proteome – the molecular blueprint for illustrating multi-functional platelets and cross-species function evolution

PubMed Central

Yu, Yanbao; Leng, Taohua; Yun, Dong; Liu, Na; Yao, Jun; Dai, Ying; Yang, Pengyuan; Chen, Xian

2013-01-01

Emerging evidences indicate that blood platelets function in multiple biological processes including immune response, bone metastasis and liver regeneration in addition to their known roles in hemostasis and thrombosis. Global elucidation of platelet proteome will provide the molecular base of these platelet functions. Here, we set up a high throughput platform for maximum exploration of the rat/human platelet proteome using integrated proteomics technologies, and then applied to identify the largest number of the proteins expressed in both rat and human platelets. After stringent statistical filtration, a total of 837 unique proteins matched with at least two unique peptides were precisely identified, making it the first comprehensive protein database so far for rat platelets. Meanwhile, quantitative analyses of the thrombin-stimulated platelets offered great insights into the biological functions of platelet proteins and therefore confirmed our global profiling data. A comparative proteomic analysis between rat and human platelets was also conducted, which revealed not only a significant similarity, but also an across-species evolutionary link that the orthologous proteins representing ‘core proteome’, and the ‘evolutionary proteome’ is actually a relatively static proteome. PMID:20443191

Psoralen inhibits bone metastasis of breast cancer in mice.

PubMed

Wu, Chunyu; Sun, Zhenping; Ye, Yiyi; Han, Xianghui; Song, Xiaoyun; Liu, Sheng

2013-12-01

Breast cancer is the most common female malignancy and it frequently metastasizes to bone. Metastatic breast cancer continues to be the primary cause of death for women in East and Southeast Asia. Psoralen is a furocoumarin that can be isolated from the seeds of Psoralea corylifolia L. Psoralen exhibits a wide range of biological properties and has been demonstrated as an antioxidant, antidepressant, anticancer, antibacterial, and antiviral agent. Additionally, it is involved in the formation and regulation of bone. This study investigated whether psoralen can inhibit metastasis of breast cancer to bone in vivo. Histological, molecular biological, and imaging analyses revealed that psoralen inhibits bone metastases in mice. Psoralen may function to inhibit breast cancer cell growth in the bone microenvironment and regulate the function of osteoblasts and osteoclasts in tumor-bearing mice. The results of this study suggest that psoralen is a bone-modifying agent and a potential therapeutic to treat patients with bone metastases. © 2013.

The influence of feeding on the evolution of sensory signals: a comparative test of an evolutionary trade-off between masticatory and sensory functions of skulls in southern African horseshoe bats (Rhinolophidae).

PubMed

Jacobs, D S; Bastian, A; Bam, L

2014-12-01

The skulls of animals have to perform many functions. Optimization for one function may mean another function is less optimized, resulting in evolutionary trade-offs. Here, we investigate whether a trade-off exists between the masticatory and sensory functions of animal skulls using echolocating bats as model species. Several species of rhinolophid bats deviate from the allometric relationship between body size and echolocation frequency. Such deviation may be the result of selection for increased bite force, resulting in a decrease in snout length which could in turn lead to higher echolocation frequencies. If so, there should be a positive relationship between bite force and echolocation frequency. We investigated this relationship in several species of southern African rhinolophids using phylogenetically informed analyses of the allometry of their bite force and echolocation frequency and of the three-dimensional shape of their skulls. As predicted, echolocation frequency was positively correlated with bite force, suggesting that its evolution is influenced by a trade-off between the masticatory and sensory functions of the skull. In support of this, variation in skull shape was explained by both echolocation frequency (80%) and bite force (20%). Furthermore, it appears that selection has acted on the nasal capsules, which have a frequency-specific impedance matching function during vocalization. There was a negative correlation between echolocation frequency and capsule volume across species. Optimization of the masticatory function of the skull may have been achieved through changes in the shape of the mandible and associated musculature, elements not considered in this study. © 2014 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Merging metagenomics and geochemistry reveals environmental controls on biological diversity and evolution.

PubMed

Alsop, Eric B; Boyd, Eric S; Raymond, Jason

2014-05-28

The metabolic strategies employed by microbes inhabiting natural systems are, in large part, dictated by the physical and geochemical properties of the environment. This study sheds light onto the complex relationship between biology and environmental geochemistry using forty-three metagenomes collected from geochemically diverse and globally distributed natural systems. It is widely hypothesized that many uncommonly measured geochemical parameters affect community dynamics and this study leverages the development and application of multidimensional biogeochemical metrics to study correlations between geochemistry and microbial ecology. Analysis techniques such as a Markov cluster-based measure of the evolutionary distance between whole communities and a principal component analysis (PCA) of the geochemical gradients between environments allows for the determination of correlations between microbial community dynamics and environmental geochemistry and provides insight into which geochemical parameters most strongly influence microbial biodiversity. By progressively building from samples taken along well defined geochemical gradients to samples widely dispersed in geochemical space this study reveals strong links between the extent of taxonomic and functional diversification of resident communities and environmental geochemistry and reveals temperature and pH as the primary factors that have shaped the evolution of these communities. Moreover, the inclusion of extensive geochemical data into analyses reveals new links between geochemical parameters (e.g. oxygen and trace element availability) and the distribution and taxonomic diversification of communities at the functional level. Further, an overall geochemical gradient (from multivariate analyses) between natural systems provides one of the most complete predictions of microbial taxonomic and functional composition. Clustering based on the frequency in which orthologous proteins occur among metagenomes facilitated accurate prediction of the ordering of community functional composition along geochemical gradients, despite a lack of geochemical input. The consistency in the results obtained from the application of Markov clustering and multivariate methods to distinct natural systems underscore their utility in predicting the functional potential of microbial communities within a natural system based on system geochemistry alone, allowing geochemical measurements to be used to predict purely biological metrics such as microbial community composition and metabolism.

Integrative and conjugative elements and their hosts: composition, distribution and organization

PubMed Central

Touchon, Marie; Rocha, Eduardo P. C.

2017-01-01

Abstract Conjugation of single-stranded DNA drives horizontal gene transfer between bacteria and was widely studied in conjugative plasmids. The organization and function of integrative and conjugative elements (ICE), even if they are more abundant, was only studied in a few model systems. Comparative genomics of ICE has been precluded by the difficulty in finding and delimiting these elements. Here, we present the results of a method that circumvents these problems by requiring only the identification of the conjugation genes and the species’ pan-genome. We delimited 200 ICEs and this allowed the first large-scale characterization of these elements. We quantified the presence in ICEs of a wide set of functions associated with the biology of mobile genetic elements, including some that are typically associated with plasmids, such as partition and replication. Protein sequence similarity networks and phylogenetic analyses revealed that ICEs are structured in functional modules. Integrases and conjugation systems have different evolutionary histories, even if the gene repertoires of ICEs can be grouped in function of conjugation types. Our characterization of the composition and organization of ICEs paves the way for future functional and evolutionary analyses of their cargo genes, composed of a majority of unknown function genes. PMID:28911112

Conserved noncoding sequences conserve biological networks and influence genome evolution.

PubMed

Xie, Jianbo; Qian, Kecheng; Si, Jingna; Xiao, Liang; Ci, Dong; Zhang, Deqiang

2018-05-01

Comparative genomics approaches have identified numerous conserved cis-regulatory sequences near genes in plant genomes. Despite the identification of these conserved noncoding sequences (CNSs), our knowledge of their functional importance and selection remains limited. Here, we used a combination of DNA methylome analysis, microarray expression analyses, and functional annotation to study these sequences in the model tree Populus trichocarpa. Methylation in CG contexts and non-CG contexts was lower in CNSs, particularly CNSs in the 5'-upstream regions of genes, compared with other sites in the genome. We observed that CNSs are enriched in genes with transcription and binding functions, and this also associated with syntenic genes and those from whole-genome duplications, suggesting that cis-regulatory sequences play a key role in genome evolution. We detected a significant positive correlation between CNS number and protein interactions, suggesting that CNSs may have roles in the evolution and maintenance of biological networks. The divergence of CNSs indicates that duplication-degeneration-complementation drives the subfunctionalization of a proportion of duplicated genes from whole-genome duplication. Furthermore, population genomics confirmed that most CNSs are under strong purifying selection and only a small subset of CNSs shows evidence of adaptive evolution. These findings provide a foundation for future studies exploring these key genomic features in the maintenance of biological networks, local adaptation, and transcription.

Proteomic Analyses of the Effects of Drugs of Abuse on Monocyte-Derived Mature Dendritic Cells

PubMed Central

Reynolds, Jessica L.; Mahajan, Supriya D.; Aalinkeel, Ravikunar; Nair, B.; Sykes, Donald E.; Schwartz, Stanley A.

2010-01-01

Drug abuse has become a global health concern. Understanding how drug abuse modulates the immune system and how the immune system responds to pathogens associated with drug abuse, such hepatitis C virus (HCV) and human immunodeficiency virus (HIV-1), can be assessed by an integrated approach comparing proteomic analyses and quantitation of gene expression. Two-dimensional (2D) difference gel electrophoresis was used to determine the molecular mechanisms underlying the proteomic changes that alter normal biological processes when monocyte-derived mature dendritic cells were treated with cocaine or methamphetamine. Both drugs differentially regulated the expression of several functional classes of proteins including those that modulate apoptosis, protein folding, protein kinase activity, and metabolism and proteins that function as intracellular signal transduction molecules. Proteomic data were validated using a combination of quantitative, real-time PCR and Western blot analyses. These studies will help to identify the molecular mechanisms, including the expression of several functionally important classes of proteins that have emerged as potential mediators of pathogenesis. These proteins may predispose immunocompetent cells, including dendritic cells, to infection with viruses such as HCV and HIV-1, which are associated with drug abuse. PMID:19811410

Proteomics in chromatin biology and epigenetics: Elucidation of post-translational modifications of histone proteins by mass spectrometry.

PubMed

Sidoli, Simone; Cheng, Lei; Jensen, Ole N

2012-06-27

Histone proteins contribute to the maintenance and regulation of the dynamic chromatin structure, to gene activation, DNA repair and many other processes in the cell nucleus. Site-specific reversible and irreversible post-translational modifications of histone proteins mediate biological functions, including recruitment of transcription factors to specific DNA regions, assembly of epigenetic reader/writer/eraser complexes onto DNA, and modulation of DNA-protein interactions. Histones thereby regulate chromatin structure and function, propagate inheritance and provide memory functions in the cell. Dysfunctional chromatin structures and misregulation may lead to pathogenic states, including diabetes and cancer, and the mapping and quantification of multivalent post-translational modifications has therefore attracted significant interest. Mass spectrometry has quickly been accepted as a versatile tool to achieve insights into chromatin biology and epigenetics. High sensitivity and high mass accuracy and the ability to sequence post-translationally modified peptides and perform large-scale analyses make this technique very well suited for histone protein characterization. In this review we discuss a range of analytical methods and various mass spectrometry-based approaches for histone analysis, from sample preparation to data interpretation. Mass spectrometry-based proteomics is already an integrated and indispensable tool in modern chromatin biology, providing insights into the mechanisms and dynamics of nuclear and epigenetic processes. This article is part of a Special Section entitled: Understanding genome regulation and genetic diversity by mass spectrometry. Copyright © 2011 Elsevier B.V. All rights reserved.

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns.

PubMed

Gruel, Jérémy; LeBorgne, Michel; LeMeur, Nolwenn; Théret, Nathalie

2011-09-12

Regulation of gene expression plays a pivotal role in cellular functions. However, understanding the dynamics of transcription remains a challenging task. A host of computational approaches have been developed to identify regulatory motifs, mainly based on the recognition of DNA sequences for transcription factor binding sites. Recent integration of additional data from genomic analyses or phylogenetic footprinting has significantly improved these methods. Here, we propose a different approach based on the compilation of Simple Shared Motifs (SSM), groups of sequences defined by their length and similarity and present in conserved sequences of gene promoters. We developed an original algorithm to search and count SSM in pairs of genes. An exceptional number of SSM is considered as a common regulatory pattern. The SSM approach is applied to a sample set of genes and validated using functional gene-set enrichment analyses. We demonstrate that the SSM approach selects genes that are over-represented in specific biological categories (Ontology and Pathways) and are enriched in co-expressed genes. Finally we show that genes co-expressed in the same tissue or involved in the same biological pathway have increased SSM values. Using unbiased clustering of genes, Simple Shared Motifs analysis constitutes an original contribution to provide a clearer definition of expression networks.

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns

PubMed Central

2011-01-01

Background Regulation of gene expression plays a pivotal role in cellular functions. However, understanding the dynamics of transcription remains a challenging task. A host of computational approaches have been developed to identify regulatory motifs, mainly based on the recognition of DNA sequences for transcription factor binding sites. Recent integration of additional data from genomic analyses or phylogenetic footprinting has significantly improved these methods. Results Here, we propose a different approach based on the compilation of Simple Shared Motifs (SSM), groups of sequences defined by their length and similarity and present in conserved sequences of gene promoters. We developed an original algorithm to search and count SSM in pairs of genes. An exceptional number of SSM is considered as a common regulatory pattern. The SSM approach is applied to a sample set of genes and validated using functional gene-set enrichment analyses. We demonstrate that the SSM approach selects genes that are over-represented in specific biological categories (Ontology and Pathways) and are enriched in co-expressed genes. Finally we show that genes co-expressed in the same tissue or involved in the same biological pathway have increased SSM values. Conclusions Using unbiased clustering of genes, Simple Shared Motifs analysis constitutes an original contribution to provide a clearer definition of expression networks. PMID:21910886

Technological advances for deciphering the complexity of psychiatric disorders: merging proteomics with cell biology.

PubMed

Wesseling, Hendrik; Guest, Paul C; Lago, Santiago G; Bahn, Sabine

2014-08-01

Proteomic studies have increased our understanding of the molecular pathways affected in psychiatric disorders. Mass spectrometry and two-dimensional gel electrophoresis analyses of post-mortem brain samples from psychiatric patients have revealed effects on synaptic, cytoskeletal, antioxidant and mitochondrial protein networks. Multiplex immunoassay profiling studies have found alterations in hormones, growth factors, transport and inflammation-related proteins in serum and plasma from living first-onset patients. Despite these advances, there are still difficulties in translating these findings into platforms for improved treatment of patients and for discovery of new drugs with better efficacy and side effect profiles. This review describes how the next phase of proteomic investigations in psychiatry should include stringent replication studies for validation of biomarker candidates and functional follow-up studies which can be used to test the impact on physiological function. All biomarker candidates should now be tested in series with traditional and emerging cell biological approaches. This should include investigations of the effects of post-translational modifications, protein dynamics and network analyses using targeted proteomic approaches. Most importantly, there is still an urgent need for development of disease-relevant cellular models for improved translation of proteomic findings into a means of developing novel drug treatments for patients with these life-altering disorders.

clubber: removing the bioinformatics bottleneck in big data analyses.

PubMed

Miller, Maximilian; Zhu, Chengsheng; Bromberg, Yana

2017-06-13

With the advent of modern day high-throughput technologies, the bottleneck in biological discovery has shifted from the cost of doing experiments to that of analyzing results. clubber is our automated cluster-load balancing system developed for optimizing these "big data" analyses. Its plug-and-play framework encourages re-use of existing solutions for bioinformatics problems. clubber's goals are to reduce computation times and to facilitate use of cluster computing. The first goal is achieved by automating the balance of parallel submissions across available high performance computing (HPC) resources. Notably, the latter can be added on demand, including cloud-based resources, and/or featuring heterogeneous environments. The second goal of making HPCs user-friendly is facilitated by an interactive web interface and a RESTful API, allowing for job monitoring and result retrieval. We used clubber to speed up our pipeline for annotating molecular functionality of metagenomes. Here, we analyzed the Deepwater Horizon oil-spill study data to quantitatively show that the beach sands have not yet entirely recovered. Further, our analysis of the CAMI-challenge data revealed that microbiome taxonomic shifts do not necessarily correlate with functional shifts. These examples (21 metagenomes processed in 172 min) clearly illustrate the importance of clubber in the everyday computational biology environment.

clubber: removing the bioinformatics bottleneck in big data analyses

PubMed Central

Miller, Maximilian; Zhu, Chengsheng; Bromberg, Yana

2018-01-01

With the advent of modern day high-throughput technologies, the bottleneck in biological discovery has shifted from the cost of doing experiments to that of analyzing results. clubber is our automated cluster-load balancing system developed for optimizing these “big data” analyses. Its plug-and-play framework encourages re-use of existing solutions for bioinformatics problems. clubber’s goals are to reduce computation times and to facilitate use of cluster computing. The first goal is achieved by automating the balance of parallel submissions across available high performance computing (HPC) resources. Notably, the latter can be added on demand, including cloud-based resources, and/or featuring heterogeneous environments. The second goal of making HPCs user-friendly is facilitated by an interactive web interface and a RESTful API, allowing for job monitoring and result retrieval. We used clubber to speed up our pipeline for annotating molecular functionality of metagenomes. Here, we analyzed the Deepwater Horizon oil-spill study data to quantitatively show that the beach sands have not yet entirely recovered. Further, our analysis of the CAMI-challenge data revealed that microbiome taxonomic shifts do not necessarily correlate with functional shifts. These examples (21 metagenomes processed in 172 min) clearly illustrate the importance of clubber in the everyday computational biology environment. PMID:28609295

Large-scale GWAS identifies multiple loci for hand grip strength providing biological insights into muscular fitness.

PubMed

Willems, Sara M; Wright, Daniel J; Day, Felix R; Trajanoska, Katerina; Joshi, Peter K; Morris, John A; Matteini, Amy M; Garton, Fleur C; Grarup, Niels; Oskolkov, Nikolay; Thalamuthu, Anbupalam; Mangino, Massimo; Liu, Jun; Demirkan, Ayse; Lek, Monkol; Xu, Liwen; Wang, Guan; Oldmeadow, Christopher; Gaulton, Kyle J; Lotta, Luca A; Miyamoto-Mikami, Eri; Rivas, Manuel A; White, Tom; Loh, Po-Ru; Aadahl, Mette; Amin, Najaf; Attia, John R; Austin, Krista; Benyamin, Beben; Brage, Søren; Cheng, Yu-Ching; Cięszczyk, Paweł; Derave, Wim; Eriksson, Karl-Fredrik; Eynon, Nir; Linneberg, Allan; Lucia, Alejandro; Massidda, Myosotis; Mitchell, Braxton D; Miyachi, Motohiko; Murakami, Haruka; Padmanabhan, Sandosh; Pandey, Ashutosh; Papadimitriou, Ioannis; Rajpal, Deepak K; Sale, Craig; Schnurr, Theresia M; Sessa, Francesco; Shrine, Nick; Tobin, Martin D; Varley, Ian; Wain, Louise V; Wray, Naomi R; Lindgren, Cecilia M; MacArthur, Daniel G; Waterworth, Dawn M; McCarthy, Mark I; Pedersen, Oluf; Khaw, Kay-Tee; Kiel, Douglas P; Pitsiladis, Yannis; Fuku, Noriyuki; Franks, Paul W; North, Kathryn N; van Duijn, Cornelia M; Mather, Karen A; Hansen, Torben; Hansson, Ola; Spector, Tim; Murabito, Joanne M; Richards, J Brent; Rivadeneira, Fernando; Langenberg, Claudia; Perry, John R B; Wareham, Nick J; Scott, Robert A

2017-07-12

Hand grip strength is a widely used proxy of muscular fitness, a marker of frailty, and predictor of a range of morbidities and all-cause mortality. To investigate the genetic determinants of variation in grip strength, we perform a large-scale genetic discovery analysis in a combined sample of 195,180 individuals and identify 16 loci associated with grip strength (P<5 × 10 -8 ) in combined analyses. A number of these loci contain genes implicated in structure and function of skeletal muscle fibres (ACTG1), neuronal maintenance and signal transduction (PEX14, TGFA, SYT1), or monogenic syndromes with involvement of psychomotor impairment (PEX14, LRPPRC and KANSL1). Mendelian randomization analyses are consistent with a causal effect of higher genetically predicted grip strength on lower fracture risk. In conclusion, our findings provide new biological insight into the mechanistic underpinnings of grip strength and the causal role of muscular strength in age-related morbidities and mortality.

Assessing the impact of fishing in shallow rocky reefs: a multivariate approach to ecosystem management.

PubMed

Sangil, Carlos; Martín-García, Laura; Clemente, Sabrina

2013-11-15

In this paper we develop a tool to assess the impact of fishing on ecosystem functioning in shallow rocky reefs. The relationships between biological parameters (fishes, sea urchins, seaweeds), and fishing activities (fish traps, boats, land-based fishing, spearfishing) were tested in La Palma island (Canary Islands). Data from fishing activities and biological parameters were analyzed using principal component analyses. We produced two models using the first component of these analyses. This component was interpreted as a new variable that described the fishing pressure and the conservation status at each studied site. Subsequently the scores on the first axis were mapped using universal kriging methods and the models obtained were extrapolated across the whole island to display the expected fishing pressure and conservation status more widely. The fishing pressure and conservation status models were spatially related; zones where fishing pressure was high coincided with zones in the unhealthiest ecological state. Copyright © 2013 Elsevier Ltd. All rights reserved.

The landscape context of cereal aphid–parasitoid interactions

PubMed Central

Thies, Carsten; Roschewitz, Indra; Tscharntke, Teja

2005-01-01

Analyses at multiple spatial scales may show how important ecosystem services such as biological control are determined by processes acting on the landscape scale. We examined cereal aphid–parasitoid interactions in wheat fields in agricultural landscapes differing in structural complexity (32–100% arable land). Complex landscapes were associated with increased aphid mortality resulting from parasitism, but also with higher aphid colonization, thereby counterbalancing possible biological control by parasitoids and lastly resulting in similar aphid densities across landscapes. Thus, undisturbed perennial habitats appeared to enhance both pests and natural enemies. Analyses at multiple spatial scales (landscape sectors of 0.5–6 km diameter) showed that correlations between parasitism and percentage of arable land were significant at scales of 0.5–2 km, whereas aphid densities responded to percentage of arable land at scales of 1–6 km diameter. Hence, the higher trophic level populations appeared to be determined by smaller landscape sectors owing to dispersal limitation, showing the ‘functional spatial scale’ for species-specific landscape management. PMID:15695212

Ecological and phylogenetic variability in the spinalis muscle of snakes.

PubMed

Tingle, J L; Gartner, G E A; Jayne, B C; Garland, T

2017-11-01

Understanding the origin and maintenance of functionally important subordinate traits is a major goal of evolutionary physiologists and ecomorphologists. Within the confines of a limbless body plan, snakes are diverse in terms of body size and ecology, but we know little about the functional traits that underlie this diversity. We used a phylogenetically diverse group of 131 snake species to examine associations between habitat use, sidewinding locomotion and constriction behaviour with the number of body vertebrae spanned by a single segment of the spinalis muscle, with total numbers of body vertebrae used as a covariate in statistical analyses. We compared models with combinations of these predictors to determine which best fit the data among all species and for the advanced snakes only (N = 114). We used both ordinary least-squares models and phylogenetic models in which the residuals were modelled as evolving by the Ornstein-Uhlenbeck process. Snakes with greater numbers of vertebrae tended to have spinalis muscles that spanned more vertebrae. Habitat effects dominated models for analyses of all species and advanced snakes only, with the spinalis length spanning more vertebrae in arboreal species and fewer vertebrae in aquatic and burrowing species. Sidewinding specialists had shorter muscle lengths than nonspecialists. The relationship between prey constriction and spinalis length was less clear. Differences among clades were also strong when considering all species, but not for advanced snakes alone. Overall, these results suggest that muscle morphology may have played a key role in the adaptive radiation of snakes. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Identification of Crowding Stress Tolerance Co-Expression Networks Involved in Sweet Corn Yield

PubMed Central

Choe, Eunsoo; Drnevich, Jenny; Williams, Martin M.

2016-01-01

Tolerance to crowding stress has played a crucial role in improving agronomic productivity in field corn; however, commercial sweet corn hybrids vary greatly in crowding stress tolerance. The objectives were to 1) explore transcriptional changes among sweet corn hybrids with differential yield under crowding stress, 2) identify relationships between phenotypic responses and gene expression patterns, and 3) identify groups of genes associated with yield and crowding stress tolerance. Under conditions of crowding stress, three high-yielding and three low-yielding sweet corn hybrids were grouped for transcriptional and phenotypic analyses. Transcriptional analyses identified from 372 to 859 common differentially expressed genes (DEGs) for each hybrid. Large gene expression pattern variation among hybrids and only 26 common DEGs across all hybrid comparisons were identified, suggesting each hybrid has a unique response to crowding stress. Over-represented biological functions of DEGs also differed among hybrids. Strong correlation was observed between: 1) modules with up-regulation in high-yielding hybrids and yield traits, and 2) modules with up-regulation in low-yielding hybrids and plant/ear traits. Modules linked with yield traits may be important crowding stress response mechanisms influencing crop yield. Functional analysis of the modules and common DEGs identified candidate crowding stress tolerant processes in photosynthesis, glycolysis, cell wall, carbohydrate/nitrogen metabolic process, chromatin, and transcription regulation. Moreover, these biological functions were greatly inter-connected, indicating the importance of improving the mechanisms as a network. PMID:26796516

Biological significance of long non-coding RNA FTX expression in human colorectal cancer.

PubMed

Guo, Xiao-Bo; Hua, Zhu; Li, Chen; Peng, Li-Pan; Wang, Jing-Shen; Wang, Bo; Zhi, Qiao-Ming

2015-01-01

The purpose of this study was to determine the expression of long non-coding RNA (lncRNA) FTX and analyze its prognostic and biological significance in colorectal cancer (CRC). A quantitative reverse transcription PCR was performed to detect the expression of long non-coding RNA FTX in 35 pairs of colorectal cancer and corresponding noncancerous tissues. The expression of long non-coding RNA FTX was detected in 187 colorectal cancer tissues and its correlations with clinicopathological factors of patients were examined. Univariate and multivariate analyses were performed to analyze the prognostic significance of Long Non-coding RNA FTX expression. The effects of long non-coding RNA FTX expression on malignant phenotypes of colorectal cancer cells and its possible biological significances were further determined. Long non-coding RNA FTX was significantly upregulated in colorectal cancer tissues, and low long non-coding RNA FTX expression was significantly correlated with differentiation grade, lymph vascular invasion, and clinical stage. Patients with high long non-coding RNA FTX showed poorer overall survival than those with low long non-coding RNA FTX. Multivariate analyses indicated that status of long non-coding RNA FTX was an independent prognostic factor for patients. Functional analyses showed that upregulation of long non-coding RNA FTX significantly promoted growth, migration, invasion, and increased colony formation in colorectal cancer cells. Therefore, long non-coding RNA FTX may be a potential biomarker for predicting the survival of colorectal cancer patients and might be a molecular target for treatment of human colorectal cancer.

An attempt to understand glioma stem cell biology through centrality analysis of a protein interaction network.

PubMed

Mallik, Mrinmay Kumar

2018-02-07

Biological networks can be analyzed using "Centrality Analysis" to identify the more influential nodes and interactions in the network. This study was undertaken to create and visualize a biological network comprising of protein-protein interactions (PPIs) amongst proteins which are preferentially over-expressed in glioma cancer stem cell component (GCSC) of glioblastomas as compared to the glioma non-stem cancer cell (GNSC) component and then to analyze this network through centrality analyses (CA) in order to identify the essential proteins in this network and their interactions. In addition, this study proposes a new centrality analysis method pertaining exclusively to transcription factors (TFs) and interactions amongst them. Moreover the relevant molecular functions, biological processes and biochemical pathways amongst these proteins were sought through enrichment analysis. A protein interaction network was created using a list of proteins which have been shown to be preferentially expressed or over-expressed in GCSCs isolated from glioblastomas as compared to the GNSCs. This list comprising of 38 proteins, created using manual literature mining, was submitted to the Reactome FIViz tool, a web based application integrated into Cytoscape, an open source software platform for visualizing and analyzing molecular interaction networks and biological pathways to produce the network. This network was subjected to centrality analyses utilizing ranked lists of six centrality measures using the FIViz application and (for the first time) a dedicated centrality analysis plug-in ; CytoNCA. The interactions exclusively amongst the transcription factors were nalyzed through a newly proposed centrality analysis method called "Gene Expression Associated Degree Centrality Analysis (GEADCA)". Enrichment analysis was performed using the "network function analysis" tool on Reactome. The CA was able to identify a small set of proteins with consistently high centrality ranks that is indicative of their strong influence in the protein protein interaction network. Similarly the newly proposed GEADCA helped identify the transcription factors with high centrality values indicative of their key roles in transcriptional regulation. The enrichment studies provided a list of molecular functions, biological processes and biochemical pathways associated with the constructed network. The study shows how pathway based databases may be used to create and analyze a relevant protein interaction network in glioma cancer stem cells and identify the essential elements within it to gather insights into the molecular interactions that regulate the properties of glioma stem cells. How these insights may be utilized to help the development of future research towards formulation of new management strategies have been discussed from a theoretical standpoint. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spectral analysis of pair-correlation bandwidth: application to cell biology images.

PubMed

Binder, Benjamin J; Simpson, Matthew J

2015-02-01

Images from cell biology experiments often indicate the presence of cell clustering, which can provide insight into the mechanisms driving the collective cell behaviour. Pair-correlation functions provide quantitative information about the presence, or absence, of clustering in a spatial distribution of cells. This is because the pair-correlation function describes the ratio of the abundance of pairs of cells, separated by a particular distance, relative to a randomly distributed reference population. Pair-correlation functions are often presented as a kernel density estimate where the frequency of pairs of objects are grouped using a particular bandwidth (or bin width), Δ>0. The choice of bandwidth has a dramatic impact: choosing Δ too large produces a pair-correlation function that contains insufficient information, whereas choosing Δ too small produces a pair-correlation signal dominated by fluctuations. Presently, there is little guidance available regarding how to make an objective choice of Δ. We present a new technique to choose Δ by analysing the power spectrum of the discrete Fourier transform of the pair-correlation function. Using synthetic simulation data, we confirm that our approach allows us to objectively choose Δ such that the appropriately binned pair-correlation function captures known features in uniform and clustered synthetic images. We also apply our technique to images from two different cell biology assays. The first assay corresponds to an approximately uniform distribution of cells, while the second assay involves a time series of images of a cell population which forms aggregates over time. The appropriately binned pair-correlation function allows us to make quantitative inferences about the average aggregate size, as well as quantifying how the average aggregate size changes with time.

TARGET Research Goals

Cancer.gov

TARGET researchers use various sequencing and array-based methods to examine the genomes, transcriptomes, and for some diseases epigenomes of select childhood cancers. This “multi-omic” approach generates a comprehensive profile of molecular alterations for each cancer type. Alterations are changes in DNA or RNA, such as rearrangements in chromosome structure or variations in gene expression, respectively. Through computational analyses and assays to validate biological function, TARGET researchers predict which alterations disrupt the function of a gene or pathway and promote cancer growth, progression, and/or survival. Researchers identify candidate therapeutic targets and/or prognostic markers from the cancer-associated alterations.

Research & market strategy: how choice of drug discovery approach can affect market position.

PubMed

Sams-Dodd, Frank

2007-04-01

In principal, drug discovery approaches can be grouped into target- and function-based, with the respective aims of developing either a target-selective drug or a drug that produces a specific biological effect irrespective of its mode of action. Most analyses of drug discovery approaches focus on productivity, whereas the strategic implications of the choice of drug discovery approach on market position and ability to maintain market exclusivity are rarely considered. However, a comparison of approaches from the perspective of market position indicates that the functional approach is superior for the development of novel, innovative treatments.

Effects of biological sex on the pathophysiology of the heart

PubMed Central

Fazal, Loubina; Azibani, Feriel; Vodovar, Nicolas; Cohen Solal, Alain; Delcayre, Claude; Samuel, Jane-Lise

2014-01-01

Cardiovascular diseases are the leading causes of death in men and women in industrialized countries. While the effects of biological sex on cardiovascular pathophysiology have long been known, the sex-specific mechanisms mediating these processes have been further elucidated over recent years. This review aims at analysing the sex-based differences in cardiac structure and function in adult mammals, and the sex-based differences in the main molecular mechanisms involved in the response of the heart to pathological situations. It emerged from this review that the sex-based difference is a variable that should be dealt with, not only in basic science or clinical research, but also with regards to therapeutic approaches. PMID:23763376

TRIENNIAL LACTATION SYMPOSIUM: Nutrigenomics in livestock: Systems biology meets nutrition.

PubMed

Loor, J J; Vailati-Riboni, M; McCann, J C; Zhou, Z; Bionaz, M

2015-12-01

The advent of high-throughput technologies to study an animal's genome, proteome, and metabolome (i.e., "omics" tools) constituted a setback to the use of reductionism in livestock research. More recent development of "next-generation sequencing" tools was instrumental in allowing in-depth studies of the microbiome in the rumen and other sections of the gastrointestinal tract. Omics, along with bioinformatics, constitutes the foundation of modern systems biology, a field of study widely used in model organisms (e.g., rodents, yeast, humans) to enhance understanding of the complex biological interactions occurring within cells and tissues at the gene, protein, and metabolite level. Application of systems biology concepts is ideal for the study of interactions between nutrition and physiological state with tissue and cell metabolism and function during key life stages of livestock species, including the transition from pregnancy to lactation, in utero development, or postnatal growth. Modern bioinformatic tools capable of discerning functional outcomes and biologically meaningful networks complement the ever-increasing ability to generate large molecular, microbial, and metabolite data sets. Simultaneous visualization of the complex intertissue adaptations to physiological state and nutrition can now be discerned. Studies to understand the linkages between the microbiome and the absorptive epithelium using the integrative approach are emerging. We present examples of new knowledge generated through the application of functional analyses of transcriptomic, proteomic, and metabolomic data sets encompassing nutritional management of dairy cows, pigs, and poultry. Published work to date underscores that the integrative approach across and within tissues may prove useful for fine-tuning nutritional management of livestock. An important goal during this process is to uncover key molecular players involved in the organismal adaptations to nutrition.

Epigenetic profiling of growth plate chondrocytes sheds insight into regulatory genetic variation influencing height.

PubMed

Guo, Michael; Liu, Zun; Willen, Jessie; Shaw, Cameron P; Richard, Daniel; Jagoda, Evelyn; Doxey, Andrew C; Hirschhorn, Joel; Capellini, Terence D

2017-12-05

GWAS have identified hundreds of height-associated loci. However, determining causal mechanisms is challenging, especially since height-relevant tissues (e.g. growth plates) are difficult to study. To uncover mechanisms by which height GWAS variants function, we performed epigenetic profiling of murine femoral growth plates. The profiled open chromatin regions recapitulate known chondrocyte and skeletal biology, are enriched at height GWAS loci, particularly near differentially expressed growth plate genes, and enriched for binding motifs of transcription factors with roles in chondrocyte biology. At specific loci, our analyses identified compelling mechanisms for GWAS variants. For example, at CHSY1 , we identified a candidate causal variant (rs9920291) overlapping an open chromatin region. Reporter assays demonstrated that rs9920291 shows allelic regulatory activity, and CRISPR/Cas9 targeting of human chondrocytes demonstrates that the region regulates CHSY1 expression. Thus, integrating biologically relevant epigenetic information (here, from growth plates) with genetic association results can identify biological mechanisms important for human growth.

Enzymatic cybernetics: an unpublished work by Jacques Monod.

PubMed

Gayon, Jean

2015-06-01

In 1959, Jacques Monod wrote a manuscript entitled Cybernétique enzymatique [Enzymatic cybernetics]. Never published, this unpublished manuscript presents a synthesis of how Monod interpreted enzymatic adaptation just before the publication of the famous papers of the 1960s on the operon. In addition, Monod offers an example of a philosophy of biology immersed in scientific investigation. Monod's philosophical thoughts are classified into two categories, methodological and ontological. On the methodological side, Monod explicitly hints at his preferences regarding the scientific method in general: hypothetical-deductive method, and use of theoretical models. He also makes heuristic proposals regarding molecular biology: the need to analyse the phenomena in question at the level of individual cells, and the dual aspect of all biological explanation, functional and evolutionary. Ontological issues deal with the notions of information and genetic determinism, "cellular memory", the irrelevance of the notion of "living matter", and the usefulness of a cybernetic comprehension of molecular biology. Copyright © 2015 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Mirror me: Imitative responses in adults with autism.

PubMed

Schunke, Odette; Schöttle, Daniel; Vettorazzi, Eik; Brandt, Valerie; Kahl, Ursula; Bäumer, Tobias; Ganos, Christos; David, Nicole; Peiker, Ina; Engel, Andreas K; Brass, Marcel; Münchau, Alexander

2016-02-01

Dysfunctions of the human mirror neuron system have been postulated to underlie some deficits in autism spectrum disorders including poor imitative performance and impaired social skills. Using three reaction time experiments addressing mirror neuron system functions under simple and complex conditions, we examined 20 adult autism spectrum disorder participants and 20 healthy controls matched for age, gender and education. Participants performed simple finger-lifting movements in response to (1) biological finger and non-biological dot movement stimuli, (2) acoustic stimuli and (3) combined visual-acoustic stimuli with different contextual (compatible/incompatible) and temporal (simultaneous/asynchronous) relation. Mixed model analyses revealed slower reaction times in autism spectrum disorder. Both groups responded faster to biological compared to non-biological stimuli (Experiment 1) implying intact processing advantage for biological stimuli in autism spectrum disorder. In Experiment 3, both groups had similar 'interference effects' when stimuli were presented simultaneously. However, autism spectrum disorder participants had abnormally slow responses particularly when incompatible stimuli were presented consecutively. Our results suggest imitative control deficits rather than global imitative system impairments. © The Author(s) 2015.

Review of the fundamental theories behind small angle X-ray scattering, molecular dynamics simulations, and relevant integrated application

PubMed Central

Boldon, Lauren; Laliberte, Fallon; Liu, Li

2015-01-01

In this paper, the fundamental concepts and equations necessary for performing small angle X-ray scattering (SAXS) experiments, molecular dynamics (MD) simulations, and MD-SAXS analyses were reviewed. Furthermore, several key biological and non-biological applications for SAXS, MD, and MD-SAXS are presented in this review; however, this article does not cover all possible applications. SAXS is an experimental technique used for the analysis of a wide variety of biological and non-biological structures. SAXS utilizes spherical averaging to produce one- or two-dimensional intensity profiles, from which structural data may be extracted. MD simulation is a computer simulation technique that is used to model complex biological and non-biological systems at the atomic level. MD simulations apply classical Newtonian mechanics’ equations of motion to perform force calculations and to predict the theoretical physical properties of the system. This review presents several applications that highlight the ability of both SAXS and MD to study protein folding and function in addition to non-biological applications, such as the study of mechanical, electrical, and structural properties of non-biological nanoparticles. Lastly, the potential benefits of combining SAXS and MD simulations for the study of both biological and non-biological systems are demonstrated through the presentation of several examples that combine the two techniques. PMID:25721341

Integration of biological networks and gene expression data using Cytoscape

PubMed Central

Cline, Melissa S; Smoot, Michael; Cerami, Ethan; Kuchinsky, Allan; Landys, Nerius; Workman, Chris; Christmas, Rowan; Avila-Campilo, Iliana; Creech, Michael; Gross, Benjamin; Hanspers, Kristina; Isserlin, Ruth; Kelley, Ryan; Killcoyne, Sarah; Lotia, Samad; Maere, Steven; Morris, John; Ono, Keiichiro; Pavlovic, Vuk; Pico, Alexander R; Vailaya, Aditya; Wang, Peng-Liang; Adler, Annette; Conklin, Bruce R; Hood, Leroy; Kuiper, Martin; Sander, Chris; Schmulevich, Ilya; Schwikowski, Benno; Warner, Guy J; Ideker, Trey; Bader, Gary D

2013-01-01

Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape. PMID:17947979

A portal for the ocean biogeographic information system

USGS Publications Warehouse

Zhang, Yunqing; Grassle, J. F.

2002-01-01

Since its inception in 1999 the Ocean Biogeographic Information System (OBIS) has developed into an international science program as well as a globally distributed network of biogeographic databases. An OBIS portal at Rutgers University provides the links and functional interoperability among member database systems. Protocols and standards have been established to support effective communication between the portal and these functional units. The portal provides distributed data searching, a taxonomy name service, a GIS with access to relevant environmental data, biological modeling, and education modules for mariners, students, environmental managers, and scientists. The portal will integrate Census of Marine Life field projects, national data archives, and other functional modules, and provides for network-wide analyses and modeling tools.

Cell-Type-Specific Predictive Network Yields Novel Insights into Mouse Embryonic Stem Cell Self-Renewal and Cell Fate

PubMed Central

Dowell, Karen G.; Simons, Allen K.; Wang, Zack Z.; Yun, Kyuson; Hibbs, Matthew A.

2013-01-01

Self-renewal, the ability of a stem cell to divide repeatedly while maintaining an undifferentiated state, is a defining characteristic of all stem cells. Here, we clarify the molecular foundations of mouse embryonic stem cell (mESC) self-renewal by applying a proven Bayesian network machine learning approach to integrate high-throughput data for protein function discovery. By focusing on a single stem-cell system, at a specific developmental stage, within the context of well-defined biological processes known to be active in that cell type, we produce a consensus predictive network that reflects biological reality more closely than those made by prior efforts using more generalized, context-independent methods. In addition, we show how machine learning efforts may be misled if the tissue specific role of mammalian proteins is not defined in the training set and circumscribed in the evidential data. For this study, we assembled an extensive compendium of mESC data: ∼2.2 million data points, collected from 60 different studies, under 992 conditions. We then integrated these data into a consensus mESC functional relationship network focused on biological processes associated with embryonic stem cell self-renewal and cell fate determination. Computational evaluations, literature validation, and analyses of predicted functional linkages show that our results are highly accurate and biologically relevant. Our mESC network predicts many novel players involved in self-renewal and serves as the foundation for future pluripotent stem cell studies. This network can be used by stem cell researchers (at http://StemSight.org) to explore hypotheses about gene function in the context of self-renewal and to prioritize genes of interest for experimental validation. PMID:23468881

Global Proteome Analyses of Lysine Acetylation and Succinylation Reveal the Widespread Involvement of both Modification in Metabolism in the Embryo of Germinating Rice Seed.

PubMed

He, Dongli; Wang, Qiong; Li, Ming; Damaris, Rebecca Njeri; Yi, Xingling; Cheng, Zhongyi; Yang, Pingfang

2016-03-04

Regulation of rice seed germination has been shown to mainly occur at post-transcriptional levels, of which the changes on proteome status is a major one. Lysine acetylation and succinylation are two prevalent protein post-translational modifications (PTMs) involved in multiple biological processes, especially for metabolism regulation. To investigate the potential mechanism controlling metabolism regulation in rice seed germination, we performed the lysine acetylation and succinylation analyses simultaneously. Using high-accuracy nano-LC-MS/MS in combination with the enrichment of lysine acetylated or succinylated peptides from digested embryonic proteins of 24 h after imbibition (HAI) rice seed, a total of 699 acetylated sites from 389 proteins and 665 succinylated sites from 261 proteins were identified. Among these modified lysine sites, 133 sites on 78 proteins were commonly modified by two PTMs. The overlapped PTM sites were more likely to be in polar acidic/basic amino acid regions and exposed on the protein surface. Both of the acetylated and succinylated proteins cover nearly all aspects of cellular functions. Ribosome complex and glycolysis/gluconeogenesis-related proteins were significantly enriched in both acetylated and succinylated protein profiles through KEGG enrichment and protein-protein interaction network analyses. The acetyl-CoA and succinyl-CoA metabolism-related enzymes were found to be extensively modified by both modifications, implying the functional interaction between the two PTMs. This study provides a rich resource to examine the modulation of the two PTMs on the metabolism pathway and other biological processes in germinating rice seed.

Healthy ageing in the Nun Study: definition and neuropathologic correlates.

PubMed

Tyas, Suzanne L; Snowdon, David A; Desrosiers, Mark F; Riley, Kathryn P; Markesbery, William R

2007-11-01

Although the concept of healthy ageing has stimulated considerable interest, no generally accepted definition has been developed nor has its biological basis been determined. To develop a definition of healthy ageing and investigate its association with longevity and neuropathology. Analyses were based on cognitive, physical, and post-mortem assessments from 1991 to 1998 in the Nun Study, a longitudinal study of ageing in participants 75+ years at baseline. We defined three mutually exclusive levels of healthy ageing (excellent, very good, and good) based on measures of global cognitive function, short-term memory, basic and instrumental activities of daily living, and self-rated function. Mortality analyses were based on 636 participants; neuropathologic analyses were restricted to 221 who had died and were autopsied. Only 11% of those meeting criteria for the excellent level of healthy ageing at baseline subsequently died, compared with 24% for the very good, 39% for the good, and 60% for the remaining participants. Survival curves showed significantly greater longevity with higher levels of healthy ageing. The risk of not attaining healthy ageing, adjusted for age, increased two-fold in participants with brain infarcts alone, six-fold in those with Alzheimer neuropathology alone, and more than thirteen-fold in those with both brain infarcts and Alzheimer neuropathology. The biological validity of our definition of healthy ageing is supported by its strong association with mortality and longevity. Avoiding Alzheimer and stroke neuropathology is critical to the maintenance of healthy ageing, and the presence of both pathologies dramatically decreases the likelihood of healthy ageing.

Healthy ageing in the Nun Study: definition and neuropathologic correlates

PubMed Central

Tyas, Suzanne L.; Snowdon, David A.; Desrosiers, Mark F.; Riley, Kathryn P.; Markesbery, William R.

2008-01-01

Background although the concept of healthy ageing has stimulated considerable interest, no generally accepted definition has been developed nor has its biological basis been determined. Objective to develop a definition of healthy ageing and investigate its association with longevity and neuropathology. Methods analyses were based on cognitive, physical, and post-mortem assessments from 1991 to 1998 in the Nun Study, a longitudinal study of ageing in participants 75+ years at baseline. We defined three mutually exclusive levels of healthy ageing (excellent, very good, and good) based on measures of global cognitive function, short-term memory, basic and instrumental activities of daily living, and self-rated function. Mortality analyses were based on 636 participants; neuropathologic analyses were restricted to 221 who had died and were autopsied. Results only 11% of those meeting criteria for the excellent level of healthy ageing at baseline subsequently died, compared with 24% for the very good, 39% for the good, and 60% for the remaining participants. Survival curves showed significantly greater longevity with higher levels of healthy ageing. The risk of not attaining healthy ageing, adjusted for age, increased two-fold in participants with brain infarcts alone, six-fold in those with Alzheimer neuropathology alone, and more than thirteen-fold in those with both brain infarcts and Alzheimer neuropathology. Conclusions the biological validity of our definition of healthy ageing is supported by its strong association with mortality and longevity. Avoiding Alzheimer and stroke neuropathology is critical to the maintenance of healthy ageing, and the presence of both pathologies dramatically decreases the likelihood of healthy ageing. PMID:17906306

Multifaceted origins of sex differences in the brain

PubMed Central

2016-01-01

Studies of sex differences in the brain range from reductionistic cell and molecular analyses in animal models to functional imaging in awake human subjects, with many other levels in between. Interpretations and conclusions about the importance of particular differences often vary with differing levels of analyses and can lead to discord and dissent. In the past two decades, the range of neurobiological, psychological and psychiatric endpoints found to differ between males and females has expanded beyond reproduction into every aspect of the healthy and diseased brain, and thereby demands our attention. A greater understanding of all aspects of neural functioning will only be achieved by incorporating sex as a biological variable. The goal of this review is to highlight the current state of the art of the discipline of sex differences research with an emphasis on the brain and to contextualize the articles appearing in the accompanying special issue. PMID:26833829

Structural Characteristics of the Novel Polysaccharide FVPA1 from Winter Culinary-Medicinal Mushroom, Flammulina velutipes (Agaricomycetes), Capable of Enhancing Natural Killer Cell Activity against K562 Tumor Cells.

PubMed

Jia, Wei; Feng, Jie; Zhang, Jing-Song; Lin, Chi-Chung; Wang, Wen-Han; Chen, Hong-Ge

2017-01-01

FVPA1, a novel polysaccharide, has been isolated from fruiting bodies of the culinary-medicinal mushroom Flammulina velutipes, a historically popular, widely cultivated and consumed functional food with an attractive taste, beneficial nutraceutical properties such as antitumor and immunomodulatory effects, and a number of essential biological activities. The average molecular weight was estimated to be ~1.8 × 104 Da based on high-performance size exclusion chromatography. Sugar analyses, methylation analyses, and 1H, 13C, and 2-dimensional nuclear magnetic resonance spectroscopy revealed the following structure of the repeating units of the FVPA1 polysaccharide Identification of this structure would conceivably lead to better understanding of the nutraceutical functions of this very important edible fungus. Bioactivity tests in vitro indicated that FVPA1 could significantly enhance natural killer cell activity against K562 tumor cells.

Computational analysis of conserved RNA secondary structure in transcriptomes and genomes.

PubMed

Eddy, Sean R

2014-01-01

Transcriptomics experiments and computational predictions both enable systematic discovery of new functional RNAs. However, many putative noncoding transcripts arise instead from artifacts and biological noise, and current computational prediction methods have high false positive rates. I discuss prospects for improving computational methods for analyzing and identifying functional RNAs, with a focus on detecting signatures of conserved RNA secondary structure. An interesting new front is the application of chemical and enzymatic experiments that probe RNA structure on a transcriptome-wide scale. I review several proposed approaches for incorporating structure probing data into the computational prediction of RNA secondary structure. Using probabilistic inference formalisms, I show how all these approaches can be unified in a well-principled framework, which in turn allows RNA probing data to be easily integrated into a wide range of analyses that depend on RNA secondary structure inference. Such analyses include homology search and genome-wide detection of new structural RNAs.

PANDORA: keyword-based analysis of protein sets by integration of annotation sources.

PubMed

Kaplan, Noam; Vaaknin, Avishay; Linial, Michal

2003-10-01

Recent advances in high-throughput methods and the application of computational tools for automatic classification of proteins have made it possible to carry out large-scale proteomic analyses. Biological analysis and interpretation of sets of proteins is a time-consuming undertaking carried out manually by experts. We have developed PANDORA (Protein ANnotation Diagram ORiented Analysis), a web-based tool that provides an automatic representation of the biological knowledge associated with any set of proteins. PANDORA uses a unique approach of keyword-based graphical analysis that focuses on detecting subsets of proteins that share unique biological properties and the intersections of such sets. PANDORA currently supports SwissProt keywords, NCBI Taxonomy, InterPro entries and the hierarchical classification terms from ENZYME, SCOP and GO databases. The integrated study of several annotation sources simultaneously allows a representation of biological relations of structure, function, cellular location, taxonomy, domains and motifs. PANDORA is also integrated into the ProtoNet system, thus allowing testing thousands of automatically generated clusters. We illustrate how PANDORA enhances the biological understanding of large, non-uniform sets of proteins originating from experimental and computational sources, without the need for prior biological knowledge on individual proteins.

An Integrated Approach for a Structural and Functional Evaluation of Biosimilars: Implications for Erythropoietin.

PubMed

Gianoncelli, Alessandra; Bonini, Sara A; Bertuzzi, Michela; Guarienti, Michela; Vezzoli, Sara; Kumar, Rajesh; Delbarba, Andrea; Mastinu, Andrea; Sigala, Sandra; Spano, Pierfranco; Pani, Luca; Pecorelli, Sergio; Memo, Maurizio

2015-08-01

Authorization to market a biosimilar product by the appropriate institutions is expected based on biosimilarity with its originator product. The analogy between the originator and its biosimilar(s) is assessed through safety, purity, and potency analyses. In this study, we proposed a useful quality control system for rapid and economic primary screening of potential biosimilar drugs. For this purpose, chemical and functional characterization of the originator rhEPO alfa and two of its biosimilars was discussed. Qualitative and quantitative analyses of the originator rhEPO alfa and its biosimilars were performed using reversed-phase high-performance liquid chromatography (RP-HPLC). The identification of proteins and the separation of isoforms were studied using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and two-dimensional gel electrophoresis (2D-PAGE), respectively. Furthermore, the biological activity of these drugs was measured both in vitro, evaluating the TF-1 cell proliferation rate, and in vivo, using the innovative experimental animal model of the zebrafish embryos. Chemical analyses showed that the quantitative concentrations of rhEPO alfa were in agreement with the labeled claims by the corresponding manufacturers. The qualitative analyses performed demonstrated that the three drugs were pure and that they had the same amino acid sequence. Chemical differences were found only at the level of isoforms containing N-glycosylation; however, functional in vitro and in vivo studies did not show any significant differences from a biosimilar point of view. These rapid and economic structural and functional analyses were effective in the evaluation of the biosimilarity between the originator rhEPO alfa and the biosimilars analyzed.

Differences in carbon source usage by dental plaque in children with and without early childhood caries

PubMed Central

Zhao, Yan; Zhong, Wen-Jie; Xun, Zhe; Zhang, Qian; Song, Ye-Qing; Liu, Yun-Song; Chen, Feng

2017-01-01

Early childhood caries (ECC) is a considerable pediatric and public health problem worldwide. Preceding studies have focused primarily on bacterial diversity at the taxonomic level. Although these studies have provided significant information regarding the connection between dental caries and oral microbiomes, further comprehension of this microbial community’s ecological relevance is limited. This study identified the carbon source metabolic differences in dental plaque between children with and without ECC. We compared the microbial community functional diversity in 18 caries-free subjects with 18 severe ECC patients based on sole carbon source usage using a Biolog assay. The anaerobic microbial community in the ECC patients displayed greater metabolic activity than that of the control group. Specific carbon source metabolism differed significantly between the two groups. Subjects from the two groups were well distinguished by cluster and principal component analyses based on discriminative carbon sources. Our results implied that the microbial functional diversity between the ECC patients and healthy subjects differed significantly. In addition, the Biolog assay furthered our understanding of oral microbiomes as a composite of functional abilities, thus enabling us to identify the ecologically relevant functional differences among oral microbial communities.

From protein interaction profile to functional assignment: the human protein Ki-1/57 is associated with pre-mRNA splicing events.

PubMed

Bressan, Gustavo Costa; Kobarg, Jörg

2010-01-01

The mapping of protein-protein interactions of a determined organism is considered fundamental to assign protein function in the post-genomic era. As part of this effort, screenings for pairwise interactions by yeast two-hybrid system have been used popularly to reveal protein interaction networks in different biological systems. Through the identification of protein interaction partners we have successfully obtained interesting functional clues for Ki-1/57, a human protein with no previous functional annotation, in the context of RNA metabolism. We briefly discuss the way we approached protein-protein interaction data to conduct and interpret further molecular biological and cellular studies as well as structural analyses on this protein. Our data suggest that Ki-1/57 belongs to the family of intrinsically unstructured proteins and that the structural flexibility may be crucial for its capacity to interact with many different proteins. A large fraction of these proteins are involved in pre-mRNA splicing control. Finally, Ki-1/57 is localized to several subnuclear domains, all of which have been described to splicing and other RNA processing events.

Integrated microfluidic devices for combinatorial cell-based assays.

PubMed

Yu, Zeta Tak For; Kamei, Ken-ichiro; Takahashi, Hiroko; Shu, Chengyi Jenny; Wang, Xiaopu; He, George Wenfu; Silverman, Robert; Radu, Caius G; Witte, Owen N; Lee, Ki-Bum; Tseng, Hsian-Rong

2009-06-01

The development of miniaturized cell culture platforms for performing parallel cultures and combinatorial assays is important in cell biology from the single-cell level to the system level. In this paper we developed an integrated microfluidic cell-culture platform, Cell-microChip (Cell-microChip), for parallel analyses of the effects of microenvironmental cues (i.e., culture scaffolds) on different mammalian cells and their cellular responses to external stimuli. As a model study, we demonstrated the ability of culturing and assaying several mammalian cells, such as NIH 3T3 fibroblast, B16 melanoma and HeLa cell lines, in a parallel way. For functional assays, first we tested drug-induced apoptotic responses from different cell lines. As a second functional assay, we performed "on-chip" transfection of a reporter gene encoding an enhanced green fluorescent protein (EGFP) followed by live-cell imaging of transcriptional activation of cyclooxygenase 2 (Cox-2) expression. Collectively, our Cell-microChip approach demonstrated the capability to carry out parallel operations and the potential to further integrate advanced functions and applications in the broader space of combinatorial chemistry and biology.

Human Induced Pluripotent Stem Cell-Derived Macrophages for Unraveling Human Macrophage Biology.

PubMed

Zhang, Hanrui; Reilly, Muredach P

2017-11-01

Despite a substantial appreciation for the critical role of macrophages in cardiometabolic diseases, understanding of human macrophage biology has been hampered by the lack of reliable and scalable models for cellular and genetic studies. Human induced pluripotent stem cell (iPSC)-derived macrophages (IPSDM), as an unlimited source of subject genotype-specific cells, will undoubtedly play an important role in advancing our understanding of the role of macrophages in human diseases. In this review, we summarize current literature in the differentiation and characterization of IPSDM at phenotypic, functional, and transcriptomic levels. We emphasize the progress in differentiating iPSC to tissue resident macrophages, and in understanding the ontogeny of in vitro differentiated IPSDM that resembles primitive hematopoiesis, rather than adult definitive hematopoiesis. We review the application of IPSDM in modeling both Mendelian genetic disorders and host-pathogen interactions. Finally, we highlighted the potential areas of research using IPSDM in functional validation of coronary artery disease loci in genome-wide association studies, functional genomic analyses, drug testing, and cell therapeutics in cardiovascular diseases. © 2017 American Heart Association, Inc.

Integrated microfluidic devices for combinatorial cell-based assays

PubMed Central

Yu, Zeta Tak For; Kamei, Ken-ichiro; Takahashi, Hiroko; Shu, Chengyi Jenny; Wang, Xiaopu; He, George Wenfu; Silverman, Robert

2010-01-01

The development of miniaturized cell culture platforms for performing parallel cultures and combinatorial assays is important in cell biology from the single-cell level to the system level. In this paper we developed an integrated microfluidic cell-culture platform, Cell-microChip (Cell-μChip), for parallel analyses of the effects of microenvir-onmental cues (i.e., culture scaffolds) on different mammalian cells and their cellular responses to external stimuli. As a model study, we demonstrated the ability of culturing and assaying several mammalian cells, such as NIH 3T3 fibro-blast, B16 melanoma and HeLa cell lines, in a parallel way. For functional assays, first we tested drug-induced apoptotic responses from different cell lines. As a second functional assay, we performed "on-chip" transfection of a reporter gene encoding an enhanced green fluorescent protein (EGFP) followed by live-cell imaging of transcriptional activation of cyclooxygenase 2 (Cox-2) expression. Collectively, our Cell-μChip approach demonstrated the capability to carry out parallel operations and the potential to further integrate advanced functions and applications in the broader space of combinatorial chemistry and biology. PMID:19130244

Will Systems Biology Deliver Its Promise and Contribute to the Development of New or Improved Vaccines? What Really Constitutes the Study of "Systems Biology" and How Might Such an Approach Facilitate Vaccine Design.

PubMed

Germain, Ronald N

2017-10-16

A dichotomy exists in the field of vaccinology about the promise versus the hype associated with application of "systems biology" approaches to rational vaccine design. Some feel it is the only way to efficiently uncover currently unknown parameters controlling desired immune responses or discover what elements actually mediate these responses. Others feel that traditional experimental, often reductionist, methods for incrementally unraveling complex biology provide a more solid way forward, and that "systems" approaches are costly ways to collect data without gaining true insight. Here I argue that both views are inaccurate. This is largely because of confusion about what can be gained from classical experimentation versus statistical analysis of large data sets (bioinformatics) versus methods that quantitatively explain emergent properties of complex assemblies of biological components, with the latter reflecting what was previously called "physiology." Reductionist studies will remain essential for generating detailed insight into the functional attributes of specific elements of biological systems, but such analyses lack the power to provide a quantitative and predictive understanding of global system behavior. But by employing (1) large-scale screening methods for discovery of unknown components and connections in the immune system ( omics ), (2) statistical analysis of large data sets ( bioinformatics ), and (3) the capacity of quantitative computational methods to translate these individual components and connections into models of emergent behavior ( systems biology ), we will be able to better understand how the overall immune system functions and to determine with greater precision how to manipulate it to produce desired protective responses. Copyright © 2017 Cold Spring Harbor Laboratory Press; all rights reserved.

Procurement of a Nanoindenter for Structure-Function Analyses of Biologically Inspired High Performance Composite Materials

DTIC Science & Technology

2012-01-13

abalone shell (Figures 3, 4). Here, we can see that the damage is significantly mitigated in the nacreous regions while cracks formed in the Calcitic...properties. Page 5 / 11 Identifying the crack propagation mechanisms helps to identify new designs for impact resistant materials, so the...human tooth from dentin – dentin/ enamel junction – enamel . It is clear that higher resolution scans are necessary to interrogate local structure

CADDIS Volume 4. Data Analysis: Advanced Analyses - Controlling for Natural Variability

EPA Pesticide Factsheets

Methods for controlling natural variability, predicting environmental conditions from biological observations method, biological trait data, species sensitivity distributions, propensity scores, Advanced Analyses of Data Analysis references.

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

Structure-guided discovery of the metabolite carboxy-SAM that modulates tRNA function.

PubMed

Kim, Jungwook; Xiao, Hui; Bonanno, Jeffrey B; Kalyanaraman, Chakrapani; Brown, Shoshana; Tang, Xiangying; Al-Obaidi, Nawar F; Patskovsky, Yury; Babbitt, Patricia C; Jacobson, Matthew P; Lee, Young-Sam; Almo, Steven C

2013-06-06

The identification of novel metabolites and the characterization of their biological functions are major challenges in biology. X-ray crystallography can reveal unanticipated ligands that persist through purification and crystallization. These adventitious protein-ligand complexes provide insights into new activities, pathways and regulatory mechanisms. We describe a new metabolite, carboxy-S-adenosyl-l-methionine (Cx-SAM), its biosynthetic pathway and its role in transfer RNA modification. The structure of CmoA, a member of the SAM-dependent methyltransferase superfamily, revealed a ligand consistent with Cx-SAM in the catalytic site. Mechanistic analyses showed an unprecedented role for prephenate as the carboxyl donor and the involvement of a unique ylide intermediate as the carboxyl acceptor in the CmoA-mediated conversion of SAM to Cx-SAM. A second member of the SAM-dependent methyltransferase superfamily, CmoB, recognizes Cx-SAM and acts as a carboxymethyltransferase to convert 5-hydroxyuridine into 5-oxyacetyl uridine at the wobble position of multiple tRNAs in Gram-negative bacteria, resulting in expanded codon-recognition properties. CmoA and CmoB represent the first documented synthase and transferase for Cx-SAM. These findings reveal new functional diversity in the SAM-dependent methyltransferase superfamily and expand the metabolic and biological contributions of SAM-based biochemistry. These discoveries highlight the value of structural genomics approaches in identifying ligands within the context of their physiologically relevant macromolecular binding partners, and in revealing their functions.

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge

PubMed Central

Wagner, Florian

2015-01-01

Method Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. Results I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets. PMID:26575370

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge.

PubMed

Wagner, Florian

2015-01-01

Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets.

Knockdown of stem cell regulator Oct4A in ovarian cancer reveals cellular reprogramming associated with key regulators of cytoskeleton-extracellular matrix remodelling

PubMed Central

Samardzija, Chantel; Greening, David W.; Escalona, Ruth; Chen, Maoshan; Bilandzic, Maree; Luwor, Rodney; Kannourakis, George; Findlay, Jock K.; Ahmed, Nuzhat

2017-01-01

Oct4A is a master regulator of self-renewal and pluripotency in embryonic stem cells. It is a well-established marker for cancer stem cell (CSC) in malignancies. Recently, using a loss of function studies, we have demonstrated key roles for Oct4A in tumor cell survival, metastasis and chemoresistance in in vitro and in vivo models of ovarian cancer. In an effort to understand the regulatory role of Oct4A in tumor biology, we employed the use of an ovarian cancer shRNA Oct4A knockdown cell line (HEY Oct4A KD) and a global mass spectrometry (MS)-based proteomic analysis to investigate novel biological targets of Oct4A in HEY samples (cell lysates, secretomes and mouse tumor xenografts). Based on significant differential expression, pathway and protein network analyses, and comprehensive literature search we identified key proteins involved with biologically relevant functions of Oct4A in tumor biology. Across all preparations of HEY Oct4A KD samples significant alterations in protein networks associated with cytoskeleton, extracellular matrix (ECM), proliferation, adhesion, metabolism, epithelial-mesenchymal transition (EMT), cancer stem cells (CSCs) and drug resistance was observed. This comprehensive proteomics study for the first time presents the Oct4A associated proteome and expands our understanding on the biological role of this stem cell regulator in carcinomas. PMID:28406185

Deconstructing the core dynamics from a complex time-lagged regulatory biological circuit.

PubMed

Eriksson, O; Brinne, B; Zhou, Y; Björkegren, J; Tegnér, J

2009-03-01

Complex regulatory dynamics is ubiquitous in molecular networks composed of genes and proteins. Recent progress in computational biology and its application to molecular data generate a growing number of complex networks. Yet, it has been difficult to understand the governing principles of these networks beyond graphical analysis or extensive numerical simulations. Here the authors exploit several simplifying biological circumstances which thereby enable to directly detect the underlying dynamical regularities driving periodic oscillations in a dynamical nonlinear computational model of a protein-protein network. System analysis is performed using the cell cycle, a mathematically well-described complex regulatory circuit driven by external signals. By introducing an explicit time delay and using a 'tearing-and-zooming' approach the authors reduce the system to a piecewise linear system with two variables that capture the dynamics of this complex network. A key step in the analysis is the identification of functional subsystems by identifying the relations between state-variables within the model. These functional subsystems are referred to as dynamical modules operating as sensitive switches in the original complex model. By using reduced mathematical representations of the subsystems the authors derive explicit conditions on how the cell cycle dynamics depends on system parameters, and can, for the first time, analyse and prove global conditions for system stability. The approach which includes utilising biological simplifying conditions, identification of dynamical modules and mathematical reduction of the model complexity may be applicable to other well-characterised biological regulatory circuits. [Includes supplementary material].

Long Non-Coding RNA as Potential Biomarker for Prostate Cancer: Is It Making a Difference?

PubMed

Deng, Junli; Tang, Jie; Wang, Guo; Zhu, Yuan-Shan

2017-03-07

Whole genome transcriptomic analyses have identified numerous long non-coding RNA (lncRNA) transcripts that are increasingly implicated in cancer biology. LncRNAs are found to promote essential cancer cell functions such as proliferation, invasion, and metastasis, with the potential to serve as novel biomarkers of various cancers and to further reveal uncharacterized aspects of tumor biology. However, the biological and molecular mechanisms as well as the clinical applications of lncRNAs in diverse diseases are not completely understood, and remain to be fully explored. LncRNAs may be critical players and regulators in prostate cancer carcinogenesis and progression, and could serve as potential biomarkers for prostate cancer. This review focuses on lncRNA biomarkers that are already available for clinical use and provides an overview of lncRNA biomarkers that are under investigation for clinical development in prostate cancer.

Damage-free vibrational spectroscopy of biological materials in the electron microscope

PubMed Central

Rez, Peter; Aoki, Toshihiro; March, Katia; Gur, Dvir; Krivanek, Ondrej L.; Dellby, Niklas; Lovejoy, Tracy C.; Wolf, Sharon G.; Cohen, Hagai

2016-01-01

Vibrational spectroscopy in the electron microscope would be transformative in the study of biological samples, provided that radiation damage could be prevented. However, electron beams typically create high-energy excitations that severely accelerate sample degradation. Here this major difficulty is overcome using an ‘aloof' electron beam, positioned tens of nanometres away from the sample: high-energy excitations are suppressed, while vibrational modes of energies <1 eV can be ‘safely' investigated. To demonstrate the potential of aloof spectroscopy, we record electron energy loss spectra from biogenic guanine crystals in their native state, resolving their characteristic C–H, N–H and C=O vibrational signatures with no observable radiation damage. The technique opens up the possibility of non-damaging compositional analyses of organic functional groups, including non-crystalline biological materials, at a spatial resolution of ∼10 nm, simultaneously combined with imaging in the electron microscope. PMID:26961578

Damage-free vibrational spectroscopy of biological materials in the electron microscope.

PubMed

Rez, Peter; Aoki, Toshihiro; March, Katia; Gur, Dvir; Krivanek, Ondrej L; Dellby, Niklas; Lovejoy, Tracy C; Wolf, Sharon G; Cohen, Hagai

2016-03-10

Vibrational spectroscopy in the electron microscope would be transformative in the study of biological samples, provided that radiation damage could be prevented. However, electron beams typically create high-energy excitations that severely accelerate sample degradation. Here this major difficulty is overcome using an 'aloof' electron beam, positioned tens of nanometres away from the sample: high-energy excitations are suppressed, while vibrational modes of energies <1 eV can be 'safely' investigated. To demonstrate the potential of aloof spectroscopy, we record electron energy loss spectra from biogenic guanine crystals in their native state, resolving their characteristic C-H, N-H and C=O vibrational signatures with no observable radiation damage. The technique opens up the possibility of non-damaging compositional analyses of organic functional groups, including non-crystalline biological materials, at a spatial resolution of ∼10 nm, simultaneously combined with imaging in the electron microscope.

Damage-free vibrational spectroscopy of biological materials in the electron microscope

DOE PAGES

Rez, Peter; Aoki, Toshihiro; March, Katia; ...

2016-03-10

Vibrational spectroscopy in the electron microscope would be transformative in the study of biological samples, provided that radiation damage could be prevented. However, electron beams typically create high-energy excitations that severely accelerate sample degradation. Here this major difficulty is overcome using an ‘aloof’ electron beam, positioned tens of nanometres away from the sample: high-energy excitations are suppressed, while vibrational modes of energies o1 eV can be ‘safely’ investigated. To demonstrate the potential of aloof spectroscopy, we record electron energy loss spectra from biogenic guanine crystals in their native state, resolving their characteristic C–H, N–H and C=O vibrational signatures with nomore » observable radiation damage. Furthermore, the technique opens up the possibility of non-damaging compositional analyses of organic functional groups, including non-crystalline biological materials, at a spatial resolution of ~10nm, simultaneously combined with imaging in the electron microscope.« less

Damage-free vibrational spectroscopy of biological materials in the electron microscope

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

Rez, Peter; Aoki, Toshihiro; March, Katia

Vibrational spectroscopy in the electron microscope would be transformative in the study of biological samples, provided that radiation damage could be prevented. However, electron beams typically create high-energy excitations that severely accelerate sample degradation. Here this major difficulty is overcome using an ‘aloof’ electron beam, positioned tens of nanometres away from the sample: high-energy excitations are suppressed, while vibrational modes of energies o1 eV can be ‘safely’ investigated. To demonstrate the potential of aloof spectroscopy, we record electron energy loss spectra from biogenic guanine crystals in their native state, resolving their characteristic C–H, N–H and C=O vibrational signatures with nomore » observable radiation damage. Furthermore, the technique opens up the possibility of non-damaging compositional analyses of organic functional groups, including non-crystalline biological materials, at a spatial resolution of ~10nm, simultaneously combined with imaging in the electron microscope.« less

Integrative biological analysis for neuropsychopharmacology.

PubMed

Emmett, Mark R; Kroes, Roger A; Moskal, Joseph R; Conrad, Charles A; Priebe, Waldemar; Laezza, Fernanda; Meyer-Baese, Anke; Nilsson, Carol L

2014-01-01

Although advances in psychotherapy have been made in recent years, drug discovery for brain diseases such as schizophrenia and mood disorders has stagnated. The need for new biomarkers and validated therapeutic targets in the field of neuropsychopharmacology is widely unmet. The brain is the most complex part of human anatomy from the standpoint of number and types of cells, their interconnections, and circuitry. To better meet patient needs, improved methods to approach brain studies by understanding functional networks that interact with the genome are being developed. The integrated biological approaches--proteomics, transcriptomics, metabolomics, and glycomics--have a strong record in several areas of biomedicine, including neurochemistry and neuro-oncology. Published applications of an integrated approach to projects of neurological, psychiatric, and pharmacological natures are still few but show promise to provide deep biological knowledge derived from cells, animal models, and clinical materials. Future studies that yield insights based on integrated analyses promise to deliver new therapeutic targets and biomarkers for personalized medicine.

Getting the most out of parasitic helminth transcriptomes using HelmDB: implications for biology and biotechnology.

PubMed

Mangiola, Stefano; Young, Neil D; Korhonen, Pasi; Mondal, Alinda; Scheerlinck, Jean-Pierre; Sternberg, Paul W; Cantacessi, Cinzia; Hall, Ross S; Jex, Aaron R; Gasser, Robin B

2013-12-01

Compounded by a massive global food shortage, many parasitic diseases have a devastating, long-term impact on animal and human health and welfare worldwide. Parasitic helminths (worms) affect the health of billions of animals. Unlocking the systems biology of these neglected pathogens will underpin the design of new and improved interventions against them. Currently, the functional annotation of genomic and transcriptomic sequence data for socio-economically important parasitic worms relies almost exclusively on comparative bioinformatic analyses using model organism- and other databases. However, many genes and gene products of parasitic helminths (often >50%) cannot be annotated using this approach, because they are specific to parasites and/or do not have identifiable homologs in other organisms for which sequence data are available. This inability to fully annotate transcriptomes and predicted proteomes is a major challenge and constrains our understanding of the biology of parasites, interactions with their hosts and of parasitism and the pathogenesis of disease on a molecular level. In the present article, we compiled transcriptomic data sets of key, socioeconomically important parasitic helminths, and constructed and validated a curated database, called HelmDB (www.helmdb.org). We demonstrate how this database can be used effectively for the improvement of functional annotation by employing data integration and clustering. Importantly, HelmDB provides a practical and user-friendly toolkit for sequence browsing and comparative analyses among divergent helminth groups (including nematodes and trematodes), and should be readily adaptable and applicable to a wide range of other organisms. This web-based, integrative database should assist 'systems biology' studies of parasitic helminths, and the discovery and prioritization of novel drug and vaccine targets. This focus provides a pathway toward developing new and improved approaches for the treatment and control of parasitic diseases, with the potential for important biotechnological outcomes. Copyright © 2012 Elsevier Inc. All rights reserved.

Disruption of functional networks in dyslexia: a whole-brain, data-driven analysis of connectivity.

PubMed

Finn, Emily S; Shen, Xilin; Holahan, John M; Scheinost, Dustin; Lacadie, Cheryl; Papademetris, Xenophon; Shaywitz, Sally E; Shaywitz, Bennett A; Constable, R Todd

2014-09-01

Functional connectivity analyses of functional magnetic resonance imaging data are a powerful tool for characterizing brain networks and how they are disrupted in neural disorders. However, many such analyses examine only one or a small number of a priori seed regions. Studies that consider the whole brain frequently rely on anatomic atlases to define network nodes, which might result in mixing distinct activation time-courses within a single node. Here, we improve upon previous methods by using a data-driven brain parcellation to compare connectivity profiles of dyslexic (DYS) versus non-impaired (NI) readers in the first whole-brain functional connectivity analysis of dyslexia. Whole-brain connectivity was assessed in children (n = 75; 43 NI, 32 DYS) and adult (n = 104; 64 NI, 40 DYS) readers. Compared to NI readers, DYS readers showed divergent connectivity within the visual pathway and between visual association areas and prefrontal attention areas; increased right-hemisphere connectivity; reduced connectivity in the visual word-form area (part of the left fusiform gyrus specialized for printed words); and persistent connectivity to anterior language regions around the inferior frontal gyrus. Together, findings suggest that NI readers are better able to integrate visual information and modulate their attention to visual stimuli, allowing them to recognize words on the basis of their visual properties, whereas DYS readers recruit altered reading circuits and rely on laborious phonology-based "sounding out" strategies into adulthood. These results deepen our understanding of the neural basis of dyslexia and highlight the importance of synchrony between diverse brain regions for successful reading. © 2013 Society of Biological Psychiatry Published by Society of Biological Psychiatry All rights reserved.

'Appeals to nature' in marriage equality debates: A content analysis of newspaper and social media discourse.

PubMed

O'Connor, Cliodhna

2017-09-01

In May 2015, Ireland held a referendum to legalize same-sex marriage, which passed with 62% of the vote. This study explores the role played by 'appeals to nature' in the referendum debate. Little research has investigated how biological attributions are spontaneously generated in real-world discourse regarding sexual rights. Through content analysis of newspaper and Twitter discussion of the referendum, this study aims to (1) establish the frequency of appeals to nature and their distribution across the various 'sides' of the debate and (2) analyse the forms these natural claims took and the rhetorical functions they fulfilled. Appeals to nature occurred in a minority of media discussion of the referendum (13.6% of newspaper articles and .3% of tweets). They were more prominent in material produced by anti-marriage equality commentators. Biological attributions predominantly occurred in relation to parenthood, traditional marriage, gender, and homosexuality. The article analyses the rhetorical dynamics of these natural claims and considers the implications for marriage equality research and activism. The analysis suggests appeals to nature allow anti-marriage equality discourse adapt to a cultural context that proscribes outright disapproval of same-sex relationships. However, it also queries whether previous research has overemphasized the significance of biological attributions in discourse about groups' rights. © 2017 The British Psychological Society.

The biological pump and lower trophic level controls on carbon cycling in Lake Superior: Insights from a multi-pronged study

NASA Astrophysics Data System (ADS)

Schreiner, K. M.; Bramburger, A.; Ozersky, T.; Sheik, C.; Steinman, B. A.

2016-02-01

Lake Superior is the largest freshwater lake in the world, supporting economically important fisheries and providing drinking water to hundreds of thousands of people. In recent decades, summer surface water temperature and the intensity and duration of water column stratification in the lake has increased steadily. These physical changes have resulted in significant perturbations to lower trophic level ecosystem characteristics. Recent observations of Great Lakes plankton assemblages have revealed multi-decadal patterns of community reorganization, with increased relative abundance of taxa characteristic of warmer waters. These changes, coupled with changing nutrient concentrations and colonization by non-native taxa, threaten to shift trophic structure and carbon dynamics at the bottom of the food web. To this end, this study seeks to quantify the impacts of this ecosystem shift on carbon fixation, the biological pump, and organic carbon cycling in Lake Superior. Utilizing a combined sampling approach, in the summer of 2015 we collected water, sediment, and biological samples across a nearshore-to-offshore gradient in the western arm of Lake Superior. Analyses included the community composition of bacteria, archaea, phytoplankton, and zooplankton; water column carbon and nutrient speciation; algal pigments and pigment degradation products; and net primary productivity. The collection of surface sediments allowed for additional assessment of benthic-pelagic coupling. The novel combination of this wide-ranging set of analyses to a locally and globally important water body like Lake Superior allowed us to fully assess the interactions between lower trophic level biology and carbon and nutrient cycling throughout the water column. Preliminary data indicates that microbial community composition was variable across the western arm of Lake Superior and showed signs of stratification at individual stations (>100 m deep). Sample collection occurred soon after lake stratification in July 2015, and the presence of a deep chlorophyll maximum was noted. The results shed light on the functioning of the biological pump and nutrient and carbon dynamics in a changing ecosystem and provides insight on how further change in Lake Superior and other aquatic systems will affect ecosystem function and services.

Untargeted Metabolomics Strategies—Challenges and Emerging Directions

NASA Astrophysics Data System (ADS)

Schrimpe-Rutledge, Alexandra C.; Codreanu, Simona G.; Sherrod, Stacy D.; McLean, John A.

2016-12-01

Metabolites are building blocks of cellular function. These species are involved in enzyme-catalyzed chemical reactions and are essential for cellular function. Upstream biological disruptions result in a series of metabolomic changes and, as such, the metabolome holds a wealth of information that is thought to be most predictive of phenotype. Uncovering this knowledge is a work in progress. The field of metabolomics is still maturing; the community has leveraged proteomics experience when applicable and developed a range of sample preparation and instrument methodology along with myriad data processing and analysis approaches. Research focuses have now shifted toward a fundamental understanding of the biology responsible for metabolomic changes. There are several types of metabolomics experiments including both targeted and untargeted analyses. While untargeted, hypothesis generating workflows exhibit many valuable attributes, challenges inherent to the approach remain. This Critical Insight comments on these challenges, focusing on the identification process of LC-MS-based untargeted metabolomics studies—specifically in mammalian systems. Biological interpretation of metabolomics data hinges on the ability to accurately identify metabolites. The range of confidence associated with identifications that is often overlooked is reviewed, and opportunities for advancing the metabolomics field are described.

Correlated evolution of thermal niches and functional physiology in tropical freshwater fishes.

PubMed

Culumber, Zachary W; Tobler, Michael

2018-05-01

The role of ecology in phenotypic and species diversification is widely documented. Nonetheless, numerous nonadaptive processes can shape realized niches and phenotypic variation in natural populations, complicating inferences about adaptive evolution at macroevolutionary scales. We tested for evolved differences in thermal tolerances and their association with the realized thermal niche (including metrics describing diurnal and seasonal patterns of temperature extremes and variability) across a genus of tropical freshwater fishes reared in a standardized environment. There was limited evolution along the thermal niche axis associated with variation in maximum temperature and in upper thermal limits. In contrast, there was considerable diversification along the first major axis of the thermal niche associated with minimum temperatures and in lower thermal limits. Across our adaptive landscape analyses, 70% of species exhibited evidence of divergence in thermal niches. Most importantly, the first two major axes of thermal niche variation were significantly correlated with variation in lower thermal limits. Our results indicate adaptation to divergent thermal niches and adaptive evolution of related functional traits, and highlight the importance of divergence in lower thermal limits for the evolution of tropical biodiversity. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Sex differences in psychological adjustment from infancy to 8 years.

PubMed

Prior, M; Smart, D; Sanson, A; Oberklaid, F

1993-03-01

The objective of this study was to explore sex differences in development from infancy to 8 years of age in a community sample. Measures of biological, social, interactive, and parental functioning as well as teacher reports were obtained. There were minimal differences in infancy, but major psychosocial differences emerged with increasing age. In the biological sphere boys were disadvantaged only in ratings of language and motor skills at 3 to 4 years old. They showed greater temperamental "difficulty" and low persistence factor scores from 5 years onward. Boys were significantly more likely to have problems with adaptive behavior and social competence and to show behavior problems of the hyperactive and aggressive type, as rated by mothers. Parent and family functioning measures did not differentiate between the sexes. Teachers rated boys as having more problems in academic and behavioral domains the first 3 years of school. Path analyses combining data sets gathered when the children were 3 to 8 years old demonstrated the differential courses of development for boys and girls although temperamental flexibility was the best predictor of behavioral adjustment for both sexes. A social learning explanation of the increased incidence of problems among males is supported, although biological influences are not ruled out.

Identifying taxonomic and functional surrogates for spring biodiversity conservation.

PubMed

Jyväsjärvi, Jussi; Virtanen, Risto; Ilmonen, Jari; Paasivirta, Lauri; Muotka, Timo

2018-02-27

Surrogate approaches are widely used to estimate overall taxonomic diversity for conservation planning. Surrogate taxa are frequently selected based on rarity or charisma, whereas selection through statistical modeling has been applied rarely. We used boosted-regression-tree models (BRT) fitted to biological data from 165 springs to identify bryophyte and invertebrate surrogates for taxonomic and functional diversity of boreal springs. We focused on these 2 groups because they are well known and abundant in most boreal springs. The best indicators of taxonomic versus functional diversity differed. The bryophyte Bryum weigelii and the chironomid larva Paratrichocladius skirwithensis best indicated taxonomic diversity, whereas the isopod Asellus aquaticus and the chironomid Macropelopia spp. were the best surrogates of functional diversity. In a scoring algorithm for priority-site selection, taxonomic surrogates performed only slightly better than random selection for all spring-dwelling taxa, but they were very effective in representing spring specialists, providing a distinct improvement over random solutions. However, the surrogates for taxonomic diversity represented functional diversity poorly and vice versa. When combined with cross-taxon complementarity analyses, surrogate selection based on statistical modeling provides a promising approach for identifying groundwater-dependent ecosystems of special conservation value, a key requirement of the EU Water Framework Directive. © 2018 Society for Conservation Biology.

Physiological enzymology: The next frontier in understanding protein structure and function at the cellular level.

PubMed

Lee, Irene; Berdis, Anthony J

2016-01-01

Historically, the study of proteins has relied heavily on characterizing the activity of a single purified protein isolated from other cellular components. This classic approach allowed scientists to unambiguously define the intrinsic kinetic and chemical properties of that protein. The ultimate hope was to extrapolate this information toward understanding how the enzyme or receptor behaves within its native cellular context. These types of detailed in vitro analyses were necessary to reduce the innate complexities of measuring the singular activity and biochemical properties of a specific enzyme without interference from other enzymes and potential competing substrates. However, recent developments in fields encompassing cell biology, molecular imaging, and chemical biology now provide the unique chemical tools and instrumentation to study protein structure, function, and regulation in their native cellular environment. These advancements provide the foundation for a new field, coined physiological enzymology, which quantifies the function and regulation of enzymes and proteins at the cellular level. In this Special Edition, we explore the area of Physiological Enzymology and Protein Function through a series of review articles that focus on the tools and techniques used to measure the cellular activity of proteins inside living cells. This article is part of a Special Issue entitled: Physiological Enzymology and Protein Functions. Copyright © 2015 Elsevier B.V. All rights reserved.

Evolution and function of CAG/polyglutamine repeats in protein–protein interaction networks

PubMed Central

Schaefer, Martin H.; Wanker, Erich E.; Andrade-Navarro, Miguel A.

2012-01-01

Expanded runs of consecutive trinucleotide CAG repeats encoding polyglutamine (polyQ) stretches are observed in the genes of a large number of patients with different genetic diseases such as Huntington's and several Ataxias. Protein aggregation, which is a key feature of most of these diseases, is thought to be triggered by these expanded polyQ sequences in disease-related proteins. However, polyQ tracts are a normal feature of many human proteins, suggesting that they have an important cellular function. To clarify the potential function of polyQ repeats in biological systems, we systematically analyzed available information stored in sequence and protein interaction databases. By integrating genomic, phylogenetic, protein interaction network and functional information, we obtained evidence that polyQ tracts in proteins stabilize protein interactions. This happens most likely through structural changes whereby the polyQ sequence extends a neighboring coiled-coil region to facilitate its interaction with a coiled-coil region in another protein. Alteration of this important biological function due to polyQ expansion results in gain of abnormal interactions, leading to pathological effects like protein aggregation. Our analyses suggest that research on polyQ proteins should shift focus from expanded polyQ proteins into the characterization of the influence of the wild-type polyQ on protein interactions. PMID:22287626

The Landscape of Circular RNA Expression Profiles in Papillary Thyroid Carcinoma Based on RNA Sequencing.

PubMed

Lan, Xiabin; Xu, Jiajie; Chen, Chao; Zheng, Chuanming; Wang, Jiafeng; Cao, Jun; Zhu, Xuhang; Ge, Minghua

2018-05-25

Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. However, the molecular mechanisms responsible for its tumorigenesis and progression remain largely unknown. Circular RNA (circRNA) is a novel type of noncoding RNA that can serve as an ideal biomarker due to its stability. Recent evidence suggests that circRNAs play important roles in tumorigenesis. This study aims to investigate circRNA expression profiles and their potential biological functions in PTC. High-throughput RNA sequencing was used to assess circRNA expression profiles in PTC, and quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate dysregulated circRNAs. Receiver operating characteristic (ROC) curves were generated to evaluate the diagnostic value of circRNAs for PTC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were employed to determine the biological functions of differentially expressed circRNAs. Bioinformatic analyses were applied to predict interactions between circRNAs and microRNAs (miRNAs), and a circRNA-miRNA-mRNA network was constructed using Cytoscape software. We identified a number of differentially expressed circRNAs in PTC tissues compared with paired normal thyroid tissues, with chr5: 160757890-160763776-, chr12: 40696591-40697936+, chr7: 22330794-22357656-, and chr21: 16386665-16415895- being upregulated, and chr7: 91924203-91957214+, chr2: 179514891-179516047-, chr9: 16435553-16437522-, and chr22: 36006931-36007153- being downregulated. These findings were confirmed by qRT-PCR, and ROC curves indicated that they can serve as potential biomarkers for PTC. GO and KEGG pathway analyses showed that some of these circRNAs are related to cancers. Additionally, bioinformatic analyses revealed a potential competing-endogenous-RNA-regulating network among circRNAs, miRNAs, and mRNAs. Our study results depict the landscape of circRNA expression profiles in PTC and also provide potential biomarkers for PTC. Further functional and mechanistic studies of these circRNAs may improve our understanding of PTC tumorigenesis. © 2018 The Author(s). Published by S. Karger AG, Basel.

Topology of molecular interaction networks.

PubMed

Winterbach, Wynand; Van Mieghem, Piet; Reinders, Marcel; Wang, Huijuan; de Ridder, Dick

2013-09-16

Molecular interactions are often represented as network models which have become the common language of many areas of biology. Graphs serve as convenient mathematical representations of network models and have themselves become objects of study. Their topology has been intensively researched over the last decade after evidence was found that they share underlying design principles with many other types of networks.Initial studies suggested that molecular interaction network topology is related to biological function and evolution. However, further whole-network analyses did not lead to a unified view on what this relation may look like, with conclusions highly dependent on the type of molecular interactions considered and the metrics used to study them. It is unclear whether global network topology drives function, as suggested by some researchers, or whether it is simply a byproduct of evolution or even an artefact of representing complex molecular interaction networks as graphs.Nevertheless, network biology has progressed significantly over the last years. We review the literature, focusing on two major developments. First, realizing that molecular interaction networks can be naturally decomposed into subsystems (such as modules and pathways), topology is increasingly studied locally rather than globally. Second, there is a move from a descriptive approach to a predictive one: rather than correlating biological network topology to generic properties such as robustness, it is used to predict specific functions or phenotypes.Taken together, this change in focus from globally descriptive to locally predictive points to new avenues of research. In particular, multi-scale approaches are developments promising to drive the study of molecular interaction networks further.

Topology of molecular interaction networks

PubMed Central

2013-01-01

Molecular interactions are often represented as network models which have become the common language of many areas of biology. Graphs serve as convenient mathematical representations of network models and have themselves become objects of study. Their topology has been intensively researched over the last decade after evidence was found that they share underlying design principles with many other types of networks. Initial studies suggested that molecular interaction network topology is related to biological function and evolution. However, further whole-network analyses did not lead to a unified view on what this relation may look like, with conclusions highly dependent on the type of molecular interactions considered and the metrics used to study them. It is unclear whether global network topology drives function, as suggested by some researchers, or whether it is simply a byproduct of evolution or even an artefact of representing complex molecular interaction networks as graphs. Nevertheless, network biology has progressed significantly over the last years. We review the literature, focusing on two major developments. First, realizing that molecular interaction networks can be naturally decomposed into subsystems (such as modules and pathways), topology is increasingly studied locally rather than globally. Second, there is a move from a descriptive approach to a predictive one: rather than correlating biological network topology to generic properties such as robustness, it is used to predict specific functions or phenotypes. Taken together, this change in focus from globally descriptive to locally predictive points to new avenues of research. In particular, multi-scale approaches are developments promising to drive the study of molecular interaction networks further. PMID:24041013

CADDIS Volume 4. Data Analysis: Advanced Analyses - Controlling for Natural Variability: SSD Plot Diagrams

EPA Pesticide Factsheets

Methods for controlling natural variability, predicting environmental conditions from biological observations method, biological trait data, species sensitivity distributions, propensity scores, Advanced Analyses of Data Analysis references.

Integrative and conjugative elements and their hosts: composition, distribution and organization.

PubMed

Cury, Jean; Touchon, Marie; Rocha, Eduardo P C

2017-09-06

Conjugation of single-stranded DNA drives horizontal gene transfer between bacteria and was widely studied in conjugative plasmids. The organization and function of integrative and conjugative elements (ICE), even if they are more abundant, was only studied in a few model systems. Comparative genomics of ICE has been precluded by the difficulty in finding and delimiting these elements. Here, we present the results of a method that circumvents these problems by requiring only the identification of the conjugation genes and the species' pan-genome. We delimited 200 ICEs and this allowed the first large-scale characterization of these elements. We quantified the presence in ICEs of a wide set of functions associated with the biology of mobile genetic elements, including some that are typically associated with plasmids, such as partition and replication. Protein sequence similarity networks and phylogenetic analyses revealed that ICEs are structured in functional modules. Integrases and conjugation systems have different evolutionary histories, even if the gene repertoires of ICEs can be grouped in function of conjugation types. Our characterization of the composition and organization of ICEs paves the way for future functional and evolutionary analyses of their cargo genes, composed of a majority of unknown function genes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Brain processing of biologically relevant odors in the awake rat, as revealed by manganese-enhanced MRI.

PubMed

Lehallier, Benoist; Rampin, Olivier; Saint-Albin, Audrey; Jérôme, Nathalie; Ouali, Christian; Maurin, Yves; Bonny, Jean-Marie

2012-01-01

So far, an overall view of olfactory structures activated by natural biologically relevant odors in the awake rat is not available. Manganese-enhanced MRI (MEMRI) is appropriate for this purpose. While MEMRI has been used for anatomical labeling of olfactory pathways, functional imaging analyses have not yet been performed beyond the olfactory bulb. Here, we have used MEMRI for functional imaging of rat central olfactory structures and for comparing activation maps obtained with odors conveying different biological messages. Odors of male fox feces and of chocolate flavored cereals were used to stimulate conscious rats previously treated by intranasal instillation of manganese (Mn). MEMRI activation maps showed Mn enhancement all along the primary olfactory cortex. Mn enhancement elicited by male fox feces odor and to a lesser extent that elicited by chocolate odor, differed from that elicited by deodorized air. This result was partly confirmed by c-Fos immunohistochemistry in the piriform cortex. By providing an overall image of brain structures activated in awake rats by odorous stimulation, and by showing that Mn enhancement is differently sensitive to different stimulating odors, the present results demonstrate the interest of MEMRI for functional studies of olfaction in the primary olfactory cortex of laboratory small animals, under conditions close to natural perception. Finally, the factors that may cause the variability of the MEMRI signal in response to different odor are discussed.

Achieving biopolymer synergy in systems chemistry.

PubMed

Bai, Yushi; Chotera, Agata; Taran, Olga; Liang, Chen; Ashkenasy, Gonen; Lynn, David G

2018-05-31

Synthetic and materials chemistry initiatives have enabled the translation of the macromolecular functions of biology into synthetic frameworks. These explorations into alternative chemistries of life attempt to capture the versatile functionality and adaptability of biopolymers in new orthogonal scaffolds. Information storage and transfer, however, so beautifully represented in the central dogma of biology, require multiple components functioning synergistically. Over a single decade, the emerging field of systems chemistry has begun to catalyze the construction of mutualistic biopolymer networks, and this review begins with the foundational small-molecule-based dynamic chemical networks and peptide amyloid-based dynamic physical networks on which this effort builds. The approach both contextualizes the versatile approaches that have been developed to enrich chemical information in synthetic networks and highlights the properties of amyloids as potential alternative genetic elements. The successful integration of both chemical and physical networks through β-sheet assisted replication processes further informs the synergistic potential of these networks. Inspired by the cooperative synergies of nucleic acids and proteins in biology, synthetic nucleic-acid-peptide chimeras are now being explored to extend their informational content. With our growing range of synthetic capabilities, structural analyses, and simulation technologies, this foundation is radically extending the structural space that might cross the Darwinian threshold for the origins of life as well as creating an array of alternative systems capable of achieving the progressive growth of novel informational materials.

Monitoring the Spatiotemporal Activities of miRNAs in Small Animal Models Using Molecular Imaging Modalities

PubMed Central

Baril, Patrick; Ezzine, Safia; Pichon, Chantal

2015-01-01

MicroRNAs (miRNAs) are a class of small non-coding RNAs that regulate gene expression by binding mRNA targets via sequence complementary inducing translational repression and/or mRNA degradation. A current challenge in the field of miRNA biology is to understand the functionality of miRNAs under physiopathological conditions. Recent evidence indicates that miRNA expression is more complex than simple regulation at the transcriptional level. MiRNAs undergo complex post-transcriptional regulations such miRNA processing, editing, accumulation and re-cycling within P-bodies. They are dynamically regulated and have a well-orchestrated spatiotemporal localization pattern. Real-time and spatio-temporal analyses of miRNA expression are difficult to evaluate and often underestimated. Therefore, important information connecting miRNA expression and function can be lost. Conventional miRNA profiling methods such as Northern blot, real-time PCR, microarray, in situ hybridization and deep sequencing continue to contribute to our knowledge of miRNA biology. However, these methods can seldom shed light on the spatiotemporal organization and function of miRNAs in real-time. Non-invasive molecular imaging methods have the potential to address these issues and are thus attracting increasing attention. This paper reviews the state-of-the-art of methods used to detect miRNAs and discusses their contribution in the emerging field of miRNA biology and therapy. PMID:25749473

Monitoring the spatiotemporal activities of miRNAs in small animal models using molecular imaging modalities.

PubMed

Baril, Patrick; Ezzine, Safia; Pichon, Chantal

2015-03-04

MicroRNAs (miRNAs) are a class of small non-coding RNAs that regulate gene expression by binding mRNA targets via sequence complementary inducing translational repression and/or mRNA degradation. A current challenge in the field of miRNA biology is to understand the functionality of miRNAs under physiopathological conditions. Recent evidence indicates that miRNA expression is more complex than simple regulation at the transcriptional level. MiRNAs undergo complex post-transcriptional regulations such miRNA processing, editing, accumulation and re-cycling within P-bodies. They are dynamically regulated and have a well-orchestrated spatiotemporal localization pattern. Real-time and spatio-temporal analyses of miRNA expression are difficult to evaluate and often underestimated. Therefore, important information connecting miRNA expression and function can be lost. Conventional miRNA profiling methods such as Northern blot, real-time PCR, microarray, in situ hybridization and deep sequencing continue to contribute to our knowledge of miRNA biology. However, these methods can seldom shed light on the spatiotemporal organization and function of miRNAs in real-time. Non-invasive molecular imaging methods have the potential to address these issues and are thus attracting increasing attention. This paper reviews the state-of-the-art of methods used to detect miRNAs and discusses their contribution in the emerging field of miRNA biology and therapy.

Experimental strategies for the identification and characterization of adhesive proteins in animals: a review

PubMed Central

Hennebert, Elise; Maldonado, Barbara; Ladurner, Peter; Flammang, Patrick; Santos, Romana

2015-01-01

Adhesive secretions occur in both aquatic and terrestrial animals, in which they perform diverse functions. Biological adhesives can therefore be remarkably complex and involve a large range of components with different functions and interactions. However, being mainly protein based, biological adhesives can be characterized by classical molecular methods. This review compiles experimental strategies that were successfully used to identify, characterize and obtain the full-length sequence of adhesive proteins from nine biological models: echinoderms, barnacles, tubeworms, mussels, sticklebacks, slugs, velvet worms, spiders and ticks. A brief description and practical examples are given for a variety of tools used to study adhesive molecules at different levels from genes to secreted proteins. In most studies, proteins, extracted from secreted materials or from adhesive organs, are analysed for the presence of post-translational modifications and submitted to peptide sequencing. The peptide sequences are then used directly for a BLAST search in genomic or transcriptomic databases, or to design degenerate primers to perform RT-PCR, both allowing the recovery of the sequence of the cDNA coding for the investigated protein. These sequences can then be used for functional validation and recombinant production. In recent years, the dual proteomic and transcriptomic approach has emerged as the best way leading to the identification of novel adhesive proteins and retrieval of their complete sequences. PMID:25657842

[The biological reaction of inflammation, methylglyoxal of blood plasma, functional and structural alterations in elastic type arteries at the early stage of hypertension disease].

PubMed

Titov, V N; Dmitriev, V A; Oshchepkov, E V; Balakhonova, T V; Tripoten', M I; Shiriaeva, Iu K

2012-08-01

The article deals with studying of the relationship between biologic reaction of inflammation with glycosylation reaction and content of methylglyoxal in blood serum. The positive correlation between pulse wave velocity and content of methylglyoxal, C-reactive protein in intercellular medium and malleolar brachial index value was established. This data matches the experimental results concerning involvement of biological reaction of inflammation into structural changes of elastic type arteries under hypertension disease, formation of arteries' rigidity and increase of pulse wave velocity. The arterial blood pressure is a biological reaction of hydrodynamic pressure which is used in vivo by several biological functions: biological function of homeostasis, function of endoecology, biological function of adaptation and function of locomotion. The biological reaction of hydrodynamic (hydraulic) pressure is a mode of compensation of derangement of several biological functions which results in the very high rate of hypertension disease in population. As a matter of fact, hypertension disease is a syndrome of lingering pathological compensation by higher arterial blood pressure of the biological functions derangements occurring in the distal section at the level of paracrine cenoses of cells. The arterial blood pressure is a kind of in vivo integral indicator of deranged metabolism. The essential hypertension disease pathogenically is a result of the derangement of three biological functions: biological function of homeostasis, biological function of trophology - nutrition (biological reaction of external feeding - exotrophia) and biological function of endoecology. In case of "littering" of intercellular medium in vivo with nonspecific endogenic flogogens a phylogenetically earlier activation of biological reactions of excretion, inflammation and hydrodynamic arterial blood pressure occur. In case of derangement of biological function of homeostasis, decreasing of perfusion even in single paracrine cenoses and derangement of biological function of endoecology ("purity" of intercellular medium) the only response always will be the increase of arterial blood pressure.

Proteomic analysis of Bombyx mori molting fluid: Insights into the molting process.

PubMed

Liu, Hua-Wei; Wang, Luo-Ling; Tang, Xin; Dong, Zhao-Ming; Guo, Peng-Chao; Zhao, Dong-Chao; Xia, Qing-You; Zhao, Ping

2018-02-20

Molting is an essential biological process occurring multiple times throughout the life cycle of most Ecdysozoa. Molting fluids accumulate and function in the exuvial space during the molting process. In this study, we used liquid chromatography-tandem mass spectrometry to investigate the molting fluids to analyze the molecular mechanisms of molting in the silkworm, Bombyx mori. In total, 375 proteins were identified in molting fluids from the silkworm at 14-16h before pupation and eclosion, including 12 chitin metabolism-related enzymes, 35 serine proteases, 15 peptidases, and 38 protease inhibitors. Gene ontology analysis indicated that "catalytic" constitutes the most enriched function in the molting fluid. Gene expression patterns and bioinformatic analyses suggested that numerous enzymes are involved in the degradation of cuticle proteins and chitin. Protein-protein interaction network and activity analyses showed that protease inhibitors are involved in the regulation of multiple pathways in molting fluid. Additionally, many immune-related proteins may be involved in the immune defense during molting. These results provide a comprehensive proteomic insight into proteolytic enzymes and protease inhibitors in molting fluid, and will likely improve the current understanding of physiological processes in insect molting. Insect molting constitutes a dynamic physiological process. To better understand this process, we used LC-MS/MS to investigate the proteome of silkworm molting fluids and identified key proteins involved in silkworm molting. The biological processes of the old cuticle degradation pathway and immune defense response were analyzed in the proteome of silkworm molting fluid. We report that protease inhibitors serve as key factors in the regulation of the molting process. The proteomic results provide new insight into biological molting processes in insects. Copyright © 2017 Elsevier B.V. All rights reserved.

RNA-Seq Analysis to Measure the Expression of SINE Retroelements.

PubMed

Román, Ángel Carlos; Morales-Hernández, Antonio; Fernández-Salguero, Pedro M

2016-01-01

The intrinsic features of retroelements, like their repetitive nature and disseminated presence in their host genomes, demand the use of advanced methodologies for their bioinformatic and functional study. The short length of SINE (short interspersed elements) retrotransposons makes such analyses even more complex. Next-generation sequencing (NGS) technologies are currently one of the most widely used tools to characterize the whole repertoire of gene expression in a specific tissue. In this chapter, we will review the molecular and computational methods needed to perform NGS analyses on SINE elements. We will also describe new methods of potential interest for researchers studying repetitive elements. We intend to outline the general ideas behind the computational analyses of NGS data obtained from SINE elements, and to stimulate other scientists to expand our current knowledge on SINE biology using RNA-seq and other NGS tools.

Contact nanomechanical measurements with the AFM

NASA Astrophysics Data System (ADS)

Geisse, Nicholas

2013-03-01

The atomic force microscope (AFM) has found broad use in the biological sciences largely due to its ability to make measurements on unfixed and unstained samples under liquid. In addition to imaging at multiple spatial scales ranging from micro- to nanometer, AFMs are commonly used as nanomechanical probes. This is pertinent for cell biology, as it has been demonstrated that the geometrical and mechanical properties of the extracellular microenvironment are important in such processes as cancer, cardiovascular disease, muscular dystrophy, and even the control of cell life and death. Indeed, the ability to control and quantify these external geometrical and mechanical parameters arises as a key issue in the field. Because AFM can quantitatively measure the mechanical properties of various biological samples, novel insights to cell function and to cell-substrate interactions are now possible. As the application of AFM to these types of problems is widened, it is important to understand the performance envelope of the technique and its associated data analyses. This talk will discuss the important issues that must be considered when mechanical models are applied to real-world data. Examples of the effect of different model assumptions on our understanding of the measured material properties will be shown. Furthermore, specific examples of the importance of mechanical stimuli and the micromechanical environment to the structure and function of biological materials will be presented.

Micro-CTvlab: A web based virtual gallery of biological specimens using X-ray microtomography (micro-CT)

PubMed Central

Faulwetter, Sarah; Chatzinikolaou, Eva; Michalakis, Nikitas; Filiopoulou, Irene; Minadakis, Nikos; Panteri, Emmanouela; Perantinos, George; Gougousis, Alexandros; Arvanitidis, Christos

2016-01-01

Abstract Background During recent years, X-ray microtomography (micro-CT) has seen an increasing use in biological research areas, such as functional morphology, taxonomy, evolutionary biology and developmental research. Micro-CT is a technology which uses X-rays to create sub-micron resolution images of external and internal features of specimens. These images can then be rendered in a three-dimensional space and used for qualitative and quantitative 3D analyses. However, the online exploration and dissemination of micro-CT datasets are rarely made available to the public due to their large size and a lack of dedicated online platforms for the interactive manipulation of 3D data. Here, the development of a virtual micro-CT laboratory (Micro-CTvlab) is described, which can be used by everyone who is interested in digitisation methods and biological collections and aims at making the micro-CT data exploration of natural history specimens freely available over the internet. New information The Micro-CTvlab offers to the user virtual image galleries of various taxa which can be displayed and downloaded through a web application. With a few clicks, accurate, detailed and three-dimensional models of species can be studied and virtually dissected without destroying the actual specimen. The data and functions of the Micro-CTvlab can be accessed either on a normal computer or through a dedicated version for mobile devices. PMID:27956848

Micro-CTvlab: A web based virtual gallery of biological specimens using X-ray microtomography (micro-CT).

PubMed

Keklikoglou, Kleoniki; Faulwetter, Sarah; Chatzinikolaou, Eva; Michalakis, Nikitas; Filiopoulou, Irene; Minadakis, Nikos; Panteri, Emmanouela; Perantinos, George; Gougousis, Alexandros; Arvanitidis, Christos

2016-01-01

During recent years, X-ray microtomography (micro-CT) has seen an increasing use in biological research areas, such as functional morphology, taxonomy, evolutionary biology and developmental research. Micro-CT is a technology which uses X-rays to create sub-micron resolution images of external and internal features of specimens. These images can then be rendered in a three-dimensional space and used for qualitative and quantitative 3D analyses. However, the online exploration and dissemination of micro-CT datasets are rarely made available to the public due to their large size and a lack of dedicated online platforms for the interactive manipulation of 3D data. Here, the development of a virtual micro-CT laboratory (Micro-CT vlab ) is described, which can be used by everyone who is interested in digitisation methods and biological collections and aims at making the micro-CT data exploration of natural history specimens freely available over the internet. The Micro-CT vlab offers to the user virtual image galleries of various taxa which can be displayed and downloaded through a web application. With a few clicks, accurate, detailed and three-dimensional models of species can be studied and virtually dissected without destroying the actual specimen. The data and functions of the Micro-CT vlab can be accessed either on a normal computer or through a dedicated version for mobile devices.

Pancreatic cancer cell lines as patient-derived avatars: genetic characterisation and functional utility.

PubMed

Knudsen, Erik S; Balaji, Uthra; Mannakee, Brian; Vail, Paris; Eslinger, Cody; Moxom, Christopher; Mansour, John; Witkiewicz, Agnieszka K

2018-03-01

Pancreatic ductal adenocarcinoma (PDAC) is a therapy recalcitrant disease with the worst survival rate of common solid tumours. Preclinical models that accurately reflect the genetic and biological diversity of PDAC will be important for delineating features of tumour biology and therapeutic vulnerabilities. 27 primary PDAC tumours were employed for genetic analysis and development of tumour models. Tumour tissue was used for derivation of xenografts and cell lines. Exome sequencing was performed on the originating tumour and developed models. RNA sequencing, histological and functional analyses were employed to determine the relationship of the patient-derived models to clinical presentation of PDAC. The cohort employed captured the genetic diversity of PDAC. From most cases, both cell lines and xenograft models were developed. Exome sequencing confirmed preservation of the primary tumour mutations in developed cell lines, which remained stable with extended passaging. The level of genetic conservation in the cell lines was comparable to that observed with patient-derived xenograft (PDX) models. Unlike historically established PDAC cancer cell lines, patient-derived models recapitulated the histological architecture of the primary tumour and exhibited metastatic spread similar to that observed clinically. Detailed genetic analyses of tumours and derived models revealed features of ex vivo evolution and the clonal architecture of PDAC. Functional analysis was used to elucidate therapeutic vulnerabilities of relevance to treatment of PDAC. These data illustrate that with the appropriate methods it is possible to develop cell lines that maintain genetic features of PDAC. Such models serve as important substrates for analysing the significance of genetic variants and create a unique biorepository of annotated cell lines and xenografts that were established simultaneously from same primary tumour. These models can be used to infer genetic and empirically determined therapeutic sensitivities that would be germane to the patient. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Effects of storage temperature on airway exosome integrity for diagnostic and functional analyses

PubMed Central

Maroto, Rosario; Zhao, Yingxin; Jamaluddin, Mohammad; Popov, Vsevolod L.; Wang, Hongwang; Kalubowilage, Madumali; Zhang, Yueqing; Luisi, Jonathan; Sun, Hong; Culbertson, Christopher T.; Bossmann, Stefan H.; Motamedi, Massoud; Brasier, Allan R.

2017-01-01

ABSTRACT Background: Extracellular vesicles contain biological molecules specified by cell-type of origin and modified by microenvironmental changes. To conduct reproducible studies on exosome content and function, storage conditions need to have minimal impact on airway exosome integrity. Aim: We compared surface properties and protein content of airway exosomes that had been freshly isolated vs. those that had been treated with cold storage or freezing. Methods: Mouse bronchoalveolar lavage fluid (BALF) exosomes purified by differential ultracentrifugation were analysed immediately or stored at +4°C or −80°C. Exosomal structure was assessed by dynamic light scattering (DLS), transmission electron microscopy (TEM) and charge density (zeta potential, ζ). Exosomal protein content, including leaking/dissociating proteins, were identified by label-free LC-MS/MS. Results: Freshly isolated BALF exosomes exhibited a mean diameter of 95 nm and characteristic morphology. Storage had significant impact on BALF exosome size and content. Compared to fresh, exosomes stored at +4°C had a 10% increase in diameter, redistribution to polydisperse aggregates and reduced ζ. Storage at −80°C produced an even greater effect, resulting in a 25% increase in diameter, significantly reducing the ζ, resulting in multilamellar structure formation. In fresh exosomes, we identified 1140 high-confidence proteins enriched in 19 genome ontology biological processes. After storage at room temperature, 848 proteins were identified. In preparations stored at +4°C, 224 proteins appeared in the supernatant fraction compared to the wash fractions from freshly prepared exosomes; these proteins represent exosome leakage or dissociation of loosely bound “peri-exosomal” proteins. In preparations stored at −80°C, 194 proteins appeared in the supernatant fraction, suggesting that distinct protein groups leak from exosomes at different storage temperatures. Conclusions: Storage destabilizes the surface characteristics, morphological features and protein content of BALF exosomes. For preservation of the exosome protein content and representative functional analysis, airway exosomes should be analysed immediately after isolation. PMID:28819550

Effects of storage temperature on airway exosome integrity for diagnostic and functional analyses.

PubMed

Maroto, Rosario; Zhao, Yingxin; Jamaluddin, Mohammad; Popov, Vsevolod L; Wang, Hongwang; Kalubowilage, Madumali; Zhang, Yueqing; Luisi, Jonathan; Sun, Hong; Culbertson, Christopher T; Bossmann, Stefan H; Motamedi, Massoud; Brasier, Allan R

2017-01-01

Background : Extracellular vesicles contain biological molecules specified by cell-type of origin and modified by microenvironmental changes. To conduct reproducible studies on exosome content and function, storage conditions need to have minimal impact on airway exosome integrity. Aim : We compared surface properties and protein content of airway exosomes that had been freshly isolated vs. those that had been treated with cold storage or freezing. Methods : Mouse bronchoalveolar lavage fluid (BALF) exosomes purified by differential ultracentrifugation were analysed immediately or stored at +4°C or -80°C. Exosomal structure was assessed by dynamic light scattering (DLS), transmission electron microscopy (TEM) and charge density (zeta potential, ζ). Exosomal protein content, including leaking/dissociating proteins, were identified by label-free LC-MS/MS. Results : Freshly isolated BALF exosomes exhibited a mean diameter of 95 nm and characteristic morphology. Storage had significant impact on BALF exosome size and content. Compared to fresh, exosomes stored at +4°C had a 10% increase in diameter, redistribution to polydisperse aggregates and reduced ζ. Storage at -80°C produced an even greater effect, resulting in a 25% increase in diameter, significantly reducing the ζ, resulting in multilamellar structure formation. In fresh exosomes, we identified 1140 high-confidence proteins enriched in 19 genome ontology biological processes. After storage at room temperature, 848 proteins were identified. In preparations stored at +4°C, 224 proteins appeared in the supernatant fraction compared to the wash fractions from freshly prepared exosomes; these proteins represent exosome leakage or dissociation of loosely bound "peri-exosomal" proteins. In preparations stored at -80°C, 194 proteins appeared in the supernatant fraction, suggesting that distinct protein groups leak from exosomes at different storage temperatures. Conclusions : Storage destabilizes the surface characteristics, morphological features and protein content of BALF exosomes. For preservation of the exosome protein content and representative functional analysis, airway exosomes should be analysed immediately after isolation.

Biological significance of long non-coding RNA FTX expression in human colorectal cancer

PubMed Central

Guo, Xiao-Bo; Hua, Zhu; Li, Chen; Peng, Li-Pan; Wang, Jing-Shen; Wang, Bo; Zhi, Qiao-Ming

2015-01-01

The purpose of this study was to determine the expression of long non-coding RNA (lncRNA) FTX and analyze its prognostic and biological significance in colorectal cancer (CRC). A quantitative reverse transcription PCR was performed to detect the expression of long non-coding RNA FTX in 35 pairs of colorectal cancer and corresponding noncancerous tissues. The expression of long non-coding RNA FTX was detected in 187 colorectal cancer tissues and its correlations with clinicopathological factors of patients were examined. Univariate and multivariate analyses were performed to analyze the prognostic significance of Long Non-coding RNA FTX expression. The effects of long non-coding RNA FTX expression on malignant phenotypes of colorectal cancer cells and its possible biological significances were further determined. Long non-coding RNA FTX was significantly upregulated in colorectal cancer tissues, and low long non-coding RNA FTX expression was significantly correlated with differentiation grade, lymph vascular invasion, and clinical stage. Patients with high long non-coding RNA FTX showed poorer overall survival than those with low long non-coding RNA FTX. Multivariate analyses indicated that status of long non-coding RNA FTX was an independent prognostic factor for patients. Functional analyses showed that upregulation of long non-coding RNA FTX significantly promoted growth, migration, invasion, and increased colony formation in colorectal cancer cells. Therefore, long non-coding RNA FTX may be a potential biomarker for predicting the survival of colorectal cancer patients and might be a molecular target for treatment of human colorectal cancer. PMID:26629053

Maize Bioactive Peptides against Cancer

NASA Astrophysics Data System (ADS)

Díaz-Gómez, Jorge L.; Castorena-Torres, Fabiola; Preciado-Ortiz, Ricardo E.; García-Lara, Silverio

2017-06-01

Cancer is one of the main chronic degenerative diseases worldwide. In recent years, consumption of whole-grain cereals and their derived food products has been associated with reduction risks of various types of cancer. Cereals main biomolecules includes proteins, peptides, and amino acids present in different quantities within the grain. The nutraceutical properties associated with peptides exerts biological functions that promote health and prevent this disease. In this review, we report the current status and advances on maize peptides regarding bioactive properties that have been reported such as antioxidant, antihypertensive, hepatoprotective, and anti-tumour activities. We also highlighted its biological potential through which maize bioactive peptides exert anti-cancer activity. Finally, we analyse and emphasize the possible areas of application for maize peptides.

Effects of biological sex on the pathophysiology of the heart.

PubMed

Fazal, Loubina; Azibani, Feriel; Vodovar, Nicolas; Cohen Solal, Alain; Delcayre, Claude; Samuel, Jane-Lise

2014-02-01

Cardiovascular diseases are the leading causes of death in men and women in industrialized countries. While the effects of biological sex on cardiovascular pathophysiology have long been known, the sex-specific mechanisms mediating these processes have been further elucidated over recent years. This review aims at analysing the sex-based differences in cardiac structure and function in adult mammals, and the sex-based differences in the main molecular mechanisms involved in the response of the heart to pathological situations. It emerged from this review that the sex-based difference is a variable that should be dealt with, not only in basic science or clinical research, but also with regards to therapeutic approaches. © 2013 The British Pharmacological Society.

SWI/SNF Chromatin-remodeling Factors: Multiscale Analyses and Diverse Functions*

PubMed Central

Euskirchen, Ghia; Auerbach, Raymond K.; Snyder, Michael

2012-01-01

Chromatin-remodeling enzymes play essential roles in many biological processes, including gene expression, DNA replication and repair, and cell division. Although one such complex, SWI/SNF, has been extensively studied, new discoveries are still being made. Here, we review SWI/SNF biochemistry; highlight recent genomic and proteomic advances; and address the role of SWI/SNF in human diseases, including cancer and viral infections. These studies have greatly increased our understanding of complex nuclear processes. PMID:22952240

Biomarkers to Assess Possible Biological Effects on Reproductive Potential, Immune Function, and Energetic Fitness of Bottlenose Dolphins Exposed to Sounds Consistent with Naval Sonars

DTIC Science & Technology

2013-09-30

ion modes. The resulting chromatograms were then processed using XCMS (alignment and peak picking ). The data were processed with in-house...UHPLC liquid chromatography Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry ( MS ). A standard method was developed for rapid analysis...extraction protocols and then implemented LC- MS / MS analyses on our Thermo Fisher Scientific TSQ Vantage triple quadrupole mass spectrometer. This

Large scale analysis of the mutational landscape in β-glucuronidase: A major player of mucopolysaccharidosis type VII.

PubMed

Khan, Faez Iqbal; Shahbaaz, Mohd; Bisetty, Krishna; Waheed, Abdul; Sly, William S; Ahmad, Faizan; Hassan, Md Imtaiyaz

2016-01-15

The lysosomal storage disorders are a group of 50 unique inherited diseases characterized by unseemly lipid storage in lysosomes. These malfunctions arise due to genetic mutations that result in deficiency or reduced activities of the lysosomal enzymes, which are responsible for catabolism of biological macromolecules. Sly syndrome or mucopolysaccharidosis type VII is a lysosomal storage disorder associated with the deficiency of β-glucuronidase (EC 3.2.1.31) that catalyzes the hydrolysis of β-D-glucuronic acid residues from the non-reducing terminal of glycosaminoglycan. The effects of the disease causing mutations on the framework of the sequences and structure of β-glucuronidase (GUSBp) were analyzed utilizing a variety of bioinformatic tools. These analyses showed that 211 mutations may result in alteration of the biological activity of GUSBp, including previously experimentally validated mutations. Finally, we refined 90 disease causing mutations, which presumably cause a significant impact on the structure, function, and stability of GUSBp. Stability analyses showed that mutations p.Phe208Pro, p.Phe539Gly, p.Leu622Gly, p.Ile499Gly and p.Ile586Gly caused the highest impact on GUSBp stability and function because of destabilization of the protein structure. Furthermore, structures of wild type and mutant GUSBp were subjected to molecular dynamics simulation to examine the relative structural behaviors in the explicit conditions of water. In a broader view, the use of in silico approaches provided a useful understanding of the effect of single point mutations on the structure-function relationship of GUSBp. Copyright © 2015 Elsevier B.V. All rights reserved.

Genetic resources for maize cell wall biology.

PubMed

Penning, Bryan W; Hunter, Charles T; Tayengwa, Reuben; Eveland, Andrea L; Dugard, Christopher K; Olek, Anna T; Vermerris, Wilfred; Koch, Karen E; McCarty, Donald R; Davis, Mark F; Thomas, Steven R; McCann, Maureen C; Carpita, Nicholas C

2009-12-01

Grass species represent a major source of food, feed, and fiber crops and potential feedstocks for biofuel production. Most of the biomass is contributed by cell walls that are distinct in composition from all other flowering plants. Identifying cell wall-related genes and their functions underpins a fundamental understanding of growth and development in these species. Toward this goal, we are building a knowledge base of the maize (Zea mays) genes involved in cell wall biology, their expression profiles, and the phenotypic consequences of mutation. Over 750 maize genes were annotated and assembled into gene families predicted to function in cell wall biogenesis. Comparative genomics of maize, rice (Oryza sativa), and Arabidopsis (Arabidopsis thaliana) sequences reveal differences in gene family structure between grass species and a reference eudicot species. Analysis of transcript profile data for cell wall genes in developing maize ovaries revealed that expression within families differed by up to 100-fold. When transcriptional analyses of developing ovaries before pollination from Arabidopsis, rice, and maize were contrasted, distinct sets of cell wall genes were expressed in grasses. These differences in gene family structure and expression between Arabidopsis and the grasses underscore the requirement for a grass-specific genetic model for functional analyses. A UniformMu population proved to be an important resource in both forward- and reverse-genetics approaches to identify hundreds of mutants in cell wall genes. A forward screen of field-grown lines by near-infrared spectroscopic screen of mature leaves yielded several dozen lines with heritable spectroscopic phenotypes. Pyrolysis-molecular beam mass spectrometry confirmed that several nir mutants had altered carbohydrate-lignin compositions.

Circulating microRNAs disclose biology of normal cognitive function in healthy elderly people - a discovery twin study.

PubMed

Mengel-From, Jonas; Feddersen, Søren; Halekoh, Ulrich; Heegaard, Niels H H; McGue, Matt; Christensen, Kaare; Tan, Qihua; Christiansen, Lene

2018-05-02

Neurobiology is regulated by miRNA. Here circulating plasma miRNAs were assayed on a 754 miRNA OpenArray platform using 90 monozygotic elderly twins (73-95 year of age) and associated with mini mental state examination (MMSE) and a five-component cognitive score (CCS) in an explorative study. Both ordinary individual and twin-pair analyses were performed with level of cognitive scores. Candidate miRNAs were further associated with cognitive decline over 10 years using up to six repeated assessments. A total of 278 miRNAs were expressed in plasma from at least ten participants and 23 miRNAs were nominally associated (i.e., at an uncorrected p < 0.05) with CCS or MMSE in the paired analyses. Generally, elderly individuals with poor cognitive function had increase miRNA expression compared with equivalent individuals who performed better on the cognitive scale. Three miRNAs, miR-151a-3p, miR-212-3p and miR-1274b were associated with CCS both in the paired and the individual analysis. Four miRNAs found to be associated with CCS in cross-sectional analysis were also found to show an association in longitudinal analysis such that increase miRNA expression was associated with steeper cognitive decline. We propose a shared biological path underlies dementia and normative cognitive aging.

Substrate-Mediated Laser Ablation under Ambient Conditions for Spatially-Resolved Tissue Proteomics

PubMed Central

Fatou, Benoit; Wisztorski, Maxence; Focsa, Cristian; Salzet, Michel; Ziskind, Michael; Fournier, Isabelle

2015-01-01

Numerous applications of ambient Mass Spectrometry (MS) have been demonstrated over the past decade. They promoted the emergence of various micro-sampling techniques such as Laser Ablation/Droplet Capture (LADC). LADC consists in the ablation of analytes from a surface and their subsequent capture in a solvent droplet which can then be analyzed by MS. LADC is thus generally performed in the UV or IR range, using a wavelength at which analytes or the matrix absorb. In this work, we explore the potential of visible range LADC (532 nm) as a micro-sampling technology for large-scale proteomics analyses. We demonstrate that biomolecule analyses using 532 nm LADC are possible, despite the low absorbance of biomolecules at this wavelength. This is due to the preponderance of an indirect substrate-mediated ablation mechanism at low laser energy which contrasts with the conventional direct ablation driven by sample absorption. Using our custom LADC system and taking advantage of this substrate-mediated ablation mechanism, we were able to perform large-scale proteomic analyses of micro-sampled tissue sections and demonstrated the possible identification of proteins with relevant biological functions. Consequently, the 532 nm LADC technique offers a new tool for biological and clinical applications. PMID:26674367

Transcriptional Profiling of Hypoxic Neural Stem Cells Identifies Calcineurin-NFATc4 Signaling as a Major Regulator of Neural Stem Cell Biology

PubMed Central

Moreno, Marta; Fernández, Virginia; Monllau, Josep M.; Borrell, Víctor; Lerin, Carles; de la Iglesia, Núria

2015-01-01

Summary Neural stem cells (NSCs) reside in a hypoxic microenvironment within the brain. However, the crucial transcription factors (TFs) that regulate NSC biology under physiologic hypoxia are poorly understood. Here we have performed gene set enrichment analysis (GSEA) of microarray datasets from hypoxic versus normoxic NSCs with the aim of identifying pathways and TFs that are activated under oxygen concentrations mimicking normal brain tissue microenvironment. Integration of TF target (TFT) and pathway enrichment analysis identified the calcium-regulated TF NFATc4 as a major candidate to regulate hypoxic NSC functions. Nfatc4 expression was coordinately upregulated by top hypoxia-activated TFs, while NFATc4 target genes were enriched in hypoxic NSCs. Loss-of-function analyses further revealed that the calcineurin-NFATc4 signaling axis acts as a major regulator of NSC self-renewal and proliferation in vitro and in vivo by promoting the expression of TFs, including Id2, that contribute to the maintenance of the NSC state. PMID:26235896

microRNA Expression Profiling: Technologies, Insights, and Prospects.

PubMed

Roden, Christine; Mastriano, Stephen; Wang, Nayi; Lu, Jun

2015-01-01

Since the early days of microRNA (miRNA) research, miRNA expression profiling technologies have provided important tools toward both better understanding of the biological functions of miRNAs and using miRNA expression as potential diagnostics. Multiple technologies, such as microarrays, next-generation sequencing, bead-based detection system, single-molecule measurements, and quantitative RT-PCR, have enabled accurate quantification of miRNAs and the subsequent derivation of key insights into diverse biological processes. As a class of ~22 nt long small noncoding RNAs, miRNAs present unique challenges in expression profiling that require careful experimental design and data analyses. We will particularly discuss how normalization and the presence of miRNA isoforms can impact data interpretation. We will present one example in which the consideration in data normalization has provided insights that helped to establish the global miRNA expression as a tumor suppressor. Finally, we discuss two future prospects of using miRNA profiling technologies to understand single cell variability and derive new rules for the functions of miRNA isoforms.

Structural data and immunomodulatory properties of a water-soluble heteroglycan extracted from the mycelium of an Italian isolate of Ganoderma lucidum.

PubMed

Carrieri, Raffaele; Manco, Rosanna; Sapio, Daniela; Iannaccone, Marco; Fulgione, Andrea; Papaianni, Marina; de Falco, Bruna; Grauso, Laura; Tarantino, Paola; Ianniello, Flora; Lanzotti, Virginia; Lahoz, Ernesto; Capparelli, Rosanna

2017-09-01

Mushrooms produce a wide range of bioactive polysaccharides, different from each other in chemical structure and biological effects. In the last years, the idea to develop functional foods or drugs containing fungal polysaccharides is attracting great attention. Fruiting bodies of Basidiomycetes Ganoderma lucidum are commonly used in Oriental medicine to treat several disorders. G. lucidum polysaccharides - mainly β-glucans and heteroglycans - have numerous biological properties such as antitumour and immunomodulatory activities. This report shows, by gene expression analyses and bioenergetic assays, immunomodulatory properties and capacity to improve glucose metabolism of a water-soluble heteroglycan extracted from mycelium of an Italian isolate of G. lucidum. The findings suggest the use of the heteroglycan as probiotic or ingredient in functional foods, being easy to produce and disperse in a food matrix thanks to its water-solubility. Heteroglycan could exert protective effects in pro-inflammatory conditions and benefits for people characterised by suppressed immune response.

From Network Analysis to Functional Metabolic Modeling of the Human Gut Microbiota.

PubMed

Bauer, Eugen; Thiele, Ines

2018-01-01

An important hallmark of the human gut microbiota is its species diversity and complexity. Various diseases have been associated with a decreased diversity leading to reduced metabolic functionalities. Common approaches to investigate the human microbiota include high-throughput sequencing with subsequent correlative analyses. However, to understand the ecology of the human gut microbiota and consequently design novel treatments for diseases, it is important to represent the different interactions between microbes with their associated metabolites. Computational systems biology approaches can give further mechanistic insights by constructing data- or knowledge-driven networks that represent microbe interactions. In this minireview, we will discuss current approaches in systems biology to analyze the human gut microbiota, with a particular focus on constraint-based modeling. We will discuss various community modeling techniques with their advantages and differences, as well as their application to predict the metabolic mechanisms of intestinal microbial communities. Finally, we will discuss future perspectives and current challenges of simulating realistic and comprehensive models of the human gut microbiota.

The Systems Biology Markup Language (SBML) Level 3 Package: Flux Balance Constraints.

PubMed

Olivier, Brett G; Bergmann, Frank T

2015-09-04

Constraint-based modeling is a well established modelling methodology used to analyze and study biological networks on both a medium and genome scale. Due to their large size, genome scale models are typically analysed using constraint-based optimization techniques. One widely used method is Flux Balance Analysis (FBA) which, for example, requires a modelling description to include: the definition of a stoichiometric matrix, an objective function and bounds on the values that fluxes can obtain at steady state. The Flux Balance Constraints (FBC) Package extends SBML Level 3 and provides a standardized format for the encoding, exchange and annotation of constraint-based models. It includes support for modelling concepts such as objective functions, flux bounds and model component annotation that facilitates reaction balancing. The FBC package establishes a base level for the unambiguous exchange of genome-scale, constraint-based models, that can be built upon by the community to meet future needs (e. g. by extending it to cover dynamic FBC models).

The Systems Biology Markup Language (SBML) Level 3 Package: Flux Balance Constraints.

PubMed

Olivier, Brett G; Bergmann, Frank T

2015-06-01

Constraint-based modeling is a well established modelling methodology used to analyze and study biological networks on both a medium and genome scale. Due to their large size, genome scale models are typically analysed using constraint-based optimization techniques. One widely used method is Flux Balance Analysis (FBA) which, for example, requires a modelling description to include: the definition of a stoichiometric matrix, an objective function and bounds on the values that fluxes can obtain at steady state. The Flux Balance Constraints (FBC) Package extends SBML Level 3 and provides a standardized format for the encoding, exchange and annotation of constraint-based models. It includes support for modelling concepts such as objective functions, flux bounds and model component annotation that facilitates reaction balancing. The FBC package establishes a base level for the unambiguous exchange of genome-scale, constraint-based models, that can be built upon by the community to meet future needs (e. g. by extending it to cover dynamic FBC models).

Functional connectomics from a "big data" perspective.

PubMed

Xia, Mingrui; He, Yong

2017-10-15

In the last decade, explosive growth regarding functional connectome studies has been observed. Accumulating knowledge has significantly contributed to our understanding of the brain's functional network architectures in health and disease. With the development of innovative neuroimaging techniques, the establishment of large brain datasets and the increasing accumulation of published findings, functional connectomic research has begun to move into the era of "big data", which generates unprecedented opportunities for discovery in brain science and simultaneously encounters various challenging issues, such as data acquisition, management and analyses. Big data on the functional connectome exhibits several critical features: high spatial and/or temporal precision, large sample sizes, long-term recording of brain activity, multidimensional biological variables (e.g., imaging, genetic, demographic, cognitive and clinic) and/or vast quantities of existing findings. We review studies regarding functional connectomics from a big data perspective, with a focus on recent methodological advances in state-of-the-art image acquisition (e.g., multiband imaging), analysis approaches and statistical strategies (e.g., graph theoretical analysis, dynamic network analysis, independent component analysis, multivariate pattern analysis and machine learning), as well as reliability and reproducibility validations. We highlight the novel findings in the application of functional connectomic big data to the exploration of the biological mechanisms of cognitive functions, normal development and aging and of neurological and psychiatric disorders. We advocate the urgent need to expand efforts directed at the methodological challenges and discuss the direction of applications in this field. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparative landscape genetics of two frugivorous bats in a biological corridor undergoing agricultural intensification.

PubMed

Cleary, Katherine A; Waits, Lisette P; Finegan, Bryan

2017-09-01

Agricultural intensification in tropical landscapes poses a new threat to the ability of biological corridors to maintain functional connectivity for native species. We use a landscape genetics approach to evaluate impacts of expanding pineapple plantations on two widespread and abundant frugivorous bats in a biological corridor in Costa Rica. We hypothesize that the larger, more mobile Artibeus jamaicensis will be less impacted by pineapple than the smaller Carollia castanea. In 2012 and 2013, we sampled 735 bats in 26 remnant forest patches surrounded by different proportions of forest, pasture, crops and pineapple. We used 10 microsatellite loci for A. jamaicensis and 16 microsatellite loci for C. castanea to estimate genetic diversity and gene flow. Canonical correspondence analyses indicate that land cover type surrounding patches has no impact on genetic diversity of A. jamaicensis. However, for C. castanea, both percentage forest and pineapple surrounding patches explained a significant proportion of the variation in genetic diversity. Least-cost transect analyses (LCTA) and pairwise G″st suggest that for A. jamaicensis, pineapple is more permeable to gene flow than expected, while as expected, forest is the most permeable land cover for gene flow of C. castanea. For both species, LCTA indicate that development may play a role in inhibiting gene flow. The current study answers the call for landscape genetic research focused on tropical and agricultural landscapes, highlights the value of comparative landscape genetics in biological corridor design and management and is one of the few studies of biological corridors in any ecosystem to implement a genetic approach to test corridor efficacy. © 2017 John Wiley & Sons Ltd.

Coexpression landscape in ATTED-II: usage of gene list and gene network for various types of pathways.

PubMed

Obayashi, Takeshi; Kinoshita, Kengo

2010-05-01

Gene coexpression analyses are a powerful method to predict the function of genes and/or to identify genes that are functionally related to query genes. The basic idea of gene coexpression analyses is that genes with similar functions should have similar expression patterns under many different conditions. This approach is now widely used by many experimental researchers, especially in the field of plant biology. In this review, we will summarize recent successful examples obtained by using our gene coexpression database, ATTED-II. Specifically, the examples will describe the identification of new genes, such as the subunits of a complex protein, the enzymes in a metabolic pathway and transporters. In addition, we will discuss the discovery of a new intercellular signaling factor and new regulatory relationships between transcription factors and their target genes. In ATTED-II, we provide two basic views of gene coexpression, a gene list view and a gene network view, which can be used as guide gene approach and narrow-down approach, respectively. In addition, we will discuss the coexpression effectiveness for various types of gene sets.

Current Progress in Tonoplast Proteomics Reveals Insights into the Function of the Large Central Vacuole

PubMed Central

Trentmann, Oliver; Haferkamp, Ilka

2013-01-01

Vacuoles of plants fulfill various biologically important functions, like turgor generation and maintenance, detoxification, solute sequestration, or protein storage. Different types of plant vacuoles (lytic versus protein storage) are characterized by different functional properties apparently caused by a different composition/abundance and regulation of transport proteins in the surrounding membrane, the tonoplast. Proteome analyses allow the identification of vacuolar proteins and provide an informative basis for assigning observed transport processes to specific carriers or channels. This review summarizes techniques required for vacuolar proteome analyses, like e.g., isolation of the large central vacuole or tonoplast membrane purification. Moreover, an overview about diverse published vacuolar proteome studies is provided. It becomes evident that qualitative proteomes from different plant species represent just the tip of the iceberg. During the past few years, mass spectrometry achieved immense improvement concerning its accuracy, sensitivity, and application. As a consequence, modern tonoplast proteome approaches are suited for detecting alterations in membrane protein abundance in response to changing environmental/physiological conditions and help to clarify the regulation of tonoplast transport processes. PMID:23459586

Modern Perspectives on Numerical Modeling of Cardiac Pacemaker Cell

PubMed Central

Maltsev, Victor A.; Yaniv, Yael; Maltsev, Anna V.; Stern, Michael D.; Lakatta, Edward G.

2015-01-01

Cardiac pacemaking is a complex phenomenon that is still not completely understood. Together with experimental studies, numerical modeling has been traditionally used to acquire mechanistic insights in this research area. This review summarizes the present state of numerical modeling of the cardiac pacemaker, including approaches to resolve present paradoxes and controversies. Specifically we discuss the requirement for realistic modeling to consider symmetrical importance of both intracellular and cell membrane processes (within a recent “coupled-clock” theory). Promising future developments of the complex pacemaker system models include the introduction of local calcium control, mitochondria function, and biochemical regulation of protein phosphorylation and cAMP production. Modern numerical and theoretical methods such as multi-parameter sensitivity analyses within extended populations of models and bifurcation analyses are also important for the definition of the most realistic parameters that describe a robust, yet simultaneously flexible operation of the coupled-clock pacemaker cell system. The systems approach to exploring cardiac pacemaker function will guide development of new therapies, such as biological pacemakers for treating insufficient cardiac pacemaker function that becomes especially prevalent with advancing age. PMID:24748434

Facile synthesis of zwitterionic polymer-coated core-shell magnetic nanoparticles for highly specific capture of N-linked glycopeptides

NASA Astrophysics Data System (ADS)

Chen, Yajing; Xiong, Zhichao; Zhang, Lingyi; Zhao, Jiaying; Zhang, Quanqing; Peng, Li; Zhang, Weibing; Ye, Mingliang; Zou, Hanfa

2015-02-01

Highly selective and efficient capture of glycosylated proteins and peptides from complex biological samples is of profound significance for the discovery of disease biomarkers in biological systems. Recently, hydrophilic interaction liquid chromatography (HILIC)-based functional materials have been extensively utilized for glycopeptide enrichment. However, the low amount of immobilized hydrophilic groups on the affinity material has limited its specificity, detection sensitivity and binding capacity in the capture of glycopeptides. Herein, a novel affinity material was synthesized to improve the binding capacity and detection sensitivity for glycopeptides by coating a poly(2-(methacryloyloxy)ethyl)-dimethyl-(3-sulfopropyl) ammonium hydroxide (PMSA) shell onto Fe3O4@SiO2 nanoparticles, taking advantage of reflux-precipitation polymerization for the first time (denoted as Fe3O4@SiO2@PMSA). The thick polymer shell endows the nanoparticles with excellent hydrophilic property and several functional groups on the polymer chains. The resulting Fe3O4@SiO2@PMSA demonstrated an outstanding ability for glycopeptide enrichment with high selectivity, extremely high detection sensitivity (0.1 fmol), large binding capacity (100 mg g-1), high enrichment recovery (above 73.6%) and rapid magnetic separation. Furthermore, in the analysis of real complicated biological samples, 905 unique N-glycosylation sites from 458 N-glycosylated proteins were reliably identified in three replicate analyses of a 65 μg protein sample extracted from mouse liver, showing the great potential of Fe3O4@SiO2@PMSA in the detection and identification of low-abundance N-linked glycopeptides in biological samples.Highly selective and efficient capture of glycosylated proteins and peptides from complex biological samples is of profound significance for the discovery of disease biomarkers in biological systems. Recently, hydrophilic interaction liquid chromatography (HILIC)-based functional materials have been extensively utilized for glycopeptide enrichment. However, the low amount of immobilized hydrophilic groups on the affinity material has limited its specificity, detection sensitivity and binding capacity in the capture of glycopeptides. Herein, a novel affinity material was synthesized to improve the binding capacity and detection sensitivity for glycopeptides by coating a poly(2-(methacryloyloxy)ethyl)-dimethyl-(3-sulfopropyl) ammonium hydroxide (PMSA) shell onto Fe3O4@SiO2 nanoparticles, taking advantage of reflux-precipitation polymerization for the first time (denoted as Fe3O4@SiO2@PMSA). The thick polymer shell endows the nanoparticles with excellent hydrophilic property and several functional groups on the polymer chains. The resulting Fe3O4@SiO2@PMSA demonstrated an outstanding ability for glycopeptide enrichment with high selectivity, extremely high detection sensitivity (0.1 fmol), large binding capacity (100 mg g-1), high enrichment recovery (above 73.6%) and rapid magnetic separation. Furthermore, in the analysis of real complicated biological samples, 905 unique N-glycosylation sites from 458 N-glycosylated proteins were reliably identified in three replicate analyses of a 65 μg protein sample extracted from mouse liver, showing the great potential of Fe3O4@SiO2@PMSA in the detection and identification of low-abundance N-linked glycopeptides in biological samples. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr05955g

Sample heterogeneity in unipolar depression as assessed by functional connectivity analyses is dominated by general disease effects.

PubMed

Feder, Stephan; Sundermann, Benedikt; Wersching, Heike; Teuber, Anja; Kugel, Harald; Teismann, Henning; Heindel, Walter; Berger, Klaus; Pfleiderer, Bettina

2017-11-01

Combinations of resting-state fMRI and machine-learning techniques are increasingly employed to develop diagnostic models for mental disorders. However, little is known about the neurobiological heterogeneity of depression and diagnostic machine learning has mainly been tested in homogeneous samples. Our main objective was to explore the inherent structure of a diverse unipolar depression sample. The secondary objective was to assess, if such information can improve diagnostic classification. We analyzed data from 360 patients with unipolar depression and 360 non-depressed population controls, who were subdivided into two independent subsets. Cluster analyses (unsupervised learning) of functional connectivity were used to generate hypotheses about potential patient subgroups from the first subset. The relationship of clusters with demographical and clinical measures was assessed. Subsequently, diagnostic classifiers (supervised learning), which incorporated information about these putative depression subgroups, were trained. Exploratory cluster analyses revealed two weakly separable subgroups of depressed patients. These subgroups differed in the average duration of depression and in the proportion of patients with concurrently severe depression and anxiety symptoms. The diagnostic classification models performed at chance level. It remains unresolved, if subgroups represent distinct biological subtypes, variability of continuous clinical variables or in part an overfitting of sparsely structured data. Functional connectivity in unipolar depression is associated with general disease effects. Cluster analyses provide hypotheses about potential depression subtypes. Diagnostic models did not benefit from this additional information regarding heterogeneity. Copyright © 2017 Elsevier B.V. All rights reserved.

Sparse feature selection methods identify unexpected global cellular response to strontium-containing materials

PubMed Central

Autefage, Hélène; Littmann, Elena; Hedegaard, Martin A. B.; Von Erlach, Thomas; O’Donnell, Matthew; Burden, Frank R.; Winkler, David A.; Stevens, Molly M.

2015-01-01

Despite the increasing sophistication of biomaterials design and functional characterization studies, little is known regarding cells’ global response to biomaterials. Here, we combined nontargeted holistic biological and physical science techniques to evaluate how simple strontium ion incorporation within the well-described biomaterial 45S5 bioactive glass (BG) influences the global response of human mesenchymal stem cells. Our objective analyses of whole gene-expression profiles, confirmed by standard molecular biology techniques, revealed that strontium-substituted BG up-regulated the isoprenoid pathway, suggesting an influence on both sterol metabolite synthesis and protein prenylation processes. This up-regulation was accompanied by increases in cellular and membrane cholesterol and lipid raft contents as determined by Raman spectroscopy mapping and total internal reflection fluorescence microscopy analyses and by an increase in cellular content of phosphorylated myosin II light chain. Our unexpected findings of this strong metabolic pathway regulation as a response to biomaterial composition highlight the benefits of discovery-driven nonreductionist approaches to gain a deeper understanding of global cell–material interactions and suggest alternative research routes for evaluating biomaterials to improve their design. PMID:25831522

Draft De Novo Transcriptome of the Rat Kangaroo Potorous tridactylus as a Tool for Cell Biology

PubMed Central

Udy, Dylan B.; Voorhies, Mark; Chan, Patricia P.; Lowe, Todd M.; Dumont, Sophie

2015-01-01

The rat kangaroo (long-nosed potoroo, Potorous tridactylus) is a marsupial native to Australia. Cultured rat kangaroo kidney epithelial cells (PtK) are commonly used to study cell biological processes. These mammalian cells are large, adherent, and flat, and contain large and few chromosomes—and are thus ideal for imaging intra-cellular dynamics such as those of mitosis. Despite this, neither the rat kangaroo genome nor transcriptome have been sequenced, creating a challenge for probing the molecular basis of these cellular dynamics. Here, we present the sequencing, assembly and annotation of the draft rat kangaroo de novo transcriptome. We sequenced 679 million reads that mapped to 347,323 Trinity transcripts and 20,079 Unigenes. We present statistics emerging from transcriptome-wide analyses, and analyses suggesting that the transcriptome covers full-length sequences of most genes, many with multiple isoforms. We also validate our findings with a proof-of-concept gene knockdown experiment. We expect that this high quality transcriptome will make rat kangaroo cells a more tractable system for linking molecular-scale function and cellular-scale dynamics. PMID:26252667

Estimation of gene induction enables a relevance-based ranking of gene sets.

PubMed

Bartholomé, Kilian; Kreutz, Clemens; Timmer, Jens

2009-07-01

In order to handle and interpret the vast amounts of data produced by microarray experiments, the analysis of sets of genes with a common biological functionality has been shown to be advantageous compared to single gene analyses. Some statistical methods have been proposed to analyse the differential gene expression of gene sets in microarray experiments. However, most of these methods either require threshhold values to be chosen for the analysis, or they need some reference set for the determination of significance. We present a method that estimates the number of differentially expressed genes in a gene set without requiring a threshold value for significance of genes. The method is self-contained (i.e., it does not require a reference set for comparison). In contrast to other methods which are focused on significance, our approach emphasizes the relevance of the regulation of gene sets. The presented method measures the degree of regulation of a gene set and is a useful tool to compare the induction of different gene sets and place the results of microarray experiments into the biological context. An R-package is available.

Integrated Genomic Analysis of Diverse Induced Pluripotent Stem Cells from the Progenitor Cell Biology Consortium.

PubMed

Salomonis, Nathan; Dexheimer, Phillip J; Omberg, Larsson; Schroll, Robin; Bush, Stacy; Huo, Jeffrey; Schriml, Lynn; Ho Sui, Shannan; Keddache, Mehdi; Mayhew, Christopher; Shanmukhappa, Shiva Kumar; Wells, James; Daily, Kenneth; Hubler, Shane; Wang, Yuliang; Zambidis, Elias; Margolin, Adam; Hide, Winston; Hatzopoulos, Antonis K; Malik, Punam; Cancelas, Jose A; Aronow, Bruce J; Lutzko, Carolyn

2016-07-12

The rigorous characterization of distinct induced pluripotent stem cells (iPSC) derived from multiple reprogramming technologies, somatic sources, and donors is required to understand potential sources of variability and downstream potential. To achieve this goal, the Progenitor Cell Biology Consortium performed comprehensive experimental and genomic analyses of 58 iPSC from ten laboratories generated using a variety of reprogramming genes, vectors, and cells. Associated global molecular characterization studies identified functionally informative correlations in gene expression, DNA methylation, and/or copy-number variation among key developmental and oncogenic regulators as a result of donor, sex, line stability, reprogramming technology, and cell of origin. Furthermore, X-chromosome inactivation in PSC produced highly correlated differences in teratoma-lineage staining and regulator expression upon differentiation. All experimental results, and raw, processed, and metadata from these analyses, including powerful tools, are interactively accessible from a new online portal at https://www.synapse.org to serve as a reusable resource for the stem cell community. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Draft De Novo Transcriptome of the Rat Kangaroo Potorous tridactylus as a Tool for Cell Biology.

PubMed

Udy, Dylan B; Voorhies, Mark; Chan, Patricia P; Lowe, Todd M; Dumont, Sophie

2015-01-01

The rat kangaroo (long-nosed potoroo, Potorous tridactylus) is a marsupial native to Australia. Cultured rat kangaroo kidney epithelial cells (PtK) are commonly used to study cell biological processes. These mammalian cells are large, adherent, and flat, and contain large and few chromosomes-and are thus ideal for imaging intra-cellular dynamics such as those of mitosis. Despite this, neither the rat kangaroo genome nor transcriptome have been sequenced, creating a challenge for probing the molecular basis of these cellular dynamics. Here, we present the sequencing, assembly and annotation of the draft rat kangaroo de novo transcriptome. We sequenced 679 million reads that mapped to 347,323 Trinity transcripts and 20,079 Unigenes. We present statistics emerging from transcriptome-wide analyses, and analyses suggesting that the transcriptome covers full-length sequences of most genes, many with multiple isoforms. We also validate our findings with a proof-of-concept gene knockdown experiment. We expect that this high quality transcriptome will make rat kangaroo cells a more tractable system for linking molecular-scale function and cellular-scale dynamics.

Probing the Xenopus laevis inner ear transcriptome for biological function

PubMed Central

2012-01-01

Background The senses of hearing and balance depend upon mechanoreception, a process that originates in the inner ear and shares features across species. Amphibians have been widely used for physiological studies of mechanotransduction by sensory hair cells. In contrast, much less is known of the genetic basis of auditory and vestibular function in this class of animals. Among amphibians, the genus Xenopus is a well-characterized genetic and developmental model that offers unique opportunities for inner ear research because of the amphibian capacity for tissue and organ regeneration. For these reasons, we implemented a functional genomics approach as a means to undertake a large-scale analysis of the Xenopus laevis inner ear transcriptome through microarray analysis. Results Microarray analysis uncovered genes within the X. laevis inner ear transcriptome associated with inner ear function and impairment in other organisms, thereby supporting the inclusion of Xenopus in cross-species genetic studies of the inner ear. The use of gene categories (inner ear tissue; deafness; ion channels; ion transporters; transcription factors) facilitated the assignment of functional significance to probe set identifiers. We enhanced the biological relevance of our microarray data by using a variety of curation approaches to increase the annotation of the Affymetrix GeneChip® Xenopus laevis Genome array. In addition, annotation analysis revealed the prevalence of inner ear transcripts represented by probe set identifiers that lack functional characterization. Conclusions We identified an abundance of targets for genetic analysis of auditory and vestibular function. The orthologues to human genes with known inner ear function and the highly expressed transcripts that lack annotation are particularly interesting candidates for future analyses. We used informatics approaches to impart biologically relevant information to the Xenopus inner ear transcriptome, thereby addressing the impediment imposed by insufficient gene annotation. These findings heighten the relevance of Xenopus as a model organism for genetic investigations of inner ear organogenesis, morphogenesis, and regeneration. PMID:22676585

Mathematical methods to analysis of topology, functional variability and evolution of metabolic systems based on different decomposition concepts.

PubMed

Mrabet, Yassine; Semmar, Nabil

2010-05-01

Complexity of metabolic systems can be undertaken at different scales (metabolites, metabolic pathways, metabolic network map, biological population) and under different aspects (structural, functional, evolutive). To analyse such a complexity, metabolic systems need to be decomposed into different components according to different concepts. Four concepts are presented here consisting in considering metabolic systems as sets of metabolites, chemical reactions, metabolic pathways or successive processes. From a metabolomic dataset, such decompositions are performed using different mathematical methods including correlation, stiochiometric, ordination, classification, combinatorial and kinetic analyses. Correlation analysis detects and quantifies affinities/oppositions between metabolites. Stoichiometric analysis aims to identify the organisation of a metabolic network into different metabolic pathways on the hand, and to quantify/optimize the metabolic flux distribution through the different chemical reactions of the system. Ordination and classification analyses help to identify different metabolic trends and their associated metabolites in order to highlight chemical polymorphism representing different variability poles of the metabolic system. Then, metabolic processes/correlations responsible for such a polymorphism can be extracted in silico by combining metabolic profiles representative of different metabolic trends according to a weighting bootstrap approach. Finally evolution of metabolic processes in time can be analysed by different kinetic/dynamic modelling approaches.

bc-GenExMiner 3.0: new mining module computes breast cancer gene expression correlation analyses.

PubMed

Jézéquel, Pascal; Frénel, Jean-Sébastien; Campion, Loïc; Guérin-Charbonnel, Catherine; Gouraud, Wilfried; Ricolleau, Gabriel; Campone, Mario

2013-01-01

We recently developed a user-friendly web-based application called bc-GenExMiner (http://bcgenex.centregauducheau.fr), which offered the possibility to evaluate prognostic informativity of genes in breast cancer by means of a 'prognostic module'. In this study, we develop a new module called 'correlation module', which includes three kinds of gene expression correlation analyses. The first one computes correlation coefficient between 2 or more (up to 10) chosen genes. The second one produces two lists of genes that are most correlated (positively and negatively) to a 'tested' gene. A gene ontology (GO) mining function is also proposed to explore GO 'biological process', 'molecular function' and 'cellular component' terms enrichment for the output lists of most correlated genes. The third one explores gene expression correlation between the 15 telomeric and 15 centromeric genes surrounding a 'tested' gene. These correlation analyses can be performed in different groups of patients: all patients (without any subtyping), in molecular subtypes (basal-like, HER2+, luminal A and luminal B) and according to oestrogen receptor status. Validation tests based on published data showed that these automatized analyses lead to results consistent with studies' conclusions. In brief, this new module has been developed to help basic researchers explore molecular mechanisms of breast cancer. DATABASE URL: http://bcgenex.centregauducheau.fr

Systems genetics of obesity in an F2 pig model by genome-wide association, genetic network, and pathway analyses

PubMed Central

Kogelman, Lisette J. A.; Pant, Sameer D.; Fredholm, Merete; Kadarmideen, Haja N.

2014-01-01

Obesity is a complex condition with world-wide exponentially rising prevalence rates, linked with severe diseases like Type 2 Diabetes. Economic and welfare consequences have led to a raised interest in a better understanding of the biological and genetic background. To date, whole genome investigations focusing on single genetic variants have achieved limited success, and the importance of including genetic interactions is becoming evident. Here, the aim was to perform an integrative genomic analysis in an F2 pig resource population that was constructed with an aim to maximize genetic variation of obesity-related phenotypes and genotyped using the 60K SNP chip. Firstly, Genome Wide Association (GWA) analysis was performed on the Obesity Index to locate candidate genomic regions that were further validated using combined Linkage Disequilibrium Linkage Analysis and investigated by evaluation of haplotype blocks. We built Weighted Interaction SNP Hub (WISH) and differentially wired (DW) networks using genotypic correlations amongst obesity-associated SNPs resulting from GWA analysis. GWA results and SNP modules detected by WISH and DW analyses were further investigated by functional enrichment analyses. The functional annotation of SNPs revealed several genes associated with obesity, e.g., NPC2 and OR4D10. Moreover, gene enrichment analyses identified several significantly associated pathways, over and above the GWA study results, that may influence obesity and obesity related diseases, e.g., metabolic processes. WISH networks based on genotypic correlations allowed further identification of various gene ontology terms and pathways related to obesity and related traits, which were not identified by the GWA study. In conclusion, this is the first study to develop a (genetic) obesity index and employ systems genetics in a porcine model to provide important insights into the complex genetic architecture associated with obesity and many biological pathways that underlie it. PMID:25071839

Plants and climate change: complexities and surprises

PubMed Central

Parmesan, Camille; Hanley, Mick E.

2015-01-01

Background Anthropogenic climate change (ACC) will influence all aspects of plant biology over coming decades. Many changes in wild species have already been well-documented as a result of increased atmospheric CO2 concentrations, warming climate and changing precipitation regimes. A wealth of available data has allowed the use of meta-analyses to examine plant–climate interactions on more sophisticated levels than before. These analyses have revealed major differences in plant response among groups, e.g. with respect to functional traits, taxonomy, life-history and provenance. Interestingly, these meta-analyses have also exposed unexpected mismatches between theory, experimental, and observational studies. Scope We reviewed the literature on species’ responses to ACC, finding ∼42 % of 4000 species studied globally are plants (primarily terrestrial). We review impacts on phenology, distributions, ecophysiology, regeneration biology, plant–plant and plant–herbivore interactions, and the roles of plasticity and evolution. We focused on apparent deviations from expectation, and highlighted cases where more sophisticated analyses revealed that unexpected changes were, in fact, responses to ACC. Conclusions We found that conventionally expected responses are generally well-understood, and that it is the aberrant responses that are now yielding greater insight into current and possible future impacts of ACC. We argue that inconclusive, unexpected, or counter-intuitive results should be embraced in order to understand apparent disconnects between theory, prediction, and observation. We highlight prime examples from the collection of papers in this Special Issue, as well as general literature. We found use of plant functional groupings/traits had mixed success, but that some underutilized approaches, such as Grime's C/S/R strategies, when incorporated, have improved understanding of observed responses. Despite inherent difficulties, we highlight the need for ecologists to conduct community-level experiments in systems that replicate multiple aspects of ACC. Specifically, we call for development of coordinating experiments across networks of field sites, both natural and man-made. PMID:26555281

Contrasting responses of functional diversity to major losses in taxonomic diversity.

PubMed

Edie, Stewart M; Jablonski, David; Valentine, James W

2018-01-23

Taxonomic diversity of benthic marine invertebrate shelf species declines at present by nearly an order of magnitude from the tropics to the poles in each hemisphere along the latitudinal diversity gradient (LDG), most steeply along the western Pacific where shallow-sea diversity is at its tropical maximum. In the Bivalvia, a model system for macroevolution and macroecology, this taxonomic trend is accompanied by a decline in the number of functional groups and an increase in the evenness of taxa distributed among those groups, with maximum functional evenness (FE) in polar waters of both hemispheres. In contrast, analyses of this model system across the two era-defining events of the Phanerozoic, the Permian-Triassic and Cretaceous-Paleogene mass extinctions, show only minor declines in functional richness despite high extinction intensities, resulting in a rise in FE owing to the persistence of functional groups. We hypothesize that the spatial decline of taxonomic diversity and increase in FE along the present-day LDG primarily reflect diversity-dependent factors, whereas retention of almost all functional groups through the two mass extinctions suggests the operation of diversity-independent factors. Comparative analyses of different aspects of biodiversity thus reveal strongly contrasting biological consequences of similarly severe declines in taxonomic diversity and can help predict the consequences for functional diversity among different drivers of past, present, and future biodiversity loss.

An introduction to microbiome analysis for human biology applications.

PubMed

Amato, Katherine R

2017-01-01

Research examining the gut microbiota is currently exploding, and results are providing new perspectives on human biology. Factors such as host diet and physiology influence the composition and function of the gut microbiota, which in turn affects human nutrition, health, and behavior via interactions with metabolism, the immune system, and the brain. These findings represent an exciting new twist on familiar topics, and as a result, gut microbiome research is likely to provide insight into unresolved biological mechanisms driving human health. However, much remains to be learned about the broader ecological and evolutionary contexts within which gut microbes and humans are affecting each other. Here, I outline the procedures for generating data describing the gut microbiota with the goal of facilitating the wider integration of microbiome analyses into studies of human biology. I describe the steps involved in sample collection, DNA extraction, PCR amplification, high-throughput sequencing, and bioinformatics. While this review serves only as an introduction to these topics, it provides sufficient resources for researchers interested in launching new microbiome initiatives. As knowledge of these methods spreads, microbiome analysis should become a standard tool in the arsenal of human biology research. © 2016 Wiley Periodicals, Inc.

Bacteria as computers making computers

PubMed Central

Danchin, Antoine

2009-01-01

Various efforts to integrate biological knowledge into networks of interactions have produced a lively microbial systems biology. Putting molecular biology and computer sciences in perspective, we review another trend in systems biology, in which recursivity and information replace the usual concepts of differential equations, feedback and feedforward loops and the like. Noting that the processes of gene expression separate the genome from the cell machinery, we analyse the role of the separation between machine and program in computers. However, computers do not make computers. For cells to make cells requires a specific organization of the genetic program, which we investigate using available knowledge. Microbial genomes are organized into a paleome (the name emphasizes the role of the corresponding functions from the time of the origin of life), comprising a constructor and a replicator, and a cenome (emphasizing community-relevant genes), made up of genes that permit life in a particular context. The cell duplication process supposes rejuvenation of the machine and replication of the program. The paleome also possesses genes that enable information to accumulate in a ratchet-like process down the generations. The systems biology must include the dynamics of information creation in its future developments. PMID:19016882

Bacteria as computers making computers.

PubMed

Danchin, Antoine

2009-01-01

Various efforts to integrate biological knowledge into networks of interactions have produced a lively microbial systems biology. Putting molecular biology and computer sciences in perspective, we review another trend in systems biology, in which recursivity and information replace the usual concepts of differential equations, feedback and feedforward loops and the like. Noting that the processes of gene expression separate the genome from the cell machinery, we analyse the role of the separation between machine and program in computers. However, computers do not make computers. For cells to make cells requires a specific organization of the genetic program, which we investigate using available knowledge. Microbial genomes are organized into a paleome (the name emphasizes the role of the corresponding functions from the time of the origin of life), comprising a constructor and a replicator, and a cenome (emphasizing community-relevant genes), made up of genes that permit life in a particular context. The cell duplication process supposes rejuvenation of the machine and replication of the program. The paleome also possesses genes that enable information to accumulate in a ratchet-like process down the generations. The systems biology must include the dynamics of information creation in its future developments.

BiNA: A Visual Analytics Tool for Biological Network Data

PubMed Central

Gerasch, Andreas; Faber, Daniel; Küntzer, Jan; Niermann, Peter; Kohlbacher, Oliver; Lenhof, Hans-Peter; Kaufmann, Michael

2014-01-01

Interactive visual analysis of biological high-throughput data in the context of the underlying networks is an essential task in modern biomedicine with applications ranging from metabolic engineering to personalized medicine. The complexity and heterogeneity of data sets require flexible software architectures for data analysis. Concise and easily readable graphical representation of data and interactive navigation of large data sets are essential in this context. We present BiNA - the Biological Network Analyzer - a flexible open-source software for analyzing and visualizing biological networks. Highly configurable visualization styles for regulatory and metabolic network data offer sophisticated drawings and intuitive navigation and exploration techniques using hierarchical graph concepts. The generic projection and analysis framework provides powerful functionalities for visual analyses of high-throughput omics data in the context of networks, in particular for the differential analysis and the analysis of time series data. A direct interface to an underlying data warehouse provides fast access to a wide range of semantically integrated biological network databases. A plugin system allows simple customization and integration of new analysis algorithms or visual representations. BiNA is available under the 3-clause BSD license at http://bina.unipax.info/. PMID:24551056

BioTextQuest(+): a knowledge integration platform for literature mining and concept discovery.

PubMed

Papanikolaou, Nikolas; Pavlopoulos, Georgios A; Pafilis, Evangelos; Theodosiou, Theodosios; Schneider, Reinhard; Satagopam, Venkata P; Ouzounis, Christos A; Eliopoulos, Aristides G; Promponas, Vasilis J; Iliopoulos, Ioannis

2014-11-15

The iterative process of finding relevant information in biomedical literature and performing bioinformatics analyses might result in an endless loop for an inexperienced user, considering the exponential growth of scientific corpora and the plethora of tools designed to mine PubMed(®) and related biological databases. Herein, we describe BioTextQuest(+), a web-based interactive knowledge exploration platform with significant advances to its predecessor (BioTextQuest), aiming to bridge processes such as bioentity recognition, functional annotation, document clustering and data integration towards literature mining and concept discovery. BioTextQuest(+) enables PubMed and OMIM querying, retrieval of abstracts related to a targeted request and optimal detection of genes, proteins, molecular functions, pathways and biological processes within the retrieved documents. The front-end interface facilitates the browsing of document clustering per subject, the analysis of term co-occurrence, the generation of tag clouds containing highly represented terms per cluster and at-a-glance popup windows with information about relevant genes and proteins. Moreover, to support experimental research, BioTextQuest(+) addresses integration of its primary functionality with biological repositories and software tools able to deliver further bioinformatics services. The Google-like interface extends beyond simple use by offering a range of advanced parameterization for expert users. We demonstrate the functionality of BioTextQuest(+) through several exemplary research scenarios including author disambiguation, functional term enrichment, knowledge acquisition and concept discovery linking major human diseases, such as obesity and ageing. The service is accessible at http://bioinformatics.med.uoc.gr/biotextquest. g.pavlopoulos@gmail.com or georgios.pavlopoulos@esat.kuleuven.be Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

"To Hold the Subject's Territory": The Swedish Association of Biology Teachers and Two Curricular Reforms, 1960-1965

ERIC Educational Resources Information Center

Hallstrom, Jonas

2010-01-01

The aim of this article is to investigate and analyse the cultural boundaries of school biology, and to a certain extent the natural science subjects in general, in two Swedish curriculum reforms, from the viewpoint of the Swedish Association of Biology Teachers (ABT). Thomas Gieryn's concept of boundary-work is thus used in analysing how the ABT…

Learning in First-Year Biology: Approaches of Distance and On-Campus Students

NASA Astrophysics Data System (ADS)

Quinn, Frances Catherine

2011-01-01

This paper aims to extend previous research into learning of tertiary biology, by exploring the learning approaches adopted by two groups of students studying the same first-year biology topic in either on-campus or off-campus "distance" modes. The research involved 302 participants, who responded to a topic-specific version of the Study Process Questionnaire, and in-depth interviews with 16 of these students. Several quantitative analytic techniques, including cluster analysis and Rasch differential item functioning analysis, showed that the younger, on-campus cohort made less use of deep approaches, and more use of surface approaches than the older, off-campus group. At a finer scale, clusters of students within these categories demonstrated different patterns of learning approach. Students' descriptions of their learning approaches at interview provided richer complementary descriptions of the approach they took to their study in the topic, showing how deep and surface approaches were manifested in the study context. These findings are critically analysed in terms of recent literature questioning the applicability of learning approaches theory in mass education, and their implications for teaching and research in undergraduate biology.

Systems Biology Markup Language (SBML) Level 2 Version 5: Structures and Facilities for Model Definitions

PubMed Central

Hucka, Michael; Bergmann, Frank T.; Dräger, Andreas; Hoops, Stefan; Keating, Sarah M.; Le Novére, Nicolas; Myers, Chris J.; Olivier, Brett G.; Sahle, Sven; Schaff, James C.; Smith, Lucian P.; Waltemath, Dagmar; Wilkinson, Darren J.

2017-01-01

Summary Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 5 of SBML Level 2. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/. PMID:26528569

Effects of small particle numbers on long-term behaviour in discrete biochemical systems.

PubMed

Kreyssig, Peter; Wozar, Christian; Peter, Stephan; Veloz, Tomás; Ibrahim, Bashar; Dittrich, Peter

2014-09-01

The functioning of many biological processes depends on the appearance of only a small number of a single molecular species. Additionally, the observation of molecular crowding leads to the insight that even a high number of copies of species do not guarantee their interaction. How single particles contribute to stabilizing biological systems is not well understood yet. Hence, we aim at determining the influence of single molecules on the long-term behaviour of biological systems, i.e. whether they can reach a steady state. We provide theoretical considerations and a tool to analyse Systems Biology Markup Language models for the possibility to stabilize because of the described effects. The theory is an extension of chemical organization theory, which we called discrete chemical organization theory. Furthermore we scanned the BioModels Database for the occurrence of discrete chemical organizations. To exemplify our method, we describe an application to the Template model of the mitotic spindle assembly checkpoint mechanism. http://www.biosys.uni-jena.de/Services.html. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core

PubMed Central

Hucka, Michael; Bergmann, Frank T.; Hoops, Stefan; Keating, Sarah M.; Sahle, Sven; Schaff, James C.; Smith, Lucian P.; Wilkinson, Darren J.

2017-01-01

Summary Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 1 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/. PMID:26528564

Systems Biology Markup Language (SBML) Level 2 Version 5: Structures and Facilities for Model Definitions.

PubMed

Hucka, Michael; Bergmann, Frank T; Dräger, Andreas; Hoops, Stefan; Keating, Sarah M; Le Novère, Nicolas; Myers, Chris J; Olivier, Brett G; Sahle, Sven; Schaff, James C; Smith, Lucian P; Waltemath, Dagmar; Wilkinson, Darren J

2015-09-04

Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 5 of SBML Level 2. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org.

The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core.

PubMed

Hucka, Michael; Bergmann, Frank T; Hoops, Stefan; Keating, Sarah M; Sahle, Sven; Schaff, James C; Smith, Lucian P; Wilkinson, Darren J

2015-09-04

Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 1 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/.

The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core.

PubMed

Hucka, Michael; Bergmann, Frank T; Hoops, Stefan; Keating, Sarah M; Sahle, Sven; Schaff, James C; Smith, Lucian P; Wilkinson, Darren J

2015-06-01

Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 1 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/.

Systems Biology Markup Language (SBML) Level 2 Version 5: Structures and Facilities for Model Definitions.

PubMed

Hucka, Michael; Bergmann, Frank T; Dräger, Andreas; Hoops, Stefan; Keating, Sarah M; Le Novère, Nicolas; Myers, Chris J; Olivier, Brett G; Sahle, Sven; Schaff, James C; Smith, Lucian P; Waltemath, Dagmar; Wilkinson, Darren J

2015-06-01

Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 5 of SBML Level 2. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/.

Modular organization of the white spruce (Picea glauca) transcriptome reveals functional organization and evolutionary signatures.

PubMed

Raherison, Elie S M; Giguère, Isabelle; Caron, Sébastien; Lamara, Mebarek; MacKay, John J

2015-07-01

Transcript profiling has shown the molecular bases of several biological processes in plants but few studies have developed an understanding of overall transcriptome variation. We investigated transcriptome structure in white spruce (Picea glauca), aiming to delineate its modular organization and associated functional and evolutionary attributes. Microarray analyses were used to: identify and functionally characterize groups of co-expressed genes; investigate expressional and functional diversity of vascular tissue preferential genes which were conserved among Picea species, and identify expression networks underlying wood formation. We classified 22 857 genes as variable (79%; 22 coexpression groups) or invariant (21%) by profiling across several vegetative tissues. Modular organization and complex transcriptome restructuring among vascular tissue preferential genes was revealed by their assignment to coexpression groups with partially overlapping profiles and partially distinct functions. Integrated analyses of tissue-based and temporally variable profiles identified secondary xylem gene networks, showed their remodelling over a growing season and identified PgNAC-7 (no apical meristerm (NAM), Arabidopsis transcription activation factor (ATAF) and cup-shaped cotyledon (CUC) transcription factor 007 in Picea glauca) as a major hub gene specific to earlywood formation. Reference profiling identified comprehensive, statistically robust coexpressed groups, revealing that modular organization underpins the evolutionary conservation of the transcriptome structure. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Clarity of objectives and working principles enhances the success of biomimetic programs.

PubMed

Wolff, Jonas O; Wells, David; Reid, Chris R; Blamires, Sean J

2017-09-26

Biomimetics, the transfer of functional principles from living systems into product designs, is increasingly being utilized by engineers. Nevertheless, recurring problems must be overcome if it is to avoid becoming a short-lived fad. Here we assess the efficiency and suitability of methods typically employed by examining three flagship examples of biomimetic design approaches from different disciplines: (1) the creation of gecko-inspired adhesives; (2) the synthesis of spider silk, and (3) the derivation of computer algorithms from natural self-organizing systems. We find that identification of the elemental working principles is the most crucial step in the biomimetic design process. It bears the highest risk of failure (e.g. losing the target function) due to false assumptions about the working principle. Common problems that hamper successful implementation are: (i) a discrepancy between biological functions and the desired properties of the product, (ii) uncertainty about objectives and applications, (iii) inherent limits in methodologies, and (iv) false assumptions about the biology of the models. Projects that aim for multi-functional products are particularly challenging to accomplish. We suggest a simplification, modularisation and specification of objectives, and a critical assessment of the suitability of the model. Comparative analyses, experimental manipulation, and numerical simulations followed by tests of artificial models have led to the successful extraction of working principles. A searchable database of biological systems would optimize the choice of a model system in top-down approaches that start at an engineering problem. Only when biomimetic projects become more predictable will there be wider acceptance of biomimetics as an innovative problem-solving tool among engineers and industry.

Biofragments: An Approach towards Predicting Protein Function Using Biologically Related Fragments and its Application to Mycobacterium tuberculosis CYP126

PubMed Central

Hudson, Sean A; Mashalidis, Ellene H; Bender, Andreas; McLean, Kirsty J; Munro, Andrew W; Abell, Chris

2014-01-01

We present a novel fragment-based approach that tackles some of the challenges for chemical biology of predicting protein function. The general approach, which we have termed biofragments, comprises two key stages. First, a biologically relevant fragment library (biofragment library) can be designed and constructed from known sets of substrate-like ligands for a protein class of interest. Second, the library can be screened for binding to a novel putative ligand-binding protein from the same or similar class, and the characterization of hits provides insight into the basis of ligand recognition, selectivity, and function at the substrate level. As a proof-of-concept, we applied the biofragments approach to the functionally uncharacterized Mycobacterium tuberculosis (Mtb) cytochrome P450 isoform, CYP126. This led to the development of a tailored CYP biofragment library with notable 3D characteristics and a significantly higher screening hit rate (14 %) than standard drug-like fragment libraries screened previously against Mtb CYP121 and 125 (4 % and 1 %, respectively). Biofragment hits were identified that make both substrate-like type-I and inhibitor-like type-II interactions with CYP126. A chemical-fingerprint-based substrate model was built from the hits and used to search a virtual TB metabolome, which led to the discovery that CYP126 has a strong preference for the recognition of aromatics and substrate-like type-I binding of chlorophenol moieties within the active site near the heme. Future catalytic analyses will be focused on assessing CYP126 for potential substrate oxidative dehalogenation. PMID:24677424

Detecting uber-operons in prokaryotic genomes.

PubMed

Che, Dongsheng; Li, Guojun; Mao, Fenglou; Wu, Hongwei; Xu, Ying

2006-01-01

We present a study on computational identification of uber-operons in a prokaryotic genome, each of which represents a group of operons that are evolutionarily or functionally associated through operons in other (reference) genomes. Uber-operons represent a rich set of footprints of operon evolution, whose full utilization could lead to new and more powerful tools for elucidation of biological pathways and networks than what operons have provided, and a better understanding of prokaryotic genome structures and evolution. Our prediction algorithm predicts uber-operons through identifying groups of functionally or transcriptionally related operons, whose gene sets are conserved across the target and multiple reference genomes. Using this algorithm, we have predicted uber-operons for each of a group of 91 genomes, using the other 90 genomes as references. In particular, we predicted 158 uber-operons in Escherichia coli K12 covering 1830 genes, and found that many of the uber-operons correspond to parts of known regulons or biological pathways or are involved in highly related biological processes based on their Gene Ontology (GO) assignments. For some of the predicted uber-operons that are not parts of known regulons or pathways, our analyses indicate that their genes are highly likely to work together in the same biological processes, suggesting the possibility of new regulons and pathways. We believe that our uber-operon prediction provides a highly useful capability and a rich information source for elucidation of complex biological processes, such as pathways in microbes. All the prediction results are available at our Uber-Operon Database: http://csbl.bmb.uga.edu/uber, the first of its kind.

Detecting uber-operons in prokaryotic genomes

PubMed Central

Che, Dongsheng; Li, Guojun; Mao, Fenglou; Wu, Hongwei; Xu, Ying

2006-01-01

We present a study on computational identification of uber-operons in a prokaryotic genome, each of which represents a group of operons that are evolutionarily or functionally associated through operons in other (reference) genomes. Uber-operons represent a rich set of footprints of operon evolution, whose full utilization could lead to new and more powerful tools for elucidation of biological pathways and networks than what operons have provided, and a better understanding of prokaryotic genome structures and evolution. Our prediction algorithm predicts uber-operons through identifying groups of functionally or transcriptionally related operons, whose gene sets are conserved across the target and multiple reference genomes. Using this algorithm, we have predicted uber-operons for each of a group of 91 genomes, using the other 90 genomes as references. In particular, we predicted 158 uber-operons in Escherichia coli K12 covering 1830 genes, and found that many of the uber-operons correspond to parts of known regulons or biological pathways or are involved in highly related biological processes based on their Gene Ontology (GO) assignments. For some of the predicted uber-operons that are not parts of known regulons or pathways, our analyses indicate that their genes are highly likely to work together in the same biological processes, suggesting the possibility of new regulons and pathways. We believe that our uber-operon prediction provides a highly useful capability and a rich information source for elucidation of complex biological processes, such as pathways in microbes. All the prediction results are available at our Uber-Operon Database: , the first of its kind. PMID:16682449

Radiation Quality Effects on Transcriptome Profiles in 3-D Cultures After Charged Particle Irradiation

NASA Technical Reports Server (NTRS)

Patel, Zarana S.; Kidane, Yared H.; Huff, Janice L.

2014-01-01

In this work, we evaluated the differential effects of low- and high-LET radiation on 3-D organotypic cultures in order to investigate radiation quality impacts on gene expression and cellular responses. Current risk models for assessment of space radiation-induced cancer have large uncertainties because the models for adverse health effects following radiation exposure are founded on epidemiological analyses of human populations exposed to low-LET radiation. Reducing these uncertainties requires new knowledge on the fundamental differences in biological responses (the so-called radiation quality effects) triggered by heavy ion particle radiation versus low-LET radiation associated with Earth-based exposures. In order to better quantify these radiation quality effects in biological systems, we are utilizing novel 3-D organotypic human tissue models for space radiation research. These models hold promise for risk assessment as they provide a format for study of human cells within a realistic tissue framework, thereby bridging the gap between 2-D monolayer culture and animal models for risk extrapolation to humans. To identify biological pathway signatures unique to heavy ion particle exposure, functional gene set enrichment analysis (GSEA) was used with whole transcriptome profiling. GSEA has been used extensively as a method to garner biological information in a variety of model systems but has not been commonly used to analyze radiation effects. It is a powerful approach for assessing the functional significance of radiation quality-dependent changes from datasets where the changes are subtle but broad, and where single gene based analysis using rankings of fold-change may not reveal important biological information.

Condensins: universal organizers of chromosomes with diverse functions

PubMed Central

Hirano, Tatsuya

2012-01-01

Condensins are multisubunit protein complexes that play a fundamental role in the structural and functional organization of chromosomes in the three domains of life. Most eukaryotic species have two different types of condensin complexes, known as condensins I and II, that fulfill nonoverlapping functions and are subjected to differential regulation during mitosis and meiosis. Recent studies revealed that the two complexes contribute to a wide variety of interphase chromosome functions, such as gene regulation, recombination, and repair. Also emerging are their cell type- and tissue-specific functions and relevance to human disease. Biochemical and structural analyses of eukaryotic and bacterial condensins steadily uncover the mechanisms of action of this class of highly sophisticated molecular machines. Future studies on condensins will not only enhance our understanding of chromosome architecture and dynamics, but also help address a previously underappreciated yet profound set of questions in chromosome biology. PMID:22855829

Exosomes and Homeostatic Synaptic Plasticity Are Linked to Each other and to Huntington's, Parkinson's, and Other Neurodegenerative Diseases by Database-Enabled Analyses of Comprehensively Curated Datasets

PubMed Central

Wang, James K. T.; Langfelder, Peter; Horvath, Steve; Palazzolo, Michael J.

2017-01-01

Huntington's disease (HD) is a progressive and autosomal dominant neurodegeneration caused by CAG expansion in the huntingtin gene (HTT), but the pathophysiological mechanism of mutant HTT (mHTT) remains unclear. To study HD using systems biological methodologies on all published data, we undertook the first comprehensive curation of two key PubMed HD datasets: perturbation genes that impact mHTT-driven endpoints and therefore are putatively linked causally to pathogenic mechanisms, and the protein interactome of HTT that reflects its biology. We perused PubMed articles containing co-citation of gene IDs and MeSH terms of interest to generate mechanistic gene sets for iterative enrichment analyses and rank ordering. The HD Perturbation database of 1,218 genes highly overlaps the HTT Interactome of 1,619 genes, suggesting links between normal HTT biology and mHTT pathology. These two HD datasets are enriched for protein networks of key genes underlying two mechanisms not previously implicated in HD nor in each other: exosome synaptic functions and homeostatic synaptic plasticity. Moreover, proteins, possibly including HTT, and miRNA detected in exosomes from a wide variety of sources also highly overlap the HD datasets, suggesting both mechanistic and biomarker links. Finally, the HTT Interactome highly intersects protein networks of pathogenic genes underlying Parkinson's, Alzheimer's and eight non-HD polyglutamine diseases, ALS, and spinal muscular atrophy. These protein networks in turn highly overlap the exosome and homeostatic synaptic plasticity gene sets. Thus, we hypothesize that HTT and other neurodegeneration pathogenic genes form a large interlocking protein network involved in exosome and homeostatic synaptic functions, particularly where the two mechanisms intersect. Mutant pathogenic proteins cause dysfunctions at distinct points in this network, each altering the two mechanisms in specific fashion that contributes to distinct disease pathologies, depending on the gene mutation and the cellular and biological context. This protein network is rich with drug targets, and exosomes may provide disease biomarkers, thus enabling drug discovery. All the curated datasets are made available for other investigators. Elucidating the roles of pathogenic neurodegeneration genes in exosome and homeostatic synaptic functions may provide a unifying framework for the age-dependent, progressive and tissue selective nature of multiple neurodegenerative diseases. PMID:28611571

Exosomes and Homeostatic Synaptic Plasticity Are Linked to Each other and to Huntington's, Parkinson's, and Other Neurodegenerative Diseases by Database-Enabled Analyses of Comprehensively Curated Datasets.

PubMed

Wang, James K T; Langfelder, Peter; Horvath, Steve; Palazzolo, Michael J

2017-01-01

Huntington's disease (HD) is a progressive and autosomal dominant neurodegeneration caused by CAG expansion in the huntingtin gene ( HTT ), but the pathophysiological mechanism of mutant HTT (mHTT) remains unclear. To study HD using systems biological methodologies on all published data, we undertook the first comprehensive curation of two key PubMed HD datasets: perturbation genes that impact mHTT-driven endpoints and therefore are putatively linked causally to pathogenic mechanisms, and the protein interactome of HTT that reflects its biology. We perused PubMed articles containing co-citation of gene IDs and MeSH terms of interest to generate mechanistic gene sets for iterative enrichment analyses and rank ordering. The HD Perturbation database of 1,218 genes highly overlaps the HTT Interactome of 1,619 genes, suggesting links between normal HTT biology and mHTT pathology. These two HD datasets are enriched for protein networks of key genes underlying two mechanisms not previously implicated in HD nor in each other: exosome synaptic functions and homeostatic synaptic plasticity. Moreover, proteins, possibly including HTT, and miRNA detected in exosomes from a wide variety of sources also highly overlap the HD datasets, suggesting both mechanistic and biomarker links. Finally, the HTT Interactome highly intersects protein networks of pathogenic genes underlying Parkinson's, Alzheimer's and eight non-HD polyglutamine diseases, ALS, and spinal muscular atrophy. These protein networks in turn highly overlap the exosome and homeostatic synaptic plasticity gene sets. Thus, we hypothesize that HTT and other neurodegeneration pathogenic genes form a large interlocking protein network involved in exosome and homeostatic synaptic functions, particularly where the two mechanisms intersect. Mutant pathogenic proteins cause dysfunctions at distinct points in this network, each altering the two mechanisms in specific fashion that contributes to distinct disease pathologies, depending on the gene mutation and the cellular and biological context. This protein network is rich with drug targets, and exosomes may provide disease biomarkers, thus enabling drug discovery. All the curated datasets are made available for other investigators. Elucidating the roles of pathogenic neurodegeneration genes in exosome and homeostatic synaptic functions may provide a unifying framework for the age-dependent, progressive and tissue selective nature of multiple neurodegenerative diseases.

A combined computational-experimental analyses of selected metabolic enzymes in Pseudomonas species.

PubMed

Perumal, Deepak; Lim, Chu Sing; Chow, Vincent T K; Sakharkar, Kishore R; Sakharkar, Meena K

2008-09-10

Comparative genomic analysis has revolutionized our ability to predict the metabolic subsystems that occur in newly sequenced genomes, and to explore the functional roles of the set of genes within each subsystem. These computational predictions can considerably reduce the volume of experimental studies required to assess basic metabolic properties of multiple bacterial species. However, experimental validations are still required to resolve the apparent inconsistencies in the predictions by multiple resources. Here, we present combined computational-experimental analyses on eight completely sequenced Pseudomonas species. Comparative pathway analyses reveal that several pathways within the Pseudomonas species show high plasticity and versatility. Potential bypasses in 11 metabolic pathways were identified. We further confirmed the presence of the enzyme O-acetyl homoserine (thiol) lyase (EC: 2.5.1.49) in P. syringae pv. tomato that revealed inconsistent annotations in KEGG and in the recently published SYSTOMONAS database. These analyses connect and integrate systematic data generation, computational data interpretation, and experimental validation and represent a synergistic and powerful means for conducting biological research.

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

A Systems Biology Approach to Synovial Joint Lubrication in Health, Injury, and Disease

PubMed Central

Hui, Alexander Y.; McCarty, William J.; Masuda, Koichi; Firestein, Gary S.; Sah, Robert L.

2013-01-01

The synovial joint contains synovial fluid (SF) within a cavity bounded by articular cartilage and synovium. SF is a viscous fluid that has lubrication, metabolic, and regulatory functions within synovial joints. SF contains lubricant molecules, including proteoglycan-4 and hyaluronan. SF is an ultrafiltrate of plasma with secreted contributions from cell populations lining and within the synovial joint space, including chondrocytes and synoviocytes. Maintenance of normal SF lubricant composition and function are important for joint homeostasis. In osteoarthritis, rheumatoid arthritis, and joint injury, changes in lubricant composition and function accompany alterations in the cytokine and growth factor environment and increased fluid and molecular transport through joint tissues. Thus, understanding the synovial joint lubrication system requires a multi-faceted study of the various parts of the synovial joint and their interactions. Systems biology approaches at multiple scales are being used to describe the molecular, cellular, and tissue components and their interactions that comprise the functioning synovial joint. Analyses of the transcriptome and proteome of SF, cartilage, and synovium suggest that particular molecules and pathways play important roles in joint homeostasis and disease. Such information may be integrated with physicochemical tissue descriptions to construct integrative models of the synovial joint that ultimately may explain maintenance of health, recovery from injury, or development and progression of arthritis. PMID:21826801

The effect of temperature on the functional response of Phytoseiulus persimilis (Acari: Phytoseiidae).

PubMed

Skirvin, David J; Fenlon, John S

2003-01-01

Environmental variables, such as temperature, are important in determining the efficiency of biological control in ornamental crops. This paper examines the effect of temperature on the functional response of adult female Phytoseiulus persimilis to eggs of the spider mite, Tetranychus urticae. The functional response was determined using a new functional response assay technique with plant stems as an arena, rather than leaf discs. The use of plant stems allows the influence that plant structure has on predation to be incorporated into the assay. Control assays were also used (without predators) to estimate natural losses of prey. The data were analysed using a binomial model, with the use of Abbot's formula to correct for the losses in the controls. A combined equation to describe the effect of temperature and prey density on the predation rate of Phytoseiulus persimilis was derived. The results showed that more prey are eaten as the temperature increases from 15 degrees C to 25 degrees C, but the number of prey eaten then declines at 30 degrees C, although not to the levels seen at 20 degrees C. The implication of these results for biological control in ornamental crops, where the temperature can often exceed 30 degrees C, is discussed.

Identification and Characterization of Genomic Amplifications in Ovarian Serous Carcinoma

DTIC Science & Technology

2008-01-01

lower cost. As a result, we have analyzed more than 40 affinity purified ovarian serous tumors and our results demonstrated that CCNE1, Notch3 , Rsf-1...serous tumors. In addition, we have further characterized the biological functions of the two of the commonly amplified genes, Notch3 and Rsf-1, in...analyses, we have focused on two of the most frequently amplified regions, 11q13.2 (Rsf-1 locus) and 19p13 ( Notch3 locus), for detailed mapping and

Beware the black box: investigating the sensitivity of FEA simulations to modelling factors in comparative biomechanics.

PubMed

Walmsley, Christopher W; McCurry, Matthew R; Clausen, Phillip D; McHenry, Colin R

2013-01-01

Finite element analysis (FEA) is a computational technique of growing popularity in the field of comparative biomechanics, and is an easily accessible platform for form-function analyses of biological structures. However, its rapid evolution in recent years from a novel approach to common practice demands some scrutiny in regards to the validity of results and the appropriateness of assumptions inherent in setting up simulations. Both validation and sensitivity analyses remain unexplored in many comparative analyses, and assumptions considered to be 'reasonable' are often assumed to have little influence on the results and their interpretation. HERE WE REPORT AN EXTENSIVE SENSITIVITY ANALYSIS WHERE HIGH RESOLUTION FINITE ELEMENT (FE) MODELS OF MANDIBLES FROM SEVEN SPECIES OF CROCODILE WERE ANALYSED UNDER LOADS TYPICAL FOR COMPARATIVE ANALYSIS: biting, shaking, and twisting. Simulations explored the effect on both the absolute response and the interspecies pattern of results to variations in commonly used input parameters. Our sensitivity analysis focuses on assumptions relating to the selection of material properties (heterogeneous or homogeneous), scaling (standardising volume, surface area, or length), tooth position (front, mid, or back tooth engagement), and linear load case (type of loading for each feeding type). Our findings show that in a comparative context, FE models are far less sensitive to the selection of material property values and scaling to either volume or surface area than they are to those assumptions relating to the functional aspects of the simulation, such as tooth position and linear load case. Results show a complex interaction between simulation assumptions, depending on the combination of assumptions and the overall shape of each specimen. Keeping assumptions consistent between models in an analysis does not ensure that results can be generalised beyond the specific set of assumptions used. Logically, different comparative datasets would also be sensitive to identical simulation assumptions; hence, modelling assumptions should undergo rigorous selection. The accuracy of input data is paramount, and simulations should focus on taking biological context into account. Ideally, validation of simulations should be addressed; however, where validation is impossible or unfeasible, sensitivity analyses should be performed to identify which assumptions have the greatest influence upon the results.

Beware the black box: investigating the sensitivity of FEA simulations to modelling factors in comparative biomechanics

PubMed Central

McCurry, Matthew R.; Clausen, Phillip D.; McHenry, Colin R.

2013-01-01

Finite element analysis (FEA) is a computational technique of growing popularity in the field of comparative biomechanics, and is an easily accessible platform for form-function analyses of biological structures. However, its rapid evolution in recent years from a novel approach to common practice demands some scrutiny in regards to the validity of results and the appropriateness of assumptions inherent in setting up simulations. Both validation and sensitivity analyses remain unexplored in many comparative analyses, and assumptions considered to be ‘reasonable’ are often assumed to have little influence on the results and their interpretation. Here we report an extensive sensitivity analysis where high resolution finite element (FE) models of mandibles from seven species of crocodile were analysed under loads typical for comparative analysis: biting, shaking, and twisting. Simulations explored the effect on both the absolute response and the interspecies pattern of results to variations in commonly used input parameters. Our sensitivity analysis focuses on assumptions relating to the selection of material properties (heterogeneous or homogeneous), scaling (standardising volume, surface area, or length), tooth position (front, mid, or back tooth engagement), and linear load case (type of loading for each feeding type). Our findings show that in a comparative context, FE models are far less sensitive to the selection of material property values and scaling to either volume or surface area than they are to those assumptions relating to the functional aspects of the simulation, such as tooth position and linear load case. Results show a complex interaction between simulation assumptions, depending on the combination of assumptions and the overall shape of each specimen. Keeping assumptions consistent between models in an analysis does not ensure that results can be generalised beyond the specific set of assumptions used. Logically, different comparative datasets would also be sensitive to identical simulation assumptions; hence, modelling assumptions should undergo rigorous selection. The accuracy of input data is paramount, and simulations should focus on taking biological context into account. Ideally, validation of simulations should be addressed; however, where validation is impossible or unfeasible, sensitivity analyses should be performed to identify which assumptions have the greatest influence upon the results. PMID:24255817

Systems biology-based approaches toward understanding drought tolerance in food crops.

PubMed

Jogaiah, Sudisha; Govind, Sharathchandra Ramsandra; Tran, Lam-Son Phan

2013-03-01

Economically important crops, such as maize, wheat, rice, barley, and other food crops are affected by even small changes in water potential at important growth stages. Developing a comprehensive understanding of host response to drought requires a global view of the complex mechanisms involved. Research on drought tolerance has generally been conducted using discipline-specific approaches. However, plant stress response is complex and interlinked to a point where discipline-specific approaches do not give a complete global analysis of all the interlinked mechanisms. Systems biology perspective is needed to understand genome-scale networks required for building long-lasting drought resistance. Network maps have been constructed by integrating multiple functional genomics data with both model plants, such as Arabidopsis thaliana, Lotus japonicus, and Medicago truncatula, and various food crops, such as rice and soybean. Useful functional genomics data have been obtained from genome-wide comparative transcriptome and proteome analyses of drought responses from different crops. This integrative approach used by many groups has led to identification of commonly regulated signaling pathways and genes following exposure to drought. Combination of functional genomics and systems biology is very useful for comparative analysis of other food crops and has the ability to develop stable food systems worldwide. In addition, studying desiccation tolerance in resurrection plants will unravel how combination of molecular genetic and metabolic processes interacts to produce a resurrection phenotype. Systems biology-based approaches have helped in understanding how these individual factors and mechanisms (biochemical, molecular, and metabolic) "interact" spatially and temporally. Signaling network maps of such interactions are needed that can be used to design better engineering strategies for improving drought tolerance of important crop species.

Comprehensive analyses of tissue-specific networks with implications to psychiatric diseases

PubMed Central

Lin, Guan Ning; Corominas, Roser; Nam, Hyun-Jun; Urresti, Jorge; Iakoucheva, Lilia M.

2017-01-01

Recent advances in genome sequencing and “omics” technologies are opening new opportunities for improving diagnosis and treatment of human diseases. The precision medicine initiative in particular aims at developing individualized treatment options that take into account individual variability in genes and environment of each person. Systems biology approaches that group genes, transcripts and proteins into functionally meaningful networks will play crucial role in the future of personalized medicine. They will allow comparison of healthy and disease-affected tissues and organs from the same individual, as well as between healthy and disease-afflicted individuals. However, the field faces a multitude of challenges ranging from data integration to statistical and combinatorial issues in data analyses. This chapter describes computational approaches developed by us and the others to tackle challenges in tissue-specific network analyses, with the main focus on psychiatric diseases. PMID:28849569

Non-random mate choice in humans: insights from a genome scan.

PubMed

Laurent, R; Toupance, B; Chaix, R

2012-02-01

Little is known about the genetic factors influencing mate choice in humans. Still, there is evidence for non-random mate choice with respect to physical traits. In addition, some studies suggest that the Major Histocompatibility Complex may affect pair formation. Nowadays, the availability of high density genomic data sets gives the opportunity to scan the genome for signatures of non-random mate choice without prior assumptions on which genes may be involved, while taking into account socio-demographic factors. Here, we performed a genome scan to detect extreme patterns of similarity or dissimilarity among spouses throughout the genome in three populations of African, European American, and Mexican origins from the HapMap 3 database. Our analyses identified genes and biological functions that may affect pair formation in humans, including genes involved in skin appearance, morphogenesis, immunity and behaviour. We found little overlap between the three populations, suggesting that the biological functions potentially influencing mate choice are population specific, in other words are culturally driven. Moreover, whenever the same functional category of genes showed a significant signal in two populations, different genes were actually involved, which suggests the possibility of evolutionary convergences. © 2011 Blackwell Publishing Ltd.

Site-specific distribution of claudin-based paracellular channels with roles in biological fluid flow and metabolism.

PubMed

Tanaka, Hiroo; Tamura, Atsushi; Suzuki, Koya; Tsukita, Sachiko

2017-10-01

The claudins are a family of membrane proteins with at least 27 members in humans and mice. The extracellular regions of claudin proteins play essential roles in cell-cell adhesion and the paracellular barrier functions of tight junctions (TJs) in epithelial cell sheets. Furthermore, the extracellular regions of some claudins function as paracellular channels in the paracellular barrier that allow the selective passage of water, ions, and/or small organic solutes across the TJ in the extracellular space. Structural analyses have revealed a common framework of transmembrane, cytoplasmic, and extracellular regions among the claudin-based paracellular barriers and paracellular channels; however, differences in the claudins' extracellular regions, such as their charges and conformations, determine their properties. Among the biological systems that involve fluid flow and metabolism, it is noted that hepatic bile flow, renal Na + reabsorption, and intestinal nutrient absorption are dynamically regulated via site-specific distributions of paracellular channel-forming claudins in tissue. Here, we focus on how site-specific distributions of claudin-2- and claudin-15-based paracellular channels drive their organ-specific functions in the liver, kidney, and intestine. © 2017 New York Academy of Sciences.

Large-Scale Analysis Exploring Evolution of Catalytic Machineries and Mechanisms in Enzyme Superfamilies.

PubMed

Furnham, Nicholas; Dawson, Natalie L; Rahman, Syed A; Thornton, Janet M; Orengo, Christine A

2016-01-29

Enzymes, as biological catalysts, form the basis of all forms of life. How these proteins have evolved their functions remains a fundamental question in biology. Over 100 years of detailed biochemistry studies, combined with the large volumes of sequence and protein structural data now available, means that we are able to perform large-scale analyses to address this question. Using a range of computational tools and resources, we have compiled information on all experimentally annotated changes in enzyme function within 379 structurally defined protein domain superfamilies, linking the changes observed in functions during evolution to changes in reaction chemistry. Many superfamilies show changes in function at some level, although one function often dominates one superfamily. We use quantitative measures of changes in reaction chemistry to reveal the various types of chemical changes occurring during evolution and to exemplify these by detailed examples. Additionally, we use structural information of the enzymes active site to examine how different superfamilies have changed their catalytic machinery during evolution. Some superfamilies have changed the reactions they perform without changing catalytic machinery. In others, large changes of enzyme function, in terms of both overall chemistry and substrate specificity, have been brought about by significant changes in catalytic machinery. Interestingly, in some superfamilies, relatives perform similar functions but with different catalytic machineries. This analysis highlights characteristics of functional evolution across a wide range of superfamilies, providing insights that will be useful in predicting the function of uncharacterised sequences and the design of new synthetic enzymes. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Evaluation of methods of determining humic acids in nucleic acid samples for molecular biological analysis.

PubMed

Wang, Yong; Fujii, Takeshi

2011-01-01

It is important in molecular biological analyses to evaluate contamination of co-extracted humic acids in DNA/RNA extracted from soil. We compared the sensitivity of various methods for measurement of humic acids, and influences of DNA/RNA and proteins on the measurement. Considering the results, we give suggestions as to choice of methods for measurement of humic acids in molecular biological analyses.

TP Atlas: integration and dissemination of advances in Targeted Proteins Research Program (TPRP)-structural biology project phase II in Japan.

PubMed

Iwayanagi, Takao; Miyamoto, Sei; Konno, Takeshi; Mizutani, Hisashi; Hirai, Tomohiro; Shigemoto, Yasumasa; Gojobori, Takashi; Sugawara, Hideaki

2012-09-01

The Targeted Proteins Research Program (TPRP) promoted by the Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan is the phase II of structural biology project (2007-2011) following the Protein 3000 Project (2002-2006) in Japan. While the phase I Protein 3000 Project put partial emphasis on the construction and maintenance of pipelines for structural analyses, the TPRP is dedicated to revealing the structures and functions of the targeted proteins that have great importance in both basic research and industrial applications. To pursue this objective, 35 Targeted Proteins (TP) Projects selected in the three areas of fundamental biology, medicine and pharmacology, and food and environment are tightly collaborated with 10 Advanced Technology (AT) Projects in the four fields of protein production, structural analyses, chemical library and screening, and information platform. Here, the outlines and achievements of the 35 TP Projects are summarized in the system named TP Atlas. Progress in the diversified areas is described in the modules of Graphical Summary, General Summary, Tabular Summary, and Structure Gallery of the TP Atlas in the standard and unified format. Advances in TP Projects owing to novel technologies stemmed from AT Projects and collaborative research among TP Projects are illustrated as a hallmark of the Program. The TP Atlas can be accessed at http://net.genes.nig.ac.jp/tpatlas/index_e.html .

Microbial Communities and Functional Genes Associated with Soil Arsenic Contamination and the Rhizosphere of the Arsenic-Hyperaccumulating Plant Pteris vittata L. ▿ †

PubMed Central

Xiong, Jinbo; Wu, Liyou; Tu, Shuxin; Van Nostrand, Joy D.; He, Zhili; Zhou, Jizhong; Wang, Gejiao

2010-01-01

To understand how microbial communities and functional genes respond to arsenic contamination in the rhizosphere of Pteris vittata, five soil samples with different arsenic contamination levels were collected from the rhizosphere of P. vittata and nonrhizosphere areas and investigated by Biolog, geochemical, and functional gene microarray (GeoChip 3.0) analyses. Biolog analysis revealed that the uncontaminated soil harbored the greatest diversity of sole-carbon utilization abilities and that arsenic contamination decreased the metabolic diversity, while rhizosphere soils had higher metabolic diversities than did the nonrhizosphere soils. GeoChip 3.0 analysis showed low proportions of overlapping genes across the five soil samples (16.52% to 45.75%). The uncontaminated soil had a higher heterogeneity and more unique genes (48.09%) than did the arsenic-contaminated soils. Arsenic resistance, sulfur reduction, phosphorus utilization, and denitrification genes were remarkably distinct between P. vittata rhizosphere and nonrhizosphere soils, which provides evidence for a strong linkage among the level of arsenic contamination, the rhizosphere, and the functional gene distribution. Canonical correspondence analysis (CCA) revealed that arsenic is the main driver in reducing the soil functional gene diversity; however, organic matter and phosphorus also have significant effects on the soil microbial community structure. The results implied that rhizobacteria play an important role during soil arsenic uptake and hyperaccumulation processes of P. vittata. PMID:20833780

Evaluating the consistency of gene sets used in the analysis of bacterial gene expression data.

PubMed

Tintle, Nathan L; Sitarik, Alexandra; Boerema, Benjamin; Young, Kylie; Best, Aaron A; Dejongh, Matthew

2012-08-08

Statistical analyses of whole genome expression data require functional information about genes in order to yield meaningful biological conclusions. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) are common sources of functionally grouped gene sets. For bacteria, the SEED and MicrobesOnline provide alternative, complementary sources of gene sets. To date, no comprehensive evaluation of the data obtained from these resources has been performed. We define a series of gene set consistency metrics directly related to the most common classes of statistical analyses for gene expression data, and then perform a comprehensive analysis of 3581 Affymetrix® gene expression arrays across 17 diverse bacteria. We find that gene sets obtained from GO and KEGG demonstrate lower consistency than those obtained from the SEED and MicrobesOnline, regardless of gene set size. Despite the widespread use of GO and KEGG gene sets in bacterial gene expression data analysis, the SEED and MicrobesOnline provide more consistent sets for a wide variety of statistical analyses. Increased use of the SEED and MicrobesOnline gene sets in the analysis of bacterial gene expression data may improve statistical power and utility of expression data.

Evolution, expression analysis, and functional verification of Catharanthus roseus RLK1-like kinase (CrRLK1L) family proteins in pear (Pyrus bretchneideri).

PubMed

Kou, Xiaobing; Qi, Kaijie; Qiao, Xin; Yin, Hao; Liu, Xing; Zhang, Shaoling; Wu, Juyou

2017-07-01

The Catharanthus roseus RLK1-like kinase (CrRLK1L) family is involved in multiple processes during plant growth. However, little is known about CrRLK1L in the wood of the pear fruit tree Pyrus bretchneideri. In this study, 26 CrRLK1L gene members were identified in pear and were grouped into six subfamilies according to phylogenetic analyses. Evolutionary analysis indicated that recent whole genome duplication (WGD) and dispersed gene duplications may contribute to the expansion of the CrRLK1L gene family in pear. Moreover, tissue-specific expression analyses suggested that CrRLK1Ls are involved in the development of various pear tissues. Subsequent qRT-PCR analyses indicated that CrRLK1Ls might play important roles in pollen tube growth. Finally, experiments with antisense oligonucleotides (ASO) demonstrated that PbrCrRLK1L26 have functions in pollen tube elongation and that PbrCrRLK1L3 regulates pollen tube rupture. These results will be useful for elaborating the biological roles of CrRLK1Ls in pear growth and development. Copyright © 2017. Published by Elsevier Inc.

Predicting 3D structure and stability of RNA pseudoknots in monovalent and divalent ion solutions.

PubMed

Shi, Ya-Zhou; Jin, Lei; Feng, Chen-Jie; Tan, Ya-Lan; Tan, Zhi-Jie

2018-06-01

RNA pseudoknots are a kind of minimal RNA tertiary structural motifs, and their three-dimensional (3D) structures and stability play essential roles in a variety of biological functions. Therefore, to predict 3D structures and stability of RNA pseudoknots is essential for understanding their functions. In the work, we employed our previously developed coarse-grained model with implicit salt to make extensive predictions and comprehensive analyses on the 3D structures and stability for RNA pseudoknots in monovalent/divalent ion solutions. The comparisons with available experimental data show that our model can successfully predict the 3D structures of RNA pseudoknots from their sequences, and can also make reliable predictions for the stability of RNA pseudoknots with different lengths and sequences over a wide range of monovalent/divalent ion concentrations. Furthermore, we made comprehensive analyses on the unfolding pathway for various RNA pseudoknots in ion solutions. Our analyses for extensive pseudokonts and the wide range of monovalent/divalent ion concentrations verify that the unfolding pathway of RNA pseudoknots is mainly dependent on the relative stability of unfolded intermediate states, and show that the unfolding pathway of RNA pseudoknots can be significantly modulated by their sequences and solution ion conditions.

Functional analysis of a viroid RNA motif mediating cell-to-cell movement in Nicotiana benthamiana.

PubMed

Jiang, Dongmei; Wang, Meng; Li, Shifang

2017-01-01

Cell-to-cell trafficking through different cellular layers is a key process for various RNAs including those of plant viruses and viroids, but the regulatory mechanisms involved are still not fully elucidated and good model systems are important. Here, we analyse the function of a simple RNA motif (termed 'loop19') in potato spindle tuber viroid (PSTVd) which is required for trafficking in Nicotiana benthamiana leaves. Northern blotting, reverse transcriptase PCR (RT-PCR) and in situ hybridization analyses demonstrated that unlike wild-type PSTVd, which was present in the nuclei in all cell types, the trafficking-defective loop19 mutants were visible only in the nuclei of upper epidermal and palisade mesophyll cells, which shows that PSTVd loop19 plays a role in mediating RNA trafficking from palisade to spongy mesophyll cells in N.benthamiana leaves. Our findings and approaches have broad implications for studying the RNA motifs mediating trafficking of RNAs across specific cellular boundaries in other biological systems.

The National Microbial Pathogen Database Resource (NMPDR): a genomics platform based on subsystem annotation.

PubMed

McNeil, Leslie Klis; Reich, Claudia; Aziz, Ramy K; Bartels, Daniela; Cohoon, Matthew; Disz, Terry; Edwards, Robert A; Gerdes, Svetlana; Hwang, Kaitlyn; Kubal, Michael; Margaryan, Gohar Rem; Meyer, Folker; Mihalo, William; Olsen, Gary J; Olson, Robert; Osterman, Andrei; Paarmann, Daniel; Paczian, Tobias; Parrello, Bruce; Pusch, Gordon D; Rodionov, Dmitry A; Shi, Xinghua; Vassieva, Olga; Vonstein, Veronika; Zagnitko, Olga; Xia, Fangfang; Zinner, Jenifer; Overbeek, Ross; Stevens, Rick

2007-01-01

The National Microbial Pathogen Data Resource (NMPDR) (http://www.nmpdr.org) is a National Institute of Allergy and Infections Disease (NIAID)-funded Bioinformatics Resource Center that supports research in selected Category B pathogens. NMPDR contains the complete genomes of approximately 50 strains of pathogenic bacteria that are the focus of our curators, as well as >400 other genomes that provide a broad context for comparative analysis across the three phylogenetic Domains. NMPDR integrates complete, public genomes with expertly curated biological subsystems to provide the most consistent genome annotations. Subsystems are sets of functional roles related by a biologically meaningful organizing principle, which are built over large collections of genomes; they provide researchers with consistent functional assignments in a biologically structured context. Investigators can browse subsystems and reactions to develop accurate reconstructions of the metabolic networks of any sequenced organism. NMPDR provides a comprehensive bioinformatics platform, with tools and viewers for genome analysis. Results of precomputed gene clustering analyses can be retrieved in tabular or graphic format with one-click tools. NMPDR tools include Signature Genes, which finds the set of genes in common or that differentiates two groups of organisms. Essentiality data collated from genome-wide studies have been curated. Drug target identification and high-throughput, in silico, compound screening are in development.

What are they thinking? Automated analysis of student writing about acid-base chemistry in introductory biology.

PubMed

Haudek, Kevin C; Prevost, Luanna B; Moscarella, Rosa A; Merrill, John; Urban-Lurain, Mark

2012-01-01

Students' writing can provide better insight into their thinking than can multiple-choice questions. However, resource constraints often prevent faculty from using writing assessments in large undergraduate science courses. We investigated the use of computer software to analyze student writing and to uncover student ideas about chemistry in an introductory biology course. Students were asked to predict acid-base behavior of biological functional groups and to explain their answers. Student explanations were rated by two independent raters. Responses were also analyzed using SPSS Text Analysis for Surveys and a custom library of science-related terms and lexical categories relevant to the assessment item. These analyses revealed conceptual connections made by students, student difficulties explaining these topics, and the heterogeneity of student ideas. We validated the lexical analysis by correlating student interviews with the lexical analysis. We used discriminant analysis to create classification functions that identified seven key lexical categories that predict expert scoring (interrater reliability with experts = 0.899). This study suggests that computerized lexical analysis may be useful for automatically categorizing large numbers of student open-ended responses. Lexical analysis provides instructors unique insights into student thinking and a whole-class perspective that are difficult to obtain from multiple-choice questions or reading individual responses.

Functionalized Polymeric Membrane with Enhanced Mechanical and Biological Properties to Control the Degradation of Magnesium Alloy.

PubMed

Wong, Hoi Man; Zhao, Ying; Leung, Frankie K L; Xi, Tingfei; Zhang, Zhixiong; Zheng, Yufeng; Wu, Shuilin; Luk, Keith D K; Cheung, Kenneth M C; Chu, Paul K; Yeung, Kelvin W K

2017-04-01

To achieve enhanced biological response and controlled degradation of magnesium alloy, a modified biodegradable polymer coating called polycaprolactone (PCL) is fabricated by a thermal approach in which the heat treatment neither alters the chemical composition of the PCL membrane nor the rate of magnesium ion release, pH value, or weight loss, compared with the untreated sample. The changes in the crystallinity, hydrophilicity, and oxygen content of heat-treated PCL coating not only improve the mechanical adhesion strength between the coating and magnesium substrate but also enhance the biological properties. Moreover, the thermally modified sample can lead to higher spreading and elongation of osteoblasts, due to the enhanced hydrophilicity and CO to CO functional group ratio. In the analyses of microcomputed tomography from one to four weeks postoperation, the total volume of new bone formation on the heat-treated sample is 10%-35% and 70%-90% higher than that of the untreated and uncoated controls, respectively. Surprisingly, the indentation modulus of the newly formed bone adjacent to the heat-treated sample is ≈20% higher than that of both controls. These promising results reveal the clinical potential of the modified PCL coating on magnesium alloy in orthopedic applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

What Are They Thinking? Automated Analysis of Student Writing about Acid–Base Chemistry in Introductory Biology

PubMed Central

Haudek, Kevin C.; Prevost, Luanna B.; Moscarella, Rosa A.; Merrill, John; Urban-Lurain, Mark

2012-01-01

Students’ writing can provide better insight into their thinking than can multiple-choice questions. However, resource constraints often prevent faculty from using writing assessments in large undergraduate science courses. We investigated the use of computer software to analyze student writing and to uncover student ideas about chemistry in an introductory biology course. Students were asked to predict acid–base behavior of biological functional groups and to explain their answers. Student explanations were rated by two independent raters. Responses were also analyzed using SPSS Text Analysis for Surveys and a custom library of science-related terms and lexical categories relevant to the assessment item. These analyses revealed conceptual connections made by students, student difficulties explaining these topics, and the heterogeneity of student ideas. We validated the lexical analysis by correlating student interviews with the lexical analysis. We used discriminant analysis to create classification functions that identified seven key lexical categories that predict expert scoring (interrater reliability with experts = 0.899). This study suggests that computerized lexical analysis may be useful for automatically categorizing large numbers of student open-ended responses. Lexical analysis provides instructors unique insights into student thinking and a whole-class perspective that are difficult to obtain from multiple-choice questions or reading individual responses. PMID:22949425

BMDExpress Data Viewer: A Visualization Tool to Analyze ...

EPA Pesticide Factsheets

Regulatory agencies increasingly apply benchmark dose (BMD) modeling to determine points of departure in human risk assessments. BMDExpress applies BMD modeling to transcriptomics datasets and groups genes to biological processes and pathways for rapid assessment of doses at which biological perturbations occur. However, graphing and analytical capabilities within BMDExpress are limited, and the analysis of output files is challenging. We developed a web-based application, BMDExpress Data Viewer, for visualization and graphical analyses of BMDExpress output files. The software application consists of two main components: ‘Summary Visualization Tools’ and ‘Dataset Exploratory Tools’. We demonstrate through two case studies that the ‘Summary Visualization Tools’ can be used to examine and assess the distributions of probe and pathway BMD outputs, as well as derive a potential regulatory BMD through the modes or means of the distributions. The ‘Functional Enrichment Analysis’ tool presents biological processes in a two-dimensional bubble chart view. By applying filters of pathway enrichment p-value and minimum number of significant genes, we showed that the Functional Enrichment Analysis tool can be applied to select pathways that are potentially sensitive to chemical perturbations. The ‘Multiple Dataset Comparison’ tool enables comparison of BMDs across multiple experiments (e.g., across time points, tissues, or organisms, etc.). The ‘BMDL-BM

Demographic factors, childhood maltreatment and psychological functioning among university students' in Ghana: A retrospective study.

PubMed

Adjorlolo, Samuel; Adu-Poku, Sarah; Andoh-Arthur, Johnny; Botchway, Irene; Mlyakado, Budeba Petro

2017-12-01

This study retrospectively investigates the influence of child (i.e., gender), care-giver (e.g., who grew up with), household size (i.e., number of siblings grew up with) and community (i.e., rural versus urban) factors on childhood maltreatment, as well as the impacts of maltreatment on psychological functioning. A cross-sectional survey and self-report methodology is used to gather data from 300 students of the University of Ghana. The results show that being a male, growing up in rural areas, living with more than 3 siblings in the same household and being raised by both biological parents have significant main effects on childhood maltreatment. Analyses of the interaction effects show that living with more than 5 siblings in a rural household with "other" parents (i.e., non-biological parents) has a significant effect on physical abuse. Furthermore, males from rural households consisting of more than 3 siblings and who did not grow up with both biological parents endorsed significantly more physical abuse and physical neglect, compared with the females. With respect to the psychological outcome, childhood maltreatment significantly predicts and account for significant variance in depression (34%), self-efficacy (18%) and life satisfaction (22%). The findings and the implications of the study are briefly discussed. © 2015 International Union of Psychological Science.

The great importance of normalization of LC-MS data for highly-accurate non-targeted metabolomics.

PubMed

Mizuno, Hajime; Ueda, Kazuki; Kobayashi, Yuta; Tsuyama, Naohiro; Todoroki, Kenichiro; Min, Jun Zhe; Toyo'oka, Toshimasa

2017-01-01

The non-targeted metabolomics analysis of biological samples is very important to understand biological functions and diseases. LC combined with electrospray ionization-based MS has been a powerful tool and widely used for metabolomic analyses. However, the ionization efficiency of electrospray ionization fluctuates for various unexpected reasons such as matrix effects and intraday variations of the instrument performances. To remove these fluctuations, normalization methods have been developed. Such techniques include increasing the sensitivity, separating co-eluting components and normalizing the ionization efficiencies. Normalization techniques allow simultaneously correcting of the ionization efficiencies of the detected metabolite peaks and achieving quantitative non-targeted metabolomics. In this review paper, we focused on these normalization methods for non-targeted metabolomics by LC-MS. Copyright © 2016 John Wiley & Sons, Ltd.

Using Big Data to Discover Diagnostics and Therapeutics for Gastrointestinal and Liver Diseases

PubMed Central

Wooden, Benjamin; Goossens, Nicolas; Hoshida, Yujin; Friedman, Scott L.

2016-01-01

Technologies such as genome sequencing, gene expression profiling, proteomic and metabolomic analyses, electronic medical records, and patient-reported health information have produced large amounts of data, from various populations, cell types, and disorders (big data). However, these data must be integrated and analyzed if they are to produce models or concepts about physiologic function or mechanisms of pathogenesis. Many of these data are available to the public, allowing researchers anywhere to search for markers of specific biologic processes or therapeutic targets for specific diseases or patient types. We review recent advances in the fields of computational and systems biology, and highlight opportunities for researchers to use big data sets in the fields of gastroenterology and hepatology, to complement traditional means of diagnostic and therapeutic discovery. PMID:27773806

A conserved tryptophan within the WRDPLVDID domain of yeast Pah1 phosphatidate phosphatase is required for its in vivo function in lipid metabolism.

PubMed

Park, Yeonhee; Han, Gil-Soo; Carman, George M

2017-12-01

PAH1 -encoded phosphatidate phosphatase, which catalyzes the dephosphorylation of phosphatidate to produce diacylglycerol at the endoplasmic reticulum membrane, plays a major role in controlling the utilization of phosphatidate for the synthesis of triacylglycerol or membrane phospholipids. The conserved N-LIP and haloacid dehalogenase-like domains of Pah1 are required for phosphatidate phosphatase activity and the in vivo function of the enzyme. Its non-conserved regions, which are located between the conserved domains and at the C terminus, contain sites for phosphorylation by multiple protein kinases. Truncation analyses of the non-conserved regions showed that they are not essential for the catalytic activity of Pah1 and its physiological functions ( e.g. triacylglycerol synthesis). This analysis also revealed that the C-terminal region contains a previously unrecognized WRDPLVDID domain (residues 637-645) that is conserved in yeast, mice, and humans. The deletion of this domain had no effect on the catalytic activity of Pah1 but caused the loss of its in vivo function. Site-specific mutational analyses of the conserved residues within WRDPLVDID indicated that Trp-637 plays a crucial role in Pah1 function. This work also demonstrated that the catalytic activity of Pah1 is required but is not sufficient for its in vivo functions. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Foxa2, a novel protein partner of the tumour suppressor menin, is deregulated in mouse and human MEN1 glucagonomas.

PubMed

Bonnavion, Rémy; Teinturier, Romain; Gherardi, Samuele; Leteurtre, Emmanuelle; Yu, Run; Cordier-Bussat, Martine; Du, Rui; Pattou, François; Vantyghem, Marie-Christine; Bertolino, Philippe; Lu, Jieli; Zhang, Chang Xian

2017-05-01

Foxa2, known as one of the pioneer factors, plays a crucial role in islet development and endocrine functions. Its expression and biological functions are regulated by various factors, including, in particular, insulin and glucagon. However, its expression and biological role in adult pancreatic α-cells remain elusive. In the current study, we showed that Foxa2 was overexpressed in islets from α-cell-specific Men1 mutant mice, at both the transcriptional level and the protein level. More importantly, immunostaining analyses showed its prominent nuclear accumulation, specifically in α-cells, at a very early stage after Men1 disruption. Similar nuclear FOXA2 expression was also detected in a substantial proportion (12/19) of human multiple endocrine neoplasia type 1 (MEN1) glucagonomas. Interestingly, our data revealed an interaction between Foxa2 and menin encoded by the Men1 gene. Furthermore, using several approaches, we demonstrated the relevance of this interaction in the regulation of two tested Foxa2 target genes, including the autoregulation of the Foxa2 promoter by Foxa2 itself. The current study establishes menin, a novel protein partner of Foxa2, as a regulator of Foxa2, the biological functions of which extend beyond the pancreatic endocrine cells. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Molecular and comparative genetics of mental retardation.

PubMed Central

Inlow, Jennifer K; Restifo, Linda L

2004-01-01

Affecting 1-3% of the population, mental retardation (MR) poses significant challenges for clinicians and scientists. Understanding the biology of MR is complicated by the extraordinary heterogeneity of genetic MR disorders. Detailed analyses of >1000 Online Mendelian Inheritance in Man (OMIM) database entries and literature searches through September 2003 revealed 282 molecularly identified MR genes. We estimate that hundreds more MR genes remain to be identified. A novel test, in which we distributed unmapped MR disorders proportionately across the autosomes, failed to eliminate the well-known X-chromosome overrepresentation of MR genes and candidate genes. This evidence argues against ascertainment bias as the main cause of the skewed distribution. On the basis of a synthesis of clinical and laboratory data, we developed a biological functions classification scheme for MR genes. Metabolic pathways, signaling pathways, and transcription are the most common functions, but numerous other aspects of neuronal and glial biology are controlled by MR genes as well. Using protein sequence and domain-organization comparisons, we found a striking conservation of MR genes and genetic pathways across the approximately 700 million years that separate Homo sapiens and Drosophila melanogaster. Eighty-seven percent have one or more fruit fly homologs and 76% have at least one candidate functional ortholog. We propose that D. melanogaster can be used in a systematic manner to study MR and possibly to develop bioassays for therapeutic drug discovery. We selected 42 Drosophila orthologs as most likely to reveal molecular and cellular mechanisms of nervous system development or plasticity relevant to MR. PMID:15020472

What do Cells Really Look Like? An Inquiry into Students' Difficulties in Visualising a 3-D Biological Cell and Lessons for Pedagogy

NASA Astrophysics Data System (ADS)

Vijapurkar, Jyotsna; Kawalkar, Aisha; Nambiar, Priya

2014-04-01

In our explorations of students' concepts in an inquiry science classroom with grade 6 students from urban schools in India, we uncovered a variety of problems in their understanding of biological cells as structural and functional units of living organisms. In particular, we found not only that they visualised the cell as a two-dimensional (2-D) structure, instead of a closed three-dimensional (3-D) functional unit, but that they had a strong resistance to changing their 2-D conception to a 3-D one. Based on analyses of students' oral as well as written descriptions of cells in the classroom, and of models they made of the cell, we were able to identify the causes of students' difficulties in correctly visualising the cell. These insights helped us design a pedagogy involving guided discussions and activities that challenges students' 2-D conceptions of the cell. The activities entail very simple, low-cost, easily doable techniques to help students visualise the cell and to understand that it would not be able to function if its structure were 2-D. We also present the results of our investigations of conceptions of grade 7 students and biology undergraduates, revealing that the incorrect 2-D mental model can persist right up to the college level if it is not explicitly addressed. The classroom interactions described in this study illustrate how students' ideas can be probed and addressed in the classroom using pedagogical action research.

What is bioinformatics? A proposed definition and overview of the field.

PubMed

Luscombe, N M; Greenbaum, D; Gerstein, M

2001-01-01

The recent flood of data from genome sequences and functional genomics has given rise to new field, bioinformatics, which combines elements of biology and computer science. Here we propose a definition for this new field and review some of the research that is being pursued, particularly in relation to transcriptional regulatory systems. Our definition is as follows: Bioinformatics is conceptualizing biology in terms of macromolecules (in the sense of physical-chemistry) and then applying "informatics" techniques (derived from disciplines such as applied maths, computer science, and statistics) to understand and organize the information associated with these molecules, on a large-scale. Analyses in bioinformatics predominantly focus on three types of large datasets available in molecular biology: macromolecular structures, genome sequences, and the results of functional genomics experiments (e.g. expression data). Additional information includes the text of scientific papers and "relationship data" from metabolic pathways, taxonomy trees, and protein-protein interaction networks. Bioinformatics employs a wide range of computational techniques including sequence and structural alignment, database design and data mining, macromolecular geometry, phylogenetic tree construction, prediction of protein structure and function, gene finding, and expression data clustering. The emphasis is on approaches integrating a variety of computational methods and heterogeneous data sources. Finally, bioinformatics is a practical discipline. We survey some representative applications, such as finding homologues, designing drugs, and performing large-scale censuses. Additional information pertinent to the review is available over the web at http://bioinfo.mbb.yale.edu/what-is-it.

Low Frequency Variants, Collapsed Based on Biological Knowledge, Uncover Complexity of Population Stratification in 1000 Genomes Project Data

PubMed Central

Moore, Carrie B.; Wallace, John R.; Wolfe, Daniel J.; Frase, Alex T.; Pendergrass, Sarah A.; Weiss, Kenneth M.; Ritchie, Marylyn D.

2013-01-01

Analyses investigating low frequency variants have the potential for explaining additional genetic heritability of many complex human traits. However, the natural frequencies of rare variation between human populations strongly confound genetic analyses. We have applied a novel collapsing method to identify biological features with low frequency variant burden differences in thirteen populations sequenced by the 1000 Genomes Project. Our flexible collapsing tool utilizes expert biological knowledge from multiple publicly available database sources to direct feature selection. Variants were collapsed according to genetically driven features, such as evolutionary conserved regions, regulatory regions genes, and pathways. We have conducted an extensive comparison of low frequency variant burden differences (MAF<0.03) between populations from 1000 Genomes Project Phase I data. We found that on average 26.87% of gene bins, 35.47% of intergenic bins, 42.85% of pathway bins, 14.86% of ORegAnno regulatory bins, and 5.97% of evolutionary conserved regions show statistically significant differences in low frequency variant burden across populations from the 1000 Genomes Project. The proportion of bins with significant differences in low frequency burden depends on the ancestral similarity of the two populations compared and types of features tested. Even closely related populations had notable differences in low frequency burden, but fewer differences than populations from different continents. Furthermore, conserved or functionally relevant regions had fewer significant differences in low frequency burden than regions under less evolutionary constraint. This degree of low frequency variant differentiation across diverse populations and feature elements highlights the critical importance of considering population stratification in the new era of DNA sequencing and low frequency variant genomic analyses. PMID:24385916

Neural Stem Cells (NSCs) and Proteomics.

PubMed

Shoemaker, Lorelei D; Kornblum, Harley I

2016-02-01

Neural stem cells (NSCs) can self-renew and give rise to the major cell types of the CNS. Studies of NSCs include the investigation of primary, CNS-derived cells as well as animal and human embryonic stem cell (ESC)-derived and induced pluripotent stem cell (iPSC)-derived sources. NSCs provide a means with which to study normal neural development, neurodegeneration, and neurological disease and are clinically relevant sources for cellular repair to the damaged and diseased CNS. Proteomics studies of NSCs have the potential to delineate molecules and pathways critical for NSC biology and the means by which NSCs can participate in neural repair. In this review, we provide a background to NSC biology, including the means to obtain them and the caveats to these processes. We then focus on advances in the proteomic interrogation of NSCs. This includes the analysis of posttranslational modifications (PTMs); approaches to analyzing different proteomic compartments, such the secretome; as well as approaches to analyzing temporal differences in the proteome to elucidate mechanisms of differentiation. We also discuss some of the methods that will undoubtedly be useful in the investigation of NSCs but which have not yet been applied to the field. While many proteomics studies of NSCs have largely catalogued the proteome or posttranslational modifications of specific cellular states, without delving into specific functions, some have led to understandings of functional processes or identified markers that could not have been identified via other means. Many challenges remain in the field, including the precise identification and standardization of NSCs used for proteomic analyses, as well as how to translate fundamental proteomics studies to functional biology. The next level of investigation will require interdisciplinary approaches, combining the skills of those interested in the biochemistry of proteomics with those interested in modulating NSC function. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Activity-Based Profiling of a Physiologic Aglycone Library Reveals Sugar Acceptor Promiscuity of Family 1 UDP-Glucosyltransferases from Grape1[W

PubMed Central

Bönisch, Friedericke; Frotscher, Johanna; Stanitzek, Sarah; Rühl, Ernst; Wüst, Matthias; Bitz, Oliver; Schwab, Wilfried

2014-01-01

Monoterpenols serve various biological functions and accumulate in grape (Vitis vinifera), where a major fraction occurs as nonvolatile glycosides. We have screened the grape genome for sequences with similarity to terpene URIDINE DIPHOSPHATE GLYCOSYLTRANSFERASES (UGTs) from Arabidopsis (Arabidopsis thaliana). A ripening-related expression pattern was shown for three candidates by spatial and temporal expression analyses in five grape cultivars. Transcript accumulation correlated with the production of monoterpenyl β-d-glucosides in grape exocarp during ripening and was low in vegetative tissue. Targeted functional screening of the recombinant UGTs for their biological substrates was performed by activity-based metabolite profiling (ABMP) employing a physiologic library of aglycones built from glycosides isolated from grape. This approach led to the identification of two UDP-glucose:monoterpenol β-d-glucosyltransferases. Whereas VvGT14a glucosylated geraniol, R,S-citronellol, and nerol with similar efficiency, the three allelic forms VvGT15a, VvGT15b, and VvGT15c preferred geraniol over nerol. Kinetic resolution of R,S-citronellol and R,S-linalool was shown for VvGT15a and VvGT14a, respectively. ABMP revealed geraniol as the major biological substrate but also disclosed that these UGTs may add to the production of further glycoconjugates in planta. ABMP of aglycone libraries provides a versatile tool to uncover novel biologically relevant substrates of small-molecule glycosyltransferases that often show broad sugar acceptor promiscuity. PMID:25073706

Fort Collins Science Center- Policy Analysis and Science Assistance Branch : Integrating social, behavioral, economic and biological sciences

USGS Publications Warehouse

2010-01-01

The Fort Collins Science Center's Policy Analysis and Science Assistance (PASA) Branch is a team of approximately 22 scientists, technicians, and graduate student researchers. PASA provides unique capabilities in the U.S. Geological Survey by leading projects that integrate social, behavioral, economic, and biological analyses in the context of human-natural resource interactions. Resource planners, managers, and policymakers in the U.S. Departments of the Interior (DOI) and Agriculture (USDA), State and local agencies, as well as international agencies use information from PASA studies to make informed natural resource management and policy decisions. PASA scientists' primary functions are to conduct both theoretical and applied social science research, provide technical assistance, and offer training to advance performance in policy relevant research areas. Management and research issues associated with human-resource interactions typically occur in a unique context, involve difficult to access populations, require knowledge of both natural/biological science in addition to social science, and require the skill to integrate multiple science disciplines. In response to these difficult contexts, PASA researchers apply traditional and state-of-the-art social science methods drawing from the fields of sociology, demography, economics, political science, communications, social-psychology, and applied industrial organization psychology. Social science methods work in concert with our rangeland/agricultural management, wildlife, ecology, and biology capabilities. The goal of PASA's research is to enhance natural resource management, agency functions, policies, and decision-making. Our research is organized into four broad areas of study.

The Experimental Study of Bacterial Evolution and Its Implications for the Modern Synthesis of Evolutionary Biology.

PubMed

O'Malley, Maureen A

2018-06-01

Since the 1940s, microbiologists, biochemists and population geneticists have experimented with the genetic mechanisms of microorganisms in order to investigate evolutionary processes. These evolutionary studies of bacteria and other microorganisms gained some recognition from the standard-bearers of the modern synthesis of evolutionary biology, especially Theodosius Dobzhansky and Ledyard Stebbins. A further period of post-synthesis bacterial evolutionary research occurred between the 1950s and 1980s. These experimental analyses focused on the evolution of population and genetic structure, the adaptive gain of new functions, and the evolutionary consequences of competition dynamics. This large body of research aimed to make evolutionary theory testable and predictive, by giving it mechanistic underpinnings. Although evolutionary microbiologists promoted bacterial experiments as methodologically advantageous and a source of general insight into evolution, they also acknowledged the biological differences of bacteria. My historical overview concludes with reflections on what bacterial evolutionary research achieved in this period, and its implications for the still-developing modern synthesis.

Biology of Grapsus grapsus (L innaeus, 1758) (Brachyura, Grapsidae) in the Saint Peter and Saint Paul Archipelago, Equatorial Atlantic Ocean

NASA Astrophysics Data System (ADS)

Freire, A. S.; Pinheiro, M. A. A.; Karam-Silva, H.; Teschima, M. M.

2011-09-01

Eleven expeditions were undertaken to the Saint Peter and Saint Paul Archipelago to study the reproductive biology of Grapsus grapsus, providing additional information on limb mutilation and carapace colour. MATURE software was used to estimate morphological maturity, while gonadal analyses were conducted to estimate physiological maturity. The puberty moult took place at larger size in males (51.4 mm of carapace length) than in females (33.8 mm), while physiological maturity occurred at a similar size in males (38.4 mm) and in females (33.4 mm). Above 50 mm, the proportion of red males increased in the population, indicating that functional maturity is also related to colour pattern. Small habitat and high local population density contributed to the high rate of cannibalism. The low diversity of food items, absence of predators of large crabs and high geographic isolation are the determinants of unique behavioural and biological characteristics observed in the G. grapsus population.

Fast gene ontology based clustering for microarray experiments.

PubMed

Ovaska, Kristian; Laakso, Marko; Hautaniemi, Sampsa

2008-11-21

Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

Integrative Biological Analysis For Neuropsychopharmacology

PubMed Central

Emmett, Mark R; Kroes, Roger A; Moskal, Joseph R; Conrad, Charles A; Priebe, Waldemar; Laezza, Fernanda; Meyer-Baese, Anke; Nilsson, Carol L

2014-01-01

Although advances in psychotherapy have been made in recent years, drug discovery for brain diseases such as schizophrenia and mood disorders has stagnated. The need for new biomarkers and validated therapeutic targets in the field of neuropsychopharmacology is widely unmet. The brain is the most complex part of human anatomy from the standpoint of number and types of cells, their interconnections, and circuitry. To better meet patient needs, improved methods to approach brain studies by understanding functional networks that interact with the genome are being developed. The integrated biological approaches—proteomics, transcriptomics, metabolomics, and glycomics—have a strong record in several areas of biomedicine, including neurochemistry and neuro-oncology. Published applications of an integrated approach to projects of neurological, psychiatric, and pharmacological natures are still few but show promise to provide deep biological knowledge derived from cells, animal models, and clinical materials. Future studes that yield insights based on integrated analyses promise to deliver new therapeutic targets and biomarkers for personalized medicine. PMID:23800968

Mathematical methods for protein science

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

Hart, W.; Istrail, S.; Atkins, J.

1997-12-31

Understanding the structure and function of proteins is a fundamental endeavor in molecular biology. Currently, over 100,000 protein sequences have been determined by experimental methods. The three dimensional structure of the protein determines its function, but there are currently less than 4,000 structures known to atomic resolution. Accordingly, techniques to predict protein structure from sequence have an important role in aiding the understanding of the Genome and the effects of mutations in genetic disease. The authors describe current efforts at Sandia to better understand the structure of proteins through rigorous mathematical analyses of simple lattice models. The efforts have focusedmore » on two aspects of protein science: mathematical structure prediction, and inverse protein folding.« less

Transcriptome Analysis of PA Gain and Loss of Function Mutants.

PubMed

Marco, Francisco; Carrasco, Pedro

2018-01-01

Functional genomics has become a forefront methodology for plant science thanks to the widespread development of microarray technology. While technical difficulties associated with the process of obtaining raw expression data have been diminishing, allowing the appearance of tremendous amounts of transcriptome data in different databases, a common problem using "omic" technologies remains: the interpretation of these data and the inference of its biological meaning. In order to assist to this complex task, a wide variety of software tools have been developed. In this chapter we describe our current workflow of the application of some of these analyses. We have used it to compare the transcriptome of plants with differences in their polyamine levels.

Monte Carlo simulation of Hamaker nanospheres coated with dipolar particles

NASA Astrophysics Data System (ADS)

Meyra, Ariel G.; Zarragoicoechea, Guillermo J.; Kuz, Victor A.

2012-01-01

Parallel tempering Monte Carlo simulation is carried out in systems of N attractive Hamaker spheres dressed with n dipolar particles, able to move on the surface of the spheres. Different cluster configurations emerge for given values of the control parameters. Energy per sphere, pair distribution functions of spheres and dipoles as function of temperature, density, external electric field, and/or the angular orientation of dipoles are used to analyse the state of aggregation of the system. As a consequence of the non-central interaction, the model predicts complex structures like self-assembly of spheres by a double crown of dipoles. This interesting result could be of help in understanding some recent experiments in colloidal science and biology.

Genome-Wide Analyses and Functional Classification of Proline Repeat-Rich Proteins: Potential Role of eIF5A in Eukaryotic Evolution

PubMed Central

Mandal, Ajeet; Mandal, Swati; Park, Myung Hee

2014-01-01

The eukaryotic translation factor, eIF5A has been recently reported as a sequence-specific elongation factor that facilitates peptide bond formation at consecutive prolines in Saccharomyces cerevisiae, as its ortholog elongation factor P (EF-P) does in bacteria. We have searched the genome databases of 35 representative organisms from six kingdoms of life for PPP (Pro-Pro-Pro) and/or PPG (Pro-Pro-Gly)-encoding genes whose expression is expected to depend on eIF5A. We have made detailed analyses of proteome data of 5 selected species, Escherichia coli, Saccharomyces cerevisiae, Drosophila melanogaster, Mus musculus and Homo sapiens. The PPP and PPG motifs are low in the prokaryotic proteomes. However, their frequencies markedly increase with the biological complexity of eukaryotic organisms, and are higher in newly derived proteins than in those orthologous proteins commonly shared in all species. Ontology classifications of S. cerevisiae and human genes encoding the highest level of polyprolines reveal their strong association with several specific biological processes, including actin/cytoskeletal associated functions, RNA splicing/turnover, DNA binding/transcription and cell signaling. Previously reported phenotypic defects in actin polarity and mRNA decay of eIF5A mutant strains are consistent with the proposed role for eIF5A in the translation of the polyproline-containing proteins. Of all the amino acid tandem repeats (≥3 amino acids), only the proline repeat frequency correlates with functional complexity of the five organisms examined. Taken together, these findings suggest the importance of proline repeat-rich proteins and a potential role for eIF5A and its hypusine modification pathway in the course of eukaryotic evolution. PMID:25364902

Effective lock-in strategy for proteomic analysis of corona complexes bound to amino-free ligands of gold nanoparticles.

PubMed

Zhou, Mi; Tang, Min; Li, Shuiming; Peng, Li; Huang, Haojun; Fang, Qihua; Liu, Zhao; Xie, Peng; Li, Gao; Zhou, Jian

2018-06-21

For specific applications, gold nanoparticles (GNPs) are commonly functionalized with various biological ligands, including amino-free ligands such as amino acids, peptides, proteins, and nucleic acids. Upon entering a biological fluid, the protein corona that forms around GNPs can conceal the targeting ligands and sterically hinder the functional properties. The protein corona is routinely prepared by standard centrifugation or sucrose cushion centrifugation. However, such methodologies are not applicable to the exclusive analysis of a ligand-binding protein corona. In this study, we first proposed a lock-in strategy based on a combination of rapid crosslinking and stringent washing. Cysteine was used as a model of amino-free ligands and attached to GNPs. After corona formation in the human plasma, GNP cysteine and corona proteins were quickly fixed by 5 s of crosslinking with 7.5% formaldehyde. After stringent washing using SDS buffer with sonication, the cysteine-bound proteins were effectively separated from unbound proteins. Qualitative and quantitative analyses using a mass spectrometry-based proteomics approach indicated that the protein composition of the cysteine-binding corona from the new method was significantly different from the composition of the whole corona from the two conventional methods. Furthermore, network and formaldehyde-linked site analyses of cysteine-binding proteins provided useful information toward a better knowledge of the behavior of protein-ligand and protein-protein interactions. Collectively, our new strategy has the capability to particularly characterize the protein composition of a cysteine-binding corona. The presented methodology in principal provides a generic way to analyze a nanoparticle corona bound to amino-free ligands and has the potential to decipher corona-masked ligand functions.

Multi-level evaluation of Escherichia coli polyphosphate related mutants using global transcriptomic, proteomic and phenomic analyses.

PubMed

Varas, Macarena; Valdivieso, Camilo; Mauriaca, Cecilia; Ortíz-Severín, Javiera; Paradela, Alberto; Poblete-Castro, Ignacio; Cabrera, Ricardo; Chávez, Francisco P

2017-04-01

Polyphosphate (polyP) is a linear biopolymer found in all living cells. In bacteria, mutants lacking polyphosphate kinase 1 (PPK1), the enzyme responsible for synthesis of most polyP, have many structural and functional defects. However, little is known about the causes of these pleiotropic alterations. The link between ppk1 deletion and those numerous phenotypes observed can be the result of complex molecular interactions that can be elucidated via a systems biology approach. By integrating different omics levels (transcriptome, proteome and phenome), we described the functioning of various metabolic pathways among Escherichia coli polyphosphate mutant strains (Δppk1, Δppx, and ΔpolyP). Bioinformatic analyses reveal the complex metabolic and regulatory bases of the phenotypes unique to polyP mutants. Our results suggest that during polyP deficiency (Δppk1 mutant), metabolic pathways needed for energy supply are up-regulated, including fermentation, aerobic and anaerobic respiration. Transcriptomic and q-proteomic contrasting changes between Δppk1 and Δppx mutant strains were observed in those central metabolic pathways and confirmed by using Phenotypic microarrays. In addition, our results suggest a regulatory connection between polyP, second messenger metabolism, alternative Sigma/Anti-Sigma factors and type-II toxin-antitoxin (TA) systems. We suggest a broader role for polyP via regulation of ATP-dependent proteolysis of type II toxin-antitoxin system and alternative Sigma/Anti-Sigma factors, that could explain the multiple structural and functional deficiencies described due to alteration of polyP metabolism. Understanding the interplay of polyP in bacterial metabolism using a systems biology approach can help to improve design of novel antimicrobials toward pathogens. Copyright © 2017 Elsevier B.V. All rights reserved.

Genetic Resources for Maize Cell Wall Biology1[C][W][OA

PubMed Central

Penning, Bryan W.; Hunter, Charles T.; Tayengwa, Reuben; Eveland, Andrea L.; Dugard, Christopher K.; Olek, Anna T.; Vermerris, Wilfred; Koch, Karen E.; McCarty, Donald R.; Davis, Mark F.; Thomas, Steven R.; McCann, Maureen C.; Carpita, Nicholas C.

2009-01-01

Grass species represent a major source of food, feed, and fiber crops and potential feedstocks for biofuel production. Most of the biomass is contributed by cell walls that are distinct in composition from all other flowering plants. Identifying cell wall-related genes and their functions underpins a fundamental understanding of growth and development in these species. Toward this goal, we are building a knowledge base of the maize (Zea mays) genes involved in cell wall biology, their expression profiles, and the phenotypic consequences of mutation. Over 750 maize genes were annotated and assembled into gene families predicted to function in cell wall biogenesis. Comparative genomics of maize, rice (Oryza sativa), and Arabidopsis (Arabidopsis thaliana) sequences reveal differences in gene family structure between grass species and a reference eudicot species. Analysis of transcript profile data for cell wall genes in developing maize ovaries revealed that expression within families differed by up to 100-fold. When transcriptional analyses of developing ovaries before pollination from Arabidopsis, rice, and maize were contrasted, distinct sets of cell wall genes were expressed in grasses. These differences in gene family structure and expression between Arabidopsis and the grasses underscore the requirement for a grass-specific genetic model for functional analyses. A UniformMu population proved to be an important resource in both forward- and reverse-genetics approaches to identify hundreds of mutants in cell wall genes. A forward screen of field-grown lines by near-infrared spectroscopic screen of mature leaves yielded several dozen lines with heritable spectroscopic phenotypes. Pyrolysis-molecular beam mass spectrometry confirmed that several nir mutants had altered carbohydrate-lignin compositions. PMID:19926802

To 3D or Not to 3D, That Is the Question: Do 3D Surface Analyses Improve the Ecomorphological Power of the Distal Femur in Placental Mammals?

PubMed Central

Gould, Francois D. H.

2014-01-01

Improvements in three-dimensional imaging technologies have renewed interest in the study of functional and ecological morphology. Quantitative approaches to shape analysis are used increasingly to study form-function relationships. These methods are computationally intensive, technically demanding, and time-consuming, which may limit sampling potential. There have been few side-by-side comparisons of the effectiveness of such approaches relative to more traditional analyses using linear measurements and ratios. Morphological variation in the distal femur of mammals has been shown to reflect differences in locomotor modes across clades. Thus I tested whether a geometric morphometric analysis of surface shape was superior to a multivariate analysis of ratios for describing ecomorphological patterns in distal femoral variation. A sample of 164 mammalian specimens from 44 genera was assembled. Each genus was assigned to one of six locomotor categories. The same hypotheses were tested using two methods. Six linear measurements of the distal femur were taken with calipers, from which four ratios were calculated. A 3D model was generated with a laser scanner, and analyzed using three dimensional geometric morphometrics. Locomotor category significantly predicted variation in distal femoral morphology in both analyses. Effect size was larger in the geometric morphometric analysis than in the analysis of ratios. Ordination reveals a similar pattern with arboreal and cursorial taxa as extremes on a continuum of morphologies in both analyses. Discriminant functions calculated from the geometric morphometric analysis were more accurate than those calculated from ratios. Both analysis of ratios and geometric morphometric surface analysis reveal similar, biologically meaningful relationships between distal femoral shape and locomotor mode. The functional signal from the morphology is slightly higher in the geometric morphometric analysis. The practical costs of conducting these sorts of analyses should be weighed against potentially slight increases in power when designing protocols for ecomorphological studies. PMID:24633081

Network analysis reveals stage-specific changes in zebrafish embryo development using time course whole transcriptome profiling and prior biological knowledge.

PubMed

Zhang, Yuji

2015-01-01

Molecular networks act as the backbone of molecular activities within cells, offering a unique opportunity to better understand the mechanism of diseases. While network data usually constitute only static network maps, integrating them with time course gene expression information can provide clues to the dynamic features of these networks and unravel the mechanistic driver genes characterizing cellular responses. Time course gene expression data allow us to broadly "watch" the dynamics of the system. However, one challenge in the analysis of such data is to establish and characterize the interplay among genes that are altered at different time points in the context of a biological process or functional category. Integrative analysis of these data sources will lead us a more complete understanding of how biological entities (e.g., genes and proteins) coordinately perform their biological functions in biological systems. In this paper, we introduced a novel network-based approach to extract functional knowledge from time-dependent biological processes at a system level using time course mRNA sequencing data in zebrafish embryo development. The proposed method was applied to investigate 1α, 25(OH)2D3-altered mechanisms in zebrafish embryo development. We applied the proposed method to a public zebrafish time course mRNA-Seq dataset, containing two different treatments along four time points. We constructed networks between gene ontology biological process categories, which were enriched in differential expressed genes between consecutive time points and different conditions. The temporal propagation of 1α, 25-Dihydroxyvitamin D3-altered transcriptional changes started from a few genes that were altered initially at earlier stage, to large groups of biological coherent genes at later stages. The most notable biological processes included neuronal and retinal development and generalized stress response. In addition, we also investigated the relationship among biological processes enriched in co-expressed genes under different conditions. The enriched biological processes include translation elongation, nucleosome assembly, and retina development. These network dynamics provide new insights into the impact of 1α, 25-Dihydroxyvitamin D3 treatment in bone and cartilage development. We developed a network-based approach to analyzing the DEGs at different time points by integrating molecular interactions and gene ontology information. These results demonstrate that the proposed approach can provide insight on the molecular mechanisms taking place in vertebrate embryo development upon treatment with 1α, 25(OH)2D3. Our approach enables the monitoring of biological processes that can serve as a basis for generating new testable hypotheses. Such network-based integration approach can be easily extended to any temporal- or condition-dependent genomic data analyses.

Biochemical characterization of the selenoproteome in Gallus gallus via bioinformatics analysis: structure-function relationships and interactions of binding molecules.

PubMed

Zhu, Shi-Yong; Li, Xue-Nan; Sun, Xiao-Chen; Lin, Jia; Li, Wei; Zhang, Cong; Li, Jin-Long

2017-02-22

Knowledge about mammalian selenoproteins is increasing. However, the selenoproteome of birds remains considerably less understood, especially concerning its biochemical characterization, structure-function relationships and the interactions of binding molecules. In this work, the SECIS elements, subcellular localization, protein domains and interactions of binding molecules of the selenoproteome in Gallus gallus were analyzed using bioinformatics tools. We carried out comprehensive analyses of the structure-function relationships and interactions of the binding molecules of selenoproteins, to provide biochemical characterization of the selenoproteome in Gallus gallus. Our data provided a wealth of information on the biochemical functions of bird selenoproteins. Members of the selenoproteome were found to be involved in various biological processes in chickens, such as in antioxidants, maintenance of the redox balance, Se transport, and interactions with metals. Six membrane-bound selenoproteins (SelI, SelK, SelS, SelT, DIO1 and DIO3) played important roles in maintaining the membrane integrity. Chicken selenoproteins were classified according to their ligand binding sites as zinc-containing matrix metalloselenoproteins (Sep15, MsrB1, SelW and SelM), POP-containing selenoproteins (GPx1-4), FAD-interacting selenoproteins (TrxR1-3), secretory transport selenoproteins (GPx3 and SelPa) and other selenoproteins. The results of our study provided new evidence for the unknown biological functions of the selenoproteome in birds. Future research is required to confirm the novel biochemical functions of bird selenoproteins.

The Functional Genetics of Handedness and Language Lateralization: Insights from Gene Ontology, Pathway and Disease Association Analyses.

PubMed

Schmitz, Judith; Lor, Stephanie; Klose, Rena; Güntürkün, Onur; Ocklenburg, Sebastian

2017-01-01

Handedness and language lateralization are partially determined by genetic influences. It has been estimated that at least 40 (and potentially more) possibly interacting genes may influence the ontogenesis of hemispheric asymmetries. Recently, it has been suggested that analyzing the genetics of hemispheric asymmetries on the level of gene ontology sets, rather than at the level of individual genes, might be more informative for understanding the underlying functional cascades. Here, we performed gene ontology, pathway and disease association analyses on genes that have previously been associated with handedness and language lateralization. Significant gene ontology sets for handedness were anatomical structure development, pattern specification (especially asymmetry formation) and biological regulation. Pathway analysis highlighted the importance of the TGF-beta signaling pathway for handedness ontogenesis. Significant gene ontology sets for language lateralization were responses to different stimuli, nervous system development, transport, signaling, and biological regulation. Despite the fact that some authors assume that handedness and language lateralization share a common ontogenetic basis, gene ontology sets barely overlap between phenotypes. Compared to genes involved in handedness, which mostly contribute to structural development, genes involved in language lateralization rather contribute to activity-dependent cognitive processes. Disease association analysis revealed associations of genes involved in handedness with diseases affecting the whole body, while genes involved in language lateralization were specifically engaged in mental and neurological diseases. These findings further support the idea that handedness and language lateralization are ontogenetically independent, complex phenotypes.

ZnO@Gd2O3 core/shell nanoparticles for biomedical applications: Physicochemical, in vitro and in vivo characterization.

PubMed

Woźniak, Anna; Grześkowiak, Bartosz F; Babayevska, Nataliya; Zalewski, Tomasz; Drobna, Monika; Woźniak-Budych, Marta; Wiweger, Małgorzata; Słomski, Ryszard; Jurga, Stefan

2017-11-01

The chemical composition of nanoparticles (NPs) may be so designed as to provide measurability for numerous imaging techniques in order to achieve synergistic advantages. Innovative and unique structure of the core/shell ZnO@Gd 2 O 3 NPs possesses luminescent and magnetic properties, and is expected that they will become a new generation of contrast agents for Magnetic Resonance Imaging (MRI) and nanocarriers for theranostics. Thus, by surface biofunctionalization, it is possible to indicate particular nanoparticle compositions which provide efficient imaging, targeted drug delivery, and biocompatibility. Novel ZnO@Gd 2 O 3 NPs were synthesized and biofunctionalized by folic acid (FA) and doxorubicin (Doxo) to provide target and anticancer functions. Physicochemical analyses of the nanoparticles were performed. The biological study included a cytotoxicity in vitro, cellular distribution evaluation, as well as toxicity analyses, performed for the first time, on the in vivo zebrafish (Danio rerio) model. Nanoparticles were found to be effective double-function biomarkers (MRI T 2 contrast agents, fluorescent imaging). The biological study showed that ZnO@Gd 2 O 3 and ZnO@Gd 2 O 3 @OA-polySi@FA NPs are biocompatible in a particular concentration ranges. Conjugation with folic acid and/or doxorubicin resulted in effective drug delivery targeting. The in vivo results described the toxicology profile toward the zebrafish embryo/larvae, including new data concerning the survival, hatching ratio, and developmental malformations. Copyright © 2017 Elsevier B.V. All rights reserved.

Conditional Spectral Analysis of Replicated Multiple Time Series with Application to Nocturnal Physiology.

PubMed

Krafty, Robert T; Rosen, Ori; Stoffer, David S; Buysse, Daniel J; Hall, Martica H

2017-01-01

This article considers the problem of analyzing associations between power spectra of multiple time series and cross-sectional outcomes when data are observed from multiple subjects. The motivating application comes from sleep medicine, where researchers are able to non-invasively record physiological time series signals during sleep. The frequency patterns of these signals, which can be quantified through the power spectrum, contain interpretable information about biological processes. An important problem in sleep research is drawing connections between power spectra of time series signals and clinical characteristics; these connections are key to understanding biological pathways through which sleep affects, and can be treated to improve, health. Such analyses are challenging as they must overcome the complicated structure of a power spectrum from multiple time series as a complex positive-definite matrix-valued function. This article proposes a new approach to such analyses based on a tensor-product spline model of Cholesky components of outcome-dependent power spectra. The approach exibly models power spectra as nonparametric functions of frequency and outcome while preserving geometric constraints. Formulated in a fully Bayesian framework, a Whittle likelihood based Markov chain Monte Carlo (MCMC) algorithm is developed for automated model fitting and for conducting inference on associations between outcomes and spectral measures. The method is used to analyze data from a study of sleep in older adults and uncovers new insights into how stress and arousal are connected to the amount of time one spends in bed.

The Functional Genetics of Handedness and Language Lateralization: Insights from Gene Ontology, Pathway and Disease Association Analyses

PubMed Central

Schmitz, Judith; Lor, Stephanie; Klose, Rena; Güntürkün, Onur; Ocklenburg, Sebastian

2017-01-01

Handedness and language lateralization are partially determined by genetic influences. It has been estimated that at least 40 (and potentially more) possibly interacting genes may influence the ontogenesis of hemispheric asymmetries. Recently, it has been suggested that analyzing the genetics of hemispheric asymmetries on the level of gene ontology sets, rather than at the level of individual genes, might be more informative for understanding the underlying functional cascades. Here, we performed gene ontology, pathway and disease association analyses on genes that have previously been associated with handedness and language lateralization. Significant gene ontology sets for handedness were anatomical structure development, pattern specification (especially asymmetry formation) and biological regulation. Pathway analysis highlighted the importance of the TGF-beta signaling pathway for handedness ontogenesis. Significant gene ontology sets for language lateralization were responses to different stimuli, nervous system development, transport, signaling, and biological regulation. Despite the fact that some authors assume that handedness and language lateralization share a common ontogenetic basis, gene ontology sets barely overlap between phenotypes. Compared to genes involved in handedness, which mostly contribute to structural development, genes involved in language lateralization rather contribute to activity-dependent cognitive processes. Disease association analysis revealed associations of genes involved in handedness with diseases affecting the whole body, while genes involved in language lateralization were specifically engaged in mental and neurological diseases. These findings further support the idea that handedness and language lateralization are ontogenetically independent, complex phenotypes. PMID:28729848

Differential Expression and Functional Analysis of High-Throughput -Omics Data Using Open Source Tools.

PubMed

Kebschull, Moritz; Fittler, Melanie Julia; Demmer, Ryan T; Papapanou, Panos N

2017-01-01

Today, -omics analyses, including the systematic cataloging of messenger RNA and microRNA sequences or DNA methylation patterns in a cell population, organ, or tissue sample, allow for an unbiased, comprehensive genome-level analysis of complex diseases, offering a large advantage over earlier "candidate" gene or pathway analyses. A primary goal in the analysis of these high-throughput assays is the detection of those features among several thousand that differ between different groups of samples. In the context of oral biology, our group has successfully utilized -omics technology to identify key molecules and pathways in different diagnostic entities of periodontal disease.A major issue when inferring biological information from high-throughput -omics studies is the fact that the sheer volume of high-dimensional data generated by contemporary technology is not appropriately analyzed using common statistical methods employed in the biomedical sciences.In this chapter, we outline a robust and well-accepted bioinformatics workflow for the initial analysis of -omics data generated using microarrays or next-generation sequencing technology using open-source tools. Starting with quality control measures and necessary preprocessing steps for data originating from different -omics technologies, we next outline a differential expression analysis pipeline that can be used for data from both microarray and sequencing experiments, and offers the possibility to account for random or fixed effects. Finally, we present an overview of the possibilities for a functional analysis of the obtained data.

Modulated Modularity Clustering as an Exploratory Tool for Functional Genomic Inference

PubMed Central

Stone, Eric A.; Ayroles, Julien F.

2009-01-01

In recent years, the advent of high-throughput assays, coupled with their diminishing cost, has facilitated a systems approach to biology. As a consequence, massive amounts of data are currently being generated, requiring efficient methodology aimed at the reduction of scale. Whole-genome transcriptional profiling is a standard component of systems-level analyses, and to reduce scale and improve inference clustering genes is common. Since clustering is often the first step toward generating hypotheses, cluster quality is critical. Conversely, because the validation of cluster-driven hypotheses is indirect, it is critical that quality clusters not be obtained by subjective means. In this paper, we present a new objective-based clustering method and demonstrate that it yields high-quality results. Our method, modulated modularity clustering (MMC), seeks community structure in graphical data. MMC modulates the connection strengths of edges in a weighted graph to maximize an objective function (called modularity) that quantifies community structure. The result of this maximization is a clustering through which tightly-connected groups of vertices emerge. Our application is to systems genetics, and we quantitatively compare MMC both to the hierarchical clustering method most commonly employed and to three popular spectral clustering approaches. We further validate MMC through analyses of human and Drosophila melanogaster expression data, demonstrating that the clusters we obtain are biologically meaningful. We show MMC to be effective and suitable to applications of large scale. In light of these features, we advocate MMC as a standard tool for exploration and hypothesis generation. PMID:19424432

Invited essay: Cognitive influences on the psychological immune system.

PubMed

Rachman, S J

2016-12-01

The construct of the psychological immune system is described and analysed. The direct and indirect cognitive influences on the system are discussed, and the implications of adding a cognitive construal to the influential model of a behavioural immune system are considered. The psychological immune system has two main properties: defensive and healing. It encompasses a good amount of health-related phenomena that is outside the scope of the behavioural model or the biological immune system. Evidence pertaining to the psychological immune system includes meta-analyses of the associations between psychological variables such as positive affect/wellbeing and diseases and mortality, and associations between wellbeing and positive health. The results of long-term prospective studies are consistent with the conclusions drawn from the meta-analyses. Laboratory investigations of the effects of psychological variables on the biological immune system show that negative affect can slow wound-healing, and positive affect can enhance resistance to infections, for example in experiments involving the introduction of the rhinovirus and the influenza A virus. A number of problems concerning the assessment of the functioning of the psychological immune system are considered, and the need to develop techniques for determining when the system is active or not, is emphasized. This problem is particularly challenging when trying to assess the effects of the psychological immune system during a prolonged psychological intervention, such as a course of resilience training. Copyright © 2016 Elsevier Ltd. All rights reserved.

Genome-Wide Variation Patterns Uncover the Origin and Selection in Cultivated Ginseng (Panax ginseng Meyer).

PubMed

Li, Ming-Rui; Shi, Feng-Xue; Li, Ya-Ling; Jiang, Peng; Jiao, Lili; Liu, Bao; Li, Lin-Feng

2017-09-01

Chinese ginseng (Panax ginseng Meyer) is a medicinally important herb and plays crucial roles in traditional Chinese medicine. Pharmacological analyses identified diverse bioactive components from Chinese ginseng. However, basic biological attributes including domestication and selection of the ginseng plant remain under-investigated. Here, we presented a genome-wide view of the domestication and selection of cultivated ginseng based on the whole genome data. A total of 8,660 protein-coding genes were selected for genome-wide scanning of the 30 wild and cultivated ginseng accessions. In complement, the 45s rDNA, chloroplast and mitochondrial genomes were included to perform phylogenetic and population genetic analyses. The observed spatial genetic structure between northern cultivated ginseng (NCG) and southern cultivated ginseng (SCG) accessions suggested multiple independent origins of cultivated ginseng. Genome-wide scanning further demonstrated that NCG and SCG have undergone distinct selection pressures during the domestication process, with more genes identified in the NCG (97 genes) than in the SCG group (5 genes). Functional analyses revealed that these genes are involved in diverse pathways, including DNA methylation, lignin biosynthesis, and cell differentiation. These findings suggested that the SCG and NCG groups have distinct demographic histories. Candidate genes identified are useful for future molecular breeding of cultivated ginseng. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Constraint Network Analysis (CNA): a Python software package for efficiently linking biomacromolecular structure, flexibility, (thermo-)stability, and function.

PubMed

Pfleger, Christopher; Rathi, Prakash Chandra; Klein, Doris L; Radestock, Sebastian; Gohlke, Holger

2013-04-22

For deriving maximal advantage from information on biomacromolecular flexibility and rigidity, results from rigidity analyses must be linked to biologically relevant characteristics of a structure. Here, we describe the Python-based software package Constraint Network Analysis (CNA) developed for this task. CNA functions as a front- and backend to the graph-based rigidity analysis software FIRST. CNA goes beyond the mere identification of flexible and rigid regions in a biomacromolecule in that it (I) provides a refined modeling of thermal unfolding simulations that also considers the temperature-dependence of hydrophobic tethers, (II) allows performing rigidity analyses on ensembles of network topologies, either generated from structural ensembles or by using the concept of fuzzy noncovalent constraints, and (III) computes a set of global and local indices for quantifying biomacromolecular stability. This leads to more robust results from rigidity analyses and extends the application domain of rigidity analyses in that phase transition points ("melting points") and unfolding nuclei ("structural weak spots") are determined automatically. Furthermore, CNA robustly handles small-molecule ligands in general. Such advancements are important for applying rigidity analysis to data-driven protein engineering and for estimating the influence of ligand molecules on biomacromolecular stability. CNA maintains the efficiency of FIRST such that the analysis of a single protein structure takes a few seconds for systems of several hundred residues on a single core. These features make CNA an interesting tool for linking biomacromolecular structure, flexibility, (thermo-)stability, and function. CNA is available from http://cpclab.uni-duesseldorf.de/software for nonprofit organizations.

ADAGE signature analysis: differential expression analysis with data-defined gene sets.

PubMed

Tan, Jie; Huyck, Matthew; Hu, Dongbo; Zelaya, René A; Hogan, Deborah A; Greene, Casey S

2017-11-22

Gene set enrichment analysis and overrepresentation analyses are commonly used methods to determine the biological processes affected by a differential expression experiment. This approach requires biologically relevant gene sets, which are currently curated manually, limiting their availability and accuracy in many organisms without extensively curated resources. New feature learning approaches can now be paired with existing data collections to directly extract functional gene sets from big data. Here we introduce a method to identify perturbed processes. In contrast with methods that use curated gene sets, this approach uses signatures extracted from public expression data. We first extract expression signatures from public data using ADAGE, a neural network-based feature extraction approach. We next identify signatures that are differentially active under a given treatment. Our results demonstrate that these signatures represent biological processes that are perturbed by the experiment. Because these signatures are directly learned from data without supervision, they can identify uncurated or novel biological processes. We implemented ADAGE signature analysis for the bacterial pathogen Pseudomonas aeruginosa. For the convenience of different user groups, we implemented both an R package (ADAGEpath) and a web server ( http://adage.greenelab.com ) to run these analyses. Both are open-source to allow easy expansion to other organisms or signature generation methods. We applied ADAGE signature analysis to an example dataset in which wild-type and ∆anr mutant cells were grown as biofilms on the Cystic Fibrosis genotype bronchial epithelial cells. We mapped active signatures in the dataset to KEGG pathways and compared with pathways identified using GSEA. The two approaches generally return consistent results; however, ADAGE signature analysis also identified a signature that revealed the molecularly supported link between the MexT regulon and Anr. We designed ADAGE signature analysis to perform gene set analysis using data-defined functional gene signatures. This approach addresses an important gap for biologists studying non-traditional model organisms and those without extensive curated resources available. We built both an R package and web server to provide ADAGE signature analysis to the community.

FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies.

PubMed

Kim, Jiwoong; Kim, Min Soo; Koh, Andrew Y; Xie, Yang; Zhan, Xiaowei

2016-10-10

Given the lack of a complete and comprehensive library of microbial reference genomes, determining the functional profile of diverse microbial communities is challenging. The available functional analysis pipelines lack several key features: (i) an integrated alignment tool, (ii) operon-level analysis, and (iii) the ability to process large datasets. Here we introduce our open-sourced, stand-alone functional analysis pipeline for analyzing whole metagenomic and metatranscriptomic sequencing data, FMAP (Functional Mapping and Analysis Pipeline). FMAP performs alignment, gene family abundance calculations, and statistical analysis (three levels of analyses are provided: differentially-abundant genes, operons and pathways). The resulting output can be easily visualized with heatmaps and functional pathway diagrams. FMAP functional predictions are consistent with currently available functional analysis pipelines. FMAP is a comprehensive tool for providing functional analysis of metagenomic/metatranscriptomic sequencing data. With the added features of integrated alignment, operon-level analysis, and the ability to process large datasets, FMAP will be a valuable addition to the currently available functional analysis toolbox. We believe that this software will be of great value to the wider biology and bioinformatics communities.

Integration of gel-based and gel-free proteomic data for functional analysis of proteins through Soybean Proteome Database.

PubMed

Komatsu, Setsuko; Wang, Xin; Yin, Xiaojian; Nanjo, Yohei; Ohyanagi, Hajime; Sakata, Katsumi

2017-06-23

The Soybean Proteome Database (SPD) stores data on soybean proteins obtained with gel-based and gel-free proteomic techniques. The database was constructed to provide information on proteins for functional analyses. The majority of the data is focused on soybean (Glycine max 'Enrei'). The growth and yield of soybean are strongly affected by environmental stresses such as flooding. The database was originally constructed using data on soybean proteins separated by two-dimensional polyacrylamide gel electrophoresis, which is a gel-based proteomic technique. Since 2015, the database has been expanded to incorporate data obtained by label-free mass spectrometry-based quantitative proteomics, which is a gel-free proteomic technique. Here, the portions of the database consisting of gel-free proteomic data are described. The gel-free proteomic database contains 39,212 proteins identified in 63 sample sets, such as temporal and organ-specific samples of soybean plants grown under flooding stress or non-stressed conditions. In addition, data on organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored. Furthermore, the database integrates multiple omics data such as genomics, transcriptomics, metabolomics, and proteomics. The SPD database is accessible at http://proteome.dc.affrc.go.jp/Soybean/. The Soybean Proteome Database stores data obtained from both gel-based and gel-free proteomic techniques. The gel-free proteomic database comprises 39,212 proteins identified in 63 sample sets, such as different organs of soybean plants grown under flooding stress or non-stressed conditions in a time-dependent manner. In addition, organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored in the gel-free proteomics database. A total of 44,704 proteins, including 5490 proteins identified using a gel-based proteomic technique, are stored in the SPD. It accounts for approximately 80% of all predicted proteins from genome sequences, though there are over lapped proteins. Based on the demonstrated application of data stored in the database for functional analyses, it is suggested that these data will be useful for analyses of biological mechanisms in soybean. Furthermore, coupled with recent advances in information and communication technology, the usefulness of this database would increase in the analyses of biological mechanisms. Copyright © 2017 Elsevier B.V. All rights reserved.

Development of the field of structural physiology

PubMed Central

FUJIYOSHI, Yoshinori

2015-01-01

Electron crystallography is especially useful for studying the structure and function of membrane proteins — key molecules with important functions in neural and other cells. Electron crystallography is now an established technique for analyzing the structures of membrane proteins in lipid bilayers that closely simulate their natural biological environment. Utilizing cryo-electron microscopes with helium-cooled specimen stages that were developed through a personal motivation to understand the functions of neural systems from a structural point of view, the structures of membrane proteins can be analyzed at a higher than 3 Å resolution. This review covers four objectives. First, I introduce the new research field of structural physiology. Second, I recount some of the struggles involved in developing cryo-electron microscopes. Third, I review the structural and functional analyses of membrane proteins mainly by electron crystallography using cryo-electron microscopes. Finally, I discuss multifunctional channels named “adhennels” based on structures analyzed using electron and X-ray crystallography. PMID:26560835

Gene expression links functional networks across cortex and striatum.

PubMed

Anderson, Kevin M; Krienen, Fenna M; Choi, Eun Young; Reinen, Jenna M; Yeo, B T Thomas; Holmes, Avram J

2018-04-12

The human brain is comprised of a complex web of functional networks that link anatomically distinct regions. However, the biological mechanisms supporting network organization remain elusive, particularly across cortical and subcortical territories with vastly divergent cellular and molecular properties. Here, using human and primate brain transcriptional atlases, we demonstrate that spatial patterns of gene expression show strong correspondence with limbic and somato/motor cortico-striatal functional networks. Network-associated expression is consistent across independent human datasets and evolutionarily conserved in non-human primates. Genes preferentially expressed within the limbic network (encompassing nucleus accumbens, orbital/ventromedial prefrontal cortex, and temporal pole) relate to risk for psychiatric illness, chloride channel complexes, and markers of somatostatin neurons. Somato/motor associated genes are enriched for oligodendrocytes and markers of parvalbumin neurons. These analyses indicate that parallel cortico-striatal processing channels possess dissociable genetic signatures that recapitulate distributed functional networks, and nominate molecular mechanisms supporting cortico-striatal circuitry in health and disease.

How hunter perceptions of wildlife regulations, agency trust, and satisfaction affect attitudes about duck bag limits

USGS Publications Warehouse

Schroeder, Susan A.; Fulton, David C.; Lawrence, Jeffrey S.; Cordts, Steven D.

2017-01-01

This study explored how factors, including the function of bag limits, agency trust, satisfaction, hunting participation, and demographics, related to opinions about duck bag limits. The results are from a survey of 2014 Minnesota resident waterfowl hunters. Analyses identified four dimensions of attitudes about functions of bag limits, including that they: (a) are descriptive in defining the acceptable number of ducks that can be bagged, (b) are injunctive in establishing how many ducks should be allowed to be bagged, (c) ensure fair opportunities for all hunters to bag ducks, and (d) reflect biological limitations to protect waterfowl populations. Descriptive and fairness functions of bag limits were related to opinions about bag limits, as were factors related to agency trust, satisfaction, ducks bagged, experience with more restrictive bag limits, hunter age, and hunting group membership. Agencies may increase support by building trust and emphasizing the descriptive and fairness functions of regulations.

The pathway not taken: understanding 'omics data in the perinatal context.

PubMed

Edlow, Andrea G; Slonim, Donna K; Wick, Heather C; Hui, Lisa; Bianchi, Diana W

2015-07-01

'Omics analysis of large datasets has an increasingly important role in perinatal research, but understanding gene expression analyses in the fetal context remains a challenge. We compared the interpretation provided by a widely used systems biology resource (ingenuity pathway analysis [IPA]) with that from gene set enrichment analysis (GSEA) with functional annotation curated specifically for the fetus (Developmental FunctionaL Annotation at Tufts [DFLAT]). Using amniotic fluid supernatant transcriptome datasets previously produced by our group, we analyzed 3 different developmental perturbations: aneuploidy (Trisomy 21 [T21]), hemodynamic (twin-twin transfusion syndrome [TTTS]), and metabolic (maternal obesity) vs sex- and gestational age-matched control subjects. Differentially expressed probe sets were identified with the use of paired t-tests with the Benjamini-Hochberg correction for multiple testing (P < .05). Functional analyses were performed with IPA and GSEA/DFLAT. Outputs were compared for biologic relevance to the fetus. Compared with control subjects, there were 414 significantly dysregulated probe sets in T21 fetuses, 2226 in TTTS recipient twins, and 470 in fetuses of obese women. Each analytic output was unique but complementary. For T21, both IPA and GSEA/DFLAT identified dysregulation of brain, cardiovascular, and integumentary system development. For TTTS, both analytic tools identified dysregulation of cell growth/proliferation, immune and inflammatory signaling, brain, and cardiovascular development. For maternal obesity, both tools identified dysregulation of immune and inflammatory signaling, brain and musculoskeletal development, and cell death. GSEA/DFLAT identified substantially more dysregulated biologic functions in fetuses of obese women (1203 vs 151). For all 3 datasets, GSEA/DFLAT provided more comprehensive information about brain development. IPA consistently provided more detailed annotation about cell death. IPA produced many dysregulated terms that pertained to cancer (14 in T21, 109 in TTTS, 26 in maternal obesity); GSEA/DFLAT did not. Interpretation of the fetal amniotic fluid supernatant transcriptome depends on the analytic program, which suggests that >1 resource should be used. Within IPA, physiologic cellular proliferation in the fetus produced many "false positive" annotations that pertained to cancer, which reflects its bias toward adult diseases. This study supports the use of gene annotation resources with a developmental focus, such as DFLAT, for 'omics studies in perinatal medicine. Copyright © 2015 Elsevier Inc. All rights reserved.

Classification of climate-change-induced stresses on biological diversity.

PubMed

Geyer, Juliane; Kiefer, Iris; Kreft, Stefan; Chavez, Veronica; Salafsky, Nick; Jeltsch, Florian; Ibisch, Pierre L

2011-08-01

Conservation actions need to account for and be adapted to address changes that will occur under global climate change. The identification of stresses on biological diversity (as defined in the Convention on Biological Diversity) is key in the process of adaptive conservation management. We considered any impact of climate change on biological diversity a stress because such an effect represents a change (negative or positive) in key ecological attributes of an ecosystem or parts of it. We applied a systemic approach and a hierarchical framework in a comprehensive classification of stresses to biological diversity that are caused directly by global climate change. Through analyses of 20 conservation sites in 7 countries and a review of the literature, we identified climate-change-induced stresses. We grouped the identified stresses according to 3 levels of biological diversity: stresses that affect individuals and populations, stresses that affect biological communities, and stresses that affect ecosystem structure and function. For each stress category, we differentiated 3 hierarchical levels of stress: stress class (thematic grouping with the coarsest resolution, 8); general stresses (thematic groups of specific stresses, 21); and specific stresses (most detailed definition of stresses, 90). We also compiled an overview of effects of climate change on ecosystem services using the categories of the Millennium Ecosystem Assessment and 2 additional categories. Our classification may be used to identify key climate-change-related stresses to biological diversity and may assist in the development of appropriate conservation strategies. The classification is in list format, but it accounts for relations among climate-change-induced stresses. © 2011 Society for Conservation Biology.

Physiological and pharmacological characterization of the larval Anopheles albimanus rectum supports a change in protein distribution and/or function in varying salinities

PubMed Central

Smith, Kristin E.; Raymond, Steven L.; Valenti, Micheala L.; Smith, Peter J.S.; Linser, Paul J.

2010-01-01

Ion regulation is a biological process crucial to the survival of mosquito larvae and a major organ responsible for this regulation is the rectum. The recta of anopheline larvae are distinct from other subfamilies of mosquitoes in several ways, yet have not yet been characterized extensively. Here we characterize the two major cell types of the anopheline rectum, DAR and non-DAR cells, using histological, physiological, and pharmacological analyses. Proton flux was measured at the basal membrane of 2%- and 50%-artificial sea water-reared An. albimanus larvae using self-referencing ion-selective microelectrodes, and the two cell types were found to differ in basal membrane proton flux. Additionally, differences in the response of that flux to pharmacological inhibitors in larvae reared in 2% versus 50% ASW indicate changes in protein function between the two rearing conditions. Finally, histological analyses suggest that the non-DAR cells are structurally suited for mediating ion transport. These data support a model of rectal ion regulation in which the non-DAR cells have a resorptive function in freshwater-reared larvae and a secretive function in saline water-reared larvae. In this way, anopheline larvae may adapt to varying salinities. PMID:20460167

Single-column purification of the tag-free, recombinant form of the neuronal calcium sensor protein, hippocalcin expressed in Escherichia coli.

PubMed

Krishnan, Anuradha; Viviano, Jeffrey; Morozov, Yaroslav; Venkataraman, Venkat

2016-07-01

Hippocalcin is a 193 aa protein that is a member of the neuronal calcium sensor protein family, whose functions are regulated by calcium. Mice that lack the function of this protein are compromised in the long term potentiation aspect of memory generation. Recently, mutations in the gene have been linked with dystonia in human. The protein has no intrinsic enzyme activity but is known to bind to variety of target proteins. Very little information is available on how the protein executes its critical role in signaling pathways, except that it is regulated by binding of calcium. Further delineation of its function requires large amounts of pure protein. In this report, we present a single-step purification procedure that yields high quantities of the bacterially expressed, recombinant protein. The procedure may be adapted to purify the protein from inclusion bodies or cytosol in its myristoylated or non-myristoylated forms. MALDI-MS (in source decay) analyses demonstrates that the myristoylation occurs at the glycine residue. The protein is also biologically active as measured through tryptophan fluorescence, mobility shift and guanylate cyclase activity assays. Thus, further analyses of hippocalcin, both structural and functional, need no longer be limited by protein availability. Copyright © 2016 Elsevier Inc. All rights reserved.

Is Our Biology to Blame?

ERIC Educational Resources Information Center

Schneider, Scott

1977-01-01

Brief analyses of three recent examples of biological determinism: sex roles, overpopulation, and sociobiology, are presented in this article. Also a brief discussion of biological determinism and education is presented. (MR)

From the ultrasonic to the infrared: molecular evolution and the sensory biology of bats

PubMed Central

Jones, Gareth; Teeling, Emma C.; Rossiter, Stephen J.

2013-01-01

Great advances have been made recently in understanding the genetic basis of the sensory biology of bats. Research has focused on the molecular evolution of candidate sensory genes, genes with known functions [e.g., olfactory receptor (OR) genes] and genes identified from mutations associated with sensory deficits (e.g., blindness and deafness). For example, the FoxP2 gene, underpinning vocal behavior and sensorimotor coordination, has undergone diversification in bats, while several genes associated with audition show parallel amino acid substitutions in unrelated lineages of echolocating bats and, in some cases, in echolocating dolphins, representing a classic case of convergent molecular evolution. Vision genes encoding the photopigments rhodopsin and the long-wave sensitive opsin are functional in bats, while that encoding the short-wave sensitive opsin has lost functionality in rhinolophoid bats using high-duty cycle laryngeal echolocation, suggesting a sensory trade-off between investment in vision and echolocation. In terms of olfaction, bats appear to have a distinctive OR repertoire compared with other mammals, and a gene involved in signal transduction in the vomeronasal system has become non-functional in most bat species. Bitter taste receptors appear to have undergone a “birth-and death” evolution involving extensive gene duplication and loss, unlike genes coding for sweet and umami tastes that show conservation across most lineages but loss in vampire bats. Common vampire bats have also undergone adaptations for thermoperception, via alternative splicing resulting in the evolution of a novel heat-sensitive channel. The future for understanding the molecular basis of sensory biology is promising, with great potential for comparative genomic analyses, studies on gene regulation and expression, exploration of the role of alternative splicing in the generation of proteomic diversity, and linking genetic mechanisms to behavioral consequences. PMID:23755015

Neural Stem Cells (NSCs) and Proteomics*

PubMed Central

Shoemaker, Lorelei D.; Kornblum, Harley I.

2016-01-01

Neural stem cells (NSCs) can self-renew and give rise to the major cell types of the CNS. Studies of NSCs include the investigation of primary, CNS-derived cells as well as animal and human embryonic stem cell (ESC)-derived and induced pluripotent stem cell (iPSC)-derived sources. NSCs provide a means with which to study normal neural development, neurodegeneration, and neurological disease and are clinically relevant sources for cellular repair to the damaged and diseased CNS. Proteomics studies of NSCs have the potential to delineate molecules and pathways critical for NSC biology and the means by which NSCs can participate in neural repair. In this review, we provide a background to NSC biology, including the means to obtain them and the caveats to these processes. We then focus on advances in the proteomic interrogation of NSCs. This includes the analysis of posttranslational modifications (PTMs); approaches to analyzing different proteomic compartments, such the secretome; as well as approaches to analyzing temporal differences in the proteome to elucidate mechanisms of differentiation. We also discuss some of the methods that will undoubtedly be useful in the investigation of NSCs but which have not yet been applied to the field. While many proteomics studies of NSCs have largely catalogued the proteome or posttranslational modifications of specific cellular states, without delving into specific functions, some have led to understandings of functional processes or identified markers that could not have been identified via other means. Many challenges remain in the field, including the precise identification and standardization of NSCs used for proteomic analyses, as well as how to translate fundamental proteomics studies to functional biology. The next level of investigation will require interdisciplinary approaches, combining the skills of those interested in the biochemistry of proteomics with those interested in modulating NSC function. PMID:26494823

Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration.

PubMed

Arneson, Douglas; Bhattacharya, Anindya; Shu, Le; Mäkinen, Ville-Petteri; Yang, Xia

2016-09-09

Human diseases are commonly the result of multidimensional changes at molecular, cellular, and systemic levels. Recent advances in genomic technologies have enabled an outpour of omics datasets that capture these changes. However, separate analyses of these various data only provide fragmented understanding and do not capture the holistic view of disease mechanisms. To meet the urgent needs for tools that effectively integrate multiple types of omics data to derive biological insights, we have developed Mergeomics, a computational pipeline that integrates multidimensional disease association data with functional genomics and molecular networks to retrieve biological pathways, gene networks, and central regulators critical for disease development. To make the Mergeomics pipeline available to a wider research community, we have implemented an online, user-friendly web server ( http://mergeomics. idre.ucla.edu/ ). The web server features a modular implementation of the Mergeomics pipeline with detailed tutorials. Additionally, it provides curated genomic resources including tissue-specific expression quantitative trait loci, ENCODE functional annotations, biological pathways, and molecular networks, and offers interactive visualization of analytical results. Multiple computational tools including Marker Dependency Filtering (MDF), Marker Set Enrichment Analysis (MSEA), Meta-MSEA, and Weighted Key Driver Analysis (wKDA) can be used separately or in flexible combinations. User-defined summary-level genomic association datasets (e.g., genetic, transcriptomic, epigenomic) related to a particular disease or phenotype can be uploaded and computed real-time to yield biologically interpretable results, which can be viewed online and downloaded for later use. Our Mergeomics web server offers researchers flexible and user-friendly tools to facilitate integration of multidimensional data into holistic views of disease mechanisms in the form of tissue-specific key regulators, biological pathways, and gene networks.

Whipworm kinomes reflect a unique biology and adaptation to the host animal.

PubMed

Stroehlein, Andreas J; Young, Neil D; Korhonen, Pasi K; Chang, Bill C H; Nejsum, Peter; Pozio, Edoardo; La Rosa, Giuseppe; Sternberg, Paul W; Gasser, Robin B

2017-11-01

Roundworms belong to a diverse phylum (Nematoda) which is comprised of many parasitic species including whipworms (genus Trichuris). These worms have adapted to a biological niche within the host and exhibit unique morphological characteristics compared with other nematodes. Although these adaptations are known, the underlying molecular mechanisms remain elusive. The availability of genomes and transcriptomes of some whipworms now enables detailed studies of their molecular biology. Here, we defined and curated the full complement of an important class of enzymes, the protein kinases (kinomes) of two species of Trichuris, using an advanced and integrated bioinformatic pipeline. We investigated the transcription of Trichuris suis kinase genes across developmental stages, sexes and tissues, and reveal that selectively transcribed genes can be linked to central roles in developmental and reproductive processes. We also classified and functionally annotated the curated kinomes by integrating evidence from structural modelling and pathway analyses, and compared them with other curated kinomes of phylogenetically diverse nematode species. Our findings suggest unique adaptations in signalling processes governing worm morphology and biology, and provide an important resource that should facilitate experimental investigations of kinases and the biology of signalling pathways in nematodes. Copyright © 2017 Australian Society for Parasitology. Published by Elsevier Ltd. All rights reserved.

circlncRNAnet: an integrated web-based resource for mapping functional networks of long or circular forms of noncoding RNAs.

PubMed

Wu, Shao-Min; Liu, Hsuan; Huang, Po-Jung; Chang, Ian Yi-Feng; Lee, Chi-Ching; Yang, Chia-Yu; Tsai, Wen-Sy; Tan, Bertrand Chin-Ming

2018-01-01

Despite their lack of protein-coding potential, long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) have emerged as key determinants in gene regulation, acting to fine-tune transcriptional and signaling output. These noncoding RNA transcripts are known to affect expression of messenger RNAs (mRNAs) via epigenetic and post-transcriptional regulation. Given their widespread target spectrum, as well as extensive modes of action, a complete understanding of their biological relevance will depend on integrative analyses of systems data at various levels. While a handful of publicly available databases have been reported, existing tools do not fully capture, from a network perspective, the functional implications of lncRNAs or circRNAs of interest. Through an integrated and streamlined design, circlncRNAnet aims to broaden the understanding of ncRNA candidates by testing in silico several hypotheses of ncRNA-based functions, on the basis of large-scale RNA-seq data. This web server is implemented with several features that represent advances in the bioinformatics of ncRNAs: (1) a flexible framework that accepts and processes user-defined next-generation sequencing-based expression data; (2) multiple analytic modules that assign and productively assess the regulatory networks of user-selected ncRNAs by cross-referencing extensively curated databases; (3) an all-purpose, information-rich workflow design that is tailored to all types of ncRNAs. Outputs on expression profiles, co-expression networks and pathways, and molecular interactomes, are dynamically and interactively displayed according to user-defined criteria. In short, users may apply circlncRNAnet to obtain, in real time, multiple lines of functionally relevant information on circRNAs/lncRNAs of their interest. In summary, circlncRNAnet provides a "one-stop" resource for in-depth analyses of ncRNA biology. circlncRNAnet is freely available at http://app.cgu.edu.tw/circlnc/. © The Authors 2017. Published by Oxford University Press.

Comparison of Two Different Ultrasound Devices Using Strain Elastography Technology in the Diagnosis of Breast Lesions Related to the Histologic Results.

PubMed

Farrokh, André; Schaefer, Fritz; Degenhardt, Friedrich; Maass, Nicolai

2018-05-01

This study was conducted to provide evidence that elastograms of two different devices and different manufacturers using the same technical approach provide the same diagnoses. A total of 110 breast lesions were prospectively analysed by two experts in ultrasound, using the strain elastography function from two different manufacturers (Hitachi HI-RTE, Hitachi Medical Systems, Wiesbaden, Germany; and Siemens eSie Touch, Siemens Medical Systems, Erlangen, Germany). Results were compared with the histopathologic results. Applying the Bowker test of symmetry, no statistically significant difference between the two elastography functions of these two devices was found (p = 0.120). The Cohen's kappa of k = 0.591 showed moderate strength of agreement between the two elastograms. The two examiners yielded moderate strength of agreement analysing the elastograms (Hitachi HI-RTE, k = 0.478; Siemens eSie Touch, k = 0.441). In conclusion, evidence is provided that elastograms of the same lesion generated by two different ultrasound devices equipped with a strain elastography function do not significantly differ. Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

Thermodynamic characterization of the multivalent interactions underlying rapid and selective translocation through the nuclear pore complex

PubMed Central

Hayama, Ryo; Sparks, Samuel; Hecht, Lee M.; Dutta, Kaushik; Karp, Jerome M.; Cabana, Christina M.; Rout, Michael P.; Cowburn, David

2018-01-01

Intrinsically disordered proteins (IDPs) play important roles in many biological systems. Given the vast conformational space that IDPs can explore, the thermodynamics of the interactions with their partners is closely linked to their biological functions. Intrinsically disordered regions of Phe–Gly nucleoporins (FG Nups) that contain multiple phenylalanine–glycine repeats are of particular interest, as their interactions with transport factors (TFs) underlie the paradoxically rapid yet also highly selective transport of macromolecules mediated by the nuclear pore complex. Here, we used NMR and isothermal titration calorimetry to thermodynamically characterize these multivalent interactions. These analyses revealed that a combination of low per-FG motif affinity and the enthalpy–entropy balance prevents high-avidity interaction between FG Nups and TFs, whereas the large number of FG motifs promotes frequent FG–TF contacts, resulting in enhanced selectivity. Our thermodynamic model underlines the importance of functional disorder of FG Nups. It helps explain the rapid and selective translocation of TFs through the nuclear pore complex and further expands our understanding of the mechanisms of “fuzzy” interactions involving IDPs. PMID:29374059

Phi in physiology, psychology and biomechanics: The golden ratio between myth and science.

PubMed

Iosa, Marco; Morone, Giovanni; Paolucci, Stefano

2018-03-01

In recent years, there has been a renewed interest in the use of the so-called golden ratio (Phi, ϕ), an irrational number with fractal properties, used in artworks since V century BC. and now for modelling complex biological structures and functions. This number, in fact, recursively pops-up in human history, from Ancient Greeks to Renaissance, and to contemporary scientific studies. Nevertheless, recent scientific results often fall between two extremes: those of a priori sceptic researchers accusing the artificial emergence of ϕ in many studies, and those of researchers that find a mystic meaning in the presence of ϕ in human physiology. This review moves between these two extremes to provide a scientifically based discussion about the possible presence of Phi in human physiology, psychology, and biomechanics of heart and locomotion. We provide scientific evidence, analysing reasons for the presence of Phi, reporting the weakness of some studies overstating the potential meaning of this number, and reporting the reasons for which it could be actually found in some biological structures and functions. Copyright © 2018 Elsevier B.V. All rights reserved.

Structure–function characterization reveals new catalytic diversity in the galactose oxidase and glyoxal oxidase family

PubMed Central

Yin, DeLu (Tyler); Urresti, Saioa; Lafond, Mickael; Johnston, Esther M.; Derikvand, Fatemeh; Ciano, Luisa; Berrin, Jean-Guy; Henrissat, Bernard; Walton, Paul H.; Davies, Gideon J.; Brumer, Harry

2015-01-01

Alcohol oxidases, including carbohydrate oxidases, have a long history of research that has generated fundamental biological understanding and biotechnological applications. Despite a long history of study, the galactose 6-oxidase/glyoxal oxidase family of mononuclear copper-radical oxidases, Auxiliary Activity Family 5 (AA5), is currently represented by only very few characterized members. Here we report the recombinant production and detailed structure–function analyses of two homologues from the phytopathogenic fungi Colletotrichum graminicola and C. gloeosporioides, CgrAlcOx and CglAlcOx, respectively, to explore the wider biocatalytic potential in AA5. EPR spectroscopy and crystallographic analysis confirm a common active-site structure vis-à-vis the archetypal galactose 6-oxidase from Fusarium graminearum. Strikingly, however, CgrAlcOx and CglAlcOx are essentially incapable of oxidizing galactose and galactosides, but instead efficiently catalyse the oxidation of diverse aliphatic alcohols. The results highlight the significant potential of prospecting the evolutionary diversity of AA5 to reveal novel enzyme specificities, thereby informing both biology and applications. PMID:26680532

Combined neurostimulation and neuroimaging in cognitive neuroscience: past, present, and future.

PubMed

Bestmann, Sven; Feredoes, Eva

2013-08-01

Modern neurostimulation approaches in humans provide controlled inputs into the operations of cortical regions, with highly specific behavioral consequences. This enables causal structure-function inferences, and in combination with neuroimaging, has provided novel insights into the basic mechanisms of action of neurostimulation on distributed networks. For example, more recent work has established the capacity of transcranial magnetic stimulation (TMS) to probe causal interregional influences, and their interaction with cognitive state changes. Combinations of neurostimulation and neuroimaging now face the challenge of integrating the known physiological effects of neurostimulation with theoretical and biological models of cognition, for example, when theoretical stalemates between opposing cognitive theories need to be resolved. This will be driven by novel developments, including biologically informed computational network analyses for predicting the impact of neurostimulation on brain networks, as well as novel neuroimaging and neurostimulation techniques. Such future developments may offer an expanded set of tools with which to investigate structure-function relationships, and to formulate and reconceptualize testable hypotheses about complex neural network interactions and their causal roles in cognition. © 2013 New York Academy of Sciences.

Engineering Pseudomonas for phenazine biosynthesis, regulation, and biotechnological applications: a review.

PubMed

Bilal, Muhammad; Guo, Shuqi; Iqbal, Hafiz M N; Hu, Hongbo; Wang, Wei; Zhang, Xuehong

2017-10-03

Pseudomonas strains are increasingly attracting considerable attention as a valuable bacterial host both for basic and applied research. It has been considered as a promising candidate to produce a variety of bioactive secondary metabolites, particularly phenazines. Apart from the biotechnological perspective, these aromatic compounds have the notable potential to inhibit plant-pathogenic fungi and thus are useful in controlling plant diseases. Nevertheless, phenazines production is quite low by the wild-type strains that necessitated its yield improvement for large-scale agricultural applications. Metabolic engineering approaches with the advent of plentiful information provided by systems-level genomic and transcriptomic analyses enabled the development of new biological agents functioning as potential cell factories for producing the desired level of value-added bioproducts. This study presents an up-to-date overview of recombinant Pseudomonas strains as the preferred choice of host organisms for the biosynthesis of natural phenazines. The biosynthetic pathway and regulatory mechanism involved in the phenazine biosynthesis are comprehensively discussed. Finally, a summary of biological functionalities and biotechnological applications of the phenazines is also provided.

Microarray-based characterization of differential gene expression during vocal fold wound healing in rats

PubMed Central

Welham, Nathan V.; Ling, Changying; Dawson, John A.; Kendziorski, Christina; Thibeault, Susan L.; Yamashita, Masaru

2015-01-01

The vocal fold (VF) mucosa confers elegant biomechanical function for voice production but is susceptible to scar formation following injury. Current understanding of VF wound healing is hindered by a paucity of data and is therefore often generalized from research conducted in skin and other mucosal systems. Here, using a previously validated rat injury model, expression microarray technology and an empirical Bayes analysis approach, we generated a VF-specific transcriptome dataset to better capture the system-level complexity of wound healing in this specialized tissue. We measured differential gene expression at 3, 14 and 60 days post-injury compared to experimentally naïve controls, pursued functional enrichment analyses to refine and add greater biological definition to the previously proposed temporal phases of VF wound healing, and validated the expression and localization of a subset of previously unidentified repair- and regeneration-related genes at the protein level. Our microarray dataset is a resource for the wider research community and has the potential to stimulate new hypotheses and avenues of investigation, improve biological and mechanistic insight, and accelerate the identification of novel therapeutic targets. PMID:25592437

Ecological biomechanics of benthic organisms: life history, mechanical design and temporal patterns of mechanical stress.

PubMed

Koehl, M A

1999-12-01

We can gain biomechanical insights if we couple knowledge of the environments, ecological roles and life history strategies of organisms with our laboratory analyses of their mechanical function or fluid dynamics, as illustrated by studies of the mechanical design of bottom-dwelling marine organisms. Obviously, measurements of the spatial and temporal distribution of loads on an organism in nature reveal the magnitudes and rates at which biomechanical tests should be performed in the laboratory. Furthermore, knowledge of the population biology and ecological interactions of the organisms being studied is crucial to determine when during the life of an individual particular aspects of mechanical performance should be measured; not only can the size, shape and material properties of an individual change during ontogeny, but so can its habitat, activities and ecological role. Such ecological information is also necessary to determine whether the aspects of mechanical performance being studied are biologically important, i.e. whether they affect the survivorship or fitness of the organisms. My point in raising these examples is to illustrate how ecological studies can enhance or change our understanding of biomechanical function.

Interactions among ecosystem stressors and their importance in conservation

PubMed Central

Darling, Emily S.; Brown, Christopher J.

2016-01-01

Interactions between multiple ecosystem stressors are expected to jeopardize biological processes, functions and biodiversity. The scientific community has declared stressor interactions—notably synergies—a key issue for conservation and management. Here, we review ecological literature over the past four decades to evaluate trends in the reporting of ecological interactions (synergies, antagonisms and additive effects) and highlight the implications and importance to conservation. Despite increasing popularity, and ever-finer terminologies, we find that synergies are (still) not the most prevalent type of interaction, and that conservation practitioners need to appreciate and manage for all interaction outcomes, including antagonistic and additive effects. However, it will not be possible to identify the effect of every interaction on every organism's physiology and every ecosystem function because the number of stressors, and their potential interactions, are growing rapidly. Predicting the type of interactions may be possible in the near-future, using meta-analyses, conservation-oriented experiments and adaptive monitoring. Pending a general framework for predicting interactions, conservation management should enact interventions that are robust to uncertainty in interaction type and that continue to bolster biological resilience in a stressful world. PMID:26865306

A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

PubMed

Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

A Hybrid Approach of Gene Sets and Single Genes for the Prediction of Survival Risks with Gene Expression Data

PubMed Central

Seok, Junhee; Davis, Ronald W.; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn’t been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge. PMID:25933378

The search for Pleiades in trait constellations: functional integration and phenotypic selection in the complex flowers of Morrenia brachystephana (Apocynaceae).

PubMed

Baranzelli, M C; Sérsic, A N; Cocucci, A A

2014-04-01

Pollinator-mediated natural selection on single traits, such as corolla tube or spur length, has been well documented. However, flower phenotypes are usually complex, and selection is expected to act on several traits that functionally interact rather than on a single isolated trait. Despite the fact that selection on complex phenotypes is expectedly widespread, multivariate selection modelling on such phenotypes still remains under-explored in plants. Species of the subfamily Asclepiadoideae (Apocynaceae) provide an opportunity to study such complex flower contrivances integrated by fine-scaled organs from disparate developmental origin. We studied the correlation structure among linear floral traits (i) by testing a priori morphological, functional or developmental hypotheses among traits and (ii) by exploring the organization of flower covariation, considering alternative expectations of modular organization or whole flower integration through conditional dependence analysis (CDA) and integration matrices. The phenotypic selection approach was applied to determine whether floral traits involved in the functioning of the pollination mechanism were affected by natural selection. Floral integration was low, suggesting that flowers are organized in more than just one correlation pleiad; our hypothetical functional correlation matrix was significantly correlated with the empirical matrix, and the CDA revealed three putative modules. Analyses of phenotypic selection showed significant linear and correlational gradients, lending support to expectations of functional interactions between floral traits. Significant correlational selection gradients found involved traits of different floral whorls, providing evidence for the existence of functional integration across developmental domains. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Meta-analysis of magnitudes, differences and variation in evolutionary parameters.

PubMed

Morrissey, M B

2016-10-01

Meta-analysis is increasingly used to synthesize major patterns in the large literatures within ecology and evolution. Meta-analytic methods that do not account for the process of observing data, which we may refer to as 'informal meta-analyses', may have undesirable properties. In some cases, informal meta-analyses may produce results that are unbiased, but do not necessarily make the best possible use of available data. In other cases, unbiased statistical noise in individual reports in the literature can potentially be converted into severe systematic biases in informal meta-analyses. I first present a general description of how failure to account for noise in individual inferences should be expected to lead to biases in some kinds of meta-analysis. In particular, informal meta-analyses of quantities that reflect the dispersion of parameters in nature, for example, the mean absolute value of a quantity, are likely to be generally highly misleading. I then re-analyse three previously published informal meta-analyses, where key inferences were of aspects of the dispersion of values in nature, for example, the mean absolute value of selection gradients. Major biological conclusions in each original informal meta-analysis closely match those that could arise as artefacts due to statistical noise. I present alternative mixed-model-based analyses that are specifically tailored to each situation, but where all analyses may be implemented with widely available open-source software. In each example meta-re-analysis, major conclusions change substantially. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Signal Correlations in Ecological Niches Can Shape the Organization and Evolution of Bacterial Gene Regulatory Networks

PubMed Central

Dufour, Yann S.; Donohue, Timothy J.

2015-01-01

Transcriptional regulation plays a significant role in the biological response of bacteria to changing environmental conditions. Therefore, mapping transcriptional regulatory networks is an important step not only in understanding how bacteria sense and interpret their environment but also to identify the functions involved in biological responses to specific conditions. Recent experimental and computational developments have facilitated the characterization of regulatory networks on a genome-wide scale in model organisms. In addition, the multiplication of complete genome sequences has encouraged comparative analyses to detect conserved regulatory elements and infer regulatory networks in other less well-studied organisms. However, transcription regulation appears to evolve rapidly, thus, creating challenges for the transfer of knowledge to nonmodel organisms. Nevertheless, the mechanisms and constraints driving the evolution of regulatory networks have been the subjects of numerous analyses, and several models have been proposed. Overall, the contributions of mutations, recombination, and horizontal gene transfer are complex. Finally, the rapid evolution of regulatory networks plays a significant role in the remarkable capacity of bacteria to adapt to new or changing environments. Conversely, the characteristics of environmental niches determine the selective pressures and can shape the structure of regulatory network accordingly. PMID:23046950

Characterizing Flexible and Instrinsically Unstructured Biological Macromolecules by SAS using the Porod-Debye Law

PubMed Central

Rambo, Robert P.; Tainer, John A.

2011-01-01

Unstructured proteins, RNA or DNA components provide functionally important flexibility that is key to many macromolecular assemblies throughout cell biology. As objective, quantitative experimental measures of flexibility and disorder in solution are limited, small angle scattering (SAS), and in particular small angle X-ray scattering (SAXS), provides a critical technology to assess macromolecular flexibility as well as shape and assembly. Here, we consider the Porod-Debye law as a powerful tool for detecting biopolymer flexibility in SAS experiments. We show that the Porod-Debye region fundamentally describes the nature of the scattering intensity decay, which captures information needed for distinguishing between folded and flexible particles. Particularly for comparative SAS experiments, application of the law, as described here, can distinguish between discrete conformational changes and localized flexibility relevant to molecular recognition and interaction networks. This approach aids insightful analyses of fully and partly flexible macromolecules that is more robust and conclusive than traditional Kratky analyses. Furthermore, we demonstrate for prototypic SAXS data that the ability to calculate particle density by the Porod-Debye criteria, as shown here, provides an objective quality assurance parameter that may prove of general use for SAXS modeling and validation. PMID:21509745

Single Cell Gene Expression Profiling of Skeletal Muscle-Derived Cells.

PubMed

Gatto, Sole; Puri, Pier Lorenzo; Malecova, Barbora

2017-01-01

Single cell gene expression profiling is a fundamental tool for studying the heterogeneity of a cell population by addressing the phenotypic and functional characteristics of each cell. Technological advances that have coupled microfluidic technologies with high-throughput quantitative RT-PCR analyses have enabled detailed analyses of single cells in various biological contexts. In this chapter, we describe the procedure for isolating the skeletal muscle interstitial cells termed Fibro-Adipogenic Progenitors (FAPs ) and their gene expression profiling at the single cell level. Moreover, we accompany our bench protocol with bioinformatics analysis designed to process raw data as well as to visualize single cell gene expression data. Single cell gene expression profiling is therefore a useful tool in the investigation of FAPs heterogeneity and their contribution to muscle homeostasis.

Impact of a in situ laboratory on physician expectancy.

PubMed

Brulé, Romain; Sarazin, Marianne; Tayeb, Nicole; Roubille, Martine; Szymanowicz, Anton

2018-01-01

Biological examinations are essential for clinicians' medical care. The aim of this study is to assess clinicians' expectations in healthcare facilities and their perception of medical biology in different types of organization. We performed a prospective transversal study by electronic questionnaire conducted among 242 practitioners in four healthcare facilities. The aspects explored were as follows: quality, reliability, rendering time of examination results and biology platform support. Analyses were conducted after rectification of the sample by weight. Sixty one clinicians responded (25.2% [19.7-30.7]). The rendering time of examination is the main criterion mentioned with a requirement of less than one hour in case of emergency (81.5% [71.8-91.2] of the answers) to less than 72 hours for specialized examinations (81.5% [71.8-91.2] of the answers). Better collaboration with biologists is expected by clinicians (54.7% [50.9-58.5]). Satisfaction with the biology platform support and rendering time of emergency cases results was significantly (p <0.005) lower in facilities without an on-site laboratory. In conclusion, although medical biology performance is generally satisfactory within medical facilities, it remains nonetheless affected when the laboratory is not on site. The rendering time of examination, depending on the biology platform support functions and the proximity of the laboratory, remains the main criterion. Clinician-biologist collaboration, which increases of the medico-economic efficiency of patient's healthcare, appears as an essential criterion in a structural conception of medical biology.

Computational biology for cardiovascular biomarker discovery.

PubMed

Azuaje, Francisco; Devaux, Yvan; Wagner, Daniel

2009-07-01

Computational biology is essential in the process of translating biological knowledge into clinical practice, as well as in the understanding of biological phenomena based on the resources and technologies originating from the clinical environment. One such key contribution of computational biology is the discovery of biomarkers for predicting clinical outcomes using 'omic' information. This process involves the predictive modelling and integration of different types of data and knowledge for screening, diagnostic or prognostic purposes. Moreover, this requires the design and combination of different methodologies based on statistical analysis and machine learning. This article introduces key computational approaches and applications to biomarker discovery based on different types of 'omic' data. Although we emphasize applications in cardiovascular research, the computational requirements and advances discussed here are also relevant to other domains. We will start by introducing some of the contributions of computational biology to translational research, followed by an overview of methods and technologies used for the identification of biomarkers with predictive or classification value. The main types of 'omic' approaches to biomarker discovery will be presented with specific examples from cardiovascular research. This will include a review of computational methodologies for single-source and integrative data applications. Major computational methods for model evaluation will be described together with recommendations for reporting models and results. We will present recent advances in cardiovascular biomarker discovery based on the combination of gene expression and functional network analyses. The review will conclude with a discussion of key challenges for computational biology, including perspectives from the biosciences and clinical areas.

Analysis of single mammalian cells on-chip.

PubMed

Sims, Christopher E; Allbritton, Nancy L

2007-04-01

A goal of modern biology is to understand the molecular mechanisms underlying cellular function. The ability to manipulate and analyze single cells is crucial for this task. The advent of microengineering is providing biologists with unprecedented opportunities for cell handling and investigation on a cell-by-cell basis. For this reason, lab-on-a-chip (LOC) technologies are emerging as the next revolution in tools for biological discovery. In the current discussion, we seek to summarize the state of the art for conventional technologies in use by biologists for the analysis of single, mammalian cells, and then compare LOC devices engineered for these same single-cell studies. While a review of the technical progress is included, a major goal is to present the view point of the practicing biologist and the advances that might increase adoption by these individuals. The LOC field is expanding rapidly, and we have focused on areas of broad interest to the biology community where the technology is sufficiently far advanced to contemplate near-term application in biological experimentation. Focus areas to be covered include flow cytometry, electrophoretic analysis of cell contents, fluorescent-indicator-based analyses, cells as small volume reactors, control of the cellular microenvironment, and single-cell PCR.

Effects of small particle numbers on long-term behaviour in discrete biochemical systems

PubMed Central

Ibrahim, Bashar; Dittrich, Peter

2014-01-01

Motivation: The functioning of many biological processes depends on the appearance of only a small number of a single molecular species. Additionally, the observation of molecular crowding leads to the insight that even a high number of copies of species do not guarantee their interaction. How single particles contribute to stabilizing biological systems is not well understood yet. Hence, we aim at determining the influence of single molecules on the long-term behaviour of biological systems, i.e. whether they can reach a steady state. Results: We provide theoretical considerations and a tool to analyse Systems Biology Markup Language models for the possibility to stabilize because of the described effects. The theory is an extension of chemical organization theory, which we called discrete chemical organization theory. Furthermore we scanned the BioModels Database for the occurrence of discrete chemical organizations. To exemplify our method, we describe an application to the Template model of the mitotic spindle assembly checkpoint mechanism. Availability and implementation: http://www.biosys.uni-jena.de/Services.html. Contact: bashar.ibrahim@uni-jena.de or dittrich@minet.uni-jena.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25161236

The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 2 Core.

PubMed

Hucka, Michael; Bergmann, Frank T; Dräger, Andreas; Hoops, Stefan; Keating, Sarah M; Le Novère, Nicolas; Myers, Chris J; Olivier, Brett G; Sahle, Sven; Schaff, James C; Smith, Lucian P; Waltemath, Dagmar; Wilkinson, Darren J

2018-03-09

Computational models can help researchers to interpret data, understand biological functions, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that different software systems can exchange. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 2 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML, their encoding in XML (the eXtensible Markup Language), validation rules that determine the validity of an SBML document, and examples of models in SBML form. The design of Version 2 differs from Version 1 principally in allowing new MathML constructs, making more child elements optional, and adding identifiers to all SBML elements instead of only selected elements. Other materials and software are available from the SBML project website at http://sbml.org/.

Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk.

PubMed

Warren, Helen R; Evangelou, Evangelos; Cabrera, Claudia P; Gao, He; Ren, Meixia; Mifsud, Borbala; Ntalla, Ioanna; Surendran, Praveen; Liu, Chunyu; Cook, James P; Kraja, Aldi T; Drenos, Fotios; Loh, Marie; Verweij, Niek; Marten, Jonathan; Karaman, Ibrahim; Lepe, Marcelo P Segura; O'Reilly, Paul F; Knight, Joanne; Snieder, Harold; Kato, Norihiro; He, Jiang; Tai, E Shyong; Said, M Abdullah; Porteous, David; Alver, Maris; Poulter, Neil; Farrall, Martin; Gansevoort, Ron T; Padmanabhan, Sandosh; Mägi, Reedik; Stanton, Alice; Connell, John; Bakker, Stephan J L; Metspalu, Andres; Shields, Denis C; Thom, Simon; Brown, Morris; Sever, Peter; Esko, Tõnu; Hayward, Caroline; van der Harst, Pim; Saleheen, Danish; Chowdhury, Rajiv; Chambers, John C; Chasman, Daniel I; Chakravarti, Aravinda; Newton-Cheh, Christopher; Lindgren, Cecilia M; Levy, Daniel; Kooner, Jaspal S; Keavney, Bernard; Tomaszewski, Maciej; Samani, Nilesh J; Howson, Joanna M M; Tobin, Martin D; Munroe, Patricia B; Ehret, Georg B; Wain, Louise V

2017-03-01

Elevated blood pressure is the leading heritable risk factor for cardiovascular disease worldwide. We report genetic association of blood pressure (systolic, diastolic, pulse pressure) among UK Biobank participants of European ancestry with independent replication in other cohorts, and robust validation of 107 independent loci. We also identify new independent variants at 11 previously reported blood pressure loci. In combination with results from a range of in silico functional analyses and wet bench experiments, our findings highlight new biological pathways for blood pressure regulation enriched for genes expressed in vascular tissues and identify potential therapeutic targets for hypertension. Results from genetic risk score models raise the possibility of a precision medicine approach through early lifestyle intervention to offset the impact of blood pressure-raising genetic variants on future cardiovascular disease risk.

Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk

PubMed Central

Ntalla, Ioanna; Surendran, Praveen; Liu, Chunyu; Cook, James P; Kraja, Aldi T; Drenos, Fotios; Loh, Marie; Verweij, Niek; Marten, Jonathan; Karaman, Ibrahim; Segura Lepe, Marcelo P; O’Reilly, Paul F; Knight, Joanne; Snieder, Harold; Kato, Norihiro; He, Jiang; Tai, E Shyong; Said, M Abdullah; Porteous, David; Alver, Maris; Poulter, Neil; Farrall, Martin; Gansevoort, Ron T; Padmanabhan, Sandosh; Mägi, Reedik; Stanton, Alice; Connell, John; Bakker, Stephan J L; Metspalu, Andres; Shields, Denis C; Thom, Simon; Brown, Morris; Sever, Peter; Esko, Tõnu; Hayward, Caroline; van der Harst, Pim; Saleheen, Danish; Chowdhury, Rajiv; Chambers, John C; Chasman, Daniel I; Chakravarti, Aravinda; Newton-Cheh, Christopher; Lindgren, Cecilia M; Levy, Daniel; Kooner, Jaspal S; Keavney, Bernard; Tomaszewski, Maciej; Samani, Nilesh J; Howson, Joanna M M; Tobin, Martin D; Munroe, Patricia B; Ehret, Georg B; Wain, Louise V

2017-01-01

Elevated blood pressure is the leading heritable risk factor for cardiovascular disease worldwide. We report genetic association of blood pressure (systolic, diastolic, pulse pressure) among UK Biobank participants of European ancestry with independent replication in other cohorts, and robust validation of 107 independent loci. We also identify new independent variants at 11 previously reported blood pressure loci. Combined with results from a range of in silico functional analyses and wet bench experiments, our findings highlight new biological pathways for blood pressure regulation enriched for genes expressed in vascular tissues and identify potential therapeutic targets for hypertension. Results from genetic risk score models raise the possibility of a precision medicine approach through early lifestyle intervention to offset the impact of blood pressure raising genetic variants on future cardiovascular disease risk. PMID:28135244

Using Big Data to Discover Diagnostics and Therapeutics for Gastrointestinal and Liver Diseases.

PubMed

Wooden, Benjamin; Goossens, Nicolas; Hoshida, Yujin; Friedman, Scott L

2017-01-01

Technologies such as genome sequencing, gene expression profiling, proteomic and metabolomic analyses, electronic medical records, and patient-reported health information have produced large amounts of data from various populations, cell types, and disorders (big data). However, these data must be integrated and analyzed if they are to produce models or concepts about physiological function or mechanisms of pathogenesis. Many of these data are available to the public, allowing researchers anywhere to search for markers of specific biological processes or therapeutic targets for specific diseases or patient types. We review recent advances in the fields of computational and systems biology and highlight opportunities for researchers to use big data sets in the fields of gastroenterology and hepatology to complement traditional means of diagnostic and therapeutic discovery. Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.

The BioHome: A spinoff of space technology

NASA Technical Reports Server (NTRS)

Johnson, Anne

1990-01-01

The discussion of the BioHome is prefaced with some information about the work done at the environmental lab over the past 15 years concerning environmental issues related to biological life support such as the use of water hyacinths for wastewater purification, artificial marshes, indoor polluted air revitalization, and the reduction of organic contaminants using a biological system comprised of plants and microorganisms. One of the main concerns, especially with respect to a closed environment, is whether or not these systems are expelling microorganisms into the air. Analyses are being conducted to determine the numbers and types of microbes that are emitted. The BioHome is a 650 sq ft habitat that will enable the evaluation of the efficiency of bioregenerative technology in a closed system. This BioHome system is described and its functions discussed.

2010 Review on the Extension of the AMedP-8(C) Methodology to New Agents, Materials, and Conditions

DTIC Science & Technology

2010-12-01

tularemia ). Applied Research Associates (ARA), under contract to the Defense Threat Reduction Agency (DTRA), has begun the development of similar...x P Included in IDA 2010 Analyses 1 Biological Staphylococcal Enterotoxin B x P Included in IDA 2010 Analyses 1 Biological Tularemia x P

Technological advances and genomics in metazoan parasites.

PubMed

Knox, D P

2004-02-01

Molecular biology has provided the means to identify parasite proteins, to define their function, patterns of expression and the means to produce them in quantity for subsequent functional analyses. Whole genome and expressed sequence tag programmes, and the parallel development of powerful bioinformatics tools, allow the execution of genome-wide between stage or species comparisons and meaningful gene-expression profiling. The latter can be undertaken with several new technologies such as DNA microarray and serial analysis of gene expression. Proteome analysis has come to the fore in recent years providing a crucial link between the gene and its protein product. RNA interference and ballistic gene transfer are exciting developments which can provide the means to precisely define the function of individual genes and, of importance in devising novel parasite control strategies, the effect that gene knockdown will have on parasite survival.

Bringing nanomedicines to market: regulatory challenges, opportunities, and uncertainties.

PubMed

Nijhara, Ruchika; Balakrishnan, Krishna

2006-06-01

Scientists and entrepreneurs who contemplate developing nanomedicine products face several unique challenges in addition to many of the traditional hurdles of product development. In this review we analyze the major physicochemical, biologic and functional characteristics of several nanomedicine products on the market and explore the question of what made them unique. What made them successful? We also focus on the regulatory challenges faced by nanomedicine product developers. Based on these analyses, we propose the factors that are most likely to contribute to the success of nanomedicine products.

Bottom-up synthetic biology: modular design for making artificial platelets

NASA Astrophysics Data System (ADS)

Majumder, Sagardip; Liu, Allen P.

2018-01-01

Engineering artificial cells to mimic one or multiple fundamental cell biological functions is an emerging area of synthetic biology. Reconstituting functional modules from biological components in vitro is a challenging yet an important essence of bottom-up synthetic biology. Here we describe the concept of building artificial platelets using bottom-up synthetic biology and the four functional modules that together could enable such an ambitious effort.

Numeric promoter description - A comparative view on concepts and general application.

PubMed

Beier, Rico; Labudde, Dirk

2016-01-01

Nucleic acid molecules play a key role in a variety of biological processes. Starting from storage and transfer tasks, this also comprises the triggering of biological processes, regulatory effects and the active influence gained by target binding. Based on the experimental output (in this case promoter sequences), further in silico analyses aid in gaining new insights into these processes and interactions. The numerical description of nucleic acids thereby constitutes a bridge between the concrete biological issues and the analytical methods. Hence, this study compares 26 descriptor sets obtained by applying well-known numerical description concepts to an established dataset of 38 DNA promoter sequences. The suitability of the description sets was evaluated by computing partial least squares regression models and assessing the model accuracy. We conclude that the major importance regarding the descriptive power is attached to positional information rather than to explicitly incorporated physico-chemical information, since a sufficient amount of implicit physico-chemical information is already encoded in the nucleobase classification. The regression models especially benefited from employing the information that is encoded in the sequential and structural neighborhood of the nucleobases. Thus, the analyses of n-grams (short fragments of length n) suggested that they are valuable descriptors for DNA target interactions. A mixed n-gram descriptor set thereby yielded the best description of the promoter sequences. The corresponding regression model was checked and found to be plausible as it was able to reproduce the characteristic binding motifs of promoter sequences in a reasonable degree. As most functional nucleic acids are based on the principle of molecular recognition, the findings are not restricted to promoter sequences, but can rather be transferred to other kinds of functional nucleic acids. Thus, the concepts presented in this study could provide advantages for future nucleic acid-based technologies, like biosensoring, therapeutics and molecular imaging. Copyright © 2015 Elsevier Inc. All rights reserved.

Genus Cistus: a model for exploring labdane-type diterpenes' biosynthesis and a natural source of high value products with biological, aromatic and pharmacological properties

NASA Astrophysics Data System (ADS)

Papaefthimiou, Dimitra; Papanikolaou, Antigoni; Falara, Vasiliki; Givanoudi, Stella; Kostas, Stefanos; Kanellis, Angelos

2014-06-01

The family Cistaceae (Angiosperm, Malvales) consists of 8 genera and 180 species, with 5 genera native of the Mediterranean area (Cistus, Fumara, Halimium, Helianthemum and Tuberaria). Traditionally, a number of Cistus specie have been used in Mediterranean folk medicine as herbal tea infusions for healing, digestive problems and colds, as extracts for the treatment of diseases, and as fragrances. The resin, ladano, secreted by the glandular trichomes of certain Cistus species contains a number of phytochemicals with antioxidant, antibacterial, antifungal and anticancer properties. Furthermore, total leaf aqueous extracts possess anti-influenza virus activity. All these properties have been attributed to phytochemicals such as terpenoids, including diterpenes, labdane-type diterpenes and clerodanes, phenylpropanoids, including flavonoids and ellagitannins, several groups of alkaloids and other types of secondary metabolites. In the past 20 years, research on Cistus involved chemical, biological and phylogenetic analysis but recent investigations have involved genomic and molecular approaches. Our lab is exploring the biosynthetic machinery that generates terpenoids and phenylpropanoids, with a goal to harness their numerous properties that have applications in the pharmaceutical, chemical and aromatic industries. This review focuses on the systematics, botanical characteristics, geographic distribution, chemical analyses, biological function and biosynthesis of major compounds, as well as genomic analyses and biotechnological approaches of the main Cistus species found in the Mediterranean basin, namely C. albidus, C. creticus, C. crispus, C. parviflorus, C. monspeliensis, C. populifolius, C. salviifolius, C. ladanifer, C. laurifolius and C. clusii.

TCGA Workflow: Analyze cancer genomics and epigenomics data using Bioconductor packages

PubMed Central

Bontempi, Gianluca; Ceccarelli, Michele; Noushmehr, Houtan

2016-01-01

Biotechnological advances in sequencing have led to an explosion of publicly available data via large international consortia such as The Cancer Genome Atlas (TCGA), The Encyclopedia of DNA Elements (ENCODE), and The NIH Roadmap Epigenomics Mapping Consortium (Roadmap). These projects have provided unprecedented opportunities to interrogate the epigenome of cultured cancer cell lines as well as normal and tumor tissues with high genomic resolution. The Bioconductor project offers more than 1,000 open-source software and statistical packages to analyze high-throughput genomic data. However, most packages are designed for specific data types (e.g. expression, epigenetics, genomics) and there is no one comprehensive tool that provides a complete integrative analysis of the resources and data provided by all three public projects. A need to create an integration of these different analyses was recently proposed. In this workflow, we provide a series of biologically focused integrative analyses of different molecular data. We describe how to download, process and prepare TCGA data and by harnessing several key Bioconductor packages, we describe how to extract biologically meaningful genomic and epigenomic data. Using Roadmap and ENCODE data, we provide a work plan to identify biologically relevant functional epigenomic elements associated with cancer. To illustrate our workflow, we analyzed two types of brain tumors: low-grade glioma (LGG) versus high-grade glioma (glioblastoma multiform or GBM). This workflow introduces the following Bioconductor packages: AnnotationHub, ChIPSeeker, ComplexHeatmap, pathview, ELMER, GAIA, MINET, RTCGAToolbox,  TCGAbiolinks. PMID:28232861

TCGA Workflow: Analyze cancer genomics and epigenomics data using Bioconductor packages.

PubMed

Silva, Tiago C; Colaprico, Antonio; Olsen, Catharina; D'Angelo, Fulvio; Bontempi, Gianluca; Ceccarelli, Michele; Noushmehr, Houtan

2016-01-01

Biotechnological advances in sequencing have led to an explosion of publicly available data via large international consortia such as The Cancer Genome Atlas (TCGA), The Encyclopedia of DNA Elements (ENCODE), and The NIH Roadmap Epigenomics Mapping Consortium (Roadmap). These projects have provided unprecedented opportunities to interrogate the epigenome of cultured cancer cell lines as well as normal and tumor tissues with high genomic resolution. The Bioconductor project offers more than 1,000 open-source software and statistical packages to analyze high-throughput genomic data. However, most packages are designed for specific data types (e.g. expression, epigenetics, genomics) and there is no one comprehensive tool that provides a complete integrative analysis of the resources and data provided by all three public projects. A need to create an integration of these different analyses was recently proposed. In this workflow, we provide a series of biologically focused integrative analyses of different molecular data. We describe how to download, process and prepare TCGA data and by harnessing several key Bioconductor packages, we describe how to extract biologically meaningful genomic and epigenomic data. Using Roadmap and ENCODE data, we provide a work plan to identify biologically relevant functional epigenomic elements associated with cancer. To illustrate our workflow, we analyzed two types of brain tumors: low-grade glioma (LGG) versus high-grade glioma (glioblastoma multiform or GBM). This workflow introduces the following Bioconductor packages: AnnotationHub, ChIPSeeker, ComplexHeatmap, pathview, ELMER, GAIA, MINET, RTCGAToolbox,  TCGAbiolinks.

Shedding light into the function of the earliest vertebrate skeleton

NASA Astrophysics Data System (ADS)

Martinez-Perez, Carlos; Purnell, Mark; Rayfield, Emily; Donoghue, Philip

2016-04-01

Conodonts are an extinct group of jawless vertebrates, the first in our evolutionary lineage to develop a biomineralized skeleton. As such, the conodont skeleton is of great significance because of the insights it provides concerning the biology and function of the primitive vertebrate skeleton. Conodont function has been debated for a century and a half on the basis of its paleocological importance in the Palaezoic ecosystems. However, due to the lack of extanct close representatives and the small size of the conodont element (under a milimiter in length) strongly limited their functional analysis, traditional restricted to analogy. More recently, qualitative approaches have been developed, facilitating tests of element function based on occlusal performance and analysis of microwear and microstructure. In this work we extend these approaches using novel quantitative experimental methods including Synchrotron Radiation X-ray Tomographic Microscopy or Finite Element Analysis to test hypotheses of conodont function. The development of high resolution virtual models of conodont elements, together with biomechanical approaches using Finite Element analysis, informed by occlusal and microwear analyses, provided conclusive support to test hypothesis of structural adaptation within the crown tissue microstructure, showing a close topological co-variation patterns of compressive and tensile stress distribution with different crystallite orientation. In addition, our computational analyses strongly support a tooth-like function for many conodont species. Above all, our study establishes a framework (experimental approach) in which the functional ecology of conodonts can be read from their rich taxonomy and phylogeny, representing an important attempt to understand the role of this abundant and diverse clade in the Phanerozoic marine ecosystems.

Biological and epistemological models of localization in the nineteenth century: from Gall to Charcot.

PubMed

Kaitaro, T

2001-12-01

In the latter half of the nineteenth century, the localizationist doctrines became closely associated with the memory trace paradigm. The analysis of the texts dealing with the localization and the nature of 'the loss of articulated speech' (motor aphasia) by Bouillaud, Lordat, Dax, Broca, Trousseau, Baillarger, Charcot and Wernicke shows how the biological paradigm of localization presented by Gall and based on the notion of organ-function correspondence was transformed into a model based on localizable memory traces. This change resulted in the theoretical unification of the mechanisms of motor and non-motor forms of aphasia. These forms, which the earlier authors tended to separate in their analyses of the underlying mechanisms, were now regarded as involving similar mechanisms related to the loss of mnestic images. The crucial step in this development was taken by Broca who presented the hypothesis that the faculty of coordination of speech movements, which according to his predecessors was the faculty lost in motor aphasia, was actually an intellectual faculty and a specific form of memory, and motor aphasia consequently a selective kind of amnesia. Theorists like Charcot and Wernicke generalized this idea into a comprehensive theory of the nature of localization based on the notion of memory traces. Thus, the localization of function was reduced to the localization of representations. Instead of biological paradigms, this model of localization is rooted in the epistemological tradition of psychology represented by Locke and Condillac, who were primarily interested in the problem of representation. In physiology, this approach usually resulted in attempts at localizing representations instead of functions.

Analyses of Dynein Heavy Chain Mutations Reveal Complex Interactions Between Dynein Motor Domains and Cellular Dynein Functions

PubMed Central

Sivagurunathan, Senthilkumar; Schnittker, Robert R.; Razafsky, David S.; Nandini, Swaran; Plamann, Michael D.; King, Stephen J.

2012-01-01

Cytoplasmic dynein transports cargoes for a variety of crucial cellular functions. However, since dynein is essential in most eukaryotic organisms, the in-depth study of the cellular function of dynein via genetic analysis of dynein mutations has not been practical. Here, we identify and characterize 34 different dynein heavy chain mutations using a genetic screen of the ascomycete fungus Neurospora crassa, in which dynein is nonessential. Interestingly, our studies show that these mutations segregate into five different classes based on the in vivo localization of the mutated dynein motors. Furthermore, we have determined that the different classes of dynein mutations alter vesicle trafficking, microtubule organization, and nuclear distribution in distinct ways and require dynactin to different extents. In addition, biochemical analyses of dynein from one mutant strain show a strong correlation between its in vitro biochemical properties and the aberrant intracellular function of that altered dynein. When the mutations were mapped to the published dynein crystal structure, we found that the three-dimensional structural locations of the heavy chain mutations were linked to particular classes of altered dynein functions observed in cells. Together, our data indicate that the five classes of dynein mutations represent the entrapment of dynein at five separate points in the dynein mechanochemical and transport cycles. We have developed N. crassa as a model system where we can dissect the complexities of dynein structure, function, and interaction with other proteins with genetic, biochemical, and cell biological studies. PMID:22649085

Diels-Alder functionalized carbon nanotubes for bone tissue engineering: in vitro/in vivo biocompatibility and biodegradability

NASA Astrophysics Data System (ADS)

Mata, D.; Amaral, M.; Fernandes, A. J. S.; Colaço, B.; Gama, A.; Paiva, M. C.; Gomes, P. S.; Silva, R. F.; Fernandes, M. H.

2015-05-01

The risk-benefit balance for carbon nanotubes (CNTs) dictates their clinical fate. To take a step forward at this crossroad it is compulsory to modulate the CNT in vivo biocompatibility and biodegradability via e.g. chemical functionalization. CNT membranes were functionalised combining a Diels-Alder cycloaddition reaction to generate cyclohexene (-C6H10) followed by a mild oxidisation to yield carboxylic acid groups (-COOH). In vitro proliferation and osteogenic differentiation of human osteoblastic cells were maximized on functionalized CNT membranes (p,f-CNTs). The in vivo subcutaneously implanted materials showed a higher biological reactivity, thus inducing a slighter intense inflammatory response compared to non-functionalized CNT membranes (p-CNTs), but still showing a reduced cytotoxicity profile. Moreover, the in vivo biodegradation of CNTs was superior for p,f-CNT membranes, likely mediated by the oxidation-induced myeloperoxidase (MPO) in neutrophil and macrophage inflammatory milieus. This proves the biodegradability faculty of functionalized CNTs, which potentially avoids long-term tissue accumulation and triggering of acute toxicity. On the whole, the proposed Diels-Alder functionalization accounts for the improved CNT biological response in terms of the biocompatibility and biodegradability profiles. Therefore, CNTs can be considered for use in bone tissue engineering without notable toxicological threats.The risk-benefit balance for carbon nanotubes (CNTs) dictates their clinical fate. To take a step forward at this crossroad it is compulsory to modulate the CNT in vivo biocompatibility and biodegradability via e.g. chemical functionalization. CNT membranes were functionalised combining a Diels-Alder cycloaddition reaction to generate cyclohexene (-C6H10) followed by a mild oxidisation to yield carboxylic acid groups (-COOH). In vitro proliferation and osteogenic differentiation of human osteoblastic cells were maximized on functionalized CNT membranes (p,f-CNTs). The in vivo subcutaneously implanted materials showed a higher biological reactivity, thus inducing a slighter intense inflammatory response compared to non-functionalized CNT membranes (p-CNTs), but still showing a reduced cytotoxicity profile. Moreover, the in vivo biodegradation of CNTs was superior for p,f-CNT membranes, likely mediated by the oxidation-induced myeloperoxidase (MPO) in neutrophil and macrophage inflammatory milieus. This proves the biodegradability faculty of functionalized CNTs, which potentially avoids long-term tissue accumulation and triggering of acute toxicity. On the whole, the proposed Diels-Alder functionalization accounts for the improved CNT biological response in terms of the biocompatibility and biodegradability profiles. Therefore, CNTs can be considered for use in bone tissue engineering without notable toxicological threats. Electronic supplementary information (ESI) available: Experimental details on the preparation of HNO3 functionalized CNTs and supplementary analyses (μ-Raman, TG, EDS, acid-base titration, FTIR, roughness measurements, SEM and optical images) are shown. See DOI: 10.1039/c5nr01829c

Structural and functional studies on Ribonuclease S, retro S and retro-inverso S peptides

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

Pal-Bhowmick, Ipsita; Pati Pandey, Ramendra; Jarori, Gotam K.

2007-12-21

Ribonuclease S peptide and S protein offer a unique complementation system to understand the finer features of molecular recognition. In the present study the S peptide (1-16), and its retro and retro-inverso analogs have been analyzed for their structural and biological attributes. RPHPLC, CD, and NMR analyses have revealed that the physicochemical and conformational properties of the S peptide are distinct from those of its retro and retro-inverso analogs. On the functional side, while the S peptide complemented the S protein to give RNase activity, was recognized by anti-S peptide antibodies and induced T cell proliferation, neither the retro normore » the retro-inverso S peptides could do so.« less

Murine macrophages: a technical approach.

PubMed

Martinez-Pomares, Luisa; Gordon, Siamon

2008-01-01

In this chapter, we describe current protocols used for the characterization of macrophages (MPhi) in mouse tissues and in cell suspensions from spleen and lymph nodes. Also, we include a brief description of a complementary approach: culture of primary MPhi. Although culture MPhi are extremely useful for analysing the basic biology of MPhi and their receptors, it should not be forgotten that the term MPhi encompasses a wide range of different types of cells with phenotypic characteristics dependent on their activation state and tissue of origin. In our view, there is no perfect MPhi marker and analysis of the expression profile of several markers, and functional studies are required to make an informed guess of the cellular characteristics and function of the MPhi population of interest.

Effect of posttranslational modifications on enzyme function and assembly.

PubMed

Ryšlavá, Helena; Doubnerová, Veronika; Kavan, Daniel; Vaněk, Ondřej

2013-10-30

The detailed examination of enzyme molecules by mass spectrometry and other techniques continues to identify hundreds of distinct PTMs. Recently, global analyses of enzymes using methods of contemporary proteomics revealed widespread distribution of PTMs on many key enzymes distributed in all cellular compartments. Critically, patterns of multiple enzymatic and nonenzymatic PTMs within a single enzyme are now functionally evaluated providing a holistic picture of a macromolecule interacting with low molecular mass compounds, some of them being substrates, enzyme regulators, or activated precursors for enzymatic and nonenzymatic PTMs. Multiple PTMs within a single enzyme molecule and their mutual interplays are critical for the regulation of catalytic activity. Full understanding of this regulation will require detailed structural investigation of enzymes, their structural analogs, and their complexes. Further, proteomics is now integrated with molecular genetics, transcriptomics, and other areas leading to systems biology strategies. These allow the functional interrogation of complex enzymatic networks in their natural environment. In the future, one might envisage the use of robust high throughput analytical techniques that will be able to detect multiple PTMs on a global scale of individual proteomes from a number of carefully selected cells and cellular compartments. This article is part of a Special Issue entitled: Posttranslational Protein modifications in biology and Medicine. Copyright © 2013 Elsevier B.V. All rights reserved.

Systemic evaluation of cellular reprogramming processes exploiting a novel R-tool: eegc.

PubMed

Zhou, Xiaoyuan; Meng, Guofeng; Nardini, Christine; Mei, Hongkang

2017-08-15

Cells derived by cellular engineering, i.e. differentiation of induced pluripotent stem cells and direct lineage reprogramming, carry a tremendous potential for medical applications and in particular for regenerative therapies. These approaches consist in the definition of lineage-specific experimental protocols that, by manipulation of a limited number of biological cues-niche mimicking factors, (in)activation of transcription factors, to name a few-enforce the final expression of cell-specific (marker) molecules. To date, given the intricate complexity of biological pathways, these approaches still present imperfect reprogramming fidelity, with uncertain consequences on the functional properties of the resulting cells. We propose a novel tool eegc to evaluate cellular engineering processes, in a systemic rather than marker-based fashion, by integrating transcriptome profiling and functional analysis. Our method clusters genes into categories representing different states of (trans)differentiation and further performs functional and gene regulatory network analyses for each of the categories of the engineered cells, thus offering practical indications on the potential lack of the reprogramming protocol. eegc R package is released under the GNU General Public License within the Bioconductor project, freely available at https://bioconductor.org/packages/eegc/. christine.nardini.rsrc@gmail.com or hongkang.k.mei@gsk.com. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Systemic evaluation of cellular reprogramming processes exploiting a novel R-tool: eegc

PubMed Central

Zhou, Xiaoyuan; Meng, Guofeng; Nardini, Christine; Mei, Hongkang

2017-01-01

Abstract Motivation Cells derived by cellular engineering, i.e. differentiation of induced pluripotent stem cells and direct lineage reprogramming, carry a tremendous potential for medical applications and in particular for regenerative therapies. These approaches consist in the definition of lineage-specific experimental protocols that, by manipulation of a limited number of biological cues—niche mimicking factors, (in)activation of transcription factors, to name a few—enforce the final expression of cell-specific (marker) molecules. To date, given the intricate complexity of biological pathways, these approaches still present imperfect reprogramming fidelity, with uncertain consequences on the functional properties of the resulting cells. Results We propose a novel tool eegc to evaluate cellular engineering processes, in a systemic rather than marker-based fashion, by integrating transcriptome profiling and functional analysis. Our method clusters genes into categories representing different states of (trans)differentiation and further performs functional and gene regulatory network analyses for each of the categories of the engineered cells, thus offering practical indications on the potential lack of the reprogramming protocol. Availability and Implementation eegc R package is released under the GNU General Public License within the Bioconductor project, freely available at https://bioconductor.org/packages/eegc/. Contact christine.nardini.rsrc@gmail.com or hongkang.k.mei@gsk.com Supplementary information Supplementary data are available at Bioinformatics online. PMID:28398503

Time dependent-density functional theory (TD-DFT) and experimental studies of UV-Visible spectra and cyclic voltammetry for Cu(II) complex with Et2DTC

NASA Astrophysics Data System (ADS)

Valle, Eliana Maira A.; Maltarollo, Vinicius Gonçalves; Almeida, Michell O.; Honorio, Kathia Maria; dos Santos, Mauro Coelho; Cerchiaro, Giselle

2018-04-01

In this work, we studied the complexation mode between copper(II) ion and the specific ligand investigated as carriers of metals though biological membranes, diethyldithiocarbamate (Et2DTC). It is important to understand how this occurs because it is an important intracellular chelator with potential therapeutic applications. Theoretical and experimental UV visible studies were performed to investigate the complexation mode between copper and the ligand. Electrochemical studies were also performed to complement the spectroscopic analyses. According to the theoretical calculations, using TD-DFT (Time dependent density functional theory), with B3LYP functional and DGDVZP basis set, implemented in Gaussian 03 package, it was observed that the formation of the complex [Cu(Et2DTC)2] is favorable with higher electron density over the sulfur atoms of the ligand. UV/Vis spectra have a charge transfer band at 450 nm, with the DMSO-d6 band shift from 800 to 650 nm. The electrochemical experiments showed the formation of a new redox process, referring to the complex, where the reduction peak potential of copper is displaced to less positive region. Therefore, the results obtained from this study give important insights on possible mechanisms involved in several biological processes related to the studied system.

PipeOnline 2.0: automated EST processing and functional data sorting.

PubMed

Ayoubi, Patricia; Jin, Xiaojing; Leite, Saul; Liu, Xianghui; Martajaja, Jeson; Abduraham, Abdurashid; Wan, Qiaolan; Yan, Wei; Misawa, Eduardo; Prade, Rolf A

2002-11-01

Expressed sequence tags (ESTs) are generated and deposited in the public domain, as redundant, unannotated, single-pass reactions, with virtually no biological content. PipeOnline automatically analyses and transforms large collections of raw DNA-sequence data from chromatograms or FASTA files by calling the quality of bases, screening and removing vector sequences, assembling and rewriting consensus sequences of redundant input files into a unigene EST data set and finally through translation, amino acid sequence similarity searches, annotation of public databases and functional data. PipeOnline generates an annotated database, retaining the processed unigene sequence, clone/file history, alignments with similar sequences, and proposed functional classification, if available. Functional annotation is automatic and based on a novel method that relies on homology of amino acid sequence multiplicity within GenBank records. Records are examined through a function ordered browser or keyword queries with automated export of results. PipeOnline offers customization for individual projects (MyPipeOnline), automated updating and alert service. PipeOnline is available at http://stress-genomics.org.

Shedding new light on opsin evolution

PubMed Central

Porter, Megan L.; Blasic, Joseph R.; Bok, Michael J.; Cameron, Evan G.; Pringle, Thomas; Cronin, Thomas W.; Robinson, Phyllis R.

2012-01-01

Opsin proteins are essential molecules in mediating the ability of animals to detect and use light for diverse biological functions. Therefore, understanding the evolutionary history of opsins is key to understanding the evolution of light detection and photoreception in animals. As genomic data have appeared and rapidly expanded in quantity, it has become possible to analyse opsins that functionally and histologically are less well characterized, and thus to examine opsin evolution strictly from a genetic perspective. We have incorporated these new data into a large-scale, genome-based analysis of opsin evolution. We use an extensive phylogeny of currently known opsin sequence diversity as a foundation for examining the evolutionary distributions of key functional features within the opsin clade. This new analysis illustrates the lability of opsin protein-expression patterns, site-specific functionality (i.e. counterion position) and G-protein binding interactions. Further, it demonstrates the limitations of current model organisms, and highlights the need for further characterization of many of the opsin sequence groups with unknown function. PMID:22012981

RUNX in Invertebrates.

PubMed

Hughes, S; Woollard, A

2017-01-01

Runx genes have been identified in all metazoans and considerable conservation of function observed across a wide range of phyla. Thus, insight gained from studying simple model organisms is invaluable in understanding RUNX biology in higher animals. Consequently, this chapter will focus on the Runx genes in the diploblasts, which includes sea anemones and sponges, as well as the lower triploblasts, including the sea urchin, nematode, planaria and insect. Due to the high degree of functional redundancy amongst vertebrate Runx genes, simpler model organisms with a solo Runx gene, like C. elegans, are invaluable systems in which to probe the molecular basis of RUNX function within a whole organism. Additionally, comparative analyses of Runx sequence and function allows for the development of novel evolutionary insights. Strikingly, recent data has emerged that reveals the presence of a Runx gene in a protist, demonstrating even more widespread occurrence of Runx genes than was previously thought. This review will summarize recent progress in using invertebrate organisms to investigate RUNX function during development and regeneration, highlighting emerging unifying themes.

Effect of brain structure, brain function, and brain connectivity on relapse in alcohol-dependent patients.

PubMed

Beck, Anne; Wüstenberg, Torsten; Genauck, Alexander; Wrase, Jana; Schlagenhauf, Florian; Smolka, Michael N; Mann, Karl; Heinz, Andreas

2012-08-01

In alcohol-dependent patients, brain atrophy and functional brain activation elicited by alcohol-associated stimuli may predict relapse. However, to date, the interaction between both factors has not been studied. To determine whether results from structural and functional magnetic resonance imaging are associated with relapse in detoxified alcohol-dependent patients. A cue-reactivity functional magnetic resonance experiment with alcohol-associated and neutral stimuli. After a follow-up period of 3 months, the group of 46 detoxified alcohol-dependent patients was subdivided into 16 abstainers and 30 relapsers. Faculty for Clinical Medicine Mannheim at the University of Heidelberg, Germany. A total of 46 detoxified alcohol-dependent patients and 46 age- and sex-matched healthy control subjects Local gray matter volume, local stimulus-related functional magnetic resonance imaging activation, joint analyses of structural and functional data with Biological Parametric Mapping, and connectivity analyses adopting the psychophysiological interaction approach. Subsequent relapsers showed pronounced atrophy in the bilateral orbitofrontal cortex and in the right medial prefrontal and anterior cingulate cortex, compared with healthy controls and patients who remained abstinent. The local gray matter volume-corrected brain response elicited by alcohol-associated vs neutral stimuli in the left medial prefrontal cortex was enhanced for subsequent relapsers, whereas abstainers displayed an increased neural response in the midbrain (the ventral tegmental area extending into the subthalamic nucleus) and ventral striatum. For alcohol-associated vs neutral stimuli in abstainers compared with relapsers, the analyses of the psychophysiological interaction showed a stronger functional connectivity between the midbrain and the left amygdala and between the midbrain and the left orbitofrontal cortex. Subsequent relapsers displayed increased brain atrophy in brain areas associated with error monitoring and behavioral control. Correcting for gray matter reductions, we found that, in these patients, alcohol-related cues elicited increased activation in brain areas associated with attentional bias toward these cues and that, in patients who remained abstinent, increased activation and connectivity were observed in brain areas associated with processing of salient or aversive stimuli.

Children's biological responsivity to acute stress predicts concurrent cognitive performance.

PubMed

Roos, Leslie E; Beauchamp, Kathryn G; Giuliano, Ryan; Zalewski, Maureen; Kim, Hyoun K; Fisher, Philip A

2018-04-10

Although prior research has characterized stress system reactivity (i.e. hypothalamic-pituitary-adrenal axis, HPAA; autonomic nervous system, ANS) in children, it has yet to examine the extent to which biological reactivity predicts concurrent goal-directed behavior. Here, we employed a stressor paradigm that allowed concurrent assessment of both stress system reactivity and performance on a speeded-response task to investigate the links between biological reactivity and cognitive function under stress. We further investigated gender as a moderator given previous research suggesting that the ANS may be particularly predictive of behavior in males due to gender differences in socialization. In a sociodemographically diverse sample of young children (N = 58, M age = 5.38 yrs; 44% male), individual differences in sociodemographic covariates (age, household income), HPAA (i.e. cortisol), and ANS (i.e. respiratory sinus arrhythmia, RSA, indexing the parasympathetic branch; pre-ejection period, PEP, indexing the sympathetic branch) function were assessed as predictors of cognitive performance under stress. We hypothesized that higher income, older age, and greater cortisol reactivity would be associated with better performance overall, and flexible ANS responsivity (i.e. RSA withdrawal, PEP shortening) would be predictive of performance for males. Overall, females performed better than males. Two-group SEM analyses suggest that, for males, greater RSA withdrawal to the stressor was associated with better performance, while for females, older age, higher income, and greater cortisol reactivity were associated with better performance. Results highlight the relevance of stress system reactivity to cognitive performance under stress. Future research is needed to further elucidate for whom and in what situations biological reactivity predicts goal-directed behavior.

Facile synthesis of zwitterionic polymer-coated core-shell magnetic nanoparticles for highly specific capture of N-linked glycopeptides.

PubMed

Chen, Yajing; Xiong, Zhichao; Zhang, Lingyi; Zhao, Jiaying; Zhang, Quanqing; Peng, Li; Zhang, Weibing; Ye, Mingliang; Zou, Hanfa

2015-02-21

Highly selective and efficient capture of glycosylated proteins and peptides from complex biological samples is of profound significance for the discovery of disease biomarkers in biological systems. Recently, hydrophilic interaction liquid chromatography (HILIC)-based functional materials have been extensively utilized for glycopeptide enrichment. However, the low amount of immobilized hydrophilic groups on the affinity material has limited its specificity, detection sensitivity and binding capacity in the capture of glycopeptides. Herein, a novel affinity material was synthesized to improve the binding capacity and detection sensitivity for glycopeptides by coating a poly(2-(methacryloyloxy)ethyl)-dimethyl-(3-sulfopropyl) ammonium hydroxide (PMSA) shell onto Fe3O4@SiO2 nanoparticles, taking advantage of reflux-precipitation polymerization for the first time (denoted as Fe3O4@SiO2@PMSA). The thick polymer shell endows the nanoparticles with excellent hydrophilic property and several functional groups on the polymer chains. The resulting Fe3O4@SiO2@PMSA demonstrated an outstanding ability for glycopeptide enrichment with high selectivity, extremely high detection sensitivity (0.1 fmol), large binding capacity (100 mg g(-1)), high enrichment recovery (above 73.6%) and rapid magnetic separation. Furthermore, in the analysis of real complicated biological samples, 905 unique N-glycosylation sites from 458 N-glycosylated proteins were reliably identified in three replicate analyses of a 65 μg protein sample extracted from mouse liver, showing the great potential of Fe3O4@SiO2@PMSA in the detection and identification of low-abundance N-linked glycopeptides in biological samples.

Genes and pathways co-associated with the exposure to multiple drugs of abuse, including alcohol, amphetamine/methamphetamine, cocaine, marijuana, morphine, and/or nicotine: a review of proteomics analyses.

PubMed

Wang, Ju; Yuan, Wenji; Li, Ming D

2011-12-01

Drug addiction is a chronic neuronal disease. In recent years, proteomics technology has been widely used to assess the protein expression in the brain tissues of both animals and humans exposed to addictive drugs. Through this approach, a large number of proteins potentially involved in the etiology of drug addictions have been identified, which provide a valuable resource to study protein function, biochemical pathways, and networks related to the molecular mechanisms underlying drug dependence. In this article, we summarize the recent application of proteomics to profiling protein expression patterns in animal or human brain tissues after the administration of alcohol, amphetamine/methamphetamine, cocaine, marijuana, morphine/heroin/butorphanol, or nicotine. From available reports, we compiled a list of 497 proteins associated with exposure to one or more addictive drugs, with 160 being related to exposure to at least two abused drugs. A number of biochemical pathways and biological processes appear to be enriched among these proteins, including synaptic transmission and signaling pathways related to neuronal functions. The data included in this work provide a summary and extension of the proteomics studies on drug addiction. Furthermore, the proteins and biological processes highlighted here may provide valuable insight into the cellular activities and biological processes in neurons in the development of drug addiction.

Plant Omics Data Center: An Integrated Web Repository for Interspecies Gene Expression Networks with NLP-Based Curation

PubMed Central

Ohyanagi, Hajime; Takano, Tomoyuki; Terashima, Shin; Kobayashi, Masaaki; Kanno, Maasa; Morimoto, Kyoko; Kanegae, Hiromi; Sasaki, Yohei; Saito, Misa; Asano, Satomi; Ozaki, Soichi; Kudo, Toru; Yokoyama, Koji; Aya, Koichiro; Suwabe, Keita; Suzuki, Go; Aoki, Koh; Kubo, Yasutaka; Watanabe, Masao; Matsuoka, Makoto; Yano, Kentaro

2015-01-01

Comprehensive integration of large-scale omics resources such as genomes, transcriptomes and metabolomes will provide deeper insights into broader aspects of molecular biology. For better understanding of plant biology, we aim to construct a next-generation sequencing (NGS)-derived gene expression network (GEN) repository for a broad range of plant species. So far we have incorporated information about 745 high-quality mRNA sequencing (mRNA-Seq) samples from eight plant species (Arabidopsis thaliana, Oryza sativa, Solanum lycopersicum, Sorghum bicolor, Vitis vinifera, Solanum tuberosum, Medicago truncatula and Glycine max) from the public short read archive, digitally profiled the entire set of gene expression profiles, and drawn GENs by using correspondence analysis (CA) to take advantage of gene expression similarities. In order to understand the evolutionary significance of the GENs from multiple species, they were linked according to the orthology of each node (gene) among species. In addition to other gene expression information, functional annotation of the genes will facilitate biological comprehension. Currently we are improving the given gene annotations with natural language processing (NLP) techniques and manual curation. Here we introduce the current status of our analyses and the web database, PODC (Plant Omics Data Center; http://bioinf.mind.meiji.ac.jp/podc/), now open to the public, providing GENs, functional annotations and additional comprehensive omics resources. PMID:25505034

Genome-wide evolutionary characterization and expression analyses of major latex protein (MLP) family genes in Vitis vinifera.

PubMed

Zhang, Ningbo; Li, Ruimin; Shen, Wei; Jiao, Shuzhen; Zhang, Junxiang; Xu, Weirong

2018-04-27

The major latex protein/ripening-related protein (MLP/RRP) subfamily is known to be involved in a wide range of biological processes of plant development and various stress responses. However, the biological function of MLP/RRP proteins is still far from being clear and identification of them may provide important clues for understanding their roles. Here, we report a genome-wide evolutionary characterization and gene expression analysis of the MLP family in European Vitis species. A total of 14 members, was found in the grape genome, all of which are located on chromosome 1, where are predominantly arranged in tandem clusters. We have noticed, most surprisingly, promoter-sharing by several non-identical but highly similar gene members to a greater extent than expected by chance. Synteny analysis between the grape and Arabidopsis thaliana genomes suggested that 3 grape MLP genes arose before the divergence of the two species. Phylogenetic analysis provided further insights into the evolutionary relationship between the genes, as well as their putative functions, and tissue-specific expression analysis suggested distinct biological roles for different members. Our expression data suggested a couple of candidate genes involved in abiotic stresses and phytohormone responses. The present work provides new insight into the evolution and regulation of Vitis MLP genes, which represent targets for future studies and inclusion in tolerance-related molecular breeding programs.

Functions in Biological Kind Classification

ERIC Educational Resources Information Center

Lombrozo, Tania; Rehder, Bob

2012-01-01

Biological traits that serve functions, such as a zebra's coloration (for camouflage) or a kangaroo's tail (for balance), seem to have a special role in conceptual representations for biological kinds. In five experiments, we investigate whether and why functional features are privileged in biological kind classification. Experiment 1…

Robust extraction of functional signals from gene set analysis using a generalized threshold free scoring function

PubMed Central

2009-01-01

Background A central task in contemporary biosciences is the identification of biological processes showing response in genome-wide differential gene expression experiments. Two types of analysis are common. Either, one generates an ordered list based on the differential expression values of the probed genes and examines the tail areas of the list for over-representation of various functional classes. Alternatively, one monitors the average differential expression level of genes belonging to a given functional class. So far these two types of method have not been combined. Results We introduce a scoring function, Gene Set Z-score (GSZ), for the analysis of functional class over-representation that combines two previous analysis methods. GSZ encompasses popular functions such as correlation, hypergeometric test, Max-Mean and Random Sets as limiting cases. GSZ is stable against changes in class size as well as across different positions of the analysed gene list in tests with randomized data. GSZ shows the best overall performance in a detailed comparison to popular functions using artificial data. Likewise, GSZ stands out in a cross-validation of methods using split real data. A comparison of empirical p-values further shows a strong difference in favour of GSZ, which clearly reports better p-values for top classes than the other methods. Furthermore, GSZ detects relevant biological themes that are missed by the other methods. These observations also hold when comparing GSZ with popular program packages. Conclusion GSZ and improved versions of earlier methods are a useful contribution to the analysis of differential gene expression. The methods and supplementary material are available from the website http://ekhidna.biocenter.helsinki.fi/users/petri/public/GSZ/GSZscore.html. PMID:19775443

Plants and climate change: complexities and surprises.

PubMed

Parmesan, Camille; Hanley, Mick E

2015-11-01

Anthropogenic climate change (ACC) will influence all aspects of plant biology over coming decades. Many changes in wild species have already been well-documented as a result of increased atmospheric CO2 concentrations, warming climate and changing precipitation regimes. A wealth of available data has allowed the use of meta-analyses to examine plant-climate interactions on more sophisticated levels than before. These analyses have revealed major differences in plant response among groups, e.g. with respect to functional traits, taxonomy, life-history and provenance. Interestingly, these meta-analyses have also exposed unexpected mismatches between theory, experimental, and observational studies. We reviewed the literature on species' responses to ACC, finding ∼42 % of 4000 species studied globally are plants (primarily terrestrial). We review impacts on phenology, distributions, ecophysiology, regeneration biology, plant-plant and plant-herbivore interactions, and the roles of plasticity and evolution. We focused on apparent deviations from expectation, and highlighted cases where more sophisticated analyses revealed that unexpected changes were, in fact, responses to ACC. We found that conventionally expected responses are generally well-understood, and that it is the aberrant responses that are now yielding greater insight into current and possible future impacts of ACC. We argue that inconclusive, unexpected, or counter-intuitive results should be embraced in order to understand apparent disconnects between theory, prediction, and observation. We highlight prime examples from the collection of papers in this Special Issue, as well as general literature. We found use of plant functional groupings/traits had mixed success, but that some underutilized approaches, such as Grime's C/S/R strategies, when incorporated, have improved understanding of observed responses. Despite inherent difficulties, we highlight the need for ecologists to conduct community-level experiments in systems that replicate multiple aspects of ACC. Specifically, we call for development of coordinating experiments across networks of field sites, both natural and man-made. © The Author 2015. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Developmental fMRI study of episodic verbal memory encoding in children.

PubMed

Maril, A; Davis, P E; Koo, J J; Reggev, N; Zuckerman, M; Ehrenfeld, L; Mulkern, R V; Waber, D P; Rivkin, M J

2010-12-07

Understanding the maturation and organization of cognitive function in the brain is a central objective of both child neurology and developmental cognitive neuroscience. This study focuses on episodic memory encoding of verbal information by children, a cognitive domain not previously studied using fMRI. Children from 7 to 19 years of age were scanned at 1.5-T field strength using event-related fMRI while performing a novel verbal memory encoding paradigm in which words were incidentally encoded. A subsequent memory analysis was performed. SPM2 was utilized for whole brain and region-of-interest analyses of data. Both whole-sample intragroup analyses and intergroup analyses of the sample divided into 2 subgroups by age were conducted. Importantly, behavioral memory performance was equal across the age range of children studied. Encoding-related activation in the left hippocampus and bilateral basal ganglia declined as age increased. In addition, while robust blood oxygen level-dependent signal was found in left prefrontal cortex with task performance, no encoding-related age-modulated prefrontal activation was observed in either hemisphere. These data are consistent with a developmental pattern of verbal memory encoding function in which left hippocampal and bilateral basal ganglionic activations are more robust earlier in childhood but then decline with age. No encoding-related activation was found in prefrontal cortex which may relate to this region's recognized delay in biologic maturation in humans. These data represent the first fMRI demonstration of verbal encoding function in children and are relevant developmentally and clinically.

Measurements of the talus in the assessment of population affinity.

PubMed

Bidmos, Mubarak A; Dayal, Manisha R; Adegboye, Oyelola A

2018-06-01

As part of their routine work, forensic anthropologists are expected to report population affinity as part of the biological profile of an individual. The skull is the most widely used bone for the estimation of population affinity but it is not always present in a forensic case. Thus, other bones that preserve well have been shown to give a good indication of either the sex or population affinity of an individual. In this study, the potential of measurements of the talus was investigated for the purpose of estimating population affinity in South Africans. Nine measurements from two hundred and twenty tali of South African Africans (SAA) and South African Whites (SAW) from the Raymond A. Dart Collection of Human Skeletons were used. Direct and step-wise discriminant function and logistic regression analyses were carried out using SPSS and SAS. Talar length was the best single variable for discriminating between these two groups for males while in females the head height was the best single predictor. Average accuracies for correct population affinity classification using logistic regression analysis were higher than those obtained from discriminant function analysis. This study was the first of its type to employ discriminant function analyses and logistic regression analyses to estimate the population affinity of an individual from the talus. Thus these equations can now be used by South African anthropologists when estimating the population affinity of dismembered or damaged or incomplete skeletal remains of SAA and SAW. Copyright © 2018 Elsevier B.V. All rights reserved.

Comparative analyses of quaternary arrangements in homo-oligomeric proteins in superfamilies: Functional implications.

PubMed

Sudha, Govindarajan; Srinivasan, Narayanaswamy

2016-09-01

A comprehensive analysis of the quaternary features of distantly related homo-oligomeric proteins is the focus of the current study. This study has been performed at the levels of quaternary state, symmetry, and quaternary structure. Quaternary state and quaternary structure refers to the number of subunits and spatial arrangements of subunits, respectively. Using a large dataset of available 3D structures of biologically relevant assemblies, we show that only 53% of the distantly related homo-oligomeric proteins have the same quaternary state. Considering these homologous homo-oligomers with the same quaternary state, conservation of quaternary structures is observed only in 38% of the pairs. In 36% of the pairs of distantly related homo-oligomers with different quaternary states the larger assembly in a pair shows high structural similarity with the entire quaternary structure of the related protein with lower quaternary state and it is referred as "Russian doll effect." The differences in quaternary state and structure have been suggested to contribute to the functional diversity. Detailed investigations show that even though the gross functions of many distantly related homo-oligomers are the same, finer level differences in molecular functions are manifested by differences in quaternary states and structures. Comparison of structures of biological assemblies in distantly and closely related homo-oligomeric proteins throughout the study differentiates the effects of sequence divergence on the quaternary structures and function. Knowledge inferred from this study can provide insights for improved protein structure classification and function prediction of homo-oligomers. Proteins 2016; 84:1190-1202. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking.

PubMed

Ballester, Pedro J; Mitchell, John B O

2010-05-01

Accurately predicting the binding affinities of large sets of diverse protein-ligand complexes is an extremely challenging task. The scoring functions that attempt such computational prediction are essential for analysing the outputs of molecular docking, which in turn is an important technique for drug discovery, chemical biology and structural biology. Each scoring function assumes a predetermined theory-inspired functional form for the relationship between the variables that characterize the complex, which also include parameters fitted to experimental or simulation data and its predicted binding affinity. The inherent problem of this rigid approach is that it leads to poor predictivity for those complexes that do not conform to the modelling assumptions. Moreover, resampling strategies, such as cross-validation or bootstrapping, are still not systematically used to guard against the overfitting of calibration data in parameter estimation for scoring functions. We propose a novel scoring function (RF-Score) that circumvents the need for problematic modelling assumptions via non-parametric machine learning. In particular, Random Forest was used to implicitly capture binding effects that are hard to model explicitly. RF-Score is compared with the state of the art on the demanding PDBbind benchmark. Results show that RF-Score is a very competitive scoring function. Importantly, RF-Score's performance was shown to improve dramatically with training set size and hence the future availability of more high-quality structural and interaction data is expected to lead to improved versions of RF-Score. pedro.ballester@ebi.ac.uk; jbom@st-andrews.ac.uk Supplementary data are available at Bioinformatics online.

Identifying functional groups for response to disturbance in an abandoned pasture

NASA Astrophysics Data System (ADS)

Lavorel, Sandra; Touzard, Blaise; Lebreton, Jean-Dominique; Clément, Bernard

1998-06-01

In an abandoned pasture in Brittany, we compared artificial small-scale disturbances to natural disturbances by wild boar and undisturbed vegetation. We developed a multivariate statistical approach which analyses how species biological attributes explain the response of community composition to disturbances. This technique, which reconciles the inductive and deductive approaches for functional classifications, identifies groups of species with similar responses to disturbance and characterizes their biological profiles. After 5 months of recolonization, artificial disturbances had a greater species richness than undisturbed vegetation as a result of recruitment of new species without the exclusion of pre-existing matrix species. Species morphology, described by canopy structure, canopy height and lateral spread, explained a large part (16 %) of community response to disturbance. Regeneration strategies, described by life history, seed mass, dispersal agent, dormancy and the existence of vegetative multiplication, explained a smaller part of community response to disturbance (8 %). Artificial disturbances were characterized by therophyte and compact rosettes with moderately dormant seeds, including a number of Asteraceae and other early successional species. Natural disturbances were colonized by leafy guerrilla species without seed dormancy. Few species were tightly related to undisturbed vegetation and were essentially grasses with a phalanx rosette morphology. The functional classification obtained is consistent with the classification of the community into fugitives, regenerators and persistors. These groups are structured according to Grubb's model for temperate grasslands, with regenerators and persistors in the matrix and fugitives taking advantage of gaps open by small-scale disturbances. The conjunction of functional diversity and species diversity within functional groups is the key to resilience to disturbance, an important ecosystem function.

Legume small GTPases and their role in the establishment of symbiotic associations with Rhizobium spp

PubMed Central

Memon, Abdul R

2009-01-01

Small GTP-binding genes act as molecular switches regulating myriad of cellular processes including vesicle-mediated intracellular trafficking, signal transduction, cytoskeletal reorganization and cell division in plants and animals. Even though these genes are well conserved both functionally and sequentially across whole Eukaryotae, occasional lineage-specific diversification in some plant species in terms of both functional and expressional characteristics have been reported. Hence, comparative phyletic and correlative functional analyses of legume small GTPases homologs with the genes from other Metazoa and Embryophyta species would be very beneficial for gleaning out the small GTPases that could have specialized in legume-specific processes; e.g., nodulation. The completion of genome sequences of two model legumes, Medicago truncatula and Lotus japonicus will significantly improve our knowledge about mechanism of biological processes taking place in legume-rhizobia symbiotic associations. Besides, the need for molecular switches coordinating busy cargo-trafficking between symbiosis partners would suggest a possible subfunctionalization of small GTPases in Fabaceae for these functions. Therefore, more detailed investigation into the functional characteristics of legume small GTPases would be helpful for the illumination of the events initialized with the perception of bacteria by host, followed by the formation of infection thread and the engulfment of rhizobial bacteria, and end with the senescence of nitrogen-fixing organelles, nodules. In summary, a more thorough functional and evolutionary characterization of small GTPases across the main lineages of Embryophyta is significant for better comprehension of evolutionary history of Plantae, that is because, these genes are associated with multitude of vital biological processes including organogenesis. PMID:19794839

Does changing pain-related knowledge reduce pain and improve function through changes in catastrophizing?

PubMed

Lee, Hopin; McAuley, James H; Hübscher, Markus; Kamper, Steven J; Traeger, Adrian C; Moseley, G Lorimer

2016-04-01

Evidence from randomized controlled studies shows that reconceptualizing pain improves patients' knowledge of pain biology, reduces catastrophizing thoughts, and improves pain and function. However, causal relationships between these variables remain untested. It is hypothesized that reductions in catastrophizing could mediate the relationship between improvements in pain knowledge and improvements in pain and function. To test this causal mechanism, we conducted longitudinal mediation analyses on a cohort of 799 patients who were exposed to a pain education intervention. Patients provided responses to the neurophysiology of pain questionnaire, catastrophic thoughts about pain scale, visual analogue pain scale, and the patient specific functional scale, at baseline, 1-month, 6-month, and 12-month follow-up. With adjustment for potential confounding variables, an improvement in pain biology knowledge was significantly associated with a reduction in pain intensity (total effect = -2.20, 95% confidence interval [CI] = -2.96 to -1.44). However, this effect was not mediated by a reduction in catastrophizing (indirect effect = -0.16, 95% CI = -0.36 to 0.02). This might be due to a weak, nonsignificant relationship between changes in catastrophizing and pain intensity (path b = 0.19, 95% CI = -0.03 to 0.41). Similar trends were found in models with function as the outcome. Our findings indicate that change in catastrophizing did not mediate the effect of pain knowledge acquisition on change in pain or function. The strength of this conclusion is moderated, however, if patient-clinician relational factors are conceptualized as a consequence of catastrophizing, rather than a cause.

Information processing in bacteria: memory, computation, and statistical physics: a key issues review

NASA Astrophysics Data System (ADS)

Lan, Ganhui; Tu, Yuhai

2016-05-01

Living systems have to constantly sense their external environment and adjust their internal state in order to survive and reproduce. Biological systems, from as complex as the brain to a single E. coli cell, have to process these data in order to make appropriate decisions. How do biological systems sense external signals? How do they process the information? How do they respond to signals? Through years of intense study by biologists, many key molecular players and their interactions have been identified in different biological machineries that carry out these signaling functions. However, an integrated, quantitative understanding of the whole system is still lacking for most cellular signaling pathways, not to say the more complicated neural circuits. To study signaling processes in biology, the key thing to measure is the input-output relationship. The input is the signal itself, such as chemical concentration, external temperature, light (intensity and frequency), and more complex signals such as the face of a cat. The output can be protein conformational changes and covalent modifications (phosphorylation, methylation, etc), gene expression, cell growth and motility, as well as more complex output such as neuron firing patterns and behaviors of higher animals. Due to the inherent noise in biological systems, the measured input-output dependence is often noisy. These noisy data can be analysed by using powerful tools and concepts from information theory such as mutual information, channel capacity, and the maximum entropy hypothesis. This information theory approach has been successfully used to reveal the underlying correlations between key components of biological networks, to set bounds for network performance, and to understand possible network architecture in generating observed correlations. Although the information theory approach provides a general tool in analysing noisy biological data and may be used to suggest possible network architectures in preserving information, it does not reveal the underlying mechanism that leads to the observed input-output relationship, nor does it tell us much about which information is important for the organism and how biological systems use information to carry out specific functions. To do that, we need to develop models of the biological machineries, e.g. biochemical networks and neural networks, to understand the dynamics of biological information processes. This is a much more difficult task. It requires deep knowledge of the underlying biological network—the main players (nodes) and their interactions (links)—in sufficient detail to build a model with predictive power, as well as quantitative input-output measurements of the system under different perturbations (both genetic variations and different external conditions) to test the model predictions to guide further development of the model. Due to the recent growth of biological knowledge thanks in part to high throughput methods (sequencing, gene expression microarray, etc) and development of quantitative in vivo techniques such as various florescence technology, these requirements are starting to be realized in different biological systems. The possible close interaction between quantitative experimentation and theoretical modeling has made systems biology an attractive field for physicists interested in quantitative biology. In this review, we describe some of the recent work in developing a quantitative predictive model of bacterial chemotaxis, which can be considered as the hydrogen atom of systems biology. Using statistical physics approaches, such as the Ising model and Langevin equation, we study how bacteria, such as E. coli, sense and amplify external signals, how they keep a working memory of the stimuli, and how they use these data to compute the chemical gradient. In particular, we will describe how E. coli cells avoid cross-talk in a heterogeneous receptor cluster to keep a ligand-specific memory. We will also study the thermodynamic costs of adaptation for cells to maintain an accurate memory. The statistical physics based approach described here should be useful in understanding design principles for cellular biochemical circuits in general.

Information processing in bacteria: memory, computation, and statistical physics: a key issues review.

PubMed

Lan, Ganhui; Tu, Yuhai

2016-05-01

Living systems have to constantly sense their external environment and adjust their internal state in order to survive and reproduce. Biological systems, from as complex as the brain to a single E. coli cell, have to process these data in order to make appropriate decisions. How do biological systems sense external signals? How do they process the information? How do they respond to signals? Through years of intense study by biologists, many key molecular players and their interactions have been identified in different biological machineries that carry out these signaling functions. However, an integrated, quantitative understanding of the whole system is still lacking for most cellular signaling pathways, not to say the more complicated neural circuits. To study signaling processes in biology, the key thing to measure is the input-output relationship. The input is the signal itself, such as chemical concentration, external temperature, light (intensity and frequency), and more complex signals such as the face of a cat. The output can be protein conformational changes and covalent modifications (phosphorylation, methylation, etc), gene expression, cell growth and motility, as well as more complex output such as neuron firing patterns and behaviors of higher animals. Due to the inherent noise in biological systems, the measured input-output dependence is often noisy. These noisy data can be analysed by using powerful tools and concepts from information theory such as mutual information, channel capacity, and the maximum entropy hypothesis. This information theory approach has been successfully used to reveal the underlying correlations between key components of biological networks, to set bounds for network performance, and to understand possible network architecture in generating observed correlations. Although the information theory approach provides a general tool in analysing noisy biological data and may be used to suggest possible network architectures in preserving information, it does not reveal the underlying mechanism that leads to the observed input-output relationship, nor does it tell us much about which information is important for the organism and how biological systems use information to carry out specific functions. To do that, we need to develop models of the biological machineries, e.g. biochemical networks and neural networks, to understand the dynamics of biological information processes. This is a much more difficult task. It requires deep knowledge of the underlying biological network-the main players (nodes) and their interactions (links)-in sufficient detail to build a model with predictive power, as well as quantitative input-output measurements of the system under different perturbations (both genetic variations and different external conditions) to test the model predictions to guide further development of the model. Due to the recent growth of biological knowledge thanks in part to high throughput methods (sequencing, gene expression microarray, etc) and development of quantitative in vivo techniques such as various florescence technology, these requirements are starting to be realized in different biological systems. The possible close interaction between quantitative experimentation and theoretical modeling has made systems biology an attractive field for physicists interested in quantitative biology. In this review, we describe some of the recent work in developing a quantitative predictive model of bacterial chemotaxis, which can be considered as the hydrogen atom of systems biology. Using statistical physics approaches, such as the Ising model and Langevin equation, we study how bacteria, such as E. coli, sense and amplify external signals, how they keep a working memory of the stimuli, and how they use these data to compute the chemical gradient. In particular, we will describe how E. coli cells avoid cross-talk in a heterogeneous receptor cluster to keep a ligand-specific memory. We will also study the thermodynamic costs of adaptation for cells to maintain an accurate memory. The statistical physics based approach described here should be useful in understanding design principles for cellular biochemical circuits in general.

Biological life-support systems

NASA Technical Reports Server (NTRS)

Shepelev, Y. Y.

1975-01-01

The establishment of human living environments by biologic methods, utilizing the appropriate functions of autotrophic and heterotrophic organisms is examined. Natural biologic systems discussed in terms of modeling biologic life support systems (BLSS), the structure of biologic life support systems, and the development of individual functional links in biologic life support systems are among the factors considered. Experimental modeling of BLSS in order to determine functional characteristics, mechanisms by which stability is maintained, and principles underlying control and regulation is also discussed.

Trade-offs in thermal adaptation: the need for a molecular to ecological integration.

PubMed

Pörtner, Hans O; Bennett, Albert F; Bozinovic, Francisco; Clarke, Andrew; Lardies, Marco A; Lucassen, Magnus; Pelster, Bernd; Schiemer, Fritz; Stillman, Jonathon H

2006-01-01

Through functional analyses, integrative physiology is able to link molecular biology with ecology as well as evolutionary biology and is thereby expected to provide access to the evolution of molecular, cellular, and organismic functions; the genetic basis of adaptability; and the shaping of ecological patterns. This paper compiles several exemplary studies of thermal physiology and ecology, carried out at various levels of biological organization from single genes (proteins) to ecosystems. In each of those examples, trade-offs and constraints in thermal adaptation are addressed; these trade-offs and constraints may limit species' distribution and define their level of fitness. For a more comprehensive understanding, the paper sets out to elaborate the functional and conceptual connections among these independent studies and the various organizational levels addressed. This effort illustrates the need for an overarching concept of thermal adaptation that encompasses molecular, organellar, cellular, and whole-organism information as well as the mechanistic links between fitness, ecological success, and organismal physiology. For this data, the hypothesis of oxygen- and capacity-limited thermal tolerance in animals provides such a conceptual framework and allows interpreting the mechanisms of thermal limitation of animals as relevant at the ecological level. While, ideally, evolutionary studies over multiple generations, illustrated by an example study in bacteria, are necessary to test the validity of such complex concepts and underlying hypotheses, animal physiology frequently is constrained to functional studies within one generation. Comparisons of populations in a latitudinal cline, closely related species from different climates, and ontogenetic stages from riverine clines illustrate how evolutionary information can still be gained. An understanding of temperature-dependent shifts in energy turnover, associated with adjustments in aerobic scope and performance, will result. This understanding builds on a mechanistic analysis of the width and location of thermal windows on the temperature scale and also on study of the functional properties of relevant proteins and associated gene expression mechanisms.

Ecosystem function in waste stabilisation ponds: Improving water quality through a better understanding of biophysical coupling

NASA Astrophysics Data System (ADS)

Ghadouani, Anas; Reichwaldt, Elke S.; Coggins, Liah X.; Ivey, Gregory N.; Ghisalberti, Marco; Zhou, Wenxu; Laurion, Isabelle; Chua, Andrew

2014-05-01

Wastewater stabilisation ponds (WSPs) are highly productive systems designed to treat wastewater using only natural biological and chemical processes. Phytoplankton, microbial communities and hydraulics play important roles for ecosystem functionality of these pond systems. Although WSPs have been used for many decades, they are still considered as 'black box' systems as very little is known about the fundamental ecological processes which occur within them. However, a better understanding of how these highly productive ecosystems function is particularly important for hydrological processes, as treated wastewater is commonly discharged into streams, rivers, and oceans, and subject to strict water quality guidelines. WSPs are known to operate at different levels of efficiency, and treatment efficiency of WSPs is dependent on physical (flow characteristics and sludge accumulation and distribution) and biological (microbial and phytoplankton communities) characteristics. Thus, it is important to gain a better understanding of the role and influence of pond hydraulics and vital microbial communities on pond performance and WSP functional stability. The main aim of this study is to investigate the processes leading to differences in treatment performance of WSPs. This study uses a novel and innovative approach to understand these factors by combining flow cytometry and metabolomics to investigate various biochemical characteristics, including the metabolite composition and microbial community within WSPs. The results of these analyses will then be combined with results from the characterisation of pond hydrodynamics and hydraulic performance, which will be performed using advanced hydrodynamic modelling and advanced sludge profiling technology. By understanding how hydrodynamic and biological processes influence each other and ecosystem function and stability in WSPs, we will be able to propose ways to improve the quality of the treatment using natural processes, with less reliance on chemical treatment. This will in turn contribute to the reduction in the cost of operation, but more importantly reduce the impact on the environment (i.e., discharge, GHGs), and increase water quality and the potential for water reuse worldwide.

Spatial and temporal variation of life-history traits documented using capture-mark-recapture methods in the vector snail Bulinus truncatus.

PubMed

Chlyeh, G; Henry, P Y; Jarne, P

2003-09-01

The population biology of the schistosome-vector snail Bulinus truncatus was studied in an irrigation area near Marrakech, Morocco, using demographic approaches, in order to estimate life-history parameters. The survey was conducted using 2 capture-mark-recapture analyses in 2 separate sites from the irrigation area, the first one in 1999 and the second one in 2000. Individuals larger than 5 mm were considered. The capture probability varied through time and space in both analyses. Apparent survival (from 0.7 to 1 per period of 2-3 days) varied with time and space (a series of sinks was considered), as well as a square function of size. These results suggest variation in population intrinsic rate of increase. They also suggest that results from more classical analyses of population demography, aiming, for example at estimating population size, should be interpreted with caution. Together with other results obtained in the same irrigation area, they also lead to some suggestions for population control.

GenomeHubs: simple containerized setup of a custom Ensembl database and web server for any species

PubMed Central

Kumar, Sujai; Stevens, Lewis; Blaxter, Mark

2017-01-01

Abstract As the generation and use of genomic datasets is becoming increasingly common in all areas of biology, the need for resources to collate, analyse and present data from one or more genome projects is becoming more pressing. The Ensembl platform is a powerful tool to make genome data and cross-species analyses easily accessible through a web interface and a comprehensive application programming interface. Here we introduce GenomeHubs, which provide a containerized environment to facilitate the setup and hosting of custom Ensembl genome browsers. This simplifies mirroring of existing content and import of new genomic data into the Ensembl database schema. GenomeHubs also provide a set of analysis containers to decorate imported genomes with results of standard analyses and functional annotations and support export to flat files, including EMBL format for submission of assemblies and annotations to International Nucleotide Sequence Database Collaboration. Database URL: http://GenomeHubs.org PMID:28605774

Integrating cell biology and proteomic approaches in plants.

PubMed

Takáč, Tomáš; Šamajová, Olga; Šamaj, Jozef

2017-10-03

Significant improvements of protein extraction, separation, mass spectrometry and bioinformatics nurtured advancements of proteomics during the past years. The usefulness of proteomics in the investigation of biological problems can be enhanced by integration with other experimental methods from cell biology, genetics, biochemistry, pharmacology, molecular biology and other omics approaches including transcriptomics and metabolomics. This review aims to summarize current trends integrating cell biology and proteomics in plant science. Cell biology approaches are most frequently used in proteomic studies investigating subcellular and developmental proteomes, however, they were also employed in proteomic studies exploring abiotic and biotic stress responses, vesicular transport, cytoskeleton and protein posttranslational modifications. They are used either for detailed cellular or ultrastructural characterization of the object subjected to proteomic study, validation of proteomic results or to expand proteomic data. In this respect, a broad spectrum of methods is employed to support proteomic studies including ultrastructural electron microscopy studies, histochemical staining, immunochemical localization, in vivo imaging of fluorescently tagged proteins and visualization of protein-protein interactions. Thus, cell biological observations on fixed or living cell compartments, cells, tissues and organs are feasible, and in some cases fundamental for the validation and complementation of proteomic data. Validation of proteomic data by independent experimental methods requires development of new complementary approaches. Benefits of cell biology methods and techniques are not sufficiently highlighted in current proteomic studies. This encouraged us to review most popular cell biology methods used in proteomic studies and to evaluate their relevance and potential for proteomic data validation and enrichment of purely proteomic analyses. We also provide examples of representative studies combining proteomic and cell biology methods for various purposes. Integrating cell biology approaches with proteomic ones allow validation and better interpretation of proteomic data. Moreover, cell biology methods remarkably extend the knowledge provided by proteomic studies and might be fundamental for the functional complementation of proteomic data. This review article summarizes current literature linking proteomics with cell biology. Copyright © 2017 Elsevier B.V. All rights reserved.

Transplanting Sensitized Kidney Transplant Patients With Equivalent Outcomes Utilizing Stringent HLA Crossmatching.

PubMed

Rohan, Vinayak S; Taber, David J; Moussa, Omar; Pilch, Nicole A; Denmark, Signe; Meadows, Holly B; McGillicuddy, John W; Chavin, Kenneth D; Baliga, Prabhakar K; Bratton, Charles F

2017-02-01

Elevated panel reactive antibody levels have been traditionally associated with increased acute rejection rate and decreased long-term graft survival after kidney transplant. In this study, our objective was to determine patient and allograft outcomes in sensitized kidney transplant recipients with advanced HLA antibody detection and stringent protein sequence epitope analyses. This was a subanalysis of a prospective, risk-stratified randomized controlled trial that compared interleukin 2 receptor antagonist to rabbit antithymocyte globulin induction in 200 kidney transplant recipients, examining outcomes based on panel reactive antibody levels of < 20% (low) versus ≥ 20% (high, sensitized). The study was conducted between February 2009 and July 2011. All patients underwent solid-phase single antigen bead assays to detect HLA antibodies and stringent HLA epitope analyses with protein sequence alignment for virtual crossmatching. Delayed graft function, acute rejection rates, and graft loss were the main outcomes measured. Both the low (134 patients) and high (66 patients) panel reactive antibody level cohorts had equivalent induction and maintenance immunosuppression. Patients in the high-level group were more likely to be female (P < .001), African American (P < .001), and received a kidney from a deceased donor (P = .004). Acute rejection rates were similar between the low (rate of 8%) and high (rate of 9%) panel reactive antibody groups (P = .783). Delayed graft function, borderline rejection, graft loss, and death were not different between groups. Multivariate analyses demonstrated delayed graft function to be the strongest predictor of acute rejection (odds ratio, 5.7; P = .005); panel reactive antibody level, as a continuous variable, had no significant correlation with acute rejection (C statistic, 0.48; P = .771). Appropriate biologic matching with single antigen bead assays and stringent epitope analyses provided excellent outcomes in sensitized patients regardless of the induction therapy choice.

Functional and phylogenetic evidence of a bacterial origin for the first enzyme in sphingolipid biosynthesis in a phylum of eukaryotic protozoan parasites.

PubMed

Mina, John G; Thye, Julie K; Alqaisi, Amjed Q I; Bird, Louise E; Dods, Robert H; Grøftehauge, Morten K; Mosely, Jackie A; Pratt, Steven; Shams-Eldin, Hosam; Schwarz, Ralph T; Pohl, Ehmke; Denny, Paul W

2017-07-21

Toxoplasma gondii is an obligate, intracellular eukaryotic apicomplexan protozoan parasite that can cause fetal damage and abortion in both animals and humans. Sphingolipids are essential and ubiquitous components of eukaryotic membranes that are both synthesized and scavenged by the Apicomplexa. Here we report the identification, isolation, and analyses of the Toxoplasma serine palmitoyltransferase, an enzyme catalyzing the first and rate-limiting step in sphingolipid biosynthesis: the condensation of serine and palmitoyl-CoA. In all eukaryotes analyzed to date, serine palmitoyltransferase is a highly conserved heterodimeric enzyme complex. However, biochemical and structural analyses demonstrated the apicomplexan orthologue to be a functional, homodimeric serine palmitoyltransferase localized to the endoplasmic reticulum. Furthermore, phylogenetic studies indicated that it was evolutionarily related to the prokaryotic serine palmitoyltransferase, identified in the Sphingomonadaceae as a soluble homodimeric enzyme. Therefore this enzyme, conserved throughout the Apicomplexa, is likely to have been obtained via lateral gene transfer from a prokaryote. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Lipid droplet biology and evolution illuminated by the characterization of a novel perilipin in teleost fish

PubMed Central

Granneman, James G; Kimler, Vickie A; Zhang, Huamei; Ye, Xiangqun; Luo, Xixia; Postlethwait, John H; Thummel, Ryan

2017-01-01

Perilipin (PLIN) proteins constitute an ancient family important in lipid droplet (LD) formation and triglyceride metabolism. We identified an additional PLIN clade (plin6) that is unique to teleosts and can be traced to the two whole genome duplications that occurred early in vertebrate evolution. Plin6 is highly expressed in skin xanthophores, which mediate red/yellow pigmentation and trafficking, but not in tissues associated with lipid metabolism. Biochemical and immunochemical analyses demonstrate that zebrafish Plin6 protein targets the surface of pigment-containing carotenoid droplets (CD). Protein kinase A (PKA) activation, which mediates CD dispersion in xanthophores, phosphorylates Plin6 on conserved residues. Knockout of plin6 in zebrafish severely impairs the ability of CD to concentrate carotenoids and prevents tight clustering of CD within carotenoid bodies. Ultrastructural and functional analyses indicate that LD and CD are homologous structures, and that Plin6 was functionalized early in vertebrate evolution for concentrating and trafficking pigment. DOI: http://dx.doi.org/10.7554/eLife.21771.001 PMID:28244868

Growth, density functional theory (DFT) and spectral studies on L-2-aminobutyric acid -biologically active material

NASA Astrophysics Data System (ADS)

Usha, C.; Santhakumari, R.; Meenakshi, R.; Jayasree, R.; Bhuvaneswari, M.

2017-12-01

Single crystal of L-2-aminobutyric acid (ABA) was grown from water by slow evaporation at room temperature. The crystalline nature of the grown crystal was confirmed using powder X-ray diffraction studies. The grown crystal was subjected to FT-IR, FT-Raman, 1H NMR and 13C NMR spectral analyses to confirm the presence of functional group and molecular structure respectively. Thermal properties were investigated by thermogravimetric and differential thermal analyses. The range and percentage of optical transmission was ascertained by recording UV-vis-NIR spectrum. The electronic charge distribution and reactivity of the molecules within the crystal were studied by HOMO and LUMO analysis and the molecular electrostatic potential (MEP) of the grown crystal was performed using the B3LYP method. The anti-bacterial activities of the crystal were performed by disk diffusion method against the standard bacteria E. coli. The crystal exhibits good anti-bacterial activity. Second harmonic generation efficiency of the powdered ABA crystal was tested using Nd:YAG laser and it is found to be ∼3.3 times that of potassium dihydrogen orthophosphate.

Protein Discovery: Combined Transcriptomic and Proteomic Analyses of Venom from the Endoparasitoid Cotesia chilonis (Hymenoptera: Braconidae)

PubMed Central

Teng, Zi-Wen; Xiong, Shi-Jiao; Xu, Gang; Gan, Shi-Yu; Chen, Xuan; Stanley, David; Yan, Zhi-Chao; Ye, Gong-Yin; Fang, Qi

2017-01-01

Many species of endoparasitoid wasps provide biological control services in agroecosystems. Although there is a great deal of information on the ecology and physiology of host/parasitoid interactions, relatively little is known about the protein composition of venom and how specific venom proteins influence physiological systems within host insects. This is a crucial gap in our knowledge because venom proteins act in modulating host physiology in ways that favor parasitoid development. Here, we identified 37 possible venom proteins from the polydnavirus-carrying endoparasitoid Cotesia chilonis by combining transcriptomic and proteomic analyses. The most abundant proteins were hydrolases, such as proteases, peptidases, esterases, glycosyl hydrolase, and endonucleases. Some components are classical parasitoid venom proteins with known functions, including extracellular superoxide dismutase 3, serine protease inhibitor and calreticulin. The venom contains novel proteins, not recorded from any other parasitoid species, including tolloid-like proteins, chitooligosaccharidolytic β-N-acetylglucosaminidase, FK506-binding protein 14, corticotropin-releasing factor-binding protein and vascular endothelial growth factor receptor 2. These new data generate hypotheses and provide a platform for functional analysis of venom components. PMID:28417942

HTS-Net: An integrated regulome-interactome approach for establishing network regulation models in high-throughput screenings

PubMed Central

Rioualen, Claire; Da Costa, Quentin; Chetrit, Bernard; Charafe-Jauffret, Emmanuelle; Ginestier, Christophe

2017-01-01

High-throughput RNAi screenings (HTS) allow quantifying the impact of the deletion of each gene in any particular function, from virus-host interactions to cell differentiation. However, there has been less development for functional analysis tools dedicated to RNAi analyses. HTS-Net, a network-based analysis program, was developed to identify gene regulatory modules impacted in high-throughput screenings, by integrating transcription factors-target genes interaction data (regulome) and protein-protein interaction networks (interactome) on top of screening z-scores. HTS-Net produces exhaustive HTML reports for results navigation and exploration. HTS-Net is a new pipeline for RNA interference screening analyses that proves better performance than simple gene rankings by z-scores, by re-prioritizing genes and replacing them in their biological context, as shown by the three studies that we reanalyzed. Formatted input data for the three studied datasets, source code and web site for testing the system are available from the companion web site at http://htsnet.marseille.inserm.fr/. We also compared our program with existing algorithms (CARD and hotnet2). PMID:28949986

Interleukin-27 induces the endothelial differentiation in Sca-1+ cardiac resident stem cells.

PubMed

Tanaka, Tomohiro; Obana, Masanori; Mohri, Tomomi; Ebara, Masaki; Otani, Yuta; Maeda, Makiko; Fujio, Yasushi

2015-10-01

Cytokines play important roles in cardiac repair and regeneration. Recently, we demonstrated that interleukin (IL)-6 family cytokines induce the endothelial differentiation of Sca-1+ cardiac resident stem cells through STAT3/Pim-1 signaling pathway. In contrast, the biological functions of IL-12 family cytokines in heart remain to be elucidated, though they show structural homology with IL-6. In the present study, we examined the effects of IL-12 family cytokines on the transdifferentiation of cardiac Sca-1+ cells into cardiac cells. RT-PCR analyses revealed that IL-27 receptor α (IL-27Rα), but not IL-12R or IL-23R, was expressed in cardiac Sca-1+ cells. The transcript expression of IL-27 was elevated in murine hearts in cardiac injury models. Intriguingly, IL-27 stimulation for 14 days induced the endothelial cell (EC) marker genes, such as CD-31 and VE-cadherin. Immunoblot analyses clarified that IL-27 treatment rapidly phosphorylated STAT3. IL-27 upregulated the expression of Pim-1, but the overexpression of dominant negative STAT3 abrogated the induction of Pim-1 by IL-27. Finally, adenoviral transfection of dominant negative Pim-1 inhibited IL-27-induced EC differentiation of cardiac Sca-1+ cells. These findings demonstrated that IL-27 promoted the commitment of cardiac stem cells into the EC lineage, possibly leading to neovascularization as a novel biological function. IL-27 could not only regulate the inflammation but also contribute to the maintenance of the tissue homeostasis through stem cell differentiation at inflammatory sites. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Correlation analyses revealed global microRNA-mRNA expression associations in human peripheral blood mononuclear cells.

PubMed

Wang, Lan; Zhu, Jiang; Deng, Fei-Yan; Wu, Long-Fei; Mo, Xing-Bo; Zhu, Xiao-Wei; Xia, Wei; Xie, Fang-Fei; He, Pei; Bing, Peng-Fei; Qiu, Ying-Hua; Lin, Xiang; Lu, Xin; Zhang, Lei; Yi, Neng-Jun; Zhang, Yong-Hong; Lei, Shu-Feng

2018-02-01

MicroRNAs (miRNAs) can regulate gene expression through binding to complementary sites in the 3'-untranslated regions of target mRNAs, which will lead to existence of correlation in expression between miRNA and mRNA. However, the miRNA-mRNA correlation patterns are complex and remain largely unclear yet. To establish the global correlation patterns in human peripheral blood mononuclear cells (PBMCs), multiple miRNA-mRNA correlation analyses and expression quantitative trait locus (eQTL) analysis were conducted in this study. We predicted and achieved 861 miRNA-mRNA pairs (65 miRNAs, 412 mRNAs) using multiple bioinformatics programs, and found global negative miRNA-mRNA correlations in PBMC from all 46 study subjects. Among the 861 pairs of correlations, 19.5% were significant (P < 0.05) and ~70% were negative. The correlation network was complex and highlighted key miRNAs/genes in PBMC. Some miRNAs, such as hsa-miR-29a, hsa-miR-148a, regulate a cluster of target genes. Some genes, e.g., TNRC6A, are regulated by multiple miRNAs. The identified genes tend to be enriched in molecular functions of DNA and RNA binding, and biological processes such as protein transport, regulation of translation and chromatin modification. The results provided a global view of the miRNA-mRNA expression correlation profile in human PBMCs, which would facilitate in-depth investigation of biological functions of key miRNAs/mRNAs and better understanding of the pathogenesis underlying PBMC-related diseases.

Data driven linear algebraic methods for analysis of molecular pathways: application to disease progression in shock/trauma.

PubMed

McGuire, Mary F; Sriram Iyengar, M; Mercer, David W

2012-04-01

Although trauma is the leading cause of death for those below 45years of age, there is a dearth of information about the temporal behavior of the underlying biological mechanisms in those who survive the initial trauma only to later suffer from syndromes such as multiple organ failure. Levels of serum cytokines potentially affect the clinical outcomes of trauma; understanding how cytokine levels modulate intra-cellular signaling pathways can yield insights into molecular mechanisms of disease progression and help to identify targeted therapies. However, developing such analyses is challenging since it necessitates the integration and interpretation of large amounts of heterogeneous, quantitative and qualitative data. Here we present the Pathway Semantics Algorithm (PSA), an algebraic process of node and edge analyses of evoked biological pathways over time for in silico discovery of biomedical hypotheses, using data from a prospective controlled clinical study of the role of cytokines in multiple organ failure (MOF) at a major US trauma center. A matrix algebra approach was used in both the PSA node and PSA edge analyses with different matrix configurations and computations based on the biomedical questions to be examined. In the edge analysis, a percentage measure of crosstalk called XTALK was also developed to assess cross-pathway interference. In the node/molecular analysis of the first 24h from trauma, PSA uncovered seven molecules evoked computationally that differentiated outcomes of MOF or non-MOF (NMOF), of which three molecules had not been previously associated with any shock/trauma syndrome. In the edge/molecular interaction analysis, PSA examined four categories of functional molecular interaction relationships--activation, expression, inhibition, and transcription--and found that the interaction patterns and crosstalk changed over time and outcome. The PSA edge analysis suggests that a diagnosis, prognosis or therapy based on molecular interaction mechanisms may be most effective within a certain time period and for a specific functional relationship. Copyright © 2011 Elsevier Inc. All rights reserved.

Data driven linear algebraic methods for analysis of molecular pathways: application to disease progression in shock/trauma

PubMed Central

McGuire, Mary F.; Iyengar, M. Sriram; Mercer, David W.

2012-01-01

Motivation Although trauma is the leading cause of death for those below 45 years of age, there is a dearth of information about the temporal behavior of the underlying biological mechanisms in those who survive the initial trauma only to later suffer from syndromes such as multiple organ failure. Levels of serum cytokines potentially affect the clinical outcomes of trauma; understanding how cytokine levels modulate intra-cellular signaling pathways can yield insights into molecular mechanisms of disease progression and help to identify targeted therapies. However, developing such analyses is challenging since it necessitates the integration and interpretation of large amounts of heterogeneous, quantitative and qualitative data. Here we present the Pathway Semantics Algorithm (PSA), an algebraic process of node and edge analyses of evoked biological pathways over time for in silico discovery of biomedical hypotheses, using data from a prospective controlled clinical study of the role of cytokines in multiple organ failure (MOF) at a major US trauma center. A matrix algebra approach was used in both the PSA node and PSA edge analyses with different matrix configurations and computations based on the biomedical questions to be examined. In the edge analysis, a percentage measure of crosstalk called XTALK was also developed to assess cross-pathway interference. Results In the node/molecular analysis of the first 24 hours from trauma, PSA uncovered 7 molecules evoked computationally that differentiated outcomes of MOF or non-MOF (NMOF), of which 3 molecules had not been previously associated with any shock / trauma syndrome. In the edge/molecular interaction analysis, PSA examined four categories of functional molecular interaction relationships – activation, expression, inhibition, and transcription – and found that the interaction patterns and crosstalk changed over time and outcome. The PSA edge analysis suggests that a diagnosis, prognosis or therapy based on molecular interaction mechanisms may be most effective within a certain time period and for a specific functional relationship. PMID:22200681

The Naples High- and Low-Excitability rats: selective breeding, behavioral profile, morphometry, and molecular biology of the mesocortical dopamine system.

PubMed

Viggiano, Davide; Vallone, Daniela; Welzl, Hans; Sadile, Adolfo G

2002-09-01

The Naples High- (NHE) and Low-Excitability (NLE) rat lines have been selected since 1976 on the basis of behavioral arousal to novelty (Làt-maze). Selective breeding has been conducted under continuous genetic pressure, with no brother-sister mating. The behavioral analyses presented here deal with (1) activity in environments of different complexity, i.e., holeboard and Làt maze; (2) maze learning in hexagonal tunnel, Olton, and Morris water mazes and; (3) two-way active avoidance and conditioned taste aversion tests. Morphometric analyses deal with central dopaminergic systems at their origin and target sites, as well as the density of dopamine transporter immunoreactivity. Molecular biology analyses are also presented, dealing with recent experiments on the prefrontal cortex (PFc), cloning and identifying differentially expressed genes using subtractive libraries and RNAase protection. The divergence between NLE and NHE rats varies as a function of the complexity level of the environment, with an impaired working and reference memory in both lines compared to random bred (NRB) controls. Moreover, data from the PFc of NHE rats show a hyperdopaminergic innervation, with overexpression of mRNA species involved in basal metabolism, and down-regulation of dopamine D1 receptors. Altogether, the evidence gathered so far supports a hyperfunctioning mesocorticolimbic system that makes NHE rats a useful tool for the study of hyperactivity and attention deficit, learning and memory disabilities, and drug abuse.

Autistic and schizotypal traits and global functioning in bipolar I disorder.

PubMed

Abu-Akel, Ahmad; Clark, Jennifer; Perry, Amy; Wood, Stephen J; Forty, Liz; Craddock, Nick; Jones, Ian; Gordon-Smith, Katherine; Jones, Lisa

2017-01-01

To determine the expression of autistic and positive schizotypal traits in a large sample of adults with bipolar I disorder (BD I), and the effect of co-occurring autistic and positive schizotypal traits on global functioning in BD I. Autistic and positive schizotypal traits were self-assessed in 797 individuals with BD-I recruited by the Bipolar Disorder Research Network. Differences in global functioning (rated using the Global Assessment Scale) during lifetime worst depressive and manic episodes (GASD and GASM respectively) were calculated in groups with high/low autistic and positive schizotypal traits. Regression analyses assessed the interactive effect of autistic and positive schizotypal traits on global functioning. 47.2% (CI=43.7-50.7%) showed clinically significant levels of autistic traits, and 23.22% (95% CI=20.29-26.14) showed clinically significant levels of positive schizotypal traits. In the worst episode of mania, the high autistic, high positive schizotypal group had better global functioning compared to the other groups. Individual differences analyses showed that high levels of both traits were associated with better global functioning in both mood states. Autistic and schizotypal traits were assessed using self-rated questionnaires. Expression of autistic and schizotypal traits in adults with BD I is prevalent, and may be important to predict illness aetiology, prognosis, and diagnostic practices in this population. Future work should focus on replicating these findings in independent samples, and on the biological and/or psychosocial mechanisms underlying better global functioning in those who have high levels of both autistic and positive schizotypal traits. Copyright © 2016 Elsevier B.V. All rights reserved.

Hormone therapy and physical function change among older women in the Women’s Health Initiative: a randomized controlled trial

PubMed Central

Michael, Yvonne L.; Gold, Rachel; Manson, JoAnn E.; Keast, Erin M.; Cochrane, Barbara B.; Woods, Nancy F.; Brzyski, Robert G.; McNeeley, S. Gene; Wallace, Robert B.

2011-01-01

Objective Although estrogen may be linked to biological pathways that maintain higher physical function, the evidence is derived mostly from observational epidemiology and therefore has numerous limitations. We examined whether hormone therapy affected physical function in women 65 to 79 years of age at enrollment. Methods This study involves an analysis of the Women’s Health Initiative randomized controlled trials of hormone therapy in which 922 nondisabled women who had previous hysterectomies were randomized to receive estrogen therapy or a placebo and 1,458 nondisabled women with intact uteri were randomized to receive estrogen + progestin therapy or a placebo. Changes in physical function were analyzed for treatment effect, and subgroup differences were evaluated. All women completed performance-based measures of physical function (grip strength, chair stands, and timed walk) at baseline. These measures were repeated after 1, 3, and 6 years. Results Overall, participants’ grip strength declined by 12.0%, chair stands declined by 3.5%, and walk pace slowed by 11.4% in the 6 years of follow-up (all P values <0.0001). Hormone therapy, as compared with placebo, was not associated with an increased or decreased risk of decline in physical function in either the intention-to-treat analyses or in analyses restricted to participants who were compliant in taking study pills. Conclusions Hormone therapy provided no overall protection against functional decline in nondisabled postmenopausal women 65 years or older in 6 years of follow-up. This study did not address the influence of hormone therapy for women of younger ages. PMID:19858764

Biological sex affects the neurobiology of autism

PubMed Central

Lombardo, Michael V.; Suckling, John; Ruigrok, Amber N. V.; Chakrabarti, Bhismadev; Ecker, Christine; Deoni, Sean C. L.; Craig, Michael C.; Murphy, Declan G. M.; Bullmore, Edward T.; Baron-Cohen, Simon

2013-01-01

In autism, heterogeneity is the rule rather than the exception. One obvious source of heterogeneity is biological sex. Since autism was first recognized, males with autism have disproportionately skewed research. Females with autism have thus been relatively overlooked, and have generally been assumed to have the same underlying neurobiology as males with autism. Growing evidence, however, suggests that this is an oversimplification that risks obscuring the biological base of autism. This study seeks to answer two questions about how autism is modulated by biological sex at the level of the brain: (i) is the neuroanatomy of autism different in males and females? and (ii) does the neuroanatomy of autism fit predictions from the ‘extreme male brain’ theory of autism, in males and/or in females? Neuroanatomical features derived from voxel-based morphometry were compared in a sample of equal-sized high-functioning male and female adults with and without autism (n = 120, n = 30/group). The first question was investigated using a 2 × 2 factorial design, and by spatial overlap analyses of the neuroanatomy of autism in males and females. The second question was tested through spatial overlap analyses of specific patterns predicted by the extreme male brain theory. We found that the neuroanatomy of autism differed between adult males and females, evidenced by minimal spatial overlap (not different from that occurred under random condition) in both grey and white matter, and substantially large white matter regions showing significant sex × diagnosis interactions in the 2 × 2 factorial design. These suggest that autism manifests differently by biological sex. Furthermore, atypical brain areas in females with autism substantially and non-randomly (P < 0.001) overlapped with areas that were sexually dimorphic in neurotypical controls, in both grey and white matter, suggesting neural ‘masculinization’. This was not seen in males with autism. How differences in neuroanatomy relate to the similarities in cognition between males and females with autism remains to be understood. Future research should stratify by biological sex to reduce heterogeneity and to provide greater insight into the neurobiology of autism. PMID:23935125

Systems biology of the structural proteome.

PubMed

Brunk, Elizabeth; Mih, Nathan; Monk, Jonathan; Zhang, Zhen; O'Brien, Edward J; Bliven, Spencer E; Chen, Ke; Chang, Roger L; Bourne, Philip E; Palsson, Bernhard O

2016-03-11

The success of genome-scale models (GEMs) can be attributed to the high-quality, bottom-up reconstructions of metabolic, protein synthesis, and transcriptional regulatory networks on an organism-specific basis. Such reconstructions are biochemically, genetically, and genomically structured knowledge bases that can be converted into a mathematical format to enable a myriad of computational biological studies. In recent years, genome-scale reconstructions have been extended to include protein structural information, which has opened up new vistas in systems biology research and empowered applications in structural systems biology and systems pharmacology. Here, we present the generation, application, and dissemination of genome-scale models with protein structures (GEM-PRO) for Escherichia coli and Thermotoga maritima. We show the utility of integrating molecular scale analyses with systems biology approaches by discussing several comparative analyses on the temperature dependence of growth, the distribution of protein fold families, substrate specificity, and characteristic features of whole cell proteomes. Finally, to aid in the grand challenge of big data to knowledge, we provide several explicit tutorials of how protein-related information can be linked to genome-scale models in a public GitHub repository ( https://github.com/SBRG/GEMPro/tree/master/GEMPro_recon/). Translating genome-scale, protein-related information to structured data in the format of a GEM provides a direct mapping of gene to gene-product to protein structure to biochemical reaction to network states to phenotypic function. Integration of molecular-level details of individual proteins, such as their physical, chemical, and structural properties, further expands the description of biochemical network-level properties, and can ultimately influence how to model and predict whole cell phenotypes as well as perform comparative systems biology approaches to study differences between organisms. GEM-PRO offers insight into the physical embodiment of an organism's genotype, and its use in this comparative framework enables exploration of adaptive strategies for these organisms, opening the door to many new lines of research. With these provided tools, tutorials, and background, the reader will be in a position to run GEM-PRO for their own purposes.

Predictive models attribute effects on fish assemblages to toxicity and habitat alteration.

PubMed

de Zwart, Dick; Dyer, Scott D; Posthuma, Leo; Hawkins, Charles P

2006-08-01

Biological assessments should both estimate the condition of a biological resource (magnitude of alteration) and provide environmental managers with a diagnosis of the potential causes of impairment. Although methods of quantifying condition are well developed, identifying and proportionately attributing impairment to probable causes remain problematic. Furthermore, analyses of both condition and cause have often been difficult to communicate. We developed an approach that (1) links fish, habitat, and chemistry data collected from hundreds of sites in Ohio (USA) streams, (2) assesses the biological condition at each site, (3) attributes impairment to multiple probable causes, and (4) provides the results of the analyses in simple-to-interpret pie charts. The data set was managed using a geographic information system. Biological condition was assessed using a RIVPACS (river invertebrate prediction and classification system)-like predictive model. The model provided probabilities of capture for 117 fish species based on the geographic location of sites and local habitat descriptors. Impaired biological condition was defined as the proportion of those native species predicted to occur at a site that were observed. The potential toxic effects of exposure to mixtures of contaminants were estimated using species sensitivity distributions and mixture toxicity principles. Generalized linear regression models described species abundance as a function of habitat characteristics. Statistically linking biological condition, habitat characteristics including mixture risks, and species abundance allowed us to evaluate the losses of species with environmental conditions. Results were mapped as simple effect and probable-cause pie charts (EPC pie diagrams), with pie sizes corresponding to magnitude of local impairment, and slice sizes to the relative probable contributions of different stressors. The types of models we used have been successfully applied in ecology and ecotoxicology, but they have not previously been used in concert to quantify impairment and its likely causes. Although data limitations constrained our ability to examine complex interactions between stressors and species, the direct relationships we detected likely represent conservative estimates of stressor contributions to local impairment. Future refinements of the general approach and specific methods described here should yield even more promising results.

Biological sex affects the neurobiology of autism.

PubMed

Lai, Meng-Chuan; Lombardo, Michael V; Suckling, John; Ruigrok, Amber N V; Chakrabarti, Bhismadev; Ecker, Christine; Deoni, Sean C L; Craig, Michael C; Murphy, Declan G M; Bullmore, Edward T; Baron-Cohen, Simon

2013-09-01

In autism, heterogeneity is the rule rather than the exception. One obvious source of heterogeneity is biological sex. Since autism was first recognized, males with autism have disproportionately skewed research. Females with autism have thus been relatively overlooked, and have generally been assumed to have the same underlying neurobiology as males with autism. Growing evidence, however, suggests that this is an oversimplification that risks obscuring the biological base of autism. This study seeks to answer two questions about how autism is modulated by biological sex at the level of the brain: (i) is the neuroanatomy of autism different in males and females? and (ii) does the neuroanatomy of autism fit predictions from the 'extreme male brain' theory of autism, in males and/or in females? Neuroanatomical features derived from voxel-based morphometry were compared in a sample of equal-sized high-functioning male and female adults with and without autism (n = 120, n = 30/group). The first question was investigated using a 2 × 2 factorial design, and by spatial overlap analyses of the neuroanatomy of autism in males and females. The second question was tested through spatial overlap analyses of specific patterns predicted by the extreme male brain theory. We found that the neuroanatomy of autism differed between adult males and females, evidenced by minimal spatial overlap (not different from that occurred under random condition) in both grey and white matter, and substantially large white matter regions showing significant sex × diagnosis interactions in the 2 × 2 factorial design. These suggest that autism manifests differently by biological sex. Furthermore, atypical brain areas in females with autism substantially and non-randomly (P < 0.001) overlapped with areas that were sexually dimorphic in neurotypical controls, in both grey and white matter, suggesting neural 'masculinization'. This was not seen in males with autism. How differences in neuroanatomy relate to the similarities in cognition between males and females with autism remains to be understood. Future research should stratify by biological sex to reduce heterogeneity and to provide greater insight into the neurobiology of autism.

An efficient method to identify differentially expressed genes in microarray experiments

PubMed Central

Qin, Huaizhen; Feng, Tao; Harding, Scott A.; Tsai, Chung-Jui; Zhang, Shuanglin

2013-01-01

Motivation Microarray experiments typically analyze thousands to tens of thousands of genes from small numbers of biological replicates. The fact that genes are normally expressed in functionally relevant patterns suggests that gene-expression data can be stratified and clustered into relatively homogenous groups. Cluster-wise dimensionality reduction should make it feasible to improve screening power while minimizing information loss. Results We propose a powerful and computationally simple method for finding differentially expressed genes in small microarray experiments. The method incorporates a novel stratification-based tight clustering algorithm, principal component analysis and information pooling. Comprehensive simulations show that our method is substantially more powerful than the popular SAM and eBayes approaches. We applied the method to three real microarray datasets: one from a Populus nitrogen stress experiment with 3 biological replicates; and two from public microarray datasets of human cancers with 10 to 40 biological replicates. In all three analyses, our method proved more robust than the popular alternatives for identification of differentially expressed genes. Availability The C++ code to implement the proposed method is available upon request for academic use. PMID:18453554

Enhanced entrainability of genetic oscillators by period mismatch

PubMed Central

Hasegawa, Yoshihiko; Arita, Masanori

2013-01-01

Biological oscillators coordinate individual cellular components so that they function coherently and collectively. They are typically composed of multiple feedback loops, and period mismatch is unavoidable in biological implementations. We investigated the advantageous effect of this period mismatch in terms of a synchronization response to external stimuli. Specifically, we considered two fundamental models of genetic circuits: smooth and relaxation oscillators. Using phase reduction and Floquet multipliers, we numerically analysed their entrainability under different coupling strengths and period ratios. We found that a period mismatch induces better entrainment in both types of oscillator; the enhancement occurs in the vicinity of the bifurcation on their limit cycles. In the smooth oscillator, the optimal period ratio for the enhancement coincides with the experimentally observed ratio, which suggests biological exploitation of the period mismatch. Although the origin of multiple feedback loops is often explained as a passive mechanism to ensure robustness against perturbation, we study the active benefits of the period mismatch, which include increasing the efficiency of the genetic oscillators. Our findings show a qualitatively different perspective for both the inherent advantages of multiple loops and their essentiality. PMID:23389900

Naumovozyma castellii: an alternative model for budding yeast molecular biology.

PubMed

Karademir Andersson, Ahu; Cohn, Marita

2017-03-01

Naumovozyma castellii (Saccharomyces castellii) is a member of the budding yeast family Saccharomycetaceae. It has been extensively used as a model organism for telomere biology research and has gained increasing interest as a budding yeast model for functional analyses owing to its amenability to genetic modifications. Owing to the suitable phylogenetic distance to S. cerevisiae, the whole genome sequence of N. castellii has provided unique data for comparative genomic studies, and it played a key role in the establishment of the timing of the whole genome duplication and the evolutionary events that took place in the subsequent genomic evolution of the Saccharomyces lineage. Here we summarize the historical background of its establishment as a laboratory yeast species, and the development of genetic and molecular tools and strains. We review the research performed on N. castellii, focusing on areas where it has significantly contributed to the discovery of new features of molecular biology and to the advancement of our understanding of molecular evolution. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Reflection on Molecular Approaches Influencing State-of-the-Art Bioremediation Design: Culturing to Microbial Community Fingerprinting to Omics

PubMed Central

Czaplicki, Lauren M.; Gunsch, Claudia K.

2017-01-01

Bioremediation is generally viewed as a cost effective and sustainable technology because it relies on microbes to transform pollutants into benign compounds. Advances in molecular biological analyses allow unprecedented microbial detection and are increasingly incorporated into bioremediation. Throughout history, state-of-the-art techniques have informed bioremediation strategies. However, the insights those techniques provided were not as in depth as those provided by recently developed omics tools. Advances in next generation sequencing (NGS) have now placed metagenomics and metatranscriptomics within reach of environmental engineers. As NGS costs decrease, metagenomics and metatranscriptomics have become increasingly feasible options to rapidly scan sites for specific degradative functions and identify microorganisms important in pollutant degradation. These omic techniques are capable of revolutionizing biological treatment in environmental engineering by allowing highly sensitive characterization of previously uncultured microorganisms. Omics enables the discovery of novel microorganisms for use in bioaugmentation and supports systematic optimization of biostimulation strategies. This review describes the omics journey from roots in biology and medicine to its current status in environmental engineering including potential future directions in commercial application. PMID:28348455

The relativity of biological function.

PubMed

Laubichler, Manfred D; Stadler, Peter F; Prohaska, Sonja J; Nowick, Katja

2015-12-01

Function is a central concept in biological theories and explanations. Yet discussions about function are often based on a narrow understanding of biological systems and processes, such as idealized molecular systems or simple evolutionary, i.e., selective, dynamics. Conflicting conceptions of function continue to be used in the scientific literature to support certain claims, for instance about the fraction of "functional DNA" in the human genome. Here we argue that all biologically meaningful interpretations of function are necessarily context dependent. This implies that they derive their meaning as well as their range of applicability only within a specific theoretical and measurement context. We use this framework to shed light on the current debate about functional DNA and argue that without considering explicitly the theoretical and measurement contexts all attempts to integrate biological theories are prone to fail.

Comprehensive evaluation of disease- and trait-specific enrichment for eight functional elements among GWAS-identified variants.

PubMed

Markunas, Christina A; Johnson, Eric O; Hancock, Dana B

2017-07-01

Genome-wide association study (GWAS)-identified variants are enriched for functional elements. However, we have limited knowledge of how functional enrichment may differ by disease/trait and tissue type. We tested a broad set of eight functional elements for enrichment among GWAS-identified SNPs (p < 5×10 -8 ) from the NHGRI-EBI Catalog across seven disease/trait categories: cancer, cardiovascular disease, diabetes, autoimmune disease, psychiatric disease, neurological disease, and anthropometric traits. SNPs were annotated using HaploReg for the eight functional elements across any tissue: DNase sites, expression quantitative trait loci (eQTL), sequence conservation, enhancers, promoters, missense variants, sequence motifs, and protein binding sites. In addition, tissue-specific annotations were considered for brain vs. blood. Disease/trait SNPs were compared to a control set of 4809 SNPs matched to the GWAS SNPs (N = 1639) on allele frequency, gene density, distance to nearest gene, and linkage disequilibrium at ~3:1 ratio. Enrichment analyses were conducted using logistic regression, with Bonferroni correction. Overall, a significant enrichment was observed for all functional elements, except sequence motifs. Missense SNPs showed the strongest magnitude of enrichment. eQTLs were the only functional element significantly enriched across all diseases/traits. Magnitudes of enrichment were generally similar across diseases/traits, where enrichment was statistically significant. Blood vs. brain tissue effects on enrichment were dependent on disease/trait and functional element (e.g., cardiovascular disease: eQTLs P TissueDifference  = 1.28 × 10 -6 vs. enhancers P TissueDifference  = 0.94). Identifying disease/trait-relevant functional elements and tissue types could provide new insight into the underlying biology, by guiding a priori GWAS analyses (e.g., brain enhancer elements for psychiatric disease) or facilitating post hoc interpretation.

Computational Selection of Transcriptomics Experiments Improves Guilt-by-Association Analyses

PubMed Central

Bhat, Prajwal; Yang, Haixuan; Bögre, László; Devoto, Alessandra; Paccanaro, Alberto

2012-01-01

The Guilt-by-Association (GBA) principle, according to which genes with similar expression profiles are functionally associated, is widely applied for functional analyses using large heterogeneous collections of transcriptomics data. However, the use of such large collections could hamper GBA functional analysis for genes whose expression is condition specific. In these cases a smaller set of condition related experiments should instead be used, but identifying such functionally relevant experiments from large collections based on literature knowledge alone is an impractical task. We begin this paper by analyzing, both from a mathematical and a biological point of view, why only condition specific experiments should be used in GBA functional analysis. We are able to show that this phenomenon is independent of the functional categorization scheme and of the organisms being analyzed. We then present a semi-supervised algorithm that can select functionally relevant experiments from large collections of transcriptomics experiments. Our algorithm is able to select experiments relevant to a given GO term, MIPS FunCat term or even KEGG pathways. We extensively test our algorithm on large dataset collections for yeast and Arabidopsis. We demonstrate that: using the selected experiments there is a statistically significant improvement in correlation between genes in the functional category of interest; the selected experiments improve GBA-based gene function prediction; the effectiveness of the selected experiments increases with annotation specificity; our algorithm can be successfully applied to GBA-based pathway reconstruction. Importantly, the set of experiments selected by the algorithm reflects the existing literature knowledge about the experiments. [A MATLAB implementation of the algorithm and all the data used in this paper can be downloaded from the paper website: http://www.paccanarolab.org/papers/CorrGene/]. PMID:22879875

Antidoping programme and biological monitoring before and during the 2014 FIFA World Cup Brazil

PubMed Central

Baume, Norbert; Jan, Nicolas; Emery, Caroline; Mandanis, Béatrice; Schweizer, Carine; Giraud, Sylvain; Leuenberger, Nicolas; Marclay, François; Nicoli, Raul; Perrenoud, Laurent; Robinson, Neil; Dvorak, Jiri; Saugy, Martial

2015-01-01

Background The FIFA has implemented an important antidoping programme for the 2014 FIFA World Cup. Aim To perform the analyses before and during the World Cup with biological monitoring of blood and urine samples. Methods All qualified players from the 32 teams participating in the World Cup were tested out-of-competition. During the World Cup, 2–8 players per match were tested. Over 1000 samples were collected in total and analysed in the WADA accredited Laboratory of Lausanne. Results The quality of the analyses was at the required level as described in the WADA technical documents. The urinary steroid profiles of the players were stable and consistent with previously published papers on football players. During the competition, amphetamine was detected in a sample collected on a player who had a therapeutic use exemption for attention deficit hyperactivity disorder. The blood passport data showed no significant difference in haemoglobin values between out-of-competition and postmatch samples. Conclusions Logistical issues linked to biological samples collection, and the overseas shipment during the World Cup did not impair the quality of the analyses, especially when used as the biological passport of football players. PMID:25878079

Quantifying side-chain conformational variations in protein structure

PubMed Central

Miao, Zhichao; Cao, Yang

2016-01-01

Protein side-chain conformation is closely related to their biological functions. The side-chain prediction is a key step in protein design, protein docking and structure optimization. However, side-chain polymorphism comprehensively exists in protein as various types and has been long overlooked by side-chain prediction. But such conformational variations have not been quantitatively studied and the correlations between these variations and residue features are vague. Here, we performed statistical analyses on large scale data sets and found that the side-chain conformational flexibility is closely related to the exposure to solvent, degree of freedom and hydrophilicity. These analyses allowed us to quantify different types of side-chain variabilities in PDB. The results underscore that protein side-chain conformation prediction is not a single-answer problem, leading us to reconsider the assessment approaches of side-chain prediction programs. PMID:27845406

Quantifying side-chain conformational variations in protein structure

NASA Astrophysics Data System (ADS)

Miao, Zhichao; Cao, Yang

2016-11-01

Protein side-chain conformation is closely related to their biological functions. The side-chain prediction is a key step in protein design, protein docking and structure optimization. However, side-chain polymorphism comprehensively exists in protein as various types and has been long overlooked by side-chain prediction. But such conformational variations have not been quantitatively studied and the correlations between these variations and residue features are vague. Here, we performed statistical analyses on large scale data sets and found that the side-chain conformational flexibility is closely related to the exposure to solvent, degree of freedom and hydrophilicity. These analyses allowed us to quantify different types of side-chain variabilities in PDB. The results underscore that protein side-chain conformation prediction is not a single-answer problem, leading us to reconsider the assessment approaches of side-chain prediction programs.

Quantifying side-chain conformational variations in protein structure.

PubMed

Miao, Zhichao; Cao, Yang

2016-11-15

Protein side-chain conformation is closely related to their biological functions. The side-chain prediction is a key step in protein design, protein docking and structure optimization. However, side-chain polymorphism comprehensively exists in protein as various types and has been long overlooked by side-chain prediction. But such conformational variations have not been quantitatively studied and the correlations between these variations and residue features are vague. Here, we performed statistical analyses on large scale data sets and found that the side-chain conformational flexibility is closely related to the exposure to solvent, degree of freedom and hydrophilicity. These analyses allowed us to quantify different types of side-chain variabilities in PDB. The results underscore that protein side-chain conformation prediction is not a single-answer problem, leading us to reconsider the assessment approaches of side-chain prediction programs.

Subtyping attention-deficit/hyperactivity disorder using temperament dimensions: toward biologically based nosologic criteria.

PubMed

Karalunas, Sarah L; Fair, Damien; Musser, Erica D; Aykes, Kamari; Iyer, Swathi P; Nigg, Joel T

2014-09-01

Psychiatric nosology is limited by behavioral and biological heterogeneity within existing disorder categories. The imprecise nature of current nosologic distinctions limits both mechanistic understanding and clinical prediction. We demonstrate an approach consistent with the National Institute of Mental Health Research Domain Criteria initiative to identify superior, neurobiologically valid subgroups with better predictive capacity than existing psychiatric categories for childhood attention-deficit/hyperactivity disorder (ADHD). To refine subtyping of childhood ADHD by using biologically based behavioral dimensions (i.e., temperament), novel classification algorithms, and multiple external validators. A total of 437 clinically well-characterized, community-recruited children, with and without ADHD, participated in an ongoing longitudinal study. Baseline data were used to classify children into subgroups based on temperament dimensions and examine external validators including physiological and magnetic resonance imaging measures. One-year longitudinal follow-up data are reported for a subgroup of the ADHD sample to address stability and clinical prediction. Parent/guardian ratings of children on a measure of temperament were used as input features in novel community detection analyses to identify subgroups within the sample. Groups were validated using 3 widely accepted external validators: peripheral physiological characteristics (cardiac measures of respiratory sinus arrhythmia and pre-ejection period), central nervous system functioning (via resting-state functional connectivity magnetic resonance imaging), and clinical outcomes (at 1-year longitudinal follow-up). The community detection algorithm suggested 3 novel types of ADHD, labeled as mild (normative emotion regulation), surgent (extreme levels of positive approach-motivation), and irritable (extreme levels of negative emotionality, anger, and poor soothability). Types were independent of existing clinical demarcations including DSM-5 presentations or symptom severity. These types showed stability over time and were distinguished by unique patterns of cardiac physiological response, resting-state functional brain connectivity, and clinical outcomes 1 year later. Results suggest that a biologically informed temperament-based typology, developed with a discovery-based community detection algorithm, provides a superior description of heterogeneity in the ADHD population than does any current clinical nosologic criteria. This demonstration sets the stage for more aggressive attempts at a tractable, biologically based nosology.

Atlas of Cancer Signalling Network: a systems biology resource for integrative analysis of cancer data with Google Maps

PubMed Central

Kuperstein, I; Bonnet, E; Nguyen, H-A; Cohen, D; Viara, E; Grieco, L; Fourquet, S; Calzone, L; Russo, C; Kondratova, M; Dutreix, M; Barillot, E; Zinovyev, A

2015-01-01

Cancerogenesis is driven by mutations leading to aberrant functioning of a complex network of molecular interactions and simultaneously affecting multiple cellular functions. Therefore, the successful application of bioinformatics and systems biology methods for analysis of high-throughput data in cancer research heavily depends on availability of global and detailed reconstructions of signalling networks amenable for computational analysis. We present here the Atlas of Cancer Signalling Network (ACSN), an interactive and comprehensive map of molecular mechanisms implicated in cancer. The resource includes tools for map navigation, visualization and analysis of molecular data in the context of signalling network maps. Constructing and updating ACSN involves careful manual curation of molecular biology literature and participation of experts in the corresponding fields. The cancer-oriented content of ACSN is completely original and covers major mechanisms involved in cancer progression, including DNA repair, cell survival, apoptosis, cell cycle, EMT and cell motility. Cell signalling mechanisms are depicted in detail, together creating a seamless ‘geographic-like' map of molecular interactions frequently deregulated in cancer. The map is browsable using NaviCell web interface using the Google Maps engine and semantic zooming principle. The associated web-blog provides a forum for commenting and curating the ACSN content. ACSN allows uploading heterogeneous omics data from users on top of the maps for visualization and performing functional analyses. We suggest several scenarios for ACSN application in cancer research, particularly for visualizing high-throughput data, starting from small interfering RNA-based screening results or mutation frequencies to innovative ways of exploring transcriptomes and phosphoproteomes. Integration and analysis of these data in the context of ACSN may help interpret their biological significance and formulate mechanistic hypotheses. ACSN may also support patient stratification, prediction of treatment response and resistance to cancer drugs, as well as design of novel treatment strategies. PMID:26192618

[Pancreatic acinar neoplasms : Comparative molecular characterization].

PubMed

Bergmann, F

2016-11-01

Pancreatic acinar cell carcinomas are biologically aggressive neoplasms for which treatment options are very limited. The molecular mechanisms of tumor initiation and progression are largely not understood and precursor lesions have not yet been identified. In this study, pancreatic acinar cell carcinomas were cytogenetically characterized as well as by molecular and immunohistochemical analyses. Corresponding investigations were carried out on pancreatic ductal adenocarcinomas and pancreatic neuroendocrine neoplasms augmented by functional analyses. We show that pancreatic acinar cell carcinomas display a microsatellite stable, chromosomal unstable genotype, characterized by recurrent chromosomal imbalances that clearly discriminate them from pancreatic ductal adenocarcinomas and neuroendocrine neoplasms. Based on findings obtained from comparative genomic hybridization, candidate genes could be identified, such as deleted in colorectal cancer (DCC) and c-MYC. Furthermore, several therapeutic targets were identified in acinar cell carcinomas and other pancreatic neoplasms, including epidermal growth factor receptor (EGFR), L1 cell adhesion molecule (L1CAM) and heat shock protein 90 (HSP90). Moreover, L1CAM was shown to play a significant role in the tumorigenesis of pancreatic ductal adenocarcinoma. Functional analyses in cell lines derived from pancreatic neuroendocrine neoplasms revealed promising anti-tumorigenic effects using EGFR and HSP90 inhibitors affecting the cell cycle and in the case of HSP90, regulating several other oncogenes. Finally, based on mutational analyses of mitochondrial DNA, molecular evidence is provided that acinar cell cystadenomas (or better cystic acinar transformation) represent non-clonal lesions, suggesting an inflammatory reactive non-neoplastic nature.

Measuring job stress among hospital nurses: an attempt to identify biological markers.

PubMed

Kawaguchi, Yoshichika; Toyomasu, Kouji; Yoshida, Noriko; Baba, Kaori; Uemoto, Masaharu; Minota, Shoichi

2007-02-01

The purpose of this study was to identify biological markers corresponding to job stress among hospital nurses. The subjects of this study were 128 nurses working at a university hospital. The NIOSH job stress questionnaire and the Miki Nurse Stressor 35-item Scale measured their job stress levels. The GHQ28 was also used to measure the subjects' general mental health status. Blood analyses for neuroendocrine function and immunity reaction were performed in order to identify biological markers of job stress. Stress is related to the plasma levels of catecholamine, cortisol, adrenocorticotrophic hormone, and natural killer cell activity, therefore these factors were measured accordingly. In consideration to circadian rhythms, blood was collected from the subjects prior to the start of the day shift. The nurses filled out the questionnaires on the day of the blood tests. In order to investigate the correlation between job stress reactions indicated by the questionnaires and the results of the blood tests, we utilized Pearson's correlation coefficient and partial correlation coefficient for which other affected items were controlled. In this study, significant correlations were found between job stress and biological factors; however, the correlations were not strong. Thus, it can be said that the biological markers associated with a specific kind of job stress remain unclear. In the future, rather than implementing a simple cross-sectional study, a longitudinal study including follow-up research will be more effective in establishing biological markers for job stress.

Integrated assessment of oil pollution using biological monitoring and chemical fingerprinting.

PubMed

Lewis, Ceri; Guitart, Carlos; Pook, Chris; Scarlett, Alan; Readman, James W; Galloway, Tamara S

2010-06-01

A full assessment of the impact of oil and chemical spills at sea requires the identification of both the polluting chemicals and the biological effects they cause. Here, a combination of chemical fingerprinting of surface oils, tissue residue analysis, and biological effects measures was used to explore the relationship between spilled oil and biological impact following the grounding of the MSC Napoli container ship in Lyme Bay, England in January 2007. Initially, oil contamination remained restricted to a surface slick in the vicinity of the wreck, and there was no chemical evidence to link biological impairment of animals (the common limpet, Patella vulgata) on the shore adjacent to the oil spill. Secondary oil contamination associated with salvage activities in July 2007 was also assessed. Chemical analyses of aliphatic hydrocarbons and terpanes in shell swabs taken from limpet shells provided an unequivocal match with the fuel oil carried by the ship. Corresponding chemical analysis of limpet tissues revealed increased concentrations of polycyclic aromatic hydrocarbons (PAHs) dominated by phenanthrene and C1 to C3 phenanthrenes with smaller contributions from heavier molecular weight PAHs. Concurrent ecotoxicological tests indicated impairment of cellular viability (p < 0.001), reduced immune function (p < 0.001), and damage to DNA (Comet assay, p < 0.001) in these animals, whereas antioxidant defenses were elevated relative to un-oiled animals. These results illustrate the value of combining biological monitoring with chemical fingerprinting for the rapid identification of spilled oils and their sublethal impacts on biota in situ. Copyright 2010 SETAC.

Cingulo-insular structural alterations associated with psychogenic symptoms, childhood abuse and PTSD in functional neurological disorders.

PubMed

Perez, David L; Matin, Nassim; Barsky, Arthur; Costumero-Ramos, Victor; Makaretz, Sara J; Young, Sigrid S; Sepulcre, Jorge; LaFrance, W Curt; Keshavan, Matcheri S; Dickerson, Bradford C

2017-06-01

Adverse early-life events are predisposing factors for functional neurological disorder (FND) and post-traumatic stress disorder (PTSD). Cingulo-insular regions are implicated in the biology of both conditions and are sites of stress-mediated neuroplasticity. We hypothesised that functional neurological symptoms and the magnitude of childhood abuse would be associated with overlapping anterior cingulate cortex (ACC) and insular volumetric reductions, and that FND and PTSD symptoms would map onto distinct cingulo-insular areas. This within-group voxel-based morphometry study probes volumetric associations with self-report measures of functional neurological symptoms, adverse life events and PTSD symptoms in 23 mixed-gender FND patients. Separate secondary analyses were also performed in the subset of 18 women with FND to account for gender-specific effects. Across the entire cohort, there were no statistically significant volumetric associations with self-report measures of functional neurological symptom severity or childhood abuse. In women with FND, however, parallel inverse associations were observed between left anterior insular volume and functional neurological symptoms as measured by the Patient Health Questionnaire-15 and the Screening for Somatoform Symptoms Conversion Disorder subscale. Similar inverse relationships were also appreciated between childhood abuse burden and left anterior insular volume. Across all subjects, PTSD symptom severity was inversely associated with dorsal ACC volume, and the magnitude of lifetime adverse events was inversely associated with left hippocampal volume. This study reveals distinct cingulo-insular alterations for FND and PTSD symptoms and may advance our understanding of FND. Potential biological convergence between stress-related neuroplasticity, functional neurological symptoms and reduced insular volume was identified. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Characterizing the Diversity and Biological Relevance of the MLPCN Assay Manifold and Screening Set

PubMed Central

Zhang, Jintao; Lushington, Gerald H.; Huan, Jun

2011-01-01

The NIH Molecular Libraries Initiative (MLI), launched in 2004 with initial goals of identifying chemical probes for characterizing gene function and druggability, has produced PubChem, a chemical genomics knowledgebase for fostering translation of basic research into new therapeutic strategies. This paper assesses progress toward these goals by evaluating MLI target novelty and propensity for undergoing biochemically or therapeutically relevant modulations and the degree of chemical diversity and biogenic bias inherent in the MLI screening set. Our analyses suggest that while MLI target selection has not yet been fully optimized for biochemical diversity, it covers biologically interesting pathway space that complements established drug targets. We find the MLI screening set to be chemically diverse and to have greater biogenic bias than comparable collections of commercially available compounds. Biogenic enhancements such as incorporation of more metabolite-like chemotypes are suggested. PMID:21568288

Genetic studies of body mass index yield new insights for obesity biology.

PubMed

Locke, Adam E; Kahali, Bratati; Berndt, Sonja I; Justice, Anne E; Pers, Tune H; Day, Felix R; Powell, Corey; Vedantam, Sailaja; Buchkovich, Martin L; Yang, Jian; Croteau-Chonka, Damien C; Esko, Tonu; Fall, Tove; Ferreira, Teresa; Gustafsson, Stefan; Kutalik, Zoltán; Luan, Jian'an; Mägi, Reedik; Randall, Joshua C; Winkler, Thomas W; Wood, Andrew R; Workalemahu, Tsegaselassie; Faul, Jessica D; Smith, Jennifer A; Zhao, Jing Hua; Zhao, Wei; Chen, Jin; Fehrmann, Rudolf; Hedman, Åsa K; Karjalainen, Juha; Schmidt, Ellen M; Absher, Devin; Amin, Najaf; Anderson, Denise; Beekman, Marian; Bolton, Jennifer L; Bragg-Gresham, Jennifer L; Buyske, Steven; Demirkan, Ayse; Deng, Guohong; Ehret, Georg B; Feenstra, Bjarke; Feitosa, Mary F; Fischer, Krista; Goel, Anuj; Gong, Jian; Jackson, Anne U; Kanoni, Stavroula; Kleber, Marcus E; Kristiansson, Kati; Lim, Unhee; Lotay, Vaneet; Mangino, Massimo; Leach, Irene Mateo; Medina-Gomez, Carolina; Medland, Sarah E; Nalls, Michael A; Palmer, Cameron D; Pasko, Dorota; Pechlivanis, Sonali; Peters, Marjolein J; Prokopenko, Inga; Shungin, Dmitry; Stančáková, Alena; Strawbridge, Rona J; Sung, Yun Ju; Tanaka, Toshiko; Teumer, Alexander; Trompet, Stella; van der Laan, Sander W; van Setten, Jessica; Van Vliet-Ostaptchouk, Jana V; Wang, Zhaoming; Yengo, Loïc; Zhang, Weihua; Isaacs, Aaron; Albrecht, Eva; Ärnlöv, Johan; Arscott, Gillian M; Attwood, Antony P; Bandinelli, Stefania; Barrett, Amy; Bas, Isabelita N; Bellis, Claire; Bennett, Amanda J; Berne, Christian; Blagieva, Roza; Blüher, Matthias; Böhringer, Stefan; Bonnycastle, Lori L; Böttcher, Yvonne; Boyd, Heather A; Bruinenberg, Marcel; Caspersen, Ida H; Chen, Yii-Der Ida; Clarke, Robert; Daw, E Warwick; de Craen, Anton J M; Delgado, Graciela; Dimitriou, Maria; Doney, Alex S F; Eklund, Niina; Estrada, Karol; Eury, Elodie; Folkersen, Lasse; Fraser, Ross M; Garcia, Melissa E; Geller, Frank; Giedraitis, Vilmantas; Gigante, Bruna; Go, Alan S; Golay, Alain; Goodall, Alison H; Gordon, Scott D; Gorski, Mathias; Grabe, Hans-Jörgen; Grallert, Harald; Grammer, Tanja B; Gräßler, Jürgen; Grönberg, Henrik; Groves, Christopher J; Gusto, Gaëlle; Haessler, Jeffrey; Hall, Per; Haller, Toomas; Hallmans, Goran; Hartman, Catharina A; Hassinen, Maija; Hayward, Caroline; Heard-Costa, Nancy L; Helmer, Quinta; Hengstenberg, Christian; Holmen, Oddgeir; Hottenga, Jouke-Jan; James, Alan L; Jeff, Janina M; Johansson, Åsa; Jolley, Jennifer; Juliusdottir, Thorhildur; Kinnunen, Leena; Koenig, Wolfgang; Koskenvuo, Markku; Kratzer, Wolfgang; Laitinen, Jaana; Lamina, Claudia; Leander, Karin; Lee, Nanette R; Lichtner, Peter; Lind, Lars; Lindström, Jaana; Lo, Ken Sin; Lobbens, Stéphane; Lorbeer, Roberto; Lu, Yingchang; Mach, François; Magnusson, Patrik K E; Mahajan, Anubha; McArdle, Wendy L; McLachlan, Stela; Menni, Cristina; Merger, Sigrun; Mihailov, Evelin; Milani, Lili; Moayyeri, Alireza; Monda, Keri L; Morken, Mario A; Mulas, Antonella; Müller, Gabriele; Müller-Nurasyid, Martina; Musk, Arthur W; Nagaraja, Ramaiah; Nöthen, Markus M; Nolte, Ilja M; Pilz, Stefan; Rayner, Nigel W; Renstrom, Frida; Rettig, Rainer; Ried, Janina S; Ripke, Stephan; Robertson, Neil R; Rose, Lynda M; Sanna, Serena; Scharnagl, Hubert; Scholtens, Salome; Schumacher, Fredrick R; Scott, William R; Seufferlein, Thomas; Shi, Jianxin; Smith, Albert Vernon; Smolonska, Joanna; Stanton, Alice V; Steinthorsdottir, Valgerdur; Stirrups, Kathleen; Stringham, Heather M; Sundström, Johan; Swertz, Morris A; Swift, Amy J; Syvänen, Ann-Christine; Tan, Sian-Tsung; Tayo, Bamidele O; Thorand, Barbara; Thorleifsson, Gudmar; Tyrer, Jonathan P; Uh, Hae-Won; Vandenput, Liesbeth; Verhulst, Frank C; Vermeulen, Sita H; Verweij, Niek; Vonk, Judith M; Waite, Lindsay L; Warren, Helen R; Waterworth, Dawn; Weedon, Michael N; Wilkens, Lynne R; Willenborg, Christina; Wilsgaard, Tom; Wojczynski, Mary K; Wong, Andrew; Wright, Alan F; Zhang, Qunyuan; Brennan, Eoin P; Choi, Murim; Dastani, Zari; Drong, Alexander W; Eriksson, Per; Franco-Cereceda, Anders; Gådin, Jesper R; Gharavi, Ali G; Goddard, Michael E; Handsaker, Robert E; Huang, Jinyan; Karpe, Fredrik; Kathiresan, Sekar; Keildson, Sarah; Kiryluk, Krzysztof; Kubo, Michiaki; Lee, Jong-Young; Liang, Liming; Lifton, Richard P; Ma, Baoshan; McCarroll, Steven A; McKnight, Amy J; Min, Josine L; Moffatt, Miriam F; Montgomery, Grant W; Murabito, Joanne M; Nicholson, George; Nyholt, Dale R; Okada, Yukinori; Perry, John R B; Dorajoo, Rajkumar; Reinmaa, Eva; Salem, Rany M; Sandholm, Niina; Scott, Robert A; Stolk, Lisette; Takahashi, Atsushi; Tanaka, Toshihiro; van 't Hooft, Ferdinand M; Vinkhuyzen, Anna A E; Westra, Harm-Jan; Zheng, Wei; Zondervan, Krina T; Heath, Andrew C; Arveiler, Dominique; Bakker, Stephan J L; Beilby, John; Bergman, Richard N; Blangero, John; Bovet, Pascal; Campbell, Harry; Caulfield, Mark J; Cesana, Giancarlo; Chakravarti, Aravinda; Chasman, Daniel I; Chines, Peter S; Collins, Francis S; Crawford, Dana C; Cupples, L Adrienne; Cusi, Daniele; Danesh, John; de Faire, Ulf; den Ruijter, Hester M; Dominiczak, Anna F; Erbel, Raimund; Erdmann, Jeanette; Eriksson, Johan G; Farrall, Martin; Felix, Stephan B; Ferrannini, Ele; Ferrières, Jean; Ford, Ian; Forouhi, Nita G; Forrester, Terrence; Franco, Oscar H; Gansevoort, Ron T; Gejman, Pablo V; Gieger, Christian; Gottesman, Omri; Gudnason, Vilmundur; Gyllensten, Ulf; Hall, Alistair S; Harris, Tamara B; Hattersley, Andrew T; Hicks, Andrew A; Hindorff, Lucia A; Hingorani, Aroon D; Hofman, Albert; Homuth, Georg; Hovingh, G Kees; Humphries, Steve E; Hunt, Steven C; Hyppönen, Elina; Illig, Thomas; Jacobs, Kevin B; Jarvelin, Marjo-Riitta; Jöckel, Karl-Heinz; Johansen, Berit; Jousilahti, Pekka; Jukema, J Wouter; Jula, Antti M; Kaprio, Jaakko; Kastelein, John J P; Keinanen-Kiukaanniemi, Sirkka M; Kiemeney, Lambertus A; Knekt, Paul; Kooner, Jaspal S; Kooperberg, Charles; Kovacs, Peter; Kraja, Aldi T; Kumari, Meena; Kuusisto, Johanna; Lakka, Timo A; Langenberg, Claudia; Marchand, Loic Le; Lehtimäki, Terho; Lyssenko, Valeriya; Männistö, Satu; Marette, André; Matise, Tara C; McKenzie, Colin A; McKnight, Barbara; Moll, Frans L; Morris, Andrew D; Morris, Andrew P; Murray, Jeffrey C; Nelis, Mari; Ohlsson, Claes; Oldehinkel, Albertine J; Ong, Ken K; Madden, Pamela A F; Pasterkamp, Gerard; Peden, John F; Peters, Annette; Postma, Dirkje S; Pramstaller, Peter P; Price, Jackie F; Qi, Lu; Raitakari, Olli T; Rankinen, Tuomo; Rao, D C; Rice, Treva K; Ridker, Paul M; Rioux, John D; Ritchie, Marylyn D; Rudan, Igor; Salomaa, Veikko; Samani, Nilesh J; Saramies, Jouko; Sarzynski, Mark A; Schunkert, Heribert; Schwarz, Peter E H; Sever, Peter; Shuldiner, Alan R; Sinisalo, Juha; Stolk, Ronald P; Strauch, Konstantin; Tönjes, Anke; Trégouët, David-Alexandre; Tremblay, Angelo; Tremoli, Elena; Virtamo, Jarmo; Vohl, Marie-Claude; Völker, Uwe; Waeber, Gérard; Willemsen, Gonneke; Witteman, Jacqueline C; Zillikens, M Carola; Adair, Linda S; Amouyel, Philippe; Asselbergs, Folkert W; Assimes, Themistocles L; Bochud, Murielle; Boehm, Bernhard O; Boerwinkle, Eric; Bornstein, Stefan R; Bottinger, Erwin P; Bouchard, Claude; Cauchi, Stéphane; Chambers, John C; Chanock, Stephen J; Cooper, Richard S; de Bakker, Paul I W; Dedoussis, George; Ferrucci, Luigi; Franks, Paul W; Froguel, Philippe; Groop, Leif C; Haiman, Christopher A; Hamsten, Anders; Hui, Jennie; Hunter, David J; Hveem, Kristian; Kaplan, Robert C; Kivimaki, Mika; Kuh, Diana; Laakso, Markku; Liu, Yongmei; Martin, Nicholas G; März, Winfried; Melbye, Mads; Metspalu, Andres; Moebus, Susanne; Munroe, Patricia B; Njølstad, Inger; Oostra, Ben A; Palmer, Colin N A; Pedersen, Nancy L; Perola, Markus; Pérusse, Louis; Peters, Ulrike; Power, Chris; Quertermous, Thomas; Rauramaa, Rainer; Rivadeneira, Fernando; Saaristo, Timo E; Saleheen, Danish; Sattar, Naveed; Schadt, Eric E; Schlessinger, David; Slagboom, P Eline; Snieder, Harold; Spector, Tim D; Thorsteinsdottir, Unnur; Stumvoll, Michael; Tuomilehto, Jaakko; Uitterlinden, André G; Uusitupa, Matti; van der Harst, Pim; Walker, Mark; Wallaschofski, Henri; Wareham, Nicholas J; Watkins, Hugh; Weir, David R; Wichmann, H-Erich; Wilson, James F; Zanen, Pieter; Borecki, Ingrid B; Deloukas, Panos; Fox, Caroline S; Heid, Iris M; O'Connell, Jeffrey R; Strachan, David P; Stefansson, Kari; van Duijn, Cornelia M; Abecasis, Gonçalo R; Franke, Lude; Frayling, Timothy M; McCarthy, Mark I; Visscher, Peter M; Scherag, André; Willer, Cristen J; Boehnke, Michael; Mohlke, Karen L; Lindgren, Cecilia M; Beckmann, Jacques S; Barroso, Inês; North, Kari E; Ingelsson, Erik; Hirschhorn, Joel N; Loos, Ruth J F; Speliotes, Elizabeth K

2015-02-12

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

Probing nanoparticles and nanoparticle-conjugated biomolecules using time-of-flight secondary ion mass spectrometry.

PubMed

Kim, Young-Pil; Shon, Hyun Kyong; Shin, Seung Koo; Lee, Tae Geol

2015-01-01

Bio-conjugated nanoparticles have emerged as novel molecular probes in nano-biotechnology and nanomedicine and chemical analyses of their surfaces have become challenges. The time-of-flight (TOF) secondary ion mass spectrometry (SIMS) has been one of the most powerful surface characterization techniques for both nanoparticles and biomolecules. When combined with various nanoparticle-based signal enhancing strategies, TOF-SIMS can probe the functionalization of nanoparticles as well as their locations and interactions in biological systems. Especially, nanoparticle-based SIMS is an attractive approach for label-free drug screening because signal-enhancing nanoparticles can be designed to directly measure the enzyme activity. The chemical-specific imaging analysis using SIMS is also well suited to screen nanoparticles and nanoparticle-biomolecule conjugates in complex environments. This review presents some recent applications of nanoparticle-based TOF-SIMS to the chemical analysis of complex biological systems. © 2014 Wiley Periodicals, Inc.

Genetic studies of body mass index yield new insights for obesity biology

PubMed Central

Day, Felix R.; Powell, Corey; Vedantam, Sailaja; Buchkovich, Martin L.; Yang, Jian; Croteau-Chonka, Damien C.; Esko, Tonu; Fall, Tove; Ferreira, Teresa; Gustafsson, Stefan; Kutalik, Zoltán; Luan, Jian’an; Mägi, Reedik; Randall, Joshua C.; Winkler, Thomas W.; Wood, Andrew R.; Workalemahu, Tsegaselassie; Faul, Jessica D.; Smith, Jennifer A.; Zhao, Jing Hua; Zhao, Wei; Chen, Jin; Fehrmann, Rudolf; Hedman, Åsa K.; Karjalainen, Juha; Schmidt, Ellen M.; Absher, Devin; Amin, Najaf; Anderson, Denise; Beekman, Marian; Bolton, Jennifer L.; Bragg-Gresham, Jennifer L.; Buyske, Steven; Demirkan, Ayse; Deng, Guohong; Ehret, Georg B.; Feenstra, Bjarke; Feitosa, Mary F.; Fischer, Krista; Goel, Anuj; Gong, Jian; Jackson, Anne U.; Kanoni, Stavroula; Kleber, Marcus E.; Kristiansson, Kati; Lim, Unhee; Lotay, Vaneet; Mangino, Massimo; Leach, Irene Mateo; Medina-Gomez, Carolina; Medland, Sarah E.; Nalls, Michael A.; Palmer, Cameron D.; Pasko, Dorota; Pechlivanis, Sonali; Peters, Marjolein J.; Prokopenko, Inga; Shungin, Dmitry; Stančáková, Alena; Strawbridge, Rona J.; Sung, Yun Ju; Tanaka, Toshiko; Teumer, Alexander; Trompet, Stella; van der Laan, Sander W.; van Setten, Jessica; Van Vliet-Ostaptchouk, Jana V.; Wang, Zhaoming; Yengo, Loïc; Zhang, Weihua; Isaacs, Aaron; Albrecht, Eva; Ärnlöv, Johan; Arscott, Gillian M.; Attwood, Antony P.; Bandinelli, Stefania; Barrett, Amy; Bas, Isabelita N.; Bellis, Claire; Bennett, Amanda J.; Berne, Christian; Blagieva, Roza; Blüher, Matthias; Böhringer, Stefan; Bonnycastle, Lori L.; Böttcher, Yvonne; Boyd, Heather A.; Bruinenberg, Marcel; Caspersen, Ida H.; Chen, Yii-Der Ida; Clarke, Robert; Daw, E. Warwick; de Craen, Anton J. M.; Delgado, Graciela; Dimitriou, Maria; Doney, Alex S. F.; Eklund, Niina; Estrada, Karol; Eury, Elodie; Folkersen, Lasse; Fraser, Ross M.; Garcia, Melissa E.; Geller, Frank; Giedraitis, Vilmantas; Gigante, Bruna; Go, Alan S.; Golay, Alain; Goodall, Alison H.; Gordon, Scott D.; Gorski, Mathias; Grabe, Hans-Jörgen; Grallert, Harald; Grammer, Tanja B.; Gräßler, Jürgen; Grönberg, Henrik; Groves, Christopher J.; Gusto, Gaëlle; Haessler, Jeffrey; Hall, Per; Haller, Toomas; Hallmans, Goran; Hartman, Catharina A.; Hassinen, Maija; Hayward, Caroline; Heard-Costa, Nancy L.; Helmer, Quinta; Hengstenberg, Christian; Holmen, Oddgeir; Hottenga, Jouke-Jan; James, Alan L.; Jeff, Janina M.; Johansson, Åsa; Jolley, Jennifer; Juliusdottir, Thorhildur; Kinnunen, Leena; Koenig, Wolfgang; Koskenvuo, Markku; Kratzer, Wolfgang; Laitinen, Jaana; Lamina, Claudia; Leander, Karin; Lee, Nanette R.; Lichtner, Peter; Lind, Lars; Lindström, Jaana; Lo, Ken Sin; Lobbens, Stéphane; Lorbeer, Roberto; Lu, Yingchang; Mach, François; Magnusson, Patrik K. E.; Mahajan, Anubha; McArdle, Wendy L.; McLachlan, Stela; Menni, Cristina; Merger, Sigrun; Mihailov, Evelin; Milani, Lili; Moayyeri, Alireza; Monda, Keri L.; Morken, Mario A.; Mulas, Antonella; Müller, Gabriele; Müller-Nurasyid, Martina; Musk, Arthur W.; Nagaraja, Ramaiah; Nöthen, Markus M.; Nolte, Ilja M.; Pilz, Stefan; Rayner, Nigel W.; Renstrom, Frida; Rettig, Rainer; Ried, Janina S.; Ripke, Stephan; Robertson, Neil R.; Rose, Lynda M.; Sanna, Serena; Scharnagl, Hubert; Scholtens, Salome; Schumacher, Fredrick R.; Scott, William R.; Seufferlein, Thomas; Shi, Jianxin; Smith, Albert Vernon; Smolonska, Joanna; Stanton, Alice V.; Steinthorsdottir, Valgerdur; Stirrups, Kathleen; Stringham, Heather M.; Sundström, Johan; Swertz, Morris A.; Swift, Amy J.; Syvänen, Ann-Christine; Tan, Sian-Tsung; Tayo, Bamidele O.; Thorand, Barbara; Thorleifsson, Gudmar; Tyrer, Jonathan P.; Uh, Hae-Won; Vandenput, Liesbeth; Verhulst, Frank C.; Vermeulen, Sita H.; Verweij, Niek; Vonk, Judith M.; Waite, Lindsay L.; Warren, Helen R.; Waterworth, Dawn; Weedon, Michael N.; Wilkens, Lynne R.; Willenborg, Christina; Wilsgaard, Tom; Wojczynski, Mary K.; Wong, Andrew; Wright, Alan F.; Zhang, Qunyuan; Brennan, Eoin P.; Choi, Murim; Dastani, Zari; Drong, Alexander W.; Eriksson, Per; Franco-Cereceda, Anders; Gådin, Jesper R.; Gharavi, Ali G.; Goddard, Michael E.; Handsaker, Robert E.; Huang, Jinyan; Karpe, Fredrik; Kathiresan, Sekar; Keildson, Sarah; Kiryluk, Krzysztof; Kubo, Michiaki; Lee, Jong-Young; Liang, Liming; Lifton, Richard P.; Ma, Baoshan; McCarroll, Steven A.; McKnight, Amy J.; Min, Josine L.; Moffatt, Miriam F.; Montgomery, Grant W.; Murabito, Joanne M.; Nicholson, George; Nyholt, Dale R.; Okada, Yukinori; Perry, John R. B.; Dorajoo, Rajkumar; Reinmaa, Eva; Salem, Rany M.; Sandholm, Niina; Scott, Robert A.; Stolk, Lisette; Takahashi, Atsushi; Tanaka, Toshihiro; van ’t Hooft, Ferdinand M.; Vinkhuyzen, Anna A. E.; Westra, Harm-Jan; Zheng, Wei; Zondervan, Krina T.; Heath, Andrew C.; Arveiler, Dominique; Bakker, Stephan J. L.; Beilby, John; Bergman, Richard N.; Blangero, John; Bovet, Pascal; Campbell, Harry; Caulfield, Mark J.; Cesana, Giancarlo; Chakravarti, Aravinda; Chasman, Daniel I.; Chines, Peter S.; Collins, Francis S.; Crawford, Dana C.; Cupples, L. Adrienne; Cusi, Daniele; Danesh, John; de Faire, Ulf; den Ruijter, Hester M.; Dominiczak, Anna F.; Erbel, Raimund; Erdmann, Jeanette; Eriksson, Johan G.; Farrall, Martin; Felix, Stephan B.; Ferrannini, Ele; Ferrières, Jean; Ford, Ian; Forouhi, Nita G.; Forrester, Terrence; Franco, Oscar H.; Gansevoort, Ron T.; Gejman, Pablo V.; Gieger, Christian; Gottesman, Omri; Gudnason, Vilmundur; Gyllensten, Ulf; Hall, Alistair S.; Harris, Tamara B.; Hattersley, Andrew T.; Hicks, Andrew A.; Hindorff, Lucia A.; Hingorani, Aroon D.; Hofman, Albert; Homuth, Georg; Hovingh, G. Kees; Humphries, Steve E.; Hunt, Steven C.; Hyppönen, Elina; Illig, Thomas; Jacobs, Kevin B.; Jarvelin, Marjo-Riitta; Jöckel, Karl-Heinz; Johansen, Berit; Jousilahti, Pekka; Jukema, J. Wouter; Jula, Antti M.; Kaprio, Jaakko; Kastelein, John J. P.; Keinanen-Kiukaanniemi, Sirkka M.; Kiemeney, Lambertus A.; Knekt, Paul; Kooner, Jaspal S.; Kooperberg, Charles; Kovacs, Peter; Kraja, Aldi T.; Kumari, Meena; Kuusisto, Johanna; Lakka, Timo A.; Langenberg, Claudia; Marchand, Loic Le; Lehtimäki, Terho; Lyssenko, Valeriya; Männistö, Satu; Marette, André; Matise, Tara C.; McKenzie, Colin A.; McKnight, Barbara; Moll, Frans L.; Morris, Andrew D.; Morris, Andrew P.; Murray, Jeffrey C.; Nelis, Mari; Ohlsson, Claes; Oldehinkel, Albertine J.; Ong, Ken K.; Madden, Pamela A. F.; Pasterkamp, Gerard; Peden, John F.; Peters, Annette; Postma, Dirkje S.; Pramstaller, Peter P.; Price, Jackie F.; Qi, Lu; Raitakari, Olli T.; Rankinen, Tuomo; Rao, D. C.; Rice, Treva K.; Ridker, Paul M.; Rioux, John D.; Ritchie, Marylyn D.; Rudan, Igor; Salomaa, Veikko; Samani, Nilesh J.; Saramies, Jouko; Sarzynski, Mark A.; Schunkert, Heribert; Schwarz, Peter E. H.; Sever, Peter; Shuldiner, Alan R.; Sinisalo, Juha; Stolk, Ronald P.; Strauch, Konstantin; Tönjes, Anke; Trégouët, David-Alexandre; Tremblay, Angelo; Tremoli, Elena; Virtamo, Jarmo; Vohl, Marie-Claude; Völker, Uwe; Waeber, Gérard; Willemsen, Gonneke; Witteman, Jacqueline C.; Zillikens, M. Carola; Adair, Linda S.; Amouyel, Philippe; Asselbergs, Folkert W.; Assimes, Themistocles L.; Bochud, Murielle; Boehm, Bernhard O.; Boerwinkle, Eric; Bornstein, Stefan R.; Bottinger, Erwin P.; Bouchard, Claude; Cauchi, Stéphane; Chambers, John C.; Chanock, Stephen J.; Cooper, Richard S.; de Bakker, Paul I. W.; Dedoussis, George; Ferrucci, Luigi; Franks, Paul W.; Froguel, Philippe; Groop, Leif C.; Haiman, Christopher A.; Hamsten, Anders; Hui, Jennie; Hunter, David J.; Hveem, Kristian; Kaplan, Robert C.; Kivimaki, Mika; Kuh, Diana; Laakso, Markku; Liu, Yongmei; Martin, Nicholas G.; März, Winfried; Melbye, Mads; Metspalu, Andres; Moebus, Susanne; Munroe, Patricia B.; Njølstad, Inger; Oostra, Ben A.; Palmer, Colin N. A.; Pedersen, Nancy L.; Perola, Markus; Pérusse, Louis; Peters, Ulrike; Power, Chris; Quertermous, Thomas; Rauramaa, Rainer; Rivadeneira, Fernando; Saaristo, Timo E.; Saleheen, Danish; Sattar, Naveed; Schadt, Eric E.; Schlessinger, David; Slagboom, P. Eline; Snieder, Harold; Spector, Tim D.; Thorsteinsdottir, Unnur; Stumvoll, Michael; Tuomilehto, Jaakko; Uitterlinden, André G.; Uusitupa, Matti; van der Harst, Pim; Walker, Mark; Wallaschofski, Henri; Wareham, Nicholas J.; Watkins, Hugh; Weir, David R.; Wichmann, H-Erich; Wilson, James F.; Zanen, Pieter; Borecki, Ingrid B.; Deloukas, Panos; Fox, Caroline S.; Heid, Iris M.; O’Connell, Jeffrey R.; Strachan, David P.; Stefansson, Kari; van Duijn, Cornelia M.; Abecasis, Gonçalo R.; Franke, Lude; Frayling, Timothy M.; McCarthy, Mark I.; Visscher, Peter M.; Scherag, André; Willer, Cristen J.; Boehnke, Michael; Mohlke, Karen L.; Lindgren, Cecilia M.; Beckmann, Jacques S.; Barroso, Inês; North, Kari E.; Ingelsson, Erik; Hirschhorn, Joel N.; Loos, Ruth J. F.; Speliotes, Elizabeth K.

2015-01-01

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10−8), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ~2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis. PMID:25673413

RE-PLAN: An Extensible Software Architecture to Facilitate Disaster Response Planning

PubMed Central

O’Neill, Martin; Mikler, Armin R.; Indrakanti, Saratchandra; Tiwari, Chetan; Jimenez, Tamara

2014-01-01

Computational tools are needed to make data-driven disaster mitigation planning accessible to planners and policymakers without the need for programming or GIS expertise. To address this problem, we have created modules to facilitate quantitative analyses pertinent to a variety of different disaster scenarios. These modules, which comprise the REsponse PLan ANalyzer (RE-PLAN) framework, may be used to create tools for specific disaster scenarios that allow planners to harness large amounts of disparate data and execute computational models through a point-and-click interface. Bio-E, a user-friendly tool built using this framework, was designed to develop and analyze the feasibility of ad hoc clinics for treating populations following a biological emergency event. In this article, the design and implementation of the RE-PLAN framework are described, and the functionality of the modules used in the Bio-E biological emergency mitigation tool are demonstrated. PMID:25419503

Coral reefs promote the evolution of morphological diversity and ecological novelty in labrid fishes.

PubMed

Price, S A; Holzman, R; Near, T J; Wainwright, P C

2011-05-01

Although coral reefs are renowned biodiversity hotspots it is not known whether they also promote the evolution of exceptional ecomorphological diversity. We investigated this question by analysing a large functional morphological dataset of trophic characters within Labridae, a highly diverse group of fishes. Using an analysis that accounts for species relationships, the time available for diversification and model uncertainty we show that coral reef species have evolved functional morphological diversity twice as fast as non-reef species. In addition, coral reef species occupy 68.6% more trophic morphospace than non-reef species. Our results suggest that coral reef habitats promote the evolution of both trophic novelty and morphological diversity within fishes. Thus, the preservation of coral reefs is necessary, not only to safeguard current biological diversity but also to conserve the underlying mechanisms that can produce functional diversity in future. © 2011 Blackwell Publishing Ltd/CNRS.

Comparing functional responses in predator-infected eco-epidemics models.

PubMed

Haque, Mainul; Rahman, Md Sabiar; Venturino, Ezio

2013-11-01

The current paper deals with the mathematical models of predator-prey system where a transmissible disease spreads among the predator species only. Four mathematical models are proposed and analysed with several popular predator functional responses in order to show the influence of functional response on eco-epidemic models. The existence, boundedness, uniqueness of solutions of all the models are established. Mathematical analysis including stability and bifurcation are observed. Comparison among the results of these models allows the general conclusion that relevant behaviour of the eco-epidemic predator-prey system, including switching of stability, extinction, persistence and oscillations for any species depends on four important parameters viz. the rate of infection, predator interspecies competition and the attack rate on susceptible predator. The paper ends with a discussion of the biological implications of the analytical and numerical results. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Functional dynamics of cell surface membrane proteins

NASA Astrophysics Data System (ADS)

Nishida, Noritaka; Osawa, Masanori; Takeuchi, Koh; Imai, Shunsuke; Stampoulis, Pavlos; Kofuku, Yutaka; Ueda, Takumi; Shimada, Ichio

2014-04-01

Cell surface receptors are integral membrane proteins that receive external stimuli, and transmit signals across plasma membranes. In the conventional view of receptor activation, ligand binding to the extracellular side of the receptor induces conformational changes, which convert the structure of the receptor into an active conformation. However, recent NMR studies of cell surface membrane proteins have revealed that their structures are more dynamic than previously envisioned, and they fluctuate between multiple conformations in an equilibrium on various timescales. In addition, NMR analyses, along with biochemical and cell biological experiments indicated that such dynamical properties are critical for the proper functions of the receptors. In this review, we will describe several NMR studies that revealed direct linkage between the structural dynamics and the functions of the cell surface membrane proteins, such as G-protein coupled receptors (GPCRs), ion channels, membrane transporters, and cell adhesion molecules.

Functional dynamics of cell surface membrane proteins.

PubMed

Nishida, Noritaka; Osawa, Masanori; Takeuchi, Koh; Imai, Shunsuke; Stampoulis, Pavlos; Kofuku, Yutaka; Ueda, Takumi; Shimada, Ichio

2014-04-01

Cell surface receptors are integral membrane proteins that receive external stimuli, and transmit signals across plasma membranes. In the conventional view of receptor activation, ligand binding to the extracellular side of the receptor induces conformational changes, which convert the structure of the receptor into an active conformation. However, recent NMR studies of cell surface membrane proteins have revealed that their structures are more dynamic than previously envisioned, and they fluctuate between multiple conformations in an equilibrium on various timescales. In addition, NMR analyses, along with biochemical and cell biological experiments indicated that such dynamical properties are critical for the proper functions of the receptors. In this review, we will describe several NMR studies that revealed direct linkage between the structural dynamics and the functions of the cell surface membrane proteins, such as G-protein coupled receptors (GPCRs), ion channels, membrane transporters, and cell adhesion molecules. Copyright © 2013 Elsevier Inc. All rights reserved.

Comparative Proteomic Profiling and Biomarker Identification of Traditional Chinese Medicine-Based HIV/AIDS Syndromes.

PubMed

Wen, Li; Liu, Ye-Fang; Jiang, Cen; Zeng, Shao-Qian; Su, Yue; Wu, Wen-Jun; Liu, Xi-Yang; Wang, Jian; Liu, Ying; Su, Chen; Li, Bai-Xue; Feng, Quan-Sheng

2018-03-08

Given the challenges in exploring lifelong therapy with little side effect for human immunodeficiency virus infection and acquired immune deficiency syndrome (HIV/AIDS) cases, there is increasing interest in developing traditional Chinese medicine (TCM) treatments based on specific TCM syndrome. However, there are few objective and biological evidences for classification and diagnosis of HIV/AIDS TCM syndromes to date. In this study, iTRAQ-2DLC-MS/MS coupled with bioinformatics were firstly employed for comparative proteomic profiling of top popular TCM syndromes of HIV/AIDS: accumulation of heat-toxicity (AHT) and Yang deficiency of spleen and kidney (YDSK). It was found that for the two TCM syndromes, the identified differential expressed proteins (DEPs) as well as their biological function distributions and participation in signaling pathways were significantly different, providing biological evidence for the classification of HIV/AIDS TCM syndromes. Furthermore, the TCM syndrome-specific DEPs were confirmed as biomarkers based on western blot analyses, including FN1, GPX3, KRT10 for AHT and RBP4, ApoE, KNG1 for YDSK. These biomarkers also biologically linked with the specific TCM syndrome closely. Thus the clinical and biological basis for differentiation and diagnosis of HIV/AIDs TCM syndromes were provided for the first time, providing more opportunities for stable exertion and better application of TCM efficacy and superiority in HIV/AIDS treatment.

Ratio index variables or ANCOVA? Fisher's cats revisited.

PubMed

Tu, Yu-Kang; Law, Graham R; Ellison, George T H; Gilthorpe, Mark S

2010-01-01

Over 60 years ago Ronald Fisher demonstrated a number of potential pitfalls with statistical analyses using ratio variables. Nonetheless, these pitfalls are largely overlooked in contemporary clinical and epidemiological research, which routinely uses ratio variables in statistical analyses. This article aims to demonstrate how very different findings can be generated as a result of less than perfect correlations among the data used to generate ratio variables. These imperfect correlations result from measurement error and random biological variation. While the former can often be reduced by improvements in measurement, random biological variation is difficult to estimate and eliminate in observational studies. Moreover, wherever the underlying biological relationships among epidemiological variables are unclear, and hence the choice of statistical model is also unclear, the different findings generated by different analytical strategies can lead to contradictory conclusions. Caution is therefore required when interpreting analyses of ratio variables whenever the underlying biological relationships among the variables involved are unspecified or unclear. (c) 2009 John Wiley & Sons, Ltd.

Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online

PubMed Central

Forsberg, Erica M; Huan, Tao; Rinehart, Duane; Benton, H Paul; Warth, Benedikt; Hilmers, Brian; Siuzdak, Gary

2018-01-01

Systems biology is the study of complex living organisms, and as such, analysis on a systems-wide scale involves the collection of information-dense data sets that are representative of an entire phenotype. To uncover dynamic biological mechanisms, bioinformatics tools have become essential to facilitating data interpretation in large-scale analyses. Global metabolomics is one such method for performing systems biology, as metabolites represent the downstream functional products of ongoing biological processes. We have developed XCMS Online, a platform that enables online metabolomics data processing and interpretation. A systems biology workflow recently implemented within XCMS Online enables rapid metabolic pathway mapping using raw metabolomics data for investigating dysregulated metabolic processes. In addition, this platform supports integration of multi-omic (such as genomic and proteomic) data to garner further systems-wide mechanistic insight. Here, we provide an in-depth procedure showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography (LCLC)–mass spectrometry (MS) data from metabolite-extracted biological samples, defining the job parameters to identify features, correcting for retention time deviations, conducting statistical analysis of features between sample classes and performing predictive metabolic pathway analysis. Additional multi-omics data can be uploaded and overlaid with previously identified pathways to enhance systems-wide analysis of the observed dysregulations. We also describe unique visualization tools to assist in elucidation of statistically significant dysregulated metabolic pathways. Parameter input takes 5–10 min, depending on user experience; data processing typically takes 1–3 h, and data analysis takes ~30 min. PMID:29494574

Database of cattle candidate genes and genetic markers for milk production and mastitis

PubMed Central

Ogorevc, J; Kunej, T; Razpet, A; Dovc, P

2009-01-01

A cattle database of candidate genes and genetic markers for milk production and mastitis has been developed to provide an integrated research tool incorporating different types of information supporting a genomic approach to study lactation, udder development and health. The database contains 943 genes and genetic markers involved in mammary gland development and function, representing candidates for further functional studies. The candidate loci were drawn on a genetic map to reveal positional overlaps. For identification of candidate loci, data from seven different research approaches were exploited: (i) gene knockouts or transgenes in mice that result in specific phenotypes associated with mammary gland (143 loci); (ii) cattle QTL for milk production (344) and mastitis related traits (71); (iii) loci with sequence variations that show specific allele-phenotype interactions associated with milk production (24) or mastitis (10) in cattle; (iv) genes with expression profiles associated with milk production (207) or mastitis (107) in cattle or mouse; (v) cattle milk protein genes that exist in different genetic variants (9); (vi) miRNAs expressed in bovine mammary gland (32) and (vii) epigenetically regulated cattle genes associated with mammary gland function (1). Fourty-four genes found by multiple independent analyses were suggested as the most promising candidates and were further in silico analysed for expression levels in lactating mammary gland, genetic variability and top biological functions in functional networks. A miRNA target search for mammary gland expressed miRNAs identified 359 putative binding sites in 3′UTRs of candidate genes. PMID:19508288

Genomic analysis of expressed sequence tags in American black bear Ursus americanus

PubMed Central

2010-01-01

Background Species of the bear family (Ursidae) are important organisms for research in molecular evolution, comparative physiology and conservation biology, but relatively little genetic sequence information is available for this group. Here we report the development and analyses of the first large scale Expressed Sequence Tag (EST) resource for the American black bear (Ursus americanus). Results Comprehensive analyses of molecular functions, alternative splicing, and tissue-specific expression of 38,757 black bear EST sequences were conducted using the dog genome as a reference. We identified 18 genes, involved in functions such as lipid catabolism, cell cycle, and vesicle-mediated transport, that are showing rapid evolution in the bear lineage Three genes, Phospholamban (PLN), cysteine glycine-rich protein 3 (CSRP3) and Troponin I type 3 (TNNI3), are related to heart contraction, and defects in these genes in humans lead to heart disease. Two genes, biphenyl hydrolase-like (BPHL) and CSRP3, contain positively selected sites in bear. Global analysis of evolution rates of hibernation-related genes in bear showed that they are largely conserved and slowly evolving genes, rather than novel and fast-evolving genes. Conclusion We provide a genomic resource for an important mammalian organism and our study sheds new light on the possible functions and evolution of bear genes. PMID:20338065

Genomic analysis of expressed sequence tags in American black bear Ursus americanus.

PubMed

Zhao, Sen; Shao, Chunxuan; Goropashnaya, Anna V; Stewart, Nathan C; Xu, Yichi; Tøien, Øivind; Barnes, Brian M; Fedorov, Vadim B; Yan, Jun

2010-03-26

Species of the bear family (Ursidae) are important organisms for research in molecular evolution, comparative physiology and conservation biology, but relatively little genetic sequence information is available for this group. Here we report the development and analyses of the first large scale Expressed Sequence Tag (EST) resource for the American black bear (Ursus americanus). Comprehensive analyses of molecular functions, alternative splicing, and tissue-specific expression of 38,757 black bear EST sequences were conducted using the dog genome as a reference. We identified 18 genes, involved in functions such as lipid catabolism, cell cycle, and vesicle-mediated transport, that are showing rapid evolution in the bear lineage Three genes, Phospholamban (PLN), cysteine glycine-rich protein 3 (CSRP3) and Troponin I type 3 (TNNI3), are related to heart contraction, and defects in these genes in humans lead to heart disease. Two genes, biphenyl hydrolase-like (BPHL) and CSRP3, contain positively selected sites in bear. Global analysis of evolution rates of hibernation-related genes in bear showed that they are largely conserved and slowly evolving genes, rather than novel and fast-evolving genes. We provide a genomic resource for an important mammalian organism and our study sheds new light on the possible functions and evolution of bear genes.

A Systematic Review of the Cost-Effectiveness of Biologics for Ulcerative Colitis.

PubMed

Stawowczyk, Ewa; Kawalec, Paweł

2018-04-01

Ulcerative colitis (UC) is a chronic autoimmune inflammation of the colon. The condition significantly decreases quality of life and generates a substantial economic burden for healthcare payers, patients and the society in which they live. Some patients require chronic pharmacotherapy, and access to novel biologic drugs might be crucial for long-term remission. The analyses of cost-effectiveness for biologic drugs are necessary to assess their efficiency and provide the best available drugs to patients. Our aim was to collect and assess the quality of economic analyses carried out for biologic agents used in the treatment of UC, as well as to summarize evidence on the drivers of cost-effectiveness and evaluate the transferability and generalizability of conclusions. A systematic database review was conducted using MEDLINE (via PubMed), EMBASE, Cost-Effectiveness Analysis Registry and CRD0. Both authors independently reviewed the identified articles to determine their eligibility for final review. Hand searching of references in collected papers was also performed to find any relevant articles. The reporting quality of economic analyses included was evaluated by two reviewers using the International Society of Pharmacoeconomics and Outcomes Research (ISPOR) Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement checklist. We reviewed the sensitivity analyses in cost-effectiveness analyses to identify the variables that may have changed the conclusions of the study. Key drivers of cost-effectiveness were selected by identifying uncertain parameters that caused the highest change of the results of the analyses compared with base-case results. Of the 576 identified records, 87 were excluded as duplicates and 16 studies were included in the final review; evaluations for Canada, the UK and Poland were mostly performed. The majority of the evaluations revealed were performed for infliximab (approximately 75% of total volume); however, some assessments were also performed for adalimumab (50%) and golimumab (31%). Only three analyses were conducted for vedolizumab, whereas no relevant studies were found for etrolizumab and tofacitinib. The reporting quality of the included economic analyses was assessed as high, with an average score of 21 points per 24 maximum possible (range 14-23 points according to the ISPOR CHEERS statement checklist). In the case of most analyses, quality-adjusted life-years were used as a clinical outcome, and endpoints such as remission, response and mucosal healing were less common. The higher clinical effectiveness (based on response rates) of biological treatment over non-biological treatments was presented in revealed analyses. The incremental cost-utility ratios for biologics, compared with standard care, varied significantly between the studies and ranged from US$36,309 to US$456,979. The lowest value was obtained for infliximab and the highest for the treatment scheme including infliximab 5 mg/kg and infliximab 10 mg/kg + adalimumab. The change of utility weights and clinical parameters had the most significant influence on the results of the analysis; the variable related to surgery was the least sensitive. Limited data on the cost-effectiveness of UC therapy were identified. In the majority of studies, the lack of cost-effectiveness was revealed for biologics, which was associated with their high costs. Clinical outcomes are transferable to other countries and could be generalized; however, cost inputs are country-specific and therefore limit the transferability and generalizability of conclusions. The key drivers and variables that showed the greatest effect on the analysis results were utility weights and clinical parameters.

Metabonomics Indicates Inhibition of Fatty Acid Synthesis, β-Oxidation, and Tricarboxylic Acid Cycle in Triclocarban-Induced Cardiac Metabolic Alterations in Male Mice.

PubMed

Xie, Wenping; Zhang, Wenpeng; Ren, Juan; Li, Wentao; Zhou, Lili; Cui, Yuan; Chen, Huiming; Yu, Wenlian; Zhuang, Xiaomei; Zhang, Zhenqing; Shen, Guolin; Li, Haishan

2018-02-14

Triclocarban (TCC) has been identified as a new environmental pollutant that is potentially hazardous to human health; however, the effects of short-term TCC exposure on cardiac function are not known. The aim of this study was to use metabonomics and molecular biology techniques to systematically elucidate the molecular mechanisms of TCC-induced effects on cardiac function in mice. Our results show that TCC inhibited the uptake, synthesis, and oxidation of fatty acids, suppressed the tricarboxylic acid (TCA) cycle, and increased aerobic glycolysis levels in heart tissue after short-term TCC exposure. TCC also inhibited the nuclear peroxisome proliferator-activated receptor α (PPARα), confirming its inhibitory effects on fatty acid uptake and oxidation. Histopathology and other analyses further confirm that TCC altered mouse cardiac physiology and pathology, ultimately affecting normal cardiac metabolic function. We elucidate the molecular mechanisms of TCC-induced harmful effects on mouse cardiac metabolism and function from a new perspective, using metabonomics and bioinformatics analysis data.

[Fine mapping of complex disease susceptibility loci].

PubMed

Song, Qingfeng; Zhang, Hongxing; Ma, Yilong; Zhou, Gangqiao

2014-01-01

Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers have identified more than 3800 susceptibility loci for more than 660 diseases or traits. However, the most significantly associated variants or causative variants in these loci and their biological functions have remained to be clarified. These causative variants can help to elucidate the pathogenesis and discover new biomarkers of complex diseases. One of the main goals in the post-GWAS era is to identify the causative variants and susceptibility genes, and clarify their functional aspects by fine mapping. For common variants, imputation or re-sequencing based strategies were implemented to increase the number of analyzed variants and help to identify the most significantly associated variants. In addition, functional element, expression quantitative trait locus (eQTL) and haplotype analyses were performed to identify functional common variants and susceptibility genes. For rare variants, fine mapping was carried out by re-sequencing, rare haplotype analysis, family-based analysis, burden test, etc.This review summarizes the strategies and problems for fine mapping.

Liquid biopsy in cancer patients: advances in capturing viable CTCs for functional studies using the EPISPOT assay.

PubMed

Alix-Panabières, Catherine; Pantel, Klaus

2015-01-01

Circulating tumor cells (CTCs) in the blood of cancer patients have received increasing attention as new diagnostic tool enabling 'liquid biopsies'. In contrast to the wealth of descriptive studies demonstrating the clinical relevance of CTCs as biomarkers, the extremely low concentration of CTCs in the peripheral blood of most cancer patients challenges further functional studies. This article discusses the current possibilities to enrich and, in particular, detect viable CTCs with emphasis on the EPithelial ImmunoSPOT technology. This functional assay detects viable CTCs at the single-cell level and has been used on hundreds of patients with different tumor types including epithelial tumors (breast, prostate and colon cancer) and melanomas. Moreover, the article summarizes recent advances in the in vitro and in vivo expansion of CTCs from cancer patients. These functional analyses will contribute to identifying the biological properties of metastatic cells and reveal new therapeutic targets against disseminating cancer cells.

Disease Model Discovery from 3,328 Gene Knockouts by The International Mouse Phenotyping Consortium

PubMed Central

Meehan, Terrence F.; Conte, Nathalie; West, David B.; Jacobsen, Julius O.; Mason, Jeremy; Warren, Jonathan; Chen, Chao-Kung; Tudose, Ilinca; Relac, Mike; Matthews, Peter; Karp, Natasha; Santos, Luis; Fiegel, Tanja; Ring, Natalie; Westerberg, Henrik; Greenaway, Simon; Sneddon, Duncan; Morgan, Hugh; Codner, Gemma F; Stewart, Michelle E; Brown, James; Horner, Neil; Haendel, Melissa; Washington, Nicole; Mungall, Christopher J.; Reynolds, Corey L; Gallegos, Juan; Gailus-Durner, Valerie; Sorg, Tania; Pavlovic, Guillaume; Bower, Lynette R; Moore, Mark; Morse, Iva; Gao, Xiang; Tocchini-Valentini, Glauco P; Obata, Yuichi; Cho, Soo Young; Seong, Je Kyung; Seavitt, John; Beaudet, Arthur L.; Dickinson, Mary E.; Herault, Yann; Wurst, Wolfgang; de Angelis, Martin Hrabe; Lloyd, K.C. Kent; Flenniken, Ann M; Nutter, Lauryl MJ; Newbigging, Susan; McKerlie, Colin; Justice, Monica J.; Murray, Stephen A.; Svenson, Karen L.; Braun, Robert E.; White, Jacqueline K.; Bradley, Allan; Flicek, Paul; Wells, Sara; Skarnes, William C.; Adams, David J.; Parkinson, Helen; Mallon, Ann-Marie; Brown, Steve D.M.; Smedley, Damian

2017-01-01

Although next generation sequencing has revolutionised the ability to associate variants with human diseases, diagnostic rates and development of new therapies are still limited by our lack of knowledge of function and pathobiological mechanism for most genes. To address this challenge, the International Mouse Phenotyping Consortium (IMPC) is creating a genome- and phenome-wide catalogue of gene function by characterizing new knockout mouse strains across diverse biological systems through a broad set of standardised phenotyping tests, with all mice made readily available to the biomedical community. Analysing the first 3328 genes reveals models for 360 diseases including the first for type C Bernard-Soulier, Bardet-Biedl-5 and Gordon Holmes syndromes. 90% of our phenotype annotations are novel, providing the first functional evidence for 1092 genes and candidates in unsolved diseases such as Arrhythmogenic Right Ventricular Dysplasia 3. Finally, we describe our role in variant functional validation with the 100,000 Genomes and other projects. PMID:28650483

Visualising biological data: a semantic approach to tool and database integration

PubMed Central

Pettifer, Steve; Thorne, David; McDermott, Philip; Marsh, James; Villéger, Alice; Kell, Douglas B; Attwood, Teresa K

2009-01-01

Motivation In the biological sciences, the need to analyse vast amounts of information has become commonplace. Such large-scale analyses often involve drawing together data from a variety of different databases, held remotely on the internet or locally on in-house servers. Supporting these tasks are ad hoc collections of data-manipulation tools, scripting languages and visualisation software, which are often combined in arcane ways to create cumbersome systems that have been customised for a particular purpose, and are consequently not readily adaptable to other uses. For many day-to-day bioinformatics tasks, the sizes of current databases, and the scale of the analyses necessary, now demand increasing levels of automation; nevertheless, the unique experience and intuition of human researchers is still required to interpret the end results in any meaningful biological way. Putting humans in the loop requires tools to support real-time interaction with these vast and complex data-sets. Numerous tools do exist for this purpose, but many do not have optimal interfaces, most are effectively isolated from other tools and databases owing to incompatible data formats, and many have limited real-time performance when applied to realistically large data-sets: much of the user's cognitive capacity is therefore focused on controlling the software and manipulating esoteric file formats rather than on performing the research. Methods To confront these issues, harnessing expertise in human-computer interaction (HCI), high-performance rendering and distributed systems, and guided by bioinformaticians and end-user biologists, we are building reusable software components that, together, create a toolkit that is both architecturally sound from a computing point of view, and addresses both user and developer requirements. Key to the system's usability is its direct exploitation of semantics, which, crucially, gives individual components knowledge of their own functionality and allows them to interoperate seamlessly, removing many of the existing barriers and bottlenecks from standard bioinformatics tasks. Results The toolkit, named Utopia, is freely available from . PMID:19534744

Visualising biological data: a semantic approach to tool and database integration.

PubMed

Pettifer, Steve; Thorne, David; McDermott, Philip; Marsh, James; Villéger, Alice; Kell, Douglas B; Attwood, Teresa K

2009-06-16

In the biological sciences, the need to analyse vast amounts of information has become commonplace. Such large-scale analyses often involve drawing together data from a variety of different databases, held remotely on the internet or locally on in-house servers. Supporting these tasks are ad hoc collections of data-manipulation tools, scripting languages and visualisation software, which are often combined in arcane ways to create cumbersome systems that have been customized for a particular purpose, and are consequently not readily adaptable to other uses. For many day-to-day bioinformatics tasks, the sizes of current databases, and the scale of the analyses necessary, now demand increasing levels of automation; nevertheless, the unique experience and intuition of human researchers is still required to interpret the end results in any meaningful biological way. Putting humans in the loop requires tools to support real-time interaction with these vast and complex data-sets. Numerous tools do exist for this purpose, but many do not have optimal interfaces, most are effectively isolated from other tools and databases owing to incompatible data formats, and many have limited real-time performance when applied to realistically large data-sets: much of the user's cognitive capacity is therefore focused on controlling the software and manipulating esoteric file formats rather than on performing the research. To confront these issues, harnessing expertise in human-computer interaction (HCI), high-performance rendering and distributed systems, and guided by bioinformaticians and end-user biologists, we are building reusable software components that, together, create a toolkit that is both architecturally sound from a computing point of view, and addresses both user and developer requirements. Key to the system's usability is its direct exploitation of semantics, which, crucially, gives individual components knowledge of their own functionality and allows them to interoperate seamlessly, removing many of the existing barriers and bottlenecks from standard bioinformatics tasks. The toolkit, named Utopia, is freely available from http://utopia.cs.man.ac.uk/.

Data Processing System (DPS) software with experimental design, statistical analysis and data mining developed for use in entomological research.

PubMed

Tang, Qi-Yi; Zhang, Chuan-Xi

2013-04-01

A comprehensive but simple-to-use software package called DPS (Data Processing System) has been developed to execute a range of standard numerical analyses and operations used in experimental design, statistics and data mining. This program runs on standard Windows computers. Many of the functions are specific to entomological and other biological research and are not found in standard statistical software. This paper presents applications of DPS to experimental design, statistical analysis and data mining in entomology. © 2012 The Authors Insect Science © 2012 Institute of Zoology, Chinese Academy of Sciences.