Enabling systematic interrogation of protein-protein interactions in live cells with a versatile ultra-high-throughput biosensor platform | Office of Cancer Genomics

Cancer.gov

The vast datasets generated by next generation gene sequencing and expression profiling have transformed biological and translational research. However, technologies to produce large-scale functional genomics datasets, such as high-throughput detection of protein-protein interactions (PPIs), are still in early development. While a number of powerful technologies have been employed to detect PPIs, a singular PPI biosensor platform featured with both high sensitivity and robustness in a mammalian cell environment remains to be established.

Novel Inducers of Fetal Globin Identified through High Throughput Screening (HTS) Are Active In Vivo in Anemic Baboons and Transgenic Mice.

PubMed

Boosalis, Michael S; Sangerman, Jose I; White, Gary L; Wolf, Roman F; Shen, Ling; Dai, Yan; White, Emily; Makala, Levi H; Li, Biaoru; Pace, Betty S; Nouraie, Mehdi; Faller, Douglas V; Perrine, Susan P

2015-01-01

High-level fetal (γ) globin expression ameliorates clinical severity of the beta (β) hemoglobinopathies, and safe, orally-bioavailable γ-globin inducing agents would benefit many patients. We adapted a LCR-γ-globin promoter-GFP reporter assay to a high-throughput robotic system to evaluate five diverse chemical libraries for this activity. Multiple structurally- and functionally-diverse compounds were identified which activate the γ-globin gene promoter at nanomolar concentrations, including some therapeutics approved for other conditions. Three candidates with established safety profiles were further evaluated in erythroid progenitors, anemic baboons and transgenic mice, with significant induction of γ-globin expression observed in vivo. A lead candidate, Benserazide, emerged which demonstrated > 20-fold induction of γ-globin mRNA expression in anemic baboons and increased F-cell proportions by 3.5-fold in transgenic mice. Benserazide has been used chronically to inhibit amino acid decarboxylase to enhance plasma levels of L-dopa. These studies confirm the utility of high-throughput screening and identify previously unrecognized fetal globin inducing candidates which can be developed expediently for treatment of hemoglobinopathies.

YAMAT-seq: an efficient method for high-throughput sequencing of mature transfer RNAs

PubMed Central

Shigematsu, Megumi; Honda, Shozo; Loher, Phillipe; Telonis, Aristeidis G.; Rigoutsos, Isidore

2017-01-01

Abstract Besides translation, transfer RNAs (tRNAs) play many non-canonical roles in various biological pathways and exhibit highly variable expression profiles. To unravel the emerging complexities of tRNA biology and molecular mechanisms underlying them, an efficient tRNA sequencing method is required. However, the rigid structure of tRNA has been presenting a challenge to the development of such methods. We report the development of Y-shaped Adapter-ligated MAture TRNA sequencing (YAMAT-seq), an efficient and convenient method for high-throughput sequencing of mature tRNAs. YAMAT-seq circumvents the issue of inefficient adapter ligation, a characteristic of conventional RNA sequencing methods for mature tRNAs, by employing the efficient and specific ligation of Y-shaped adapter to mature tRNAs using T4 RNA Ligase 2. Subsequent cDNA amplification and next-generation sequencing successfully yield numerous mature tRNA sequences. YAMAT-seq has high specificity for mature tRNAs and high sensitivity to detect most isoacceptors from minute amount of total RNA. Moreover, YAMAT-seq shows quantitative capability to estimate expression levels of mature tRNAs, and has high reproducibility and broad applicability for various cell lines. YAMAT-seq thus provides high-throughput technique for identifying tRNA profiles and their regulations in various transcriptomes, which could play important regulatory roles in translation and other biological processes. PMID:28108659

Analysis, annotation, and profiling of the oat seed transcriptome

USDA-ARS?s Scientific Manuscript database

Novel high-throughput next generation sequencing (NGS) technologies are providing opportunities to explore genomes and transcriptomes in a cost-effective manner. To construct a gene expression atlas of developing oat (Avena sativa) seeds, two software packages specifically designed for RNA-seq (Trin...

Validation of high-throughput single cell analysis methodology.

PubMed

Devonshire, Alison S; Baradez, Marc-Olivier; Morley, Gary; Marshall, Damian; Foy, Carole A

2014-05-01

High-throughput quantitative polymerase chain reaction (qPCR) approaches enable profiling of multiple genes in single cells, bringing new insights to complex biological processes and offering opportunities for single cell-based monitoring of cancer cells and stem cell-based therapies. However, workflows with well-defined sources of variation are required for clinical diagnostics and testing of tissue-engineered products. In a study of neural stem cell lines, we investigated the performance of lysis, reverse transcription (RT), preamplification (PA), and nanofluidic qPCR steps at the single cell level in terms of efficiency, precision, and limit of detection. We compared protocols using a separate lysis buffer with cell capture directly in RT-PA reagent. The two methods were found to have similar lysis efficiencies, whereas the direct RT-PA approach showed improved precision. Digital PCR was used to relate preamplified template copy numbers to Cq values and reveal where low-quality signals may affect the analysis. We investigated the impact of calibration and data normalization strategies as a means of minimizing the impact of inter-experimental variation on gene expression values and found that both approaches can improve data comparability. This study provides validation and guidance for the application of high-throughput qPCR workflows for gene expression profiling of single cells. Copyright © 2014 Elsevier Inc. All rights reserved.

Uncovering leaf rust responsive miRNAs in wheat (Triticum aestivum L.) using high-throughput sequencing and prediction of their targets through degradome analysis.

PubMed

Kumar, Dhananjay; Dutta, Summi; Singh, Dharmendra; Prabhu, Kumble Vinod; Kumar, Manish; Mukhopadhyay, Kunal

2017-01-01

Deep sequencing identified 497 conserved and 559 novel miRNAs in wheat, while degradome analysis revealed 701 targets genes. QRT-PCR demonstrated differential expression of miRNAs during stages of leaf rust progression. Bread wheat (Triticum aestivum L.) is an important cereal food crop feeding 30 % of the world population. Major threat to wheat production is the rust epidemics. This study was targeted towards identification and functional characterizations of micro(mi)RNAs and their target genes in wheat in response to leaf rust ingression. High-throughput sequencing was used for transcriptome-wide identification of miRNAs and their expression profiling in retort to leaf rust using mock and pathogen-inoculated resistant and susceptible near-isogenic wheat plants. A total of 1056 mature miRNAs were identified, of which 497 miRNAs were conserved and 559 miRNAs were novel. The pathogen-inoculated resistant plants manifested more miRNAs compared with the pathogen infected susceptible plants. The miRNA counts increased in susceptible isoline due to leaf rust, conversely, the counts decreased in the resistant isoline in response to pathogenesis illustrating precise spatial tuning of miRNAs during compatible and incompatible interaction. Stem-loop quantitative real-time PCR was used to profile 10 highly differentially expressed miRNAs obtained from high-throughput sequencing data. The spatio-temporal profiling validated the differential expression of miRNAs between the isolines as well as in retort to pathogen infection. Degradome analysis provided 701 predicted target genes associated with defense response, signal transduction, development, metabolism, and transcriptional regulation. The obtained results indicate that wheat isolines employ diverse arrays of miRNAs that modulate their target genes during compatible and incompatible interaction. Our findings contribute to increase knowledge on roles of microRNA in wheat-leaf rust interactions and could help in rust resistance breeding programs.

Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium

PubMed Central

Ryan, Natalia; Chorley, Brian; Tice, Raymond R.; Judson, Richard; Corton, J. Christopher

2016-01-01

Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including “very weak” agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. PMID:26865669

Novel Inducers of Fetal Globin Identified through High Throughput Screening (HTS) Are Active In Vivo in Anemic Baboons and Transgenic Mice

PubMed Central

Boosalis, Michael S.; Sangerman, Jose I.; White, Gary L.; Wolf, Roman F.; Shen, Ling; Dai, Yan; White, Emily; Makala, Levi H.; Li, Biaoru; Pace, Betty S.; Nouraie, Mehdi; Faller, Douglas V.; Perrine, Susan P.

2015-01-01

High-level fetal (γ) globin expression ameliorates clinical severity of the beta (β) hemoglobinopathies, and safe, orally-bioavailable γ-globin inducing agents would benefit many patients. We adapted a LCR-γ-globin promoter-GFP reporter assay to a high-throughput robotic system to evaluate five diverse chemical libraries for this activity. Multiple structurally- and functionally-diverse compounds were identified which activate the γ-globin gene promoter at nanomolar concentrations, including some therapeutics approved for other conditions. Three candidates with established safety profiles were further evaluated in erythroid progenitors, anemic baboons and transgenic mice, with significant induction of γ-globin expression observed in vivo. A lead candidate, Benserazide, emerged which demonstrated > 20-fold induction of γ-globin mRNA expression in anemic baboons and increased F-cell proportions by 3.5-fold in transgenic mice. Benserazide has been used chronically to inhibit amino acid decarboxylase to enhance plasma levels of L-dopa. These studies confirm the utility of high-throughput screening and identify previously unrecognized fetal globin inducing candidates which can be developed expediently for treatment of hemoglobinopathies. PMID:26713848

YAMAT-seq: an efficient method for high-throughput sequencing of mature transfer RNAs.

PubMed

Shigematsu, Megumi; Honda, Shozo; Loher, Phillipe; Telonis, Aristeidis G; Rigoutsos, Isidore; Kirino, Yohei

2017-05-19

Besides translation, transfer RNAs (tRNAs) play many non-canonical roles in various biological pathways and exhibit highly variable expression profiles. To unravel the emerging complexities of tRNA biology and molecular mechanisms underlying them, an efficient tRNA sequencing method is required. However, the rigid structure of tRNA has been presenting a challenge to the development of such methods. We report the development of Y-shaped Adapter-ligated MAture TRNA sequencing (YAMAT-seq), an efficient and convenient method for high-throughput sequencing of mature tRNAs. YAMAT-seq circumvents the issue of inefficient adapter ligation, a characteristic of conventional RNA sequencing methods for mature tRNAs, by employing the efficient and specific ligation of Y-shaped adapter to mature tRNAs using T4 RNA Ligase 2. Subsequent cDNA amplification and next-generation sequencing successfully yield numerous mature tRNA sequences. YAMAT-seq has high specificity for mature tRNAs and high sensitivity to detect most isoacceptors from minute amount of total RNA. Moreover, YAMAT-seq shows quantitative capability to estimate expression levels of mature tRNAs, and has high reproducibility and broad applicability for various cell lines. YAMAT-seq thus provides high-throughput technique for identifying tRNA profiles and their regulations in various transcriptomes, which could play important regulatory roles in translation and other biological processes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

High-throughput full-length single-cell mRNA-seq of rare cells.

PubMed

Ooi, Chin Chun; Mantalas, Gary L; Koh, Winston; Neff, Norma F; Fuchigami, Teruaki; Wong, Dawson J; Wilson, Robert J; Park, Seung-Min; Gambhir, Sanjiv S; Quake, Stephen R; Wang, Shan X

2017-01-01

Single-cell characterization techniques, such as mRNA-seq, have been applied to a diverse range of applications in cancer biology, yielding great insight into mechanisms leading to therapy resistance and tumor clonality. While single-cell techniques can yield a wealth of information, a common bottleneck is the lack of throughput, with many current processing methods being limited to the analysis of small volumes of single cell suspensions with cell densities on the order of 107 per mL. In this work, we present a high-throughput full-length mRNA-seq protocol incorporating a magnetic sifter and magnetic nanoparticle-antibody conjugates for rare cell enrichment, and Smart-seq2 chemistry for sequencing. We evaluate the efficiency and quality of this protocol with a simulated circulating tumor cell system, whereby non-small-cell lung cancer cell lines (NCI-H1650 and NCI-H1975) are spiked into whole blood, before being enriched for single-cell mRNA-seq by EpCAM-functionalized magnetic nanoparticles and the magnetic sifter. We obtain high efficiency (> 90%) capture and release of these simulated rare cells via the magnetic sifter, with reproducible transcriptome data. In addition, while mRNA-seq data is typically only used for gene expression analysis of transcriptomic data, we demonstrate the use of full-length mRNA-seq chemistries like Smart-seq2 to facilitate variant analysis of expressed genes. This enables the use of mRNA-seq data for differentiating cells in a heterogeneous population by both their phenotypic and variant profile. In a simulated heterogeneous mixture of circulating tumor cells in whole blood, we utilize this high-throughput protocol to differentiate these heterogeneous cells by both their phenotype (lung cancer versus white blood cells), and mutational profile (H1650 versus H1975 cells), in a single sequencing run. This high-throughput method can help facilitate single-cell analysis of rare cell populations, such as circulating tumor or endothelial cells, with demonstrably high-quality transcriptomic data.

Single-cell multimodal profiling reveals cellular epigenetic heterogeneity.

PubMed

Cheow, Lih Feng; Courtois, Elise T; Tan, Yuliana; Viswanathan, Ramya; Xing, Qiaorui; Tan, Rui Zhen; Tan, Daniel S W; Robson, Paul; Loh, Yuin-Han; Quake, Stephen R; Burkholder, William F

2016-10-01

Sample heterogeneity often masks DNA methylation signatures in subpopulations of cells. Here, we present a method to genotype single cells while simultaneously interrogating gene expression and DNA methylation at multiple loci. We used this targeted multimodal approach, implemented on an automated, high-throughput microfluidic platform, to assess primary lung adenocarcinomas and human fibroblasts undergoing reprogramming by profiling epigenetic variation among cell types identified through genotyping and transcriptional analysis.

Comparison of L1000 and Affymetrix Microarray for In Vitro Concentration-Response Gene Expression Profiling (SOT)

EPA Science Inventory

Advances in high-throughput screening technologies and in vitro systems have opened doors for cost-efficient evaluation of chemical effects on a diversity of biological endpoints. However, toxicogenomics platforms remain too costly to evaluate large libraries of chemicals in conc...

Genome-scale deletion screening of human long non-coding RNAs using a paired-guide RNA CRISPR library

PubMed Central

Zhu, Shiyou; Li, Wei; Liu, Jingze; Chen, Chen-Hao; Liao, Qi; Xu, Ping; Xu, Han; Xiao, Tengfei; Cao, Zhongzheng; Peng, Jingyu; Yuan, Pengfei; Brown, Myles; Liu, Xiaole Shirley; Wei, Wensheng

2017-01-01

CRISPR/Cas9 screens have been widely adopted to analyse coding gene functions, but high throughput screening of non-coding elements using this method is more challenging, because indels caused by a single cut in non-coding regions are unlikely to produce a functional knockout. A high-throughput method to produce deletions of non-coding DNA is needed. Herein, we report a high throughput genomic deletion strategy to screen for functional long non-coding RNAs (lncRNAs) that is based on a lentiviral paired-guide RNA (pgRNA) library. Applying our screening method, we identified 51 lncRNAs that can positively or negatively regulate human cancer cell growth. We individually validated 9 lncRNAs using CRISPR/Cas9-mediated genomic deletion and functional rescue, CRISPR activation or inhibition, and gene expression profiling. Our high-throughput pgRNA genome deletion method should enable rapid identification of functional mammalian non-coding elements. PMID:27798563

Targeted and genome-scale methylomics reveals gene body signatures in human cell lines

PubMed Central

Ball, Madeleine Price; Li, Jin Billy; Gao, Yuan; Lee, Je-Hyuk; LeProust, Emily; Park, In-Hyun; Xie, Bin; Daley, George Q.; Church, George M.

2012-01-01

Cytosine methylation, an epigenetic modification of DNA, is a target of growing interest for developing high throughput profiling technologies. Here we introduce two new, complementary techniques for cytosine methylation profiling utilizing next generation sequencing technology: bisulfite padlock probes (BSPPs) and methyl sensitive cut counting (MSCC). In the first method, we designed a set of ~10,000 BSPPs distributed over the ENCODE pilot project regions to take advantage of existing expression and chromatin immunoprecipitation data. We observed a pattern of low promoter methylation coupled with high gene body methylation in highly expressed genes. Using the second method, MSCC, we gathered genome-scale data for 1.4 million HpaII sites and confirmed that gene body methylation in highly expressed genes is a consistent phenomenon over the entire genome. Our observations highlight the usefulness of techniques which are not inherently or intentionally biased in favor of only profiling particular subsets like CpG islands or promoter regions. PMID:19329998

Advanced colorectal adenoma related gene expression signature may predict prognostic for colorectal cancer patients with adenoma-carcinoma sequence.

PubMed

Li, Bing; Shi, Xiao-Yu; Liao, Dai-Xiang; Cao, Bang-Rong; Luo, Cheng-Hua; Cheng, Shu-Jun

2015-01-01

There are still no absolute parameters predicting progression of adenoma into cancer. The present study aimed to characterize functional differences on the multistep carcinogenetic process from the adenoma-carcinoma sequence. All samples were collected and mRNA expression profiling was performed by using Agilent Microarray high-throughput gene-chip technology. Then, the characteristics of mRNA expression profiles of adenoma-carcinoma sequence were described with bioinformatics software, and we analyzed the relationship between gene expression profiles of adenoma-adenocarcinoma sequence and clinical prognosis of colorectal cancer. The mRNA expressions of adenoma-carcinoma sequence were significantly different between high-grade intraepithelial neoplasia group and adenocarcinoma group. The biological process of gene ontology function enrichment analysis on differentially expressed genes between high-grade intraepithelial neoplasia group and adenocarcinoma group showed that genes enriched in the extracellular structure organization, skeletal system development, biological adhesion and itself regulated growth regulation, with the P value after FDR correction of less than 0.05. In addition, IPR-related protein mainly focused on the insulin-like growth factor binding proteins. The variable trends of gene expression profiles for adenoma-carcinoma sequence were mainly concentrated in high-grade intraepithelial neoplasia and adenocarcinoma. The differentially expressed genes are significantly correlated between high-grade intraepithelial neoplasia group and adenocarcinoma group. Bioinformatics analysis is an effective way to study the gene expression profiles in the adenoma-carcinoma sequence, and may provide an effective tool to involve colorectal cancer research strategy into colorectal adenoma or advanced adenoma.

qFlow Cytometry-Based Receptoromic Screening: A High-Throughput Quantification Approach Informing Biomarker Selection and Nanosensor Development.

PubMed

Chen, Si; Weddell, Jared; Gupta, Pavan; Conard, Grace; Parkin, James; Imoukhuede, Princess I

2017-01-01

Nanosensor-based detection of biomarkers can improve medical diagnosis; however, a critical factor in nanosensor development is deciding which biomarker to target, as most diseases present several biomarkers. Biomarker-targeting decisions can be informed via an understanding of biomarker expression. Currently, immunohistochemistry (IHC) is the accepted standard for profiling biomarker expression. While IHC provides a relative mapping of biomarker expression, it does not provide cell-by-cell readouts of biomarker expression or absolute biomarker quantification. Flow cytometry overcomes both these IHC challenges by offering biomarker expression on a cell-by-cell basis, and when combined with calibration standards, providing quantitation of biomarker concentrations: this is known as qFlow cytometry. Here, we outline the key components for applying qFlow cytometry to detect biomarkers within the angiogenic vascular endothelial growth factor receptor family. The key aspects of the qFlow cytometry methodology include: antibody specificity testing, immunofluorescent cell labeling, saturation analysis, fluorescent microsphere calibration, and quantitative analysis of both ensemble and cell-by-cell data. Together, these methods enable high-throughput quantification of biomarker expression.

Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium.

PubMed

Ryan, Natalia; Chorley, Brian; Tice, Raymond R; Judson, Richard; Corton, J Christopher

2016-05-01

Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including "very weak" agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. Published by Oxford University Press on behalf of the Society of Toxicology 2016. This work is written by US Government employees and is in the public domain in the US.

[Expression profiles of the exosomal miRNAs in the chronic hepatitis B patients with persistently normal ALT].

PubMed

Li, Ronghua; Fu, Xiaoyu; Tang, Yujing; Fu, Lei; Tan, Deming; Ouyang, Yi; Peng, Shifang

2018-05-28

To investigate expression profiles of the plasma exosomal miRNAs of the chronic hepatitis B (CHB) patients with persistently normal alamine aminotransferase (PNALT) for the first time and try to find exosomal miRNAs which could reflect liver inflammation better. 
 Methods: Five CHB patients with liver tissue inflammation grade ≥A2 of PNALT and 5 CHB patients with liver tissue inflammation grade

High-throughput deep screening and identification of four peripheral leucocyte microRNAs as novel potential combination biomarkers for preeclampsia

PubMed Central

Wang, Yonghong; Yang, Xukui; Yang, Yuanyuan; Wang, Wenjun; Zhao, Meiling; Liu, Huiqiang; Li, Dongyan; Hao, Min

2016-01-01

Objective: To identify the specific microRNA (miRNA) biomarkers of preeclampsia (PE), the miRNA profiles analysis were performed. Study Design: The blood samples were obtained from five PE patients and five normal healthy pregnant women. The small RNA profiles were analyzed to identify miRNA expression levels and find out miRNAs that may associate with PE. The quantitative reverse transcriptase–PCR (qRT-PCR) assay was used to validate differentially expressed peripheral leucocyte miRNAs in a new cohort. Result: The data analysis showed that 10 peripheral leucocyte miRNAs were significantly differently expressed in severe PE patients. Four differently expressed miRNAs were successfully validated using qRT-PCR method. Conclusion: We successfully constructed a model with high accuracy to predict PE. A combination of four peripheral leucocyte miRNAs has great potential to serve as diagnostic biomarkers of PE. PMID:26675000

Gene Expression Analysis of Copper Tolerance and Wood Decay in the Brown Rot Fungus Fibroporia radiculosa

Treesearch

J. D. Tang; L. A. Parker; A. D. Perkins; T. S. Sonstegard; S. G. Schroeder; D. D. Nicholas; S. V. Diehl

2013-01-01

High-throughput transcriptomics was used to identify Fibroporia radiculosa genes that were differentially regulated during colonization of wood treated with a copper-based preservative. The transcriptome was profiled at two time points while the fungus was growing on wood treated with micronized copper quat (MCQ). A total of 917 transcripts were...

Cancer biomarker discovery: the entropic hallmark.

PubMed

Berretta, Regina; Moscato, Pablo

2010-08-18

It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases.

Impact of Profiling Technologies in the Understanding of Recombinant Protein Production

NASA Astrophysics Data System (ADS)

Vijayendran, Chandran; Flaschel, Erwin

Since expression profiling methods have been available in a high throughput fashion, the implication of these technologies in the field of biotechnology has increased dramatically. Microarray technology is one such unique and efficient methodology for simultaneous exploration of expression levels of numerous genes. Likewise, two-dimensional gel electrophoresis or multidimensional liquid chromatography coupled with mass spectrometry are extensively utilised for studying expression levels of numerous proteins. In the field of biotechnology these highly parallel analytical methods have paved the way to study and understand various biological phenomena depending on expression patterns. The next phenomenological level is represented by the metabolome and the (metabolic) fluxome. However, this chapter reviews gene and protein profiling and their impact on understanding recombinant protein production. We focus on the computational methods utilised for the analyses of data obtained from these profiling technologies as well as prominent results focusing on recombinant protein expression with Escherichia coli. Owing to the knowledge accumulated with respect to cellular signals triggered during recombinant protein production, this field is on the way to design strategies for developing improved processes. Both gene and protein profiling have exhibited a handful of functional categories to concentrate on in order to identify target genes and proteins, respectively, involved in the signalling network with major impact on recombinant protein production.

Single-cell genomic profiling of acute myeloid leukemia for clinical use: A pilot study

PubMed Central

Yan, Benedict; Hu, Yongli; Ban, Kenneth H.K.; Tiang, Zenia; Ng, Christopher; Lee, Joanne; Tan, Wilson; Chiu, Lily; Tan, Tin Wee; Seah, Elaine; Ng, Chin Hin; Chng, Wee-Joo; Foo, Roger

2017-01-01

Although bulk high-throughput genomic profiling studies have led to a significant increase in the understanding of cancer biology, there is increasing awareness that bulk profiling approaches do not completely elucidate tumor heterogeneity. Single-cell genomic profiling enables the distinction of tumor heterogeneity, and may improve clinical diagnosis through the identification and characterization of putative subclonal populations. In the present study, the challenges associated with a single-cell genomics profiling workflow for clinical diagnostics were investigated. Single-cell RNA-sequencing (RNA-seq) was performed on 20 cells from an acute myeloid leukemia bone marrow sample. Putative blasts were identified based on their gene expression profiles and principal component analysis was performed to identify outlier cells. Variant calling was performed on the single-cell RNA-seq data. The present pilot study demonstrates a proof of concept for clinical single-cell genomic profiling. The recognized limitations include significant stochastic RNA loss and the relatively low throughput of the current proposed platform. Although the results of the present study are promising, further technological advances and protocol optimization are necessary for single-cell genomic profiling to be clinically viable. PMID:28454300

MicroRNA-21 promotes proliferation of rat hepatocyte BRL-3A by targeting FASLG.

PubMed

Li, J J; Chan, W H; Leung, W Y; Wang, Y; Xu, C S

2015-04-27

Rat liver regeneration (RLR) induced by partial hepatectomy involves cell proliferation regulated by numerous factors, including microRNAs (miRNAs). miRNA high-throughput sequencing has been established and used to analyze miRNA expression profiles. This study showed that 39 miRNAs were related to RLR through the analysis of miRNA high-throughput sequencing. Their role toward rat normal hepatocyte line BRL-3A was studied by gain- and loss-of-function analyses, and one of them, microRNA-21 (miR-21), obviously upregulated and promoted BRL-3A cell proliferation. Using bioinformatics to search for miR-21 targets revealed that Fas ligand (FASLG) is one of miR-21's target genes. A dual-luciferase report assay and Western blot assay showed that miR-21 directly targeted the 3'-untranslated region of FASLG and inhibited the expression of FASLG, which suggests that miR-21 promoted BRL-3A cell proliferation by reducing FASLG expression.

In silico gene expression profiling in Cannabis sativa.

PubMed

Massimino, Luca

2017-01-01

The cannabis plant and its active ingredients (i.e., cannabinoids and terpenoids) have been socially stigmatized for half a century. Luckily, with more than 430,000 published scientific papers and about 600 ongoing and completed clinical trials, nowadays cannabis is employed for the treatment of many different medical conditions. Nevertheless, even if a large amount of high-throughput functional genomic data exists, most researchers feature a strong background in molecular biology but lack advanced bioinformatics skills. In this work, publicly available gene expression datasets have been analyzed giving rise to a total of 40,224 gene expression profiles taken from cannabis plant tissue at different developmental stages. The resource presented here will provide researchers with a starting point for future investigations with Cannabis sativa .

Unsupervised Outlier Profile Analysis

PubMed Central

Ghosh, Debashis; Li, Song

2014-01-01

In much of the analysis of high-throughput genomic data, “interesting” genes have been selected based on assessment of differential expression between two groups or generalizations thereof. Most of the literature focuses on changes in mean expression or the entire distribution. In this article, we explore the use of C(α) tests, which have been applied in other genomic data settings. Their use for the outlier expression problem, in particular with continuous data, is problematic but nevertheless motivates new statistics that give an unsupervised analog to previously developed outlier profile analysis approaches. Some simulation studies are used to evaluate the proposal. A bivariate extension is described that can accommodate data from two platforms on matched samples. The proposed methods are applied to data from a prostate cancer study. PMID:25452686

Customized Molecular Phenotyping by Quantitative Gene Expression and Pattern Recognition Analysis

PubMed Central

Akilesh, Shreeram; Shaffer, Daniel J.; Roopenian, Derry

2003-01-01

Description of the molecular phenotypes of pathobiological processes in vivo is a pressing need in genomic biology. We have implemented a high-throughput real-time PCR strategy to establish quantitative expression profiles of a customized set of target genes. It enables rapid, reproducible data acquisition from limited quantities of RNA, permitting serial sampling of mouse blood during disease progression. We developed an easy to use statistical algorithm—Global Pattern Recognition—to readily identify genes whose expression has changed significantly from healthy baseline profiles. This approach provides unique molecular signatures for rheumatoid arthritis, systemic lupus erythematosus, and graft versus host disease, and can also be applied to defining the molecular phenotype of a variety of other normal and pathological processes. PMID:12840047

Droplet barcoding for single cell transcriptomics applied to embryonic stem cells

PubMed Central

Klein, Allon M; Mazutis, Linas; Akartuna, Ilke; Tallapragada, Naren; Veres, Adrian; Li, Victor; Peshkin, Leonid; Weitz, David A; Kirschner, Marc W

2015-01-01

Summary It has long been the dream of biologists to map gene expression at the single cell level. With such data one might track heterogeneous cell sub-populations, and infer regulatory relationships between genes and pathways. Recently, RNA sequencing has achieved single cell resolution. What is limiting is an effective way to routinely isolate and process large numbers of individual cells for quantitative in-depth sequencing. We have developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing. The method shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays. We analyzed mouse embryonic stem cells, revealing in detail the population structure and the heterogeneous onset of differentiation after LIF withdrawal. The reproducibility of these high-throughput single cell data allowed us to deconstruct cell populations and infer gene expression relationships. PMID:26000487

Identifying kinase dependency in cancer cells by integrating high-throughput drug screening and kinase inhibition data.

PubMed

Ryall, Karen A; Shin, Jimin; Yoo, Minjae; Hinz, Trista K; Kim, Jihye; Kang, Jaewoo; Heasley, Lynn E; Tan, Aik Choon

2015-12-01

Targeted kinase inhibitors have dramatically improved cancer treatment, but kinase dependency for an individual patient or cancer cell can be challenging to predict. Kinase dependency does not always correspond with gene expression and mutation status. High-throughput drug screens are powerful tools for determining kinase dependency, but drug polypharmacology can make results difficult to interpret. We developed Kinase Addiction Ranker (KAR), an algorithm that integrates high-throughput drug screening data, comprehensive kinase inhibition data and gene expression profiles to identify kinase dependency in cancer cells. We applied KAR to predict kinase dependency of 21 lung cancer cell lines and 151 leukemia patient samples using published datasets. We experimentally validated KAR predictions of FGFR and MTOR dependence in lung cancer cell line H1581, showing synergistic reduction in proliferation after combining ponatinib and AZD8055. KAR can be downloaded as a Python function or a MATLAB script along with example inputs and outputs at: http://tanlab.ucdenver.edu/KAR/. aikchoon.tan@ucdenver.edu. 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.

A Pipeline for High-Throughput Concentration Response Modeling of Gene Expression for Toxicogenomics

PubMed Central

House, John S.; Grimm, Fabian A.; Jima, Dereje D.; Zhou, Yi-Hui; Rusyn, Ivan; Wright, Fred A.

2017-01-01

Cell-based assays are an attractive option to measure gene expression response to exposure, but the cost of whole-transcriptome RNA sequencing has been a barrier to the use of gene expression profiling for in vitro toxicity screening. In addition, standard RNA sequencing adds variability due to variable transcript length and amplification. Targeted probe-sequencing technologies such as TempO-Seq, with transcriptomic representation that can vary from hundreds of genes to the entire transcriptome, may reduce some components of variation. Analyses of high-throughput toxicogenomics data require renewed attention to read-calling algorithms and simplified dose–response modeling for datasets with relatively few samples. Using data from induced pluripotent stem cell-derived cardiomyocytes treated with chemicals at varying concentrations, we describe here and make available a pipeline for handling expression data generated by TempO-Seq to align reads, clean and normalize raw count data, identify differentially expressed genes, and calculate transcriptomic concentration–response points of departure. The methods are extensible to other forms of concentration–response gene-expression data, and we discuss the utility of the methods for assessing variation in susceptibility and the diseased cellular state. PMID:29163636

TCP Throughput Profiles Using Measurements over Dedicated Connections

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

Rao, Nageswara S.; Liu, Qiang; Sen, Satyabrata

Wide-area data transfers in high-performance computing infrastructures are increasingly being carried over dynamically provisioned dedicated network connections that provide high capacities with no competing traffic. We present extensive TCP throughput measurements and time traces over a suite of physical and emulated 10 Gbps connections with 0-366 ms round-trip times (RTTs). Contrary to the general expectation, they show significant statistical and temporal variations, in addition to the overall dependencies on the congestion control mechanism, buffer size, and the number of parallel streams. We analyze several throughput profiles that have highly desirable concave regions wherein the throughput decreases slowly with RTTs, inmore » stark contrast to the convex profiles predicted by various TCP analytical models. We present a generic throughput model that abstracts the ramp-up and sustainment phases of TCP flows, which provides insights into qualitative trends observed in measurements across TCP variants: (i) slow-start followed by well-sustained throughput leads to concave regions; (ii) large buffers and multiple parallel streams expand the concave regions in addition to improving the throughput; and (iii) stable throughput dynamics, indicated by a smoother Poincare map and smaller Lyapunov exponents, lead to wider concave regions. These measurements and analytical results together enable us to select a TCP variant and its parameters for a given connection to achieve high throughput with statistical guarantees.« less

Differentially expressed circulating microRNAs in the development of acute diabetic Charcot foot.

PubMed

Pasquier, Jennifer; Ramachandran, Vimal; Abu-Qaoud, Moh'd Rasheed; Thomas, Binitha; Benurwar, Manasi J; Chidiac, Omar; Hoarau-Véchot, Jessica; Robay, Amal; Fakhro, Khalid; Menzies, Robert A; Jayyousi, Amin; Zirie, Mahmoud; Al Suwaidi, Jassim; Malik, Rayaz A; Talal, Talal K; Najafi-Shoushtari, Seyed Hani; Rafii, Arash; Abi Khalil, Charbel

2018-06-05

Charcot foot (CF) is a rare complication of Type 2 diabetes (T2D). We assessed circulating miRNAs in 17 patients with T2D and acute CF (G1), 17 patients with T2D (G2) and equivalent neuropathy and 17 patients with T2D without neuropathy (G3) using the high-throughput miRNA expression profiling. 51 significantly deregulated miRNAs were identified in G1 versus G2, 37 in G1 versus G3 and 64 in G2 versus G3. Furthermore, we demonstrated that 16 miRNAs differentially expressed between G1 versus G2 could be involved in osteoclastic differentiation. Among them, eight are key factors involved in CF pathophysiology. Our data reveal that CF patients exhibit an altered expression profile of circulating miRNAs.

High throughput gene expression profiling: a molecular approach to integrative physiology

PubMed Central

Liang, Mingyu; Cowley, Allen W; Greene, Andrew S

2004-01-01

Integrative physiology emphasizes the importance of understanding multiple pathways with overlapping, complementary, or opposing effects and their interactions in the context of intact organisms. The DNA microarray technology, the most commonly used method for high-throughput gene expression profiling, has been touted as an integrative tool that provides insights into regulatory pathways. However, the physiology community has been slow in acceptance of these techniques because of early failure in generating useful data and the lack of a cohesive theoretical framework in which experiments can be analysed. With recent advances in both technology and analysis, we propose a concept of multidimensional integration of physiology that incorporates data generated by DNA microarray and other functional, genomic, and proteomic approaches to achieve a truly integrative understanding of physiology. Analysis of several studies performed in simpler organisms or in mammalian model animals supports the feasibility of such multidimensional integration and demonstrates the power of DNA microarray as an indispensable molecular tool for such integration. Evaluation of DNA microarray techniques indicates that these techniques, despite limitations, have advanced to a point where the question-driven profiling research has become a feasible complement to the conventional, hypothesis-driven research. With a keen sense of homeostasis, global regulation, and quantitative analysis, integrative physiologists are uniquely positioned to apply these techniques to enhance the understanding of complex physiological functions. PMID:14678487

eRNA: a graphic user interface-based tool optimized for large data analysis from high-throughput RNA sequencing

PubMed Central

2014-01-01

Background RNA sequencing (RNA-seq) is emerging as a critical approach in biological research. However, its high-throughput advantage is significantly limited by the capacity of bioinformatics tools. The research community urgently needs user-friendly tools to efficiently analyze the complicated data generated by high throughput sequencers. Results We developed a standalone tool with graphic user interface (GUI)-based analytic modules, known as eRNA. The capacity of performing parallel processing and sample management facilitates large data analyses by maximizing hardware usage and freeing users from tediously handling sequencing data. The module miRNA identification” includes GUIs for raw data reading, adapter removal, sequence alignment, and read counting. The module “mRNA identification” includes GUIs for reference sequences, genome mapping, transcript assembling, and differential expression. The module “Target screening” provides expression profiling analyses and graphic visualization. The module “Self-testing” offers the directory setups, sample management, and a check for third-party package dependency. Integration of other GUIs including Bowtie, miRDeep2, and miRspring extend the program’s functionality. Conclusions eRNA focuses on the common tools required for the mapping and quantification analysis of miRNA-seq and mRNA-seq data. The software package provides an additional choice for scientists who require a user-friendly computing environment and high-throughput capacity for large data analysis. eRNA is available for free download at https://sourceforge.net/projects/erna/?source=directory. PMID:24593312

eRNA: a graphic user interface-based tool optimized for large data analysis from high-throughput RNA sequencing.

PubMed

Yuan, Tiezheng; Huang, Xiaoyi; Dittmar, Rachel L; Du, Meijun; Kohli, Manish; Boardman, Lisa; Thibodeau, Stephen N; Wang, Liang

2014-03-05

RNA sequencing (RNA-seq) is emerging as a critical approach in biological research. However, its high-throughput advantage is significantly limited by the capacity of bioinformatics tools. The research community urgently needs user-friendly tools to efficiently analyze the complicated data generated by high throughput sequencers. We developed a standalone tool with graphic user interface (GUI)-based analytic modules, known as eRNA. The capacity of performing parallel processing and sample management facilitates large data analyses by maximizing hardware usage and freeing users from tediously handling sequencing data. The module miRNA identification" includes GUIs for raw data reading, adapter removal, sequence alignment, and read counting. The module "mRNA identification" includes GUIs for reference sequences, genome mapping, transcript assembling, and differential expression. The module "Target screening" provides expression profiling analyses and graphic visualization. The module "Self-testing" offers the directory setups, sample management, and a check for third-party package dependency. Integration of other GUIs including Bowtie, miRDeep2, and miRspring extend the program's functionality. eRNA focuses on the common tools required for the mapping and quantification analysis of miRNA-seq and mRNA-seq data. The software package provides an additional choice for scientists who require a user-friendly computing environment and high-throughput capacity for large data analysis. eRNA is available for free download at https://sourceforge.net/projects/erna/?source=directory.

A gene expression resource generated by genome-wide lacZ profiling in the mouse

PubMed Central

Tuck, Elizabeth; Estabel, Jeanne; Oellrich, Anika; Maguire, Anna Karin; Adissu, Hibret A.; Souter, Luke; Siragher, Emma; Lillistone, Charlotte; Green, Angela L.; Wardle-Jones, Hannah; Carragher, Damian M.; Karp, Natasha A.; Smedley, Damian; Adams, Niels C.; Bussell, James N.; Adams, David J.; Ramírez-Solis, Ramiro; Steel, Karen P.; Galli, Antonella; White, Jacqueline K.

2015-01-01

ABSTRACT Knowledge of the expression profile of a gene is a critical piece of information required to build an understanding of the normal and essential functions of that gene and any role it may play in the development or progression of disease. High-throughput, large-scale efforts are on-going internationally to characterise reporter-tagged knockout mouse lines. As part of that effort, we report an open access adult mouse expression resource, in which the expression profile of 424 genes has been assessed in up to 47 different organs, tissues and sub-structures using a lacZ reporter gene. Many specific and informative expression patterns were noted. Expression was most commonly observed in the testis and brain and was most restricted in white adipose tissue and mammary gland. Over half of the assessed genes presented with an absent or localised expression pattern (categorised as 0-10 positive structures). A link between complexity of expression profile and viability of homozygous null animals was observed; inactivation of genes expressed in ≥21 structures was more likely to result in reduced viability by postnatal day 14 compared with more restricted expression profiles. For validation purposes, this mouse expression resource was compared with Bgee, a federated composite of RNA-based expression data sets. Strong agreement was observed, indicating a high degree of specificity in our data. Furthermore, there were 1207 observations of expression of a particular gene in an anatomical structure where Bgee had no data, indicating a large amount of novelty in our data set. Examples of expression data corroborating and extending genotype-phenotype associations and supporting disease gene candidacy are presented to demonstrate the potential of this powerful resource. PMID:26398943

Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering☆

PubMed Central

Rabitz, Herschel; Welsh, William J.; Kohn, Joachim; de Boer, Jan

2016-01-01

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. PMID:26876875

High-Throughput Data of Circular RNA Profiles in Human Temporal Cortex Tissue Reveals Novel Insights into Temporal Lobe Epilepsy.

PubMed

Li, Jiaxin; Lin, Haijun; Sun, Zhenrong; Kong, Guanyi; Yan, Xu; Wang, Yujiao; Wang, Xiaoxuan; Wen, Yanhua; Liu, Xiang; Zheng, Hongkun; Jia, Mei; Shi, Zhongfang; Xu, Rong; Yang, Shaohua; Yuan, Fang

2018-01-01

Circular RNAs (circRNAs) are a class of long noncoding RNAs with a closed loop structure that regulate gene expression as microRNA sponges. CircRNAs are more enriched in brain tissue, but knowledge of the role of circRNAs in temporal lobe epilepsy (TLE) has remained limited. This study is the first to identify the global expression profiles and characteristics of circRNAs in human temporal cortex tissue from TLE patients. Temporal cortices were collected from 17 TLE patients and 17 non-TLE patients. Total RNA was isolated, and high-throughput sequencing was used to profile the transcriptome of dysregulated circRNAs. Quantitative PCR was performed for the validation of changed circRNAs. In total, 78983 circRNAs, including 15.29% known and 84.71% novel circRNAs, were detected in this study. Intriguingly, 442 circRNAs were differentially expressed between the TLE and non-TLE groups (fold change≥2.0 and FDR≤0.05). Of these circRNAs, 188 were up-regulated, and 254 were down-regulated in the TLE patient group. Eight circRNAs were validated by real-time PCR. Remarkably, circ-EFCAB2 was intensely up-regulated, while circ-DROSHA expression was significantly lower in the TLE group than in the non-TLE group (P<0.05). Bioinformatic analysis revealed that circ-EFCAB2 binds to miR-485-5p to increase the expression level of the ion channel CLCN6, while circ-DROSHA interacts with miR-1252-5p to decrease the expression level of ATP1A2. The dysregulations of circRNAs may reflect the pathogenesis of TLE and circ-EFCAB2 and circ-DROSHA might be potential therapeutic targets and biomarkers in TLE patients. © 2018 The Author(s). Published by S. Karger AG, Basel.

Emory University: High-Throughput Protein-Protein Interaction Analysis for Hippo Pathway Profiling | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory University used high-throughput protein-protein interaction (PPI) mapping for Hippo signaling pathway profiling to rapidly unveil promising PPIs as potential therapeutic targets and advance functional understanding of signaling circuitry in cells. Read the abstract.

High-Throughput Sequencing of microRNAs in Glucocorticoid Sensitive Paediatric Inflammatory Bowel Disease Patients.

PubMed

De Iudicibus, Sara; Lucafò, Marianna; Vitulo, Nicola; Martelossi, Stefano; Zimbello, Rosanna; De Pascale, Fabio; Forcato, Claudio; Naviglio, Samuele; Di Silvestre, Alessia; Gerdol, Marco; Stocco, Gabriele; Valle, Giorgio; Ventura, Alessandro; Bramuzzo, Matteo; Decorti, Giuliana

2018-05-08

The aim of this research was the identification of novel pharmacogenomic biomarkers for better understanding the complex gene regulation mechanisms underpinning glucocorticoid (GC) action in paediatric inflammatory bowel disease (IBD). This goal was achieved by evaluating high-throughput microRNA (miRNA) profiles during GC treatment, integrated with the assessment of expression changes in GC receptor (GR) heterocomplex genes. Furthermore, we tested the hypothesis that differentially expressed miRNAs could be directly regulated by GCs through investigating the presence of GC responsive elements (GREs) in their gene promoters. Ten IBD paediatric patients responding to GCs were enrolled. Peripheral blood was obtained at diagnosis (T0) and after four weeks of steroid treatment (T4). MicroRNA profiles were analyzed using next generation sequencing, and selected significantly differentially expressed miRNAs were validated by quantitative reverse transcription-polymerase chain reaction. In detail, 18 miRNAs were differentially expressed from T0 to T4, 16 of which were upregulated and 2 of which were downregulated. Out of these, three miRNAs (miR-144, miR-142, and miR-96) could putatively recognize the 3’UTR of the GR gene and three miRNAs (miR-363, miR-96, miR-142) contained GREs sequences, thereby potentially enabling direct regulation by the GR. In conclusion, we identified miRNAs differently expressed during GC treatment and miRNAs which could be directly regulated by GCs in blood cells of young IBD patients. These results could represent a first step towards their translation as pharmacogenomic biomarkers.

Discovery of agents that eradicate leukemia stem cells using an in silico screen of public gene expression data

PubMed Central

Hassane, Duane C.; Guzman, Monica L.; Corbett, Cheryl; Li, Xiaojie; Abboud, Ramzi; Young, Fay; Liesveld, Jane L.; Carroll, Martin

2008-01-01

Increasing evidence indicates that malignant stem cells are important for the pathogenesis of acute myelogenous leukemia (AML) and represent a reservoir of cells that drive the development of AML and relapse. Therefore, new treatment regimens are necessary to prevent relapse and improve therapeutic outcomes. Previous studies have shown that the sesquiterpene lactone, parthenolide (PTL), ablates bulk, progenitor, and stem AML cells while causing no appreciable toxicity to normal hematopoietic cells. Thus, PTL must evoke cellular responses capable of mediating AML selective cell death. Given recent advances in chemical genomics such as gene expression-based high-throughput screening (GE-HTS) and the Connectivity Map, we hypothesized that the gene expression signature resulting from treatment of primary AML with PTL could be used to search for similar signatures in publicly available gene expression profiles deposited into the Gene Expression Omnibus (GEO). We therefore devised a broad in silico screen of the GEO database using the PTL gene expression signature as a template and discovered 2 new agents, celastrol and 4-hydroxy-2-nonenal, that effectively eradicate AML at the bulk, progenitor, and stem cell level. These findings suggest the use of multicenter collections of high-throughput data to facilitate discovery of leukemia drugs and drug targets. PMID:18305216

Fidelity and enhanced sensitivity of differential transcription profiles following linear amplification of nanogram amounts of endothelial mRNA

NASA Technical Reports Server (NTRS)

Polacek, Denise C.; Passerini, Anthony G.; Shi, Congzhu; Francesco, Nadeene M.; Manduchi, Elisabetta; Grant, Gregory R.; Powell, Steven; Bischof, Helen; Winkler, Hans; Stoeckert, Christian J Jr;

Reverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression Data

PubMed Central

Liu, Zhi-Ping

2015-01-01

Transcriptional regulation plays vital roles in many fundamental biological processes. Reverse engineering of genome-wide regulatory networks from high-throughput transcriptomic data provides a promising way to characterize the global scenario of regulatory relationships between regulators and their targets. In this review, we summarize and categorize the main frameworks and methods currently available for inferring transcriptional regulatory networks from microarray gene expression profiling data. We overview each of strategies and introduce representative methods respectively. Their assumptions, advantages, shortcomings, and possible improvements and extensions are also clarified and commented. PMID:25937810

PLASMA PROTEIN PROFILING AS A HIGH THROUGHPUT TOOL FOR CHEMICAL SCREENING USING A SMALL FISH MODEL

EPA Science Inventory

Hudson, R. Tod, Michael J. Hemmer, Kimberly A. Salinas, Sherry S. Wilkinson, James Watts, James T. Winstead, Peggy S. Harris, Amy Kirkpatrick and Calvin C. Walker. In press. Plasma Protein Profiling as a High Throughput Tool for Chemical Screening Using a Small Fish Model (Abstra...

Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells.

PubMed

Klein, Allon M; Mazutis, Linas; Akartuna, Ilke; Tallapragada, Naren; Veres, Adrian; Li, Victor; Peshkin, Leonid; Weitz, David A; Kirschner, Marc W

2015-05-21

It has long been the dream of biologists to map gene expression at the single-cell level. With such data one might track heterogeneous cell sub-populations, and infer regulatory relationships between genes and pathways. Recently, RNA sequencing has achieved single-cell resolution. What is limiting is an effective way to routinely isolate and process large numbers of individual cells for quantitative in-depth sequencing. We have developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing. The method shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays. We analyzed mouse embryonic stem cells, revealing in detail the population structure and the heterogeneous onset of differentiation after leukemia inhibitory factor (LIF) withdrawal. The reproducibility of these high-throughput single-cell data allowed us to deconstruct cell populations and infer gene expression relationships. VIDEO ABSTRACT. Copyright © 2015 Elsevier Inc. All rights reserved.

Identification of candidate miRNAs and expression profile of yak oocytes before and after in vitro maturation by high-throughput sequencing.

PubMed

Xiong, X R; Lan, D L; Li, J; Zi, X D; Li, M Y

2016-12-01

Small RNA represents several unique non-coding RNA classes that have important function in a wide range of biological processes including development of germ cells and early embryonic, cell differentiation, cell proliferation and apoptosis in diverse organisms. However, little is known about their expression profiles and effects in yak oocytes maturation and early development. To investigate the function of small RNAs in the maturation process of yak oocyte and early development, two small RNA libraries of oocytes were constructed from germinal vesicle stage (GV) and maturation in vitro to metaphase II-arrested stage (M II) and then sequenced using small RNA high-throughput sequencing technology. A total of 9,742,592 and 12,168,523 clean reads were obtained from GV and M II oocytes, respectively. In total, 801 and 1,018 known miRNAs were acquired from GV and M II oocytes, and 75 miRNAs were found to be significantly differentially expressed: 47 miRNAs were upregulated and 28 miRNAs were downregulated in the M II oocytes compared to the GV stage. Among the upregulated miRNAs, miR-342 has the largest fold change (9.25-fold). Six highly expressed miRNAs (let-7i, miR-10b, miR-10c, miR-143, miR-146b and miR-148) were validated by real-time quantitative PCR (RT-qPCR) and consistent with the sequencing results. Furthermore, the expression patterns of two miRNAs and their potential targets were analysed in different developmental stages of oocytes and early embryos. This study provides the first miRNA profile in the mature process of yak oocyte. Seventy-five miRNAs are expressed differentially in GV and M II oocytes as well as among different development stages of early embryos, suggesting miRNAs involved in regulating oocyte maturation and early development of yak. These results showed specific miRNAs in yak oocytes had dynamic changes during meiosis. Further functional and mechanistic studies on the miRNAs during meiosis may beneficial to understanding the role of miRNAs on meiotic division. © 2016 Blackwell Verlag GmbH.

Gene expression profiling reveals underlying molecular mechanisms of the early stages of tamoxifen-induced rat hepatocarcinogenesis

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

Pogribny, Igor P.; Bagnyukova, Tetyana V.; Tryndyak, Volodymyr P.

2007-11-15

Tamoxifen is a widely used anti-estrogenic drug for chemotherapy and, more recently, for the chemoprevention of breast cancer. Despite the indisputable benefits of tamoxifen in preventing the occurrence and re-occurrence of breast cancer, the use of tamoxifen has been shown to induce non-alcoholic steatohepatitis, which is a life-threatening fatty liver disease with a risk of progression to cirrhosis and hepatocellular carcinoma. In recent years, the high-throughput microarray technology for large-scale analysis of gene expression has become a powerful tool for increasing the understanding of the molecular mechanisms of carcinogenesis and for identifying new biomarkers with diagnostic and predictive values. Inmore » the present study, we used the high-throughput microarray technology to determine the gene expression profiles in the liver during early stages of tamoxifen-induced rat hepatocarcinogenesis. Female Fisher 344 rats were fed a 420 ppm tamoxifen containing diet for 12 or 24 weeks, and gene expression profiles were determined in liver of control and tamoxifen-exposed rats. The results indicate that early stages of tamoxifen-induced liver carcinogenesis are characterized by alterations in several major cellular pathways, specifically those involved in the tamoxifen metabolism, lipid metabolism, cell cycle signaling, and apoptosis/cell proliferation control. One of the most prominent changes during early stages of tamoxifen-induced hepatocarcinogenesis is dysregulation of signaling pathways in cell cycle progression from the G{sub 1} to S phase, evidenced by the progressive and sustained increase in expression of the Pdgfc, Calb3, Ets1, and Ccnd1 genes accompanied by the elevated level of the PI3K, p-PI3K, Akt1/2, Akt3, and cyclin B, D1, and D3 proteins. The early appearance of these alterations suggests their importance in the mechanism of neoplastic cell transformation induced by tamoxifen.« less

GETPrime: a gene- or transcript-specific primer database for quantitative real-time PCR.

PubMed

Gubelmann, Carine; Gattiker, Alexandre; Massouras, Andreas; Hens, Korneel; David, Fabrice; Decouttere, Frederik; Rougemont, Jacques; Deplancke, Bart

2011-01-01

The vast majority of genes in humans and other organisms undergo alternative splicing, yet the biological function of splice variants is still very poorly understood in large part because of the lack of simple tools that can map the expression profiles and patterns of these variants with high sensitivity. High-throughput quantitative real-time polymerase chain reaction (qPCR) is an ideal technique to accurately quantify nucleic acid sequences including splice variants. However, currently available primer design programs do not distinguish between splice variants and also differ substantially in overall quality, functionality or throughput mode. Here, we present GETPrime, a primer database supported by a novel platform that uniquely combines and automates several features critical for optimal qPCR primer design. These include the consideration of all gene splice variants to enable either gene-specific (covering the majority of splice variants) or transcript-specific (covering one splice variant) expression profiling, primer specificity validation, automated best primer pair selection according to strict criteria and graphical visualization of the latter primer pairs within their genomic context. GETPrime primers have been extensively validated experimentally, demonstrating high transcript specificity in complex samples. Thus, the free-access, user-friendly GETPrime database allows fast primer retrieval and visualization for genes or groups of genes of most common model organisms, and is available at http://updepla1srv1.epfl.ch/getprime/. Database URL: http://deplanckelab.epfl.ch.

GETPrime: a gene- or transcript-specific primer database for quantitative real-time PCR

PubMed Central

Gubelmann, Carine; Gattiker, Alexandre; Massouras, Andreas; Hens, Korneel; David, Fabrice; Decouttere, Frederik; Rougemont, Jacques; Deplancke, Bart

2011-01-01

The vast majority of genes in humans and other organisms undergo alternative splicing, yet the biological function of splice variants is still very poorly understood in large part because of the lack of simple tools that can map the expression profiles and patterns of these variants with high sensitivity. High-throughput quantitative real-time polymerase chain reaction (qPCR) is an ideal technique to accurately quantify nucleic acid sequences including splice variants. However, currently available primer design programs do not distinguish between splice variants and also differ substantially in overall quality, functionality or throughput mode. Here, we present GETPrime, a primer database supported by a novel platform that uniquely combines and automates several features critical for optimal qPCR primer design. These include the consideration of all gene splice variants to enable either gene-specific (covering the majority of splice variants) or transcript-specific (covering one splice variant) expression profiling, primer specificity validation, automated best primer pair selection according to strict criteria and graphical visualization of the latter primer pairs within their genomic context. GETPrime primers have been extensively validated experimentally, demonstrating high transcript specificity in complex samples. Thus, the free-access, user-friendly GETPrime database allows fast primer retrieval and visualization for genes or groups of genes of most common model organisms, and is available at http://updepla1srv1.epfl.ch/getprime/. Database URL: http://deplanckelab.epfl.ch. PMID:21917859

The Prediction of Drug-Disease Correlation Based on Gene Expression Data.

PubMed

Cui, Hui; Zhang, Menghuan; Yang, Qingmin; Li, Xiangyi; Liebman, Michael; Yu, Ying; Xie, Lu

2018-01-01

The explosive growth of high-throughput experimental methods and resulting data yields both opportunity and challenge for selecting the correct drug to treat both a specific patient and their individual disease. Ideally, it would be useful and efficient if computational approaches could be applied to help achieve optimal drug-patient-disease matching but current efforts have met with limited success. Current approaches have primarily utilized the measureable effect of a specific drug on target tissue or cell lines to identify the potential biological effect of such treatment. While these efforts have met with some level of success, there exists much opportunity for improvement. This specifically follows the observation that, for many diseases in light of actual patient response, there is increasing need for treatment with combinations of drugs rather than single drug therapies. Only a few previous studies have yielded computational approaches for predicting the synergy of drug combinations by analyzing high-throughput molecular datasets. However, these computational approaches focused on the characteristics of the drug itself, without fully accounting for disease factors. Here, we propose an algorithm to specifically predict synergistic effects of drug combinations on various diseases, by integrating the data characteristics of disease-related gene expression profiles with drug-treated gene expression profiles. We have demonstrated utility through its application to transcriptome data, including microarray and RNASeq data, and the drug-disease prediction results were validated using existing publications and drug databases. It is also applicable to other quantitative profiling data such as proteomics data. We also provide an interactive web interface to allow our Prediction of Drug-Disease method to be readily applied to user data. While our studies represent a preliminary exploration of this critical problem, we believe that the algorithm can provide the basis for further refinement towards addressing a large clinical need.

Picking Cell Lines for High-Throughput Transcriptomic Toxicity ...

EPA Pesticide Factsheets

High throughput, whole genome transcriptomic profiling is a promising approach to comprehensively evaluate chemicals for potential biological effects. To be useful for in vitro toxicity screening, gene expression must be quantified in a set of representative cell types that captures the diversity of potential responses across chemicals. The ideal dataset to select these cell types would consist of hundreds of cell types treated with thousands of chemicals, but does not yet exist. However, basal gene expression data may be useful as a surrogate for representing the relevant biological space necessary for cell type selection. The goal of this study was to identify a small (< 20) number of cell types that capture a large, quantifiable fraction of basal gene expression diversity. Three publicly available collections of Affymetrix U133+2.0 cellular gene expression data were used: 1) 59 cell lines from the NCI60 set; 2) 303 primary cell types from the Mabbott et al (2013) expression atlas; and 3) 1036 cell lines from the Cancer Cell Line Encyclopedia. The data were RMA normalized, log-transformed, and the probe sets mapped to HUGO gene identifiers. The results showed that <20 cell lines capture only a small fraction of the total diversity in basal gene expression when evaluated using either the entire set of 20960 HUGO genes or a subset of druggable genes likely to be chemical targets. The fraction of the total gene expression variation explained was consistent when

High-Throughput Sequencing Reveals Differential Expression of miRNAs in Intestine from Sea Cucumber during Aestivation

PubMed Central

Chen, Muyan; Zhang, Xiumei; Liu, Jianning; Storey, Kenneth B.

2013-01-01

The regulatory role of miRNA in gene expression is an emerging hot new topic in the control of hypometabolism. Sea cucumber aestivation is a complicated physiological process that includes obvious hypometabolism as evidenced by a decrease in the rates of oxygen consumption and ammonia nitrogen excretion, as well as a serious degeneration of the intestine into a very tiny filament. To determine whether miRNAs play regulatory roles in this process, the present study analyzed profiles of miRNA expression in the intestine of the sea cucumber (Apostichopus japonicus), using Solexa deep sequencing technology. We identified 308 sea cucumber miRNAs, including 18 novel miRNAs specific to sea cucumber. Animals sampled during deep aestivation (DA) after at least 15 days of continuous torpor, were compared with animals from a non-aestivation (NA) state (animals that had passed through aestivation and returned to the active state). We identified 42 differentially expressed miRNAs [RPM (reads per million) >10, |FC| (|fold change|) ≥1, FDR (false discovery rate) <0.01] during aestivation, which were validated by two other miRNA profiling methods: miRNA microarray and real-time PCR. Among the most prominent miRNA species, miR-200-3p, miR-2004, miR-2010, miR-22, miR-252a, miR-252a-3p and miR-92 were significantly over-expressed during deep aestivation compared with non-aestivation animals. Preliminary analyses of their putative target genes and GO analysis suggest that these miRNAs could play important roles in global transcriptional depression and cell differentiation during aestivation. High-throughput sequencing data and microarray data have been submitted to GEO database. PMID:24143179

Gene expression profile change and growth inhibition in Drosophila larvae treated with azadirachtin.

PubMed

Lai, Duo; Jin, Xiaoyong; Wang, Hao; Yuan, Mei; Xu, Hanhong

2014-09-20

Azadirachtin is a botanical insecticide that affects various biological processes. The effects of azadirachtin on the digital gene expression profile and growth inhibition in Drosophila larvae have not been investigated. In this study, we applied high-throughput sequencing technology to detect the differentially expressed genes of Drosophila larvae regulated by azadirachtin. A total of 15,322 genes were detected, and 28 genes were found to be significantly regulated by azadirachtin. Biological process and pathway analysis showed that azadirachtin affected starch and sucrose metabolism, defense response, signal transduction, instar larval or pupal development, and chemosensory behavior processes. The genes regulated by azadirachtin were mainly enriched in starch and sucrose metabolism. This study provided a general digital gene expression profile of dysregulated genes in response to azadirachtin and showed that azadirachtin provoked potent growth inhibitory effects in Drosophila larvae by regulating the genes of cuticular protein, amylase, and odorant-binding protein. Finally, we propose a potential mechanism underlying the dysregulation of the insulin/insulin-like growth factor signaling pathway by azadirachtin. Copyright © 2014 Elsevier B.V. All rights reserved.

High-throughput sequencing of small RNAs and analysis of differentially expressed microRNAs associated with pistil development in Japanese apricot

PubMed Central

2012-01-01

Background MicroRNAs (miRNAs) are a class of endogenous, small, non-coding RNAs that regulate gene expression by mediating gene silencing at transcriptional and post-transcriptional levels in high plants. However, the diversity of miRNAs and their roles in floral development in Japanese apricot (Prunus mume Sieb. et Zucc) remains largely unexplored. Imperfect flowers with pistil abortion seriously decrease production yields. To understand the role of miRNAs in pistil development, pistil development-related miRNAs were identified by Solexa sequencing in Japanese apricot. Results Solexa sequencing was used to identify and quantitatively profile small RNAs from perfect and imperfect flower buds of Japanese apricot. A total of 22,561,972 and 24,952,690 reads were sequenced from two small RNA libraries constructed from perfect and imperfect flower buds, respectively. Sixty-one known miRNAs, belonging to 24 families, were identified. Comparative profiling revealed that seven known miRNAs exhibited significant differential expression between perfect and imperfect flower buds. A total of 61 potentially novel miRNAs/new members of known miRNA families were also identified by the presence of mature miRNAs and corresponding miRNA*s in the sRNA libraries. Comparative analysis showed that six potentially novel miRNAs were differentially expressed between perfect and imperfect flower buds. Target predictions of the 13 differentially expressed miRNAs resulted in 212 target genes. Gene ontology (GO) annotation revealed that high-ranking miRNA target genes are those implicated in the developmental process, the regulation of transcription and response to stress. Conclusions This study represents the first comparative identification of miRNAomes between perfect and imperfect Japanese apricot flowers. Seven known miRNAs and six potentially novel miRNAs associated with pistil development were identified, using high-throughput sequencing of small RNAs. The findings, both computationally and experimentally, provide valuable information for further functional characterisation of miRNAs associated with pistil development in plants. PMID:22863067

Carbohydrate Microarray Technology Applied to High-Throughput Mapping of Plant Cell Wall Glycans Using Comprehensive Microarray Polymer Profiling (CoMPP).

PubMed

Kračun, Stjepan Krešimir; Fangel, Jonatan Ulrik; Rydahl, Maja Gro; Pedersen, Henriette Lodberg; Vidal-Melgosa, Silvia; Willats, William George Tycho

2017-01-01

Cell walls are an important feature of plant cells and a major component of the plant glycome. They have both structural and physiological functions and are critical for plant growth and development. The diversity and complexity of these structures demand advanced high-throughput techniques to answer questions about their structure, functions and roles in both fundamental and applied scientific fields. Microarray technology provides both the high-throughput and the feasibility aspects required to meet that demand. In this chapter, some of the most recent microarray-based techniques relating to plant cell walls are described together with an overview of related contemporary techniques applied to carbohydrate microarrays and their general potential in glycoscience. A detailed experimental procedure for high-throughput mapping of plant cell wall glycans using the comprehensive microarray polymer profiling (CoMPP) technique is included in the chapter and provides a good example of both the robust and high-throughput nature of microarrays as well as their applicability to plant glycomics.

Independent and high-level dual-gene expression in adult stem-progenitor cells from a single lentiviral vector.

PubMed

Tian, J; Andreadis, S T

2009-07-01

Expression of multiple genes from the same target cell is required in several technological and therapeutic applications such as quantitative measurements of promoter activity or in vivo tracking of stem cells. In spite of such need, reaching independent and high-level dual-gene expression cannot be reliably accomplished by current gene transfer vehicles. To address this issue, we designed a lentiviral vector carrying two transcriptional units separated by polyadenylation, terminator and insulator sequences. With this design, the expression level of both genes was as high as that yielded from lentiviral vectors containing only a single transcriptional unit. Similar results were observed with several promoters and cell types including epidermal keratinocytes, bone marrow mesenchymal stem cells and hair follicle stem cells. Notably, we demonstrated quantitative dynamic monitoring of gene expression in primary cells with no need for selection protocols suggesting that this optimized lentivirus may be useful in high-throughput gene expression profiling studies.

Gene expression profiling via LongSAGE in a non-model plant species: a case study in seeds of Brassica napus

PubMed Central

Obermeier, Christian; Hosseini, Bashir; Friedt, Wolfgang; Snowdon, Rod

2009-01-01

Background Serial analysis of gene expression (LongSAGE) was applied for gene expression profiling in seeds of oilseed rape (Brassica napus ssp. napus). The usefulness of this technique for detailed expression profiling in a non-model organism was demonstrated for the highly complex, neither fully sequenced nor annotated genome of B. napus by applying a tag-to-gene matching strategy based on Brassica ESTs and the annotated proteome of the closely related model crucifer A. thaliana. Results Transcripts from 3,094 genes were detected at two time-points of seed development, 23 days and 35 days after pollination (DAP). Differential expression showed a shift from gene expression involved in diverse developmental processes including cell proliferation and seed coat formation at 23 DAP to more focussed metabolic processes including storage protein accumulation and lipid deposition at 35 DAP. The most abundant transcripts at 23 DAP were coding for diverse protease inhibitor proteins and proteases, including cysteine proteases involved in seed coat formation and a number of lipid transfer proteins involved in embryo pattern formation. At 35 DAP, transcripts encoding napin, cruciferin and oleosin storage proteins were most abundant. Over both time-points, 18.6% of the detected genes were matched by Brassica ESTs identified by LongSAGE tags in antisense orientation. This suggests a strong involvement of antisense transcript expression in regulatory processes during B. napus seed development. Conclusion This study underlines the potential of transcript tagging approaches for gene expression profiling in Brassica crop species via EST matching to annotated A. thaliana genes. Limits of tag detection for low-abundance transcripts can today be overcome by ultra-high throughput sequencing approaches, so that tag-based gene expression profiling may soon become the method of choice for global expression profiling in non-model species. PMID:19575793

Cardiogenic Genes Expressed in Cardiac Fibroblasts Contribute to Heart Development and Repair

PubMed Central

Furtado, Milena B.; Costa, Mauro W.; Pranoto, Edward Adi; Salimova, Ekaterina; Pinto, Alex; Lam, Nicholas T.; Park, Anthony; Snider, Paige; Chandran, Anjana; Harvey, Richard P.; Boyd, Richard; Conway, Simon J.; Pearson, James; Kaye, David M.; Rosenthal, Nadia A.

2014-01-01

Rationale Cardiac fibroblasts are critical to proper heart function through multiple interactions with the myocardial compartment but appreciation of their contribution has suffered from incomplete characterization and lack of cell-specific markers. Objective To generate an unbiased comparative gene expression profile of the cardiac fibroblast pool, identify and characterize the role of key genes in cardiac fibroblast function, and determine their contribution to myocardial development and regeneration. Methods and Results High-throughput cell surface and intracellular profiling of cardiac and tail fibroblasts identified canonical MSC and a surprising number of cardiogenic genes, some expressed at higher levels than in whole heart. Whilst genetically marked fibroblasts contributed heterogeneously to interstitial but not cardiomyocyte compartments in infarcted hearts, fibroblast-restricted depletion of one highly expressed cardiogenic marker, Tbx20, caused marked myocardial dysmorphology and perturbations in scar formation upon myocardial infarction. Conclusions The surprising transcriptional identity of cardiac fibroblasts, the adoption of cardiogenic gene programs and direct contribution to cardiac development and repair provokes alternative interpretations for studies on more specialized cardiac progenitors, offering a novel perspective for reinterpreting cardiac regenerative therapies. PMID:24650916

NCBI GEO: archive for functional genomics data sets--10 years on.

PubMed

Barrett, Tanya; Troup, Dennis B; Wilhite, Stephen E; Ledoux, Pierre; Evangelista, Carlos; Kim, Irene F; Tomashevsky, Maxim; Marshall, Kimberly A; Phillippy, Katherine H; Sherman, Patti M; Muertter, Rolf N; Holko, Michelle; Ayanbule, Oluwabukunmi; Yefanov, Andrey; Soboleva, Alexandra

2011-01-01

A decade ago, the Gene Expression Omnibus (GEO) database was established at the National Center for Biotechnology Information (NCBI). The original objective of GEO was to serve as a public repository for high-throughput gene expression data generated mostly by microarray technology. However, the research community quickly applied microarrays to non-gene-expression studies, including examination of genome copy number variation and genome-wide profiling of DNA-binding proteins. Because the GEO database was designed with a flexible structure, it was possible to quickly adapt the repository to store these data types. More recently, as the microarray community switches to next-generation sequencing technologies, GEO has again adapted to host these data sets. Today, GEO stores over 20,000 microarray- and sequence-based functional genomics studies, and continues to handle the majority of direct high-throughput data submissions from the research community. Multiple mechanisms are provided to help users effectively search, browse, download and visualize the data at the level of individual genes or entire studies. This paper describes recent database enhancements, including new search and data representation tools, as well as a brief review of how the community uses GEO data. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.

Molecular classification of fatty liver by high-throughput profiling of protein post-translational modifications.

PubMed

Urasaki, Yasuyo; Fiscus, Ronald R; Le, Thuc T

2016-04-01

We describe an alternative approach to classifying fatty liver by profiling protein post-translational modifications (PTMs) with high-throughput capillary isoelectric focusing (cIEF) immunoassays. Four strains of mice were studied, with fatty livers induced by different causes, such as ageing, genetic mutation, acute drug usage, and high-fat diet. Nutrient-sensitive PTMs of a panel of 12 liver metabolic and signalling proteins were simultaneously evaluated with cIEF immunoassays, using nanograms of total cellular protein per assay. Changes to liver protein acetylation, phosphorylation, and O-N-acetylglucosamine glycosylation were quantified and compared between normal and diseased states. Fatty liver tissues could be distinguished from one another by distinctive protein PTM profiles. Fatty liver is currently classified by morphological assessment of lipid droplets, without identifying the underlying molecular causes. In contrast, high-throughput profiling of protein PTMs has the potential to provide molecular classification of fatty liver. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Gene set differential analysis of time course expression profiles via sparse estimation in functional logistic model with application to time-dependent biomarker detection.

PubMed

Kayano, Mitsunori; Matsui, Hidetoshi; Yamaguchi, Rui; Imoto, Seiya; Miyano, Satoru

2016-04-01

High-throughput time course expression profiles have been available in the last decade due to developments in measurement techniques and devices. Functional data analysis, which treats smoothed curves instead of originally observed discrete data, is effective for the time course expression profiles in terms of dimension reduction, robustness, and applicability to data measured at small and irregularly spaced time points. However, the statistical method of differential analysis for time course expression profiles has not been well established. We propose a functional logistic model based on elastic net regularization (F-Logistic) in order to identify the genes with dynamic alterations in case/control study. We employ a mixed model as a smoothing method to obtain functional data; then F-Logistic is applied to time course profiles measured at small and irregularly spaced time points. We evaluate the performance of F-Logistic in comparison with another functional data approach, i.e. functional ANOVA test (F-ANOVA), by applying the methods to real and synthetic time course data sets. The real data sets consist of the time course gene expression profiles for long-term effects of recombinant interferon β on disease progression in multiple sclerosis. F-Logistic distinguishes dynamic alterations, which cannot be found by competitive approaches such as F-ANOVA, in case/control study based on time course expression profiles. F-Logistic is effective for time-dependent biomarker detection, diagnosis, and therapy. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Analysis of Protein Expression in Cell Microarrays: A Tool for Antibody-based Proteomics

PubMed Central

Andersson, Ann-Catrin; Strömberg, Sara; Bäckvall, Helena; Kampf, Caroline; Uhlen, Mathias; Wester, Kenneth; Pontén, Fredrik

2006-01-01

Tissue microarray (TMA) technology provides a possibility to explore protein expression patterns in a multitude of normal and disease tissues in a high-throughput setting. Although TMAs have been used for analysis of tissue samples, robust methods for studying in vitro cultured cell lines and cell aspirates in a TMA format have been lacking. We have adopted a technique to homogeneously distribute cells in an agarose gel matrix, creating an artificial tissue. This enables simultaneous profiling of protein expression in suspension- and adherent-grown cell samples assembled in a microarray. In addition, the present study provides an optimized strategy for the basic laboratory steps to efficiently produce TMAs. Presented modifications resulted in an improved quality of specimens and a higher section yield compared with standard TMA production protocols. Sections from the generated cell TMAs were tested for immunohistochemical staining properties using 20 well-characterized antibodies. Comparison of immunoreactivity in cultured dispersed cells and corresponding cells in tissue samples showed congruent results for all tested antibodies. We conclude that a modified TMA technique, including cell samples, provides a valuable tool for high-throughput analysis of protein expression, and that this technique can be used for global approaches to explore the human proteome. PMID:16957166

Gene Expression Profile Change and Associated Physiological and Pathological Effects in Mouse Liver Induced by Fasting and Refeeding

PubMed Central

Zhang, Fang; Xu, Xiang; Zhou, Ben; He, Zhishui; Zhai, Qiwei

2011-01-01

Food availability regulates basal metabolism and progression of many diseases, and liver plays an important role in these processes. The effects of food availability on digital gene expression profile, physiological and pathological functions in liver are yet to be further elucidated. In this study, we applied high-throughput sequencing technology to detect digital gene expression profile of mouse liver in fed, fasted and refed states. Totally 12162 genes were detected, and 2305 genes were significantly regulated by food availability. Biological process and pathway analysis showed that fasting mainly affected lipid and carboxylic acid metabolic processes in liver. Moreover, the genes regulated by fasting and refeeding in liver were mainly enriched in lipid metabolic process or fatty acid metabolism. Network analysis demonstrated that fasting mainly regulated Drug Metabolism, Small Molecule Biochemistry and Endocrine System Development and Function, and the networks including Lipid Metabolism, Small Molecule Biochemistry and Gene Expression were affected by refeeding. In addition, FunDo analysis showed that liver cancer and diabetes mellitus were most likely to be affected by food availability. This study provides the digital gene expression profile of mouse liver regulated by food availability, and demonstrates the main biological processes, pathways, gene networks and potential hepatic diseases regulated by fasting and refeeding. These results show that food availability mainly regulates hepatic lipid metabolism and is highly correlated with liver-related diseases including liver cancer and diabetes. PMID:22096593

Gene expression profile change and associated physiological and pathological effects in mouse liver induced by fasting and refeeding.

PubMed

Zhang, Fang; Xu, Xiang; Zhou, Ben; He, Zhishui; Zhai, Qiwei

2011-01-01

Food availability regulates basal metabolism and progression of many diseases, and liver plays an important role in these processes. The effects of food availability on digital gene expression profile, physiological and pathological functions in liver are yet to be further elucidated. In this study, we applied high-throughput sequencing technology to detect digital gene expression profile of mouse liver in fed, fasted and refed states. Totally 12162 genes were detected, and 2305 genes were significantly regulated by food availability. Biological process and pathway analysis showed that fasting mainly affected lipid and carboxylic acid metabolic processes in liver. Moreover, the genes regulated by fasting and refeeding in liver were mainly enriched in lipid metabolic process or fatty acid metabolism. Network analysis demonstrated that fasting mainly regulated Drug Metabolism, Small Molecule Biochemistry and Endocrine System Development and Function, and the networks including Lipid Metabolism, Small Molecule Biochemistry and Gene Expression were affected by refeeding. In addition, FunDo analysis showed that liver cancer and diabetes mellitus were most likely to be affected by food availability. This study provides the digital gene expression profile of mouse liver regulated by food availability, and demonstrates the main biological processes, pathways, gene networks and potential hepatic diseases regulated by fasting and refeeding. These results show that food availability mainly regulates hepatic lipid metabolism and is highly correlated with liver-related diseases including liver cancer and diabetes.

Inertial-ordering-assisted droplet microfluidics for high-throughput single-cell RNA-sequencing.

PubMed

Moon, Hui-Sung; Je, Kwanghwi; Min, Jae-Woong; Park, Donghyun; Han, Kyung-Yeon; Shin, Seung-Ho; Park, Woong-Yang; Yoo, Chang Eun; Kim, Shin-Hyun

2018-02-27

Single-cell RNA-seq reveals the cellular heterogeneity inherent in the population of cells, which is very important in many clinical and research applications. Recent advances in droplet microfluidics have achieved the automatic isolation, lysis, and labeling of single cells in droplet compartments without complex instrumentation. However, barcoding errors occurring in the cell encapsulation process because of the multiple-beads-in-droplet and insufficient throughput because of the low concentration of beads for avoiding multiple-beads-in-a-droplet remain important challenges for precise and efficient expression profiling of single cells. In this study, we developed a new droplet-based microfluidic platform that significantly improved the throughput while reducing barcoding errors through deterministic encapsulation of inertially ordered beads. Highly concentrated beads containing oligonucleotide barcodes were spontaneously ordered in a spiral channel by an inertial effect, which were in turn encapsulated in droplets one-by-one, while cells were simultaneously encapsulated in the droplets. The deterministic encapsulation of beads resulted in a high fraction of single-bead-in-a-droplet and rare multiple-beads-in-a-droplet although the bead concentration increased to 1000 μl -1 , which diminished barcoding errors and enabled accurate high-throughput barcoding. We successfully validated our device with single-cell RNA-seq. In addition, we found that multiple-beads-in-a-droplet, generated using a normal Drop-Seq device with a high concentration of beads, underestimated transcript numbers and overestimated cell numbers. This accurate high-throughput platform can expand the capability and practicality of Drop-Seq in single-cell analysis.

Combination of automated high throughput platforms, flow cytometry, and hierarchical clustering to detect cell state.

PubMed

Kitsos, Christine M; Bhamidipati, Phani; Melnikova, Irena; Cash, Ethan P; McNulty, Chris; Furman, Julia; Cima, Michael J; Levinson, Douglas

2007-01-01

This study examined whether hierarchical clustering could be used to detect cell states induced by treatment combinations that were generated through automation and high-throughput (HT) technology. Data-mining techniques were used to analyze the large experimental data sets to determine whether nonlinear, non-obvious responses could be extracted from the data. Unary, binary, and ternary combinations of pharmacological factors (examples of stimuli) were used to induce differentiation of HL-60 cells using a HT automated approach. Cell profiles were analyzed by incorporating hierarchical clustering methods on data collected by flow cytometry. Data-mining techniques were used to explore the combinatorial space for nonlinear, unexpected events. Additional small-scale, follow-up experiments were performed on cellular profiles of interest. Multiple, distinct cellular profiles were detected using hierarchical clustering of expressed cell-surface antigens. Data-mining of this large, complex data set retrieved cases of both factor dominance and cooperativity, as well as atypical cellular profiles. Follow-up experiments found that treatment combinations producing "atypical cell types" made those cells more susceptible to apoptosis. CONCLUSIONS Hierarchical clustering and other data-mining techniques were applied to analyze large data sets from HT flow cytometry. From each sample, the data set was filtered and used to define discrete, usable states that were then related back to their original formulations. Analysis of resultant cell populations induced by a multitude of treatments identified unexpected phenotypes and nonlinear response profiles.

New Era of Studying RNA Secondary Structure and Its Influence on Gene Regulation in Plants.

PubMed

Yang, Xiaofei; Yang, Minglei; Deng, Hongjing; Ding, Yiliang

2018-01-01

The dynamic structure of RNA plays a central role in post-transcriptional regulation of gene expression such as RNA maturation, degradation, and translation. With the rise of next-generation sequencing, the study of RNA structure has been transformed from in vitro low-throughput RNA structure probing methods to in vivo high-throughput RNA structure profiling. The development of these methods enables incremental studies on the function of RNA structure to be performed, revealing new insights of novel regulatory mechanisms of RNA structure in plants. Genome-wide scale RNA structure profiling allows us to investigate general RNA structural features over 10s of 1000s of mRNAs and to compare RNA structuromes between plant species. Here, we provide a comprehensive and up-to-date overview of: (i) RNA structure probing methods; (ii) the biological functions of RNA structure; (iii) genome-wide RNA structural features corresponding to their regulatory mechanisms; and (iv) RNA structurome evolution in plants.

MicroRNA expression profiling in alveolar macrophages of indigenous Chinese Tongcheng pigs infected with PRRSV in vivo.

PubMed

Zhou, Xiang; Michal, Jennifer J; Jiang, Zhihua; Liu, Bang

2017-11-01

Porcine respiratory and reproductive syndrome (PRRS), caused by PRRS virus (PRRSV), is one of the most serious infectious diseases in the swine industry worldwide. Indigenous Chinese Tongcheng (TC) pigs reportedly show strong resistance to PRRSV infection. The miRNA expression profiles of porcine alveolar macrophages (PAMs) of control TC pigs and those infected with PRRSV in vivo were analyzed by high-throughput sequencing to explore changes induced by infection. A total of 182 known miRNAs including 101 miRNA-5p and 81 miRNA-3p were identified with 23 up-regulated differentially expressed miRNAs (DEmiRNAs) and 25 down-regulated DEmiRNAs. Gene Ontology analysis showed that predicted target genes for the DEmiRNAs were enriched in immune response, transcription regulation, and cell death. The integrative analysis of mRNA and miRNA expression revealed that down-regulated methylation-related genes (DNMT1 and DNMT3b) were targeted by five up-regulated DEmiRNAs. Furthermore, 35 pairs of miRNAs (70 miRNAs) were co-expressed after PRRSV infection and six pairs were co-expressed differently. Our results describe miRNA expression profiles of TC pigs in response to PRRSV infection and lay a strong foundation for developing novel therapies to control PRRS in pigs.

Identifying potential maternal genes of Bombyx mori using digital gene expression profiling

PubMed Central

Xu, Pingzhen

2018-01-01

Maternal genes present in mature oocytes play a crucial role in the early development of silkworm. Although maternal genes have been widely studied in many other species, there has been limited research in Bombyx mori. High-throughput next generation sequencing provides a practical method for gene discovery on a genome-wide level. Herein, a transcriptome study was used to identify maternal-related genes from silkworm eggs. Unfertilized eggs from five different stages of early development were used to detect the changing situation of gene expression. The expressed genes showed different patterns over time. Seventy-six maternal genes were annotated according to homology analysis with Drosophila melanogaster. More than half of the differentially expressed maternal genes fell into four expression patterns, while the expression patterns showed a downward trend over time. The functional annotation of these material genes was mainly related to transcription factor activity, growth factor activity, nucleic acid binding, RNA binding, ATP binding, and ion binding. Additionally, twenty-two gene clusters including maternal genes were identified from 18 scaffolds. Altogether, we plotted a profile for the maternal genes of Bombyx mori using a digital gene expression profiling method. This will provide the basis for maternal-specific signature research and improve the understanding of the early development of silkworm. PMID:29462160

Molecular profiling of multiple myeloma: from gene expression analysis to next-generation sequencing.

PubMed

Agnelli, Luca; Tassone, Pierfrancesco; Neri, Antonino

2013-06-01

Multiple myeloma is a fatal malignant proliferation of clonal bone marrow Ig-secreting plasma cells, characterized by wide clinical, biological, and molecular heterogeneity. Herein, global gene and microRNA expression, genome-wide DNA profilings, and next-generation sequencing technology used to investigate the genomic alterations underlying the bio-clinical heterogeneity in multiple myeloma are discussed. High-throughput technologies have undoubtedly allowed a better comprehension of the molecular basis of the disease, a fine stratification, and early identification of high-risk patients, and have provided insights toward targeted therapy studies. However, such technologies are at risk of being affected by laboratory- or cohort-specific biases, and are moreover influenced by high number of expected false positives. This aspect has a major weight in myeloma, which is characterized by large molecular heterogeneity. Therefore, meta-analysis as well as multiple approaches are desirable if not mandatory to validate the results obtained, in line with commonly accepted recommendation for tumor diagnostic/prognostic biomarker studies.

CellAtlasSearch: a scalable search engine for single cells.

PubMed

Srivastava, Divyanshu; Iyer, Arvind; Kumar, Vibhor; Sengupta, Debarka

2018-05-21

Owing to the advent of high throughput single cell transcriptomics, past few years have seen exponential growth in production of gene expression data. Recently efforts have been made by various research groups to homogenize and store single cell expression from a large number of studies. The true value of this ever increasing data deluge can be unlocked by making it searchable. To this end, we propose CellAtlasSearch, a novel search architecture for high dimensional expression data, which is massively parallel as well as light-weight, thus infinitely scalable. In CellAtlasSearch, we use a Graphical Processing Unit (GPU) friendly version of Locality Sensitive Hashing (LSH) for unmatched speedup in data processing and query. Currently, CellAtlasSearch features over 300 000 reference expression profiles including both bulk and single-cell data. It enables the user query individual single cell transcriptomes and finds matching samples from the database along with necessary meta information. CellAtlasSearch aims to assist researchers and clinicians in characterizing unannotated single cells. It also facilitates noise free, low dimensional representation of single-cell expression profiles by projecting them on a wide variety of reference samples. The web-server is accessible at: http://www.cellatlassearch.com.

Prediction of epigenetically regulated genes in breast cancer cell lines.

PubMed

Loss, Leandro A; Sadanandam, Anguraj; Durinck, Steffen; Nautiyal, Shivani; Flaucher, Diane; Carlton, Victoria E H; Moorhead, Martin; Lu, Yontao; Gray, Joe W; Faham, Malek; Spellman, Paul; Parvin, Bahram

2010-06-04

Methylation of CpG islands within the DNA promoter regions is one mechanism that leads to aberrant gene expression in cancer. In particular, the abnormal methylation of CpG islands may silence associated genes. Therefore, using high-throughput microarrays to measure CpG island methylation will lead to better understanding of tumor pathobiology and progression, while revealing potentially new biomarkers. We have examined a recently developed high-throughput technology for measuring genome-wide methylation patterns called mTACL. Here, we propose a computational pipeline for integrating gene expression and CpG island methylation profiles to identify epigenetically regulated genes for a panel of 45 breast cancer cell lines, which is widely used in the Integrative Cancer Biology Program (ICBP). The pipeline (i) reduces the dimensionality of the methylation data, (ii) associates the reduced methylation data with gene expression data, and (iii) ranks methylation-expression associations according to their epigenetic regulation. Dimensionality reduction is performed in two steps: (i) methylation sites are grouped across the genome to identify regions of interest, and (ii) methylation profiles are clustered within each region. Associations between the clustered methylation and the gene expression data sets generate candidate matches within a fixed neighborhood around each gene. Finally, the methylation-expression associations are ranked through a logistic regression, and their significance is quantified through permutation analysis. Our two-step dimensionality reduction compressed 90% of the original data, reducing 137,688 methylation sites to 14,505 clusters. Methylation-expression associations produced 18,312 correspondences, which were used to further analyze epigenetic regulation. Logistic regression was used to identify 58 genes from these correspondences that showed a statistically significant negative correlation between methylation profiles and gene expression in the panel of breast cancer cell lines. Subnetwork enrichment of these genes has identified 35 common regulators with 6 or more predicted markers. In addition to identifying epigenetically regulated genes, we show evidence of differentially expressed methylation patterns between the basal and luminal subtypes. Our results indicate that the proposed computational protocol is a viable platform for identifying epigenetically regulated genes. Our protocol has generated a list of predictors including COL1A2, TOP2A, TFF1, and VAV3, genes whose key roles in epigenetic regulation is documented in the literature. Subnetwork enrichment of these predicted markers further suggests that epigenetic regulation of individual genes occurs in a coordinated fashion and through common regulators.

Comparative Transcriptomes and EVO-DEVO Studies Depending on Next Generation Sequencing.

PubMed

Liu, Tiancheng; Yu, Lin; Liu, Lei; Li, Hong; Li, Yixue

2015-01-01

High throughput technology has prompted the progressive omics studies, including genomics and transcriptomics. We have reviewed the improvement of comparative omic studies, which are attributed to the high throughput measurement of next generation sequencing technology. Comparative genomics have been successfully applied to evolution analysis while comparative transcriptomics are adopted in comparison of expression profile from two subjects by differential expression or differential coexpression, which enables their application in evolutionary developmental biology (EVO-DEVO) studies. EVO-DEVO studies focus on the evolutionary pressure affecting the morphogenesis of development and previous works have been conducted to illustrate the most conserved stages during embryonic development. Old measurements of these studies are based on the morphological similarity from macro view and new technology enables the micro detection of similarity in molecular mechanism. Evolutionary model of embryo development, which includes the "funnel-like" model and the "hourglass" model, has been evaluated by combination of these new comparative transcriptomic methods with prior comparative genomic information. Although the technology has promoted the EVO-DEVO studies into a new era, technological and material limitation still exist and further investigations require more subtle study design and procedure.

A high-throughput quantitative expression analysis of cancer-related genes in human HepG2 cells in response to limonene, a potential anticancer agent.

PubMed

Hafidh, Rand R; Hussein, Saba Z; MalAllah, Mohammed Q; Abdulamir, Ahmed S; Abu Bakar, Fatimah

2017-11-14

Citrus bioactive compounds, as active anticancer agent, have been under focus by several studies worldwide. However, the underlying genes responsible for the anticancer potential have not been sufficiently highlighted. The current study investigated the gene expression profile of hepatocellular carcinoma, HepG2, cells after treatment with Limonene. The concentration that killed 50% of HepG2 cells was used to elucidate the genetic mechanisms of limonene anticancer activity. The apoptotic induction was detected by flow cytometry and confocal fluorescence microscope. Two of pro-apoptotic events, caspase-3 activation and phosphatidylserine translocation were manifested by confocal fluorescence microscopy. High-throughput real-time PCR was used to profile 1023 cancer-related genes in 16 different gene families related to the cancer development. In comparison to untreated cells, limonene increased the percentage of apoptotic cells up to 89.61%, by flow cytometry, and 48.2% by fluorescence microscopy. There was a significant limonene-driven differential gene expression of HepG2 cells in 15 different gene families. Limonene was shown to significantly (>2log) up-regulate and down-regulate 14 and 59 genes, respectively. The affected gene families, from most to least affected, were apoptosis induction, signal transduction, cancer genes augmentation, alteration in kinases expression, inflammation, DNA damage repair, and cell cycle proteins. The current study reveals that limonene could be a promising, cheap, and effective anticancer compound. The broad spectrum of limonene anticancer activity is interesting for anticancer drug development. Further research is needed to confirm the current findings and to examine the anticancer potential of limonene along with underlying mechanisms on different cell lines. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Internal validation of the GlobalFiler™ Express PCR Amplification Kit for the direct amplification of reference DNA samples on a high-throughput automated workflow.

PubMed

Flores, Shahida; Sun, Jie; King, Jonathan; Budowle, Bruce

2014-05-01

The GlobalFiler™ Express PCR Amplification Kit uses 6-dye fluorescent chemistry to enable multiplexing of 21 autosomal STRs, 1 Y-STR, 1 Y-indel and the sex-determining marker amelogenin. The kit is specifically designed for processing reference DNA samples in a high throughput manner. Validation studies were conducted to assess the performance and define the limitations of this direct amplification kit for typing blood and buccal reference DNA samples on various punchable collection media. Studies included thermal cycling sensitivity, reproducibility, precision, sensitivity of detection, minimum detection threshold, system contamination, stochastic threshold and concordance. Results showed that optimal amplification and injection parameters for a 1.2mm punch from blood and buccal samples were 27 and 28 cycles, respectively, combined with a 12s injection on an ABI 3500xL Genetic Analyzer. Minimum detection thresholds were set at 100 and 120RFUs for 27 and 28 cycles, respectively, and it was suggested that data from positive amplification controls provided a better threshold representation. Stochastic thresholds were set at 250 and 400RFUs for 27 and 28 cycles, respectively, as stochastic effects increased with cycle number. The minimum amount of input DNA resulting in a full profile was 0.5ng, however, the optimum range determined was 2.5-10ng. Profile quality from the GlobalFiler™ Express Kit and the previously validated AmpFlSTR(®) Identifiler(®) Direct Kit was comparable. The validation data support that reliable DNA typing results from reference DNA samples can be obtained using the GlobalFiler™ Express PCR Amplification Kit. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

PmiRExAt: plant miRNA expression atlas database and web applications

PubMed Central

Gurjar, Anoop Kishor Singh; Panwar, Abhijeet Singh; Gupta, Rajinder; Mantri, Shrikant S.

2016-01-01

High-throughput small RNA (sRNA) sequencing technology enables an entirely new perspective for plant microRNA (miRNA) research and has immense potential to unravel regulatory networks. Novel insights gained through data mining in publically available rich resource of sRNA data will help in designing biotechnology-based approaches for crop improvement to enhance plant yield and nutritional value. Bioinformatics resources enabling meta-analysis of miRNA expression across multiple plant species are still evolving. Here, we report PmiRExAt, a new online database resource that caters plant miRNA expression atlas. The web-based repository comprises of miRNA expression profile and query tool for 1859 wheat, 2330 rice and 283 maize miRNA. The database interface offers open and easy access to miRNA expression profile and helps in identifying tissue preferential, differential and constitutively expressing miRNAs. A feature enabling expression study of conserved miRNA across multiple species is also implemented. Custom expression analysis feature enables expression analysis of novel miRNA in total 117 datasets. New sRNA dataset can also be uploaded for analysing miRNA expression profiles for 73 plant species. PmiRExAt application program interface, a simple object access protocol web service allows other programmers to remotely invoke the methods written for doing programmatic search operations on PmiRExAt database. Database URL: http://pmirexat.nabi.res.in. PMID:27081157

Integrative Analysis of miRNA and mRNA Profiles in Response to Ethylene in Rose Petals during Flower Opening

PubMed Central

Pei, Haixia; Ma, Nan; Chen, Jiwei; Zheng, Yi; Tian, Ji; Li, Jing; Zhang, Shuai; Fei, Zhangjun; Gao, Junping

2013-01-01

MicroRNAs play an important role in plant development and plant responses to various biotic and abiotic stimuli. As one of the most important ornamental crops, rose (Rosa hybrida) possesses several specific morphological and physiological features, including recurrent flowering, highly divergent flower shapes, colors and volatiles. Ethylene plays an important role in regulating petal cell expansion during rose flower opening. Here, we report the population and expression profiles of miRNAs in rose petals during flower opening and in response to ethylene based on high throughput sequencing. We identified a total of 33 conserved miRNAs, as well as 47 putative novel miRNAs were identified from rose petals. The conserved and novel targets to those miRNAs were predicted using the rose floral transcriptome database. Expression profiling revealed that expression of 28 known (84.8% of known miRNAs) and 39 novel (83.0% of novel miRNAs) miRNAs was substantially changed in rose petals during the earlier opening period. We also found that 28 known and 22 novel miRNAs showed expression changes in response to ethylene treatment. Furthermore, we performed integrative analysis of expression profiles of miRNAs and their targets. We found that ethylene-caused expression changes of five miRNAs (miR156, miR164, miR166, miR5139 and rhy-miRC1) were inversely correlated to those of their seven target genes. These results indicate that these miRNA/target modules might be regulated by ethylene and were involved in ethylene-regulated petal growth. PMID:23696879

Highly Sensitive and High-Throughput Analysis of Plant Hormones Using MS-Probe Modification and Liquid Chromatography–Tandem Mass Spectrometry: An Application for Hormone Profiling in Oryza sativa

PubMed Central

Kojima, Mikiko; Kamada-Nobusada, Tomoe; Komatsu, Hirokazu; Takei, Kentaro; Kuroha, Takeshi; Mizutani, Masaharu; Ashikari, Motoyuki; Ueguchi-Tanaka, Miyako; Matsuoka, Makoto; Suzuki, Koji; Sakakibara, Hitoshi

2009-01-01

We have developed a highly sensitive and high-throughput method for the simultaneous analysis of 43 molecular species of cytokinins, auxins, ABA and gibberellins. This method consists of an automatic liquid handling system for solid phase extraction and ultra-performance liquid chromatography (UPLC) coupled with a tandem quadrupole mass spectrometer (qMS/MS) equipped with an electrospray interface (ESI; UPLC-ESI-qMS/MS). In order to improve the detection limit of negatively charged compounds, such as gibberellins, we chemically derivatized fractions containing auxin, ABA and gibberellins with bromocholine that has a quaternary ammonium functional group. This modification, that we call ‘MS-probe’, makes these hormone derivatives have a positive ion charge and permits all compounds to be measured in the positive ion mode with UPLC-ESI-qMS/MS in a single run. Consequently, quantification limits of gibberellins increased up to 50-fold. Our current method needs <100 mg (FW) of plant tissues to determine phytohormone profiles and enables us to analyze >180 plant samples simultaneously. Application of this method to plant hormone profiling enabled us to draw organ distribution maps of hormone species in rice and also to identify interactions among the four major hormones in the rice gibberellin signaling mutants, gid1-3, gid2-1 and slr1. Combining the results of hormone profiling data with transcriptome data in the gibberellin signaling mutants allows us to analyze relationships between changes in gene expression and hormone metabolism. PMID:19369275

Evaluation of Sequencing Approaches for High-Throughput Transcriptomics - (BOSC)

EPA Science Inventory

Whole-genome in vitro transcriptomics has shown the capability to identify mechanisms of action and estimates of potency for chemical-mediated effects in a toxicological framework, but with limited throughput and high cost. The generation of high-throughput global gene expression...

Primary Characterization of Small RNAs in Symbiotic Nitrogen-Fixing Bacteria.

PubMed

Robledo, Marta; García-Tomsig, Natalia I; Jiménez-Zurdo, José I

2018-01-01

High-throughput transcriptome profiling (RNAseq) has uncovered large and heterogeneous populations of small noncoding RNA species (sRNAs) with potential regulatory roles in bacteria. A large fraction of sRNAs are differentially regulated and rely on protein-assisted antisense interactions to trans-encoded target mRNAs to fine-tune posttranscriptional reprogramming of gene expression in response to external cues. However, annotation and function of sRNAs are still largely overlooked in nonmodel bacteria with complex lifestyles. Here, we describe experimental protocols successfully applied for the accurate annotation, expression profiling and target mRNA identification of trans-acting sRNAs in the nitrogen-fixing α-rhizobium Sinorhizobium meliloti. The protocols presented here can be similarly applied for the characterization of trans-sRNAs in genetically tractable α-proteobacteria of agronomical or clinical relevance interacting with eukaryotic hosts.

Baculovirus expression system and method for high throughput expression of genetic material

DOEpatents

Clark, Robin; Davies, Anthony

2001-01-01

The present invention provides novel recombinant baculovirus expression systems for expressing foreign genetic material in a host cell. Such expression systems are readily adapted to an automated method for expression foreign genetic material in a high throughput manner. In other aspects, the present invention features a novel automated method for determining the function of foreign genetic material by transfecting the same into a host by way of the recombinant baculovirus expression systems according to the present invention.

The Spatial and Temporal Transcriptomic Landscapes of Ginseng, Panax ginseng C. A. Meyer.

PubMed

Wang, Kangyu; Jiang, Shicui; Sun, Chunyu; Lin, Yanping; Yin, Rui; Wang, Yi; Zhang, Meiping

2015-12-11

Ginseng, including Asian ginseng (Panax ginseng C. A. Meyer) and American ginseng (P. quinquefolius L.), is one of the most important medicinal herbs in Asia and North America, but significantly understudied. This study sequenced and characterized the transcriptomes and expression profiles of genes expressed in 14 tissues and four different aged roots of Asian ginseng. A total of 265.2 million 100-bp clean reads were generated using the high-throughput sequencing platform HiSeq 2000, representing >8.3x of the 3.2-Gb ginseng genome. From the sequences, 248,993 unigenes were assembled for whole plant, 61,912-113,456 unigenes for each tissue and 54,444-65,412 unigenes for different year-old roots. We comprehensively analyzed the unigene sets and gene expression profiles. We found that the number of genes allocated to each functional category is stable across tissues or developmental stages, while the expression profiles of different genes of a gene family or involved in ginsenoside biosynthesis dramatically diversified spatially and temporally. These results provide an overall insight into the spatial and temporal transcriptome dynamics and landscapes of Asian ginseng, and comprehensive resources for advanced research and breeding of ginseng and related species.

Recent developments in software tools for high-throughput in vitro ADME support with high-resolution MS.

PubMed

Paiva, Anthony; Shou, Wilson Z

2016-08-01

The last several years have seen the rapid adoption of the high-resolution MS (HRMS) for bioanalytical support of high throughput in vitro ADME profiling. Many capable software tools have been developed and refined to process quantitative HRMS bioanalysis data for ADME samples with excellent performance. Additionally, new software applications specifically designed for quan/qual soft spot identification workflows using HRMS have greatly enhanced the quality and efficiency of the structure elucidation process for high throughput metabolite ID in early in vitro ADME profiling. Finally, novel approaches in data acquisition and compression, as well as tools for transferring, archiving and retrieving HRMS data, are being continuously refined to tackle the issue of large data file size typical for HRMS analyses.

High Throughput Genotoxicity Profiling of the US EPA ToxCast Chemical Library

EPA Science Inventory

A key aim of the ToxCast project is to investigate modern molecular and genetic high content and high throughput screening (HTS) assays, along with various computational tools to supplement and perhaps replace traditional assays for evaluating chemical toxicity. Genotoxicity is a...

Identification of differentially expressed genes in cucumber (Cucumis sativus L.) root under waterlogging stress by digital gene expression profile.

PubMed

Qi, Xiao-Hua; Xu, Xue-Wen; Lin, Xiao-Jian; Zhang, Wen-Jie; Chen, Xue-Hao

2012-03-01

High-throughput tag-sequencing (Tag-seq) analysis based on the Solexa Genome Analyzer platform was applied to analyze the gene expression profiling of cucumber plant at 5 time points over a 24h period of waterlogging treatment. Approximately 5.8 million total clean sequence tags per library were obtained with 143013 distinct clean tag sequences. Approximately 23.69%-29.61% of the distinct clean tags were mapped unambiguously to the unigene database, and 53.78%-60.66% of the distinct clean tags were mapped to the cucumber genome database. Analysis of the differentially expressed genes revealed that most of the genes were down-regulated in the waterlogging stages, and the differentially expressed genes mainly linked to carbon metabolism, photosynthesis, reactive oxygen species generation/scavenging, and hormone synthesis/signaling. Finally, quantitative real-time polymerase chain reaction using nine genes independently verified the tag-mapped results. This present study reveals the comprehensive mechanisms of waterlogging-responsive transcription in cucumber. Copyright © 2011 Elsevier Inc. All rights reserved.

Identification and Expression Analysis of microRNAs at the Grain Filling Stage in Rice(Oryza sativa L.)via Deep Sequencing

PubMed Central

Yi, Rong; Zhu, Zhixuan; Hu, Jihong; Qian, Qian; Dai, Jincheng; Ding, Yi

2013-01-01

MicroRNAs (miRNAs) have been shown to play crucial roles in the regulation of plant development. In this study, high-throughput RNA-sequencing technology was used to identify novel miRNAs, and to reveal miRNAs expression patterns at different developmental stages during rice (Oryza sativa L.) grain filling. A total of 434 known miRNAs (380, 402, 390 and 392 at 5, 7, 12 and 17 days after fertilization, respectively.) were obtained from rice grain. The expression profiles of these identified miRNAs were analyzed and the results showed that 161 known miRNAs were differentially expressed during grain development, a high proportion of which were up-regulated from 5 to 7 days after fertilization. In addition, sixty novel miRNAs were identified, and five of these were further validated experimentally. Additional analysis showed that the predicted targets of the differentially expressed miRNAs may participate in signal transduction, carbohydrate and nitrogen metabolism, the response to stimuli and epigenetic regulation. In this study, differences were revealed in the composition and expression profiles of miRNAs among individual developmental stages during the rice grain filling process, and miRNA editing events were also observed, analyzed and validated during this process. The results provide novel insight into the dynamic profiles of miRNAs in developing rice grain and contribute to the understanding of the regulatory roles of miRNAs in grain filling. PMID:23469249

iPSC-derived neurons as a higher-throughput readout for autism: Promises and pitfalls

PubMed Central

Prilutsky, Daria; Palmer, Nathan P.; Smedemark-Margulies, Niklas; Schlaeger, Thorsten M.; Margulies, David M.; Kohane, Isaac S.

2014-01-01

The elucidation of disease etiologies and establishment of robust, scalable, high-throughput screening assays for autism spectrum disorders (ASDs) have been impeded by both inaccessibility of disease-relevant neuronal tissue and the genetic heterogeneity of the disorder. Neuronal cells derived from induced pluripotent stem cells (iPSCs) from autism patients may circumvent these obstacles and serve as relevant cell models. To date, derived cells are characterized and screened by assessing their neuronal phenotypes. These characterizations are often etiology-specific or lack reproducibility and stability. In this manuscript, we present an overview of efforts to study iPSC-derived neurons as a model for autism, and we explore the plausibility of gene expression profiling as a reproducible and stable disease marker. PMID:24374161

Expression profiling of peroxisome proliferator-activated receptor-delta (PPAR-delta) in mouse tissues using tissue microarray.

PubMed

Higashiyama, Hiroyuki; Billin, Andrew N; Okamoto, Yuji; Kinoshita, Mine; Asano, Satoshi

2007-05-01

Peroxisome proliferator-activated receptor-delta (PPAR-delta) is known as a transcription factor involved in the regulation of fatty acid oxidation and mitochondrial biogenesis in several tissues, such as skeletal muscle, liver and adipose tissues. In this study, to elucidate systemic physiological functions of PPAR-delta, we examined the tissue distribution and localization of PPAR-delta in adult mouse tissues using tissue microarray (TMA)-based immunohistochemistry. PPAR-delta positive signals were observed on variety of tissues/cells in multiple systems including cardiovascular, urinary, respiratory, digestive, endocrine, nervous, hematopoietic, immune, musculoskeletal, sensory and reproductive organ systems. In these organs, PPAR-delta immunoreactivity was generally localized on the nucleus, although cytoplasmic localization was observed on several cell types including neurons in the nervous system and cells of the islet of Langerhans. These expression profiling data implicate various physiological roles of PPAR-delta in multiple organ systems. TMA-based immunohistochemistry enables to profile comprehensive protein localization and distribution in a high-throughput manner.

Near-isogenic cotton germplasm lines that differ in fiber-bundle strength have temporal differences in fiber gene expression patterns as revealed by comparative high-throughput profiling.

PubMed

Hinchliffe, Doug J; Meredith, William R; Yeater, Kathleen M; Kim, Hee Jin; Woodward, Andrew W; Chen, Z Jeffrey; Triplett, Barbara A

2010-05-01

Gene expression profiles of developing cotton (Gossypium hirsutum L.) fibers from two near-isogenic lines (NILs) that differ in fiber-bundle strength, short-fiber content, and in fewer than two genetic loci were compared using an oligonucleotide microarray. Fiber gene expression was compared at five time points spanning fiber elongation and secondary cell wall (SCW) biosynthesis. Fiber samples were collected from field plots in a randomized, complete block design, with three spatially distinct biological replications for each NIL at each time point. Microarray hybridizations were performed in a loop experimental design that allowed comparisons of fiber gene expression profiles as a function of time between the two NILs. Overall, developmental expression patterns revealed by the microarray experiment agreed with previously reported cotton fiber gene expression patterns for specific genes. Additionally, genes expressed coordinately with the onset of SCW biosynthesis in cotton fiber correlated with gene expression patterns of other SCW-producing plant tissues. Functional classification and enrichment analysis of differentially expressed genes between the two NILs revealed that genes associated with SCW biosynthesis were significantly up-regulated in fibers of the high-fiber quality line at the transition stage of cotton fiber development. For independent corroboration of the microarray results, 15 genes were selected for quantitative reverse transcription PCR analysis of fiber gene expression. These analyses, conducted over multiple field years, confirmed the temporal difference in fiber gene expression between the two NILs. We hypothesize that the loci conferring temporal differences in fiber gene expression between the NILs are important regulatory sequences that offer the potential for more targeted manipulation of cotton fiber quality.

High-throughput screening, predictive modeling and computational embryology - Abstract

EPA Science Inventory

High-throughput screening (HTS) studies are providing a rich source of data that can be applied to chemical profiling to address sensitivity and specificity of molecular targets, biological pathways, cellular and developmental processes. EPA’s ToxCast project is testing 960 uniq...

High-throughput profiling and analysis of plant responses over time to abiotic stress

USDA-ARS?s Scientific Manuscript database

Energy sorghum (Sorghum bicolor (L.) Moench) is a rapidly growing, high-biomass, annual crop prized for abiotic stress tolerance. Measuring genotype-by-environment (G x E) interactions remains a progress bottleneck. High throughput phenotyping within controlled environments has been proposed as a po...

NCBI GEO: archive for functional genomics data sets—10 years on

PubMed Central

Barrett, Tanya; Troup, Dennis B.; Wilhite, Stephen E.; Ledoux, Pierre; Evangelista, Carlos; Kim, Irene F.; Tomashevsky, Maxim; Marshall, Kimberly A.; Phillippy, Katherine H.; Sherman, Patti M.; Muertter, Rolf N.; Holko, Michelle; Ayanbule, Oluwabukunmi; Yefanov, Andrey; Soboleva, Alexandra

2011-01-01

A decade ago, the Gene Expression Omnibus (GEO) database was established at the National Center for Biotechnology Information (NCBI). The original objective of GEO was to serve as a public repository for high-throughput gene expression data generated mostly by microarray technology. However, the research community quickly applied microarrays to non-gene-expression studies, including examination of genome copy number variation and genome-wide profiling of DNA-binding proteins. Because the GEO database was designed with a flexible structure, it was possible to quickly adapt the repository to store these data types. More recently, as the microarray community switches to next-generation sequencing technologies, GEO has again adapted to host these data sets. Today, GEO stores over 20 000 microarray- and sequence-based functional genomics studies, and continues to handle the majority of direct high-throughput data submissions from the research community. Multiple mechanisms are provided to help users effectively search, browse, download and visualize the data at the level of individual genes or entire studies. This paper describes recent database enhancements, including new search and data representation tools, as well as a brief review of how the community uses GEO data. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/. PMID:21097893

Defining the limits of physiological plasticity: how gene expression can assess and predict the consequences of ocean change

PubMed Central

Evans, Tyler G.; Hofmann, Gretchen E.

2012-01-01

Anthropogenic stressors, such as climate change, are driving fundamental shifts in the abiotic characteristics of marine ecosystems. As the environmental aspects of our world's oceans deviate from evolved norms, of major concern is whether extant marine species possess the capacity to cope with such rapid change. In what many scientists consider the post-genomic era, tools that exploit the availability of DNA sequence information are being increasingly recognized as relevant to questions surrounding ocean change and marine conservation. In this review, we highlight the application of high-throughput gene-expression profiling, primarily transcriptomics, to the field of marine conservation physiology. Through the use of case studies, we illustrate how gene expression can be used to standardize metrics of sub-lethal stress, track organism condition in natural environments and bypass phylogenetic barriers that hinder the application of other physiological techniques to conservation. When coupled with fine-scale monitoring of environmental variables, gene-expression profiling provides a powerful approach to conservation capable of informing diverse issues related to ocean change, from coral bleaching to the spread of invasive species. Integrating novel approaches capable of improving existing conservation strategies, including gene-expression profiling, will be critical to ensuring the ecological and economic health of the global ocean. PMID:22566679

The effect of red light and far-red light conditions on secondary metabolism in agarwood.

PubMed

Kuo, Tony Chien-Yen; Chen, Chuan-Hung; Chen, Shu-Hwa; Lu, I-Hsuan; Chu, Mei-Ju; Huang, Li-Chun; Lin, Chung-Yen; Chen, Chien-Yu; Lo, Hsiao-Feng; Jeng, Shih-Tong; Chen, Long-Fang O

2015-06-12

Agarwood, a heartwood derived from Aquilaria trees, is a valuable commodity that has seen prevalent use among many cultures. In particular, it is widely used in herbal medicine and many compounds in agarwood are known to exhibit medicinal properties. Although there exists much research into medicinal herbs and extraction of high value compounds, few have focused on increasing the quantity of target compounds through stimulation of its related pathways in this species. In this study, we observed that cucurbitacin yield can be increased through the use of different light conditions to stimulate related pathways and conducted three types of high-throughput sequencing experiments in order to study the effect of light conditions on secondary metabolism in agarwood. We constructed genome-wide profiles of RNA expression, small RNA, and DNA methylation under red light and far-red light conditions. With these profiles, we identified a set of small RNA which potentially regulates gene expression via the RNA-directed DNA methylation pathway. We demonstrate that light conditions can be used to stimulate pathways related to secondary metabolism, increasing the yield of cucurbitacins. The genome-wide expression and methylation profiles from our study provide insight into the effect of light on gene expression for secondary metabolism in agarwood and provide compelling new candidates towards the study of functional secondary metabolic components.

MicroRNA Expression Profiling of the Armed Forces Health Surveillance Branch Cohort for Identification of "Enviro-miRs" Associated With Deployment-Based Environmental Exposure.

PubMed

Dalgard, Clifton L; Polston, Keith F; Sukumar, Gauthaman; Mallon, Col Timothy M; Wilkerson, Matthew D; Pollard, Harvey B

2016-08-01

The aim of this study was to identify serum microRNA (miRNA) biomarkers that indicate deployment-associated exposures in service members at military installations with open burn pits. Another objective was to determine detection rates of miRNAs in Department of Defense Serum Repository (DoDSR) samples with a high-throughput methodology. Low-volume serum samples (n = 800) were profiled by miRNA-capture isolation, pre-amplification, and measurement by a quantitative PCR-based OpenArray platform. Normalized quantitative cycle values were used for differential expression analysis between groups. Assay specificity, dynamic range, reproducibility, and detection rates by OpenArray passed target desired specifications. Serum abundant miRNAs were consistently measured in study specimens. Four miRNAs were differentially expressed in the case deployment group subjects. miRNAs are suitable RNA species for biomarker discovery in the DoDSR serum specimens. Serum miRNAs are candidate biomarkers for deployment and environmental exposure in military service members.

Risk stratification in myelodysplastic syndromes: is there a role for gene expression profiling?

PubMed

Zeidan, Amer M; Prebet, Thomas; Saad Aldin, Ehab; Gore, Steven David

2014-04-01

Evaluation of: Pellagatti A, Benner A, Mills KI et al. Identification of gene expression-based prognostic markers in the hematopoietic stem cells of patients with myelodysplastic syndromes. J. Clin. Oncol. 31(28), 3557-3564 (2013). Patients with myelodysplastic syndromes (MDS) exhibit wide heterogeneity in clinical outcomes making accurate risk-stratification an integral part of the risk-adaptive management paradigm. Current prognostic schemes for MDS rely on clinicopathological parameters. Despite the increasing knowledge of the genetic landscape of MDS and the prognostic impact of many newly discovered molecular aberrations, none to date has been incorporated formally into the major risk models. Efforts are ongoing to use data generated from genome-wide high-throughput techniques to improve the 'individualized' outcome prediction for patients. We here discuss an important paper in which gene expression profiling (GEP) technology was applied to marrow CD34(+) cells from 125 MDS patients to generate and validate a standardized GEP-based prognostic signature.

Fun with High Throughput Toxicokinetics (CalEPA webinar)

EPA Science Inventory

Thousands of chemicals have been profiled by high-throughput screening (HTS) programs such as ToxCast and Tox21. These chemicals are tested in part because there are limited or no data on hazard, exposure, or toxicokinetics (TK). TK models aid in predicting tissue concentrations ...

HTTK: R Package for High-Throughput Toxicokinetics

EPA Science Inventory

Thousands of chemicals have been profiled by high-throughput screening programs such as ToxCast and Tox21; these chemicals are tested in part because most of them have limited or no data on hazard, exposure, or toxicokinetics. Toxicokinetic models aid in predicting tissue concent...

High-throughput screening, predictive modeling and computational embryology

EPA Science Inventory

High-throughput screening (HTS) studies are providing a rich source of data that can be applied to profile thousands of chemical compounds for biological activity and potential toxicity. EPA’s ToxCast™ project, and the broader Tox21 consortium, in addition to projects worldwide,...

LncRNA Expression Profile of Human Thoracic Aortic Dissection by High-Throughput Sequencing.

PubMed

Sun, Jie; Chen, Guojun; Jing, Yuanwen; He, Xiang; Dong, Jianting; Zheng, Junmeng; Zou, Meisheng; Li, Hairui; Wang, Shifei; Sun, Yili; Liao, Wangjun; Liao, Yulin; Feng, Li; Bin, Jianping

2018-01-01

In this study, the long non-coding RNA (lncRNA) expression profile in human thoracic aortic dissection (TAD), a highly lethal cardiovascular disease, was investigated. Human TAD (n=3) and normal aortic tissues (NA) (n=3) were examined by high-throughput sequencing. Bioinformatics analyses were performed to predict the roles of aberrantly expressed lncRNAs. Quantitative real-time polymerase chain reaction (qRT-PCR) was applied to validate the results. A total of 269 lncRNAs (159 up-regulated and 110 down-regulated) and 2, 255 mRNAs (1 294 up-regulated and 961 down-regulated) were aberrantly expressed in human TAD (fold-change> 1.5, P< 0.05). QRT-PCR results of five dysregulated genes were consistent with HTS data. A lncRNA-mRNA coexpression analysis showed positive correlations between the up-regulated lncRNA (ENSG00000269936) and its adjacent up-regulated mRNA (MAP2K6, R=0.940, P< 0.01), and between the down-regulated lncRNA_1421 and its down-regulated mRNAs (FBLN5, R=0.950, P< 0.01; ACTA2, R=0.96, P< 0.01; TIMP3, R=0.96, P< 0.05). The lncRNA-miRNA-mRNA network indicated that the up-regulated lncRNA XIST and p21 had similar sequences targeted by has-miR-17-5p. The results of luciferase assay and fluorescence immuno-cytochemistry were consistent with that. And qRT-PCR results showed that lncRNA XIST and p21 were expressed at a higher level and has-miR-17-5p was expressed at a lower level in TAD than in NA. The predicted binding motifs of three up-regulated lncRNAs (ENSG00000248508, ENSG00000226530, and EG00000259719) were correlated with up-regulated RUNX1 (R=0.982, P< 0.001; R=0.967, P< 0.01; R=0.960, P< 0.01, respectively). Our study revealed a set of dysregulated lncRNAs and predicted their multiple potential functions in human TAD. These findings suggest that lncRNAs are novel potential therapeutic targets for human TAD. © 2018 The Author(s). Published by S. Karger AG, Basel.

In vivo Monitoring of Transcriptional Dynamics After Lower-Limb Muscle Injury Enables Quantitative Classification of Healing

PubMed Central

Aguilar, Carlos A.; Shcherbina, Anna; Ricke, Darrell O.; Pop, Ramona; Carrigan, Christopher T.; Gifford, Casey A.; Urso, Maria L.; Kottke, Melissa A.; Meissner, Alexander

2015-01-01

Traumatic lower-limb musculoskeletal injuries are pervasive amongst athletes and the military and typically an individual returns to activity prior to fully healing, increasing a predisposition for additional injuries and chronic pain. Monitoring healing progression after a musculoskeletal injury typically involves different types of imaging but these approaches suffer from several disadvantages. Isolating and profiling transcripts from the injured site would abrogate these shortcomings and provide enumerative insights into the regenerative potential of an individual’s muscle after injury. In this study, a traumatic injury was administered to a mouse model and healing progression was examined from 3 hours to 1 month using high-throughput RNA-Sequencing (RNA-Seq). Comprehensive dissection of the genome-wide datasets revealed the injured site to be a dynamic, heterogeneous environment composed of multiple cell types and thousands of genes undergoing significant expression changes in highly regulated networks. Four independent approaches were used to determine the set of genes, isoforms, and genetic pathways most characteristic of different time points post-injury and two novel approaches were developed to classify injured tissues at different time points. These results highlight the possibility to quantitatively track healing progression in situ via transcript profiling using high- throughput sequencing. PMID:26381351

An image analysis toolbox for high-throughput C. elegans assays

PubMed Central

Wählby, Carolina; Kamentsky, Lee; Liu, Zihan H.; Riklin-Raviv, Tammy; Conery, Annie L.; O’Rourke, Eyleen J.; Sokolnicki, Katherine L.; Visvikis, Orane; Ljosa, Vebjorn; Irazoqui, Javier E.; Golland, Polina; Ruvkun, Gary; Ausubel, Frederick M.; Carpenter, Anne E.

2012-01-01

We present a toolbox for high-throughput screening of image-based Caenorhabditis elegans phenotypes. The image analysis algorithms measure morphological phenotypes in individual worms and are effective for a variety of assays and imaging systems. This WormToolbox is available via the open-source CellProfiler project and enables objective scoring of whole-animal high-throughput image-based assays of C. elegans for the study of diverse biological pathways relevant to human disease. PMID:22522656

Development of Engineered Bacteriophages for Escherichia coli Detection and High-Throughput Antibiotic Resistance Determination.

PubMed

Chen, Juhong; Alcaine, Samuel D; Jackson, Angelyca A; Rotello, Vincent M; Nugen, Sam R

2017-04-28

T7 bacteriophages (phages) have been genetically engineered to carry the lacZ operon, enabling the overexpression of beta-galactosidase (β-gal) during phage infection and allowing for the enhanced colorimetric detection of Escherichia coli (E. coli). Following the phage infection of E. coli, the enzymatic activity of the released β-gal was monitored using a colorimetric substrate. Compared with a control T7 phage, our T7 lacZ phage generated significantly higher levels of β-gal expression following phage infection, enabling a lower limit of detection for E. coli cells. Using this engineered T7 lacZ phage, we were able to detect E. coli cells at 10 CFU·mL -1 within 7 h. Furthermore, we demonstrated the potential for phage-based sensing of bacteria antibiotic resistance profiling using our T7 lacZ phage, and subsequent β-gal expression to detect antibiotic resistant profile of E. coli strains.

Pathway Profiling and Tissue Modeling Using ToxCast HTS Data

EPA Science Inventory

High-throughput screening (HTS) and high-content screening (HCS) assays are providing data-rich studies to probe and profile the direct cellular effects of thousands of chemical compounds in commerce or potentially entering the environment. In vitro profiling may compare unknown ...

Analytic expressions for Atomic Layer Deposition: coverage, throughput, and materials utilization in cross-flow, particle coating, and spatial ALD

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

Yanguas-Gil, Angel; Elam, Jeffrey W.

2014-05-01

In this work, the authors present analytic models for atomic layer deposition (ALD) in three common experimental configurations: cross-flow, particle coating, and spatial ALD. These models, based on the plug-flow and well-mixed approximations, allow us to determine the minimum dose times and materials utilization for all three configurations. A comparison between the three models shows that throughput and precursor utilization can each be expressed by universal equations, in which the particularity of the experimental system is contained in a single parameter related to the residence time of the precursor in the reactor. For the case of cross-flow reactors, the authorsmore » show how simple analytic expressions for the reactor saturation profiles agree well with experimental results. Consequently, the analytic model can be used to extract information about the ALD surface chemistry (e. g., the reaction probability) by comparing the analytic and experimental saturation profiles, providing a useful tool for characterizing new and existing ALD processes. (C) 2014 American Vacuum Society« less

Identification of microRNAs in the Toxigenic Dinoflagellate Alexandrium catenella by High-Throughput Illumina Sequencing and Bioinformatic Analysis

PubMed Central

Geng, Huili; Sui, Zhenghong; Zhang, Shu; Du, Qingwei; Ren, Yuanyuan; Liu, Yuan; Kong, Fanna; Zhong, Jie; Ma, Qingxia

2015-01-01

Micro-ribonucleic acids (miRNAs) are a large group of endogenous, tiny, non-coding RNAs consisting of 19–25 nucleotides that regulate gene expression at either the transcriptional or post-transcriptional level by mediating gene silencing in eukaryotes. They are considered to be important regulators that affect growth, development, and response to various stresses in plants. Alexandrium catenella is an important marine toxic phytoplankton species that can cause harmful algal blooms (HABs). To date, identification and function analysis of miRNAs in A. catenella remain largely unexamined. In this study, high-throughput sequencing was performed on A. catenella to identify and quantitatively profile the repertoire of small RNAs from two different growth phases. A total of 38,092,056 and 32,969,156 raw reads were obtained from the two small RNA libraries, respectively. In total, 88 mature miRNAs belonging to 32 miRNA families were identified. Significant differences were found in the member number, expression level of various families, and expression abundance of each member within a family. A total of 15 potentially novel miRNAs were identified. Comparative profiling showed that 12 known miRNAs exhibited differential expression between the lag phase and the logarithmic phase. Real-time quantitative RT-PCR (qPCR) was performed to confirm the expression of two differentially expressed miRNAs that were one up-regulated novel miRNA (aca-miR-3p-456915), and one down-regulated conserved miRNA (tae-miR159a). The expression trend of the qPCR assay was generally consistent with the deep sequencing result. Target predictions of the 12 differentially expressed miRNAs resulted in 1813target genes. Gene ontology (GO) analysis and the Kyoto Encyclopedia of Genes and Genomes pathway database (KEGG) annotations revealed that some miRNAs were associated with growth and developmental processes of the alga. These results provide insights into the roles that miRNAs play in the growth of A. catenella, and they provide the basis for further studies of the molecular mechanisms that underlie bloom growth in red tides species. PMID:26398216

Use of High-Throughput Testing and Approaches for Evaluating Chemical Risk-Relevance to Humans

EPA Science Inventory

ToxCast is profiling the bioactivity of thousands of chemicals based on high-throughput screening (HTS) and computational models that integrate knowledge of biological systems and in vivo toxicities. Many of these assays probe signaling pathways and cellular processes critical to...

Circular RNA Expression Profile of Pancreatic Ductal Adenocarcinoma Revealed by Microarray.

PubMed

Li, Haimin; Hao, Xiaokun; Wang, Huimin; Liu, Zhengcai; He, Yong; Pu, Meng; Zhang, Hongtao; Yu, Hengchao; Duan, Juanli; Qu, Shibin

2016-01-01

Circular RNAs (circRNAs) are a special novel type of a stable, diverse and conserved noncoding RNA in mammalian cells. Particularly in cancer, circRNAs have been reported to be widely involved in the physiological/pathological process of life. However, it is unclear whether circRNAs are specifically involved in pancreatic ductal adenocarcinoma (PDAC). We investigated the expression profile of circRNAs in six PDAC cancer samples and paired adjacent normal tissues using microarray. A high-throughput circRNA microarray was used to identify dysregulated circular RNAs in six PDAC patients. Bioinformatic analyses were applied to study these differentially expressed circRNAs. Furthermore, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to confirm these results. We revealed and confirmed that a number of circRNAs were dysregulated, which suggests a potential role in pancreatic cancer. this study demonstrates that clusters of circRNAs are aberrantly expressed in PDAC compared with normal samples and provides new potential targets for the future treatment of PDAC and novel insights into PDAC biology. © 2016 The Author(s) Published by S. Karger AG, Basel.

Comprehensive analysis of RNA-protein interactions by high-throughput sequencing-RNA affinity profiling.

PubMed

Tome, Jacob M; Ozer, Abdullah; Pagano, John M; Gheba, Dan; Schroth, Gary P; Lis, John T

2014-06-01

RNA-protein interactions play critical roles in gene regulation, but methods to quantitatively analyze these interactions at a large scale are lacking. We have developed a high-throughput sequencing-RNA affinity profiling (HiTS-RAP) assay by adapting a high-throughput DNA sequencer to quantify the binding of fluorescently labeled protein to millions of RNAs anchored to sequenced cDNA templates. Using HiTS-RAP, we measured the affinity of mutagenized libraries of GFP-binding and NELF-E-binding aptamers to their respective targets and identified critical regions of interaction. Mutations additively affected the affinity of the NELF-E-binding aptamer, whose interaction depended mainly on a single-stranded RNA motif, but not that of the GFP aptamer, whose interaction depended primarily on secondary structure.

Gene expression profiling of flax (Linum usitatissimum L.) under edaphic stress.

PubMed

Dmitriev, Alexey A; Kudryavtseva, Anna V; Krasnov, George S; Koroban, Nadezhda V; Speranskaya, Anna S; Krinitsina, Anastasia A; Belenikin, Maxim S; Snezhkina, Anastasiya V; Sadritdinova, Asiya F; Kishlyan, Natalya V; Rozhmina, Tatiana A; Yurkevich, Olga Yu; Muravenko, Olga V; Bolsheva, Nadezhda L; Melnikova, Nataliya V

2016-11-16

Cultivated flax (Linum usitatissimum L.) is widely used for production of textile, food, chemical and pharmaceutical products. However, various stresses decrease flax production. Search for genes, which are involved in stress response, is necessary for breeding of adaptive cultivars. Imbalanced concentration of nutrient elements in soil decrease flax yields and also results in heritable changes in some flax lines. The appearance of Linum Insertion Sequence 1 (LIS-1) is the most studied modification. However, LIS-1 function is still unclear. High-throughput sequencing of transcriptome of flax plants grown under normal (N), phosphate deficient (P), and nutrient excess (NPK) conditions was carried out using Illumina platform. The assembly of transcriptome was performed, and a total of 34924, 33797, and 33698 unique transcripts for N, P, and NPK sequencing libraries were identified, respectively. We have not revealed any LIS-1 derived mRNA in our sequencing data. The analysis of high-throughput sequencing data allowed us to identify genes with potentially differential expression under imbalanced nutrition. For further investigation with qPCR, 15 genes were chosen and their expression levels were evaluated in the extended sampling of 31 flax plants. Significant expression alterations were revealed for genes encoding WRKY and JAZ protein families under P and NPK conditions. Moreover, the alterations of WRKY family genes differed depending on LIS-1 presence in flax plant genome. Besides, we revealed slight and LIS-1 independent mRNA level changes of KRP2 and ING1 genes, which are adjacent to LIS-1, under nutrition stress. Differentially expressed genes were identified in flax plants, which were grown under phosphate deficiency and excess nutrition, on the basis of high-throughput sequencing and qPCR data. We showed that WRKY and JAS gene families participate in flax response to imbalanced nutrient content in soil. Besides, we have not identified any mRNA, which could be derived from LIS-1, in our transcriptome sequencing data. Expression of LIS-1 flanking genes, ING1 and KRP2, was suggested not to be nutrient stress-induced. Obtained results provide new insights into edaphic stress response in flax and the role of LIS-1 in these process.

Accounting for isotopic clustering in Fourier transform mass spectrometry data analysis for clinical diagnostic studies.

PubMed

Kakourou, Alexia; Vach, Werner; Nicolardi, Simone; van der Burgt, Yuri; Mertens, Bart

2016-10-01

Mass spectrometry based clinical proteomics has emerged as a powerful tool for high-throughput protein profiling and biomarker discovery. Recent improvements in mass spectrometry technology have boosted the potential of proteomic studies in biomedical research. However, the complexity of the proteomic expression introduces new statistical challenges in summarizing and analyzing the acquired data. Statistical methods for optimally processing proteomic data are currently a growing field of research. In this paper we present simple, yet appropriate methods to preprocess, summarize and analyze high-throughput MALDI-FTICR mass spectrometry data, collected in a case-control fashion, while dealing with the statistical challenges that accompany such data. The known statistical properties of the isotopic distribution of the peptide molecules are used to preprocess the spectra and translate the proteomic expression into a condensed data set. Information on either the intensity level or the shape of the identified isotopic clusters is used to derive summary measures on which diagnostic rules for disease status allocation will be based. Results indicate that both the shape of the identified isotopic clusters and the overall intensity level carry information on the class outcome and can be used to predict the presence or absence of the disease.

Long non-coding RNA expression patterns in lung tissues of chronic cigarette smoke induced COPD mouse model.

PubMed

Zhang, Haiyun; Sun, Dejun; Li, Defu; Zheng, Zeguang; Xu, Jingyi; Liang, Xue; Zhang, Chenting; Wang, Sheng; Wang, Jian; Lu, Wenju

2018-05-15

Long non-coding RNAs (lncRNAs) have critical regulatory roles in protein-coding gene expression. Aberrant expression profiles of lncRNAs have been observed in various human diseases. In this study, we investigated transcriptome profiles in lung tissues of chronic cigarette smoke (CS)-induced COPD mouse model. We found that 109 lncRNAs and 260 mRNAs were significantly differential expressed in lungs of chronic CS-induced COPD mouse model compared with control animals. GO and KEGG analyses indicated that differentially expressed lncRNAs associated protein-coding genes were mainly involved in protein processing of endoplasmic reticulum pathway, and taurine and hypotaurine metabolism pathway. The combination of high throughput data analysis and the results of qRT-PCR validation in lungs of chronic CS-induced COPD mouse model, 16HBE cells with CSE treatment and PBMC from patients with COPD revealed that NR_102714 and its associated protein-coding gene UCHL1 might be involved in the development of COPD both in mouse and human. In conclusion, our study demonstrated that aberrant expression profiles of lncRNAs and mRNAs existed in lungs of chronic CS-induced COPD mouse model. From animal models perspective, these results might provide further clues to investigate biological functions of lncRNAs and their potential target protein-coding genes in the pathogenesis of COPD.

The growing impact of lyophilized cell-free protein expression systems

PubMed Central

Hunt, J. Porter; Yang, Seung Ook; Wilding, Kristen M.; Bundy, Bradley C.

2017-01-01

ABSTRACT Recently reported shelf-stable, on-demand protein synthesis platforms are enabling new possibilities in biotherapeutics, biosensing, biocatalysis, and high throughput protein expression. Lyophilized cell-free protein expression systems not only overcome cold-storage limitations, but also enable stockpiling for on-demand synthesis and completely sterilize the protein synthesis platform. Recently reported high-yield synthesis of cytotoxic protein Onconase from lyophilized E. coli extract preparations demonstrates the utility of lyophilized cell-free protein expression and its potential for creating on-demand biotherapeutics, vaccines, biosensors, biocatalysts, and high throughput protein synthesis. PMID:27791452

Predictive Model of Rat Reproductive Toxicity from ToxCast High Throughput Screening

EPA Science Inventory

The EPA ToxCast research program uses high throughput screening for bioactivity profiling and predicting the toxicity of large numbers of chemicals. ToxCast Phase‐I tested 309 well‐characterized chemicals in over 500 assays for a wide range of molecular targets and cellular respo...

microRNA profiling in the zoonotic parasite Echinococcus canadensis using a high-throughput approach.

PubMed

Macchiaroli, Natalia; Cucher, Marcela; Zarowiecki, Magdalena; Maldonado, Lucas; Kamenetzky, Laura; Rosenzvit, Mara Cecilia

2015-02-06

microRNAs (miRNAs), a class of small non-coding RNAs, are key regulators of gene expression at post-transcriptional level and play essential roles in fundamental biological processes such as development and metabolism. The particular developmental and metabolic characteristics of cestode parasites highlight the importance of studying miRNA gene regulation in these organisms. Here, we perform a comprehensive analysis of miRNAs in the parasitic cestode Echinococcus canadensis G7, one of the causative agents of the neglected zoonotic disease cystic echinococcosis. Small RNA libraries from protoscoleces and cyst walls of E. canadensis G7 and protoscoleces of E. granulosus sensu stricto G1 were sequenced using Illumina technology. For miRNA prediction, miRDeep2 core algorithm was used. The output list of candidate precursors was manually curated to generate a high confidence set of miRNAs. Differential expression analysis of miRNAs between stages or species was estimated with DESeq. Expression levels of selected miRNAs were validated using poly-A RT-qPCR. In this study we used a high-throughput approach and found transcriptional evidence of 37 miRNAs thus expanding the miRNA repertoire of E. canadensis G7. Differential expression analysis showed highly regulated miRNAs between life cycle stages, suggesting a role in maintaining the features of each developmental stage or in the regulation of developmental timing. In this work we characterize conserved and novel Echinococcus miRNAs which represent 30 unique miRNA families. Here we confirmed the remarkable loss of conserved miRNA families in E. canadensis, reflecting their low morphological complexity and high adaptation to parasitism. We performed the first in-depth study profiling of small RNAs in the zoonotic parasite E. canadensis G7. We found that miRNAs are the preponderant small RNA silencing molecules, suggesting that these small RNAs could be an essential mechanism of gene regulation in this species. We also identified both parasite specific and divergent miRNAs which are potential biomarkers of infection. This study will provide valuable information for better understanding of the complex biology of this parasite and could help to find new potential targets for therapy and/or diagnosis.

Genome-wide identification of heat stress-responsive small RNAs in tall fescue (Festuca arundinacea) by high-throughput sequencing.

PubMed

Li, Huiying; Hu, Tao; Amombo, Erick; Fu, Jinmin

2017-06-01

MicroRNAs (miRNAs) play vital roles in the adaptive response of plants to various abiotic and biotic stresses. Tall fescue (Festuca arundinacea Schreb.) is a major cool-season forage and turf grass species which is severely influenced by heat stress. To unravel possible heat stress-responsive miRNAs, high-throughput sequencing was employed for heat-tolerant PI578718 and heat-sensitive PI234881 genotypes growing in presence and absence of heat stress (40°C for 36h). By searching against the miRBase database, among 1421 reference monocotyledon miRNAs, more than 850 were identified in all samples. Among these miRNAs, 1.46% and 2.29% were differentially expressed in PI234881 and PI578718 under heat stress, respectively, and most of them were down-regulated. In addition, a total of 170 novel miRNAs belonging to 145 miRNA families were identified. Furthermore, putative targets of differentially expressed miRNAs were predicted. The regulation of selected miRNAs by heat stress was revalidated through quantitative reverse transcription PCR (qRT-PCR) analysis. Most of these miRNAs shared similar expression patterns; however, some showed distinct expression patterns under heat stress, with their putative targets displaying different transcription levels. This is the first genome-wide miRNA identification in tall fescue. miRNAs specific to PI578718, or those that exhibited differential expression profiles between the two genotypes under high temperature, were probably associated with the variation in thermotolerance of tall fescue. The differentially expressed miRNAs between these two tall fescue genotypes and their putative targeted genes will provide essential information for further study on miRNAs mediating heat response and facilitate to improve turf grass breeding. Copyright © 2017. Published by Elsevier GmbH.

Robo-Lector - a novel platform for automated high-throughput cultivations in microtiter plates with high information content.

PubMed

Huber, Robert; Ritter, Daniel; Hering, Till; Hillmer, Anne-Kathrin; Kensy, Frank; Müller, Carsten; Wang, Le; Büchs, Jochen

2009-08-01

In industry and academic research, there is an increasing demand for flexible automated microfermentation platforms with advanced sensing technology. However, up to now, conventional platforms cannot generate continuous data in high-throughput cultivations, in particular for monitoring biomass and fluorescent proteins. Furthermore, microfermentation platforms are needed that can easily combine cost-effective, disposable microbioreactors with downstream processing and analytical assays. To meet this demand, a novel automated microfermentation platform consisting of a BioLector and a liquid-handling robot (Robo-Lector) was sucessfully built and tested. The BioLector provides a cultivation system that is able to permanently monitor microbial growth and the fluorescence of reporter proteins under defined conditions in microtiter plates. Three examplary methods were programed on the Robo-Lector platform to study in detail high-throughput cultivation processes and especially recombinant protein expression. The host/vector system E. coli BL21(DE3) pRhotHi-2-EcFbFP, expressing the fluorescence protein EcFbFP, was hereby investigated. With the method 'induction profiling' it was possible to conduct 96 different induction experiments (varying inducer concentrations from 0 to 1.5 mM IPTG at 8 different induction times) simultaneously in an automated way. The method 'biomass-specific induction' allowed to automatically induce cultures with different growth kinetics in a microtiter plate at the same biomass concentration, which resulted in a relative standard deviation of the EcFbFP production of only +/- 7%. The third method 'biomass-specific replication' enabled to generate equal initial biomass concentrations in main cultures from precultures with different growth kinetics. This was realized by automatically transferring an appropiate inoculum volume from the different preculture microtiter wells to respective wells of the main culture plate, where subsequently similar growth kinetics could be obtained. The Robo-Lector generates extensive kinetic data in high-throughput cultivations, particularly for biomass and fluorescence protein formation. Based on the non-invasive on-line-monitoring signals, actions of the liquid-handling robot can easily be triggered. This interaction between the robot and the BioLector (Robo-Lector) combines high-content data generation with systematic high-throughput experimentation in an automated fashion, offering new possibilities to study biological production systems. The presented platform uses a standard liquid-handling workstation with widespread automation possibilities. Thus, high-throughput cultivations can now be combined with small-scale downstream processing techniques and analytical assays. Ultimately, this novel versatile platform can accelerate and intensify research and development in the field of systems biology as well as modelling and bioprocess optimization.

NCBI GEO: archive for high-throughput functional genomic data.

PubMed

Barrett, Tanya; Troup, Dennis B; Wilhite, Stephen E; Ledoux, Pierre; Rudnev, Dmitry; Evangelista, Carlos; Kim, Irene F; Soboleva, Alexandra; Tomashevsky, Maxim; Marshall, Kimberly A; Phillippy, Katherine H; Sherman, Patti M; Muertter, Rolf N; Edgar, Ron

2009-01-01

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest public repository for high-throughput gene expression data. Additionally, GEO hosts other categories of high-throughput functional genomic data, including those that examine genome copy number variations, chromatin structure, methylation status and transcription factor binding. These data are generated by the research community using high-throughput technologies like microarrays and, more recently, next-generation sequencing. The database has a flexible infrastructure that can capture fully annotated raw and processed data, enabling compliance with major community-derived scientific reporting standards such as 'Minimum Information About a Microarray Experiment' (MIAME). In addition to serving as a centralized data storage hub, GEO offers many tools and features that allow users to effectively explore, analyze and download expression data from both gene-centric and experiment-centric perspectives. This article summarizes the GEO repository structure, content and operating procedures, as well as recently introduced data mining features. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.

Large-scale identification and comparative analysis of miRNA expression profile in the respiratory tree of the sea cucumber Apostichopus japonicus during aestivation.

PubMed

Chen, Muyan; Storey, Kenneth B

2014-02-01

The sea cucumber Apostichopus japonicus withstands high water temperatures in the summer by suppressing its metabolic rate and entering a state of aestivation. We hypothesized that changes in the expression of miRNAs could provide important post-transcriptional regulation of gene expression during hypometabolism via control over mRNA translation. The present study analyzed profiles of miRNA expression in the sea cucumber respiratory tree using Solexa deep sequencing technology. We identified 279 sea cucumber miRNAs, including 15 novel miRNAs specific to sea cucumber. Animals sampled during deep aestivation (DA; after at least 15 days of continuous torpor) were compared with animals from a non-aestivation (NA) state (animals that had passed through aestivation and returned to an active state). We identified 30 differentially expressed miRNAs ([RPM (reads per million) >10, |FC| (|fold change|)≥1, FDR (false discovery rate)<0.01]) during aestivation, which were validated by two other miRNA profiling methods: miRNA microarray and real-time PCR. Among the most prominent miRNA species, miR-124, miR-124-3p, miR-79, miR-9 and miR-2010 were significantly over-expressed during deep aestivation compared with non-aestivation animals, suggesting that these miRNAs may play important roles in metabolic rate suppression during aestivation. High-throughput sequencing data and microarray data have been submitted to the GEO database with accession number: 16902695. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparative expression profiling reveals gene functions in female meiosis and gametophyte development in Arabidopsis.

PubMed

Zhao, Lihua; He, Jiangman; Cai, Hanyang; Lin, Haiyan; Li, Yanqiang; Liu, Renyi; Yang, Zhenbiao; Qin, Yuan

2014-11-01

Megasporogenesis is essential for female fertility, and requires the accomplishment of meiosis and the formation of functional megaspores. The inaccessibility and low abundance of female meiocytes make it particularly difficult to elucidate the molecular basis underlying megasporogenesis. We used high-throughput tag-sequencing analysis to identify genes expressed in female meiocytes (FMs) by comparing gene expression profiles from wild-type ovules undergoing megasporogenesis with those from the spl mutant ovules, which lack megasporogenesis. A total of 862 genes were identified as FMs, with levels that are consistently reduced in spl ovules in two biological replicates. Fluorescence-assisted cell sorting followed by RNA-seq analysis of DMC1:GFP-labeled female meiocytes confirmed that 90% of the FMs are indeed detected in the female meiocyte protoplast profiling. We performed reverse genetic analysis of 120 candidate genes and identified four FM genes with a function in female meiosis progression in Arabidopsis. We further revealed that KLU, a putative cytochrome P450 monooxygenase, is involved in chromosome pairing during female meiosis, most likely by affecting the normal expression pattern of DMC1 in ovules during female meiosis. Our studies provide valuable information for functional genomic analyses of plant germline development as well as insights into meiosis. © 2014 The Authors The Plant Journal © 2014 John Wiley & Sons Ltd.

Recombinant Human Lysyl Oxidase-like 2 Secreted from Human Embryonic Kidney Cells Displays Complex and Acidic Glycans at All Three N-Linked Glycosylation Sites.

PubMed

Go, Eden P; Moon, Hee-Jung; Mure, Minae; Desaire, Heather

2018-05-04

Human lysyl oxidase-like 2 (hLOXL2), a glycoprotein implicated in tumor progression and organ fibrosis, is a molecular target for anticancer and antifibrosis treatment. This glycoprotein contains three predicted N-linked glycosylation sites; one is near the protein's active site, and at least one more is known to facilitate the protein's secretion. Because the glycosylation impacts the protein's biology, we sought to characterize the native, mammalian glycosylation profile and to determine how closely this profile is recapitulated when the protein is expressed in insect cells. All three glycosylation sites on the protein, expressed in human embryonic kidney (HEK) cells, were characterized individually using a mass spectrometry-based glycopeptide analysis workflow. These data were compared to the glycosylation profile of the same protein expressed in insect cells. We found that the producer cell type imparts a substantial influence on the glycosylation of this important protein. The more-relevant version, expressed in HEK cells, contains large, acidic glycoforms; these glycans are not generated in insect cells. The glycosylation differences likely have structural and functional consequences, and these data should be considered when generating protein for functional studies or for high-throughput screening campaigns.

DOSE RESPONSE FROM HIGH THROUGHPUT GENE EXPRESSION STUDIES AND THE INFLUENCE OF TIME AND CELL LINE ON INFERRED MODE OF ACTION BY ONTOLOGIC ENRICHMENT (SOT)

EPA Science Inventory

Gene expression with ontologic enrichment and connectivity mapping tools is widely used to infer modes of action (MOA) for therapeutic drugs. Despite progress in high-throughput (HT) genomic systems, strategies suitable to identify industrial chemical MOA are needed. The L1000 is...

The multidimensional perturbation value: a single metric to measure similarity and activity of treatments in high-throughput multidimensional screens.

PubMed

Hutz, Janna E; Nelson, Thomas; Wu, Hua; McAllister, Gregory; Moutsatsos, Ioannis; Jaeger, Savina A; Bandyopadhyay, Somnath; Nigsch, Florian; Cornett, Ben; Jenkins, Jeremy L; Selinger, Douglas W

2013-04-01

Screens using high-throughput, information-rich technologies such as microarrays, high-content screening (HCS), and next-generation sequencing (NGS) have become increasingly widespread. Compared with single-readout assays, these methods produce a more comprehensive picture of the effects of screened treatments. However, interpreting such multidimensional readouts is challenging. Univariate statistics such as t-tests and Z-factors cannot easily be applied to multidimensional profiles, leaving no obvious way to answer common screening questions such as "Is treatment X active in this assay?" and "Is treatment X different from (or equivalent to) treatment Y?" We have developed a simple, straightforward metric, the multidimensional perturbation value (mp-value), which can be used to answer these questions. Here, we demonstrate application of the mp-value to three data sets: a multiplexed gene expression screen of compounds and genomic reagents, a microarray-based gene expression screen of compounds, and an HCS compound screen. In all data sets, active treatments were successfully identified using the mp-value, and simulations and follow-up analyses supported the mp-value's statistical and biological validity. We believe the mp-value represents a promising way to simplify the analysis of multidimensional data while taking full advantage of its richness.

PROTEOMICS IN ECOTOXICOLOGY: PROTEIN EXPRESSION PROFILING TO SCREEN CHEMICALS FOR ENDOCRINE ACTIVITY

EPA Science Inventory

Abstract for poster.

Current endocrine testing methods are animal intensive and lack the throughput necessary to screen large numbers of environmental chemicals for adverse effects. In this study, Matrix Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry...

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding.

PubMed

Shahi, Payam; Kim, Samuel C; Haliburton, John R; Gartner, Zev J; Abate, Adam R

2017-03-14

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing.

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding

NASA Astrophysics Data System (ADS)

Shahi, Payam; Kim, Samuel C.; Haliburton, John R.; Gartner, Zev J.; Abate, Adam R.

2017-03-01

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing.

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding

PubMed Central

Shahi, Payam; Kim, Samuel C.; Haliburton, John R.; Gartner, Zev J.; Abate, Adam R.

2017-01-01

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing. PMID:28290550

Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis

PubMed Central

Grassi, Elena; Damasco, Christian; Silengo, Lorenzo; Oti, Martin; Provero, Paolo; Di Cunto, Ferdinando

2008-01-01

Background Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates. Methodology/Principal Findings We show that it is possible to reliably identify disease-relevant relationships among genes from massive microarray datasets by concentrating only on genes sharing similar expression profiles in both human and mouse. Moreover, we show systematically that the integration of human-mouse conserved coexpression with a phenotype similarity map allows the efficient identification of disease genes in large genomic regions. Finally, using this approach on 850 OMIM loci characterized by an unknown molecular basis, we propose high-probability candidates for 81 genetic diseases. Conclusion Our results demonstrate that conserved coexpression, even at the human-mouse phylogenetic distance, represents a very strong criterion to predict disease-relevant relationships among human genes. PMID:18369433

High Throughput PBTK: Evaluating EPA’s Open-Source Data and Tools for Dosimetry and Exposure Reconstruction

EPA Science Inventory

Thousands of chemicals have been profiled by high-throughput screening (HTS) programs such as ToxCast and Tox21; these chemicals are tested in part because most of them have limited or no data on hazard, exposure, or toxicokinetics (TK). While HTS generates in vitro bioactivity d...

High Throughput Prioritization for Integrated Toxicity Testing Based on ToxCast Chemical Profiling

EPA Science Inventory

The rational prioritization of chemicals for integrated toxicity testing is a central goal of the U.S. EPA’s ToxCast™ program (http://epa.gov/ncct/toxcast/). ToxCast includes a wide-ranging battery of over 500 in vitro high-throughput screening assays which in Phase I was used to...

Evaluation of High-throughput Genotoxicity Assays Used in Profiling the US EPA ToxCast Chemicals

EPA Science Inventory

Three high-throughput screening (HTS) genotoxicity assays-GreenScreen HC GADD45a-GFP (Gentronix Ltd.), CellCiphr p53 (Cellumen Inc.) and CellSensor p53RE-bla (Invitrogen Corp.)-were used to analyze the collection of 320 predominantly pesticide active compounds being tested in Pha...

Defining the Human Macula Transcriptome and Candidate Retinal Disease Genes UsingEyeSAGE

PubMed Central

Rickman, Catherine Bowes; Ebright, Jessica N.; Zavodni, Zachary J.; Yu, Ling; Wang, Tianyuan; Daiger, Stephen P.; Wistow, Graeme; Boon, Kathy; Hauser, Michael A.

2009-01-01

Purpose To develop large-scale, high-throughput annotation of the human macula transcriptome and to identify and prioritize candidate genes for inherited retinal dystrophies, based on ocular-expression profiles using serial analysis of gene expression (SAGE). Methods Two human retina and two retinal pigment epithelium (RPE)/choroid SAGE libraries made from matched macula or midperipheral retina and adjacent RPE/choroid of morphologically normal 28- to 66-year-old donors and a human central retina longSAGE library made from 41- to 66-year-old donors were generated. Their transcription profiles were entered into a relational database, EyeSAGE, including microarray expression profiles of retina and publicly available normal human tissue SAGE libraries. EyeSAGE was used to identify retina- and RPE-specific and -associated genes, and candidate genes for retina and RPE disease loci. Differential and/or cell-type specific expression was validated by quantitative and single-cell RT-PCR. Results Cone photoreceptor-associated gene expression was elevated in the macula transcription profiles. Analysis of the longSAGE retina tags enhanced tag-to-gene mapping and revealed alternatively spliced genes. Analysis of candidate gene expression tables for the identified Bardet-Biedl syndrome disease gene (BBS5) in the BBS5 disease region table yielded BBS5 as the top candidate. Compelling candidates for inherited retina diseases were identified. Conclusions The EyeSAGE database, combining three different gene-profiling platforms including the authors’ multidonor-derived retina/RPE SAGE libraries and existing single-donor retina/RPE libraries, is a powerful resource for definition of the retina and RPE transcriptomes. It can be used to identify retina-specific genes, including alternatively spliced transcripts and to prioritize candidate genes within mapped retinal disease regions. PMID:16723438

Defining the human macula transcriptome and candidate retinal disease genes using EyeSAGE.

PubMed

Bowes Rickman, Catherine; Ebright, Jessica N; Zavodni, Zachary J; Yu, Ling; Wang, Tianyuan; Daiger, Stephen P; Wistow, Graeme; Boon, Kathy; Hauser, Michael A

2006-06-01

To develop large-scale, high-throughput annotation of the human macula transcriptome and to identify and prioritize candidate genes for inherited retinal dystrophies, based on ocular-expression profiles using serial analysis of gene expression (SAGE). Two human retina and two retinal pigment epithelium (RPE)/choroid SAGE libraries made from matched macula or midperipheral retina and adjacent RPE/choroid of morphologically normal 28- to 66-year-old donors and a human central retina longSAGE library made from 41- to 66-year-old donors were generated. Their transcription profiles were entered into a relational database, EyeSAGE, including microarray expression profiles of retina and publicly available normal human tissue SAGE libraries. EyeSAGE was used to identify retina- and RPE-specific and -associated genes, and candidate genes for retina and RPE disease loci. Differential and/or cell-type specific expression was validated by quantitative and single-cell RT-PCR. Cone photoreceptor-associated gene expression was elevated in the macula transcription profiles. Analysis of the longSAGE retina tags enhanced tag-to-gene mapping and revealed alternatively spliced genes. Analysis of candidate gene expression tables for the identified Bardet-Biedl syndrome disease gene (BBS5) in the BBS5 disease region table yielded BBS5 as the top candidate. Compelling candidates for inherited retina diseases were identified. The EyeSAGE database, combining three different gene-profiling platforms including the authors' multidonor-derived retina/RPE SAGE libraries and existing single-donor retina/RPE libraries, is a powerful resource for definition of the retina and RPE transcriptomes. It can be used to identify retina-specific genes, including alternatively spliced transcripts and to prioritize candidate genes within mapped retinal disease regions.

Correlation analysis of the mRNA and miRNA expression profiles in the nascent synthetic allotetraploid Raphanobrassica

PubMed Central

Ye, Bingyuan; Wang, Ruihua; Wang, Jianbo

2016-01-01

Raphanobrassica is an allopolyploid species derived from inter-generic hybridization that combines the R genome from R. sativus and the C genome from B. oleracea var. alboglabra. In the present study, we used a high-throughput sequencing method to identify the mRNA and miRNA profiles in Raphanobrassica and its parents. A total of 33,561 mRNAs and 283 miRNAs were detected, 9,209 mRNAs and 134 miRNAs were differentially expressed respectively, 7,633 mRNAs and 39 miRNAs showed ELD expression, 5,219 mRNAs and 57 miRNAs were non-additively expressed in Raphanobrassica. Remarkably, differentially expressed genes (DEGs) were up-regulated and maternal bias was detected in Raphanobrassica. In addition, a miRNA-mRNA interaction network was constructed based on reverse regulated miRNA-mRNAs, which included 75 miRNAs and 178 mRNAs, 31 miRNAs were non-additively expressed target by 13 miRNAs. The related target genes were significantly enriched in the GO term ‘metabolic processes’. Non-additive related target genes regulation is involved in a range of biological pathways, like providing a driving force for variation and adaption in this allopolyploid. The integrative analysis of mRNA and miRNA profiling provides more information to elucidate gene expression mechanism and may supply a comprehensive and corresponding method to study genetic and transcription variation of allopolyploid. PMID:27874043

High-Throughput Sequencing of RNA Silencing-Associated Small RNAs in Olive (Olea europaea L.)

PubMed Central

Donaire, Livia; Pedrola, Laia; de la Rosa, Raúl; Llave, César

2011-01-01

Small RNAs (sRNAs) of 20 to 25 nucleotides (nt) in length maintain genome integrity and control gene expression in a multitude of developmental and physiological processes. Despite RNA silencing has been primarily studied in model plants, the advent of high-throughput sequencing technologies has enabled profiling of the sRNA component of more than 40 plant species. Here, we used deep sequencing and molecular methods to report the first inventory of sRNAs in olive (Olea europaea L.). sRNA libraries prepared from juvenile and adult shoots revealed that the 24-nt class dominates the sRNA transcriptome and atypically accumulates to levels never seen in other plant species, suggesting an active role of heterochromatin silencing in the maintenance and integrity of its large genome. A total of 18 known miRNA families were identified in the libraries. Also, 5 other sRNAs derived from potential hairpin-like precursors remain as plausible miRNA candidates. RNA blots confirmed miRNA expression and suggested tissue- and/or developmental-specific expression patterns. Target mRNAs of conserved miRNAs were computationally predicted among the olive cDNA collection and experimentally validated through endonucleolytic cleavage assays. Finally, we use expression data to uncover genetic components of the miR156, miR172 and miR390/TAS3-derived trans-acting small interfering RNA (tasiRNA) regulatory nodes, suggesting that these interactive networks controlling developmental transitions are fully operational in olive. PMID:22140484

Fractal-like Distributions over the Rational Numbers in High-throughput Biological and Clinical Data

NASA Astrophysics Data System (ADS)

Trifonov, Vladimir; Pasqualucci, Laura; Dalla-Favera, Riccardo; Rabadan, Raul

2011-12-01

Recent developments in extracting and processing biological and clinical data are allowing quantitative approaches to studying living systems. High-throughput sequencing (HTS), expression profiles, proteomics, and electronic health records (EHR) are some examples of such technologies. Extracting meaningful information from those technologies requires careful analysis of the large volumes of data they produce. In this note, we present a set of fractal-like distributions that commonly appear in the analysis of such data. The first set of examples are drawn from a HTS experiment. Here, the distributions appear as part of the evaluation of the error rate of the sequencing and the identification of tumorogenic genomic alterations. The other examples are obtained from risk factor evaluation and analysis of relative disease prevalence and co-mordbidity as these appear in EHR. The distributions are also relevant to identification of subclonal populations in tumors and the study of quasi-species and intrahost diversity of viral populations.

Machine learning in computational biology to accelerate high-throughput protein expression.

PubMed

Sastry, Anand; Monk, Jonathan; Tegel, Hanna; Uhlen, Mathias; Palsson, Bernhard O; Rockberg, Johan; Brunk, Elizabeth

2017-08-15

The Human Protein Atlas (HPA) enables the simultaneous characterization of thousands of proteins across various tissues to pinpoint their spatial location in the human body. This has been achieved through transcriptomics and high-throughput immunohistochemistry-based approaches, where over 40 000 unique human protein fragments have been expressed in E. coli. These datasets enable quantitative tracking of entire cellular proteomes and present new avenues for understanding molecular-level properties influencing expression and solubility. Combining computational biology and machine learning identifies protein properties that hinder the HPA high-throughput antibody production pipeline. We predict protein expression and solubility with accuracies of 70% and 80%, respectively, based on a subset of key properties (aromaticity, hydropathy and isoelectric point). We guide the selection of protein fragments based on these characteristics to optimize high-throughput experimentation. We present the machine learning workflow as a series of IPython notebooks hosted on GitHub (https://github.com/SBRG/Protein_ML). The workflow can be used as a template for analysis of further expression and solubility datasets. ebrunk@ucsd.edu or johanr@biotech.kth.se. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Profiling of drought-responsive microRNA and mRNA in tomato using high-throughput sequencing.

PubMed

Liu, Minmin; Yu, Huiyang; Zhao, Gangjun; Huang, Qiufeng; Lu, Yongen; Ouyang, Bo

2017-06-26

Abiotic stresses cause severe loss of crop production. Among them, drought is one of the most frequent environmental stresses, which limits crop growth, development and productivity. Plant drought tolerance is fine-tuned by a complex gene regulatory network. Understanding the molecular regulation of this polygenic trait is crucial for the eventual success to improve plant yield and quality. Recent studies have demonstrated that microRNAs play critical roles in plant drought tolerance. However, little is known about the microRNA in drought response of the model plant tomato. Here, we described the profiling of drought-responsive microRNA and mRNA in tomato using high-throughput next-generation sequencing. Drought stress was applied on the seedlings of M82, a drought-sensitive cultivated tomato genotype, and IL9-1, a drought-tolerant introgression line derived from the stress-resistant wild species Solanum pennellii LA0716 and M82. Under drought, IL9-1 performed superior than M82 regarding survival rate, H 2 O 2 elimination and leaf turgor maintenance. A total of four small RNA and eight mRNA libraries were constructed and sequenced using Illumina sequencing technology. 105 conserved and 179 novel microRNAs were identified, among them, 54 and 98 were differentially expressed upon drought stress, respectively. The majority of the differentially-expressed conserved microRNAs was up-regulated in IL9-1 whereas down-regulated in M82. Under drought stress, 2714 and 1161 genes were found to be differentially expressed in M82 and IL9-1, respectively, and many of their homologues are involved in plant stress, such as genes encoding transcription factor and protein kinase. Various pathways involved in abiotic stress were revealed by Gene Ontology and pathway analysis. The mRNA sequencing results indicated that most of the target genes were regulated by their corresponding microRNAs, which suggested that microRNAs may play essential roles in the drought tolerance of tomato. In this study, numerous microRNAs and mRNAs involved in the drought response of tomato were identified using high-throughput sequencing, which will provide new insights into the complex regulatory network of plant adaption to drought stress. This work will also help to exploit new players functioning in plant drought-stress tolerance.

Identification of Reference Genes for RT-qPCR Data Normalization in Cannabis sativa Stem Tissues.

PubMed

Mangeot-Peter, Lauralie; Legay, Sylvain; Hausman, Jean-Francois; Esposito, Sergio; Guerriero, Gea

2016-09-15

Gene expression profiling via quantitative real-time PCR is a robust technique widely used in the life sciences to compare gene expression patterns in, e.g., different tissues, growth conditions, or after specific treatments. In the field of plant science, real-time PCR is the gold standard to study the dynamics of gene expression and is used to validate the results generated with high throughput techniques, e.g., RNA-Seq. An accurate relative quantification of gene expression relies on the identification of appropriate reference genes, that need to be determined for each experimental set-up used and plant tissue studied. Here, we identify suitable reference genes for expression profiling in stems of textile hemp (Cannabis sativa L.), whose tissues (isolated bast fibres and core) are characterized by remarkable differences in cell wall composition. We additionally validate the reference genes by analysing the expression of putative candidates involved in the non-oxidative phase of the pentose phosphate pathway and in the first step of the shikimate pathway. The goal is to describe the possible regulation pattern of some genes involved in the provision of the precursors needed for lignin biosynthesis in the different hemp stem tissues. The results here shown are useful to design future studies focused on gene expression analyses in hemp.

Massively parallel nanowell-based single-cell gene expression profiling.

PubMed

Goldstein, Leonard D; Chen, Ying-Jiun Jasmine; Dunne, Jude; Mir, Alain; Hubschle, Hermann; Guillory, Joseph; Yuan, Wenlin; Zhang, Jingli; Stinson, Jeremy; Jaiswal, Bijay; Pahuja, Kanika Bajaj; Mann, Ishminder; Schaal, Thomas; Chan, Leo; Anandakrishnan, Sangeetha; Lin, Chun-Wah; Espinoza, Patricio; Husain, Syed; Shapiro, Harris; Swaminathan, Karthikeyan; Wei, Sherry; Srinivasan, Maithreyan; Seshagiri, Somasekar; Modrusan, Zora

2017-07-07

Technological advances have enabled transcriptome characterization of cell types at the single-cell level providing new biological insights. New methods that enable simple yet high-throughput single-cell expression profiling are highly desirable. Here we report a novel nanowell-based single-cell RNA sequencing system, ICELL8, which enables processing of thousands of cells per sample. The system employs a 5,184-nanowell-containing microchip to capture ~1,300 single cells and process them. Each nanowell contains preprinted oligonucleotides encoding poly-d(T), a unique well barcode, and a unique molecular identifier. The ICELL8 system uses imaging software to identify nanowells containing viable single cells and only wells with single cells are processed into sequencing libraries. Here, we report the performance and utility of ICELL8 using samples of increasing complexity from cultured cells to mouse solid tissue samples. Our assessment of the system to discriminate between mixed human and mouse cells showed that ICELL8 has a low cell multiplet rate (< 3%) and low cross-cell contamination. We characterized single-cell transcriptomes of more than a thousand cultured human and mouse cells as well as 468 mouse pancreatic islets cells. We were able to identify distinct cell types in pancreatic islets, including alpha, beta, delta and gamma cells. Overall, ICELL8 provides efficient and cost-effective single-cell expression profiling of thousands of cells, allowing researchers to decipher single-cell transcriptomes within complex biological samples.

A translatable predictor of human radiation exposure.

PubMed

Lucas, Joseph; Dressman, Holly K; Suchindran, Sunil; Nakamura, Mai; Chao, Nelson J; Himburg, Heather; Minor, Kerry; Phillips, Gary; Ross, Joel; Abedi, Majid; Terbrueggen, Robert; Chute, John P

2014-01-01

Terrorism using radiological dirty bombs or improvised nuclear devices is recognized as a major threat to both public health and national security. In the event of a radiological or nuclear disaster, rapid and accurate biodosimetry of thousands of potentially affected individuals will be essential for effective medical management to occur. Currently, health care providers lack an accurate, high-throughput biodosimetric assay which is suitable for the triage of large numbers of radiation injury victims. Here, we describe the development of a biodosimetric assay based on the analysis of irradiated mice, ex vivo-irradiated human peripheral blood (PB) and humans treated with total body irradiation (TBI). Interestingly, a gene expression profile developed via analysis of murine PB radiation response alone was inaccurate in predicting human radiation injury. In contrast, generation of a gene expression profile which incorporated data from ex vivo irradiated human PB and human TBI patients yielded an 18-gene radiation classifier which was highly accurate at predicting human radiation status and discriminating medically relevant radiation dose levels in human samples. Although the patient population was relatively small, the accuracy of this classifier in discriminating radiation dose levels in human TBI patients was not substantially confounded by gender, diagnosis or prior exposure to chemotherapy. We have further incorporated genes from this human radiation signature into a rapid and high-throughput chemical ligation-dependent probe amplification assay (CLPA) which was able to discriminate radiation dose levels in a pilot study of ex vivo irradiated human blood and samples from human TBI patients. Our results illustrate the potential for translation of a human genetic signature for the diagnosis of human radiation exposure and suggest the basis for further testing of CLPA as a candidate biodosimetric assay.

Combined Effect of Random Transmit Power Control and Inter-Path Interference Cancellation on DS-CDMA Packet Mobile Communications

NASA Astrophysics Data System (ADS)

Kudoh, Eisuke; Ito, Haruki; Wang, Zhisen; Adachi, Fumiyuki

In mobile communication systems, high speed packet data services are demanded. In the high speed data transmission, throughput degrades severely due to severe inter-path interference (IPI). Recently, we proposed a random transmit power control (TPC) to increase the uplink throughput of DS-CDMA packet mobile communications. In this paper, we apply IPI cancellation in addition to the random TPC. We derive the numerical expression of the received signal-to-interference plus noise power ratio (SINR) and introduce IPI cancellation factor. We also derive the numerical expression of system throughput when IPI is cancelled ideally to compare with the Monte Carlo numerically evaluated system throughput. Then we evaluate, by Monte-Carlo numerical computation method, the combined effect of random TPC and IPI cancellation on the uplink throughput of DS-CDMA packet mobile communications.

Transcriptome Profile Reveals that Pu-Erh Tea Represses the Expression of Vitellogenin Family to Reduce Fat Accumulation in Caenorhabditis elegans.

PubMed

Xiao, Ru-Yue; Hao, Junjun; Ding, Yi-Hong; Che, Yan-Yun; Zou, Xiao-Ju; Liang, Bin

2016-10-17

Due to misbalanced energy surplus and expenditure, obesity has become a common chronic disorder that is highly associated with many metabolic diseases. Pu-erh tea, a traditional Chinese beverage, has been believed to have numerous health benefits, such as anti-obesity. However, the underlying mechanisms of its anti-obesity effect are yet to be understood. Here, we take the advantages of transcriptional profile by RNA sequencing (RNA-Seq) to view the global gene expression of Pu-erh tea. The model organism Caenorhabditis elegans was treated with different concentrations of Pu-erh tea water extract (PTE, 0 g/mL, 0.025 g/mL, and 0.05 g/mL). Compared with the control, PTE indeed decreases lipid droplets size and fat accumulation. The high-throughput RNA-Sequence technique detected 18073 and 18105 genes expressed in 0.025 g/mL and 0.05 g/mL PTE treated groups, respectively. Interestingly, the expression of the vitellogenin family ( vit-1 , vit-2 , vit-3, vit-4 and vit-5 ) was significantly decreased by PTE, which was validated by qPCR analysis. Furthermore, vit-1(ok2616) , vit-3(ok2348) and vit-5(ok3239) mutants are insensitive to PTE triggered fat reduction. In conclusion, our transcriptional profile by RNA-Sequence suggests that Pu-erh tea lowers the fat accumulation primarily through repression of the expression of vit (vitellogenin) family, in addition to our previously reported (sterol regulatory element binding protein) SREBP-SCD (stearoyl-CoA desaturase) axis.

High-Throughput Screening Using a Whole-Cell Virus Replication Reporter Gene Assay to Identify Inhibitory Compounds against Rift Valley Fever Virus Infection.

PubMed

Islam, Md Koushikul; Baudin, Maria; Eriksson, Jonas; Öberg, Christopher; Habjan, Matthias; Weber, Friedemann; Överby, Anna K; Ahlm, Clas; Evander, Magnus

2016-04-01

Rift Valley fever virus (RVFV) is an emerging virus that causes serious illness in humans and livestock. There are no approved vaccines or treatments for humans. The purpose of the study was to identify inhibitory compounds of RVFV infection without any preconceived idea of the mechanism of action. A whole-cell-based high-throughput drug screening assay was developed to screen 28,437 small chemical compounds targeting RVFV infection. To accomplish both speed and robustness, a replication-competent NSs-deleted RVFV expressing a fluorescent reporter gene was developed. Inhibition of fluorescence intensity was quantified by spectrophotometry and related to virus infection in human lung epithelial cells (A549). Cell toxicity was assessed by the Resazurin cell viability assay. After primary screening, 641 compounds were identified that inhibited RVFV infection by ≥80%, with ≥50% cell viability at 50 µM concentration. These compounds were subjected to a second screening regarding dose-response profiles, and 63 compounds with ≥60% inhibition of RVFV infection at 3.12 µM compound concentration and ≥50% cell viability at 25 µM were considered hits. Of these, six compounds with high inhibitory activity were identified. In conclusion, the high-throughput assay could efficiently and safely identify several promising compounds that inhibited RVFV infection. © 2016 Society for Laboratory Automation and Screening.

A Systematic Approach to Time-series Metabolite Profiling and RNA-seq Analysis of Chinese Hamster Ovary Cell Culture.

PubMed

Hsu, Han-Hsiu; Araki, Michihiro; Mochizuki, Masao; Hori, Yoshimi; Murata, Masahiro; Kahar, Prihardi; Yoshida, Takanobu; Hasunuma, Tomohisa; Kondo, Akihiko

2017-03-02

Chinese hamster ovary (CHO) cells are the primary host used for biopharmaceutical protein production. The engineering of CHO cells to produce higher amounts of biopharmaceuticals has been highly dependent on empirical approaches, but recent high-throughput "omics" methods are changing the situation in a rational manner. Omics data analyses using gene expression or metabolite profiling make it possible to identify key genes and metabolites in antibody production. Systematic omics approaches using different types of time-series data are expected to further enhance understanding of cellular behaviours and molecular networks for rational design of CHO cells. This study developed a systematic method for obtaining and analysing time-dependent intracellular and extracellular metabolite profiles, RNA-seq data (enzymatic mRNA levels) and cell counts from CHO cell cultures to capture an overall view of the CHO central metabolic pathway (CMP). We then calculated correlation coefficients among all the profiles and visualised the whole CMP by heatmap analysis and metabolic pathway mapping, to classify genes and metabolites together. This approach provides an efficient platform to identify key genes and metabolites in CHO cell culture.

Use of Threshold of Toxicological Concern (TTC) with High Throughput Exposure Predictions as a Risk-Based Screening Approach of Several Thousand Commodity Chemicals (SOT Poster)

EPA Science Inventory

Although progress has been made with HTS (high throughput screening) in profiling biological activity (e.g., EPA’s ToxCast™), challenges arise interpreting HTS results in the context of adversity & converting HTS assay concentrations to equivalent human doses for the broad domain...

Searching for microbial protein over-expression in a complex matrix using automated high throughput MS-based proteomics tools.

PubMed

Akeroyd, Michiel; Olsthoorn, Maurien; Gerritsma, Jort; Gutker-Vermaas, Diana; Ekkelkamp, Laurens; van Rij, Tjeerd; Klaassen, Paul; Plugge, Wim; Smit, Ed; Strupat, Kerstin; Wenzel, Thibaut; van Tilborg, Marcel; van der Hoeven, Rob

2013-03-10

In the discovery of new enzymes genomic and cDNA expression libraries containing thousands of differential clones are generated to obtain biodiversity. These libraries need to be screened for the activity of interest. Removing so-called empty and redundant clones significantly reduces the size of these expression libraries and therefore speeds up new enzyme discovery. Here, we present a sensitive, generic workflow for high throughput screening of successful microbial protein over-expression in microtiter plates containing a complex matrix based on mass spectrometry techniques. MALDI-LTQ-Orbitrap screening followed by principal component analysis and peptide mass fingerprinting was developed to obtain a throughput of ∼12,000 samples per week. Alternatively, a UHPLC-MS(2) approach including MS(2) protein identification was developed for microorganisms with a complex protein secretome with a throughput of ∼2000 samples per week. TCA-induced protein precipitation enhanced by addition of bovine serum albumin is used for protein purification prior to MS detection. We show that this generic workflow can effectively reduce large expression libraries from fungi and bacteria to their minimal size by detection of successful protein over-expression using MS. Copyright © 2012 Elsevier B.V. All rights reserved.

Global Profiling of Reactive Oxygen and Nitrogen Species in Biological Systems

PubMed Central

Zielonka, Jacek; Zielonka, Monika; Sikora, Adam; Adamus, Jan; Joseph, Joy; Hardy, Micael; Ouari, Olivier; Dranka, Brian P.; Kalyanaraman, Balaraman

2012-01-01

Herein we describe a high-throughput fluorescence and HPLC-based methodology for global profiling of reactive oxygen and nitrogen species (ROS/RNS) in biological systems. The combined use of HPLC and fluorescence detection is key to successful implementation and validation of this methodology. Included here are methods to specifically detect and quantitate the products formed from interaction between the ROS/RNS species and the fluorogenic probes, as follows: superoxide using hydroethidine, peroxynitrite using boronate-based probes, nitric oxide-derived nitrosating species with 4,5-diaminofluorescein, and hydrogen peroxide and other oxidants using 10-acetyl-3,7-dihydroxyphenoxazine (Amplex® Red) with and without horseradish peroxidase, respectively. In this study, we demonstrate real-time monitoring of ROS/RNS in activated macrophages using high-throughput fluorescence and HPLC methods. This global profiling approach, simultaneous detection of multiple ROS/RNS products of fluorescent probes, developed in this study will be useful in unraveling the complex role of ROS/RNS in redox regulation, cell signaling, and cellular oxidative processes and in high-throughput screening of anti-inflammatory antioxidants. PMID:22139901

Lateral Temperature-Gradient Method for High-Throughput Characterization of Material Processing by Millisecond Laser Annealing.

PubMed

Bell, Robert T; Jacobs, Alan G; Sorg, Victoria C; Jung, Byungki; Hill, Megan O; Treml, Benjamin E; Thompson, Michael O

2016-09-12

A high-throughput method for characterizing the temperature dependence of material properties following microsecond to millisecond thermal annealing, exploiting the temperature gradients created by a lateral gradient laser spike anneal (lgLSA), is presented. Laser scans generate spatial thermal gradients of up to 5 °C/μm with peak temperatures ranging from ambient to in excess of 1400 °C, limited only by laser power and materials thermal limits. Discrete spatial property measurements across the temperature gradient are then equivalent to independent measurements after varying temperature anneals. Accurate temperature calibrations, essential to quantitative analysis, are critical and methods for both peak temperature and spatial/temporal temperature profile characterization are presented. These include absolute temperature calibrations based on melting and thermal decomposition, and time-resolved profiles measured using platinum thermistors. A variety of spatially resolved measurement probes, ranging from point-like continuous profiling to large area sampling, are discussed. Examples from annealing of III-V semiconductors, CdSe quantum dots, low-κ dielectrics, and block copolymers are included to demonstrate the flexibility, high throughput, and precision of this technique.

Comprehensive analysis of the T-cell receptor beta chain gene in rhesus monkey by high throughput sequencing

PubMed Central

Li, Zhoufang; Liu, Guangjie; Tong, Yin; Zhang, Meng; Xu, Ying; Qin, Li; Wang, Zhanhui; Chen, Xiaoping; He, Jiankui

2015-01-01

Profiling immune repertoires by high throughput sequencing enhances our understanding of immune system complexity and immune-related diseases in humans. Previously, cloning and Sanger sequencing identified limited numbers of T cell receptor (TCR) nucleotide sequences in rhesus monkeys, thus their full immune repertoire is unknown. We applied multiplex PCR and Illumina high throughput sequencing to study the TCRβ of rhesus monkeys. We identified 1.26 million TCRβ sequences corresponding to 643,570 unique TCRβ sequences and 270,557 unique complementarity-determining region 3 (CDR3) gene sequences. Precise measurements of CDR3 length distribution, CDR3 amino acid distribution, length distribution of N nucleotide of junctional region, and TCRV and TCRJ gene usage preferences were performed. A comprehensive profile of rhesus monkey immune repertoire might aid human infectious disease studies using rhesus monkeys. PMID:25961410

Strategies to explore functional genomics data sets in NCBI's GEO database.

PubMed

Wilhite, Stephen E; Barrett, Tanya

2012-01-01

The Gene Expression Omnibus (GEO) database is a major repository that stores high-throughput functional genomics data sets that are generated using both microarray-based and sequence-based technologies. Data sets are submitted to GEO primarily by researchers who are publishing their results in journals that require original data to be made freely available for review and analysis. In addition to serving as a public archive for these data, GEO has a suite of tools that allow users to identify, analyze, and visualize data relevant to their specific interests. These tools include sample comparison applications, gene expression profile charts, data set clusters, genome browser tracks, and a powerful search engine that enables users to construct complex queries.

Strategies to Explore Functional Genomics Data Sets in NCBI’s GEO Database

PubMed Central

Wilhite, Stephen E.; Barrett, Tanya

2012-01-01

The Gene Expression Omnibus (GEO) database is a major repository that stores high-throughput functional genomics data sets that are generated using both microarray-based and sequence-based technologies. Data sets are submitted to GEO primarily by researchers who are publishing their results in journals that require original data to be made freely available for review and analysis. In addition to serving as a public archive for these data, GEO has a suite of tools that allow users to identify, analyze and visualize data relevant to their specific interests. These tools include sample comparison applications, gene expression profile charts, data set clusters, genome browser tracks, and a powerful search engine that enables users to construct complex queries. PMID:22130872

The Human Cell Atlas.

PubMed

Regev, Aviv; Teichmann, Sarah A; Lander, Eric S; Amit, Ido; Benoist, Christophe; Birney, Ewan; Bodenmiller, Bernd; Campbell, Peter; Carninci, Piero; Clatworthy, Menna; Clevers, Hans; Deplancke, Bart; Dunham, Ian; Eberwine, James; Eils, Roland; Enard, Wolfgang; Farmer, Andrew; Fugger, Lars; Göttgens, Berthold; Hacohen, Nir; Haniffa, Muzlifah; Hemberg, Martin; Kim, Seung; Klenerman, Paul; Kriegstein, Arnold; Lein, Ed; Linnarsson, Sten; Lundberg, Emma; Lundeberg, Joakim; Majumder, Partha; Marioni, John C; Merad, Miriam; Mhlanga, Musa; Nawijn, Martijn; Netea, Mihai; Nolan, Garry; Pe'er, Dana; Phillipakis, Anthony; Ponting, Chris P; Quake, Stephen; Reik, Wolf; Rozenblatt-Rosen, Orit; Sanes, Joshua; Satija, Rahul; Schumacher, Ton N; Shalek, Alex; Shapiro, Ehud; Sharma, Padmanee; Shin, Jay W; Stegle, Oliver; Stratton, Michael; Stubbington, Michael J T; Theis, Fabian J; Uhlen, Matthias; van Oudenaarden, Alexander; Wagner, Allon; Watt, Fiona; Weissman, Jonathan; Wold, Barbara; Xavier, Ramnik; Yosef, Nir

2017-12-05

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

Transcriptomic and phenotypic profiling in developing zebrafish exposed to thyroid hormone receptor agonists

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

Haggard, Derik E.; Noyes, Pamela D.; Waters, Katrina M.

There is a need to develop novel, high-throughput screening and prioritization methods to identify chemicals with adverse estrogen, androgen, and thyroid activity to protect human health and the environment and is of interest to the Endocrine Disruptor Screening Program. The current aim is to explore the utility of zebrafish as a testing paradigm to classify endocrine activity using phenotypically anchored transcriptome profiling. Transcriptome analysis was conducted on embryos exposed to 25 estrogen-, androgen-, or thyroid-active chemicals at a concentration that elicited adverse malformations or mortality at 120 hours post-fertilization in 80% of the animals exposed. Analysis of the top 1000more » significant differentially expressed transcripts across all treatments identified a unique transcriptional and phenotypic profile for thyroid hormone receptor agonists, which can be used as a biomarker screen for potential thyroid hormone agonists.« less

The Human Cell Atlas

PubMed Central

Amit, Ido; Benoist, Christophe; Birney, Ewan; Bodenmiller, Bernd; Campbell, Peter; Carninci, Piero; Clatworthy, Menna; Clevers, Hans; Deplancke, Bart; Dunham, Ian; Eberwine, James; Eils, Roland; Enard, Wolfgang; Farmer, Andrew; Fugger, Lars; Göttgens, Berthold; Hacohen, Nir; Haniffa, Muzlifah; Hemberg, Martin; Kim, Seung; Klenerman, Paul; Kriegstein, Arnold; Lein, Ed; Linnarsson, Sten; Lundberg, Emma; Lundeberg, Joakim; Majumder, Partha; Marioni, John C; Merad, Miriam; Mhlanga, Musa; Nawijn, Martijn; Netea, Mihai; Nolan, Garry; Pe'er, Dana; Phillipakis, Anthony; Ponting, Chris P; Quake, Stephen; Reik, Wolf; Rozenblatt-Rosen, Orit; Sanes, Joshua; Satija, Rahul; Schumacher, Ton N; Shalek, Alex; Shapiro, Ehud; Sharma, Padmanee; Shin, Jay W; Stegle, Oliver; Stratton, Michael; Stubbington, Michael J T; Theis, Fabian J; Uhlen, Matthias; van Oudenaarden, Alexander; Wagner, Allon; Watt, Fiona; Weissman, Jonathan; Wold, Barbara; Xavier, Ramnik; Yosef, Nir

2017-01-01

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community. PMID:29206104

The development of retrosynthetic glycan libraries to profile and classify the human serum N-linked glycome.

PubMed

Kronewitter, Scott R; An, Hyun Joo; de Leoz, Maria Lorna; Lebrilla, Carlito B; Miyamoto, Suzanne; Leiserowitz, Gary S

2009-06-01

Annotation of the human serum N-linked glycome is a formidable challenge but is necessary for disease marker discovery. A new theoretical glycan library was constructed and proposed to provide all possible glycan compositions in serum. It was developed based on established glycobiology and retrosynthetic state-transition networks. We find that at least 331 compositions are possible in the serum N-linked glycome. By pairing the theoretical glycan mass library with a high mass accuracy and high-resolution MS, human serum glycans were effectively profiled. Correct isotopic envelope deconvolution to monoisotopic masses and the high mass accuracy instruments drastically reduced the amount of false composition assignments. The high throughput capacity enabled by this library permitted the rapid glycan profiling of large control populations. With the use of the library, a human serum glycan mass profile was developed from 46 healthy individuals. This paper presents a theoretical N-linked glycan mass library that was used for accurate high-throughput human serum glycan profiling. Rapid methods for evaluating a patient's glycome are instrumental for studying glycan-based markers.

The high throughput biomedicine unit at the institute for molecular medicine Finland: high throughput screening meets precision medicine.

PubMed

Pietiainen, Vilja; Saarela, Jani; von Schantz, Carina; Turunen, Laura; Ostling, Paivi; Wennerberg, Krister

2014-05-01

The High Throughput Biomedicine (HTB) unit at the Institute for Molecular Medicine Finland FIMM was established in 2010 to serve as a national and international academic screening unit providing access to state of the art instrumentation for chemical and RNAi-based high throughput screening. The initial focus of the unit was multiwell plate based chemical screening and high content microarray-based siRNA screening. However, over the first four years of operation, the unit has moved to a more flexible service platform where both chemical and siRNA screening is performed at different scales primarily in multiwell plate-based assays with a wide range of readout possibilities with a focus on ultraminiaturization to allow for affordable screening for the academic users. In addition to high throughput screening, the equipment of the unit is also used to support miniaturized, multiplexed and high throughput applications for other types of research such as genomics, sequencing and biobanking operations. Importantly, with the translational research goals at FIMM, an increasing part of the operations at the HTB unit is being focused on high throughput systems biological platforms for functional profiling of patient cells in personalized and precision medicine projects.

An automated workflow for enhancing microbial bioprocess optimization on a novel microbioreactor platform

PubMed Central

2012-01-01

Background High-throughput methods are widely-used for strain screening effectively resulting in binary information regarding high or low productivity. Nevertheless achieving quantitative and scalable parameters for fast bioprocess development is much more challenging, especially for heterologous protein production. Here, the nature of the foreign protein makes it impossible to predict the, e.g. best expression construct, secretion signal peptide, inductor concentration, induction time, temperature and substrate feed rate in fed-batch operation to name only a few. Therefore, a high number of systematic experiments are necessary to elucidate the best conditions for heterologous expression of each new protein of interest. Results To increase the throughput in bioprocess development, we used a microtiter plate based cultivation system (Biolector) which was fully integrated into a liquid-handling platform enclosed in laminar airflow housing. This automated cultivation platform was used for optimization of the secretory production of a cutinase from Fusarium solani pisi with Corynebacterium glutamicum. The online monitoring of biomass, dissolved oxygen and pH in each of the microtiter plate wells enables to trigger sampling or dosing events with the pipetting robot used for a reliable selection of best performing cutinase producers. In addition to this, further automated methods like media optimization and induction profiling were developed and validated. All biological and bioprocess parameters were exclusively optimized at microtiter plate scale and showed perfect scalable results to 1 L and 20 L stirred tank bioreactor scale. Conclusions The optimization of heterologous protein expression in microbial systems currently requires extensive testing of biological and bioprocess engineering parameters. This can be efficiently boosted by using a microtiter plate cultivation setup embedded into a liquid-handling system, providing more throughput by parallelization and automation. Due to improved statistics by replicate cultivations, automated downstream analysis, and scalable process information, this setup has superior performance compared to standard microtiter plate cultivation. PMID:23113930

Quantifying whole transcriptome size, a prerequisite for understanding transcriptome evolution across species: an example from a plant allopolyploid.

PubMed

Coate, Jeremy E; Doyle, Jeff J

2010-01-01

Evolutionary biologists are increasingly comparing gene expression patterns across species. Due to the way in which expression assays are normalized, such studies provide no direct information about expression per gene copy (dosage responses) or per cell and can give a misleading picture of genes that are differentially expressed. We describe an assay for estimating relative expression per cell. When used in conjunction with transcript profiling data, it is possible to compare the sizes of whole transcriptomes, which in turn makes it possible to compare expression per cell for each gene in the transcript profiling data set. We applied this approach, using quantitative reverse transcriptase-polymerase chain reaction and high throughput RNA sequencing, to a recently formed allopolyploid and showed that its leaf transcriptome was approximately 1.4-fold larger than either progenitor transcriptome (70% of the sum of the progenitor transcriptomes). In contrast, the allopolyploid genome is 94.3% as large as the sum of its progenitor genomes and retains > or =93.5% of the sum of its progenitor gene complements. Thus, "transcriptome downsizing" is greater than genome downsizing. Using this transcriptome size estimate, we inferred dosage responses for several thousand genes and showed that the majority exhibit partial dosage compensation. Homoeologue silencing is nonrandomly distributed across dosage responses, with genes showing extreme responses in either direction significantly more likely to have a silent homoeologue. This experimental approach will add value to transcript profiling experiments involving interspecies and interploidy comparisons by converting expression per transcriptome to expression per genome, eliminating the need for assumptions about transcriptome size.

High-throughput Cloning and Expression of Integral Membrane Proteins in Escherichia coli

PubMed Central

Bruni, Renato

2014-01-01

Recently, several structural genomics centers have been established and a remarkable number of three-dimensional structures of soluble proteins have been solved. For membrane proteins, the number of structures solved has been significantly trailing those for their soluble counterparts, not least because over-expression and purification of membrane proteins is a much more arduous process. By using high throughput technologies, a large number of membrane protein targets can be screened simultaneously and a greater number of expression and purification conditions can be employed, leading to a higher probability of successfully determining the structure of membrane proteins. This unit describes the cloning, expression and screening of membrane proteins using high throughput methodologies developed in our laboratory. Basic Protocol 1 deals with the cloning of inserts into expression vectors by ligation-independent cloning. Basic Protocol 2 describes the expression and purification of the target proteins on a miniscale. Lastly, for the targets that express at the miniscale, basic protocols 3 and 4 outline the methods employed for the expression and purification of targets at the midi-scale, as well as a procedure for detergent screening and identification of detergent(s) in which the target protein is stable. PMID:24510647

Transcriptome analysis of Cronobacter sakazakii ATCC BAA-894 after interaction with human intestinal epithelial cell line HCT-8.

PubMed

Jing, Chun-e; Du, Xin-jun; Li, Ping; Wang, Shuo

2016-01-01

Cronobacter spp. are opportunistic pathogens that are responsible for infections including severe meningitis, septicemia, and necrotizing enterocolitis in neonates and infants. To date, questions still remain regarding the mechanisms of pathogenicity and virulence determinants for each bacterial strain. In this study, we established an in vitro model for Cronobacter sakazakii ATCC BAA-894 infection of HCT-8 human colorectal epithelial cells. The transcriptome profile of C. sakazakii ATCC BAA-894 after interaction with HCT-8 cells was determined using high-throughput whole-transcriptome sequencing (RNA sequencing (RNA-seq)). Gene expression profiles indicated that 139 genes were upregulated and 72 genes were downregulated in the adherent C. sakazakii ATCC BAA-894 strain on HCT-8 cells compared to the cultured bacteria in the cell-free medium. Expressions of some flagella genes and virulence factors involved in adherence were upregulated. High osmolarity and osmotic stress-associated genes were highly upregulated, as well as genes responsible for the synthesis of lipopolysaccharides and outer membrane proteins, iron acquisition systems, and glycerol and glycerophospholipid metabolism. In sum, our study provides further insight into the mechanisms underlying C. sakazakii pathogenesis in the human gastrointestinal tract.

Phage phenomics: Physiological approaches to characterize novel viral proteins

ScienceCinema

Sanchez, Savannah E. [San Diego State Univ., San Diego, CA (United States); Cuevas, Daniel A. [San Diego State Univ., San Diego, CA (United States); Rostron, Jason E. [San Diego State Univ., San Diego, CA (United States); Liang, Tiffany Y. [San Diego State Univ., San Diego, CA (United States); Pivaroff, Cullen G. [San Diego State Univ., San Diego, CA (United States); Haynes, Matthew R. [San Diego State Univ., San Diego, CA (United States); Nulton, Jim [San Diego State Univ., San Diego, CA (United States); Felts, Ben [San Diego State Univ., San Diego, CA (United States); Bailey, Barbara A. [San Diego State Univ., San Diego, CA (United States); Salamon, Peter [San Diego State Univ., San Diego, CA (United States); Edwards, Robert A. [San Diego State Univ., San Diego, CA (United States); Argonne National Lab. (ANL), Argonne, IL (United States); Burgin, Alex B. [Broad Institute, Cambridge, MA (United States); Segall, Anca M. [San Diego State Univ., San Diego, CA (United States); Rohwer, Forest [San Diego State Univ., San Diego, CA (United States)

2018-06-21

Current investigations into phage-host interactions are dependent on extrapolating knowledge from (meta)genomes. Interestingly, 60 - 95% of all phage sequences share no homology to current annotated proteins. As a result, a large proportion of phage genes are annotated as hypothetical. This reality heavily affects the annotation of both structural and auxiliary metabolic genes. Here we present phenomic methods designed to capture the physiological response(s) of a selected host during expression of one of these unknown phage genes. Multi-phenotype Assay Plates (MAPs) are used to monitor the diversity of host substrate utilization and subsequent biomass formation, while metabolomics provides bi-product analysis by monitoring metabolite abundance and diversity. Both tools are used simultaneously to provide a phenotypic profile associated with expression of a single putative phage open reading frame (ORF). Thus, representative results for both methods are compared, highlighting the phenotypic profile differences of a host carrying either putative structural or metabolic phage genes. In addition, the visualization techniques and high throughput computational pipelines that facilitated experimental analysis are presented.

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

Sanchez, Savannah E.; Cuevas, Daniel A.; Rostron, Jason E.

Current investigations into phage-host interactions are dependent on extrapolating knowledge from (meta)genomes. Interestingly, 60 - 95% of all phage sequences share no homology to current annotated proteins. As a result, a large proportion of phage genes are annotated as hypothetical. This reality heavily affects the annotation of both structural and auxiliary metabolic genes. Here we present phenomic methods designed to capture the physiological response(s) of a selected host during expression of one of these unknown phage genes. Multi-phenotype Assay Plates (MAPs) are used to monitor the diversity of host substrate utilization and subsequent biomass formation, while metabolomics provides bi-product analysismore » by monitoring metabolite abundance and diversity. Both tools are used simultaneously to provide a phenotypic profile associated with expression of a single putative phage open reading frame (ORF). Thus, representative results for both methods are compared, highlighting the phenotypic profile differences of a host carrying either putative structural or metabolic phage genes. In addition, the visualization techniques and high throughput computational pipelines that facilitated experimental analysis are presented.« less

Omics Profiling in Precision Oncology*

PubMed Central

Yu, Kun-Hsing; Snyder, Michael

2016-01-01

Cancer causes significant morbidity and mortality worldwide, and is the area most targeted in precision medicine. Recent development of high-throughput methods enables detailed omics analysis of the molecular mechanisms underpinning tumor biology. These studies have identified clinically actionable mutations, gene and protein expression patterns associated with prognosis, and provided further insights into the molecular mechanisms indicative of cancer biology and new therapeutics strategies such as immunotherapy. In this review, we summarize the techniques used for tumor omics analysis, recapitulate the key findings in cancer omics studies, and point to areas requiring further research on precision oncology. PMID:27099341

Quantitative High-Throughput Identification of Drugs as Modulators of Human Constitutive Androstane Receptor

PubMed Central

Lynch, Caitlin; Zhao, Jinghua; Huang, Ruili; Xiao, Jingwei; Li, Linhao; Heyward, Scott; Xia, Menghang; Wang, Hongbing

2015-01-01

The constitutive androstane receptor (CAR, NR1I3) plays a key role in governing the transcription of numerous hepatic genes that involve xenobiotic metabolism/clearance, energy homeostasis, and cell proliferation. Thus, identification of novel human CAR (hCAR) modulators may not only enhance early prediction of drug-drug interactions but also offer potentially novel therapeutics for diseases such as metabolic disorders and cancer. In this study, we have generated a double stable cell line expressing both hCAR and a CYP2B6-driven luciferase reporter for quantitative high-throughput screening (qHTS) of hCAR modulators. Approximately 2800 compounds from the NIH Chemical Genomics Center Pharmaceutical Collection were screened employing both the activation and deactivation modes of the qHTS. Activators (115) and deactivators (152) of hCAR were identified from the primary qHTS, among which 10 agonists and 10 antagonists were further validated in the physiologically relevant human primary hepatocytes for compound-mediated hCAR nuclear translocation and target gene expression. Collectively, our results reveal that hCAR modulators can be efficiently identified through this newly established qHTS assay. Profiling drug collections for hCAR activity would facilitate the prediction of metabolism-based drug-drug interactions, and may lead to the identification of potential novel therapeutics. PMID:25993555

Zebrafish Behavioral Profiling Links Drugs to Biological Targets and Rest/Wake Regulation

PubMed Central

Rihel, Jason; Prober, David A.; Arvanites, Anthony; Lam, Kelvin; Zimmerman, Steven; Jang, Sumin; Haggarty, Stephen J.; Kokel, David; Rubin, Lee L.; Peterson, Randall T.; Schier, Alexander F.

2010-01-01

A major obstacle for the discovery of psychoactive drugs is the inability to predict how small molecules will alter complex behaviors. We report the development and application of a high-throughput, quantitative screen for drugs that alter the behavior of larval zebrafish. We found that the multi-dimensional nature of observed phenotypes enabled the hierarchical clustering of molecules according to shared behaviors. Behavioral profiling revealed conserved functions of psychotropic molecules and predicted the mechanisms of action of poorly characterized compounds. In addition, behavioral profiling implicated new factors such as ether-a-go-go-related gene (ERG) potassium channels and immunomodulators in the control of rest and locomotor activity. These results demonstrate the power of high-throughput behavioral profiling in zebrafish to discover and characterize psychotropic drugs and to dissect the pharmacology of complex behaviors. PMID:20075256

Comprehensive circular RNA expression profile in radiation-treated HeLa cells and analysis of radioresistance-related circRNAs.

PubMed

Yu, Duo; Li, Yunfeng; Ming, Zhihui; Wang, Hongyong; Dong, Zhuo; Qiu, Ling; Wang, Tiejun

2018-01-01

Cervical cancer is one of the most common cancers in women worldwide. Malignant tumors develop resistance mechanisms and are less sensitive to or do not respond to irradiation. With the development of high-throughput sequencing technologies, circular RNA (circRNA) has been identified in an increasing number of diseases, especially cancers. It has been reported that circRNA can compete with microRNAs (miRNAs) to change the stability or translation of target RNAs, thus regulating gene expression at the transcriptional level. However, the role of circRNAs in cervical cancer and the radioresistance mechanisms of HeLa cells are unknown. The objective of this study is to investigate the role of circRNAs in radioresistance in HeLa cells. High-throughput sequencing and bioinformatics analysis of irradiated and sham-irradiated HeLa cells. The reliability of high-throughput RNA sequencing was validated using quantitative real-time polymerase chain reaction. The most significant circRNA functions and pathways were selected by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. A circRNA-miRNA-target gene interaction network was used to find circRNAs associated with radioresistance. Moreover, a protein-protein interaction network was constructed to identify radioresistance-related hub proteins. High-throughput sequencing allowed the identification of 16,893 circRNAs involved in the response of HeLa cells to radiation. Compared with the control group, there were 153 differentially expressed circRNAs, of which 76 were up-regulated and 77 were down-regulated. GO covered three domains: biological process (BP), cellular component (CC) and molecular function (MF). The terms assigned to the BP domain were peptidyl-tyrosine dephosphorylation and regulation of cell migration. The identified CC terms were cell-cell adherens junction, nucleoplasm and cytosol, and the identified MF terms were protein binding and protein tyrosine phosphatase activity. The top five KEGG pathways were MAPK signaling pathway, endocytosis, axon guidance, neurotrophin signaling pathway, and SNARE interactions in vesicular transport. The protein-protein interaction analysis indicated that 19 proteins might be hub proteins. CircRNAs may play a major role in the response to radiation. These findings may improve our understanding of the role of circRNAs in radioresistance in HeLa cells and allow the development of novel therapeutic approaches.

Robo-Lector – a novel platform for automated high-throughput cultivations in microtiter plates with high information content

PubMed Central

Huber, Robert; Ritter, Daniel; Hering, Till; Hillmer, Anne-Kathrin; Kensy, Frank; Müller, Carsten; Wang, Le; Büchs, Jochen

2009-01-01

Background In industry and academic research, there is an increasing demand for flexible automated microfermentation platforms with advanced sensing technology. However, up to now, conventional platforms cannot generate continuous data in high-throughput cultivations, in particular for monitoring biomass and fluorescent proteins. Furthermore, microfermentation platforms are needed that can easily combine cost-effective, disposable microbioreactors with downstream processing and analytical assays. Results To meet this demand, a novel automated microfermentation platform consisting of a BioLector and a liquid-handling robot (Robo-Lector) was sucessfully built and tested. The BioLector provides a cultivation system that is able to permanently monitor microbial growth and the fluorescence of reporter proteins under defined conditions in microtiter plates. Three examplary methods were programed on the Robo-Lector platform to study in detail high-throughput cultivation processes and especially recombinant protein expression. The host/vector system E. coli BL21(DE3) pRhotHi-2-EcFbFP, expressing the fluorescence protein EcFbFP, was hereby investigated. With the method 'induction profiling' it was possible to conduct 96 different induction experiments (varying inducer concentrations from 0 to 1.5 mM IPTG at 8 different induction times) simultaneously in an automated way. The method 'biomass-specific induction' allowed to automatically induce cultures with different growth kinetics in a microtiter plate at the same biomass concentration, which resulted in a relative standard deviation of the EcFbFP production of only ± 7%. The third method 'biomass-specific replication' enabled to generate equal initial biomass concentrations in main cultures from precultures with different growth kinetics. This was realized by automatically transferring an appropiate inoculum volume from the different preculture microtiter wells to respective wells of the main culture plate, where subsequently similar growth kinetics could be obtained. Conclusion The Robo-Lector generates extensive kinetic data in high-throughput cultivations, particularly for biomass and fluorescence protein formation. Based on the non-invasive on-line-monitoring signals, actions of the liquid-handling robot can easily be triggered. This interaction between the robot and the BioLector (Robo-Lector) combines high-content data generation with systematic high-throughput experimentation in an automated fashion, offering new possibilities to study biological production systems. The presented platform uses a standard liquid-handling workstation with widespread automation possibilities. Thus, high-throughput cultivations can now be combined with small-scale downstream processing techniques and analytical assays. Ultimately, this novel versatile platform can accelerate and intensify research and development in the field of systems biology as well as modelling and bioprocess optimization. PMID:19646274

Re-engineering adenovirus vector systems to enable high-throughput analyses of gene function.

PubMed

Stanton, Richard J; McSharry, Brian P; Armstrong, Melanie; Tomasec, Peter; Wilkinson, Gavin W G

2008-12-01

With the enhanced capacity of bioinformatics to interrogate extensive banks of sequence data, more efficient technologies are needed to test gene function predictions. Replication-deficient recombinant adenovirus (Ad) vectors are widely used in expression analysis since they provide for extremely efficient expression of transgenes in a wide range of cell types. To facilitate rapid, high-throughput generation of recombinant viruses, we have re-engineered an adenovirus vector (designated AdZ) to allow single-step, directional gene insertion using recombineering technology. Recombineering allows for direct insertion into the Ad vector of PCR products, synthesized sequences, or oligonucleotides encoding shRNAs without requirement for a transfer vector Vectors were optimized for high-throughput applications by making them "self-excising" through incorporating the I-SceI homing endonuclease into the vector removing the need to linearize vectors prior to transfection into packaging cells. AdZ vectors allow genes to be expressed in their native form or with strep, V5, or GFP tags. Insertion of tetracycline operators downstream of the human cytomegalovirus major immediate early (HCMV MIE) promoter permits silencing of transgenes in helper cells expressing the tet repressor thus making the vector compatible with the cloning of toxic gene products. The AdZ vector system is robust, straightforward, and suited to both sporadic and high-throughput applications.

Arsenic responsive microRNAs in vivo and their potential involvement in arsenic-induced oxidative stress

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

Ren, Xuefeng, E-mail: xuefengr@buffalo.edu; Department of Pharmacology and Toxicology, School of Biomedical Sciences, The State University of New York, Buffalo, NY 14214; Gaile, Daniel P.

Arsenic exposure is postulated to modify microRNA (miRNA) expression, leading to changes of gene expression and toxicities, but studies relating the responses of miRNAs to arsenic exposure are lacking, especially with respect to in vivo studies. We utilized high-throughput sequencing technology and generated miRNA expression profiles of liver tissues from Sprague Dawley (SD) rats exposed to various concentrations of sodium arsenite (0, 0.1, 1, 10 and 100 mg/L) for 60 days. Unsupervised hierarchical clustering analysis of the miRNA expression profiles clustered the SD rats into different groups based on the arsenic exposure status, indicating a highly significant association between arsenicmore » exposure and cluster membership (p-value of 0.0012). Multiple miRNA expressions were altered by arsenic in an exposure concentration-dependent manner. Among the identified arsenic-responsive miRNAs, several are predicted to target Nfe2l2-regulated antioxidant genes, including glutamate–cysteine ligase (GCL) catalytic subunit (GCLC) and modifier subunit (GCLM) which are involved in glutathione (GSH) synthesis. Exposure to low concentrations of arsenic increased mRNA expression for Gclc and Gclm, while high concentrations significantly reduced their expression, which were correlated to changes in hepatic GCL activity and GSH level. Moreover, our data suggested that other mechanisms, e.g., miRNAs, rather than Nfe2l2-signaling pathway, could be involved in the regulation of mRNA expression of Gclc and Gclm post-arsenic exposure in vivo. Together, our findings show that arsenic exposure disrupts the genome-wide expression of miRNAs in vivo, which could lead to the biological consequence, such as an altered balance of antioxidant defense and oxidative stress. - Highlights: • Chronic arsenic exposure induces changes of hepatic miRNA expression profiles. • Hepatic GCL activity and GSH level in rats are altered following arsenic exposure. • Arsenic induced GCL expression change is independent to Nfe2l2-signaling pathway. • Expression of several miRNAs predicted to target GCL changed after arsenic exposure.« less

Novel Informatic Approaches to Analyze Gene Expression Data with the ToxCast 320 Chemical Library in Cultures of Primary Human Hepatocytes

EPA Science Inventory

Prevailing methodologies in the analysis of gene expression data often neglect to incorporate full concentration and time response due to limitations in throughput and sensitivity with traditional microarray approaches. We have developed a high throughput assay suite using primar...

MicroRNAs regulate the main events in rice drought stress response by manipulating the water supply to shoots.

PubMed

Fard, Ehsan Mohseni; Bakhshi, Behnam; Farsi, Mohammad; Kakhki, Amin Mirshamsi; Nikpay, Nava; Ebrahimi, Mohammad Ali; Mardi, Mohsen; Salekdeh, Ghasem Hosseini

2017-10-24

MicroRNAs (miRNAs) are small endogenous regulatory RNAs that are involved in a variety of biological processes related to proliferation, development, and response to biotic and abiotic stresses. miRNA profiles of rice (Oryza sativa L. cv. IR64.) leaves in a partial root zone drying (PRD) system were analysed using a high-throughput sequencing approach to identify miRNAs associated with drought signalling. The treatments performed in this study were as follows: well-watered ("wet" roots, WW), wherein both halves of the pot were watered daily; drought ("dry" roots, DD), wherein water was withheld from both halves of the pot; and well-watered/drought ("wet" and "dry" roots, WD), wherein one half of each pot was watered daily, the same as in WW, and water was withheld from the other part, the same as in DD. High-throughput sequencing enabled us to detect novel miRNAs and study the differential expression of known miRNAs. A total of 209 novel miRNAs were detected in this study. Differential miRNA profiling of the DD, WD and WW conditions showed differential expression of 159 miRNAs, among which 83, 44 and 32 miRNAs showed differential expression under both DD and WD conditions. The detection of putative targets of the differentially expressed miRNAs and investigation of their functions showed that most of these genes encode transcription factors involved in growth and development, leaf morphology, regulation of hormonal homeostasis, and stress response. The most important differences between the DD and WD conditions involved regulation of the levels of hormones such as auxin, cytokinin, abscisic acid, and jasmonic acid and also regulation of phosphor homeostasis. Overall, differentially expressed miRNAs under WD conditions were found to differ from those under DD conditions, with such differences playing a role in adaptation and inducing the normal condition. The mechanisms involved in regulating hormonal homeostasis and involved in energy production and consumption were found to be the most important regulatory pathways distinguishing the DD and WD conditions.

Differential Expression of HERV-K (HML-2) Proviruses in Cells and Virions of the Teratocarcinoma Cell Line Tera-1

PubMed Central

Bhardwaj, Neeru; Montesion, Meagan; Roy, Farrah; Coffin, John M.

2015-01-01

Human endogenous retrovirus (HERV-K (HML-2)) proviruses are among the few endogenous retroviral elements in the human genome that retain coding sequence. HML-2 expression has been widely associated with human disease states, including different types of cancers as well as with HIV-1 infection. Understanding of the potential impact of this expression requires that it be annotated at the proviral level. Here, we utilized the high throughput capabilities of next-generation sequencing to profile HML-2 expression at the level of individual proviruses and secreted virions in the teratocarcinoma cell line Tera-1. We identified well-defined expression patterns, with transcripts emanating primarily from two proviruses located on chromosome 22, only one of which was efficiently packaged. Interestingly, there was a preference for transcripts of recently integrated proviruses, over those from other highly expressed but older elements, to be packaged into virions. We also assessed the promoter competence of the 5’ long terminal repeats (LTRs) of expressed proviruses via a luciferase assay following transfection of Tera-1 cells. Consistent with the RNASeq results, we found that the activity of most LTRs corresponded to their transcript levels. PMID:25746218

Pathway Profiling and Tissue Modeling of Developmental Toxicity

EPA Science Inventory

High-throughput and high-content screening (HTS-HCS) studies are providing a rich source of data that can be applied to in vitro profiling of chemical compounds for biological activity and potential toxicity. EPA’s ToxCast™ project, and the broader Tox21 consortium, in addition t...

Diffraction efficiency of radially-profiled off-plane reflection gratings

NASA Astrophysics Data System (ADS)

Miles, Drew M.; Tutt, James H.; DeRoo, Casey T.; Marlowe, Hannah; Peterson, Thomas J.; McEntaffer, Randall L.; Menz, Benedikt; Burwitz, Vadim; Hartner, Gisela; Laubis, Christian; Scholze, Frank

2015-09-01

Future X-ray missions will require gratings with high throughput and high spectral resolution. Blazed off-plane reflection gratings are capable of meeting these demands. A blazed grating profile optimizes grating efficiency, providing higher throughput to one side of zero-order on the arc of diffraction. This paper presents efficiency measurements made in the 0.3 - 1.5 keV energy band at the Physikalisch-Technische Bundesanstalt (PTB) BESSY II facility for three holographically-ruled gratings, two of which are blazed. Each blazed grating was tested in both the Littrow configuration and anti-Littrow configuration in order to test the alignment sensitivity of these gratings with regard to throughput. This paper outlines the procedure of the grating experiment performed at BESSY II and discuss the resulting efficiency measurements across various energies. Experimental results are generally consistent with theory and demonstrate that the blaze does increase throughput to one side of zero-order. However, the total efficiency of the non-blazed, sinusoidal grating is greater than that of the blazed gratings, which suggests that the method of manufacturing these blazed profiles fails to produce facets with the desired level of precision. Finally, evidence of a successful blaze implementation from first diffraction results of prototype blazed gratings produce via a new fabrication technique at the University of Iowa are presented.

Object-location training elicits an overlapping but temporally distinct transcriptional profile from contextual fear conditioning.

PubMed

Poplawski, Shane G; Schoch, Hannah; Wimmer, Mathieu; Hawk, Joshua D; Walsh, Jennifer L; Giese, Karl P; Abel, Ted

2014-12-01

Hippocampus-dependent learning is known to induce changes in gene expression, but information on gene expression differences between different learning paradigms that require the hippocampus is limited. The bulk of studies investigating RNA expression after learning use the contextual fear conditioning task, which couples a novel environment with a footshock. Although contextual fear conditioning has been useful in discovering gene targets, gene expression after spatial memory tasks has received less attention. In this study, we used the object-location memory task and studied gene expression at two time points after learning in a high-throughput manner using a microfluidic qPCR approach. We found that expression of the classic immediate-early genes changes after object-location training in a fashion similar to that observed after contextual fear conditioning. However, the temporal dynamics of gene expression are different between the two tasks, with object-location memory producing gene expression changes that last at least 2 hours. Our findings indicate that different training paradigms may give rise to distinct temporal dynamics of gene expression after learning. Copyright © 2014 Elsevier Inc. All rights reserved.

Object-Location Training Elicits an Overlapping but Temporally Distinct Transcriptional Profile from Contextual Fear Conditioning

PubMed Central

Wimmer, Mathieu; Hawk, Joshua D.; Walsh, Jennifer L.; Giese, Karl P.; Abel, Ted

2014-01-01

Hippocampus-dependent learning is known to induce changes in gene expression, but information on gene expression differences between different learning paradigms that require the hippocampus is limited. The bulk of studies investigating RNA expression after learning use the contextual fear conditioning task, which couples a novel environment with a footshock. Although contextual fear conditioning has been useful in discovering gene targets, gene expression after spatial memory tasks has received less attention. In this study, we used the object-location memory task and studied gene expression at two time points after learning in a high-throughput manner using a microfluidic qPCR approach. We found that expression of the classic immediate-early genes changes after object-location training in a fashion similar to that observed after contextual fear conditioning. However, the temporal dynamics of gene expression are different between the two tasks, with object-location memory producing gene expression changes that last at least 2 hours. Our findings indicate that different training paradigms may give rise to distinct temporal dynamics of gene expression after learning. PMID:25242102

g:Profiler-a web server for functional interpretation of gene lists (2016 update).

PubMed

Reimand, Jüri; Arak, Tambet; Adler, Priit; Kolberg, Liis; Reisberg, Sulev; Peterson, Hedi; Vilo, Jaak

2016-07-08

Functional enrichment analysis is a key step in interpreting gene lists discovered in diverse high-throughput experiments. g:Profiler studies flat and ranked gene lists and finds statistically significant Gene Ontology terms, pathways and other gene function related terms. Translation of hundreds of gene identifiers is another core feature of g:Profiler. Since its first publication in 2007, our web server has become a popular tool of choice among basic and translational researchers. Timeliness is a major advantage of g:Profiler as genome and pathway information is synchronized with the Ensembl database in quarterly updates. g:Profiler supports 213 species including mammals and other vertebrates, plants, insects and fungi. The 2016 update of g:Profiler introduces several novel features. We have added further functional datasets to interpret gene lists, including transcription factor binding site predictions, Mendelian disease annotations, information about protein expression and complexes and gene mappings of human genetic polymorphisms. Besides the interactive web interface, g:Profiler can be accessed in computational pipelines using our R package, Python interface and BioJS component. g:Profiler is freely available at http://biit.cs.ut.ee/gprofiler/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Genome-Wide Characterization and Expression Profiling of the AUXIN RESPONSE FACTOR (ARF) Gene Family in Eucalyptus grandis

PubMed Central

Yu, Hong; Soler, Marçal; Mila, Isabelle; San Clemente, Hélène; Savelli, Bruno; Dunand, Christophe; Paiva, Jorge A. P.; Myburg, Alexander A.; Bouzayen, Mondher; Grima-Pettenati, Jacqueline; Cassan-Wang, Hua

2014-01-01

Auxin is a central hormone involved in a wide range of developmental processes including the specification of vascular stem cells. Auxin Response Factors (ARF) are important actors of the auxin signalling pathway, regulating the transcription of auxin-responsive genes through direct binding to their promoters. The recent availability of the Eucalyptus grandis genome sequence allowed us to examine the characteristics and evolutionary history of this gene family in a woody plant of high economic importance. With 17 members, the E. grandis ARF gene family is slightly contracted, as compared to those of most angiosperms studied hitherto, lacking traces of duplication events. In silico analysis of alternative transcripts and gene truncation suggested that these two mechanisms were preeminent in shaping the functional diversity of the ARF family in Eucalyptus. Comparative phylogenetic analyses with genomes of other taxonomic lineages revealed the presence of a new ARF clade found preferentially in woody and/or perennial plants. High-throughput expression profiling among different organs and tissues and in response to environmental cues highlighted genes expressed in vascular cambium and/or developing xylem, responding dynamically to various environmental stimuli. Finally, this study allowed identification of three ARF candidates potentially involved in the auxin-regulated transcriptional program underlying wood formation. PMID:25269088

Distinct effects of calorie restriction on adipose tissue cytokine and angiogenesis profiles in obese and lean mice

PubMed Central

2012-01-01

Background Obesity associates with low-grade inflammation and adipose tissue remodeling. Using sensitive high-throughput protein arrays we here investigated adipose tissue cytokine and angiogenesis-related protein profiles from obese and lean mice, and in particular, the influence of calorie restriction (CR). Methods Tissue samples from visceral fat were harvested from obese mice fed with a high-fat diet (60% of energy), lean controls receiving low-fat control diet as well as from obese and lean mice kept under CR (energy intake 70% of ad libitum intake) for 50 days. Protein profiles were analyzed using mouse cytokine and angiogenesis protein array kits. Results In obese and lean mice, CR was associated with 11.3% and 15.6% reductions in body weight, as well as with 4.0% and 4.6% reductions in body fat percentage, respectively. Obesity induced adipose tissue cytokine expressions, the most highly upregulated cytokines being IL-1ra, IL-2, IL-16, MCP-1, MIG, RANTES, C5a, sICAM-1 and TIMP-1. CR increased sICAM-1 and TIMP-1 expression both in obese and lean mice. Overall, CR showed distinct effects on cytokine expressions; in obese mice CR largely decreased but in lean mice increased adipose tissue cytokine expressions. Obesity was also associated with increased expressions of angiogenesis-related proteins, in particular, angiogenin, endoglin, endostatin, endothelin-1, IGFBP-3, leptin, MMP-3, PAI-1, TIMP-4, CXCL16, platelet factor 4, DPPIV and coagulation factor III. CR increased endoglin, endostatin and platelet factor 4 expressions, and decreased IGFBP-3, NOV, MMP-9, CXCL16 and osteopontin expressions both in obese and lean mice. Interestingly, in obese mice, CR decreased leptin and TIMP-4 expressions, whereas in lean mice their expressions were increased. CR decreased MMP-3 and PAI-1 only in obese mice, whereas CR decreased FGF acidic, FGF basic and coagulation factor III, and increased angiogenin and DPPIV expression only in lean mice. Conclusions CR exerts distinct effects on adipocyte cytokine and angiogenesis profiles in obese and lean mice. Our study also underscores the importance of angiogenesis-related proteins and cytokines in adipose tissue remodeling and development of obesity. PMID:22748184

High-Throughput RT-PCR for small-molecule screening assays

PubMed Central

Bittker, Joshua A.

2012-01-01

Quantitative measurement of the levels of mRNA expression using real-time reverse transcription polymerase chain reaction (RT-PCR) has long been used for analyzing expression differences in tissue or cell lines of interest. This method has been used somewhat less frequently to measure the changes in gene expression due to perturbagens such as small molecules or siRNA. The availability of new instrumentation for liquid handling and real-time PCR analysis as well as the commercial availability of start-to-finish kits for RT-PCR has enabled the use of this method for high-throughput small-molecule screening on a scale comparable to traditional high-throughput screening (HTS) assays. This protocol focuses on the special considerations necessary for using quantitative RT-PCR as a primary small-molecule screening assay, including the different methods available for mRNA isolation and analysis. PMID:23487248

Differentially Expressed microRNAs and Target Genes Associated with Plastic Internode Elongation in Alternanthera philoxeroides in Contrasting Hydrological Habitats

PubMed Central

Li, Gengyun; Deng, Ying; Geng, Yupeng; Zhou, Chengchuan; Wang, Yuguo; Zhang, Wenju; Song, Zhiping; Gao, Lexuan; Yang, Ji

2017-01-01

Phenotypic plasticity is crucial for plants to survive in changing environments. Discovering microRNAs, identifying their targets and further inferring microRNA functions in mediating plastic developmental responses to environmental changes have been a critical strategy for understanding the underlying molecular mechanisms of phenotypic plasticity. In this study, the dynamic expression patterns of microRNAs under contrasting hydrological habitats in the amphibious species Alternanthera philoxeroides were identified by time course expression profiling using high-throughput sequencing technology. A total of 128 known and 18 novel microRNAs were found to be differentially expressed under contrasting hydrological habitats. The microRNA:mRNA pairs potentially associated with plastic internode elongation were identified by integrative analysis of microRNA and mRNA expression profiles, and were validated by qRT-PCR and 5′ RLM-RACE. The results showed that both the universal microRNAs conserved across different plants and the unique microRNAs novelly identified in A. philoxeroides were involved in the responses to varied water regimes. The results also showed that most of the differentially expressed microRNAs were transiently up-/down-regulated at certain time points during the treatments. The fine-scale temporal changes in microRNA expression highlighted the importance of time-series sampling in identifying stress-responsive microRNAs and analyzing their role in stress response/tolerance. PMID:29259617

Dynamic integrated analysis of DNA methylation and gene expression profiles in in vivo and in vitro fertilized mouse post-implantation extraembryonic and placental tissues.

PubMed

Tan, Kun; Zhang, Zhenni; Miao, Kai; Yu, Yong; Sui, Linlin; Tian, Jianhui; An, Lei

2016-07-01

How does in vitro fertilization (IVF) alter promoter DNA methylation patterns and its subsequent effects on gene expression profiles during placentation in mice? IVF-induced alterations in promoter DNA methylation might have functional consequences in a number of biological processes and functions during IVF placentation, including actin cytoskeleton organization, hematopoiesis, vasculogenesis, energy metabolism and nutrient transport. During post-implantation embryonic development, both embryonic and extraembryonic tissues undergo de novo DNA methylation, thereby establishing a global DNA methylation pattern, and influencing gene expression profiles. Embryonic and placental tissues of IVF conceptuses can have aberrant morphology and functions, resulting in adverse pregnancy outcomes such as pregnancy loss, low birthweight, and long-term health effects. To date, the IVF-induced global profiling of DNA methylation alterations, and their functional consequences on aberrant gene expression profiles in IVF placentas have not been systematically studied. Institute for Cancer Research mice (6 week-old females and 8-9 week-old males) were used to generate in vivo fertilization (IVO) and IVF blastocysts. After either IVO and development (IVO group as control) or in vitro fertilization and culture (IVF group), blastocysts were collected and transferred to pseudo-pregnant recipient mice. Extraembryonic (ectoplacental cone and extraembryonic ectoderm) and placental tissues from both groups were sampled at embryonic day (E) 7.5 (IVO, n = 822; IVF, n = 795) and E10.5 (IVO, n = 324; IVF, n = 278), respectively. The collected extraembryonic (E7.5) and placental tissues (E10.5) were then used for high-throughput RNA sequencing (RNA-seq) and methylated DNA immunoprecipitation sequencing (MeDIP-seq). The main dysfunctions indicated by bioinformatic analyses were further validated using molecular detection, and morphometric and phenotypic analyses. Dynamic functional profiling of high-throughput data, together with molecular detection, and morphometric and phenotypic analyses, showed that differentially expressed genes dysregulated by DNA methylation were functionally involved in: (i) actin cytoskeleton disorganization in IVF extraembryonic tissues, which may impair allantois or chorion formation, and chorioallantoic fusion; (ii) disturbed hematopoiesis and vasculogenesis, which may lead to abnormal placenta labyrinth formation and thereby impairing nutrition transport in IVF placentas; (iii) dysregulated energy and amino acid metabolism, which may cause placental dysfunctions, leading to delayed embryonic development or even lethality; (iv) disrupted genetic information processing, which can further influence gene transcriptional and translational processes. Findings in mouse placental tissues may not be fully representative of human placentas. Further studies are necessary to confirm these findings and determine their clinical significance. Our study is the first to provide the genome-wide analysis of gene expression dysregulation caused by DNA methylation during IVF placentation. Systematic understanding of the molecular mechanisms implicated in IVF placentation can be useful for the improvement of existing assisted conception systems to prevent these IVF-associated safety concerns. This work was supported by grants from the National Natural Science Foundation of China (No. 31472092), and the National High-Tech R&D Program (Nos. 2011|AA100303, 2013AA102506). There was no conflict of interest. © The Author 2016. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Statistical use of argonaute expression and RISC assembly in microRNA target identification.

PubMed

Stanhope, Stephen A; Sengupta, Srikumar; den Boon, Johan; Ahlquist, Paul; Newton, Michael A

2009-09-01

MicroRNAs (miRNAs) posttranscriptionally regulate targeted messenger RNAs (mRNAs) by inducing cleavage or otherwise repressing their translation. We address the problem of detecting m/miRNA targeting relationships in homo sapiens from microarray data by developing statistical models that are motivated by the biological mechanisms used by miRNAs. The focus of our modeling is the construction, activity, and mediation of RNA-induced silencing complexes (RISCs) competent for targeted mRNA cleavage. We demonstrate that regression models accommodating RISC abundance and controlling for other mediating factors fit the expression profiles of known target pairs substantially better than models based on m/miRNA expressions alone, and lead to verifications of computational target pair predictions that are more sensitive than those based on marginal expression levels. Because our models are fully independent of exogenous results from sequence-based computational methods, they are appropriate for use as either a primary or secondary source of information regarding m/miRNA target pair relationships, especially in conjunction with high-throughput expression studies.

High-Throughput Sequencing Identifies MicroRNAs from Posterior Intestine of Loach (Misgurnus anguillicaudatus) and Their Response to Intestinal Air-Breathing Inhibition.

PubMed

Huang, Songqian; Cao, Xiaojuan; Tian, Xianchang; Wang, Weimin

2016-01-01

MicroRNAs (miRNAs) exert important roles in animal growth, immunity, and development, and regulate gene expression at the post-transcriptional level. Knowledges about the diversities of miRNAs and their roles in accessory air-breathing organs (ABOs) of fish remain unknown. In this work, we used high-throughput sequencing to identify known and novel miRNAs from the posterior intestine, an important ABO, in loach (Misgurnus anguillicaudatus) under normal and intestinal air-breathing inhibited conditions. A total of 204 known and 84 novel miRNAs were identified, while 47 miRNAs were differentially expressed between the two small RNA libraries (i.e. between the normal and intestinal air-breathing inhibited group). Potential miRNA target genes were predicted by combining our transcriptome data of the posterior intestine of the loach under the same conditions, and then annotated using COG, GO, KEGG, Swissprot and Nr databases. The regulatory networks of miRNAs and their target genes were analyzed. The abundances of nine known miRNAs were validated by qRT-PCR. The relative expression profiles of six known miRNAs and their eight corresponding target genes, and two novel potential miRNAs were also detected. Histological characteristics of the posterior intestines in both normal and air-breathing inhibited group were further analyzed. This study contributes to our understanding on the functions and molecular regulatory mechanisms of miRNAs in accessory air-breathing organs of fish.

Analysis of the Effects of Five Factors Relevant to In Vitro Chondrogenesis of Human Mesenchymal Stem Cells Using Factorial Design and High Throughput mRNA-Profiling

PubMed Central

Jakobsen, Rune B.; Østrup, Esben; Zhang, Xiaolan; Mikkelsen, Tarjei S.; Brinchmann, Jan E.

2014-01-01

The in vitro process of chondrogenic differentiation of mesenchymal stem cells for tissue engineering has been shown to require three-dimensional culture along with the addition of differentiation factors to the culture medium. In general, this leads to a phenotype lacking some of the cardinal features of native articular chondrocytes and their extracellular matrix. The factors used vary, but regularly include members of the transforming growth factor β superfamily and dexamethasone, sometimes in conjunction with fibroblast growth factor 2 and insulin-like growth factor 1, however the use of soluble factors to induce chondrogenesis has largely been studied on a single factor basis. In the present study we combined a factorial quality-by-design experiment with high-throughput mRNA profiling of a customized chondrogenesis related gene set as a tool to study in vitro chondrogenesis of human bone marrow derived mesenchymal stem cells in alginate. 48 different conditions of transforming growth factor β 1, 2 and 3, bone morphogenetic protein 2, 4 and 6, dexamethasone, insulin-like growth factor 1, fibroblast growth factor 2 and cell seeding density were included in the experiment. The analysis revealed that the best of the tested differentiation cocktails included transforming growth factor β 1 and dexamethasone. Dexamethasone acted in synergy with transforming growth factor β 1 by increasing many chondrogenic markers while directly downregulating expression of the pro-osteogenic gene osteocalcin. However, all factors beneficial to the expression of desirable hyaline cartilage markers also induced undesirable molecules, indicating that perfect chondrogenic differentiation is not achievable with the current differentiation protocols. PMID:24816923

Estimation of Dynamic Systems for Gene Regulatory Networks from Dependent Time-Course Data.

PubMed

Kim, Yoonji; Kim, Jaejik

2018-06-15

Dynamic system consisting of ordinary differential equations (ODEs) is a well-known tool for describing dynamic nature of gene regulatory networks (GRNs), and the dynamic features of GRNs are usually captured through time-course gene expression data. Owing to high-throughput technologies, time-course gene expression data have complex structures such as heteroscedasticity, correlations between genes, and time dependence. Since gene experiments typically yield highly noisy data with small sample size, for a more accurate prediction of the dynamics, the complex structures should be taken into account in ODE models. Hence, this study proposes an ODE model considering such data structures and a fast and stable estimation method for the ODE parameters based on the generalized profiling approach with data smoothing techniques. The proposed method also provides statistical inference for the ODE estimator and it is applied to a zebrafish retina cell network.

Species-Specific Predictive Signatures of Developmental Toxicity Using the ToxCast Chemical Library

EPA Science Inventory

EPA’s ToxCastTM project is profiling the in vitro bioactivity of chemicals to generate predictive signatures that correlate with observed in vivo toxicity. In vitro profiling methods from ToxCast data consist of over 600 high-throughput screening (HTS) and high-content screening ...

High-Throughput Cloning and Expression Library Creation for Functional Proteomics

PubMed Central

Festa, Fernanda; Steel, Jason; Bian, Xiaofang; Labaer, Joshua

2013-01-01

The study of protein function usually requires the use of a cloned version of the gene for protein expression and functional assays. This strategy is particular important when the information available regarding function is limited. The functional characterization of the thousands of newly identified proteins revealed by genomics requires faster methods than traditional single gene experiments, creating the need for fast, flexible and reliable cloning systems. These collections of open reading frame (ORF) clones can be coupled with high-throughput proteomics platforms, such as protein microarrays and cell-based assays, to answer biological questions. In this tutorial we provide the background for DNA cloning, discuss the major high-throughput cloning systems (Gateway® Technology, Flexi® Vector Systems, and Creator™ DNA Cloning System) and compare them side-by-side. We also report an example of high-throughput cloning study and its application in functional proteomics. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP12). Details can be found at http://www.proteomicstutorials.org. PMID:23457047

High-throughput cloning and expression library creation for functional proteomics.

PubMed

Festa, Fernanda; Steel, Jason; Bian, Xiaofang; Labaer, Joshua

2013-05-01

The study of protein function usually requires the use of a cloned version of the gene for protein expression and functional assays. This strategy is particularly important when the information available regarding function is limited. The functional characterization of the thousands of newly identified proteins revealed by genomics requires faster methods than traditional single-gene experiments, creating the need for fast, flexible, and reliable cloning systems. These collections of ORF clones can be coupled with high-throughput proteomics platforms, such as protein microarrays and cell-based assays, to answer biological questions. In this tutorial, we provide the background for DNA cloning, discuss the major high-throughput cloning systems (Gateway® Technology, Flexi® Vector Systems, and Creator(TM) DNA Cloning System) and compare them side-by-side. We also report an example of high-throughput cloning study and its application in functional proteomics. This tutorial is part of the International Proteomics Tutorial Programme (IPTP12). © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An enzyme-mediated protein-fragment complementation assay for substrate screening of sortase A.

PubMed

Li, Ning; Yu, Zheng; Ji, Qun; Sun, Jingying; Liu, Xiao; Du, Mingjuan; Zhang, Wei

2017-04-29

Enzyme-mediated protein conjugation has gained great attention recently due to the remarkable site-selectivity and mild reaction condition affected by the nature of enzyme. Among all sorts of enzymes reported, sortase A from Staphylococcus aureus (SaSrtA) is the most popular enzyme due to its selectivity and well-demonstrated applications. Position scanning has been widely applied to understand enzyme substrate specificity, but the low throughput of chemical synthesis of peptide substrates and analytical methods (HPLC, LC-ESI-MS) have been the major hurdle to fully decode enzyme substrate profile. We have developed a simple high-throughput substrate profiling method to reveal novel substrates of SaSrtA 7M, a widely used hyperactive peptide ligase, by modified protein-fragment complementation assay (PCA). A small library targeting the LPATG motif recognized by SaSrtA 7M was generated and screened against proteins carrying N-terminal glycine. Using this method, we have confirmed all currently known substrates of the enzyme, and moreover identified some previously unknown substrates with varying activities. The method provides an easy, fast and highly-sensitive way to determine substrate profile of a peptide ligase in a high-throughput manner. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluation of high throughput gene expression platforms using a genomic biomarker signature for prediction of skin sensitization.

PubMed

Forreryd, Andy; Johansson, Henrik; Albrekt, Ann-Sofie; Lindstedt, Malin

2014-05-16

Allergic contact dermatitis (ACD) develops upon exposure to certain chemical compounds termed skin sensitizers. To reduce the occurrence of skin sensitizers, chemicals are regularly screened for their capacity to induce sensitization. The recently developed Genomic Allergen Rapid Detection (GARD) assay is an in vitro alternative to animal testing for identification of skin sensitizers, classifying chemicals by evaluating transcriptional levels of a genomic biomarker signature. During assay development and biomarker identification, genome-wide expression analysis was applied using microarrays covering approximately 30,000 transcripts. However, the microarray platform suffers from drawbacks in terms of low sample throughput, high cost per sample and time consuming protocols and is a limiting factor for adaption of GARD into a routine assay for screening of potential sensitizers. With the purpose to simplify assay procedures, improve technical parameters and increase sample throughput, we assessed the performance of three high throughput gene expression platforms--nCounter®, BioMark HD™ and OpenArray®--and correlated their performance metrics against our previously generated microarray data. We measured the levels of 30 transcripts from the GARD biomarker signature across 48 samples. Detection sensitivity, reproducibility, correlations and overall structure of gene expression measurements were compared across platforms. Gene expression data from all of the evaluated platforms could be used to classify most of the sensitizers from non-sensitizers in the GARD assay. Results also showed high data quality and acceptable reproducibility for all platforms but only medium to poor correlations of expression measurements across platforms. In addition, evaluated platforms were superior to the microarray platform in terms of cost efficiency, simplicity of protocols and sample throughput. We evaluated the performance of three non-array based platforms using a limited set of transcripts from the GARD biomarker signature. We demonstrated that it was possible to achieve acceptable discriminatory power in terms of separation between sensitizers and non-sensitizers in the GARD assay while reducing assay costs, simplify assay procedures and increase sample throughput by using an alternative platform, providing a first step towards the goal to prepare GARD for formal validation and adaption of the assay for industrial screening of potential sensitizers.

NCBI GEO: mining tens of millions of expression profiles--database and tools update.

PubMed

Barrett, Tanya; Troup, Dennis B; Wilhite, Stephen E; Ledoux, Pierre; Rudnev, Dmitry; Evangelista, Carlos; Kim, Irene F; Soboleva, Alexandra; Tomashevsky, Maxim; Edgar, Ron

2007-01-01

The Gene Expression Omnibus (GEO) repository at the National Center for Biotechnology Information (NCBI) archives and freely disseminates microarray and other forms of high-throughput data generated by the scientific community. The database has a minimum information about a microarray experiment (MIAME)-compliant infrastructure that captures fully annotated raw and processed data. Several data deposit options and formats are supported, including web forms, spreadsheets, XML and Simple Omnibus Format in Text (SOFT). In addition to data storage, a collection of user-friendly web-based interfaces and applications are available to help users effectively explore, visualize and download the thousands of experiments and tens of millions of gene expression patterns stored in GEO. This paper provides a summary of the GEO database structure and user facilities, and describes recent enhancements to database design, performance, submission format options, data query and retrieval utilities. GEO is accessible at http://www.ncbi.nlm.nih.gov/geo/

Identification of FGF-dependent genes in the Drosophila tracheal system.

PubMed

Stahl, Markus; Schuh, Reinhard; Adryan, Boris

2007-01-01

The embryonic development of the tracheal system of the fruit fly Drosophila provides a paradigm for genetic studies of branching morphogenesis. Efforts of many laboratories have identified Branchless (Bnl, a fibroblast growth factor homologue) and Breathless (Btl, the receptor homologue) as crucial factors at many stages of tracheal system development. The downstream targets of the Bnl/Btl signalling cascade, however, remain mostly unknown. Misexpression of the bnl gene results in specific tracheal phenotypes that lead to larval death. We characterised the transcriptional profiles of targeted over-expression of bnl in the embryonic trachea and of loss-of-function bnl(P1) mutant embryos. Gene expression data was mapped to high-throughput in situ hybridisation based ImaGO-annotation. Thus, we identified and confirmed by quantitative PCR 13 Bnl-dependent genes that are expressed in cells within and outside of the tracheal system.

Effects of Different Substrates on Lignocellulosic Enzyme Expression, Enzyme Activity, Substrate Utilization and Biological Efficiency of Pleurotus Eryngii.

PubMed

Xie, Chunliang; Yan, Li; Gong, Wenbing; Zhu, Zuohua; Tan, Senwei; Chen, Du; Hu, Zhenxiu; Peng, Yuande

2016-01-01

Pleurotus eryngii is one of the most valued and delicious mushrooms which are commercially cultivated on various agro-wastes. How different substrates affect lignocellulosic biomass degradation, lignocellulosic enzyme production and biological efficiency in Pleurotus eryngii was unclear. In this report, Pleurotus eryngii was cultivated in substrates including ramie stalks, kenaf stalks, cottonseed hulls and bulrush stalks. The results showed that ramie stalks and kenaf stalks were found to best suitable to cultivate Pleurotus eryngii with the biological efficiency achieved at 55% and 57%, respectively. In order to establish correlations between different substrates and lignocellulosic enzymes expression, the extracellular proteins from four substrates were profiled with high throughput TMT-based quantitative proteomic approach. 241 non-redundant proteins were identified and 74 high confidence lignocellulosic enzymes were quantified. Most of the cellulases, hemicellulases and lignin depolymerization enzymes were highly up-regulated when ramie stalks and kenaf stalks were used as carbon sources. The enzyme activities results suggested cellulases, hemicellulases and lignin depolymerization enzymes were significantly induced by ramie stalks and kenaf stalks. The lignocelluloses degradation, most of the lignocellulosic enzymes expressions and activities of Pleurotus eryngii had positive correlation with the biological efficiency, which depend on the nature of lignocellulosic substrates. In addition, the lignocellulosic enzymes expression profiles during Pleurotus eryngii growth in different substrates were obtained. The present study suggested that most of the lignocellulosic enzymes expressions and activities can be used as tools for selecting better performing substrates for commercial mushroom cultivation. © 2016 The Author(s) Published by S. Karger AG, Basel.

CellProfiler Tracer: exploring and validating high-throughput, time-lapse microscopy image data.

PubMed

Bray, Mark-Anthony; Carpenter, Anne E

2015-11-04

Time-lapse analysis of cellular images is an important and growing need in biology. Algorithms for cell tracking are widely available; what researchers have been missing is a single open-source software package to visualize standard tracking output (from software like CellProfiler) in a way that allows convenient assessment of track quality, especially for researchers tuning tracking parameters for high-content time-lapse experiments. This makes quality assessment and algorithm adjustment a substantial challenge, particularly when dealing with hundreds of time-lapse movies collected in a high-throughput manner. We present CellProfiler Tracer, a free and open-source tool that complements the object tracking functionality of the CellProfiler biological image analysis package. Tracer allows multi-parametric morphological data to be visualized on object tracks, providing visualizations that have already been validated within the scientific community for time-lapse experiments, and combining them with simple graph-based measures for highlighting possible tracking artifacts. CellProfiler Tracer is a useful, free tool for inspection and quality control of object tracking data, available from http://www.cellprofiler.org/tracer/.

The changes of gene expression profiling between segmental vitiligo, generalized vitiligo and healthy individual.

PubMed

Wang, Ping; Li, Yong; Nie, Huiqiong; Zhang, Xiaoyan; Shao, Qiongyan; Hou, Xiuli; Xu, Wen; Hong, Weisong; Xu, Aie

2016-10-01

Vitiligo is a common acquired depigmentation skin disease characterized by loss or dysfunction of melanocytes within the skin lesion, but its pathologenesis is far from lucid. The gene expression profiling of segmental vitiligo (SV) and generalized vitiligo (GV) need further investigation. To better understanding the common and distinct factors, especially in the view of gene expression profile, which were involved in the diseases development and maintenance of segmental vitiligo (SV) and generalized vitiligo (GV). Peripheral bloods were collected from SV, GV and healthy individual (HI), followed by leukocytes separation and total RNA extraction. The high-throughput whole genome expression microarrays were used to assay the gene expression profiles between HI, SV and GV. Bioinformatics tools were employed to annotated the biological function of differently expressed genes. Quantitative PCR assay was used to validate the gene expression of array. Compared to HI, 239 over-expressed genes and 175 down-expressed genes detected in SV, 688 over-expressed genes and 560 down-expressed genes were found in GV, following the criteria of log2 (fold change)≥0.585 and P value<0.05. In these differently expressed genes, 60 over-expressed genes and 60 down-expressed genes had similar tendency in SV and GV. Compared to SV, 223 genes were up regulated and 129 genes were down regulated in GV. In the SV with HI as control, the differently expressed genes were mainly involved in the adaptive immune response, cytokine-cytokine receptor interaction, chemokine signaling, focal adhesion and sphingolipid metabolism. The differently expressed genes between GV and HI were mainly involved in the innate immune, autophagy, apoptosis, melanocyte biology, ubiquitin mediated proteolysis and tyrosine metabolism, which was different from SV. While the differently expressed genes between SV and GV were mainly involved in the metabolism pathway of purine, pyrimidine, glycolysis and sphingolipid. Above results suggested that they not only shared part bio-process and signal pathway, but more important, they utilized different biological mechanism in their pathogenesis and maintenance. Our results provide a comprehensive view on the gene expression profiling change between SV and GV especially in the side of leukocytes, and may facilitate the future study on their molecular mechanism and theraputic targets. Copyright © 2016 Japanese Society for Investigative Dermatology. Published by Elsevier Ireland Ltd. All rights reserved.

A powerful and flexible statistical framework for testing hypotheses of allele-specific gene expression from RNA-seq data

PubMed Central

Skelly, Daniel A.; Johansson, Marnie; Madeoy, Jennifer; Wakefield, Jon; Akey, Joshua M.

2011-01-01

Variation in gene expression is thought to make a significant contribution to phenotypic diversity among individuals within populations. Although high-throughput cDNA sequencing offers a unique opportunity to delineate the genome-wide architecture of regulatory variation, new statistical methods need to be developed to capitalize on the wealth of information contained in RNA-seq data sets. To this end, we developed a powerful and flexible hierarchical Bayesian model that combines information across loci to allow both global and locus-specific inferences about allele-specific expression (ASE). We applied our methodology to a large RNA-seq data set obtained in a diploid hybrid of two diverse Saccharomyces cerevisiae strains, as well as to RNA-seq data from an individual human genome. Our statistical framework accurately quantifies levels of ASE with specified false-discovery rates, achieving high reproducibility between independent sequencing platforms. We pinpoint loci that show unusual and biologically interesting patterns of ASE, including allele-specific alternative splicing and transcription termination sites. Our methodology provides a rigorous, quantitative, and high-resolution tool for profiling ASE across whole genomes. PMID:21873452

Quantitative Assessment of RNA-Protein Interactions with High Throughput Sequencing - RNA Affinity Profiling (HiTS-RAP)

PubMed Central

Ozer, Abdullah; Tome, Jacob M.; Friedman, Robin C.; Gheba, Dan; Schroth, Gary P.; Lis, John T.

2016-01-01

Because RNA-protein interactions play a central role in a wide-array of biological processes, methods that enable a quantitative assessment of these interactions in a high-throughput manner are in great demand. Recently, we developed the High Throughput Sequencing-RNA Affinity Profiling (HiTS-RAP) assay, which couples sequencing on an Illumina GAIIx with the quantitative assessment of one or several proteins’ interactions with millions of different RNAs in a single experiment. We have successfully used HiTS-RAP to analyze interactions of EGFP and NELF-E proteins with their corresponding canonical and mutant RNA aptamers. Here, we provide a detailed protocol for HiTS-RAP, which can be completed in about a month (8 days hands-on time) including the preparation and testing of recombinant proteins and DNA templates, clustering DNA templates on a flowcell, high-throughput sequencing and protein binding with GAIIx, and finally data analysis. We also highlight aspects of HiTS-RAP that can be further improved and points of comparison between HiTS-RAP and two other recently developed methods, RNA-MaP and RBNS. A successful HiTS-RAP experiment provides the sequence and binding curves for approximately 200 million RNAs in a single experiment. PMID:26182240

High-throughput sequencing methods to study neuronal RNA-protein interactions.

PubMed

Ule, Jernej

2009-12-01

UV-cross-linking and RNase protection, combined with high-throughput sequencing, have provided global maps of RNA sites bound by individual proteins or ribosomes. Using a stringent purification protocol, UV-CLIP (UV-cross-linking and immunoprecipitation) was able to identify intronic and exonic sites bound by splicing regulators in mouse brain tissue. Ribosome profiling has been used to quantify ribosome density on budding yeast mRNAs under different environmental conditions. Post-transcriptional regulation in neurons requires high spatial and temporal precision, as is evident from the role of localized translational control in synaptic plasticity. It remains to be seen if the high-throughput methods can be applied quantitatively to study the dynamics of RNP (ribonucleoprotein) remodelling in specific neuronal populations during the neurodegenerative process. It is certain, however, that applications of new biochemical techniques followed by high-throughput sequencing will continue to provide important insights into the mechanisms of neuronal post-transcriptional regulation.

Next Generation Sequencing Technology and Genomewide Data Analysis: Perspectives for Retinal Research

PubMed Central

Chaitankar, Vijender; Karakülah, Gökhan; Ratnapriya, Rinki; Giuste, Felipe O.; Brooks, Matthew J.; Swaroop, Anand

2016-01-01

The advent of high throughput next generation sequencing (NGS) has accelerated the pace of discovery of disease-associated genetic variants and genomewide profiling of expressed sequences and epigenetic marks, thereby permitting systems-based analyses of ocular development and disease. Rapid evolution of NGS and associated methodologies presents significant challenges in acquisition, management, and analysis of large data sets and for extracting biologically or clinically relevant information. Here we illustrate the basic design of commonly used NGS-based methods, specifically whole exome sequencing, transcriptome, and epigenome profiling, and provide recommendations for data analyses. We briefly discuss systems biology approaches for integrating multiple data sets to elucidate gene regulatory or disease networks. While we provide examples from the retina, the NGS guidelines reviewed here are applicable to other tissues/cell types as well. PMID:27297499

Transcriptome Response Mediated by Cold Stress in Lotus japonicus.

PubMed

Calzadilla, Pablo I; Maiale, Santiago J; Ruiz, Oscar A; Escaray, Francisco J

2016-01-01

Members of the Lotus genus are important as agricultural forage sources under marginal environmental conditions given their high nutritional value and tolerance of various abiotic stresses. However, their dry matter production is drastically reduced in cooler seasons, while their response to such conditions is not well studied. This paper analyzes cold acclimation of the genus by studying Lotus japonicus over a stress period of 24 h. High-throughput RNA sequencing was used to identify and classify 1077 differentially expressed genes, of which 713 were up-regulated and 364 were down-regulated. Up-regulated genes were principally related to lipid, cell wall, phenylpropanoid, sugar, and proline regulation, while down-regulated genes affected the photosynthetic process and chloroplast development. Together, a total of 41 cold-inducible transcription factors were identified, including members of the AP2/ERF, NAC, MYB, and WRKY families; two of them were described as putative novel transcription factors. Finally, DREB1/CBFs were described with respect to their cold stress expression profiles. This is the first transcriptome profiling of the model legume L. japonicus under cold stress. Data obtained may be useful in identifying candidate genes for breeding modified species of forage legumes that more readily acclimate to low temperatures.

Data-Driven Discovery of Extravasation Pathway in Circulating Tumor Cells

PubMed Central

Yadavalli, S.; Jayaram, S.; Manda, S. S.; Madugundu, A. K.; Nayakanti, D. S.; Tan, T. Z.; Bhat, R.; Rangarajan, A.; Chatterjee, A.; Gowda, H.; Thiery, J. P.; Kumar, P.

2017-01-01

Circulating tumor cells (CTCs) play a crucial role in cancer dissemination and provide a promising source of blood-based markers. Understanding the spectrum of transcriptional profiles of CTCs and their corresponding regulatory mechanisms will allow for a more robust analysis of CTC phenotypes. The current challenge in CTC research is the acquisition of useful clinical information from the multitude of high-throughput studies. To gain a deeper understanding of CTC heterogeneity and identify genes, pathways and processes that are consistently affected across tumors, we mined the literature for gene expression profiles in CTCs. Through in silico analysis and the integration of CTC-specific genes, we found highly significant biological mechanisms and regulatory processes acting in CTCs across various cancers, with a particular enrichment of the leukocyte extravasation pathway. This pathway appears to play a pivotal role in the migration of CTCs to distant metastatic sites. We find that CTCs from multiple cancers express both epithelial and mesenchymal markers in varying amounts, which is suggestive of dynamic and hybrid states along the epithelial-mesenchymal transition (EMT) spectrum. Targeting the specific molecular nodes to monitor disease and therapeutic control of CTCs in real time will likely improve the clinical management of cancer progression and metastases. PMID:28262832

Systems genetics: a paradigm to improve discovery of candidate genes and mechanisms underlying complex traits.

PubMed

Feltus, F Alex

2014-06-01

Understanding the control of any trait optimally requires the detection of causal genes, gene interaction, and mechanism of action to discover and model the biochemical pathways underlying the expressed phenotype. Functional genomics techniques, including RNA expression profiling via microarray and high-throughput DNA sequencing, allow for the precise genome localization of biological information. Powerful genetic approaches, including quantitative trait locus (QTL) and genome-wide association study mapping, link phenotype with genome positions, yet genetics is less precise in localizing the relevant mechanistic information encoded in DNA. The coupling of salient functional genomic signals with genetically mapped positions is an appealing approach to discover meaningful gene-phenotype relationships. Techniques used to define this genetic-genomic convergence comprise the field of systems genetics. This short review will address an application of systems genetics where RNA profiles are associated with genetically mapped genome positions of individual genes (eQTL mapping) or as gene sets (co-expression network modules). Both approaches can be applied for knowledge independent selection of candidate genes (and possible control mechanisms) underlying complex traits where multiple, likely unlinked, genomic regions might control specific complex traits. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Drug-Path: a database for drug-induced pathways

PubMed Central

Zeng, Hui; Cui, Qinghua

2015-01-01

Some databases for drug-associated pathways have been built and are publicly available. However, the pathways curated in most of these databases are drug-action or drug-metabolism pathways. In recent years, high-throughput technologies such as microarray and RNA-sequencing have produced lots of drug-induced gene expression profiles. Interestingly, drug-induced gene expression profile frequently show distinct patterns, indicating that drugs normally induce the activation or repression of distinct pathways. Therefore, these pathways contribute to study the mechanisms of drugs and drug-repurposing. Here, we present Drug-Path, a database of drug-induced pathways, which was generated by KEGG pathway enrichment analysis for drug-induced upregulated genes and downregulated genes based on drug-induced gene expression datasets in Connectivity Map. Drug-Path provides user-friendly interfaces to retrieve, visualize and download the drug-induced pathway data in the database. In addition, the genes deregulated by a given drug are highlighted in the pathways. All data were organized using SQLite. The web site was implemented using Django, a Python web framework. Finally, we believe that this database will be useful for related researches. Database URL: http://www.cuilab.cn/drugpath PMID:26130661

Drug-Path: a database for drug-induced pathways.

PubMed

Zeng, Hui; Qiu, Chengxiang; Cui, Qinghua

2015-01-01

Some databases for drug-associated pathways have been built and are publicly available. However, the pathways curated in most of these databases are drug-action or drug-metabolism pathways. In recent years, high-throughput technologies such as microarray and RNA-sequencing have produced lots of drug-induced gene expression profiles. Interestingly, drug-induced gene expression profile frequently show distinct patterns, indicating that drugs normally induce the activation or repression of distinct pathways. Therefore, these pathways contribute to study the mechanisms of drugs and drug-repurposing. Here, we present Drug-Path, a database of drug-induced pathways, which was generated by KEGG pathway enrichment analysis for drug-induced upregulated genes and downregulated genes based on drug-induced gene expression datasets in Connectivity Map. Drug-Path provides user-friendly interfaces to retrieve, visualize and download the drug-induced pathway data in the database. In addition, the genes deregulated by a given drug are highlighted in the pathways. All data were organized using SQLite. The web site was implemented using Django, a Python web framework. Finally, we believe that this database will be useful for related researches. © The Author(s) 2015. Published by Oxford University Press.

Comparative Transcriptomic Characterization of the Early Development in Pacific White Shrimp Litopenaeus vannamei

PubMed Central

Wei, Jiankai; Zhang, Xiaojun; Yu, Yang; Huang, Hao; Li, Fuhua; Xiang, Jianhai

2014-01-01

Penaeid shrimp has a distinctive metamorphosis stage during early development. Although morphological and biochemical studies about this ontogeny have been developed for decades, researches on gene expression level are still scarce. In this study, we have investigated the transcriptomes of five continuous developmental stages in Pacific white shrimp (Litopenaeus vannamei) with high throughput Illumina sequencing technology. The reads were assembled and clustered into 66,815 unigenes, of which 32,398 have putative homologues in nr database, 14,981 have been classified into diverse functional categories by Gene Ontology (GO) annotation and 26,257 have been associated with 255 pathways by KEGG pathway mapping. Meanwhile, the differentially expressed genes (DEGs) between adjacent developmental stages were identified and gene expression patterns were clustered. By GO term enrichment analysis, KEGG pathway enrichment analysis and functional gene profiling, the physiological changes during shrimp metamorphosis could be better understood, especially histogenesis, diet transition, muscle development and exoskeleton reconstruction. In conclusion, this is the first study that characterized the integrated transcriptomic profiles during early development of penaeid shrimp, and these findings will serve as significant references for shrimp developmental biology and aquaculture research. PMID:25197823

Odor Coding by a Mammalian Receptor Repertoire

PubMed Central

Saito, Harumi; Chi, Qiuyi; Zhuang, Hanyi; Matsunami, Hiro; Mainland, Joel D.

2009-01-01

Deciphering olfactory encoding requires a thorough description of the ligands that activate each odorant receptor (OR). In mammalian systems, however, ligands are known for fewer than 50 of over 1400 human and mouse ORs, greatly limiting our understanding of olfactory coding. We performed high-throughput screening of 93 odorants against 464 ORs expressed in heterologous cells and identified agonists for 52 mouse and 10 human ORs. We used the resulting interaction profiles to develop a predictive model relating physicochemical odorant properties, OR sequences, and their interactions. Our results provide a basis for translating odorants into receptor neuron responses and unraveling mammalian odor coding. PMID:19261596

Species-specific predictive models of developmental toxicity using the ToxCast chemical library

EPA Science Inventory

EPA’s ToxCastTM project is profiling the in vitro bioactivity of chemicals to generate predictive models that correlate with observed in vivo toxicity. In vitro profiling methods are based on ToxCast data, consisting of over 600 high-throughput screening (HTS) and high-content sc...

ToxCast: Using high throughput screening to identify profiles of biological activity

EPA Science Inventory

ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry and bioactivity profiling to predict potential for toxicity and prioritize limited testing resources (www.epa.gov/toc...

Applications of high throughput screening to identify profiles of biological activity

EPA Science Inventory

ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry and bioactivity profiling to predict potential for toxicity and prioritize limited testing resources (www.epa.gov/toc...

Transcript profiling reveals expression differences in wild-type and glabrous soybean lines

PubMed Central

2011-01-01

Background Trichome hairs affect diverse agronomic characters such as seed weight and yield, prevent insect damage and reduce loss of water but their molecular control has not been extensively studied in soybean. Several detailed models for trichome development have been proposed for Arabidopsis thaliana, but their applicability to important crops such as cotton and soybean is not fully known. Results Two high throughput transcript sequencing methods, Digital Gene Expression (DGE) Tag Profiling and RNA-Seq, were used to compare the transcriptional profiles in wild-type (cv. Clark standard, CS) and a mutant (cv. Clark glabrous, i.e., trichomeless or hairless, CG) soybean isoline that carries the dominant P1 allele. DGE data and RNA-Seq data were mapped to the cDNAs (Glyma models) predicted from the reference soybean genome, Williams 82. Extending the model length by 250 bp at both ends resulted in significantly more matches of authentic DGE tags indicating that many of the predicted gene models are prematurely truncated at the 5' and 3' UTRs. The genome-wide comparative study of the transcript profiles of the wild-type versus mutant line revealed a number of differentially expressed genes. One highly-expressed gene, Glyma04g35130, in wild-type soybean was of interest as it has high homology to the cotton gene GhRDL1 gene that has been identified as being involved in cotton fiber initiation and is a member of the BURP protein family. Sequence comparison of Glyma04g35130 among Williams 82 with our sequences derived from CS and CG isolines revealed various SNPs and indels including addition of one nucleotide C in the CG and insertion of ~60 bp in the third exon of CS that causes a frameshift mutation and premature truncation of peptides in both lines as compared to Williams 82. Conclusion Although not a candidate for the P1 locus, a BURP family member (Glyma04g35130) from soybean has been shown to be abundantly expressed in the CS line and very weakly expressed in the glabrous CG line. RNA-Seq and DGE data are compared and provide experimental data on the expression of predicted soybean gene models as well as an overview of the genes expressed in young shoot tips of two closely related isolines. PMID:22029708

Comparison of Leaf Sheath Transcriptome Profiles with Physiological Traits of Bread Wheat Cultivars under Salinity Stress

PubMed Central

Trittermann, Christine; Berger, Bettina; Roy, Stuart J.; Seki, Motoaki; Shinozaki, Kazuo; Tester, Mark

2015-01-01

Salinity stress has significant negative effects on plant biomass production and crop yield. Salinity tolerance is controlled by complex systems of gene expression and ion transport. The relationship between specific features of mild salinity stress adaptation and gene expression was analyzed using four commercial varieties of bread wheat (Triticum aestivum) that have different levels of salinity tolerance. The high-throughput phenotyping system in The Plant Accelerator at the Australian Plant Phenomics Facility revealed variation in shoot relative growth rate and salinity tolerance among the four cultivars. Comparative analysis of gene expression in the leaf sheaths identified genes whose functions are potentially linked to shoot biomass development and salinity tolerance. Early responses to mild salinity stress through changes in gene expression have an influence on the acquisition of stress tolerance and improvement in biomass accumulation during the early “osmotic” phase of salinity stress. In addition, results revealed transcript profiles for the wheat cultivars that were different from those of usual stress-inducible genes, but were related to those of plant growth. These findings suggest that, in the process of breeding, selection of specific traits with various salinity stress-inducible genes in commercial bread wheat has led to adaptation to mild salinity conditions. PMID:26244554

Expression profiling of cardiovascular disease

PubMed Central

2004-01-01

Cardiovascular disease is the most important cause of morbidity and mortality in developed countries, causing twice as many deaths as cancer in the USA. The major cardiovascular diseases, including coronary artery disease (CAD), myocardial infarction (MI), congestive heart failure (CHF) and common congenital heart disease (CHD), are caused by multiple genetic and environmental factors, as well as the interactions between them. The underlying molecular pathogenic mechanisms for these disorders are still largely unknown, but gene expression may play a central role in the development and progression of cardiovascular disease. Microarrays are high-throughput genomic tools that allow the comparison of global expression changes in thousands of genes between normal and diseased cells/tissues. Microarrays have recently been applied to CAD/MI, CHF and CHD to profile changes in gene expression patterns in diseased and non-diseased patients. This same technology has also been used to characterise endothelial cells, vascular smooth muscle cells and inflammatory cells, with or without various treatments that mimic disease processes involved in CAD/MI. These studies have led to the identification of unique subsets of genes associated with specific diseases and disease processes. Ongoing microarray studies in the field will provide insights into the molecular mechanism of cardiovascular disease and may generate new diagnostic and therapeutic markers. PMID:15588496

BATS: a Bayesian user-friendly software for analyzing time series microarray experiments.

PubMed

Angelini, Claudia; Cutillo, Luisa; De Canditiis, Daniela; Mutarelli, Margherita; Pensky, Marianna

2008-10-06

Gene expression levels in a given cell can be influenced by different factors, namely pharmacological or medical treatments. The response to a given stimulus is usually different for different genes and may depend on time. One of the goals of modern molecular biology is the high-throughput identification of genes associated with a particular treatment or a biological process of interest. From methodological and computational point of view, analyzing high-dimensional time course microarray data requires very specific set of tools which are usually not included in standard software packages. Recently, the authors of this paper developed a fully Bayesian approach which allows one to identify differentially expressed genes in a 'one-sample' time-course microarray experiment, to rank them and to estimate their expression profiles. The method is based on explicit expressions for calculations and, hence, very computationally efficient. The software package BATS (Bayesian Analysis of Time Series) presented here implements the methodology described above. It allows an user to automatically identify and rank differentially expressed genes and to estimate their expression profiles when at least 5-6 time points are available. The package has a user-friendly interface. BATS successfully manages various technical difficulties which arise in time-course microarray experiments, such as a small number of observations, non-uniform sampling intervals and replicated or missing data. BATS is a free user-friendly software for the analysis of both simulated and real microarray time course experiments. The software, the user manual and a brief illustrative example are freely available online at the BATS website: http://www.na.iac.cnr.it/bats.

Microfluidic-SANS: insitu molecular insight into complex fluid processing and high throughput characterisation

NASA Astrophysics Data System (ADS)

Lopez, Carlos; Watanabe, Takaichi; Cabral, Joao; Graham, Peter; Porcar, Lionel; Martel, Anne

2014-03-01

The coupling of microfluidics and small angle neutron scattering (SANS) is successfully demonstrated for the first time. We have developed novel microdevices with suitably low SANS background and high pressure compatibility for the investigation of flow-induced phenomena and high throughput phase mapping of complex fluids. We successfully obtained scattering profiles from 50 micron channels, in 10s - 100s second acquisition times. The microfluidic geometry enables the variation of both flow type and magnitude, beyond traditional rheo-SANS setups, and is exceptionally well-suited for complex fluids due to the commensurability of relevant time and lengthscales. We demonstrate our approach by studying model flow responsive systems, including surfactant/co-surfactant/water mixtures, with well-known equilibrium phase behaviour,: sodium dodecyl sulfate (SDS)/octanol/brine, cetyltrimethyl ammonium chloride (C16TAC)/pentanol/water and a model microemulsion system (C10E4 /decane/ D20), as well as polyelectrolyte solutions. Finally, using an online micromixer we are able to implement a high throughput approach, scanning in excess of 10 scattering profiles/min for a continuous aqueous surfactant dilution over two decades in concentration.

NCBI GEO: mining millions of expression profiles--database and tools.

PubMed

Barrett, Tanya; Suzek, Tugba O; Troup, Dennis B; Wilhite, Stephen E; Ngau, Wing-Chi; Ledoux, Pierre; Rudnev, Dmitry; Lash, Alex E; Fujibuchi, Wataru; Edgar, Ron

2005-01-01

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest fully public repository for high-throughput molecular abundance data, primarily gene expression data. The database has a flexible and open design that allows the submission, storage and retrieval of many data types. These data include microarray-based experiments measuring the abundance of mRNA, genomic DNA and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. GEO currently holds over 30,000 submissions representing approximately half a billion individual molecular abundance measurements, for over 100 organisms. Here, we describe recent database developments that facilitate effective mining and visualization of these data. Features are provided to examine data from both experiment- and gene-centric perspectives using user-friendly Web-based interfaces accessible to those without computational or microarray-related analytical expertise. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

Using Genome-Wide Expression Profiling to Define Gene Networks Relevant to the Study of Complex Traits: From RNA Integrity to Network Topology

PubMed Central

O'Brien, M.A.; Costin, B.N.; Miles, M.F.

2014-01-01

Postgenomic studies of the function of genes and their role in disease have now become an area of intense study since efforts to define the raw sequence material of the genome have largely been completed. The use of whole-genome approaches such as microarray expression profiling and, more recently, RNA-sequence analysis of transcript abundance has allowed an unprecedented look at the workings of the genome. However, the accurate derivation of such high-throughput data and their analysis in terms of biological function has been critical to truly leveraging the postgenomic revolution. This chapter will describe an approach that focuses on the use of gene networks to both organize and interpret genomic expression data. Such networks, derived from statistical analysis of large genomic datasets and the application of multiple bioinformatics data resources, poten-tially allow the identification of key control elements for networks associated with human disease, and thus may lead to derivation of novel therapeutic approaches. However, as discussed in this chapter, the leveraging of such networks cannot occur without a thorough understanding of the technical and statistical factors influencing the derivation of genomic expression data. Thus, while the catch phrase may be “it's the network … stupid,” the understanding of factors extending from RNA isolation to genomic profiling technique, multivariate statistics, and bioinformatics are all critical to defining fully useful gene networks for study of complex biology. PMID:23195313

Genome-wide transcriptome and expression profile analysis of Phalaenopsis during explant browning.

PubMed

Xu, Chuanjun; Zeng, Biyu; Huang, Junmei; Huang, Wen; Liu, Yumei

2015-01-01

Explant browning presents a major problem for in vitro culture, and can lead to the death of the explant and failure of regeneration. Considerable work has examined the physiological mechanisms underlying Phalaenopsis leaf explant browning, but the molecular mechanisms of browning remain elusive. In this study, we used whole genome RNA sequencing to examine Phalaenopsis leaf explant browning at genome-wide level. We first used Illumina high-throughput technology to sequence the transcriptome of Phalaenopsis and then performed de novo transcriptome assembly. We assembled 79,434,350 clean reads into 31,708 isogenes and generated 26,565 annotated unigenes. We assigned Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations, and potential Pfam domains to each transcript. Using the transcriptome data as a reference, we next analyzed the differential gene expression of explants cultured for 0, 3, and 6 d, respectively. We then identified differentially expressed genes (DEGs) before and after Phalaenopsis explant browning. We also performed GO, KEGG functional enrichment and Pfam analysis of all DEGs. Finally, we selected 11 genes for quantitative real-time PCR (qPCR) analysis to confirm the expression profile analysis. Here, we report the first comprehensive analysis of transcriptome and expression profiles during Phalaenopsis explant browning. Our results suggest that Phalaenopsis explant browning may be due in part to gene expression changes that affect the secondary metabolism, such as: phenylpropanoid pathway and flavonoid biosynthesis. Genes involved in photosynthesis and ATPase activity have been found to be changed at transcription level; these changes may perturb energy metabolism and thus lead to the decay of plant cells and tissues. This study provides comprehensive gene expression data for Phalaenopsis browning. Our data constitute an important resource for further functional studies to prevent explant browning.

Genome-Wide Transcriptome and Expression Profile Analysis of Phalaenopsis during Explant Browning

PubMed Central

Xu, Chuanjun; Zeng, Biyu; Huang, Junmei; Huang, Wen; Liu, Yumei

2015-01-01

Background Explant browning presents a major problem for in vitro culture, and can lead to the death of the explant and failure of regeneration. Considerable work has examined the physiological mechanisms underlying Phalaenopsis leaf explant browning, but the molecular mechanisms of browning remain elusive. In this study, we used whole genome RNA sequencing to examine Phalaenopsis leaf explant browning at genome-wide level. Methodology/Principal Findings We first used Illumina high-throughput technology to sequence the transcriptome of Phalaenopsis and then performed de novo transcriptome assembly. We assembled 79,434,350 clean reads into 31,708 isogenes and generated 26,565 annotated unigenes. We assigned Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations, and potential Pfam domains to each transcript. Using the transcriptome data as a reference, we next analyzed the differential gene expression of explants cultured for 0, 3, and 6 d, respectively. We then identified differentially expressed genes (DEGs) before and after Phalaenopsis explant browning. We also performed GO, KEGG functional enrichment and Pfam analysis of all DEGs. Finally, we selected 11 genes for quantitative real-time PCR (qPCR) analysis to confirm the expression profile analysis. Conclusions/Significance Here, we report the first comprehensive analysis of transcriptome and expression profiles during Phalaenopsis explant browning. Our results suggest that Phalaenopsis explant browning may be due in part to gene expression changes that affect the secondary metabolism, such as: phenylpropanoid pathway and flavonoid biosynthesis. Genes involved in photosynthesis and ATPase activity have been found to be changed at transcription level; these changes may perturb energy metabolism and thus lead to the decay of plant cells and tissues. This study provides comprehensive gene expression data for Phalaenopsis browning. Our data constitute an important resource for further functional studies to prevent explant browning. PMID:25874455

The Development of Protein Microarrays and Their Applications in DNA-Protein and Protein-Protein Interaction Analyses of Arabidopsis Transcription Factors

PubMed Central

Gong, Wei; He, Kun; Covington, Mike; Dinesh-Kumar, S. P.; Snyder, Michael; Harmer, Stacey L.; Zhu, Yu-Xian; Deng, Xing Wang

2009-01-01

We used our collection of Arabidopsis transcription factor (TF) ORFeome clones to construct protein microarrays containing as many as 802 TF proteins. These protein microarrays were used for both protein-DNA and protein-protein interaction analyses. For protein-DNA interaction studies, we examined AP2/ERF family TFs and their cognate cis-elements. By careful comparison of the DNA-binding specificity of 13 TFs on the protein microarray with previous non-microarray data, we showed that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions. This microarray protein-DNA interaction analysis allowed us to derive a comprehensive view of DNA-binding profiles of AP2/ERF family proteins in Arabidopsis. It also revealed four TFs that bound the EE (evening element) and had the expected phased gene expression under clock-regulation, thus providing a basis for further functional analysis of their roles in clock regulation of gene expression. We also developed procedures for detecting protein interactions using this TF protein microarray and discovered four novel partners that interact with HY5, which can be validated by yeast two-hybrid assays. Thus, plant TF protein microarrays offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale. PMID:19802365

Microfluidic technologies for synthetic biology.

PubMed

Vinuselvi, Parisutham; Park, Seongyong; Kim, Minseok; Park, Jung Min; Kim, Taesung; Lee, Sung Kuk

2011-01-01

Microfluidic technologies have shown powerful abilities for reducing cost, time, and labor, and at the same time, for increasing accuracy, throughput, and performance in the analysis of biological and biochemical samples compared with the conventional, macroscale instruments. Synthetic biology is an emerging field of biology and has drawn much attraction due to its potential to create novel, functional biological parts and systems for special purposes. Since it is believed that the development of synthetic biology can be accelerated through the use of microfluidic technology, in this review work we focus our discussion on the latest microfluidic technologies that can provide unprecedented means in synthetic biology for dynamic profiling of gene expression/regulation with high resolution, highly sensitive on-chip and off-chip detection of metabolites, and whole-cell analysis.

High-throughput SNP discovery and transcriptome expression profiles from the salmon louse Caligus rogercresseyi (Copepoda: Caligidae).

PubMed

Nuñez-Acuña, Gustavo; Valenzuela-Muñoz, Valentina; Gallardo-Escárate, Cristian

2014-06-01

The salmon louse Caligus rogercresseyi is the dominant ectoparasite species affecting the salmon aquaculture industry in the Southern hemisphere, and it is currently the main cause for economic losses in Chilean aquaculture. However, despite the great concern over Caligus infestations, genomic information on this louse is still scarce, even while the need to develop high-resolution molecular markers is growing. This study provides the first deep transcriptome survey to identify thousands of SNP markers from C. rogercresseyi, with a total of 69,466 SNPs identified using the MiSeq platform (Illumina®), 30,605 (52%) of which were found in contigs successfully annotated against known protein databases. Furthermore, in silico gene expression profiles associated with SNP variants were evaluated, and the results evidenced a wide array of genes that were down- and upregulated throughout the developmental stages of C. rogercresseyi. Interestingly, putative KEGG pathways involved in resistance to antiparasitic agents were also identified, where ten pathways were associated with the nervous system and one was related to ABC transporters. Taken together, this information could be highly useful for investigating the molecular underpinnings involved in the susceptibility or resistance of salmon lice to chemical treatments. Copyright © 2014 Elsevier Inc. All rights reserved.

Analysis of translation using polysome profiling

PubMed Central

Chassé, Héloïse; Boulben, Sandrine; Costache, Vlad; Cormier, Patrick

2017-01-01

Abstract During the past decade, there has been growing interest in the role of translational regulation of gene expression in many organisms. Polysome profiling has been developed to infer the translational status of a specific mRNA species or to analyze the translatome, i.e. the subset of mRNAs actively translated in a cell. Polysome profiling is especially suitable for emergent model organisms for which genomic data are limited. In this paper, we describe an optimized protocol for the purification of sea urchin polysomes and highlight the critical steps involved in polysome purification. We applied this protocol to obtain experimental results on translational regulation of mRNAs following fertilization. Our protocol should prove useful for integrating the study of the role of translational regulation in gene regulatory networks in any biological model. In addition, we demonstrate how to carry out high-throughput processing of polysome gradient fractions, for the simultaneous screening of multiple biological conditions and large-scale preparation of samples for next-generation sequencing. PMID:28180329

Analytical workflow profiling gene expression in murine macrophages

PubMed Central

Nixon, Scott E.; González-Peña, Dianelys; Lawson, Marcus A.; McCusker, Robert H.; Hernandez, Alvaro G.; O’Connor, Jason C.; Dantzer, Robert; Kelley, Keith W.

2015-01-01

Comprehensive and simultaneous analysis of all genes in a biological sample is a capability of RNA-Seq technology. Analysis of the entire transcriptome benefits from summarization of genes at the functional level. As a cellular response of interest not previously explored with RNA-Seq, peritoneal macrophages from mice under two conditions (control and immunologically challenged) were analyzed for gene expression differences. Quantification of individual transcripts modeled RNA-Seq read distribution and uncertainty (using a Beta Negative Binomial distribution), then tested for differential transcript expression (False Discovery Rate-adjusted p-value < 0.05). Enrichment of functional categories utilized the list of differentially expressed genes. A total of 2079 differentially expressed transcripts representing 1884 genes were detected. Enrichment of 92 categories from Gene Ontology Biological Processes and Molecular Functions, and KEGG pathways were grouped into 6 clusters. Clusters included defense and inflammatory response (Enrichment Score = 11.24) and ribosomal activity (Enrichment Score = 17.89). Our work provides a context to the fine detail of individual gene expression differences in murine peritoneal macrophages during immunological challenge with high throughput RNA-Seq. PMID:25708305

A high-throughput approach to profile RNA structure.

PubMed

Delli Ponti, Riccardo; Marti, Stefanie; Armaos, Alexandros; Tartaglia, Gian Gaetano

2017-03-17

Here we introduce the Computational Recognition of Secondary Structure (CROSS) method to calculate the structural profile of an RNA sequence (single- or double-stranded state) at single-nucleotide resolution and without sequence length restrictions. We trained CROSS using data from high-throughput experiments such as Selective 2΄-Hydroxyl Acylation analyzed by Primer Extension (SHAPE; Mouse and HIV transcriptomes) and Parallel Analysis of RNA Structure (PARS; Human and Yeast transcriptomes) as well as high-quality NMR/X-ray structures (PDB database). The algorithm uses primary structure information alone to predict experimental structural profiles with >80% accuracy, showing high performances on large RNAs such as Xist (17 900 nucleotides; Area Under the ROC Curve AUC of 0.75 on dimethyl sulfate (DMS) experiments). We integrated CROSS in thermodynamics-based methods to predict secondary structure and observed an increase in their predictive power by up to 30%. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Applications of high throughput screening to identify profiles of biological activity relevant to carcinogenesis

EPA Science Inventory

ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry and bioactivity profiling to predict potential for toxicity and prioritize limited testing resources (www.epa.gov/toc...

Automated Purification of Recombinant Proteins: Combining High-throughput with High Yield

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

Lin, Chiann Tso; Moore, Priscilla A.; Auberry, Deanna L.

2006-05-01

Protein crystallography, mapping protein interactions and other approaches of current functional genomics require not only purifying large numbers of proteins but also obtaining sufficient yield and homogeneity for downstream high-throughput applications. There is a need for the development of robust automated high-throughput protein expression and purification processes to meet these requirements. We developed and compared two alternative workflows for automated purification of recombinant proteins based on expression of bacterial genes in Escherichia coli: First - a filtration separation protocol based on expression of 800 ml E. coli cultures followed by filtration purification using Ni2+-NTATM Agarose (Qiagen). Second - a smallermore » scale magnetic separation method based on expression in 25 ml cultures of E.coli followed by 96-well purification on MagneHisTM Ni2+ Agarose (Promega). Both workflows provided comparable average yields of proteins about 8 ug of purified protein per unit of OD at 600 nm of bacterial culture. We discuss advantages and limitations of the automated workflows that can provide proteins more than 90 % pure in the range of 100 ug – 45 mg per purification run as well as strategies for optimization of these protocols.« less

Phage phenomics: Physiological approaches to characterize novel viral proteins

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

Sanchez, Savannah E.; Cuevas, Daniel A.; Rostron, Jason E.

Current investigations into phage-host interactions are dependent on extrapolating knowledge from (meta)genomes. Interestingly, 60 - 95% of all phage sequences share no homology to current annotated proteins. As a result, a large proportion of phage genes are annotated as hypothetical. This reality heavily affects the annotation of both structural and auxiliary metabolic genes. Here we present phenomic methods designed to capture the physiological response(s) of a selected host during expression of one of these unknown phage genes. Multi-phenotype Assay Plates (MAPs) are used to monitor the diversity of host substrate utilization and subsequent biomass formation, while metabolomics provides bi-product analysismore » by monitoring metabolite abundance and diversity. Both tools are used simultaneously to provide a phenotypic profile associated with expression of a single putative phage open reading frame (ORF). Thus, representative results for both methods are compared, highlighting the phenotypic profile differences of a host carrying either putative structural or metabolic phage genes. In addition, the visualization techniques and high throughput computational pipelines that facilitated experimental analysis are presented.« less

Phage phenomics: Physiological approaches to characterize novel viral proteins

DOE PAGES

Sanchez, Savannah E.; Cuevas, Daniel A.; Rostron, Jason E.; ...

2015-06-11

Current investigations into phage-host interactions are dependent on extrapolating knowledge from (meta)genomes. Interestingly, 60 - 95% of all phage sequences share no homology to current annotated proteins. As a result, a large proportion of phage genes are annotated as hypothetical. This reality heavily affects the annotation of both structural and auxiliary metabolic genes. Here we present phenomic methods designed to capture the physiological response(s) of a selected host during expression of one of these unknown phage genes. Multi-phenotype Assay Plates (MAPs) are used to monitor the diversity of host substrate utilization and subsequent biomass formation, while metabolomics provides bi-product analysismore » by monitoring metabolite abundance and diversity. Both tools are used simultaneously to provide a phenotypic profile associated with expression of a single putative phage open reading frame (ORF). Thus, representative results for both methods are compared, highlighting the phenotypic profile differences of a host carrying either putative structural or metabolic phage genes. In addition, the visualization techniques and high throughput computational pipelines that facilitated experimental analysis are presented.« less

Integrated automation for continuous high-throughput synthetic chromosome assembly and transformation to identify improved yeast strains for industrial production of peptide sweetener brazzein

USDA-ARS?s Scientific Manuscript database

Production and recycling of recombinant sweetener peptides in industrial biorefineries involves the evaluation of large numbers of genes and proteins. High-throughput integrated robotic molecular biology platforms that have the capacity to rapidly synthesize, clone, and express heterologous gene ope...

HTP-NLP: A New NLP System for High Throughput Phenotyping.

PubMed

Schlegel, Daniel R; Crowner, Chris; Lehoullier, Frank; Elkin, Peter L

2017-01-01

Secondary use of clinical data for research requires a method to quickly process the data so that researchers can quickly extract cohorts. We present two advances in the High Throughput Phenotyping NLP system which support the aim of truly high throughput processing of clinical data, inspired by a characterization of the linguistic properties of such data. Semantic indexing to store and generalize partially-processed results and the use of compositional expressions for ungrammatical text are discussed, along with a set of initial timing results for the system.

Profiling Cholinesterase Adduction: A High-Throughput Prioritization Method for Organophosphate Exposure Samples

PubMed Central

Carter, Melissa D.; Crow, Brian S.; Pantazides, Brooke G.; Watson, Caroline M.; deCastro, B. Rey; Thomas, Jerry D.; Blake, Thomas A.; Johnson, Rudolph C.

2017-01-01

A high-throughput prioritization method was developed for use with a validated confirmatory method detecting organophosphorus nerve agent exposure by immunomagnetic separation-HPLC-MS/MS. A ballistic gradient was incorporated into this analytical method in order to profile unadducted butyrylcholinesterase (BChE) in clinical samples. With Zhang, et al. 1999’s Z′-factor of 0.88 ± 0.01 (SD) of control analytes and Z-factor of 0.25 ± 0.06 (SD) of serum samples, the assay is rated an “excellent assay” for the synthetic peptide controls used and a “double assay” when used to prioritize clinical samples. Hits, defined as samples containing BChE Ser-198 adducts or no BChE present, were analyzed in a confirmatory method for identification and quantitation of the BChE adduct, if present. The ability to prioritize samples by highest exposure for confirmatory analysis is of particular importance in an exposure to cholinesterase inhibitors such as organophosphorus nerve agents where a large number of clinical samples may be collected. In an initial blind screen, 67 out of 70 samples were accurately identified giving an assay accuracy of 96% and yielded no false negatives. The method is the first to provide a high-throughput prioritization assay for profiling adduction of Ser-198 BChE in clinical samples. PMID:23954929

Improved Selection of Internal Transcribed Spacer-Specific Primers Enables Quantitative, Ultra-High-Throughput Profiling of Fungal Communities

PubMed Central

Bokulich, Nicholas A.

2013-01-01

Ultra-high-throughput sequencing (HTS) of fungal communities has been restricted by short read lengths and primer amplification bias, slowing the adoption of newer sequencing technologies to fungal community profiling. To address these issues, we evaluated the performance of several common internal transcribed spacer (ITS) primers and designed a novel primer set and work flow for simultaneous quantification and species-level interrogation of fungal consortia. Primer comparison and validation were predicted in silico and by sequencing a “mock community” of mixed yeast species to explore the challenges of amplicon length and amplification bias for reconstructing defined yeast community structures. The amplicon size and distribution of this primer set are smaller than for all preexisting ITS primer sets, maximizing sequencing coverage of hypervariable ITS domains by very-short-amplicon, high-throughput sequencing platforms. This feature also enables the optional integration of quantitative PCR (qPCR) directly into the HTS preparatory work flow by substituting qPCR with these primers for standard PCR, yielding quantification of individual community members. The complete work flow described here, utilizing any of the qualified primer sets evaluated, can rapidly profile mixed fungal communities and capably reconstructed well-characterized beer and wine fermentation fungal communities. PMID:23377949

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

PubMed Central

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

2012-01-01

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

Industrializing electrophysiology: HT automated patch clamp on SyncroPatch® 96 using instant frozen cells.

PubMed

Polonchuk, Liudmila

2014-01-01

Patch-clamping is a powerful technique for investigating the ion channel function and regulation. However, its low throughput hampered profiling of large compound series in early drug development. Fortunately, automation has revolutionized the area of experimental electrophysiology over the past decade. Whereas the first automated patch-clamp instruments using the planar patch-clamp technology demonstrated rather a moderate throughput, few second-generation automated platforms recently launched by various companies have significantly increased ability to form a high number of high-resistance seals. Among them is SyncroPatch(®) 96 (Nanion Technologies GmbH, Munich, Germany), a fully automated giga-seal patch-clamp system with the highest throughput on the market. By recording from up to 96 cells simultaneously, the SyncroPatch(®) 96 allows to substantially increase throughput without compromising data quality. This chapter describes features of the innovative automated electrophysiology system and protocols used for a successful transfer of the established hERG assay to this high-throughput automated platform.

[Weighted gene co-expression network analysis in biomedicine research].

PubMed

Liu, Wei; Li, Li; Ye, Hua; Tu, Wei

2017-11-25

High-throughput biological technologies are now widely applied in biology and medicine, allowing scientists to monitor thousands of parameters simultaneously in a specific sample. However, it is still an enormous challenge to mine useful information from high-throughput data. The emergence of network biology provides deeper insights into complex bio-system and reveals the modularity in tissue/cellular networks. Correlation networks are increasingly used in bioinformatics applications. Weighted gene co-expression network analysis (WGCNA) tool can detect clusters of highly correlated genes. Therefore, we systematically reviewed the application of WGCNA in the study of disease diagnosis, pathogenesis and other related fields. First, we introduced principle, workflow, advantages and disadvantages of WGCNA. Second, we presented the application of WGCNA in disease, physiology, drug, evolution and genome annotation. Then, we indicated the application of WGCNA in newly developed high-throughput methods. We hope this review will help to promote the application of WGCNA in biomedicine research.

A simple dual online ultra-high pressure liquid chromatography system (sDO-UHPLC) for high throughput proteome analysis.

PubMed

Lee, Hangyeore; Mun, Dong-Gi; Bae, Jingi; Kim, Hokeun; Oh, Se Yeon; Park, Young Soo; Lee, Jae-Hyuk; Lee, Sang-Won

2015-08-21

We report a new and simple design of a fully automated dual-online ultra-high pressure liquid chromatography system. The system employs only two nano-volume switching valves (a two-position four port valve and a two-position ten port valve) that direct solvent flows from two binary nano-pumps for parallel operation of two analytical columns and two solid phase extraction (SPE) columns. Despite the simple design, the sDO-UHPLC offers many advantageous features that include high duty cycle, back flushing sample injection for fast and narrow zone sample injection, online desalting, high separation resolution and high intra/inter-column reproducibility. This system was applied to analyze proteome samples not only in high throughput deep proteome profiling experiments but also in high throughput MRM experiments.

Genome editing in the mushroom-forming basidiomycete Coprinopsis cinerea, optimized by a high-throughput transformation system.

PubMed

Sugano, Shigeo S; Suzuki, Hiroko; Shimokita, Eisuke; Chiba, Hirofumi; Noji, Sumihare; Osakabe, Yuriko; Osakabe, Keishi

2017-04-28

Mushroom-forming basidiomycetes produce a wide range of metabolites and have great value not only as food but also as an important global natural resource. Here, we demonstrate CRISPR/Cas9-based genome editing in the model species Coprinopsis cinerea. Using a high-throughput reporter assay with cryopreserved protoplasts, we identified a novel promoter, CcDED1 pro , with seven times stronger activity in this assay than the conventional promoter GPD2. To develop highly efficient genome editing using CRISPR/Cas9 in C. cinerea, we used the CcDED1 pro to express Cas9 and a U6-snRNA promoter from C. cinerea to express gRNA. Finally, CRISPR/Cas9-mediated GFP mutagenesis was performed in a stable GFP expression line. Individual genome-edited lines were isolated, and loss of GFP function was detected in hyphae and fruiting body primordia. This novel method of high-throughput CRISPR/Cas9-based genome editing using cryopreserved protoplasts should be a powerful tool in the study of edible mushrooms.

High throughput and miniaturised systems for biodegradability assessments.

PubMed

Cregut, Mickael; Jouanneau, Sulivan; Brillet, François; Durand, Marie-José; Sweetlove, Cyril; Chenèble, Jean-Charles; L'Haridon, Jacques; Thouand, Gérald

2014-01-01

The society demands safer products with a better ecological profile. Regulatory criteria have been developed to prevent risks for human health and the environment, for example, within the framework of the European regulation REACH (Regulation (EC) No 1907, 2006). This has driven industry to consider the development of high throughput screening methodologies for assessing chemical biodegradability. These new screening methodologies must be scalable for miniaturisation, reproducible and as reliable as existing procedures for enhanced biodegradability assessment. Here, we evaluate two alternative systems that can be scaled for high throughput screening and conveniently miniaturised to limit costs in comparison with traditional testing. These systems are based on two dyes as follows: an invasive fluorescent dyes that serves as a cellular activity marker (a resazurin-like dye reagent) and a noninvasive fluorescent oxygen optosensor dye (an optical sensor). The advantages and limitations of these platforms for biodegradability assessment are presented. Our results confirm the feasibility of these systems for evaluating and screening chemicals for ready biodegradability. The optosensor is a miniaturised version of a component already used in traditional ready biodegradability testing, whereas the resazurin dye offers an interesting new screening mechanism for chemical concentrations greater than 10 mg/l that are not amenable to traditional closed bottle tests. The use of these approaches allows generalisation of high throughput screening methodologies to meet the need of developing new compounds with a favourable ecological profile and also assessment for regulatory purpose.

High throughput 16SrRNA gene sequencing reveals the correlation between Propionibacterium acnes and sarcoidosis.

PubMed

Zhao, Meng-Meng; Du, Shan-Shan; Li, Qiu-Hong; Chen, Tao; Qiu, Hui; Wu, Qin; Chen, Shan-Shan; Zhou, Ying; Zhang, Yuan; Hu, Yang; Su, Yi-Liang; Shen, Li; Zhang, Fen; Weng, Dong; Li, Hui-Ping

2017-02-01

This study aims to use high throughput 16SrRNA gene sequencing to examine the bacterial profile of lymph node biopsy samples of patients with sarcoidosis and to further verify the association between Propionibacterium acnes (P. acnes) and sarcoidosis. A total of 36 mediastinal lymph node biopsy specimens were collected from 17 cases of sarcoidosis, 8 tuberculosis (TB group), and 11 non-infectious lung diseases (control group). The V4 region of the bacterial 16SrRNA gene in the specimens was amplified and sequenced using the high throughput sequencing platform MiSeq, and bacterial profile was established. The data analysis software QIIME and Metastats were used to compare bacterial relative abundance in the three patient groups. Overall, 545 genera were identified; 38 showed significantly lower and 29 had significantly higher relative abundance in the sarcoidosis group than in the TB and control groups (P < 0.01). P. acnes 16SrRNA was exclusively found in all the 17 samples of the sarcoidosis group, whereas was not detected in the TB and control groups. The relative abundance of P. acnes in the sarcoidosis group (0.16% ± 0. 11%) was significantly higher than that in the TB (Metastats analysis: P = 0.0010, q = 0.0044) and control groups (Metastats analysis: P = 0.0010, q = 0.0038). The relative abundance of P. granulosum was only 0.0022% ± 0. 0044% in the sarcoidosis group. P. granulosum 16SrRNA was not detected in the other two groups. High throughput 16SrRNA gene sequencing appears to be a useful tool to investigate the bacterial profile of sarcoidosis specimens. The results suggest that P. acnes may be involved in sarcoidosis development.

Molecular-genetic profiling and high-throughput in vitro drug screening in NUT midline carcinoma—an aggressive and fatal disease

PubMed Central

Stirnweiss, Anja; Oommen, Joyce; Kotecha, Rishi S.; Kees, Ursula R.; Beesley, Alex H.

2017-01-01

NUT midline carcinoma (NMC) is a rare and aggressive cancer, with survival typically less than seven months, that can arise in people of any age. Genetically, NMC is defined by the chromosomal fusion of NUTM1 with a chromatin-binding partner, typically the bromodomain-containing protein BRD4. However, little is known about other genetic aberrations in this disease. In this study, we used a unique panel of cell lines to describe the molecular-genetic features of NMC. Next-generation sequencing identified a recurring high-impact mutation in the DNA-helicase gene RECQL5 in 75% of lines studied, and biological signals from mutation-signature and network analyses consistent with a general failure in DNA-repair. A high-throughput drug screen confirmed that microtubule inhibitors, topoisomerase inhibitors and anthracyclines are highly cytotoxic in the majority of NMC lines, and that cell lines expressing the BRD4-NUTM1 (exon11:exon2) variant are an order of magnitude more responsive to bromodomain inhibitors (iBETs) on average than those with other BRD4-NUTM1 translocation variants. We also identified a highly significant correlation between iBET and aurora kinase inhibitor efficacy in this study. Integration of exome sequencing, transcriptome, and drug sensitivity profiles suggested that aberrant activity of the nuclear receptor co-activator NCOA3 may correlate with poor response to iBETs. In conclusion, our data emphasize the heterogeneity of NMC and highlights genetic aberrations that could be explored to improve therapeutic strategies. The novel finding of a recurring RECQL5 mutation, together with recent reports of chromoplexy in this disease, suggests that DNA-repair pathways are likely to play a central role in NMC tumorigenesis. PMID:29348827

Absolute quantification of microbial taxon abundances.

PubMed

Props, Ruben; Kerckhof, Frederiek-Maarten; Rubbens, Peter; De Vrieze, Jo; Hernandez Sanabria, Emma; Waegeman, Willem; Monsieurs, Pieter; Hammes, Frederik; Boon, Nico

2017-02-01

High-throughput amplicon sequencing has become a well-established approach for microbial community profiling. Correlating shifts in the relative abundances of bacterial taxa with environmental gradients is the goal of many microbiome surveys. As the abundances generated by this technology are semi-quantitative by definition, the observed dynamics may not accurately reflect those of the actual taxon densities. We combined the sequencing approach (16S rRNA gene) with robust single-cell enumeration technologies (flow cytometry) to quantify the absolute taxon abundances. A detailed longitudinal analysis of the absolute abundances resulted in distinct abundance profiles that were less ambiguous and expressed in units that can be directly compared across studies. We further provide evidence that the enrichment of taxa (increase in relative abundance) does not necessarily relate to the outgrowth of taxa (increase in absolute abundance). Our results highlight that both relative and absolute abundances should be considered for a comprehensive biological interpretation of microbiome surveys.

Data Reduction Approaches for Dissecting Transcriptional Effects on Metabolism

PubMed Central

Schwahn, Kevin; Nikoloski, Zoran

2018-01-01

The availability of high-throughput data from transcriptomics and metabolomics technologies provides the opportunity to characterize the transcriptional effects on metabolism. Here we propose and evaluate two computational approaches rooted in data reduction techniques to identify and categorize transcriptional effects on metabolism by combining data on gene expression and metabolite levels. The approaches determine the partial correlation between two metabolite data profiles upon control of given principal components extracted from transcriptomics data profiles. Therefore, they allow us to investigate both data types with all features simultaneously without doing preselection of genes. The proposed approaches allow us to categorize the relation between pairs of metabolites as being under transcriptional or post-transcriptional regulation. The resulting classification is compared to existing literature and accumulated evidence about regulatory mechanism of reactions and pathways in the cases of Escherichia coli, Saccharomycies cerevisiae, and Arabidopsis thaliana. PMID:29731765

Diversity amongst trigeminal neurons revealed by high throughput single cell sequencing

PubMed Central

Nguyen, Minh Q.; Wu, Youmei; Bonilla, Lauren S.; von Buchholtz, Lars J.

2017-01-01

The trigeminal ganglion contains somatosensory neurons that detect a range of thermal, mechanical and chemical cues and innervate unique sensory compartments in the head and neck including the eyes, nose, mouth, meninges and vibrissae. We used single-cell sequencing and in situ hybridization to examine the cellular diversity of the trigeminal ganglion in mice, defining thirteen clusters of neurons. We show that clusters are well conserved in dorsal root ganglia suggesting they represent distinct functional classes of somatosensory neurons and not specialization associated with their sensory targets. Notably, functionally important genes (e.g. the mechanosensory channel Piezo2 and the capsaicin gated ion channel Trpv1) segregate into multiple clusters and often are expressed in subsets of cells within a cluster. Therefore, the 13 genetically-defined classes are likely to be physiologically heterogeneous rather than highly parallel (i.e., redundant) lines of sensory input. Our analysis harnesses the power of single-cell sequencing to provide a unique platform for in silico expression profiling that complements other approaches linking gene-expression with function and exposes unexpected diversity in the somatosensory system. PMID:28957441

Methods for efficient high-throughput screening of protein expression in recombinant Pichia pastoris strains.

PubMed

Camattari, Andrea; Weinhandl, Katrin; Gudiminchi, Rama K

2014-01-01

The methylotrophic yeast Pichia pastoris is becoming one of the favorite industrial workhorses for protein expression. Due to the widespread use of integration vectors, which generates significant clonal variability, screening methods allowing assaying hundreds of individual clones are of particular importance. Here we describe methods to detect and analyze protein expression, developed in a 96-well format for high-throughput screening of recombinant P. pastoris strains. The chapter covers essentially three common scenarios: (1) an enzymatic assay for proteins expressed in the cell cytoplasm, requiring cell lysis; (2) a whole-cell assay for a fungal cytochrome P450; and (3) a nonenzymatic assay for detection and quantification of tagged protein secreted into the supernatant.

The development of a general purpose ARM-based processing unit for the ATLAS TileCal sROD

NASA Astrophysics Data System (ADS)

Cox, M. A.; Reed, R.; Mellado, B.

2015-01-01

After Phase-II upgrades in 2022, the data output from the LHC ATLAS Tile Calorimeter will increase significantly. ARM processors are common in mobile devices due to their low cost, low energy consumption and high performance. It is proposed that a cost-effective, high data throughput Processing Unit (PU) can be developed by using several consumer ARM processors in a cluster configuration to allow aggregated processing performance and data throughput while maintaining minimal software design difficulty for the end-user. This PU could be used for a variety of high-level functions on the high-throughput raw data such as spectral analysis and histograms to detect possible issues in the detector at a low level. High-throughput I/O interfaces are not typical in consumer ARM System on Chips but high data throughput capabilities are feasible via the novel use of PCI-Express as the I/O interface to the ARM processors. An overview of the PU is given and the results for performance and throughput testing of four different ARM Cortex System on Chips are presented.

LSGermOPA, a custom OPA of 384 EST-derived SNPs for high-throughput lettuce (Lactuca sativa L.) germplasm fingerprinting

USDA-ARS?s Scientific Manuscript database

We assessed the genetic diversity and population structure among 148 cultivated lettuce (Lactuca sativa L.) accessions using the high-throughput GoldenGate assay and 384 EST (Expressed Sequence Tag)-derived SNP (single nucleotide polymorphism) markers. A custom OPA (Oligo Pool All), LSGermOPA was fo...

Topology based data analysis identifies a subgroup of breast cancers with a unique mutational profile and excellent survival.

PubMed

Nicolau, Monica; Levine, Arnold J; Carlsson, Gunnar

2011-04-26

High-throughput biological data, whether generated as sequencing, transcriptional microarrays, proteomic, or other means, continues to require analytic methods that address its high dimensional aspects. Because the computational part of data analysis ultimately identifies shape characteristics in the organization of data sets, the mathematics of shape recognition in high dimensions continues to be a crucial part of data analysis. This article introduces a method that extracts information from high-throughput microarray data and, by using topology, provides greater depth of information than current analytic techniques. The method, termed Progression Analysis of Disease (PAD), first identifies robust aspects of cluster analysis, then goes deeper to find a multitude of biologically meaningful shape characteristics in these data. Additionally, because PAD incorporates a visualization tool, it provides a simple picture or graph that can be used to further explore these data. Although PAD can be applied to a wide range of high-throughput data types, it is used here as an example to analyze breast cancer transcriptional data. This identified a unique subgroup of Estrogen Receptor-positive (ER(+)) breast cancers that express high levels of c-MYB and low levels of innate inflammatory genes. These patients exhibit 100% survival and no metastasis. No supervised step beyond distinction between tumor and healthy patients was used to identify this subtype. The group has a clear and distinct, statistically significant molecular signature, it highlights coherent biology but is invisible to cluster methods, and does not fit into the accepted classification of Luminal A/B, Normal-like subtypes of ER(+) breast cancers. We denote the group as c-MYB(+) breast cancer.

Statistical Use of Argonaute Expression and RISC Assembly in microRNA Target Identification

PubMed Central

Stanhope, Stephen A.; Sengupta, Srikumar; den Boon, Johan; Ahlquist, Paul; Newton, Michael A.

2009-01-01

MicroRNAs (miRNAs) posttranscriptionally regulate targeted messenger RNAs (mRNAs) by inducing cleavage or otherwise repressing their translation. We address the problem of detecting m/miRNA targeting relationships in homo sapiens from microarray data by developing statistical models that are motivated by the biological mechanisms used by miRNAs. The focus of our modeling is the construction, activity, and mediation of RNA-induced silencing complexes (RISCs) competent for targeted mRNA cleavage. We demonstrate that regression models accommodating RISC abundance and controlling for other mediating factors fit the expression profiles of known target pairs substantially better than models based on m/miRNA expressions alone, and lead to verifications of computational target pair predictions that are more sensitive than those based on marginal expression levels. Because our models are fully independent of exogenous results from sequence-based computational methods, they are appropriate for use as either a primary or secondary source of information regarding m/miRNA target pair relationships, especially in conjunction with high-throughput expression studies. PMID:19779550

VIRTUAL EMBRYO: SYSTEMS MODELING IN DEVELOPMENTAL TOXICITY - Symposium: SOT 2012

EPA Science Inventory

High-throughput screening (HTS) studies are providing a rich source of data that can be applied to in vitro profiling of chemical compounds for biological activity and potential toxicity. Chemical profiling in ToxCast covered 965 drugs-chemicals in over 500 diverse assays testing...

Small RNA Profiling of Two Important Cultivars of Banana and Overexpression of miRNA156 in Transgenic Banana Plants

PubMed Central

Ganapathi, Thumballi R.

2015-01-01

Micro RNAs (miRNAs) are a class of non-coding, short RNAs having important roles in regulation of gene expression. Although plant miRNAs have been studied in detail in some model plants, less is known about these miRNAs in important fruit plants like banana. miRNAs have pivotal roles in plant growth and development, and in responses to diverse biotic and abiotic stress stimuli. Here, we have analyzed the small RNA expression profiles of two different economically significant banana cultivars by using high-throughput sequencing technology. We identified a total of 170 and 244 miRNAs in the two libraries respectively derived from cv. Grand Naine and cv. Rasthali leaves. In addition, several cultivar specific microRNAs along with their putative target transcripts were also detected in our studies. To validate our findings regarding the small RNA profiles, we also undertook overexpression of a common microRNA, MusamiRNA156 in transgenic banana plants. The transgenic plants overexpressing the stem-loop sequence derived from MusamiRNA156 gene were stunted in their growth together with peculiar changes in leaf anatomy. These results provide a foundation for further investigations into important physiological and metabolic pathways operational in banana in general and cultivar specific traits in particular. PMID:25962076

Role of bioinformatics in establishing microRNAs as modulators of abiotic stress responses: the new revolution

PubMed Central

Tripathi, Anita; Goswami, Kavita; Sanan-Mishra, Neeti

2015-01-01

microRNAs (miRs) are a class of 21–24 nucleotide long non-coding RNAs responsible for regulating the expression of associated genes mainly by cleavage or translational inhibition of the target transcripts. With this characteristic of silencing, miRs act as an important component in regulation of plant responses in various stress conditions. In recent years, with drastic change in environmental and soil conditions different type of stresses have emerged as a major challenge for plants growth and productivity. The identification and profiling of miRs has itself been a challenge for research workers given their small size and large number of many probable sequences in the genome. Application of computational approaches has expedited the process of identification of miRs and their expression profiling in different conditions. The development of High-Throughput Sequencing (HTS) techniques has facilitated to gain access to the global profiles of the miRs for understanding their mode of action in plants. Introduction of various bioinformatics databases and tools have revolutionized the study of miRs and other small RNAs. This review focuses the role of bioinformatics approaches in the identification and study of the regulatory roles of plant miRs in the adaptive response to stresses. PMID:26578966

A novel assay for monoacylglycerol hydrolysis suitable for high-throughput screening.

PubMed

Brengdahl, Johan; Fowler, Christopher J

2006-12-01

A simple assay for monoacylglycerol hydrolysis suitable for high-throughput screening is described. The assay uses [(3)H]2-oleoylglycerol as substrate, with the tritium label in the glycerol part of the molecule and the use of phenyl sepharose gel to separate the hydrolyzed product ([(3)H]glycerol) from substrate. Using cytosolic fractions derived from rat cerebella as a source of hydrolytic activity, the assay gives the appropriate pH profile and sensitivity to inhibition with compounds known to inhibit hydrolysis of this substrate. The assay could also be adapted to a 96-well plate format, using C6 cells as the source of hydrolytic activity. Thus the assay is simple and appropriate for high-throughput screening of inhibitors of monoacylglycerol hydrolysis.

Genome-Wide Identification of Differentially Expressed Genes Associated with the High Yielding of Oleoresin in Secondary Xylem of Masson Pine (Pinus massoniana Lamb) by Transcriptomic Analysis

PubMed Central

Liu, Qinghua; Zhou, Zhichun; Wei, Yongcheng; Shen, Danyu; Feng, Zhongping; Hong, Shanping

2015-01-01

Masson pine is an important timber and resource for oleoresin in South China. Increasing yield of oleoresin in stems can raise economic benefits and enhance the resistance to bark beetles. However, the genetic mechanisms for regulating the yield of oleoresin were still unknown. Here, high-throughput sequencing technology was used to investigate the transcriptome and compare the gene expression profiles of high and low oleoresin-yielding genotypes. A total of 40,690,540 reads were obtained and assembled into 137,499 transcripts from the secondary xylem tissues. We identified 84,842 candidate unigenes based on sequence annotation using various databases and 96 unigenes were candidates for terpenoid backbone biosynthesis in pine. By comparing the expression profiles of high and low oleoresin-yielding genotypes, 649 differentially expressed genes (DEGs) were identified. GO enrichment analysis of DEGs revealed that multiple pathways were related to high yield of oleoresin. Nine candidate genes were validated by QPCR analysis. Among them, the candidate genes encoding geranylgeranyl diphosphate synthase (GGPS) and (-)-alpha/beta-pinene synthase were up-regulated in the high oleoresin-yielding genotype, while tricyclene synthase revealed lower expression level, which was in good agreement with the GC/MS result. In addition, DEG encoding ABC transporters, pathogenesis-related proteins (PR5 and PR9), phosphomethylpyrimidine synthase, non-specific lipid-transfer protein-like protein and ethylene responsive transcription factors (ERFs) were also confirmed to be critical for the biosynthesis of oleoresin. The next-generation sequencing strategy used in this study has proven to be a powerful means for analyzing transcriptome variation related to the yield of oleoresin in masson pine. The candidate genes encoding GGPS, (-)-alpha/beta-pinene, tricyclene synthase, ABC transporters, non-specific lipid-transfer protein-like protein, phosphomethylpyrimidine synthase, ERFs and pathogen responses may play important roles in regulating the yield of oleoresin. These DEGs are worthy of special attention in future studies. PMID:26167875

Long Noncoding RNAs and mRNA Regulation in Peripheral Blood Mononuclear Cells of Patients with Chronic Obstructive Pulmonary Disease

PubMed Central

Wang, Weijia; Xu, Dan

2018-01-01

Background Inflammation plays a pivotal role in the pathogenesis of chronic obstructive pulmonary disease (COPD). We evaluated the lncRNA and mRNA expression profile of peripheral blood mononuclear cells (PBMCs) from healthy nonsmokers, smokers without airflow limitation, and COPD patients. Methods lncRNA and mRNA profiling of PBMCs from 17 smokers and 14 COPD subjects was detected by high-throughput microarray. The expression of dysregulated lncRNAs was validated by qPCR. The lncRNA targets in dysregulated mRNAs were predicted and the GO enrichment was analyzed. The regulatory role of lncRNA ENST00000502883.1 on CXCL16 expression and consequently the effect on PBMC recruitment were investigated by siRNA knockdown and chemotaxis analysis. Results We identified 158 differentially expressed lncRNAs in PBMCs from COPD subjects compared with smokers. The dysregulated expression of 5 selected lncRNAs NR_026891.1 (FLJ10038), ENST00000502883.1 (RP11-499E18.1), HIT000648516, XR_429541.1, and ENST00000597550.1 (CTD-2245F17.3), was validated. The GO enrichment showed that leukocyte migration, immune response, and apoptosis are the main enriched processes that previously reported to be involved in the pathogenesis of COPD. The regulatory role of ENST00000502883.1 on CXCL16 expression and consequently the effect on PBMC recruitment was confirmed. Conclusion This study may provide clues for further studies targeting lncRNAs to control inflammation in COPD. PMID:29725270

Revealing complex function, process and pathway interactions with high-throughput expression and biological annotation data.

PubMed

Singh, Nitesh Kumar; Ernst, Mathias; Liebscher, Volkmar; Fuellen, Georg; Taher, Leila

2016-10-20

The biological relationships both between and within the functions, processes and pathways that operate within complex biological systems are only poorly characterized, making the interpretation of large scale gene expression datasets extremely challenging. Here, we present an approach that integrates gene expression and biological annotation data to identify and describe the interactions between biological functions, processes and pathways that govern a phenotype of interest. The product is a global, interconnected network, not of genes but of functions, processes and pathways, that represents the biological relationships within the system. We validated our approach on two high-throughput expression datasets describing organismal and organ development. Our findings are well supported by the available literature, confirming that developmental processes and apoptosis play key roles in cell differentiation. Furthermore, our results suggest that processes related to pluripotency and lineage commitment, which are known to be critical for development, interact mainly indirectly, through genes implicated in more general biological processes. Moreover, we provide evidence that supports the relevance of cell spatial organization in the developing liver for proper liver function. Our strategy can be viewed as an abstraction that is useful to interpret high-throughput data and devise further experiments.

Exploring Genome-Wide Expression Profiles Using Machine Learning Techniques.

PubMed

Kebschull, Moritz; Papapanou, Panos N

2017-01-01

Although contemporary high-throughput -omics methods produce high-dimensional data, the resulting wealth of information is difficult to assess using traditional statistical procedures. Machine learning methods facilitate the detection of additional patterns, beyond the mere identification of lists of features that differ between groups.Here, we demonstrate the utility of (1) supervised classification algorithms in class validation, and (2) unsupervised clustering in class discovery. We use data from our previous work that described the transcriptional profiles of gingival tissue samples obtained from subjects suffering from chronic or aggressive periodontitis (1) to test whether the two diagnostic entities were also characterized by differences on the molecular level, and (2) to search for a novel, alternative classification of periodontitis based on the tissue transcriptomes.Using machine learning technology, we provide evidence for diagnostic imprecision in the currently accepted classification of periodontitis, and demonstrate that a novel, alternative classification based on differences in gingival tissue transcriptomes is feasible. The outlined procedures allow for the unbiased interrogation of high-dimensional datasets for characteristic underlying classes, and are applicable to a broad range of -omics data.

High-throughput method for the quantitation of metabolites and co-factors from homocysteine-methionine cycle for nutritional status assessment.

PubMed

Da Silva, Laeticia; Collino, Sebastiano; Cominetti, Ornella; Martin, Francois-Pierre; Montoliu, Ivan; Moreno, Sergio Oller; Corthesy, John; Kaput, Jim; Kussmann, Martin; Monteiro, Jacqueline Pontes; Guiraud, Seu Ping

2016-09-01

There is increasing interest in the profiling and quantitation of methionine pathway metabolites for health management research. Currently, several analytical approaches are required to cover metabolites and co-factors. We report the development and the validation of a method for the simultaneous detection and quantitation of 13 metabolites in red blood cells. The method, validated in a cohort of healthy human volunteers, shows a high level of accuracy and reproducibility. This high-throughput protocol provides a robust coverage of central metabolites and co-factors in one single analysis and in a high-throughput fashion. In large-scale clinical settings, the use of such an approach will significantly advance the field of nutritional research in health and disease.

A method for quantitative analysis of standard and high-throughput qPCR expression data based on input sample quantity.

PubMed

Adamski, Mateusz G; Gumann, Patryk; Baird, Alison E

2014-01-01

Over the past decade rapid advances have occurred in the understanding of RNA expression and its regulation. Quantitative polymerase chain reactions (qPCR) have become the gold standard for quantifying gene expression. Microfluidic next generation, high throughput qPCR now permits the detection of transcript copy number in thousands of reactions simultaneously, dramatically increasing the sensitivity over standard qPCR. Here we present a gene expression analysis method applicable to both standard polymerase chain reactions (qPCR) and high throughput qPCR. This technique is adjusted to the input sample quantity (e.g., the number of cells) and is independent of control gene expression. It is efficiency-corrected and with the use of a universal reference sample (commercial complementary DNA (cDNA)) permits the normalization of results between different batches and between different instruments--regardless of potential differences in transcript amplification efficiency. Modifications of the input quantity method include (1) the achievement of absolute quantification and (2) a non-efficiency corrected analysis. When compared to other commonly used algorithms the input quantity method proved to be valid. This method is of particular value for clinical studies of whole blood and circulating leukocytes where cell counts are readily available.

High resolution array CGH and gene expression profiling of alveolar soft part sarcoma

PubMed Central

Selvarajah, Shamini; Pyne, Saumyadipta; Chen, Eleanor; Sompallae, Ramakrishna; Ligon, Azra H.; Nielsen, Gunnlaugur P.; Dranoff, Glenn; Stack, Edward; Loda, Massimo; Flavin, Richard

2014-01-01

Purpose Alveolar soft part sarcoma (ASPS) is a soft tissue sarcoma with poor prognosis, and little molecular evidence for its origin, initiation and progression. The aim of this study was to elucidate candidate molecular pathways involved in tumor pathogenesis. Experimental Design We employed high-throughput array comparative genomic hybridization and cDNA-Mediated Annealing, Selection, Ligation, and Extension Assay to profile the genomic and expression signatures of primary and metastatic ASPS from 17 tumors derived from 11 patients. We used an integrative bioinformatics approach to elucidate the molecular pathways associated with ASPS progression. Fluorescence in situ hybridization was performed to validate the presence of the t(X;17)(p11.2;q25) ASPL-TFE3 fusion and hence confirm the aCGH observations. Results FISH analysis identified the ASPL-TFE3 fusion in all cases. ArrayCGH revealed a higher number of numerical aberrations in metastatic tumors relative to primaries, but failed to identify consistent alterations in either group. Gene expression analysis highlighted 1,063 genes which were differentially expressed between the two groups. Gene set enrichment analysis identified 16 enriched gene sets (p < 0.1) associated with differentially expressed genes. Notable among these were several stem cell gene expression signatures and pathways related to differentiation. In particular, the paired box transcription factor PAX6 was up-regulated in the primary tumors, along with several genes whose mouse orthologs have previously been implicated in Pax6-DNA binding during neural stem cell differentiation. Conclusion In addition to suggesting a tentative neural line of differentiation for ASPS, these results implicate transcriptional deregulation from fusion genes in the pathogenesis of ASPS. PMID:24493828

Mapping human pluripotent stem cell differentiation pathways using high throughput single-cell RNA-sequencing.

PubMed

Han, Xiaoping; Chen, Haide; Huang, Daosheng; Chen, Huidong; Fei, Lijiang; Cheng, Chen; Huang, He; Yuan, Guo-Cheng; Guo, Guoji

2018-04-05

Human pluripotent stem cells (hPSCs) provide powerful models for studying cellular differentiations and unlimited sources of cells for regenerative medicine. However, a comprehensive single-cell level differentiation roadmap for hPSCs has not been achieved. We use high throughput single-cell RNA-sequencing (scRNA-seq), based on optimized microfluidic circuits, to profile early differentiation lineages in the human embryoid body system. We present a cellular-state landscape for hPSC early differentiation that covers multiple cellular lineages, including neural, muscle, endothelial, stromal, liver, and epithelial cells. Through pseudotime analysis, we construct the developmental trajectories of these progenitor cells and reveal the gene expression dynamics in the process of cell differentiation. We further reprogram primed H9 cells into naïve-like H9 cells to study the cellular-state transition process. We find that genes related to hemogenic endothelium development are enriched in naïve-like H9. Functionally, naïve-like H9 show higher potency for differentiation into hematopoietic lineages than primed cells. Our single-cell analysis reveals the cellular-state landscape of hPSC early differentiation, offering new insights that can be harnessed for optimization of differentiation protocols.

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

PubMed Central

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

2014-01-01

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

Microfluidic Technologies for Synthetic Biology

PubMed Central

Vinuselvi, Parisutham; Park, Seongyong; Kim, Minseok; Park, Jung Min; Kim, Taesung; Lee, Sung Kuk

2011-01-01

Microfluidic technologies have shown powerful abilities for reducing cost, time, and labor, and at the same time, for increasing accuracy, throughput, and performance in the analysis of biological and biochemical samples compared with the conventional, macroscale instruments. Synthetic biology is an emerging field of biology and has drawn much attraction due to its potential to create novel, functional biological parts and systems for special purposes. Since it is believed that the development of synthetic biology can be accelerated through the use of microfluidic technology, in this review work we focus our discussion on the latest microfluidic technologies that can provide unprecedented means in synthetic biology for dynamic profiling of gene expression/regulation with high resolution, highly sensitive on-chip and off-chip detection of metabolites, and whole-cell analysis. PMID:21747695

Profiling and bioinformatic analysis of circular RNA expression regulated by c-Myc.

PubMed

Gou, Qiheng; Wu, Ke; Zhou, Jian-Kang; Xie, Yuxin; Liu, Lunxu; Peng, Yong

2017-09-22

The c-Myc transcription factor is involved in cell proliferation, cell cycle and apoptosis by activating or repressing transcription of multiple genes. Circular RNAs (circRNAs) are widely expressed non-coding RNAs participating in the regulation of gene expression. Using a high-throughput microarray assay, we showed that Myc regulates the expression of certain circRNAs. A total of 309 up- and 252 down-regulated circRNAs were identified. Among them, randomly selected 8 circRNAs were confirmed by real-time PCR. Subsequently, Myc-binding sites were found to generally exist in the promoter regions of differentially expressed circRNAs. Based on miRNA sponge mechanism, we constructed circRNAs/miRNAs network regulated by Myc, suggesting that circRNAs may widely regulate protein expression through miRNA sponge mechanism. Lastly, we took advantage of Gene Ontology and KEGG analyses to point out that Myc-regulated circRNAs could impact cell proliferation through affecting Ras signaling pathway and pathways in cancer. Our study for the first time demonstrated that Myc transcription factor regulates the expression of circRNAs, adding a novel component of the Myc tumorigenic program and opening a window to investigate the function of certain circRNAs in tumorigenesis.

Regulation of miRNA Processing and miRNA Mediated Gene Repression in Cancer

PubMed Central

Bajan, Sarah; Hutvagner, Gyorgy

2014-01-01

The majority of human protein-coding genes are predicted to be targets of miRNA-mediated post-transcriptional regulation. The widespread influence of miRNAs is illustrated by their essential roles in all biological processes. Regulated miRNA expression is essential for maintaining cellular differentiation; therefore alterations in miRNA expression patterns are associated with several diseases, including various cancers. High-throughput sequencing technologies revealed low level expressing miRNA isoforms, termed isomiRs. IsomiRs may differ in sequence, length, target preference and expression patterns from their parental miRNA and can arise from differences in miRNA biosynthesis, RNA editing, or SNPs inherent to the miRNA gene. The association between isomiR expression and disease progression is largely unknown. Misregulated miRNA expression is thought to contribute to the formation and/or progression of cancer. However, due to the diversity of targeted transcripts, miRNAs can function as both tumor-suppressor genes and oncogenes as defined by cellular context. Despite this, miRNA profiling studies concluded that the differential expression of particular miRNAs in diseased tissue could aid the diagnosis and treatment of some cancers. PMID:25069508

MicroRNA signature of the human developing pancreas.

PubMed

Rosero, Samuel; Bravo-Egana, Valia; Jiang, Zhijie; Khuri, Sawsan; Tsinoremas, Nicholas; Klein, Dagmar; Sabates, Eduardo; Correa-Medina, Mayrin; Ricordi, Camillo; Domínguez-Bendala, Juan; Diez, Juan; Pastori, Ricardo L

2010-09-22

MicroRNAs are non-coding RNAs that regulate gene expression including differentiation and development by either inhibiting translation or inducing target degradation. The aim of this study is to determine the microRNA expression signature during human pancreatic development and to identify potential microRNA gene targets calculating correlations between the signature microRNAs and their corresponding mRNA targets, predicted by bioinformatics, in genome-wide RNA microarray study. The microRNA signature of human fetal pancreatic samples 10-22 weeks of gestational age (wga), was obtained by PCR-based high throughput screening with Taqman Low Density Arrays. This method led to identification of 212 microRNAs. The microRNAs were classified in 3 groups: Group number I contains 4 microRNAs with the increasing profile; II, 35 microRNAs with decreasing profile and III with 173 microRNAs, which remain unchanged. We calculated Pearson correlations between the expression profile of microRNAs and target mRNAs, predicted by TargetScan 5.1 and miRBase algorithms, using genome-wide mRNA expression data. Group I correlated with the decreasing expression of 142 target mRNAs and Group II with the increasing expression of 876 target mRNAs. Most microRNAs correlate with multiple targets, just as mRNAs are targeted by multiple microRNAs. Among the identified targets are the genes and transcription factors known to play an essential role in pancreatic development. We have determined specific groups of microRNAs in human fetal pancreas that change the degree of their expression throughout the development. A negative correlative analysis suggests an intertwined network of microRNAs and mRNAs collaborating with each other. This study provides information leading to potential two-way level of combinatorial control regulating gene expression through microRNAs targeting multiple mRNAs and, conversely, target mRNAs regulated in parallel by other microRNAs as well. This study may further the understanding of gene expression regulation in the human developing pancreas.

MicroRNA signature of the human developing pancreas

PubMed Central

2010-01-01

Background MicroRNAs are non-coding RNAs that regulate gene expression including differentiation and development by either inhibiting translation or inducing target degradation. The aim of this study is to determine the microRNA expression signature during human pancreatic development and to identify potential microRNA gene targets calculating correlations between the signature microRNAs and their corresponding mRNA targets, predicted by bioinformatics, in genome-wide RNA microarray study. Results The microRNA signature of human fetal pancreatic samples 10-22 weeks of gestational age (wga), was obtained by PCR-based high throughput screening with Taqman Low Density Arrays. This method led to identification of 212 microRNAs. The microRNAs were classified in 3 groups: Group number I contains 4 microRNAs with the increasing profile; II, 35 microRNAs with decreasing profile and III with 173 microRNAs, which remain unchanged. We calculated Pearson correlations between the expression profile of microRNAs and target mRNAs, predicted by TargetScan 5.1 and miRBase altgorithms, using genome-wide mRNA expression data. Group I correlated with the decreasing expression of 142 target mRNAs and Group II with the increasing expression of 876 target mRNAs. Most microRNAs correlate with multiple targets, just as mRNAs are targeted by multiple microRNAs. Among the identified targets are the genes and transcription factors known to play an essential role in pancreatic development. Conclusions We have determined specific groups of microRNAs in human fetal pancreas that change the degree of their expression throughout the development. A negative correlative analysis suggests an intertwined network of microRNAs and mRNAs collaborating with each other. This study provides information leading to potential two-way level of combinatorial control regulating gene expression through microRNAs targeting multiple mRNAs and, conversely, target mRNAs regulated in parallel by other microRNAs as well. This study may further the understanding of gene expression regulation in the human developing pancreas. PMID:20860821

Digital transcriptome profiling of normal and glioblastoma-derived neural stem cells identifies genes associated with patient survival

PubMed Central

2012-01-01

Background Glioblastoma multiforme, the most common type of primary brain tumor in adults, is driven by cells with neural stem (NS) cell characteristics. Using derivation methods developed for NS cells, it is possible to expand tumorigenic stem cells continuously in vitro. Although these glioblastoma-derived neural stem (GNS) cells are highly similar to normal NS cells, they harbor mutations typical of gliomas and initiate authentic tumors following orthotopic xenotransplantation. Here, we analyzed GNS and NS cell transcriptomes to identify gene expression alterations underlying the disease phenotype. Methods Sensitive measurements of gene expression were obtained by high-throughput sequencing of transcript tags (Tag-seq) on adherent GNS cell lines from three glioblastoma cases and two normal NS cell lines. Validation by quantitative real-time PCR was performed on 82 differentially expressed genes across a panel of 16 GNS and 6 NS cell lines. The molecular basis and prognostic relevance of expression differences were investigated by genetic characterization of GNS cells and comparison with public data for 867 glioma biopsies. Results Transcriptome analysis revealed major differences correlated with glioma histological grade, and identified misregulated genes of known significance in glioblastoma as well as novel candidates, including genes associated with other malignancies or glioma-related pathways. This analysis further detected several long non-coding RNAs with expression profiles similar to neighboring genes implicated in cancer. Quantitative PCR validation showed excellent agreement with Tag-seq data (median Pearson r = 0.91) and discerned a gene set robustly distinguishing GNS from NS cells across the 22 lines. These expression alterations include oncogene and tumor suppressor changes not detected by microarray profiling of tumor tissue samples, and facilitated the identification of a GNS expression signature strongly associated with patient survival (P = 1e-6, Cox model). Conclusions These results support the utility of GNS cell cultures as a model system for studying the molecular processes driving glioblastoma and the use of NS cells as reference controls. The association between a GNS expression signature and survival is consistent with the hypothesis that a cancer stem cell component drives tumor growth. We anticipate that analysis of normal and malignant stem cells will be an important complement to large-scale profiling of primary tumors. PMID:23046790

Comparative Transcriptomics to Identify Novel Genes and Pathways in Dinoflagellates

NASA Astrophysics Data System (ADS)

Ryan, D.

2016-02-01

The unarmored dinoflagellate Karenia brevis is among the most prominent harmful, bloom-forming phytoplankton species in the Gulf of Mexico. During blooms, the polyketides PbTx-1 and PbTx-2 (brevetoxins) are produced by K. brevis. Brevetoxins negatively impact human health and the Gulf shellfish harvest. However, the genes underlying brevetoxin synthesis are currently unknown. Because the K. brevis genome is extremely large ( 1 × 1011 base pairs long), and with a high proportion of repetitive, non-coding DNA, it has not been sequenced. In fact, large, repetitive genomes are common among the dinoflagellate group. High-throughput RNA sequencing technology enabled us to assemble Karenia transcriptomes de novo and investigate potential genes in the brevetoxin pathway through comparative transcriptomics. The brevetoxin profile varies among K. brevis clonal cultures. For example, well-documented Wilson-CCFWC268 typically produces 8-10 pg PbTx per cell, whereas SP1 produces < 2 pg PbTx/cell, and the mutant low-toxin Wilson clone produces undetectable to low (<0.05 pg/cell) amounts. Further, PbTx-2 has been measured in Karenia papilionacea but not Karenia mikimotoi. We compared the transcriptomes of four K. brevis clones (Wilson-CCFWC268, SP3, SP1, and mutant low-toxin Wilson) with K. papilionacea and K. mikimotoi to investigate nucleotide-level genetic variations and differences in gene expression. Of the 85,000 transcripts in the K. brevis transcriptome, 4,600 transcripts, including novel unannotated orthologs and putative polyketide synthases (PKSs), were only expressed by brevetoxin-producing K. brevis and K. papilionacea, not K. mikimotoi. Examination of gene expression between the typical- and low-toxin Wilson clones identified about 3,500 genes with significantly different expression levels, including 2 putative PKSs. One of the 2 PKSs was only found in the brevetoxin-producing Karenia species. These transcriptomes could not have been characterized without high-throughput RNA sequencing.

Characterization and Comparative Expression Profiling of Browning Response in Medinilla formosana after Cutting.

PubMed

Wang, Yan; Wang, Yiting; Li, Kunfeng; Song, Xijiao; Chen, Jianping

2016-01-01

Plant browning is a recalcitrant problem for in vitro culture and often leads to poor growth of explants and even failure of tissue culture. However, the molecular mechanisms underlying browning-induced physiological processes remain unclear. Medinilla is considered one of the most difficult genera for tissue culture owning to its severe browning. In the present study, intact aseptic plantlets of Medinilla formosana Hayata previously obtained by ovary culture, were used to explore the characteristics and molecular mechanism of the browning response. Successive morphological and anatomical observations after cutting showed that the browning of M. formosana was not lethal but adaptive. De novo transcriptome and digital gene expression (DGE) profiling using Illumina high-throughput sequencing were then used to explore molecular regulation after cutting. About 7.5 million tags of de novo transcriptome were obtained and 58,073 unigenes were assembled and annotated. A total of 6,431 differentially expressed genes (DEGs) at three stages after cutting were identified, and the expression patterns of these browning-related genes were clustered and analyzed. A number of putative DEGs involved in signal transduction and secondary metabolism were particularly studied and the potential roles of these cutting-responsive mRNAs in plant defense to diverse abiotic stresses are discussed. The DGE profiling data were also validated by quantitative RT-PCR analysis. The data obtained in this study provide an excellent resource for unraveling the molecular mechanisms of browning processes during in vitro tissue culture, and lay a foundation for future studies to inhibit and eliminate browning damage.

Characterization and Comparative Expression Profiling of Browning Response in Medinilla formosana after Cutting

PubMed Central

Wang, Yan; Wang, Yiting; Li, Kunfeng; Song, Xijiao; Chen, Jianping

2016-01-01

Plant browning is a recalcitrant problem for in vitro culture and often leads to poor growth of explants and even failure of tissue culture. However, the molecular mechanisms underlying browning-induced physiological processes remain unclear. Medinilla is considered one of the most difficult genera for tissue culture owning to its severe browning. In the present study, intact aseptic plantlets of Medinilla formosana Hayata previously obtained by ovary culture, were used to explore the characteristics and molecular mechanism of the browning response. Successive morphological and anatomical observations after cutting showed that the browning of M. formosana was not lethal but adaptive. De novo transcriptome and digital gene expression (DGE) profiling using Illumina high-throughput sequencing were then used to explore molecular regulation after cutting. About 7.5 million tags of de novo transcriptome were obtained and 58,073 unigenes were assembled and annotated. A total of 6,431 differentially expressed genes (DEGs) at three stages after cutting were identified, and the expression patterns of these browning-related genes were clustered and analyzed. A number of putative DEGs involved in signal transduction and secondary metabolism were particularly studied and the potential roles of these cutting-responsive mRNAs in plant defense to diverse abiotic stresses are discussed. The DGE profiling data were also validated by quantitative RT-PCR analysis. The data obtained in this study provide an excellent resource for unraveling the molecular mechanisms of browning processes during in vitro tissue culture, and lay a foundation for future studies to inhibit and eliminate browning damage. PMID:28066460

Principles of gene microarray data analysis.

PubMed

Mocellin, Simone; Rossi, Carlo Riccardo

2007-01-01

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

Genetic Network Inference: From Co-Expression Clustering to Reverse Engineering

NASA Technical Reports Server (NTRS)

Dhaeseleer, Patrik; Liang, Shoudan; Somogyi, Roland

2000-01-01

Advances in molecular biological, analytical, and computational technologies are enabling us to systematically investigate the complex molecular processes underlying biological systems. In particular, using high-throughput gene expression assays, we are able to measure the output of the gene regulatory network. We aim here to review datamining and modeling approaches for conceptualizing and unraveling the functional relationships implicit in these datasets. Clustering of co-expression profiles allows us to infer shared regulatory inputs and functional pathways. We discuss various aspects of clustering, ranging from distance measures to clustering algorithms and multiple-duster memberships. More advanced analysis aims to infer causal connections between genes directly, i.e., who is regulating whom and how. We discuss several approaches to the problem of reverse engineering of genetic networks, from discrete Boolean networks, to continuous linear and non-linear models. We conclude that the combination of predictive modeling with systematic experimental verification will be required to gain a deeper insight into living organisms, therapeutic targeting, and bioengineering.

Cytoscape: a software environment for integrated models of biomolecular interaction networks.

PubMed

Shannon, Paul; Markiel, Andrew; Ozier, Owen; Baliga, Nitin S; Wang, Jonathan T; Ramage, Daniel; Amin, Nada; Schwikowski, Benno; Ideker, Trey

2003-11-01

Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

Nile Red Detection of Bacterial Hydrocarbons and Ketones in a High-Throughput Format

PubMed Central

Pinzon, Neissa M.; Aukema, Kelly G.; Gralnick, Jeffrey A.; Wackett, Lawrence P.

2011-01-01

ABSTRACT A method for use in high-throughput screening of bacteria for the production of long-chain hydrocarbons and ketones by monitoring fluorescent light emission in the presence of Nile red is described. Nile red has previously been used to screen for polyhydroxybutyrate (PHB) and fatty acid esters, but this is the first report of screening for recombinant bacteria making hydrocarbons or ketones. The microtiter plate assay was evaluated using wild-type and recombinant strains of Shewanella oneidensis and Escherichia coli expressing the enzyme OleA, previously shown to initiate hydrocarbon biosynthesis. The strains expressing exogenous Stenotrophomonas maltophilia oleA, with increased levels of ketone production as determined by gas chromatography-mass spectrometry, were distinguished with Nile red fluorescence. Confocal microscopy images of S. oneidensis oleA-expressing strains stained with Nile red were consistent with a membrane localization of the ketones. This differed from Nile red staining of bacterial PHB or algal lipid droplets that showed intracellular inclusion bodies. These results demonstrated the applicability of Nile red in a high-throughput technique for the detection of bacterial hydrocarbons and ketones. PMID:21712420

Use of high-throughput mass spectrometry to elucidate host pathogen interactions in Salmonella

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

Rodland, Karin D.; Adkins, Joshua N.; Ansong, Charles

Capabilities in mass spectrometry are evolving rapidly, with recent improvements in sensitivity, data analysis, and most important, from the standpoint of this review, much higher throughput allowing analysis of many samples in a single day. This short review describes how these improvements in mass spectrometry can be used to dissect host-pathogen interactions using Salmonella as a model system. This approach enabled direct identification of the majority of annotated Salmonella proteins, quantitation of expression changes under various in vitro growth conditions, and new insights into virulence and expression of Salmonella proteins within host cell cells. One of the most significant findingsmore » is that a very high percentage of the all annotated genes (>20%) in Salmonella are regulated post-transcriptionally. In addition, new and unexpected interactions have been identified for several Salmonella virulence regulators that involve protein-protein interactions, suggesting additional functions of these regulators in coordinating virulence expression. Overall high throughput mass spectrometry provides a new view of pathogen-host interactions emphasizing the protein products and defining how protein interactions determine the outcome of infection.« less

High-Throughput Lectin Microarray-Based Analysis of Live Cell Surface Glycosylation

PubMed Central

Li, Yu; Tao, Sheng-ce; Zhu, Heng; Schneck, Jonathan P.

2011-01-01

Lectins, plant-derived glycan-binding proteins, have long been used to detect glycans on cell surfaces. However, the techniques used to characterize serum or cells have largely been limited to mass spectrometry, blots, flow cytometry, and immunohistochemistry. While these lectin-based approaches are well established and they can discriminate a limited number of sugar isomers by concurrently using a limited number of lectins, they are not amenable for adaptation to a high-throughput platform. Fortunately, given the commercial availability of lectins with a variety of glycan specificities, lectins can be printed on a glass substrate in a microarray format to profile accessible cell-surface glycans. This method is an inviting alternative for analysis of a broad range of glycans in a high-throughput fashion and has been demonstrated to be a feasible method of identifying binding-accessible cell surface glycosylation on living cells. The current unit presents a lectin-based microarray approach for analyzing cell surface glycosylation in a high-throughput fashion. PMID:21400689

An improved high-throughput lipid extraction method for the analysis of human brain lipids.

PubMed

Abbott, Sarah K; Jenner, Andrew M; Mitchell, Todd W; Brown, Simon H J; Halliday, Glenda M; Garner, Brett

2013-03-01

We have developed a protocol suitable for high-throughput lipidomic analysis of human brain samples. The traditional Folch extraction (using chloroform and glass-glass homogenization) was compared to a high-throughput method combining methyl-tert-butyl ether (MTBE) extraction with mechanical homogenization utilizing ceramic beads. This high-throughput method significantly reduced sample handling time and increased efficiency compared to glass-glass homogenizing. Furthermore, replacing chloroform with MTBE is safer (less carcinogenic/toxic), with lipids dissolving in the upper phase, allowing for easier pipetting and the potential for automation (i.e., robotics). Both methods were applied to the analysis of human occipital cortex. Lipid species (including ceramides, sphingomyelins, choline glycerophospholipids, ethanolamine glycerophospholipids and phosphatidylserines) were analyzed via electrospray ionization mass spectrometry and sterol species were analyzed using gas chromatography mass spectrometry. No differences in lipid species composition were evident when the lipid extraction protocols were compared, indicating that MTBE extraction with mechanical bead homogenization provides an improved method for the lipidomic profiling of human brain tissue.

High-Throughput Method for Automated Colony and Cell Counting by Digital Image Analysis Based on Edge Detection

PubMed Central

Choudhry, Priya

2016-01-01

Counting cells and colonies is an integral part of high-throughput screens and quantitative cellular assays. Due to its subjective and time-intensive nature, manual counting has hindered the adoption of cellular assays such as tumor spheroid formation in high-throughput screens. The objective of this study was to develop an automated method for quick and reliable counting of cells and colonies from digital images. For this purpose, I developed an ImageJ macro Cell Colony Edge and a CellProfiler Pipeline Cell Colony Counting, and compared them to other open-source digital methods and manual counts. The ImageJ macro Cell Colony Edge is valuable in counting cells and colonies, and measuring their area, volume, morphology, and intensity. In this study, I demonstrate that Cell Colony Edge is superior to other open-source methods, in speed, accuracy and applicability to diverse cellular assays. It can fulfill the need to automate colony/cell counting in high-throughput screens, colony forming assays, and cellular assays. PMID:26848849

Circular RNA hsa_circ_0001982 Promotes Breast Cancer Cell Carcinogenesis Through Decreasing miR-143.

PubMed

Tang, Yi-Yin; Zhao, Ping; Zou, Tian-Ning; Duan, Jia-Jun; Zhi, Rong; Yang, Si-Yuan; Yang, De-Chun; Wang, Xiao-Li

2017-11-01

Circular RNAs (circRNAs) are a type of noncoding RNAs generated from back-splicing, which have been verified to mediate multiple tumorigenesis. With the development of high-throughput sequencing, massive circRNAs are discovered in tumorous tissue. However, the potential physiological effect of circRNAs in breast cancer is still unknown. The purpose of this study is to investigate the expression profile of circRNA in breast cancer tissue and explore the in-depth regulatory mechanism in breast cancer tumorigenesis. In the present study, we screened the circRNA expression profiles in breast cancer tissue using circRNA microarray analysis. Totally 1705 circRNAs were identified to be significantly aberrant. Among these dysregulated circRNAs, hsa_circ_0001982 was markedly overexpressed in breast cancer tissue and cell lines. Bioinformatics analysis predicted that miR-143 acted as target of hsa_circ_0001982, which was confirmed by Dual-luciferase reporter assay. Loss-of-function and rescue experiments revealed that hsa_circ_0001982 knockdown suppressed breast cancer cell proliferation and invasion and induced apoptosis by targeting miR-143. In summary, our study preliminarily investigates the circRNA expression in breast cancer tissue and explores the role of competing endogenous RNA (ceRNA) mechanism in the progression, providing a novel insight for breast cancer tumorigenesis.

Dual Transcriptome Profiling of Leishmania-Infected Human Macrophages Reveals Distinct Reprogramming Signatures

PubMed Central

Fernandes, Maria Cecilia; Dillon, Laura A. L.; Belew, Ashton Trey; Bravo, Hector Corrada; Mosser, David M.

2016-01-01

ABSTRACT Macrophages are mononuclear phagocytes that constitute a first line of defense against pathogens. While lethal to many microbes, they are the primary host cells of Leishmania spp. parasites, the obligate intracellular pathogens that cause leishmaniasis. We conducted transcriptomic profiling of two Leishmania species and the human macrophage over the course of intracellular infection by using high-throughput RNA sequencing to characterize the global gene expression changes and reprogramming events that underlie the interactions between the pathogen and its host. A systematic exclusion of the generic effects of large-particle phagocytosis revealed a vigorous, parasite-specific response of the human macrophage early in the infection that was greatly tempered at later time points. An analogous temporal expression pattern was observed with the parasite, suggesting that much of the reprogramming that occurs as parasites transform into intracellular forms generally stabilizes shortly after entry. Following that, the parasite establishes an intracellular niche within macrophages, with minimal communication between the parasite and the host cell later during the infection. No significant difference was observed between parasite species transcriptomes or in the transcriptional response of macrophages infected with each species. Our comparative analysis of gene expression changes that occur as mouse and human macrophages are infected by Leishmania spp. points toward a general signature of the Leishmania-macrophage infectome. PMID:27165796

Integrated analysis of gene expression and methylation profiles of 48 candidate genes in breast cancer patients.

PubMed

Li, Zibo; Heng, Jianfu; Yan, Jinhua; Guo, Xinwu; Tang, Lili; Chen, Ming; Peng, Limin; Wu, Yepeng; Wang, Shouman; Xiao, Zhi; Deng, Zhongping; Dai, Lizhong; Wang, Jun

2016-11-01

Gene-specific methylation and expression have shown biological and clinical importance for breast cancer diagnosis and prognosis. Integrated analysis of gene methylation and gene expression may identify genes associated with biology mechanism and clinical outcome of breast cancer and aid in clinical management. Using high-throughput microfluidic quantitative PCR, we analyzed the expression profiles of 48 candidate genes in 96 Chinese breast cancer patients and investigated their correlation with gene methylation and associations with breast cancer clinical parameters. Breast cancer-specific gene expression alternation was found in 25 genes with significant expression difference between paired tumor and normal tissues. A total of 9 genes (CCND2, EGFR, GSTP1, PGR, PTGS2, RECK, SOX17, TNFRSF10D, and WIF1) showed significant negative correlation between methylation and gene expression, which were validated in the TCGA database. Total 23 genes (ACADL, APC, BRCA2, CADM1, CAV1, CCND2, CST6, EGFR, ESR2, GSTP1, ICAM5, NPY, PGR, PTGS2, RECK, RUNX3, SFRP1, SOX17, SYK, TGFBR2, TNFRSF10D, WIF1, and WRN) annotated with potential TFBSs in the promoter regions showed negative correlation between methylation and expression. In logistics regression analysis, 31 of the 48 genes showed improved performance in disease prediction with combination of methylation and expression coefficient. Our results demonstrated the complex correlation and the possible regulatory mechanisms between DNA methylation and gene expression. Integration analysis of methylation and expression of candidate genes could improve performance in breast cancer prediction. These findings would contribute to molecular characterization and identification of biomarkers for potential clinical applications.

MOPED 2.5—An Integrated Multi-Omics Resource: Multi-Omics Profiling Expression Database Now Includes Transcriptomics Data

PubMed Central

Montague, Elizabeth; Stanberry, Larissa; Higdon, Roger; Janko, Imre; Lee, Elaine; Anderson, Nathaniel; Choiniere, John; Stewart, Elizabeth; Yandl, Gregory; Broomall, William; Kolker, Natali

2014-01-01

Abstract Multi-omics data-driven scientific discovery crucially rests on high-throughput technologies and data sharing. Currently, data are scattered across single omics repositories, stored in varying raw and processed formats, and are often accompanied by limited or no metadata. The Multi-Omics Profiling Expression Database (MOPED, http://moped.proteinspire.org) version 2.5 is a freely accessible multi-omics expression database. Continual improvement and expansion of MOPED is driven by feedback from the Life Sciences Community. In order to meet the emergent need for an integrated multi-omics data resource, MOPED 2.5 now includes gene relative expression data in addition to protein absolute and relative expression data from over 250 large-scale experiments. To facilitate accurate integration of experiments and increase reproducibility, MOPED provides extensive metadata through the Data-Enabled Life Sciences Alliance (DELSA Global, http://delsaglobal.org) metadata checklist. MOPED 2.5 has greatly increased the number of proteomics absolute and relative expression records to over 500,000, in addition to adding more than four million transcriptomics relative expression records. MOPED has an intuitive user interface with tabs for querying different types of omics expression data and new tools for data visualization. Summary information including expression data, pathway mappings, and direct connection between proteins and genes can be viewed on Protein and Gene Details pages. These connections in MOPED provide a context for multi-omics expression data exploration. Researchers are encouraged to submit omics data which will be consistently processed into expression summaries. MOPED as a multi-omics data resource is a pivotal public database, interdisciplinary knowledge resource, and platform for multi-omics understanding. PMID:24910945

Pre-amplification in the context of high-throughput qPCR gene expression experiment.

PubMed

Korenková, Vlasta; Scott, Justin; Novosadová, Vendula; Jindřichová, Marie; Langerová, Lucie; Švec, David; Šídová, Monika; Sjöback, Robert

2015-03-11

With the introduction of the first high-throughput qPCR instrument on the market it became possible to perform thousands of reactions in a single run compared to the previous hundreds. In the high-throughput reaction, only limited volumes of highly concentrated cDNA or DNA samples can be added. This necessity can be solved by pre-amplification, which became a part of the high-throughput experimental workflow. Here, we focused our attention on the limits of the specific target pre-amplification reaction and propose the optimal, general setup for gene expression experiment using BioMark instrument (Fluidigm). For evaluating different pre-amplification factors following conditions were combined: four human blood samples from healthy donors and five transcripts having high to low expression levels; each cDNA sample was pre-amplified at four cycles (15, 18, 21, and 24) and five concentrations (equivalent to 0.078 ng, 0.32 ng, 1.25 ng, 5 ng, and 20 ng of total RNA). Factors identified as critical for a success of cDNA pre-amplification were cycle of pre-amplification, total RNA concentration, and type of gene. The selected pre-amplification reactions were further tested for optimal Cq distribution in a BioMark Array. The following concentrations combined with pre-amplification cycles were optimal for good quality samples: 20 ng of total RNA with 15 cycles of pre-amplification, 20x and 40x diluted; and 5 ng and 20 ng of total RNA with 18 cycles of pre-amplification, both 20x and 40x diluted. We set up upper limits for the bulk gene expression experiment using gene expression Dynamic Array and provided an easy-to-obtain tool for measuring of pre-amplification success. We also showed that variability of the pre-amplification, introduced into the experimental workflow of reverse transcription-qPCR, is lower than variability caused by the reverse transcription step.

High-throughput profiling of nanoparticle-protein interactions by fluorescamine labeling.

PubMed

Ashby, Jonathan; Duan, Yaokai; Ligans, Erik; Tamsi, Michael; Zhong, Wenwan

2015-02-17

A rapid, high throughput fluorescence assay was designed to screen interactions between proteins and nanoparticles. The assay employs fluorescamine, a primary-amine specific fluorogenic dye, to label proteins. Because fluorescamine could specifically target the surface amines on proteins, a conformational change of the protein upon interaction with nanoparticles will result in a change in fluorescence. In the present study, the assay was applied to test the interactions between a selection of proteins and nanoparticles made of polystyrene, silica, or iron oxide. The particles were also different in their hydrodynamic diameter, synthesis procedure, or surface modification. Significant labeling differences were detected when the same protein incubated with different particles. Principal component analysis (PCA) on the collected fluorescence profiles revealed clear grouping effects of the particles based on their properties. The results prove that fluorescamine labeling is capable of detecting protein-nanoparticle interactions, and the resulting fluorescence profile is sensitive to differences in nanoparticle's physical properties. The assay can be carried out in a high-throughput manner, and is rapid with low operation cost. Thus, it is well suited for evaluating interactions between a larger number of proteins and nanoparticles. Such assessment can help to improve our understanding on the molecular basis that governs the biological behaviors of nanomaterials. It will also be useful for initial examination of the bioactivity and reproducibility of nanomaterials employed in biomedical fields.

Combining differential expression, chromosomal and pathway analyses for the molecular characterization of renal cell carcinoma

PubMed Central

Furge, Kyle A; Dykema, Karl; Petillo, David; Westphal, Michael; Zhang, Zhongfa; Kort, Eric J; Teh, Bin Tean

2007-01-01

Using high-throughput gene-expression profiling technology, we can now gain a better understanding of the complex biology that is taking place in cancer cells. This complexity is largely dictated by the abnormal genetic makeup of the cancer cells. This abnormal genetic makeup can have profound effects on cellular activities such as cell growth, cell survival and other regulatory processes. Based on the pattern of gene expression, or molecular signatures of the tumours, we can distinguish or subclassify different types of cancers according to their cell of origin, behaviour, and the way they respond to therapeutic agents and radiation. These approaches will lead to better molecular subclassification of tumours, the basis of personalized medicine. We have, to date, done whole-genome microarray gene-expression profiling on several hundreds of kidney tumours. We adopt a combined bioinformatic approach, based on an integrative analysis of the gene-expression data. These data are used to identify both cytogenetic abnormalities and molecular pathways that are deregulated in renal cell carcinoma (RCC). For example, we have identified the deregulation of the VHL-hypoxia pathway in clear-cell RCC, as previously known, and the c-Myc pathway in aggressive papillary RCC. Besides the more common clear-cell, papillary and chromophobe RCCs, we are currently characterizing the molecular signatures of rarer forms of renal neoplasia such as carcinoma of the collecting ducts, mixed epithelial and stromal tumours, chromosome Xp11 translocations associated with papillary RCC, renal medullary carcinoma, mucinous tubular and spindle-cell carcinoma, and a group of unclassified tumours. Continued development and improvement in the field of molecular profiling will better characterize cancer and provide more accurate diagnosis, prognosis and prediction of drug response. PMID:18542781

Multiplexed ChIP-Seq Using Direct Nucleosome Barcoding: A Tool for High-Throughput Chromatin Analysis.

PubMed

Chabbert, Christophe D; Adjalley, Sophie H; Steinmetz, Lars M; Pelechano, Vicent

2018-01-01

Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) or microarray hybridization (ChIP-on-chip) are standard methods for the study of transcription factor binding sites and histone chemical modifications. However, these approaches only allow profiling of a single factor or protein modification at a time.In this chapter, we present Bar-ChIP, a higher throughput version of ChIP-Seq that relies on the direct ligation of molecular barcodes to chromatin fragments. Bar-ChIP enables the concurrent profiling of multiple DNA-protein interactions and is therefore amenable to experimental scale-up, without the need for any robotic instrumentation.

A high-throughput pipeline for the production of synthetic antibodies for analysis of ribonucleoprotein complexes

PubMed Central

Na, Hong; Laver, John D.; Jeon, Jouhyun; Singh, Fateh; Ancevicius, Kristin; Fan, Yujie; Cao, Wen Xi; Nie, Kun; Yang, Zhenglin; Luo, Hua; Wang, Miranda; Rissland, Olivia; Westwood, J. Timothy; Kim, Philip M.; Smibert, Craig A.; Lipshitz, Howard D.; Sidhu, Sachdev S.

2016-01-01

Post-transcriptional regulation of mRNAs plays an essential role in the control of gene expression. mRNAs are regulated in ribonucleoprotein (RNP) complexes by RNA-binding proteins (RBPs) along with associated protein and noncoding RNA (ncRNA) cofactors. A global understanding of post-transcriptional control in any cell type requires identification of the components of all of its RNP complexes. We have previously shown that these complexes can be purified by immunoprecipitation using anti-RBP synthetic antibodies produced by phage display. To develop the large number of synthetic antibodies required for a global analysis of RNP complex composition, we have established a pipeline that combines (i) a computationally aided strategy for design of antigens located outside of annotated domains, (ii) high-throughput antigen expression and purification in Escherichia coli, and (iii) high-throughput antibody selection and screening. Using this pipeline, we have produced 279 antibodies against 61 different protein components of Drosophila melanogaster RNPs. Together with those produced in our low-throughput efforts, we have a panel of 311 antibodies for 67 RNP complex proteins. Tests of a subset of our antibodies demonstrated that 89% immunoprecipitate their endogenous target from embryo lysate. This panel of antibodies will serve as a resource for global studies of RNP complexes in Drosophila. Furthermore, our high-throughput pipeline permits efficient production of synthetic antibodies against any large set of proteins. PMID:26847261

Unravelling the complexity of microRNA-mediated gene regulation in black pepper (Piper nigrum L.) using high-throughput small RNA profiling.

PubMed

Asha, Srinivasan; Sreekumar, Sweda; Soniya, E V

2016-01-01

Analysis of high-throughput small RNA deep sequencing data, in combination with black pepper transcriptome sequences revealed microRNA-mediated gene regulation in black pepper ( Piper nigrum L.). Black pepper is an important spice crop and its berries are used worldwide as a natural food additive that contributes unique flavour to foods. In the present study to characterize microRNAs from black pepper, we generated a small RNA library from black pepper leaf and sequenced it by Illumina high-throughput sequencing technology. MicroRNAs belonging to a total of 303 conserved miRNA families were identified from the sRNAome data. Subsequent analysis from recently sequenced black pepper transcriptome confirmed precursor sequences of 50 conserved miRNAs and four potential novel miRNA candidates. Stem-loop qRT-PCR experiments demonstrated differential expression of eight conserved miRNAs in black pepper. Computational analysis of targets of the miRNAs showed 223 potential black pepper unigene targets that encode diverse transcription factors and enzymes involved in plant development, disease resistance, metabolic and signalling pathways. RLM-RACE experiments further mapped miRNA-mediated cleavage at five of the mRNA targets. In addition, miRNA isoforms corresponding to 18 miRNA families were also identified from black pepper. This study presents the first large-scale identification of microRNAs from black pepper and provides the foundation for the future studies of miRNA-mediated gene regulation of stress responses and diverse metabolic processes in black pepper.

Fluorescent Reporter Libraries as Useful Tools for Optimizing Microbial Cell Factories: A Review of the Current Methods and Applications

PubMed Central

Delvigne, Frank; Pêcheux, Hélène; Tarayre, Cédric

2015-01-01

The use of genetically encoded fluorescent reporters allows speeding up the initial optimization steps of microbial bioprocesses. These reporters can be used for determining the expression level of a particular promoter, not only the synthesis of a specific protein but also the content of intracellular metabolites. The level of protein/metabolite is thus proportional to a fluorescence signal. By this way, mean expression profiles of protein/metabolites can be determined non-invasively at a high-throughput rate, allowing the rapid identification of the best producers. Actually, different kinds of reporter systems are available, as well as specific cultivation devices allowing the on-line recording of the fluorescent signal. Cell-to-cell variability is another important phenomenon that can be integrated into the screening procedures for the selection of more efficient microbial cell factories. PMID:26442261

Transcriptome sequencing and annotation of the halophytic microalga Dunaliella salina * #

PubMed Central

Hong, Ling; Liu, Jun-li; Midoun, Samira Z.; Miller, Philip C.

2017-01-01

The unicellular green alga Dunaliella salina is well adapted to salt stress and contains compounds (including β-carotene and vitamins) with potential commercial value. A large transcriptome database of D. salina during the adjustment, exponential and stationary growth phases was generated using a high throughput sequencing platform. We characterized the metabolic processes in D. salina with a focus on valuable metabolites, with the aim of manipulating D. salina to achieve greater economic value in large-scale production through a bioengineering strategy. Gene expression profiles under salt stress verified using quantitative polymerase chain reaction (qPCR) implied that salt can regulate the expression of key genes. This study generated a substantial fraction of D. salina transcriptional sequences for the entire growth cycle, providing a basis for the discovery of novel genes. This first full-scale transcriptome study of D. salina establishes a foundation for further comparative genomic studies. PMID:28990374

Nile Red Detection of Bacterial Hydrocarbons and Ketones in a High-Throughput Format

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

Pinzon, NM; Aukema, KG; Gralnick, JA

A method for use in high-throughput screening of bacteria for the production of long-chain hydrocarbons and ketones by monitoring fluorescent light emission in the presence of Nile red is described. Nile red has previously been used to screen for polyhydroxybutyrate (PHB) and fatty acid esters, but this is the first report of screening for recombinant bacteria making hydrocarbons or ketones. The microtiter plate assay was evaluated using wild-type and recombinant strains of Shewanella oneidensis and Escherichia coli expressing the enzyme OleA, previously shown to initiate hydrocarbon biosynthesis. The strains expressing exogenous Stenotrophomonas maltophilia oleA, with increased levels of ketone productionmore » as determined by gas chromatography-mass spectrometry, were distinguished with Nile red fluorescence. Confocal microscopy images of S. oneidensis oleA-expressing strains stained with Nile red were consistent with a membrane localization of the ketones. This differed from Nile red staining of bacterial PHB or algal lipid droplets that showed intracellular inclusion bodies. These results demonstrated the applicability of Nile red in a high-throughput technique for the detection of bacterial hydrocarbons and ketones. IMPORTANCE In recent years, there has been renewed interest in advanced biofuel sources such as bacterial hydrocarbon production. Previous studies used solvent extraction of bacterial cultures followed by gas chromatography-mass spectrometry (GC-MS) to detect and quantify ketones and hydrocarbons (Beller HR, Goh EB, Keasling JD, Appl. Environ. Microbiol. 76: 1212-1223, 2010; Sukovich DJ, Seffernick JL, Richman JE, Gralnick JA, Wackett LP, Appl. Environ. Microbiol. 76: 3850-3862, 2010). While these analyses are powerful and accurate, their labor-intensive nature makes them intractable to high-throughput screening; therefore, methods for rapid identification of bacterial strains that are overproducing hydrocarbons are needed. The use of high-throughput evaluation of bacterial and algal hydrophobic molecule production via Nile red fluorescence from lipids and esters was extended in this study to include hydrocarbons and ketones. This work demonstrated accurate, high-throughput detection of high-level bacterial long-chain ketone and hydrocarbon production by screening for increased fluorescence of the hydrophobic dye Nile red.« less

Plant-pathogen interactions: what microarray tells about it?

PubMed

Lodha, T D; Basak, J

2012-01-01

Plant defense responses are mediated by elementary regulatory proteins that affect expression of thousands of genes. Over the last decade, microarray technology has played a key role in deciphering the underlying networks of gene regulation in plants that lead to a wide variety of defence responses. Microarray is an important tool to quantify and profile the expression of thousands of genes simultaneously, with two main aims: (1) gene discovery and (2) global expression profiling. Several microarray technologies are currently in use; most include a glass slide platform with spotted cDNA or oligonucleotides. Till date, microarray technology has been used in the identification of regulatory genes, end-point defence genes, to understand the signal transduction processes underlying disease resistance and its intimate links to other physiological pathways. Microarray technology can be used for in-depth, simultaneous profiling of host/pathogen genes as the disease progresses from infection to resistance/susceptibility at different developmental stages of the host, which can be done in different environments, for clearer understanding of the processes involved. A thorough knowledge of plant disease resistance using successful combination of microarray and other high throughput techniques, as well as biochemical, genetic, and cell biological experiments is needed for practical application to secure and stabilize yield of many crop plants. This review starts with a brief introduction to microarray technology, followed by the basics of plant-pathogen interaction, the use of DNA microarrays over the last decade to unravel the mysteries of plant-pathogen interaction, and ends with the future prospects of this technology.

Application of adenosine triphosphate affinity probe and scheduled multiple-reaction monitoring analysis for profiling global kinome in human cells in response to arsenite treatment.

PubMed

Guo, Lei; Xiao, Yongsheng; Wang, Yinsheng

2014-11-04

Phosphorylation of cellular components catalyzed by kinases plays important roles in cell signaling and proliferation. Quantitative assessment of perturbation in global kinome may provide crucial knowledge for elucidating the mechanisms underlying the cytotoxic effects of environmental toxicants. Here, we utilized an adenosine triphosphate (ATP) affinity probe coupled with stable isotope labeling by amino acids in cell culture (SILAC) to assess quantitatively the arsenite-induced alteration of global kinome in human cells. We constructed a SILAC-compatible kinome library for scheduled multiple-reaction monitoring (MRM) analysis and adopted on-the-fly recalibration of retention time shift, which provided better throughput of the analytical method and enabled the simultaneous quantification of the expression of ∼300 kinases in two LC-MRM runs. With this improved analytical method, we conducted an in-depth quantitative analysis of the perturbation of kinome of GM00637 human skin fibroblast cells induced by arsenite exposure. Several kinases involved in cell cycle progression, including cyclin-dependent kinases (CDK1 and CDK4) and Aurora kinases A, B, and C, were found to be hyperactivated, and the altered expression of CDK1 was further validated by Western analysis. In addition, treatment with a CDK inhibitor, flavopiridol, partially restored the arsenite-induced growth inhibition of human skin fibroblast cells. Thus, sodium arsenite may confer its cytotoxic effect partly through the aberrant activation of CDKs and the resultant perturbation of cell cycle progression. Together, we developed a high-throughput, SILAC-compatible, and MRM-based kinome profiling method and demonstrated that the method is powerful in deciphering the molecular modes of action of a widespread environmental toxicant. The method should be generally applicable for uncovering the cellular pathways triggered by other extracellular stimuli.

Application of Adenosine Triphosphate Affinity Probe and Scheduled Multiple-Reaction Monitoring Analysis for Profiling Global Kinome in Human Cells in Response to Arsenite Treatment

PubMed Central

2015-01-01

Phosphorylation of cellular components catalyzed by kinases plays important roles in cell signaling and proliferation. Quantitative assessment of perturbation in global kinome may provide crucial knowledge for elucidating the mechanisms underlying the cytotoxic effects of environmental toxicants. Here, we utilized an adenosine triphosphate (ATP) affinity probe coupled with stable isotope labeling by amino acids in cell culture (SILAC) to assess quantitatively the arsenite-induced alteration of global kinome in human cells. We constructed a SILAC-compatible kinome library for scheduled multiple-reaction monitoring (MRM) analysis and adopted on-the-fly recalibration of retention time shift, which provided better throughput of the analytical method and enabled the simultaneous quantification of the expression of ∼300 kinases in two LC-MRM runs. With this improved analytical method, we conducted an in-depth quantitative analysis of the perturbation of kinome of GM00637 human skin fibroblast cells induced by arsenite exposure. Several kinases involved in cell cycle progression, including cyclin-dependent kinases (CDK1 and CDK4) and Aurora kinases A, B, and C, were found to be hyperactivated, and the altered expression of CDK1 was further validated by Western analysis. In addition, treatment with a CDK inhibitor, flavopiridol, partially restored the arsenite-induced growth inhibition of human skin fibroblast cells. Thus, sodium arsenite may confer its cytotoxic effect partly through the aberrant activation of CDKs and the resultant perturbation of cell cycle progression. Together, we developed a high-throughput, SILAC-compatible, and MRM-based kinome profiling method and demonstrated that the method is powerful in deciphering the molecular modes of action of a widespread environmental toxicant. The method should be generally applicable for uncovering the cellular pathways triggered by other extracellular stimuli. PMID:25301106

A tunable single-monochromator Raman system based on the supercontinuum laser and tunable filters for resonant Raman profile measurements.

PubMed

Liu, X-L; Liu, H-N; Tan, P-H

2017-08-01

Resonant Raman spectroscopy requires that the wavelength of the laser used is close to that of an electronic transition. A tunable laser source and a triple spectrometer are usually necessary for resonant Raman profile measurements. However, such a system is complex with low signal throughput, which limits its wide application by scientific community. Here, a tunable micro-Raman spectroscopy system based on the supercontinuum laser, transmission grating, tunable filters, and single-stage spectrometer is introduced to measure the resonant Raman profile. The supercontinuum laser in combination with transmission grating makes a tunable excitation source with a bandwidth of sub-nanometer. Such a system exhibits continuous excitation tunability and high signal throughput. Its good performance and flexible tunability are verified by resonant Raman profile measurement of twisted bilayer graphene, which demonstrates its potential application prospect for resonant Raman spectroscopy.

Optimisation of insect cell growth in deep-well blocks: development of a high-throughput insect cell expression screen.

PubMed

Bahia, Daljit; Cheung, Robert; Buchs, Mirjam; Geisse, Sabine; Hunt, Ian

2005-01-01

This report describes a method to culture insects cells in 24 deep-well blocks for the routine small-scale optimisation of baculovirus-mediated protein expression experiments. Miniaturisation of this process provides the necessary reduction in terms of resource allocation, reagents, and labour to allow extensive and rapid optimisation of expression conditions, with the concomitant reduction in lead-time before commencement of large-scale bioreactor experiments. This therefore greatly simplifies the optimisation process and allows the use of liquid handling robotics in much of the initial optimisation stages of the process, thereby greatly increasing the throughput of the laboratory. We present several examples of the use of deep-well block expression studies in the optimisation of therapeutically relevant protein targets. We also discuss how the enhanced throughput offered by this approach can be adapted to robotic handling systems and the implications this has on the capacity to conduct multi-parallel protein expression studies.

JASPAR 2010: the greatly expanded open-access database of transcription factor binding profiles

PubMed Central

Portales-Casamar, Elodie; Thongjuea, Supat; Kwon, Andrew T.; Arenillas, David; Zhao, Xiaobei; Valen, Eivind; Yusuf, Dimas; Lenhard, Boris; Wasserman, Wyeth W.; Sandelin, Albin

2010-01-01

JASPAR (http://jaspar.genereg.net) is the leading open-access database of matrix profiles describing the DNA-binding patterns of transcription factors (TFs) and other proteins interacting with DNA in a sequence-specific manner. Its fourth major release is the largest expansion of the core database to date: the database now holds 457 non-redundant, curated profiles. The new entries include the first batch of profiles derived from ChIP-seq and ChIP-chip whole-genome binding experiments, and 177 yeast TF binding profiles. The introduction of a yeast division brings the convenience of JASPAR to an active research community. As binding models are refined by newer data, the JASPAR database now uses versioning of matrices: in this release, 12% of the older models were updated to improved versions. Classification of TF families has been improved by adopting a new DNA-binding domain nomenclature. A curated catalog of mammalian TFs is provided, extending the use of the JASPAR profiles to additional TFs belonging to the same structural family. The changes in the database set the system ready for more rapid acquisition of new high-throughput data sources. Additionally, three new special collections provide matrix profile data produced by recent alternative high-throughput approaches. PMID:19906716

Adenylylation of small RNA sequencing adapters using the TS2126 RNA ligase I.

PubMed

Lama, Lodoe; Ryan, Kevin

2016-01-01

Many high-throughput small RNA next-generation sequencing protocols use 5' preadenylylated DNA oligonucleotide adapters during cDNA library preparation. Preadenylylation of the DNA adapter's 5' end frees from ATP-dependence the ligation of the adapter to RNA collections, thereby avoiding ATP-dependent side reactions. However, preadenylylation of the DNA adapters can be costly and difficult. The currently available method for chemical adenylylation of DNA adapters is inefficient and uses techniques not typically practiced in laboratories profiling cellular RNA expression. An alternative enzymatic method using a commercial RNA ligase was recently introduced, but this enzyme works best as a stoichiometric adenylylating reagent rather than a catalyst and can therefore prove costly when several variant adapters are needed or during scale-up or high-throughput adenylylation procedures. Here, we describe a simple, scalable, and highly efficient method for the 5' adenylylation of DNA oligonucleotides using the thermostable RNA ligase 1 from bacteriophage TS2126. Adapters with 3' blocking groups are adenylylated at >95% yield at catalytic enzyme-to-adapter ratios and need not be gel purified before ligation to RNA acceptors. Experimental conditions are also reported that enable DNA adapters with free 3' ends to be 5' adenylylated at >90% efficiency. © 2015 Lama and Ryan; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

On Data Transfers Over Wide-Area Dedicated Connections

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

Rao, Nageswara S.; Liu, Qiang

Dedicated wide-area network connections are employed in big data and high-performance computing scenarios, since the absence of cross-traffic promises to make it easier to analyze and optimize data transfers over them. However, nonlinear transport dynamics and end-system complexity due to multi-core hosts and distributed file systems make these tasks surprisingly challenging. We present an overview of methods to analyze memory and disk file transfers using extensive measurements over 10 Gbps physical and emulated connections with 0–366 ms round trip times (RTTs). For memory transfers, we derive performance profiles of TCP and UDT throughput as a function of RTT, which showmore » concave regions in contrast to entirely convex regions predicted by previous models. These highly desirable concave regions can be expanded by utilizing large buffers and more parallel flows. We also present Poincar´e maps and Lyapunov exponents of TCP and UDT throughputtraces that indicate complex throughput dynamics. For disk file transfers, we show that throughput can be optimized using a combination of parallel I/O and network threads under direct I/O mode. Our initial throughput measurements of Lustre filesystems mounted over long-haul connections using LNet routers show convex profiles indicative of I/O limits.« less

The shortest path is not the one you know: application of biological network resources in precision oncology research.

PubMed

Kuperstein, Inna; Grieco, Luca; Cohen, David P A; Thieffry, Denis; Zinovyev, Andrei; Barillot, Emmanuel

2015-03-01

Several decades of molecular biology research have delivered a wealth of detailed descriptions of molecular interactions in normal and tumour cells. This knowledge has been functionally organised and assembled into dedicated biological pathway resources that serve as an invaluable tool, not only for structuring the information about molecular interactions but also for making it available for biological, clinical and computational studies. With the advent of high-throughput molecular profiling of tumours, close to complete molecular catalogues of mutations, gene expression and epigenetic modifications are available and require adequate interpretation. Taking into account the information about biological signalling machinery in cells may help to better interpret molecular profiles of tumours. Making sense out of these descriptions requires biological pathway resources for functional interpretation of the data. In this review, we describe the available biological pathway resources, their characteristics in terms of construction mode, focus, aims and paradigms of biological knowledge representation. We present a new resource that is focused on cancer-related signalling, the Atlas of Cancer Signalling Networks. We briefly discuss current approaches for data integration, visualisation and analysis, using biological networks, such as pathway scoring, guilt-by-association and network propagation. Finally, we illustrate with several examples the added value of data interpretation in the context of biological networks and demonstrate that it may help in analysis of high-throughput data like mutation, gene expression or small interfering RNA screening and can guide in patients stratification. Finally, we discuss perspectives for improving precision medicine using biological network resources and tools. Taking into account the information about biological signalling machinery in cells may help to better interpret molecular patterns of tumours and enable to put precision oncology into general clinical practice. © The Author 2015. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

High-throughput analysis of sulfatides in cerebrospinal fluid using automated extraction and UPLC-MS/MS.

PubMed

Blomqvist, Maria; Borén, Jan; Zetterberg, Henrik; Blennow, Kaj; Månsson, Jan-Eric; Ståhlman, Marcus

2017-07-01

Sulfatides (STs) are a group of glycosphingolipids that are highly expressed in brain. Due to their importance for normal brain function and their potential involvement in neurological diseases, development of accurate and sensitive methods for their determination is needed. Here we describe a high-throughput oriented and quantitative method for the determination of STs in cerebrospinal fluid (CSF). The STs were extracted using a fully automated liquid/liquid extraction method and quantified using ultra-performance liquid chromatography coupled to tandem mass spectrometry. With the high sensitivity of the developed method, quantification of 20 ST species from only 100 μl of CSF was performed. Validation of the method showed that the STs were extracted with high recovery (90%) and could be determined with low inter- and intra-day variation. Our method was applied to a patient cohort of subjects with an Alzheimer's disease biomarker profile. Although the total ST levels were unaltered compared with an age-matched control group, we show that the ratio of hydroxylated/nonhydroxylated STs was increased in the patient cohort. In conclusion, we believe that the fast, sensitive, and accurate method described in this study is a powerful new tool for the determination of STs in clinical as well as preclinical settings. Copyright © 2017 by the American Society for Biochemistry and Molecular Biology, Inc.

Comprehensive gene and microRNA expression profiling on cardiovascular system in zebrafish co-exposured of SiNPs and MeHg.

PubMed

Hu, Hejing; Shi, Yanfeng; Zhang, Yannan; Wu, Jing; Asweto, Collins Otieno; Feng, Lin; Yang, Xiaozhe; Duan, Junchao; Sun, Zhiwei

2017-12-31

Air pollution has been shown to increase cardiovascular diseases. However, little attention has been paid to the combined effects of PM and air pollutants on the cardiovascular system. To explore this, a high-throughput sequencing technology was used to determine combined effects of silica nanoparticles (SiNPs) and MeHg in zebrafish. Our study demonstrated that SiNPs and MeHg co-exposure could cause significant changes in mRNA and miRNA expression patterns in zebrafish. The differentially expressed (DE) genes in profiles 17 and 26 of STC analysis suggest that SiNPs and MeHg co-exposure had more proinflammatory and cardiovascular toxicity in zebrafish than single exposure. Major gene functions associated with cardiovascular system in the co-exposed zebrafish were discerned from the dynamic-gene-network, including stxbp1a, celf4, ahr1b and bai2. In addition, the prominently expressed pathway of cardiac muscle contraction was targeted by 3 DE miRNAs identified by the miRNA-pathway-network (dre-miR-7147, dre-miR-26a and dre-miR-375), which included 23 DE genes. This study presents a global view of the combined SiNPs and MeHg toxicity on the dynamic expression of both mRNAs and miRNAs in zebrafish, and could serve as fundamental research clues for future studies, especially on cardiovascular system toxicity. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification and comparative analysis of the microRNA transcriptome in roots of two contrasting tobacco genotypes in response to cadmium stress

NASA Astrophysics Data System (ADS)

He, Xiaoyan; Zheng, Weite; Cao, Fangbin; Wu, Feibo

2016-09-01

Tobacco (Nicotiana tabacum L.) is more acclimated to cadmium (Cd) uptake and preferentially enriches Cd in leaves than other crops. MicroRNAs (miRNAs) play crucial roles in regulating expression of various stress response genes in plants. However, genome-wide expression of miRNAs and their target genes in response to Cd stress in tobacco are still unknown. Here, miRNA high-throughput sequencing technology was performed using two contrasting tobacco genotypes Guiyan 1 and Yunyan 2 of Cd-sensitive and tolerance. Comprehensive analysis of miRNA expression profiles in control and Cd treated plants identified 72 known (27 families) and 14 novel differentially expressed miRNAs in the two genotypes. Among them, 28 known (14 families) and 5 novel miRNAs were considered as Cd tolerance associated miRNAs, which mainly involved in cell growth, ion homeostasis, stress defense, antioxidant and hormone signaling. Finally, a hypothetical model of Cd tolerance mechanism in Yunyan 2 was presented. Our findings suggest that some miRNAs and their target genes and pathways may play critical roles in Cd tolerance.

High-throughput tool to discriminate effects of NMs (Cu-NPs, Cu-nanowires, CuNO3, and Cu salt aged): transcriptomics in Enchytraeus crypticus.

PubMed

Gomes, Susana I L; Roca, Carlos P; Pegoraro, Natália; Trindade, Tito; Scott-Fordsmand, Janeck J; Amorim, Mónica J B

2018-05-01

The current testing of nanomaterials (NMs) via standard toxicity tests does not cover many of the NMs specificities. One of the recommendations lays on understanding the mechanisms of action, as these can help predicting long-term effects and safe-by-design production. In the present study, we used the high-throughput gene expression tool, developed for Enchytraeus crypticus (4 × 44k Agilent microarray), to study the effects of exposure to several copper (Cu) forms. The Cu treatments included two NMs (spherical and wires) and two copper-salt treatments (CuNO 3 spiked and Cu salt field historical contamination). To relate gene expression with higher effect level, testing was done with reproduction effect concentrations (EC 20 , EC 50 ), using 3 and 7 days as exposure periods. Results showed that time plays a major role in the transcriptomic response, most of it occurring after 3 days. Analysis of gene expression profiles showed that Cu-salt-aged and Cu-nanowires (Nwires) differed from CuNO 3 and Cu-nanoparticles (NPs). Functional analysis revealed specific mechanisms: Cu-NPs uniquely affected senescence and cuticle pattern formation, which can result from the contact of the NPs with the worms' tegument. Cu-Nwires affected reproduction via male gamete generation and hermaphrodite genitalia development. CuNO 3 affected neurotransmission and locomotory behavior, both of which can be related with avoidance response. Cu salt-aged uniquely affected phagocytosis and reproductive system development (via different mechanisms than Cu-Nwires). For the first time for Cu (nano)materials, the adverse outcome pathways (AOPs) drafted here provide an overview for common and unique effects per material and linkage with apical effects.

Quantitative Proteomics of Sleep-Deprived Mouse Brains Reveals Global Changes in Mitochondrial Proteins

PubMed Central

Li, Tie-Mei; Zhang, Ju-en; Lin, Rui; Chen, She; Luo, Minmin; Dong, Meng-Qiu

2016-01-01

Sleep is a ubiquitous, tightly regulated, and evolutionarily conserved behavior observed in almost all animals. Prolonged sleep deprivation can be fatal, indicating that sleep is a physiological necessity. However, little is known about its core function. To gain insight into this mystery, we used advanced quantitative proteomics technology to survey the global changes in brain protein abundance. Aiming to gain a comprehensive profile, our proteomics workflow included filter-aided sample preparation (FASP), which increased the coverage of membrane proteins; tandem mass tag (TMT) labeling, for relative quantitation; and high resolution, high mass accuracy, high throughput mass spectrometry (MS). In total, we obtained the relative abundance ratios of 9888 proteins encoded by 6070 genes. Interestingly, we observed significant enrichment for mitochondrial proteins among the differentially expressed proteins. This finding suggests that sleep deprivation strongly affects signaling pathways that govern either energy metabolism or responses to mitochondrial stress. Additionally, the differentially-expressed proteins are enriched in pathways implicated in age-dependent neurodegenerative diseases, including Parkinson’s, Huntington’s, and Alzheimer’s, hinting at possible connections between sleep loss, mitochondrial stress, and neurodegeneration. PMID:27684481

Extent, Causes, and Consequences of Small RNA Expression Variation in Human Adipose Tissue

PubMed Central

Knights, Andrew J.; Abreu-Goodger, Cei; van de Bunt, Martijn; Guerra-Assunção, José Afonso; Bartonicek, Nenad; van Dongen, Stijn; Mägi, Reedik; Nisbet, James; Barrett, Amy; Rantalainen, Mattias; Nica, Alexandra C.; Quail, Michael A.; Small, Kerrin S.; Glass, Daniel; Enright, Anton J.; Winn, John; Deloukas, Panos; Dermitzakis, Emmanouil T.; McCarthy, Mark I.; Spector, Timothy D.; Durbin, Richard; Lindgren, Cecilia M.

2012-01-01

Small RNAs are functional molecules that modulate mRNA transcripts and have been implicated in the aetiology of several common diseases. However, little is known about the extent of their variability within the human population. Here, we characterise the extent, causes, and effects of naturally occurring variation in expression and sequence of small RNAs from adipose tissue in relation to genotype, gene expression, and metabolic traits in the MuTHER reference cohort. We profiled the expression of 15 to 30 base pair RNA molecules in subcutaneous adipose tissue from 131 individuals using high-throughput sequencing, and quantified levels of 591 microRNAs and small nucleolar RNAs. We identified three genetic variants and three RNA editing events. Highly expressed small RNAs are more conserved within mammals than average, as are those with highly variable expression. We identified 14 genetic loci significantly associated with nearby small RNA expression levels, seven of which also regulate an mRNA transcript level in the same region. In addition, these loci are enriched for variants significant in genome-wide association studies for body mass index. Contrary to expectation, we found no evidence for negative correlation between expression level of a microRNA and its target mRNAs. Trunk fat mass, body mass index, and fasting insulin were associated with more than twenty small RNA expression levels each, while fasting glucose had no significant associations. This study highlights the similar genetic complexity and shared genetic control of small RNA and mRNA transcripts, and gives a quantitative picture of small RNA expression variation in the human population. PMID:22589741

High-Throughput Sequencing Reveals Principles of Adeno-Associated Virus Serotype 2 Integration

PubMed Central

Janovitz, Tyler; Klein, Isaac A.; Oliveira, Thiago; Mukherjee, Piali; Nussenzweig, Michel C.; Sadelain, Michel

2013-01-01

Viral integrations are important in human biology, yet genome-wide integration profiles have not been determined for many viruses. Adeno-associated virus (AAV) infects most of the human population and is a prevalent gene therapy vector. AAV integrates into the human genome with preference for a single locus, termed AAVS1. However, the genome-wide integration of AAV has not been defined, and the principles underlying this recombination remain unclear. Using a novel high-throughput approach, integrant capture sequencing, nearly 12 million AAV junctions were recovered from a human cell line, providing five orders of magnitude more data than were previously available. Forty-five percent of integrations occurred near AAVS1, and several thousand novel integration hotspots were identified computationally. Most of these occurred in genes, with dozens of hotspots targeting known oncogenes. Viral replication protein binding sites (RBS) and transcriptional activity were major factors favoring integration. In a first for eukaryotic viruses, the data reveal a unique asymmetric integration profile with distinctive directional orientation of viral genomes. These studies provide a new understanding of AAV integration biology through the use of unbiased high-throughput data acquisition and bioinformatics. PMID:23720718

Neuroproteomic profiling of human body fluids.

PubMed

Häggmark, Anna; Schwenk, Jochen M; Nilsson, Peter

2016-04-01

Analysis of protein expression and abundance provides a possibility to extend the current knowledge on disease-associated processes and pathways. The human brain is a complex organ and dysfunction or damage can give rise to a variety of neurological diseases. Although many proteins potentially reflecting disease progress are originating from brain, the scarce availability of human tissue material has lead to utilization of body fluids such as cerebrospinal fluid and blood in disease-related research. Within the most common neurological disorders, much effort has been spent on studying the role of a few hallmark proteins in disease pathogenesis but despite extensive investigation, the signatures they provide seem insufficient to fully understand and predict disease progress. In order to expand the view the field of neuroproteomics has lately emerged alongside developing technologies, such as affinity proteomics and mass spectrometry, for multiplexed and high-throughput protein profiling. Here, we provide an overview of how such technologies have been applied to study neurological disease and we also discuss some important considerations concerning discovery of disease-associated profiles. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification of the miRNA-mRNA regulatory network of small cell osteosarcoma based on RNA-seq.

PubMed

Xie, Lin; Liao, Yedan; Shen, Lida; Hu, Fengdi; Yu, Sunlin; Zhou, Yonghong; Zhang, Ya; Yang, Yihao; Li, Dongqi; Ren, Minyan; Yuan, Zhongqin; Yang, Zuozhang

2017-06-27

Small cell osteosarcoma (SCO) is a rare subtype of osteosarcoma characterized by highly aggressive progression and a poor prognosis. The miRNA and mRNA expression profiles of peripheral blood mononuclear cells (PBMCs) were obtained in 3 patients with SCO and 10 healthy individuals using high-throughput RNA-sequencing. We identified 37 dysregulated miRNAs and 1636 dysregulated mRNAs in patients with SCO compared to the healthy controls. Specifically, the 37 dysregulated miRNAs consisted of 27 up-regulated miRNAs and 10 down-regulated miRNAs; the 1636 dysregulated mRNAs consisted of 555 up-regulated mRNAs and 1081 down-regulated mRNAs. The target-genes of miRNAs were predicted, and 1334 negative correlations between miRNAs and mRNAs were used to construct an miRNA-mRNA regulatory network. Dysregulated genes were significantly enriched in pathways related to cancer, mTOR signaling and cell cycle signaling. Specifically, hsa-miR-26b-5p, hsa-miR-221-3p and hsa-miR-125b-2-3p were significantly dysregulated miRNAs and exhibited a high degree of connectivity with target genes. Overall, the expression of dysregulated genes in tumor tissues and peripheral blood samples of patients with SCO measured by quantitative real-time polymerase chain reaction corroborated with our bioinformatics analyses based on the expression profiles of PBMCs from patients with SCO. Thus, hsa-miR-26b-5p, hsa-miR-221-3p and hsa-miR-125b-2-3p may be involved in SCO tumorigenesis.

A Novel Real-Time PCR Assay of microRNAs Using S-Poly(T), a Specific Oligo(dT) Reverse Transcription Primer with Excellent Sensitivity and Specificity

PubMed Central

Kang, Kang; Zhang, Xiaoying; Liu, Hongtao; Wang, Zhiwei; Zhong, Jiasheng; Huang, Zhenting; Peng, Xiao; Zeng, Yan; Wang, Yuna; Yang, Yi; Luo, Jun; Gou, Deming

2012-01-01

Background MicroRNAs (miRNAs) are small, non-coding RNAs capable of postranscriptionally regulating gene expression. Accurate expression profiling is crucial for understanding the biological roles of miRNAs, and exploring them as biomarkers of diseases. Methodology/Principal Findings A novel, highly sensitive, and reliable miRNA quantification approach,termed S-Poly(T) miRNA assay, is designed. In this assay, miRNAs are subjected to polyadenylation and reverse transcription with a S-Poly(T) primer that contains a universal reverse primer, a universal Taqman probe, an oligo(dT)11 sequence and six miRNA-specific bases. Individual miRNAs are then amplified by a specific forward primer and a universal reverse primer, and the PCR products are detected by a universal Taqman probe. The S-Poly(T) assay showed a minimum of 4-fold increase in sensitivity as compared with the stem-loop or poly(A)-based methods. A remarkable specificity in discriminating among miRNAs with high sequence similarity was also obtained with this approach. Using this method, we profiled miRNAs in human pulmonary arterial smooth muscle cells (HPASMC) and identified 9 differentially expressed miRNAs associated with hypoxia treatment. Due to its outstanding sensitivity, the number of circulating miRNAs from normal human serum was significantly expanded from 368 to 518. Conclusions/Significance With excellent sensitivity, specificity, and high-throughput, the S-Poly(T) method provides a powerful tool for miRNAs quantification and identification of tissue- or disease-specific miRNA biomarkers. PMID:23152780

NATbox: a network analysis toolbox in R.

PubMed

Chavan, Shweta S; Bauer, Michael A; Scutari, Marco; Nagarajan, Radhakrishnan

2009-10-08

There has been recent interest in capturing the functional relationships (FRs) from high-throughput assays using suitable computational techniques. FRs elucidate the working of genes in concert as a system as opposed to independent entities hence may provide preliminary insights into biological pathways and signalling mechanisms. Bayesian structure learning (BSL) techniques and its extensions have been used successfully for modelling FRs from expression profiles. Such techniques are especially useful in discovering undocumented FRs, investigating non-canonical signalling mechanisms and cross-talk between pathways. The objective of the present study is to develop a graphical user interface (GUI), NATbox: Network Analysis Toolbox in the language R that houses a battery of BSL algorithms in conjunction with suitable statistical tools for modelling FRs in the form of acyclic networks from gene expression profiles and their subsequent analysis. NATbox is a menu-driven open-source GUI implemented in the R statistical language for modelling and analysis of FRs from gene expression profiles. It provides options to (i) impute missing observations in the given data (ii) model FRs and network structure from gene expression profiles using a battery of BSL algorithms and identify robust dependencies using a bootstrap procedure, (iii) present the FRs in the form of acyclic graphs for visualization and investigate its topological properties using network analysis metrics, (iv) retrieve FRs of interest from published literature. Subsequently, use these FRs as structural priors in BSL (v) enhance scalability of BSL across high-dimensional data by parallelizing the bootstrap routines. NATbox provides a menu-driven GUI for modelling and analysis of FRs from gene expression profiles. By incorporating readily available functions from existing R-packages, it minimizes redundancy and improves reproducibility, transparency and sustainability, characteristic of open-source environments. NATbox is especially suited for interdisciplinary researchers and biologists with minimal programming experience and would like to use systems biology approaches without delving into the algorithmic aspects. The GUI provides appropriate parameter recommendations for the various menu options including default parameter choices for the user. NATbox can also prove to be a useful demonstration and teaching tool in graduate and undergraduate course in systems biology. It has been tested successfully under Windows and Linux operating systems. The source code along with installation instructions and accompanying tutorial can be found at http://bioinformatics.ualr.edu/natboxWiki/index.php/Main_Page.

Regulatory Efficacy of Brown Seaweed Lessonia nigrescens Extract on the Gene Expression Profile and Intestinal Microflora in Type 2 Diabetic Mice.

PubMed

Zhao, Chao; Yang, Chengfeng; Chen, Mingjun; Lv, Xucong; Liu, Bin; Yi, Lunzhao; Cornara, Laura; Wei, Ming-Chi; Yang, Yu-Chiao; Tundis, Rosa; Xiao, Jianbo

2018-02-01

In this study, the antidiabetic activity of Lessonia nigrescens ethanolic extract (LNE) is investigated in streptozotocin (SZT)-induced type 2 diabetic mice fed with a high-sucrose/high-fat diet. Ultra high performance liquid chromatography coupled with photo-DAD and electospray ionization-mass spectrometry (ESI-MS) is employed to analyze the major compounds in LNE. The components of the intestinal microflora in type 2 diabetic mice are analyzed by high-throughput next-generation 16S rRNA gene sequencing. Fasting blood glucose levels in diabetic mice are significantly decreased after LNE administration. The histology reveals that LNE could protect the cellular architecture of liver and kidney. LNE treatment significantly increases Bacteroidetes and decreases Firmicutes populations in intestinal microflora. Specifically, It could selectively enrich the amounts of beneficial bacteria, Barnesiella, as well as reduce the abundances of Clostridium and Alistipes. The increased gene and protein expression levels of phosphatidylinositol 3-kinase (PI3K) in the liver are observed in LNE treatment groups, while the expressions of c-Jun N-terminal kinase (JNK) are significantly downregulated. The above findings suggest that LNE could be considered as a functional food for reducing blood glucose and regulating intestinal microflora. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A high-throughput and quantitative method to assess the mutagenic potential of translesion DNA synthesis

PubMed Central

Taggart, David J.; Camerlengo, Terry L.; Harrison, Jason K.; Sherrer, Shanen M.; Kshetry, Ajay K.; Taylor, John-Stephen; Huang, Kun; Suo, Zucai

2013-01-01

Cellular genomes are constantly damaged by endogenous and exogenous agents that covalently and structurally modify DNA to produce DNA lesions. Although most lesions are mended by various DNA repair pathways in vivo, a significant number of damage sites persist during genomic replication. Our understanding of the mutagenic outcomes derived from these unrepaired DNA lesions has been hindered by the low throughput of existing sequencing methods. Therefore, we have developed a cost-effective high-throughput short oligonucleotide sequencing assay that uses next-generation DNA sequencing technology for the assessment of the mutagenic profiles of translesion DNA synthesis catalyzed by any error-prone DNA polymerase. The vast amount of sequencing data produced were aligned and quantified by using our novel software. As an example, the high-throughput short oligonucleotide sequencing assay was used to analyze the types and frequencies of mutations upstream, downstream and at a site-specifically placed cis–syn thymidine–thymidine dimer generated individually by three lesion-bypass human Y-family DNA polymerases. PMID:23470999

MicroRNA Expression Profiling to Identify and Validate Reference Genes for the Relative Quantification of microRNA in Rectal Cancer.

PubMed

Eriksen, Anne Haahr Mellergaard; Andersen, Rikke Fredslund; Pallisgaard, Niels; Sørensen, Flemming Brandt; Jakobsen, Anders; Hansen, Torben Frøstrup

2016-01-01

MicroRNAs (miRNAs) play important roles in regulating biological processes at the post-transcriptional level. Deregulation of miRNAs has been observed in cancer, and miRNAs are being investigated as potential biomarkers regarding diagnosis, prognosis and prediction in cancer management. Real-time quantitative polymerase chain reaction (RT-qPCR) is commonly used, when measuring miRNA expression. Appropriate normalisation of RT-qPCR data is important to ensure reliable results. The aim of the present study was to identify stably expressed miRNAs applicable as normaliser candidates in future studies of miRNA expression in rectal cancer. We performed high-throughput miRNA profiling (OpenArray®) on ten pairs of laser micro-dissected rectal cancer tissue and adjacent stroma. A global mean expression normalisation strategy was applied to identify the most stably expressed miRNAs for subsequent validation. In the first validation experiment, a panel of miRNAs were analysed on 25 pairs of micro dissected rectal cancer tissue and adjacent stroma. Subsequently, the same miRNAs were analysed in 28 pairs of rectal cancer tissue and normal rectal mucosa. From the miRNA profiling experiment, miR-645, miR-193a-5p, miR-27a and let-7g were identified as stably expressed, both in malignant and stromal tissue. In addition, NormFinder confirmed high expression stability for the four miRNAs. In the RT-qPCR based validation experiments, no significant difference between tumour and stroma/normal rectal mucosa was detected for the mean of the normaliser candidates miR-27a, miR-193a-5p and let-7g (first validation P = 0.801, second validation P = 0.321). MiR-645 was excluded from the data analysis, because it was undetected in 35 of 50 samples (first validation) and in 24 of 56 samples (second validation), respectively. Significant difference in expression level of RNU6B was observed between tumour and adjacent stromal (first validation), and between tumour and normal rectal mucosa (second validation). We recommend the mean expression of miR-27a, miR-193a-5p and let-7g as normalisation factor, when performing miRNA expression analyses by RT-qPCR on rectal cancer tissue.

High-throughput STR analysis for DNA database using direct PCR.

PubMed

Sim, Jeong Eun; Park, Su Jeong; Lee, Han Chul; Kim, Se-Yong; Kim, Jong Yeol; Lee, Seung Hwan

2013-07-01

Since the Korean criminal DNA database was launched in 2010, we have focused on establishing an automated DNA database profiling system that analyzes short tandem repeat loci in a high-throughput and cost-effective manner. We established a DNA database profiling system without DNA purification using a direct PCR buffer system. The quality of direct PCR procedures was compared with that of conventional PCR system under their respective optimized conditions. The results revealed not only perfect concordance but also an excellent PCR success rate, good electropherogram quality, and an optimal intra/inter-loci peak height ratio. In particular, the proportion of DNA extraction required due to direct PCR failure could be minimized to <3%. In conclusion, the newly developed direct PCR system can be adopted for automated DNA database profiling systems to replace or supplement conventional PCR system in a time- and cost-saving manner. © 2013 American Academy of Forensic Sciences Published 2013. This article is a U.S. Government work and is in the public domain in the U.S.A.

Use of early passage fetal intestinal epithelial cells in semi-high-throughput screening assays: an approach to identify new innate immune system adjuvants.

PubMed

Buckner, Diana; Wilson, Suzanne; Kurk, Sandra; Hardy, Michele; Miessner, Nicole; Jutila, Mark A

2006-09-01

Innate immune system stimulants (innate adjuvants) offer complementary approaches to vaccines and antimicrobial compounds to increase host resistance to infection. The authors established fetal bovine intestinal epithelial cell (BIEC) cultures to screen natural product and synthetic compound libraries for novel mucosal adjuvants. They showed that BIECs from fetal intestine maintained an in vivo phenotype as reflected in cytokeratin expression, expression of antigens restricted to intestinal enterocytes, and induced interleukin-8 (IL-8) production. BIECs could be infected by and support replication of bovine rotavirus. A semi-high-throughput enzyme-linked immunosorbent assay-based assay that measured IL-8 production by BIECs was established and used to screen commercially available natural compounds for novel adjuvant activity. Five novel hits were identified, demonstrating the utility of the assay for selecting and screening new epithelial cell adjuvants. Although the identified compounds had not previously been shown to induce IL-8 production in epithelial cells, other known functions for 3 of the 5 were consistent with this activity. Statistical analysis of the throughput data demonstrated that the assay is adaptable to a high-throughput format for screening both synthetic and natural product derived compound libraries.

Steroid Profiling by Gas Chromatography–Mass Spectrometry and High Performance Liquid Chromatography–Mass Spectrometry for Adrenal Diseases

PubMed Central

McDonald, Jeffrey G.; Matthew, Susan

2012-01-01

The ability to measure steroid hormone concentrations in blood and urine specimens is central to the diagnosis and proper treatment of adrenal diseases. The traditional approach has been to assay each steroid hormone, precursor, or metabolite using individual aliquots of serum, each with a separate immunoassay. For complex diseases, such as congenital adrenal hyperplasia and adrenocortical cancer, in which the assay of several steroids is essential for management, this approach is time consuming and costly, in addition to using large amounts of serum. Gas chromatography/mass spectrometry profiling of steroid metabolites in urine has been employed for many years but only in a small number of specialized laboratories and suffers from slow throughput. The advent of commercial high-performance liquid chromatography instruments coupled to tandem mass spectrometers offers the potential for medium- to high-throughput profiling of serum steroids using small quantities of sample. Here, we review the physical principles of mass spectrometry, the instrumentation used for these techniques, the terminology used in this field and applications to steroid analysis. PMID:22170384

Digital gene expression for non-model organisms

PubMed Central

Hong, Lewis Z.; Li, Jun; Schmidt-Küntzel, Anne; Warren, Wesley C.; Barsh, Gregory S.

2011-01-01

Next-generation sequencing technologies offer new approaches for global measurements of gene expression but are mostly limited to organisms for which a high-quality assembled reference genome sequence is available. We present a method for gene expression profiling called EDGE, or EcoP15I-tagged Digital Gene Expression, based on ultra-high-throughput sequencing of 27-bp cDNA fragments that uniquely tag the corresponding gene, thereby allowing direct quantification of transcript abundance. We show that EDGE is capable of assaying for expression in >99% of genes in the genome and achieves saturation after 6–8 million reads. EDGE exhibits very little technical noise, reveals a large (106) dynamic range of gene expression, and is particularly suited for quantification of transcript abundance in non-model organisms where a high-quality annotated genome is not available. In a direct comparison with RNA-seq, both methods provide similar assessments of relative transcript abundance, but EDGE does better at detecting gene expression differences for poorly expressed genes and does not exhibit transcript length bias. Applying EDGE to laboratory mice, we show that a loss-of-function mutation in the melanocortin 1 receptor (Mc1r), recognized as a Mendelian determinant of yellow hair color in many different mammals, also causes reduced expression of genes involved in the interferon response. To illustrate the application of EDGE to a non-model organism, we examine skin biopsy samples from a cheetah (Acinonyx jubatus) and identify genes likely to control differences in the color of spotted versus non-spotted regions. PMID:21844123

Body Fluids as a Source of Diagnostic Biomarkers: Prostate — EDRN Public Portal

Cancer.gov

Recent advances in high-throughput protein expression profiling of bodily fluids has generated great enthusiasm and hope for this approach as a potent diagnostic tool. At the center of these efforts is the application of SELDI-TOF-MS and artificial intelligence algorithms by the EDRN BDL site at Eastern Virginia Medical School and the DMCC respectively. When the expression profiling process was applied to sera from individuals with prostate cancer (N=197), BPH (N=92) or from otherwise healthy donors (N=97) we achieved an overall misclassification rate of 90% sensitivity. Since this represents a noticeable improvement in current clinical approach we are proposing to embark upon a validation process. The described studies are designed to address validation issues and include three phases. Phase 1; Synchronization of SELDI Output within the EDRN-Prostate-SELDI Investigational Collaboration (EPSIC); addressing portability (A) Synchronize SELDI instrumentation and robotic sample processing across the EPSIC using pooled serum(QC); (B) Establish the portability and reproducibility of the SELDI protein profiling approach within the EPSIC using normal and prostate cancer patient’s serum from a single site; (C) Establish robustness of the approach toward geographic, sample collection and processing differences within EPSIC using case and control serum from five different sites. Phase 2; Population Validation Establish geographic variability and robustness in a large cross-sectional study among different sample population. Phase 3; Clinical Validation; validate the serum protein expression profiling coupled with a learning algorithm as a means for early detection of prostate cancer using longitudinal PCPT samples. We have assembled a cohesive multi-institutional team for completing these studies in a timely and efficient manner. The team consists of five EDRN laboratories, DMCC and CBI and the proposed budget reflects the total involvement.

Comprehensive identification and profiling of host miRNAs in response to Singapore grouper iridovirus (SGIV) infection in grouper (Epinephelus coioides).

PubMed

Guo, Chuanyu; Cui, Huachun; Ni, Songwei; Yan, Yang; Qin, Qiwei

2015-10-01

microRNAs (miRNAs) are an evolutionarily conserved class of non-coding RNA molecules that participate in various biological processes. Employment of high-throughput screening strategies greatly prompts the investigation and profiling of miRNAs in diverse species. In recent years, grouper (Epinephelus spp.) aquaculture was severely affected by iridoviral diseases. However, knowledge regarding the host immune responses to viral infection, especially the miRNA-mediated immune regulatory roles, is rather limited. In this study, by employing Solexa deep sequencing approach, we identified 116 grouper miRNAs from grouper spleen-derived cells (GS). As expected, these miRNAs shared high sequence similarity with miRNAs identified in zebrafish (Danio rerio), pufferfish (Fugu rubripes), and other higher vertebrates. In the process of Singapore grouper iridovirus (SGIV) infection, 45 and 43 miRNAs with altered expression (>1.5-fold) were identified by miRNA microarray assays in grouper spleen tissues and GS cells, respectively. Furthermore, target prediction revealed 189 putative targets of these grouper miRNAs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Profiling of G protein-coupled receptors in vagal afferents reveals novel gut-to-brain sensing mechanisms.

PubMed

Egerod, Kristoffer L; Petersen, Natalia; Timshel, Pascal N; Rekling, Jens C; Wang, Yibing; Liu, Qinghua; Schwartz, Thue W; Gautron, Laurent

2018-06-01

G protein-coupled receptors (GPCRs) act as transmembrane molecular sensors of neurotransmitters, hormones, nutrients, and metabolites. Because unmyelinated vagal afferents richly innervate the gastrointestinal mucosa, gut-derived molecules may directly modulate the activity of vagal afferents through GPCRs. However, the types of GPCRs expressed in vagal afferents are largely unknown. Here, we determined the expression profile of all GPCRs expressed in vagal afferents of the mouse, with a special emphasis on those innervating the gastrointestinal tract. Using a combination of high-throughput quantitative PCR, RNA sequencing, and in situ hybridization, we systematically quantified GPCRs expressed in vagal unmyelinated Na v 1.8-expressing afferents. GPCRs for gut hormones that were the most enriched in Na v 1.8-expressing vagal unmyelinated afferents included NTSR1, NPY2R, CCK1R, and to a lesser extent, GLP1R, but not GHSR and GIPR. Interestingly, both GLP1R and NPY2R were coexpressed with CCK1R. In contrast, NTSR1 was coexpressed with GPR65, a marker preferentially enriched in intestinal mucosal afferents. Only few microbiome-derived metabolite sensors such as GPR35 and, to a lesser extent, GPR119 and CaSR were identified in the Na v 1.8-expressing vagal afferents. GPCRs involved in lipid sensing and inflammation (e.g. CB1R, CYSLTR2, PTGER4), and neurotransmitters signaling (CHRM4, DRD2, CRHR2) were also highly enriched in Na v 1.8-expressing neurons. Finally, we identified 21 orphan GPCRs with unknown functions in vagal afferents. Overall, this study provides a comprehensive description of GPCR-dependent sensing mechanisms in vagal afferents, including novel coexpression patterns, and conceivably coaction of key receptors for gut-derived molecules involved in gut-brain communication. Copyright © 2018 The Authors. Published by Elsevier GmbH.. All rights reserved.

Comparison of Normal and Breast Cancer Cell lines using Proteome, Genome and Interactome data

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

Patwardhan, Anil J.; Strittmatter, Eric F.; Camp, David G.

2005-12-01

Normal and cancer cell line proteomes were profiled using high throughput mass spectrometry techniques. Application of both protein-level and peptide-level sample fractionation combined with LC-MS/MS analysis enabled the confident identification of 2,235 unmodified proteins representing a broad range of functional and compartmental classes. An iterative multi-step search strategy was used to identify post-translational modifications and detected several proteins that are preferentially modified in cancer cells. Information regarding both unmodified and modified protein forms was combined with publicly available gene expression and protein-protein interaction data. The resulting integrated dataset revealed several functionally related proteins that are differentially regulated between normal andmore » cancer cell lines.« less

Droplet-based microfluidic analysis and screening of single plant cells.

PubMed

Yu, Ziyi; Boehm, Christian R; Hibberd, Julian M; Abell, Chris; Haseloff, Jim; Burgess, Steven J; Reyna-Llorens, Ivan

2018-01-01

Droplet-based microfluidics has been used to facilitate high-throughput analysis of individual prokaryote and mammalian cells. However, there is a scarcity of similar workflows applicable to rapid phenotyping of plant systems where phenotyping analyses typically are time-consuming and low-throughput. We report on-chip encapsulation and analysis of protoplasts isolated from the emergent plant model Marchantia polymorpha at processing rates of >100,000 cells per hour. We use our microfluidic system to quantify the stochastic properties of a heat-inducible promoter across a population of transgenic protoplasts to demonstrate its potential for assessing gene expression activity in response to environmental conditions. We further demonstrate on-chip sorting of droplets containing YFP-expressing protoplasts from wild type cells using dielectrophoresis force. This work opens the door to droplet-based microfluidic analysis of plant cells for applications ranging from high-throughput characterisation of DNA parts to single-cell genomics to selection of rare plant phenotypes.

Emory University: High-Throughput Protein-Protein Interaction Dataset for Lung Cancer-Associated Genes | Office of Cancer Genomics

Cancer.gov

To discover novel PPI signaling hubs for lung cancer, CTD2 Center at Emory utilized large-scale genomics datasets and literature to compile a set of lung cancer-associated genes. A library of expression vectors were generated for these genes and utilized for detecting pairwise PPIs with cell lysate-based TR-FRET assays in high-throughput screening format. Read the abstract.

Clinical Trials of Precision Medicine through Molecular Profiling: Focus on Breast Cancer.

PubMed

Zardavas, Dimitrios; Piccart-Gebhart, Martine

2015-01-01

High-throughput technologies of molecular profiling in cancer, such as gene-expression profiling and next-generation sequencing, are expanding our knowledge of the molecular landscapes of several cancer types. This increasing knowledge coupled with the development of several molecularly targeted agents hold the promise for personalized cancer medicine to be fully realized. Moreover, an expanding armamentarium of targeted agents has been approved for the treatment of specific molecular cancer subgroups in different diagnoses. According to this paradigm, treatment selection should be dictated by the specific molecular aberrations found in each patient's tumor. The classical clinical trials paradigm of patients' eligibility being based on clinicopathologic parameters is being abandoned, with current clinical trials enrolling patients on the basis of specific molecular aberrations. New, innovative trial designs have been generated to better tackle the multiple challenges induced by the increasing molecular fragmentation of cancer, namely: (1) longitudinal cohort studies with or without downstream trials, (2) studies assessing the clinical utility of molecular profiling, (3) master or umbrella trials, (4) basket trials, (5) N-of-1 trials, and (6) adaptive design trials. This article provides an overview of the challenges for clinical trials in the era of molecular profiling of cancer. Subsequently, innovative trial designs with respective examples and their potential to expedite efficient clinical development of targeted anticancer agents is discussed.

Characterization of three human cell line models for high-throughput neuronal cytotoxicity screening.

PubMed

Tong, Zhi-Bin; Hogberg, Helena; Kuo, David; Sakamuru, Srilatha; Xia, Menghang; Smirnova, Lena; Hartung, Thomas; Gerhold, David

2017-02-01

More than 75 000 man-made chemicals contaminate the environment; many of these have not been tested for toxicities. These chemicals demand quantitative high-throughput screening assays to assess them for causative roles in neurotoxicities, including Parkinson's disease and other neurodegenerative disorders. To facilitate high throughput screening for cytotoxicity to neurons, three human neuronal cellular models were compared: SH-SY5Y neuroblastoma cells, LUHMES conditionally-immortalized dopaminergic neurons, and Neural Stem Cells (NSC) derived from human fetal brain. These three cell lines were evaluated for rapidity and degree of differentiation, and sensitivity to 32 known or candidate neurotoxicants. First, expression of neural differentiation genes was assayed during a 7-day differentiation period. Of the three cell lines, LUHMES showed the highest gene expression of neuronal markers after differentiation. Both in the undifferentiated state and after 7 days of neuronal differentiation, LUHMES cells exhibited greater cytotoxic sensitivity to most of 32 suspected or known neurotoxicants than SH-SY5Y or NSCs. LUHMES cells were also unique in being more susceptible to several compounds in the differentiating state than in the undifferentiated state; including known neurotoxicants colchicine, methyl-mercury (II), and vincristine. Gene expression results suggest that differentiating LUHMES cells may be susceptible to apoptosis because they express low levels of anti-apoptotic genes BCL2 and BIRC5/survivin, whereas SH-SY5Y cells may be resistant to apoptosis because they express high levels of BCL2, BIRC5/survivin, and BIRC3 genes. Thus, LUHMES cells exhibited favorable characteristics for neuro-cytotoxicity screening: rapid differentiation into neurons that exhibit high level expression neuronal marker genes, and marked sensitivity of LUHMES cells to known neurotoxicants. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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

PubMed

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

2015-05-01

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

On the possibility of using polycrystalline material in the development of structure-based generic assays

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

Allaire, Marc, E-mail: allaire@bnl.gov; Moiseeva, Natalia; Botez, Cristian E.

The correlation coefficients calculated between raw powder diffraction profiles can be used to identify ligand-bound/unbound states of lysozyme. The discovery of ligands that bind specifically to a targeted protein benefits from the development of generic assays for high-throughput screening of a library of chemicals. Protein powder diffraction (PPD) has been proposed as a potential method for use as a structure-based assay for high-throughput screening applications. Building on this effort, powder samples of bound/unbound states of soluble hen-egg white lysozyme precipitated with sodium chloride were compared. The correlation coefficients calculated between the raw diffraction profiles were consistent with the known bindingmore » properties of the ligands and suggested that the PPD approach can be used even prior to a full description using stereochemically restrained Rietveld refinement.« less

Large-scale screening of transcription factor–promoter interactions in spruce reveals a transcriptional network involved in vascular development

PubMed Central

Lachance, Denis; Giguère, Isabelle; Séguin, Armand

2014-01-01

This research aimed to investigate the role of diverse transcription factors (TFs) and to delineate gene regulatory networks directly in conifers at a relatively high-throughput level. The approach integrated sequence analyses, transcript profiling, and development of a conifer-specific activation assay. Transcript accumulation profiles of 102 TFs and potential target genes were clustered to identify groups of coordinately expressed genes. Several different patterns of transcript accumulation were observed by profiling in nine different organs and tissues: 27 genes were preferential to secondary xylem both in stems and roots, and other genes were preferential to phelloderm and periderm or were more ubiquitous. A robust system has been established as a screening approach to define which TFs have the ability to regulate a given promoter in planta. Trans-activation or repression effects were observed in 30% of TF–candidate gene promoter combinations. As a proof of concept, phylogenetic analysis and expression and trans-activation data were used to demonstrate that two spruce NAC-domain proteins most likely play key roles in secondary vascular growth as observed in other plant species. This study tested many TFs from diverse families in a conifer tree species, which broadens the knowledge of promoter–TF interactions in wood development and enables comparisons of gene regulatory networks found in angiosperms and gymnosperms. PMID:24713992

Using Poisson mixed-effects model to quantify transcript-level gene expression in RNA-Seq.

PubMed

Hu, Ming; Zhu, Yu; Taylor, Jeremy M G; Liu, Jun S; Qin, Zhaohui S

2012-01-01

RNA sequencing (RNA-Seq) is a powerful new technology for mapping and quantifying transcriptomes using ultra high-throughput next-generation sequencing technologies. Using deep sequencing, gene expression levels of all transcripts including novel ones can be quantified digitally. Although extremely promising, the massive amounts of data generated by RNA-Seq, substantial biases and uncertainty in short read alignment pose challenges for data analysis. In particular, large base-specific variation and between-base dependence make simple approaches, such as those that use averaging to normalize RNA-Seq data and quantify gene expressions, ineffective. In this study, we propose a Poisson mixed-effects (POME) model to characterize base-level read coverage within each transcript. The underlying expression level is included as a key parameter in this model. Since the proposed model is capable of incorporating base-specific variation as well as between-base dependence that affect read coverage profile throughout the transcript, it can lead to improved quantification of the true underlying expression level. POME can be freely downloaded at http://www.stat.purdue.edu/~yuzhu/pome.html. yuzhu@purdue.edu; zhaohui.qin@emory.edu Supplementary data are available at Bioinformatics online.

Characterization and expression patterns of small RNAs in synthesized Brassica hexaploids.

PubMed

Shen, Yanyue; Zhao, Qin; Zou, Jun; Wang, Wenliang; Gao, Yi; Meng, Jinling; Wang, Jianbo

2014-06-01

Polyploidy has played an important role in promoting plant evolution through genomic merging and doubling. We used high-throughput sequencing to compare miRNA expression profiles between Brassica hexaploid and its parents. A total of 613, 784 and 742 known miRNAs were identified in Brassica rapa, Brassica carinata, and Brassica hexaploid, respectively. We detected 618 miRNAs were differentially expressed (log(2)Ratio ≥ 1, P ≤ 0.05) between Brassica hexaploid and its parents, and 425 miRNAs were non-additively expressed in Brassica hexaploid, which suggest a trend of non-additive miRNA regulation following hybridization and polyploidization. Remarkably, majority of the non-additively expressed miRNAs in the Brassica hexaploid are repressed, and there was a bias toward repression of B. rapa miRNAs, which is consistent with the progenitor-biased gene repression in the synthetic allopolyploids. In addition, we identified 653 novel mature miRNAs in Brassica hexaploid and its parents. Finally, we found that almost all the non-additive accumulation of siRNA clusters exhibited a low-parent pattern in Brassica hexaploid. Non-additive small RNA regulation is involved in a range of biological pathways, probably providing a driving force for variation and adaptation in allopolyploids.

Hydrocortisone-induced parkin prevents dopaminergic cell death via CREB pathway in Parkinson's disease model.

PubMed

Ham, Sangwoo; Lee, Yun-Il; Jo, Minkyung; Kim, Hyojung; Kang, Hojin; Jo, Areum; Lee, Gum Hwa; Mo, Yun Jeong; Park, Sang Chul; Lee, Yun Song; Shin, Joo-Ho; Lee, Yunjong

2017-04-03

Dysfunctional parkin due to mutations or post-translational modifications contributes to dopaminergic neurodegeneration in Parkinson's disease (PD). Overexpression of parkin provides protection against cellular stresses and prevents dopamine cell loss in several PD animal models. Here we performed an unbiased high-throughput luciferase screening to identify chemicals that can increase parkin expression. Among promising parkin inducers, hydrocortisone possessed the most favorable profiles including parkin induction ability, cell protection ability, and physicochemical property of absorption, distribution, metabolism, and excretion (ADME) without inducing endoplasmic reticulum stress. We found that hydrocortisone-induced parkin expression was accountable for cell protection against oxidative stress. Hydrocortisone-activated parkin expression was mediated by CREB pathway since gRNA to CREB abolished hydrocortisone's ability to induce parkin. Finally, hydrocortisone treatment in mice increased brain parkin levels and prevented 6-hydroxy dopamine induced dopamine cell loss when assessed at 4 days after the toxin's injection. Our results showed that hydrocortisone could stimulate parkin expression via CREB pathway and the induced parkin expression was accountable for its neuroprotective effect. Since glucocorticoid is a physiological hormone, maintaining optimal levels of glucocorticoid might be a potential therapeutic or preventive strategy for Parkinson's disease.

A versatile and efficient high-throughput cloning tool for structural biology.

PubMed

Geertsma, Eric R; Dutzler, Raimund

2011-04-19

Methods for the cloning of large numbers of open reading frames into expression vectors are of critical importance for challenging structural biology projects. Here we describe a system termed fragment exchange (FX) cloning that facilitates the high-throughput generation of expression constructs. The method is based on a class IIS restriction enzyme and negative selection markers. FX cloning combines attractive features of established recombination- and ligation-independent cloning methods: It allows the straightforward transfer of an open reading frame into a variety of expression vectors and is highly efficient and very economic in its use. In addition, FX cloning avoids the common but undesirable feature of significantly extending target open reading frames with cloning related sequences, as it leaves a minimal seam of only a single extra amino acid to either side of the protein. The method has proven to be very robust and suitable for all common pro- and eukaryotic expression systems. It considerably speeds up the generation of expression constructs compared to traditional methods and thus facilitates a broader expression screening.

Differential deposition of H2A.Z in rice seedling tissue during the day-night cycle.

PubMed

Zhang, Kang; Xu, Wenying; Wang, Chunchao; Yi, Xin; Su, Zhen

2017-03-04

Chromatin structure has an important role in modulating gene expression. The incorporation of histone variants into the nucleosome leads to important changes in the chromatin structure. The histone variant H2A.Z is highly conserved between different species of fungi, animals, and plants. However, dynamic changes to H2A.Z in rice have not been reported during the day-night cycle. In this study, we generated genome wide maps of H2A.Z for day and night time in harvested seedling tissues by combining chromatin immunoprecipitation and high-throughput sequencing. The analysis results for the H2A.Z data sets detected 7099 genes with higher depositions of H2A.Z in seedling tissues harvested at night compared with seedling tissues harvested during the day, whereas 4597 genes had higher H2A.Z depositions in seedlings harvested during the day. The gene expression profiles data suggested that H2A.Z probably negatively regulated gene expression during the day-night cycle and was involved in many important biologic processes. In general, our results indicated that H2A.Z may play an important role in plant responses to the diurnal oscillation process.

Characterization of gonadal transcriptomes from the turbot (Scophthalmus maximus).

PubMed

Hu, Yulong; Huang, Meng; Wang, Weiji; Guan, Jiantao; Kong, Jie

2016-01-01

The mechanisms underlying sexual reproduction and sex ratio determination remains unclear in turbot, a flatfish of great commercial value. And there is limited information in the turbot database regarding genes related to the reproductive system. Here, we conducted high-throughput transcriptome profiling of turbot gonad tissues to better understand their reproductive functions and to supply essential gene sequence information for marker-assisted selection programs in the turbot industry. In this study, two gonad libraries representing sex differences in Scophthalmus maximus yielded 453 818 high-quality reads that were assembled into 24 611 contigs and 33 713 singletons by using 454 pyrosequencing, 13 936 contigs and singletons (CS) of which were annotated using BLASTx. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses revealed that various biological functions and processes were associated with many of the annotated CS. Expression analyses showed that 510 genes were differentially expressed in males versus females; 80% of these genes were annotated. In addition, 6484 and 6036 single nucleotide polymorphisms (SNPs) were identified in male and female libraries, respectively. This transcriptome resource will serve as the foundation for cDNA or SNP microarray construction, gene expression characterization, and sex-specific linkage mapping in turbot.

ReTrOS: a MATLAB toolbox for reconstructing transcriptional activity from gene and protein expression data.

PubMed

Minas, Giorgos; Momiji, Hiroshi; Jenkins, Dafyd J; Costa, Maria J; Rand, David A; Finkenstädt, Bärbel

2017-06-26

Given the development of high-throughput experimental techniques, an increasing number of whole genome transcription profiling time series data sets, with good temporal resolution, are becoming available to researchers. The ReTrOS toolbox (Reconstructing Transcription Open Software) provides MATLAB-based implementations of two related methods, namely ReTrOS-Smooth and ReTrOS-Switch, for reconstructing the temporal transcriptional activity profile of a gene from given mRNA expression time series or protein reporter time series. The methods are based on fitting a differential equation model incorporating the processes of transcription, translation and degradation. The toolbox provides a framework for model fitting along with statistical analyses of the model with a graphical interface and model visualisation. We highlight several applications of the toolbox, including the reconstruction of the temporal cascade of transcriptional activity inferred from mRNA expression data and protein reporter data in the core circadian clock in Arabidopsis thaliana, and how such reconstructed transcription profiles can be used to study the effects of different cell lines and conditions. The ReTrOS toolbox allows users to analyse gene and/or protein expression time series where, with appropriate formulation of prior information about a minimum of kinetic parameters, in particular rates of degradation, users are able to infer timings of changes in transcriptional activity. Data from any organism and obtained from a range of technologies can be used as input due to the flexible and generic nature of the model and implementation. The output from this software provides a useful analysis of time series data and can be incorporated into further modelling approaches or in hypothesis generation.

Quartz-Seq2: a high-throughput single-cell RNA-sequencing method that effectively uses limited sequence reads.

PubMed

Sasagawa, Yohei; Danno, Hiroki; Takada, Hitomi; Ebisawa, Masashi; Tanaka, Kaori; Hayashi, Tetsutaro; Kurisaki, Akira; Nikaido, Itoshi

2018-03-09

High-throughput single-cell RNA-seq methods assign limited unique molecular identifier (UMI) counts as gene expression values to single cells from shallow sequence reads and detect limited gene counts. We thus developed a high-throughput single-cell RNA-seq method, Quartz-Seq2, to overcome these issues. Our improvements in the reaction steps make it possible to effectively convert initial reads to UMI counts, at a rate of 30-50%, and detect more genes. To demonstrate the power of Quartz-Seq2, we analyzed approximately 10,000 transcriptomes from in vitro embryonic stem cells and an in vivo stromal vascular fraction with a limited number of reads.

Conceptualizing adverse outcome pathways for ...

EPA Pesticide Factsheets

Cyclooxygenase (COX) inhibition is of concern in fish because COX inhibitors (e.g., ibuprofen) are ubiquitous in aquatic systems/fish tissues, and can disrupt synthesis of prostaglandins that modulate a variety of essential biological functions (e.g., reproduction). This study utilized newly generated high content (transcriptomic and metabolomic) empirical data in combination with existing high throughput (ACTOR, epa.gov) toxicity data to facilitate development of adverse outcome pathways (AOPs) for molecular initiating event (MIE) of COX inhibition. We examined effects of a waterborne, 96h exposure to three COX inhibitors (indomethacin (IN; 100 µg/L), ibuprofen (IB; 200 µg/L) and celecoxib (CX; 20 µg/L) on the liver metabolome and ovarian gene expression (using oligonucleotide microarray 4 x15K platform) in sexually mature fathead minnows (n=8). Differentially expressed genes were identified (t-test, p < 0.01), and functional analyses performed to determine enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways (p < 0.05). Principal component analysis indicated that liver metabolomics profiles of IN, IB and CX were not significantly different from control or one another. When compared to control, exposure to IB and CX resulted in differential expression of comparable numbers of genes (IB = 433, CX= 545). In contrast, 2558 genes were differentially expressed in IN-treated fish. KEGG pathway analyses show that IN had extensive effects on oocyte meios

NF-κB dynamics show digital activation and analog information processing in cells

NASA Astrophysics Data System (ADS)

Tay, Savas; Hughey, Jake; Lee, Timothy; Lipniacki, Tomasz; Covert, Markus; Quake, Stephen

2010-03-01

Cells operate in ever changing environments using extraordinary communication capabilities. Cell-to-cell communication is mediated by signaling molecules that form spatiotemporal concentration gradients, which requires cells to respond to a wide range of signal intensities. We used high-throughput microfluidic cell culture, quantitative gene expression analysis and mathematical modeling to investigate how single mammalian cells respond to different concentrations of the signaling molecule TNF-α via the transcription factor NF-κB. We measured NF-κB activity in thousands of live cells under TNF-α doses covering four orders of magnitude. In contrast to population studies, the activation is a stochastic, switch-like process at the single cell level with fewer cells responding at lower doses. The activated cells respond fully and express early genes independent of the TNF-α concentration, while only high dose stimulation results in the expression of late genes. Cells also encode a set of analog parameters such as the NF-κB peak intensity, response time and number of oscillations to modulate the outcome. We developed a stochastic model that reproduces both the digital and analog dynamics as well as the gene expression profiles at all measured conditions, constituting a broadly applicable model for TNF-α induced NF-κB signaling in various types of cells.

Transcriptomics of mRNA and egg quality in farmed fish: Some recent developments and future directions.

PubMed

Sullivan, Craig V; Chapman, Robert W; Reading, Benjamin J; Anderson, Paul E

2015-09-15

Maternal mRNA transcripts deposited in growing oocytes regulate early development and are under intensive investigation as determinants of egg quality. The research has evolved from single gene studies to microarray and now RNA-Seq analyses in which mRNA expression by virtually every gene can be assessed and related to gamete quality. Such studies have mainly focused on genes changing two- to several-fold in expression between biological states, and have identified scores of candidate genes and a few gene networks whose functioning is related to successful development. However, ever-increasing yields of information from high throughput methods for detecting transcript abundance have far outpaced progress in methods for analyzing the massive quantities of gene expression data, and especially for meaningful relation of whole transcriptome profiles to gamete quality. We have developed a new approach to this problem employing artificial neural networks and supervised machine learning with other novel bioinformatics procedures to discover a previously unknown level of ovarian transcriptome function at which minute changes in expression of a few hundred genes is highly predictive of egg quality. In this paper, we briefly review the progress in transcriptomics of fish egg quality and discuss some future directions for this field of study. Copyright © 2015 Elsevier Inc. All rights reserved.

Integrative Analysis of Cancer Diagnosis Studies with Composite Penalization

PubMed Central

Liu, Jin; Huang, Jian; Ma, Shuangge

2013-01-01

Summary In cancer diagnosis studies, high-throughput gene profiling has been extensively conducted, searching for genes whose expressions may serve as markers. Data generated from such studies have the “large d, small n” feature, with the number of genes profiled much larger than the sample size. Penalization has been extensively adopted for simultaneous estimation and marker selection. Because of small sample sizes, markers identified from the analysis of single datasets can be unsatisfactory. A cost-effective remedy is to conduct integrative analysis of multiple heterogeneous datasets. In this article, we investigate composite penalization methods for estimation and marker selection in integrative analysis. The proposed methods use the minimax concave penalty (MCP) as the outer penalty. Under the homogeneity model, the ridge penalty is adopted as the inner penalty. Under the heterogeneity model, the Lasso penalty and MCP are adopted as the inner penalty. Effective computational algorithms based on coordinate descent are developed. Numerical studies, including simulation and analysis of practical cancer datasets, show satisfactory performance of the proposed methods. PMID:24578589

Comprehensive RNA-Seq profiling to evaluate lactating sheep mammary gland transcriptome

PubMed Central

Suárez-Vega, Aroa; Gutiérrez-Gil, Beatriz; Klopp, Christophe; Tosser-Klopp, Gwenola; Arranz, Juan-José

2016-01-01

RNA-Seq enables the generation of extensive transcriptome information providing the capability to characterize transcripts (including alternative isoforms and polymorphism), to quantify expression and to identify differential regulation in a single experiment. Our aim in this study was to take advantage of using RNA-Seq high-throughput technology to provide a comprehensive transcriptome profiling of the sheep lactating mammary gland. Eight ewes of two dairy sheep breeds with differences in milk production traits were used in this experiment (four Churra and four Assaf ewes). Milk samples from these animals were collected on days 10, 50, 120 and 150 after lambing to cover the various physiological stages of the mammary gland across the complete lactation. RNA samples were extracted from milk somatic cells. The RNA-Seq dataset was generated using an Illumina HiSeq 2000 sequencer. The information reported here will be useful to understand the biology of lactation in sheep, providing also an opportunity to characterize their different patterns on milk production aptitude. PMID:27377755

Clustering Single-Cell Expression Data Using Random Forest Graphs.

PubMed

Pouyan, Maziyar Baran; Nourani, Mehrdad

2017-07-01

Complex tissues such as brain and bone marrow are made up of multiple cell types. As the study of biological tissue structure progresses, the role of cell-type-specific research becomes increasingly important. Novel sequencing technology such as single-cell cytometry provides researchers access to valuable biological data. Applying machine-learning techniques to these high-throughput datasets provides deep insights into the cellular landscape of the tissue where those cells are a part of. In this paper, we propose the use of random-forest-based single-cell profiling, a new machine-learning-based technique, to profile different cell types of intricate tissues using single-cell cytometry data. Our technique utilizes random forests to capture cell marker dependences and model the cellular populations using the cell network concept. This cellular network helps us discover what cell types are in the tissue. Our experimental results on public-domain datasets indicate promising performance and accuracy of our technique in extracting cell populations of complex tissues.

Comprehensive RNA-Seq profiling to evaluate lactating sheep mammary gland transcriptome.

PubMed

Suárez-Vega, Aroa; Gutiérrez-Gil, Beatriz; Klopp, Christophe; Tosser-Klopp, Gwenola; Arranz, Juan-José

2016-07-05

RNA-Seq enables the generation of extensive transcriptome information providing the capability to characterize transcripts (including alternative isoforms and polymorphism), to quantify expression and to identify differential regulation in a single experiment. Our aim in this study was to take advantage of using RNA-Seq high-throughput technology to provide a comprehensive transcriptome profiling of the sheep lactating mammary gland. Eight ewes of two dairy sheep breeds with differences in milk production traits were used in this experiment (four Churra and four Assaf ewes). Milk samples from these animals were collected on days 10, 50, 120 and 150 after lambing to cover the various physiological stages of the mammary gland across the complete lactation. RNA samples were extracted from milk somatic cells. The RNA-Seq dataset was generated using an Illumina HiSeq 2000 sequencer. The information reported here will be useful to understand the biology of lactation in sheep, providing also an opportunity to characterize their different patterns on milk production aptitude.

High throughput screening and profiling of high-value carotenoids from a wide diversity of bacteria in surface seawater.

PubMed

Asker, Dalal

2018-09-30

Carotenoids are valuable natural colorants that exhibit numerous health promoting properties, and thus are widely used in food, feeds, pharmaceutical and nutraceuticals industries. In this study, we isolated and identified novel microbial sources that produced high-value carotenoids using high throughput screening (HTS). A total of 701 pigmented microbial strains library including marine bacteria and red yeast was constructed. Carotenoids profiling using HPLC-DAD-MS methods showed 88 marine bacterial strains with potential for the production of high-value carotenoids including astaxanthin (28 strains), zeaxanthin (21 strains), lutein (1 strains) and canthaxanthin (2 strains). A comprehensive 16S rRNA gene based phylogenetic analysis revealed that these strains can be classified into 30 species belonging to five bacterial classes (Flavobacteriia, α-Proteobacteria, γ-Proteobacteria, Actinobacteria and Bacilli). Importantly, we discovered novel producers of zeaxanthin and lutein, and a high diversity in both carotenoids and producing microbial strains, which are promising and highly selective biotechnological sources for high-value carotenoids. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multiplex enrichment quantitative PCR (ME-qPCR): a high-throughput, highly sensitive detection method for GMO identification.

PubMed

Fu, Wei; Zhu, Pengyu; Wei, Shuang; Zhixin, Du; Wang, Chenguang; Wu, Xiyang; Li, Feiwu; Zhu, Shuifang

2017-04-01

Among all of the high-throughput detection methods, PCR-based methodologies are regarded as the most cost-efficient and feasible methodologies compared with the next-generation sequencing or ChIP-based methods. However, the PCR-based methods can only achieve multiplex detection up to 15-plex due to limitations imposed by the multiplex primer interactions. The detection throughput cannot meet the demands of high-throughput detection, such as SNP or gene expression analysis. Therefore, in our study, we have developed a new high-throughput PCR-based detection method, multiplex enrichment quantitative PCR (ME-qPCR), which is a combination of qPCR and nested PCR. The GMO content detection results in our study showed that ME-qPCR could achieve high-throughput detection up to 26-plex. Compared to the original qPCR, the Ct values of ME-qPCR were lower for the same group, which showed that ME-qPCR sensitivity is higher than the original qPCR. The absolute limit of detection for ME-qPCR could achieve levels as low as a single copy of the plant genome. Moreover, the specificity results showed that no cross-amplification occurred for irrelevant GMO events. After evaluation of all of the parameters, a practical evaluation was performed with different foods. The more stable amplification results, compared to qPCR, showed that ME-qPCR was suitable for GMO detection in foods. In conclusion, ME-qPCR achieved sensitive, high-throughput GMO detection in complex substrates, such as crops or food samples. In the future, ME-qPCR-based GMO content identification may positively impact SNP analysis or multiplex gene expression of food or agricultural samples. Graphical abstract For the first-step amplification, four primers (A, B, C, and D) have been added into the reaction volume. In this manner, four kinds of amplicons have been generated. All of these four amplicons could be regarded as the target of second-step PCR. For the second-step amplification, three parallels have been taken for the final evaluation. After the second evaluation, the final amplification curves and melting curves have been achieved.

Construction of siRNA/miRNA expression vectors based on a one-step PCR process

PubMed Central

Xu, Jun; Zeng, Jie Qiong; Wan, Gang; Hu, Gui Bin; Yan, Hong; Ma, Li Xin

2009-01-01

Background RNA interference (RNAi) has become a powerful means for silencing target gene expression in mammalian cells and is envisioned to be useful in therapeutic approaches to human disease. In recent years, high-throughput, genome-wide screening of siRNA/miRNA libraries has emerged as a desirable approach. Current methods for constructing siRNA/miRNA expression vectors require the synthesis of long oligonucleotides, which is costly and suffers from mutation problems. Results Here we report an ingenious method to solve traditional problems associated with construction of siRNA/miRNA expression vectors. We synthesized shorter primers (< 50 nucleotides) to generate a linear expression structure by PCR. The PCR products were directly transformed into chemically competent E. coli and converted to functional vectors in vivo via homologous recombination. The positive clones could be easily screened under UV light. Using this method we successfully constructed over 500 functional siRNA/miRNA expression vectors. Sequencing of the vectors confirmed a high accuracy rate. Conclusion This novel, convenient, low-cost and highly efficient approach may be useful for high-throughput assays of RNAi libraries. PMID:19490634

Genome-wide coexpression dynamics: Theory and application

PubMed Central

Li, Ker-Chau

2002-01-01

High-throughput expression profiling enables the global study of gene activities. Genes with positively correlated expression profiles are likely to encode functionally related proteins. However, all biological processes are interlocked, and each protein may play multiple cellular roles. Thus the coexpression of any two functionally related genes may depend on the constantly varying, yet often-unknown cellular state. To initiate a systematic study on this issue, a theory of coexpression dynamics is presented. This theory is used to rationalize a strategy of conducting a genome-wide search for the most critical cellular players that may affect the coexpression pattern of any two genes. In one example, using a yeast data set, our method reveals how the enzymes associated with the urea cycle are expressed to ensure proper mass flow of the involved metabolites. The correlation between ARG2 and CAR2 is found to change from positive to negative as the expression level of CPA2 increases. This delicate interplay in correlation signifies a remarkable control on the influx and efflux of ornithine and reflects well the intrinsic cellular demand for arginine. In addition to the urea cycle, our examples include SCH9 and CYR1 (both implicated in a recent longevity study), cytochrome c1 (mitochondrial electron transport), calmodulin (main calcium-binding protein), PFK1 and PFK2 (glycolysis), and two genes, ECM1 and YNL101W, the functions of which are newly revealed. The complexity in computation is eased by a new result from mathematical statistics. PMID:12486219

Quantitative multiplex quantum dot in-situ hybridisation based gene expression profiling in tissue microarrays identifies prognostic genes in acute myeloid leukaemia

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

Tholouli, Eleni; MacDermott, Sarah; Hoyland, Judith

2012-08-24

Highlights: Black-Right-Pointing-Pointer Development of a quantitative high throughput in situ expression profiling method. Black-Right-Pointing-Pointer Application to a tissue microarray of 242 AML bone marrow samples. Black-Right-Pointing-Pointer Identification of HOXA4, HOXA9, Meis1 and DNMT3A as prognostic markers in AML. -- Abstract: Measurement and validation of microarray gene signatures in routine clinical samples is problematic and a rate limiting step in translational research. In order to facilitate measurement of microarray identified gene signatures in routine clinical tissue a novel method combining quantum dot based oligonucleotide in situ hybridisation (QD-ISH) and post-hybridisation spectral image analysis was used for multiplex in-situ transcript detection inmore » archival bone marrow trephine samples from patients with acute myeloid leukaemia (AML). Tissue-microarrays were prepared into which white cell pellets were spiked as a standard. Tissue microarrays were made using routinely processed bone marrow trephines from 242 patients with AML. QD-ISH was performed for six candidate prognostic genes using triplex QD-ISH for DNMT1, DNMT3A, DNMT3B, and for HOXA4, HOXA9, Meis1. Scrambled oligonucleotides were used to correct for background staining followed by normalisation of expression against the expression values for the white cell pellet standard. Survival analysis demonstrated that low expression of HOXA4 was associated with poorer overall survival (p = 0.009), whilst high expression of HOXA9 (p < 0.0001), Meis1 (p = 0.005) and DNMT3A (p = 0.04) were associated with early treatment failure. These results demonstrate application of a standardised, quantitative multiplex QD-ISH method for identification of prognostic markers in formalin-fixed paraffin-embedded clinical samples, facilitating measurement of gene expression signatures in routine clinical samples.« less

Genome-wide analysis of alternative splicing during human heart development

NASA Astrophysics Data System (ADS)

Wang, He; Chen, Yanmei; Li, Xinzhong; Chen, Guojun; Zhong, Lintao; Chen, Gangbing; Liao, Yulin; Liao, Wangjun; Bin, Jianping

2016-10-01

Alternative splicing (AS) drives determinative changes during mouse heart development. Recent high-throughput technological advancements have facilitated genome-wide AS, while its analysis in human foetal heart transition to the adult stage has not been reported. Here, we present a high-resolution global analysis of AS transitions between human foetal and adult hearts. RNA-sequencing data showed extensive AS transitions occurred between human foetal and adult hearts, and AS events occurred more frequently in protein-coding genes than in long non-coding RNA (lncRNA). A significant difference of AS patterns was found between foetal and adult hearts. The predicted difference in AS events was further confirmed using quantitative reverse transcription-polymerase chain reaction analysis of human heart samples. Functional foetal-specific AS event analysis showed enrichment associated with cell proliferation-related pathways including cell cycle, whereas adult-specific AS events were associated with protein synthesis. Furthermore, 42.6% of foetal-specific AS events showed significant changes in gene expression levels between foetal and adult hearts. Genes exhibiting both foetal-specific AS and differential expression were highly enriched in cell cycle-associated functions. In conclusion, we provided a genome-wide profiling of AS transitions between foetal and adult hearts and proposed that AS transitions and deferential gene expression may play determinative roles in human heart development.

Global Analysis of Transcriptome Responses and Gene Expression Profiles to Cold Stress of Jatropha curcas L.

PubMed Central

Wang, Haibo; Zou, Zhurong; Wang, Shasha; Gong, Ming

2013-01-01

Background Jatropha curcas L., also called the Physic nut, is an oil-rich shrub with multiple uses, including biodiesel production, and is currently exploited as a renewable energy resource in many countries. Nevertheless, because of its origin from the tropical MidAmerican zone, J. curcas confers an inherent but undesirable characteristic (low cold resistance) that may seriously restrict its large-scale popularization. This adaptive flaw can be genetically improved by elucidating the mechanisms underlying plant tolerance to cold temperatures. The newly developed Illumina Hiseq™ 2000 RNA-seq and Digital Gene Expression (DGE) are deep high-throughput approaches for gene expression analysis at the transcriptome level, using which we carefully investigated the gene expression profiles in response to cold stress to gain insight into the molecular mechanisms of cold response in J. curcas. Results In total, 45,251 unigenes were obtained by assembly of clean data generated by RNA-seq analysis of the J. curcas transcriptome. A total of 33,363 and 912 complete or partial coding sequences (CDSs) were determined by protein database alignments and ESTScan prediction, respectively. Among these unigenes, more than 41.52% were involved in approximately 128 known metabolic or signaling pathways, and 4,185 were possibly associated with cold resistance. DGE analysis was used to assess the changes in gene expression when exposed to cold condition (12°C) for 12, 24, and 48 h. The results showed that 3,178 genes were significantly upregulated and 1,244 were downregulated under cold stress. These genes were then functionally annotated based on the transcriptome data from RNA-seq analysis. Conclusions This study provides a global view of transcriptome response and gene expression profiling of J. curcas in response to cold stress. The results can help improve our current understanding of the mechanisms underlying plant cold resistance and favor the screening of crucial genes for genetically enhancing cold resistance in J. curcas. PMID:24349370

Global analysis of transcriptome responses and gene expression profiles to cold stress of Jatropha curcas L.

PubMed

Wang, Haibo; Zou, Zhurong; Wang, Shasha; Gong, Ming

2013-01-01

Jatropha curcas L., also called the Physic nut, is an oil-rich shrub with multiple uses, including biodiesel production, and is currently exploited as a renewable energy resource in many countries. Nevertheless, because of its origin from the tropical MidAmerican zone, J. curcas confers an inherent but undesirable characteristic (low cold resistance) that may seriously restrict its large-scale popularization. This adaptive flaw can be genetically improved by elucidating the mechanisms underlying plant tolerance to cold temperatures. The newly developed Illumina Hiseq™ 2000 RNA-seq and Digital Gene Expression (DGE) are deep high-throughput approaches for gene expression analysis at the transcriptome level, using which we carefully investigated the gene expression profiles in response to cold stress to gain insight into the molecular mechanisms of cold response in J. curcas. In total, 45,251 unigenes were obtained by assembly of clean data generated by RNA-seq analysis of the J. curcas transcriptome. A total of 33,363 and 912 complete or partial coding sequences (CDSs) were determined by protein database alignments and ESTScan prediction, respectively. Among these unigenes, more than 41.52% were involved in approximately 128 known metabolic or signaling pathways, and 4,185 were possibly associated with cold resistance. DGE analysis was used to assess the changes in gene expression when exposed to cold condition (12°C) for 12, 24, and 48 h. The results showed that 3,178 genes were significantly upregulated and 1,244 were downregulated under cold stress. These genes were then functionally annotated based on the transcriptome data from RNA-seq analysis. This study provides a global view of transcriptome response and gene expression profiling of J. curcas in response to cold stress. The results can help improve our current understanding of the mechanisms underlying plant cold resistance and favor the screening of crucial genes for genetically enhancing cold resistance in J. curcas.

Epigenetic Control of Skeletal Development by the Histone Methyltransferase Ezh2*

PubMed Central

Dudakovic, Amel; Camilleri, Emily T.; Xu, Fuhua; Riester, Scott M.; McGee-Lawrence, Meghan E.; Bradley, Elizabeth W.; Paradise, Christopher R.; Lewallen, Eric A.; Thaler, Roman; Deyle, David R.; Larson, A. Noelle; Lewallen, David G.; Dietz, Allan B.; Stein, Gary S.; Montecino, Martin A.; Westendorf, Jennifer J.; van Wijnen, Andre J.

2015-01-01

Epigenetic control of gene expression is critical for normal fetal development. However, chromatin-related mechanisms that activate bone-specific programs during osteogenesis have remained underexplored. Therefore, we investigated the expression profiles of a large cohort of epigenetic regulators (>300) during osteogenic differentiation of human mesenchymal cells derived from the stromal vascular fraction of adipose tissue (AMSCs). Molecular analyses establish that the polycomb group protein EZH2 (enhancer of zeste homolog 2) is down-regulated during osteoblastic differentiation of AMSCs. Chemical inhibitor and siRNA knockdown studies show that EZH2, a histone methyltransferase that catalyzes trimethylation of histone 3 lysine 27 (H3K27me3), suppresses osteogenic differentiation. Blocking EZH2 activity promotes osteoblast differentiation and suppresses adipogenic differentiation of AMSCs. High throughput RNA sequence (mRNASeq) analysis reveals that EZH2 inhibition stimulates cell cycle inhibitory proteins and enhances the production of extracellular matrix proteins. Conditional genetic loss of Ezh2 in uncommitted mesenchymal cells (Prrx1-Cre) results in multiple defects in skeletal patterning and bone formation, including shortened forelimbs, craniosynostosis, and clinodactyly. Histological analysis and mRNASeq profiling suggest that these effects are attributable to growth plate abnormalities and premature cranial suture closure because of precocious maturation of osteoblasts. We conclude that the epigenetic activity of EZH2 is required for skeletal patterning and development, but EZH2 expression declines during terminal osteoblast differentiation and matrix production. PMID:26424790

Characterization of novel biomarkers in selecting for subtype specific medulloblastoma phenotypes.

PubMed

Liang, Lisa; Aiken, Christopher; McClelland, Robyn; Morrison, Ludivine Coudière; Tatari, Nazanin; Remke, Marc; Ramaswamy, Vijay; Issaivanan, Magimairajan; Ryken, Timothy; Del Bigio, Marc R; Taylor, Michael D; Werbowetski-Ogilvie, Tamra E

2015-11-17

Major research efforts have focused on defining cell surface marker profiles for characterization and selection of brain tumor stem/progenitor cells. Medulloblastoma is the most common primary malignant pediatric brain cancer and consists of 4 molecular subgroups: WNT, SHH, Group 3 and Group 4. Given the heterogeneity within and between medulloblastoma variants, surface marker profiles may be subtype-specific. Here, we employed a high throughput flow cytometry screen to identify differentially expressed cell surface markers in self-renewing vs. non-self-renewing SHH medulloblastoma cells. The top 25 markers were reduced to 4, CD271/p75NTR/NGFR, CD106/VCAM1, EGFR and CD171/NCAM-L1, by evaluating transcript levels in SHH tumors relative to samples representing the other variants. However, only CD271/p75NTR/NGFR and CD171/NCAM-L1 maintain differential expression between variants at the protein level. Functional characterization of CD271, a low affinity neurotrophin receptor, in cell lines and primary cultures suggested that CD271 selects for lower self-renewing progenitors or stem cells. Moreover, CD271 levels were negatively correlated with expression of SHH pathway genes. Our study reveals a novel role for CD271 in SHH medulloblastoma and suggests that targeting CD271 pathways could lead to the design of more selective therapies that lessen the broad impact of current treatments on developing nervous systems.

Selection of reference genes for quantitative real-time PCR normalization in Panax ginseng at different stages of growth and in different organs.

PubMed

Liu, Jing; Wang, Qun; Sun, Minying; Zhu, Linlin; Yang, Michael; Zhao, Yu

2014-01-01

Quantitative real-time reverse transcription PCR (qRT-PCR) has become a widely used method for gene expression analysis; however, its data interpretation largely depends on the stability of reference genes. The transcriptomics of Panax ginseng, one of the most popular and traditional ingredients used in Chinese medicines, is increasingly being studied. Furthermore, it is vital to establish a series of reliable reference genes when qRT-PCR is used to assess the gene expression profile of ginseng. In this study, we screened out candidate reference genes for ginseng using gene expression data generated by a high-throughput sequencing platform. Based on the statistical tests, 20 reference genes (10 traditional housekeeping genes and 10 novel genes) were selected. These genes were tested for the normalization of expression levels in five growth stages and three distinct plant organs of ginseng by qPCR. These genes were subsequently ranked and compared according to the stability of their expressions using geNorm, NormFinder, and BestKeeper computational programs. Although the best reference genes were found to vary across different samples, CYP and EF-1α were the most stable genes amongst all samples. GAPDH/30S RPS20, CYP/60S RPL13 and CYP/QCR were the optimum pair of reference genes in the roots, stems, and leaves. CYP/60S RPL13, CYP/eIF-5A, aTUB/V-ATP, eIF-5A/SAR1, and aTUB/pol IIa were the most stably expressed combinations in each of the five developmental stages. Our study serves as a foundation for developing an accurate method of qRT-PCR and will benefit future studies on gene expression profiles of Panax Ginseng.

Analyses of Brucella Pathogenesis, Host Immunity, and Vaccine Targets using Systems Biology and Bioinformatics

PubMed Central

He, Yongqun

2011-01-01

Brucella is a Gram-negative, facultative intracellular bacterium that causes zoonotic brucellosis in humans and various animals. Out of 10 classified Brucella species, B. melitensis, B. abortus, B. suis, and B. canis are pathogenic to humans. In the past decade, the mechanisms of Brucella pathogenesis and host immunity have been extensively investigated using the cutting edge systems biology and bioinformatics approaches. This article provides a comprehensive review of the applications of Omics (including genomics, transcriptomics, and proteomics) and bioinformatics technologies for the analysis of Brucella pathogenesis, host immune responses, and vaccine targets. Based on more than 30 sequenced Brucella genomes, comparative genomics is able to identify gene variations among Brucella strains that help to explain host specificity and virulence differences among Brucella species. Diverse transcriptomics and proteomics gene expression studies have been conducted to analyze gene expression profiles of wild type Brucella strains and mutants under different laboratory conditions. High throughput Omics analyses of host responses to infections with virulent or attenuated Brucella strains have been focused on responses by mouse and cattle macrophages, bovine trophoblastic cells, mouse and boar splenocytes, and ram buffy coat. Differential serum responses in humans and rams to Brucella infections have been analyzed using high throughput serum antibody screening technology. The Vaxign reverse vaccinology has been used to predict many Brucella vaccine targets. More than 180 Brucella virulence factors and their gene interaction networks have been identified using advanced literature mining methods. The recent development of community-based Vaccine Ontology and Brucellosis Ontology provides an efficient way for Brucella data integration, exchange, and computer-assisted automated reasoning. PMID:22919594

Analyses of Brucella pathogenesis, host immunity, and vaccine targets using systems biology and bioinformatics.

PubMed

He, Yongqun

2012-01-01

Brucella is a Gram-negative, facultative intracellular bacterium that causes zoonotic brucellosis in humans and various animals. Out of 10 classified Brucella species, B. melitensis, B. abortus, B. suis, and B. canis are pathogenic to humans. In the past decade, the mechanisms of Brucella pathogenesis and host immunity have been extensively investigated using the cutting edge systems biology and bioinformatics approaches. This article provides a comprehensive review of the applications of Omics (including genomics, transcriptomics, and proteomics) and bioinformatics technologies for the analysis of Brucella pathogenesis, host immune responses, and vaccine targets. Based on more than 30 sequenced Brucella genomes, comparative genomics is able to identify gene variations among Brucella strains that help to explain host specificity and virulence differences among Brucella species. Diverse transcriptomics and proteomics gene expression studies have been conducted to analyze gene expression profiles of wild type Brucella strains and mutants under different laboratory conditions. High throughput Omics analyses of host responses to infections with virulent or attenuated Brucella strains have been focused on responses by mouse and cattle macrophages, bovine trophoblastic cells, mouse and boar splenocytes, and ram buffy coat. Differential serum responses in humans and rams to Brucella infections have been analyzed using high throughput serum antibody screening technology. The Vaxign reverse vaccinology has been used to predict many Brucella vaccine targets. More than 180 Brucella virulence factors and their gene interaction networks have been identified using advanced literature mining methods. The recent development of community-based Vaccine Ontology and Brucellosis Ontology provides an efficient way for Brucella data integration, exchange, and computer-assisted automated reasoning.

Transcriptome profiling analysis of Mactra veneriformis by deep sequencing after exposure to 2,2',4,4'-tetrabromodiphenyl ether

NASA Astrophysics Data System (ADS)

Shi, Pengju; Dong, Shihang; Zhang, Huanjun; Wang, Peiliang; Niu, Zhuang; Fang, Yan

2018-03-01

Polybrominated diphenyl ethers (PBDEs) are ubiquitous global pollutants, which are known to have immune, development, reproduction, and endocrine toxicity in aquatic organisms, including bivalves. 2,2',4,4'-Tetrabromodiphenyl ether (BDE-47) is the predominant PBDE congener detected in environmental samples and the tissues of organisms. However, the mechanism of its toxicity remains unclear. In this study, high-throughput sequencing was performed using the clam Mactra veneriformis, a good model for toxicological research, to clarify the transcriptomic response to BDE-47 and the mechanism responsible for the toxicity of BDE-47. The clams were exposed to 5 μg/L BDE-47 for 3 days and the digestive glands were sampled for high-throughput sequencing analysis. We obtained 127 648, 154 225, and 124 985 unigenes by de novo assembly of the control group reads (CG), BDE-47 group reads (BDEG), and control and BDE-47 reads (CG & BDEG), respectively. We annotated 32 176 unigenes from the CG & BDEG reads using the NR database. We categorized 24 401 unigenes into 25 functional COG clusters and 21 749 unigenes were assigned to 259 KEGG pathways. Moreover, 17 625 differentially expressed genes (DEGs) were detected, with 10 028 upregulated DEGs and 7 597 downregulated DEGs. Functional enrichment analysis showed that the DEGs were involved with detoxification, antioxidant defense, immune response, apoptosis, and other functions. The mRNA expression levels of 26 DEGs were verified by quantitative real-time PCR, which demonstrated the high agreement between the two methods. These results provide a good basis for future research using the M. veneriformis model into the mechanism of PBDEs toxicity and molecular biomarkers for BDE-47 pollution. The regulation and interaction of the DEGs would be studied in the future for clarifying the mechanism of PBDEs toxicity.

Identification of functional modules using network topology and high-throughput data.

PubMed

Ulitsky, Igor; Shamir, Ron

2007-01-26

With the advent of systems biology, biological knowledge is often represented today by networks. These include regulatory and metabolic networks, protein-protein interaction networks, and many others. At the same time, high-throughput genomics and proteomics techniques generate very large data sets, which require sophisticated computational analysis. Usually, separate and different analysis methodologies are applied to each of the two data types. An integrated investigation of network and high-throughput information together can improve the quality of the analysis by accounting simultaneously for topological network properties alongside intrinsic features of the high-throughput data. We describe a novel algorithmic framework for this challenge. We first transform the high-throughput data into similarity values, (e.g., by computing pairwise similarity of gene expression patterns from microarray data). Then, given a network of genes or proteins and similarity values between some of them, we seek connected sub-networks (or modules) that manifest high similarity. We develop algorithms for this problem and evaluate their performance on the osmotic shock response network in S. cerevisiae and on the human cell cycle network. We demonstrate that focused, biologically meaningful and relevant functional modules are obtained. In comparison with extant algorithms, our approach has higher sensitivity and higher specificity. We have demonstrated that our method can accurately identify functional modules. Hence, it carries the promise to be highly useful in analysis of high throughput data.

Human Disease-Drug Network Based on Genomic Expression Profiles

PubMed Central

Hu, Guanghui; Agarwal, Pankaj

2009-01-01

Background Drug repositioning offers the possibility of faster development times and reduced risks in drug discovery. With the rapid development of high-throughput technologies and ever-increasing accumulation of whole genome-level datasets, an increasing number of diseases and drugs can be comprehensively characterized by the changes they induce in gene expression, protein, metabolites and phenotypes. Methodology/Principal Findings We performed a systematic, large-scale analysis of genomic expression profiles of human diseases and drugs to create a disease-drug network. A network of 170,027 significant interactions was extracted from the ∼24.5 million comparisons between ∼7,000 publicly available transcriptomic profiles. The network includes 645 disease-disease, 5,008 disease-drug, and 164,374 drug-drug relationships. At least 60% of the disease-disease pairs were in the same disease area as determined by the Medical Subject Headings (MeSH) disease classification tree. The remaining can drive a molecular level nosology by discovering relationships between seemingly unrelated diseases, such as a connection between bipolar disorder and hereditary spastic paraplegia, and a connection between actinic keratosis and cancer. Among the 5,008 disease-drug links, connections with negative scores suggest new indications for existing drugs, such as the use of some antimalaria drugs for Crohn's disease, and a variety of existing drugs for Huntington's disease; while the positive scoring connections can aid in drug side effect identification, such as tamoxifen's undesired carcinogenic property. From the ∼37K drug-drug relationships, we discover relationships that aid in target and pathway deconvolution, such as 1) KCNMA1 as a potential molecular target of lobeline, and 2) both apoptotic DNA fragmentation and G2/M DNA damage checkpoint regulation as potential pathway targets of daunorubicin. Conclusions/Significance We have automatically generated thousands of disease and drug expression profiles using GEO datasets, and constructed a large scale disease-drug network for effective and efficient drug repositioning as well as drug target/pathway identification. PMID:19657382

Ethoscopes: An open platform for high-throughput ethomics.

PubMed

Geissmann, Quentin; Garcia Rodriguez, Luis; Beckwith, Esteban J; French, Alice S; Jamasb, Arian R; Gilestro, Giorgio F

2017-10-01

Here, we present the use of ethoscopes, which are machines for high-throughput analysis of behavior in Drosophila and other animals. Ethoscopes provide a software and hardware solution that is reproducible and easily scalable. They perform, in real-time, tracking and profiling of behavior by using a supervised machine learning algorithm, are able to deliver behaviorally triggered stimuli to flies in a feedback-loop mode, and are highly customizable and open source. Ethoscopes can be built easily by using 3D printing technology and rely on Raspberry Pi microcomputers and Arduino boards to provide affordable and flexible hardware. All software and construction specifications are available at http://lab.gilest.ro/ethoscope.

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.

A high-throughput platform for population reformatting and mammalian expression of phage display libraries to enable functional screening as full-length IgG.

PubMed

Xiao, Xiaodong; Douthwaite, Julie A; Chen, Yan; Kemp, Ben; Kidd, Sara; Percival-Alwyn, Jennifer; Smith, Alison; Goode, Kate; Swerdlow, Bonnie; Lowe, David; Wu, Herren; Dall'Acqua, William F; Chowdhury, Partha S

Phage display antibody libraries are a rich resource for discovery of potential therapeutic antibodies. Single-chain variable fragment (scFv) libraries are the most common format due to the efficient display of scFv by phage particles and the ease by which soluble scFv antibodies can be expressed for high-throughput screening. Typically, a cascade of screening and triaging activities are performed, beginning with the assessment of large numbers of E. coli-expressed scFv, and progressing through additional assays with individual reformatting of the most promising scFv to full-length IgG. However, use of high-throughput screening of scFv for the discovery of full-length IgG is not ideal because of the differences between these molecules. Furthermore, the reformatting step represents a bottle neck in the process because each antibody has to be handled individually to preserve the unique VH and VL pairing. These problems could be resolved if populations of scFv could be reformatted to full-length IgG before screening without disrupting the variable region pairing. Here, we describe a novel strategy that allows the reformatting of diverse populations of scFv from phage selections to full-length IgG in a batch format. The reformatting process maintains the diversity and variable region pairing with high fidelity, and the resulted IgG pool enables high-throughput expression of IgG in mammalian cells and cell-based functional screening. The improved process led to the discovery of potent candidates that are comparable or better than those obtained by traditional methods. This strategy should also be readily applicable to Fab-based phage libraries. Our approach, Screening in Product Format (SiPF), represents a substantial improvement in the field of antibody discovery using phage display.

RIPiT-Seq: A high-throughput approach for footprinting RNA:protein complexes

PubMed Central

Singh, Guramrit; Ricci, Emiliano P.; Moore, Melissa J.

2013-01-01

Development of high-throughput approaches to map the RNA interaction sites of individual RNA binding proteins (RBPs) transcriptome-wide is rapidly transforming our understanding of post-transcriptional gene regulatory mechanisms. Here we describe a ribonucleoprotein (RNP) footprinting approach we recently developed for identifying occupancy sites of both individual RBPs and multi-subunit RNP complexes. RNA:protein immunoprecipitation in tandem (RIPiT) yields highly specific RNA footprints of cellular RNPs isolated via two sequential purifications; the resulting RNA footprints can then be identified by high-throughput sequencing (Seq). RIPiT-Seq is broadly applicable to all RBPs regardless of their RNA binding mode and thus provides a means to map the RNA binding sites of RBPs with poor inherent ultraviolet (UV) crosslinkability. Further, among current high-throughput approaches, RIPiT has the unique capacity to differentiate binding sites of RNPs with overlapping protein composition. It is therefore particularly suited for studying dynamic RNP assemblages whose composition evolves as gene expression proceeds. PMID:24096052

Design and construction of a first-generation high-throughput integrated robotic molecular biology platform for bioenergy applications.

PubMed

Hughes, Stephen R; Butt, Tauseef R; Bartolett, Scott; Riedmuller, Steven B; Farrelly, Philip

2011-08-01

The molecular biological techniques for plasmid-based assembly and cloning of gene open reading frames are essential for elucidating the function of the proteins encoded by the genes. High-throughput integrated robotic molecular biology platforms that have the capacity to rapidly clone and express heterologous gene open reading frames in bacteria and yeast and to screen large numbers of expressed proteins for optimized function are an important technology for improving microbial strains for biofuel production. The process involves the production of full-length complementary DNA libraries as a source of plasmid-based clones to express the desired proteins in active form for determination of their functions. Proteins that were identified by high-throughput screening as having desired characteristics are overexpressed in microbes to enable them to perform functions that will allow more cost-effective and sustainable production of biofuels. Because the plasmid libraries are composed of several thousand unique genes, automation of the process is essential. This review describes the design and implementation of an automated integrated programmable robotic workcell capable of producing complementary DNA libraries, colony picking, isolating plasmid DNA, transforming yeast and bacteria, expressing protein, and performing appropriate functional assays. These operations will allow tailoring microbial strains to use renewable feedstocks for production of biofuels, bioderived chemicals, fertilizers, and other coproducts for profitable and sustainable biorefineries. Published by Elsevier Inc.

Culture-independent discovery of natural products from soil metagenomes.

PubMed

Katz, Micah; Hover, Bradley M; Brady, Sean F

2016-03-01

Bacterial natural products have proven to be invaluable starting points in the development of many currently used therapeutic agents. Unfortunately, traditional culture-based methods for natural product discovery have been deemphasized by pharmaceutical companies due in large part to high rediscovery rates. Culture-independent, or "metagenomic," methods, which rely on the heterologous expression of DNA extracted directly from environmental samples (eDNA), have the potential to provide access to metabolites encoded by a large fraction of the earth's microbial biosynthetic diversity. As soil is both ubiquitous and rich in bacterial diversity, it is an appealing starting point for culture-independent natural product discovery efforts. This review provides an overview of the history of soil metagenome-driven natural product discovery studies and elaborates on the recent development of new tools for sequence-based, high-throughput profiling of environmental samples used in discovering novel natural product biosynthetic gene clusters. We conclude with several examples of these new tools being employed to facilitate the recovery of novel secondary metabolite encoding gene clusters from soil metagenomes and the subsequent heterologous expression of these clusters to produce bioactive small molecules.

A Systems Biology Approach to Link Nuclear Factor Kappa B Activation with Lethal Prostate Cancer

DTIC Science & Technology

2014-05-01

developed as a routine clinical assay. 12 Task 1B: Perform protein profiling of circulating blood proteins and determine whether a protein...or set of proteins indicative of NFκB activation are associated with lethal prostate cancer. Circulating proteins will be assessed in two cohorts of...throughput functional genomic data. Nucleic acids research 2009;37:D885-90. 3. Parkinson H, Kapushesky M, Kolesnikov N, et al. ArrayExpress update--from

Evaluating whole transcriptome amplification for gene profiling experiments using RNA-Seq.

PubMed

Faherty, Sheena L; Campbell, C Ryan; Larsen, Peter A; Yoder, Anne D

2015-07-30

RNA-Seq has enabled high-throughput gene expression profiling to provide insight into the functional link between genotype and phenotype. Low quantities of starting RNA can be a severe hindrance for studies that aim to utilize RNA-Seq. To mitigate this bottleneck, whole transcriptome amplification (WTA) technologies have been developed to generate sufficient sequencing targets from minute amounts of RNA. Successful WTA requires accurate replication of transcript abundance without the loss or distortion of specific mRNAs. Here, we test the efficacy of NuGEN's Ovation RNA-Seq V2 system, which uses linear isothermal amplification with a unique chimeric primer for amplification, using white adipose tissue from standard laboratory rats (Rattus norvegicus). Our goal was to investigate potential biological artifacts introduced through WTA approaches by establishing comparisons between matched raw and amplified RNA libraries derived from biological replicates. We found that 93% of expressed genes were identical between all unamplified versus matched amplified comparisons, also finding that gene density is similar across all comparisons. Our sequencing experiment and downstream bioinformatic analyses using the Tuxedo analysis pipeline resulted in the assembly of 25,543 high-quality transcripts. Libraries constructed from raw RNA and WTA samples averaged 15,298 and 15,253 expressed genes, respectively. Although significant differentially expressed genes (P < 0.05) were identified in all matched samples, each of these represents less than 0.15% of all shared genes for each comparison. Transcriptome amplification is efficient at maintaining relative transcript frequencies with no significant bias when using this NuGEN linear isothermal amplification kit under ideal laboratory conditions as presented in this study. This methodology has broad applications, from clinical and diagnostic, to field-based studies when sample acquisition, or sample preservation, methods prove challenging.

Gene identification for risk of relapse in stage I lung adenocarcinoma patients: a combined methodology of gene expression profiling and computational gene network analysis.

PubMed

Ludovini, Vienna; Bianconi, Fortunato; Siggillino, Annamaria; Piobbico, Danilo; Vannucci, Jacopo; Metro, Giulio; Chiari, Rita; Bellezza, Guido; Puma, Francesco; Della Fazia, Maria Agnese; Servillo, Giuseppe; Crinò, Lucio

2016-05-24

Risk assessment and treatment choice remains a challenge in early non-small-cell lung cancer (NSCLC). The aim of this study was to identify novel genes involved in the risk of early relapse (ER) compared to no relapse (NR) in resected lung adenocarcinoma (AD) patients using a combination of high throughput technology and computational analysis. We identified 18 patients (n.13 NR and n.5 ER) with stage I AD. Frozen samples of patients in ER, NR and corresponding normal lung (NL) were subjected to Microarray technology and quantitative-PCR (Q-PCR). A gene network computational analysis was performed to select predictive genes. An independent set of 79 ADs stage I samples was used to validate selected genes by Q-PCR.From microarray analysis we selected 50 genes, using the fold change ratio of ER versus NR. They were validated both in pool and individually in patient samples (ER and NR) by Q-PCR. Fourteen increased and 25 decreased genes showed a concordance between two methods. They were used to perform a computational gene network analysis that identified 4 increased (HOXA10, CLCA2, AKR1B10, FABP3) and 6 decreased (SCGB1A1, PGC, TFF1, PSCA, SPRR1B and PRSS1) genes. Moreover, in an independent dataset of ADs samples, we showed that both high FABP3 expression and low SCGB1A1 expression was associated with a worse disease-free survival (DFS).Our results indicate that it is possible to define, through gene expression and computational analysis, a characteristic gene profiling of patients with an increased risk of relapse that may become a tool for patient selection for adjuvant therapy.

Drug repositioning for orphan genetic diseases through Conserved Anticoexpressed Gene Clusters (CAGCs)

PubMed Central

2013-01-01

Background The development of new therapies for orphan genetic diseases represents an extremely important medical and social challenge. Drug repositioning, i.e. finding new indications for approved drugs, could be one of the most cost- and time-effective strategies to cope with this problem, at least in a subset of cases. Therefore, many computational approaches based on the analysis of high throughput gene expression data have so far been proposed to reposition available drugs. However, most of these methods require gene expression profiles directly relevant to the pathologic conditions under study, such as those obtained from patient cells and/or from suitable experimental models. In this work we have developed a new approach for drug repositioning, based on identifying known drug targets showing conserved anti-correlated expression profiles with human disease genes, which is completely independent from the availability of ‘ad hoc’ gene expression data-sets. Results By analyzing available data, we provide evidence that the genes displaying conserved anti-correlation with drug targets are antagonistically modulated in their expression by treatment with the relevant drugs. We then identified clusters of genes associated to similar phenotypes and showing conserved anticorrelation with drug targets. On this basis, we generated a list of potential candidate drug-disease associations. Importantly, we show that some of the proposed associations are already supported by independent experimental evidence. Conclusions Our results support the hypothesis that the identification of gene clusters showing conserved anticorrelation with drug targets can be an effective method for drug repositioning and provide a wide list of new potential drug-disease associations for experimental validation. PMID:24088245

Distinct endothelial phenotypes evoked by arterial waveforms derived from atherosclerosis-susceptible and -resistant regions of human vasculature

NASA Astrophysics Data System (ADS)

Dai, Guohao; Kaazempur-Mofrad, Mohammad R.; Natarajan, Sripriya; Zhang, Yuzhi; Vaughn, Saran; Blackman, Brett R.; Kamm, Roger D.; García-Cardeña, Guillermo; Gimbrone, Michael A., Jr.

2004-10-01

Atherosclerotic lesion localization to regions of disturbed flow within certain arterial geometries, in humans and experimental animals, suggests an important role for local hemodynamic forces in atherogenesis. To explore how endothelial cells (EC) acquire functional/dysfunctional phenotypes in response to vascular region-specific flow patterns, we have used an in vitro dynamic flow system to accurately reproduce arterial shear stress waveforms on cultured human EC and have examined the effects on EC gene expression by using a high-throughput transcriptional profiling approach. The flow patterns in the carotid artery bifurcations of several normal human subjects were characterized by using 3D flow analysis based on actual vascular geometries and blood flow profiles. Two prototypic arterial waveforms, "athero-prone" and "athero-protective," were defined as representative of the wall shear stresses in two distinct regions of the carotid artery (carotid sinus and distal internal carotid artery) that are typically "susceptible" or "resistant," respectively, to atherosclerotic lesion development. These two waveforms were applied to cultured EC, and cDNA microarrays were used to analyze the differential patterns of EC gene expression. In addition, the differential effects of athero-prone vs. athero-protective waveforms were further characterized on several parameters of EC structure and function, including actin cytoskeletal organization, expression and localization of junctional proteins, activation of the NF-B transcriptional pathway, and expression of proinflammatory cytokines and adhesion molecules. These global gene expression patterns and functional data reveal a distinct phenotypic modulation in response to the wall shear stresses present in atherosclerosis-susceptible vs. atherosclerosis-resistant human arterial geometries.

Rapid automation of a cell-based assay using a modular approach: case study of a flow-based Varicella Zoster Virus infectivity assay.

PubMed

Joelsson, Daniel; Gates, Irina V; Pacchione, Diana; Wang, Christopher J; Bennett, Philip S; Zhang, Yuhua; McMackin, Jennifer; Frey, Tina; Brodbeck, Kristin C; Baxter, Heather; Barmat, Scott L; Benetti, Luca; Bodmer, Jean-Luc

2010-06-01

Vaccine manufacturing requires constant analytical monitoring to ensure reliable quality and a consistent safety profile of the final product. Concentration and bioactivity of active components of the vaccine are key attributes routinely evaluated throughout the manufacturing cycle and for product release and dosage. In the case of live attenuated virus vaccines, bioactivity is traditionally measured in vitro by infection of susceptible cells with the vaccine followed by quantification of virus replication, cytopathology or expression of viral markers. These assays are typically multi-day procedures that require trained technicians and constant attention. Considering the need for high volumes of testing, automation and streamlining of these assays is highly desirable. In this study, the automation and streamlining of a complex infectivity assay for Varicella Zoster Virus (VZV) containing test articles is presented. The automation procedure was completed using existing liquid handling infrastructure in a modular fashion, limiting custom-designed elements to a minimum to facilitate transposition. In addition, cellular senescence data provided an optimal population doubling range for long term, reliable assay operation at high throughput. The results presented in this study demonstrate a successful automation paradigm resulting in an eightfold increase in throughput while maintaining assay performance characteristics comparable to the original assay. Copyright 2010 Elsevier B.V. All rights reserved.

Ionomic screening of field-grown soybeans identifies mutants with altered seed elemental composition

USDA-ARS?s Scientific Manuscript database

Soybean seeds contain high levels of mineral nutrients essential for human and animal nutrition. High throughput elemental profiling (ionomics) has identified mutants in model plant species grown in controlled environments. Here, we describe a method for identifying potential soybean ionomics mutant...

Virtual Embryo: Systems Modeling in Developmental Toxicity

EPA Science Inventory

High-throughput and high-content screening (HTS-HCS) studies are providing a rich source of data that can be applied to in vitro profiling of chemical compounds for biological activity and potential toxicity. EPA’s ToxCast™ project, and the broader Tox21 consortium, in addition t...

Expression profiling during arabidopsis/downy mildew interaction reveals a highly-expressed effector that attenuates responses to salicylic acid.

PubMed

Asai, Shuta; Rallapalli, Ghanasyam; Piquerez, Sophie J M; Caillaud, Marie-Cécile; Furzer, Oliver J; Ishaque, Naveed; Wirthmueller, Lennart; Fabro, Georgina; Shirasu, Ken; Jones, Jonathan D G

2014-10-01

Plants have evolved strong innate immunity mechanisms, but successful pathogens evade or suppress plant immunity via effectors delivered into the plant cell. Hyaloperonospora arabidopsidis (Hpa) causes downy mildew on Arabidopsis thaliana, and a genome sequence is available for isolate Emoy2. Here, we exploit the availability of genome sequences for Hpa and Arabidopsis to measure gene-expression changes in both Hpa and Arabidopsis simultaneously during infection. Using a high-throughput cDNA tag sequencing method, we reveal expression patterns of Hpa predicted effectors and Arabidopsis genes in compatible and incompatible interactions, and promoter elements associated with Hpa genes expressed during infection. By resequencing Hpa isolate Waco9, we found it evades Arabidopsis resistance gene RPP1 through deletion of the cognate recognized effector ATR1. Arabidopsis salicylic acid (SA)-responsive genes including PR1 were activated not only at early time points in the incompatible interaction but also at late time points in the compatible interaction. By histochemical analysis, we found that Hpa suppresses SA-inducible PR1 expression, specifically in the haustoriated cells into which host-translocated effectors are delivered, but not in non-haustoriated adjacent cells. Finally, we found a highly-expressed Hpa effector candidate that suppresses responsiveness to SA. As this approach can be easily applied to host-pathogen interactions for which both host and pathogen genome sequences are available, this work opens the door towards transcriptome studies in infection biology that should help unravel pathogen infection strategies and the mechanisms by which host defense responses are overcome.

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

USDA-ARS?s Scientific Manuscript database

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

Different Metabolic Pathways Are Involved in Response of Saccharomyces cerevisiae to L-A and M Viruses

PubMed Central

Lukša, Juliana; Ravoitytė, Bazilė; Konovalovas, Aleksandras; Aitmanaitė, Lina; Butenko, Anzhelika; Serva, Saulius; Servienė, Elena

2017-01-01

Competitive and naturally occurring yeast killer phenotype is governed by coinfection with dsRNA viruses. Long-term relationship between the host cell and viruses appear to be beneficial and co-adaptive; however, the impact of viral dsRNA on the host gene expression has barely been investigated. Here, we determined the transcriptomic profiles of the host Saccharomyces cerevisiae upon the loss of the M-2 dsRNA alone and the M-2 along with the L-A-lus dsRNAs. We provide a comprehensive study based on the high-throughput RNA-Seq data, Gene Ontology and the analysis of the interaction networks. We identified 486 genes differentially expressed after curing yeast cells of the M-2 dsRNA and 715 genes affected by the elimination of both M-2 and L-A-lus dsRNAs. We report that most of the transcriptional responses induced by viral dsRNAs are moderate. Differently expressed genes are related to ribosome biogenesis, mitochondrial functions, stress response, biosynthesis of lipids and amino acids. Our study also provided insight into the virus–host and virus–virus interplays. PMID:28757599

Different Metabolic Pathways Are Involved in Response of Saccharomyces cerevisiae to L-A and M Viruses.

PubMed

Lukša, Juliana; Ravoitytė, Bazilė; Konovalovas, Aleksandras; Aitmanaitė, Lina; Butenko, Anzhelika; Yurchenko, Vyacheslav; Serva, Saulius; Servienė, Elena

2017-07-25

Competitive and naturally occurring yeast killer phenotype is governed by coinfection with dsRNA viruses. Long-term relationship between the host cell and viruses appear to be beneficial and co-adaptive; however, the impact of viral dsRNA on the host gene expression has barely been investigated. Here, we determined the transcriptomic profiles of the host Saccharomyces cerevisiae upon the loss of the M-2 dsRNA alone and the M-2 along with the L-A-lus dsRNAs. We provide a comprehensive study based on the high-throughput RNA-Seq data, Gene Ontology and the analysis of the interaction networks. We identified 486 genes differentially expressed after curing yeast cells of the M-2 dsRNA and 715 genes affected by the elimination of both M-2 and L-A-lus dsRNAs. We report that most of the transcriptional responses induced by viral dsRNAs are moderate. Differently expressed genes are related to ribosome biogenesis, mitochondrial functions, stress response, biosynthesis of lipids and amino acids. Our study also provided insight into the virus-host and virus-virus interplays.

High-Throughput Quantitative Lipidomics Analysis of Nonesterified Fatty Acids in Human Plasma.

PubMed

Christinat, Nicolas; Morin-Rivron, Delphine; Masoodi, Mojgan

2016-07-01

We present a high-throughput, nontargeted lipidomics approach using liquid chromatography coupled to high-resolution mass spectrometry for quantitative analysis of nonesterified fatty acids. We applied this method to screen a wide range of fatty acids from medium-chain to very long-chain (8 to 24 carbon atoms) in human plasma samples. The method enables us to chromatographically separate branched-chain species from their straight-chain isomers as well as separate biologically important ω-3 and ω-6 polyunsaturated fatty acids. We used 51 fatty acid species to demonstrate the quantitative capability of this method with quantification limits in the nanomolar range; however, this method is not limited only to these fatty acid species. High-throughput sample preparation was developed and carried out on a robotic platform that allows extraction of 96 samples simultaneously within 3 h. This high-throughput platform was used to assess the influence of different types of human plasma collection and preparation on the nonesterified fatty acid profile of healthy donors. Use of the anticoagulants EDTA and heparin has been compared with simple clotting, and only limited changes have been detected in most nonesterified fatty acid concentrations.

Quantitative profiling of immune repertoires for minor lymphocyte counts using unique molecular identifiers.

PubMed

Egorov, Evgeny S; Merzlyak, Ekaterina M; Shelenkov, Andrew A; Britanova, Olga V; Sharonov, George V; Staroverov, Dmitriy B; Bolotin, Dmitriy A; Davydov, Alexey N; Barsova, Ekaterina; Lebedev, Yuriy B; Shugay, Mikhail; Chudakov, Dmitriy M

2015-06-15

Emerging high-throughput sequencing methods for the analyses of complex structure of TCR and BCR repertoires give a powerful impulse to adaptive immunity studies. However, there are still essential technical obstacles for performing a truly quantitative analysis. Specifically, it remains challenging to obtain comprehensive information on the clonal composition of small lymphocyte populations, such as Ag-specific, functional, or tissue-resident cell subsets isolated by sorting, microdissection, or fine needle aspirates. In this study, we report a robust approach based on unique molecular identifiers that allows profiling Ag receptors for several hundred to thousand lymphocytes while preserving qualitative and quantitative information on clonal composition of the sample. We also describe several general features regarding the data analysis with unique molecular identifiers that are critical for accurate counting of starting molecules in high-throughput sequencing applications. Copyright © 2015 by The American Association of Immunologists, Inc.

Illumina whole-genome complementary DNA-mediated annealing, selection, extension and ligation platform: assessing its performance in formalin-fixed, paraffin-embedded samples and identifying invasion pattern-related genes in oral squamous cell carcinoma.

PubMed

Loudig, Olivier; Brandwein-Gensler, Margaret; Kim, Ryung S; Lin, Juan; Isayeva, Tatyana; Liu, Christina; Segall, Jeffrey E; Kenny, Paraic A; Prystowsky, Michael B

2011-12-01

High-throughput gene expression profiling from formalin-fixed, paraffin-embedded tissues has become a reality, and several methods are now commercially available. The Illumina whole-genome complementary DNA-mediated annealing, selection, extension and ligation assay (Illumina, Inc) is a full-transcriptome version of the original 512-gene complementary DNA-mediated annealing, selection, extension and ligation assay, allowing high-throughput profiling of 24,526 annotated genes from degraded and formalin-fixed, paraffin-embedded RNA. This assay has the potential to allow identification of novel gene signatures associated with clinical outcome using banked archival pathology specimen resources. We tested the reproducibility of the whole-genome complementary DNA-mediated annealing, selection, extension and ligation assay and its sensitivity for detecting differentially expressed genes in RNA extracted from matched fresh and formalin-fixed, paraffin-embedded cells, after 1 and 13 months of storage, using the human breast cell lines MCF7 and MCF10A. Then, using tumor worst pattern of invasion as a classifier, 1 component of the "risk model," we selected 12 formalin-fixed, paraffin-embedded oral squamous cell carcinomas for whole-genome complementary DNA-mediated annealing, selection, extension and ligation assay analysis. We profiled 5 tumors with nonaggressive, nondispersed pattern of invasion, and 7 tumors with aggressive dispersed pattern of invasion and satellites scattered at least 1 mm apart. To minimize variability, the formalin-fixed, paraffin-embedded specimens were prepared from snap-frozen tissues, and RNA was obtained within 24 hours of fixation. One hundred four down-regulated genes and 72 up-regulated genes in tumors with aggressive dispersed pattern of invasion were identified. We performed quantitative reverse transcriptase polymerase chain reaction validation of 4 genes using Taqman assays and in situ protein detection of 1 gene by immunohistochemistry. Functional cluster analysis of genes up-regulated in tumors with aggressive pattern of invasion suggests presence of genes involved in cellular cytoarchitecture, some of which already associated with tumor invasion. Identification of these genes provides biologic rationale for our histologic classification, with regard to tumor invasion, and demonstrates that the whole-genome complementary DNA-mediated annealing, selection, extension and ligation assay is a powerful assay for profiling degraded RNA from archived specimens when combined with quantitative reverse transcriptase polymerase chain reaction validation. Copyright © 2011 Elsevier Inc. All rights reserved.

Transcriptomic profiling and quantitative high-throughput (qHTS) drug screening of CDH1 deficient hereditary diffuse gastric cancer (HDGC) cells identify treatment leads for familial gastric cancer.

PubMed

Chen, Ina; Mathews-Greiner, Lesley; Li, Dandan; Abisoye-Ogunniyan, Abisola; Ray, Satyajit; Bian, Yansong; Shukla, Vivek; Zhang, Xiaohu; Guha, Raj; Thomas, Craig; Gryder, Berkley; Zacharia, Athina; Beane, Joal D; Ravichandran, Sarangan; Ferrer, Marc; Rudloff, Udo

2017-05-01

Patients with hereditary diffuse gastric cancer (HDGC), a cancer predisposition syndrome associated with germline mutations of the CDH1 (E-cadherin) gene, have few effective treatment options. Despite marked differences in natural history, histopathology, and genetic profile to patients afflicted by sporadic gastric cancer, patients with HDGC receive, in large, identical systemic regimens. The lack of a robust preclinical in vitro system suitable for effective drug screening has been one of the obstacles to date which has hampered therapeutic advances in this rare disease. In order to identify therapeutic leads selective for the HDGC subtype of gastric cancer, we compared gene expression profiles and drug phenotype derived from an oncology library of 1912 compounds between gastric cancer cells established from a patient with metastatic HDGC harboring a c.1380delA CDH1 germline variant and sporadic gastric cancer cells. Unsupervised hierarchical cluster analysis shows select gene expression alterations in c.1380delA CDH1 SB.mhdgc-1 cells compared to a panel of sporadic gastric cancer cell lines with enrichment of ERK1-ERK2 (extracellular signal regulated kinase) and IP3 (inositol trisphosphate)/DAG (diacylglycerol) signaling as the top networks in c.1380delA SB.mhdgc-1 cells. Intracellular phosphatidylinositol intermediaries were increased upon direct measure in c.1380delA CDH1 SB.mhdgc-1 cells. Differential high-throughput drug screening of c.1380delA CDH1 SB.mhdgc-1 versus sporadic gastric cancer cells identified several compound classes with enriched activity in c.1380 CDH1 SB.mhdgc-1 cells including mTOR (Mammalian Target Of Rapamycin), MEK (Mitogen-Activated Protein Kinase), c-Src kinase, FAK (Focal Adhesion Kinase), PKC (Protein Kinase C), or TOPO2 (Topoisomerase II) inhibitors. Upon additional drug response testing, dual PI3K (Phosphatidylinositol 3-Kinase)/mTOR and topoisomerase 2A inhibitors displayed up to >100-fold increased activity in hereditary c.1380delA CDH1 gastric cancer cells inducing apoptosis most effectively in cells with deficient CDH1 function. Integrated pharmacological and transcriptomic profiling of hereditary diffuse gastric cancer cells with a loss-of-function c.1380delA CDH1 mutation implies various pharmacological vulnerabilities selective to CDH1-deficient familial gastric cancer cells and suggests novel treatment leads for future preclinical and clinical treatment studies of familial gastric cancer.

High-Throughput Protein Expression Using a Combination of Ligation-Independent Cloning (LIC) and Infrared Fluorescent Protein (IFP) Detection

PubMed Central

Dortay, Hakan; Akula, Usha Madhuri; Westphal, Christin; Sittig, Marie; Mueller-Roeber, Bernd

2011-01-01

Protein expression in heterologous hosts for functional studies is a cumbersome effort. Here, we report a superior platform for parallel protein expression in vivo and in vitro. The platform combines highly efficient ligation-independent cloning (LIC) with instantaneous detection of expressed proteins through N- or C-terminal fusions to infrared fluorescent protein (IFP). For each open reading frame, only two PCR fragments are generated (with three PCR primers) and inserted by LIC into ten expression vectors suitable for protein expression in microbial hosts, including Escherichia coli, Kluyveromyces lactis, Pichia pastoris, the protozoon Leishmania tarentolae, and an in vitro transcription/translation system. Accumulation of IFP-fusion proteins is detected by infrared imaging of living cells or crude protein extracts directly after SDS-PAGE without additional processing. We successfully employed the LIC-IFP platform for in vivo and in vitro expression of ten plant and fungal proteins, including transcription factors and enzymes. Using the IFP reporter, we additionally established facile methods for the visualisation of protein-protein interactions and the detection of DNA-transcription factor interactions in microtiter and gel-free format. We conclude that IFP represents an excellent reporter for high-throughput protein expression and analysis, which can be easily extended to numerous other expression hosts using the setup reported here. PMID:21541323

Characterization of Adelphocoris suturalis (Hemiptera: Miridae) Transcriptome from Different Developmental Stages

NASA Astrophysics Data System (ADS)

Tian, Caihong; Tek Tay, Wee; Feng, Hongqiang; Wang, Ying; Hu, Yongmin; Li, Guoping

2015-06-01

Adelphocoris suturalis is one of the most serious pest insects of Bt cotton in China, however its molecular genetics, biochemistry and physiology are poorly understood. We used high throughput sequencing platform to perform de novo transcriptome assembly and gene expression analyses across different developmental stages (eggs, 2nd and 5th instar nymphs, female and male adults). We obtained 20 GB of clean data and revealed 88,614 unigenes, including 23,830 clusters and 64,784 singletons. These unigene sequences were annotated and classified by Gene Ontology, Clusters of Orthologous Groups, and Kyoto Encyclopedia of Genes and Genomes databases. A large number of differentially expressed genes were discovered through pairwise comparisons between these developmental stages. Gene expression profiles were dramatically different between life stage transitions, with some of these most differentially expressed genes being associated with sex difference, metabolism and development. Quantitative real-time PCR results confirm deep-sequencing findings based on relative expression levels of nine randomly selected genes. Furthermore, over 791,390 single nucleotide polymorphisms and 2,682 potential simple sequence repeats were identified. Our study provided comprehensive transcriptional gene expression information for A. suturalis that will form the basis to better understanding of development pathways, hormone biosynthesis, sex differences and wing formation in mirid bugs.

Characterization of Adelphocoris suturalis (Hemiptera: Miridae) Transcriptome from Different Developmental Stages

PubMed Central

Tian, Caihong; Tek Tay, Wee; Feng, Hongqiang; Wang, Ying; Hu, Yongmin; Li, Guoping

2015-01-01

Adelphocoris suturalis is one of the most serious pest insects of Bt cotton in China, however its molecular genetics, biochemistry and physiology are poorly understood. We used high throughput sequencing platform to perform de novo transcriptome assembly and gene expression analyses across different developmental stages (eggs, 2nd and 5th instar nymphs, female and male adults). We obtained 20 GB of clean data and revealed 88,614 unigenes, including 23,830 clusters and 64,784 singletons. These unigene sequences were annotated and classified by Gene Ontology, Clusters of Orthologous Groups, and Kyoto Encyclopedia of Genes and Genomes databases. A large number of differentially expressed genes were discovered through pairwise comparisons between these developmental stages. Gene expression profiles were dramatically different between life stage transitions, with some of these most differentially expressed genes being associated with sex difference, metabolism and development. Quantitative real-time PCR results confirm deep-sequencing findings based on relative expression levels of nine randomly selected genes. Furthermore, over 791,390 single nucleotide polymorphisms and 2,682 potential simple sequence repeats were identified. Our study provided comprehensive transcriptional gene expression information for A. suturalis that will form the basis to better understanding of development pathways, hormone biosynthesis, sex differences and wing formation in mirid bugs. PMID:26047353

Data-driven high-throughput prediction of the 3-D structure of small molecules: review and progress. A response to the letter by the Cambridge Crystallographic Data Centre.

PubMed

Baldi, Pierre

2011-12-27

A response is presented to sentiments expressed in "Data-Driven High-Throughput Prediction of the 3-D Structure of Small Molecules: Review and Progress. A Response from The Cambridge Crystallographic Data Centre", recently published in the Journal of Chemical Information and Modeling, (1) which may give readers a misleading impression regarding significant impediments to scientific research posed by the CCDC.

Expression Profiling Smackdown: Human Transcriptome Array HTA 2.0 vs. RNA-Seq

PubMed Central

Palermo, Meghann; Driscoll, Heather; Tighe, Scott; Dragon, Julie; Bond, Jeff; Shukla, Arti; Vangala, Mahesh; Vincent, James; Hunter, Tim

2014-01-01

The advent of both microarray and massively parallel sequencing have revolutionized high-throughput analysis of the human transcriptome. Due to limitations in microarray technology, detecting and quantifying coding transcript isoforms, in addition to non-coding transcripts, has been challenging. As a result, RNA-Seq has been the preferred method for characterizing the full human transcriptome, until now. A new high-resolution array from Affymetrix, GeneChip Human Transcriptome Array 2.0 (HTA 2.0), has been designed to interrogate all transcript isoforms in the human transcriptome with >6 million probes targeting coding transcripts, exon-exon splice junctions, and non-coding transcripts. Here we compare expression results from GeneChip HTA 2.0 and RNA-Seq data using identical RNA extractions from three samples each of healthy human mesothelial cells in culture, LP9-C1, and healthy mesothelial cells treated with asbestos, LP9-A1. For GeneChip HTA 2.0 sample preparation, we chose to compare two target preparation methods, NuGEN Ovation Pico WTA V2 with the Encore Biotin Module versus Affymetrix's GeneChip WT PLUS with the WT Terminal Labeling Kit, on identical RNA extractions from both untreated and treated samples. These same RNA extractions were used for the RNA-Seq library preparation. All analyses were performed in Partek Genomics Suite 6.6. Expression profiles for control and asbestos-treated mesothelial cells prepared with NuGEN versus Affymetrix target preparation methods (GeneChip HTA 2.0) are compared to each other as well as to RNA-Seq results.

Finding Groups in Gene Expression Data

PubMed Central

2005-01-01

The vast potential of the genomic insight offered by microarray technologies has led to their widespread use since they were introduced a decade ago. Application areas include gene function discovery, disease diagnosis, and inferring regulatory networks. Microarray experiments enable large-scale, high-throughput investigations of gene activity and have thus provided the data analyst with a distinctive, high-dimensional field of study. Many questions in this field relate to finding subgroups of data profiles which are very similar. A popular type of exploratory tool for finding subgroups is cluster analysis, and many different flavors of algorithms have been used and indeed tailored for microarray data. Cluster analysis, however, implies a partitioning of the entire data set, and this does not always match the objective. Sometimes pattern discovery or bump hunting tools are more appropriate. This paper reviews these various tools for finding interesting subgroups. PMID:16046827

OSG-GEM: Gene Expression Matrix Construction Using the Open Science Grid.

PubMed

Poehlman, William L; Rynge, Mats; Branton, Chris; Balamurugan, D; Feltus, Frank A

2016-01-01

High-throughput DNA sequencing technology has revolutionized the study of gene expression while introducing significant computational challenges for biologists. These computational challenges include access to sufficient computer hardware and functional data processing workflows. Both these challenges are addressed with our scalable, open-source Pegasus workflow for processing high-throughput DNA sequence datasets into a gene expression matrix (GEM) using computational resources available to U.S.-based researchers on the Open Science Grid (OSG). We describe the usage of the workflow (OSG-GEM), discuss workflow design, inspect performance data, and assess accuracy in mapping paired-end sequencing reads to a reference genome. A target OSG-GEM user is proficient with the Linux command line and possesses basic bioinformatics experience. The user may run this workflow directly on the OSG or adapt it to novel computing environments.

OSG-GEM: Gene Expression Matrix Construction Using the Open Science Grid

PubMed Central

Poehlman, William L.; Rynge, Mats; Branton, Chris; Balamurugan, D.; Feltus, Frank A.

2016-01-01

High-throughput DNA sequencing technology has revolutionized the study of gene expression while introducing significant computational challenges for biologists. These computational challenges include access to sufficient computer hardware and functional data processing workflows. Both these challenges are addressed with our scalable, open-source Pegasus workflow for processing high-throughput DNA sequence datasets into a gene expression matrix (GEM) using computational resources available to U.S.-based researchers on the Open Science Grid (OSG). We describe the usage of the workflow (OSG-GEM), discuss workflow design, inspect performance data, and assess accuracy in mapping paired-end sequencing reads to a reference genome. A target OSG-GEM user is proficient with the Linux command line and possesses basic bioinformatics experience. The user may run this workflow directly on the OSG or adapt it to novel computing environments. PMID:27499617

In vitro data and in silico models for computational toxicology (Teratology Society ILSI HESI workshop)

EPA Science Inventory

The challenge of assessing the potential developmental health risks for the tens of thousands of environmental chemicals is beyond the capacity for resource-intensive animal protocols. Large data streams coming from high-throughput (HTS) and high-content (HCS) profiling of biolog...

HIGH-DIMENSIONAL PROFILING OF TRANSCRIPTION FACTOR ACTIVITY DIFFERENTIATES TOXCAST CHEMICAL GROUPS

EPA Science Inventory

The ToxCast™ project at the U.S. EPA uses a diverse battery of high throughput screening assays and informatics models to rapidly characterize the activity of chemicals. A central goal of the project is to provide empirical evidence to aid in the prioritization of chemicals for a...

Simultaneous Profiling of Lysoglycerophospholipids in Rice (Oryza sativa L.) Using Direct Infusion-Tandem Mass Spectrometry with Multiple Reaction Monitoring.

PubMed

Lim, Dong Kyu; Mo, Changyeun; Long, Nguyen Phuoc; Kim, Giyoung; Kwon, Sung Won

2017-03-29

White rice is the final product after the hull and bran layers have been removed during the milling process. Although lysoglycerophospholipids (lysoGPLs) only occupy a small proportion in white rice, they are essential for evaluating rice authenticity and quality. In this study, we developed a high-throughput and targeted lipidomics approach that involved direct infusion-tandem mass spectrometry with multiple reaction monitoring to simultaneously profile lysoGPLs in white rice. The method is capable of characterizing 17 lysoGPLs within 1 min. In addition, unsupervised and supervised analyses exhibited a considerably large diversity of lysoGPL concentrations in white rice from different origins. In particular, a classification model was built using identified lysoGPLs that can differentiate white rice from Korea, China, and Japan. Among the discriminatory lysoGPLs, for the lysoPE(16:0) and lysoPE(18:2) compositions, there were relatively small within-group variations, and they were considerably different among the three countries. In conclusion, our proposed method provides a rapid, high-throughput, and comprehensive format for profiling lysoGPLs in rice samples.

Cross-Platform Toxicogenomics for the Prediction of Non-Genotoxic Hepatocarcinogenesis in Rat

PubMed Central

Metzger, Ute; Templin, Markus F.; Plummer, Simon; Ellinger-Ziegelbauer, Heidrun; Zell, Andreas

2014-01-01

In the area of omics profiling in toxicology, i.e. toxicogenomics, characteristic molecular profiles have previously been incorporated into prediction models for early assessment of a carcinogenic potential and mechanism-based classification of compounds. Traditionally, the biomarker signatures used for model construction were derived from individual high-throughput techniques, such as microarrays designed for monitoring global mRNA expression. In this study, we built predictive models by integrating omics data across complementary microarray platforms and introduced new concepts for modeling of pathway alterations and molecular interactions between multiple biological layers. We trained and evaluated diverse machine learning-based models, differing in the incorporated features and learning algorithms on a cross-omics dataset encompassing mRNA, miRNA, and protein expression profiles obtained from rat liver samples treated with a heterogeneous set of substances. Most of these compounds could be unambiguously classified as genotoxic carcinogens, non-genotoxic carcinogens, or non-hepatocarcinogens based on evidence from published studies. Since mixed characteristics were reported for the compounds Cyproterone acetate, Thioacetamide, and Wy-14643, we reclassified these compounds as either genotoxic or non-genotoxic carcinogens based on their molecular profiles. Evaluating our toxicogenomics models in a repeated external cross-validation procedure, we demonstrated that the prediction accuracy of our models could be increased by joining the biomarker signatures across multiple biological layers and by adding complex features derived from cross-platform integration of the omics data. Furthermore, we found that adding these features resulted in a better separation of the compound classes and a more confident reclassification of the three undefined compounds as non-genotoxic carcinogens. PMID:24830643

Automated image alignment for 2D gel electrophoresis in a high-throughput proteomics pipeline.

PubMed

Dowsey, Andrew W; Dunn, Michael J; Yang, Guang-Zhong

2008-04-01

The quest for high-throughput proteomics has revealed a number of challenges in recent years. Whilst substantial improvements in automated protein separation with liquid chromatography and mass spectrometry (LC/MS), aka 'shotgun' proteomics, have been achieved, large-scale open initiatives such as the Human Proteome Organization (HUPO) Brain Proteome Project have shown that maximal proteome coverage is only possible when LC/MS is complemented by 2D gel electrophoresis (2-DE) studies. Moreover, both separation methods require automated alignment and differential analysis to relieve the bioinformatics bottleneck and so make high-throughput protein biomarker discovery a reality. The purpose of this article is to describe a fully automatic image alignment framework for the integration of 2-DE into a high-throughput differential expression proteomics pipeline. The proposed method is based on robust automated image normalization (RAIN) to circumvent the drawbacks of traditional approaches. These use symbolic representation at the very early stages of the analysis, which introduces persistent errors due to inaccuracies in modelling and alignment. In RAIN, a third-order volume-invariant B-spline model is incorporated into a multi-resolution schema to correct for geometric and expression inhomogeneity at multiple scales. The normalized images can then be compared directly in the image domain for quantitative differential analysis. Through evaluation against an existing state-of-the-art method on real and synthetically warped 2D gels, the proposed analysis framework demonstrates substantial improvements in matching accuracy and differential sensitivity. High-throughput analysis is established through an accelerated GPGPU (general purpose computation on graphics cards) implementation. Supplementary material, software and images used in the validation are available at http://www.proteomegrid.org/rain/.

Line-edge quality optimization of electron beam resist for high-throughput character projection exposure utilizing atomic force microscope analysis

NASA Astrophysics Data System (ADS)

Ikeno, Rimon; Mita, Yoshio; Asada, Kunihiro

2017-04-01

High-throughput electron-beam lithography (EBL) by character projection (CP) and variable-shaped beam (VSB) methods is a promising technique for low-to-medium volume device fabrication with regularly arranged layouts, such as standard-cell logics and memory arrays. However, non-VLSI applications like MEMS and MOEMS may not fully utilize the benefits of CP method due to their wide variety of layout figures including curved and oblique edges. In addition, the stepwise shapes that appear on such irregular edges by VSB exposure often result in intolerable edge roughness, which may degrade performances of the fabricated devices. In our former study, we proposed a general EBL methodology for such applications utilizing a combination of CP and VSB methods, and demonstrated its capabilities in electron beam (EB) shot reduction and edge-quality improvement by using a leading-edge EB exposure tool, ADVANTEST F7000S-VD02, and high-resolution Hydrogen Silsesquioxane resist. Both scanning electron microscope and atomic force microscope observations were used to analyze quality of the resist edge profiles to determine the influence of the control parameters used in the exposure-data preparation process. In this study, we carried out detailed analysis of the captured edge profiles utilizing Fourier analysis, and successfully distinguish the systematic undulation by the exposed CP character profiles from random roughness components. Such capability of precise edge-roughness analysis is useful to our EBL methodology to maintain both the line-edge quality and the exposure throughput by optimizing the control parameters in the layout data conversion.

Next-generation sequencing facilitates quantitative analysis of wild-type and Nrl−/− retinal transcriptomes

PubMed Central

Brooks, Matthew J.; Rajasimha, Harsha K.; Roger, Jerome E.

2011-01-01

Purpose Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived retinal transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis. Methods Retinal mRNA profiles of 21-day-old wild-type (WT) and neural retina leucine zipper knockout (Nrl−/−) mice were generated by deep sequencing, in triplicate, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays. Results Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9) and identified 16,014 transcripts in the retinas of WT and Nrl−/− mice with BWA workflow and 34,115 transcripts with TopHat workflow. RNA-seq data confirmed stable expression of 25 known housekeeping genes, and 12 of these were validated with qRT–PCR. RNA-seq data had a linear relationship with qRT–PCR for more than four orders of magnitude and a goodness of fit (R2) of 0.8798. Approximately 10% of the transcripts showed differential expression between the WT and Nrl−/− retina, with a fold change ≥1.5 and p value <0.05. Altered expression of 25 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered several as yet uncharacterized genes that may contribute to retinal function. Data analysis with BWA and TopHat workflows revealed a significant overlap yet provided complementary insights in transcriptome profiling. Conclusions Our study represents the first detailed analysis of retinal transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. PMID:22162623

Reprogramming cell fate with a genome-scale library of artificial transcription factors.

PubMed

Eguchi, Asuka; Wleklinski, Matthew J; Spurgat, Mackenzie C; Heiderscheit, Evan A; Kropornicka, Anna S; Vu, Catherine K; Bhimsaria, Devesh; Swanson, Scott A; Stewart, Ron; Ramanathan, Parameswaran; Kamp, Timothy J; Slukvin, Igor; Thomson, James A; Dutton, James R; Ansari, Aseem Z

2016-12-20

Artificial transcription factors (ATFs) are precision-tailored molecules designed to bind DNA and regulate transcription in a preprogrammed manner. Libraries of ATFs enable the high-throughput screening of gene networks that trigger cell fate decisions or phenotypic changes. We developed a genome-scale library of ATFs that display an engineered interaction domain (ID) to enable cooperative assembly and synergistic gene expression at targeted sites. We used this ATF library to screen for key regulators of the pluripotency network and discovered three combinations of ATFs capable of inducing pluripotency without exogenous expression of Oct4 (POU domain, class 5, TF 1). Cognate site identification, global transcriptional profiling, and identification of ATF binding sites reveal that the ATFs do not directly target Oct4; instead, they target distinct nodes that converge to stimulate the endogenous pluripotency network. This forward genetic approach enables cell type conversions without a priori knowledge of potential key regulators and reveals unanticipated gene network dynamics that drive cell fate choices.

High-Throughput Analysis of Age-Dependent Protein Changes in Layer II/III of the Human Orbitofrontal Cortex

NASA Astrophysics Data System (ADS)

Kapadia, Fenika

Studies on the orbitofrontal cortex (OFC) during normal aging have shown a decline in cognitive functions, a loss of spines/synapses in layer III and gene expression changes related to neural communication. Biological changes during the course of normal aging are summarized into 9 hallmarks based on aging in peripheral tissue. Whether these hallmarks apply to non-dividing brain tissue is not known. Therefore, we opted to perform large-scale proteomic profiling of the OFC layer II/III during normal aging from 15 young and 18 old male subjects. MaxQuant was utilized for label-free quantification and statistical analysis by the Random Intercept Model (RIM) identified 118 differentially expressed (DE) age-related proteins. Altered neural communication was the most represented hallmark of aging (54% of DE proteins), highlighting the importance of communication in the brain. Functional analysis showed enrichment in GABA/glutamate signaling and pro-inflammatory responses. The former may contribute to alterations in excitation/inhibition, leading to cognitive decline during aging.

Gene expression profiling of human breast tissue samples using SAGE-Seq.

PubMed

Wu, Zhenhua Jeremy; Meyer, Clifford A; Choudhury, Sibgat; Shipitsin, Michail; Maruyama, Reo; Bessarabova, Marina; Nikolskaya, Tatiana; Sukumar, Saraswati; Schwartzman, Armin; Liu, Jun S; Polyak, Kornelia; Liu, X Shirley

2010-12-01

We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around five million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less-abundant genes, including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease.

Regulatory Response to Carbon Starvation in Caulobacter crescentus

PubMed Central

Britos, Leticia; Abeliuk, Eduardo; Taverner, Thomas; Lipton, Mary; McAdams, Harley; Shapiro, Lucy

2011-01-01

Bacteria adapt to shifts from rapid to slow growth, and have developed strategies for long-term survival during prolonged starvation and stress conditions. We report the regulatory response of C. crescentus to carbon starvation, based on combined high-throughput proteome and transcriptome analyses. Our results identify cell cycle changes in gene expression in response to carbon starvation that involve the prominent role of the FixK FNR/CAP family transcription factor and the CtrA cell cycle regulator. Notably, the SigT ECF sigma factor mediates the carbon starvation-induced degradation of CtrA, while activating a core set of general starvation-stress genes that respond to carbon starvation, osmotic stress, and exposure to heavy metals. Comparison of the response of swarmer cells and stalked cells to carbon starvation revealed four groups of genes that exhibit different expression profiles. Also, cell pole morphogenesis and initiation of chromosome replication normally occurring at the swarmer-to-stalked cell transition are uncoupled in carbon-starved cells. PMID:21494595

Reprogramming cell fate with a genome-scale library of artificial transcription factors

PubMed Central

Eguchi, Asuka; Wleklinski, Matthew J.; Spurgat, Mackenzie C.; Heiderscheit, Evan A.; Kropornicka, Anna S.; Vu, Catherine K.; Bhimsaria, Devesh; Swanson, Scott A.; Stewart, Ron; Ramanathan, Parameswaran; Kamp, Timothy J.; Slukvin, Igor; Thomson, James A.; Dutton, James R.; Ansari, Aseem Z.

2016-01-01

Artificial transcription factors (ATFs) are precision-tailored molecules designed to bind DNA and regulate transcription in a preprogrammed manner. Libraries of ATFs enable the high-throughput screening of gene networks that trigger cell fate decisions or phenotypic changes. We developed a genome-scale library of ATFs that display an engineered interaction domain (ID) to enable cooperative assembly and synergistic gene expression at targeted sites. We used this ATF library to screen for key regulators of the pluripotency network and discovered three combinations of ATFs capable of inducing pluripotency without exogenous expression of Oct4 (POU domain, class 5, TF 1). Cognate site identification, global transcriptional profiling, and identification of ATF binding sites reveal that the ATFs do not directly target Oct4; instead, they target distinct nodes that converge to stimulate the endogenous pluripotency network. This forward genetic approach enables cell type conversions without a priori knowledge of potential key regulators and reveals unanticipated gene network dynamics that drive cell fate choices. PMID:27930301

Rapid high-throughput cloning and stable expression of antibodies in HEK293 cells.

PubMed

Spidel, Jared L; Vaessen, Benjamin; Chan, Yin Yin; Grasso, Luigi; Kline, J Bradford

2016-12-01

Single-cell based amplification of immunoglobulin variable regions is a rapid and powerful technique for cloning antigen-specific monoclonal antibodies (mAbs) for purposes ranging from general laboratory reagents to therapeutic drugs. From the initial screening process involving small quantities of hundreds or thousands of mAbs through in vitro characterization and subsequent in vivo experiments requiring large quantities of only a few, having a robust system for generating mAbs from cloning through stable cell line generation is essential. A protocol was developed to decrease the time, cost, and effort required by traditional cloning and expression methods by eliminating bottlenecks in these processes. Removing the clonal selection steps from the cloning process using a highly efficient ligation-independent protocol and from the stable cell line process by utilizing bicistronic plasmids to generate stable semi-clonal cell pools facilitated an increased throughput of the entire process from plasmid assembly through transient transfections and selection of stable semi-clonal cell pools. Furthermore, the time required by a single individual to clone, express, and select stable cell pools in a high-throughput format was reduced from 4 to 6months to only 4 to 6weeks. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Accounting Artifacts in High-Throughput Toxicity Assays.

PubMed

Hsieh, Jui-Hua

2016-01-01

Compound activity identification is the primary goal in high-throughput screening (HTS) assays. However, assay artifacts including both systematic (e.g., compound auto-fluorescence) and nonsystematic (e.g., noise) complicate activity interpretation. In addition, other than the traditional potency parameter, half-maximal effect concentration (EC50), additional activity parameters (e.g., point-of-departure, POD) could be derived from HTS data for activity profiling. A data analysis pipeline has been developed to handle the artifacts and to provide compound activity characterization with either binary or continuous metrics. This chapter outlines the steps in the pipeline using Tox21 glucocorticoid receptor (GR) β-lactamase assays, including the formats to identify either agonists or antagonists, as well as the counter-screen assays for identifying artifacts as examples. The steps can be applied to other lower-throughput assays with concentration-response data.

High-throughput sequencing of human plasma RNA by using thermostable group II intron reverse transcriptases

PubMed Central

Qin, Yidan; Yao, Jun; Wu, Douglas C.; Nottingham, Ryan M.; Mohr, Sabine; Hunicke-Smith, Scott; Lambowitz, Alan M.

2016-01-01

Next-generation RNA-sequencing (RNA-seq) has revolutionized transcriptome profiling, gene expression analysis, and RNA-based diagnostics. Here, we developed a new RNA-seq method that exploits thermostable group II intron reverse transcriptases (TGIRTs) and used it to profile human plasma RNAs. TGIRTs have higher thermostability, processivity, and fidelity than conventional reverse transcriptases, plus a novel template-switching activity that can efficiently attach RNA-seq adapters to target RNA sequences without RNA ligation. The new TGIRT-seq method enabled construction of RNA-seq libraries from <1 ng of plasma RNA in <5 h. TGIRT-seq of RNA in 1-mL plasma samples from a healthy individual revealed RNA fragments mapping to a diverse population of protein-coding gene and long ncRNAs, which are enriched in intron and antisense sequences, as well as nearly all known classes of small ncRNAs, some of which have never before been seen in plasma. Surprisingly, many of the small ncRNA species were present as full-length transcripts, suggesting that they are protected from plasma RNases in ribonucleoprotein (RNP) complexes and/or exosomes. This TGIRT-seq method is readily adaptable for profiling of whole-cell, exosomal, and miRNAs, and for related procedures, such as HITS-CLIP and ribosome profiling. PMID:26554030

Expression of proteins in Escherichia coli as fusions with maltose-binding protein to rescue non-expressed targets in a high-throughput protein-expression and purification pipeline

PubMed Central

Hewitt, Stephen N.; Choi, Ryan; Kelley, Angela; Crowther, Gregory J.; Napuli, Alberto J.; Van Voorhis, Wesley C.

2011-01-01

Despite recent advances, the expression of heterologous proteins in Escherichia coli for crystallization remains a nontrivial challenge. The present study investigates the efficacy of maltose-binding protein (MBP) fusion as a general strategy for rescuing the expression of target proteins. From a group of sequence-verified clones with undetectable levels of protein expression in an E. coli T7 expression system, 95 clones representing 16 phylogenetically diverse organisms were selected for recloning into a chimeric expression vector with an N-terminal histidine-tagged MBP. PCR-amplified inserts were annealed into an identical ligation-independent cloning region in an MBP-fusion vector and were analyzed for expression and solubility by high-throughput nickel-affinity binding. This approach yielded detectable expression of 72% of the clones; soluble expression was visible in 62%. However, the solubility of most proteins was marginal to poor upon cleavage of the MBP tag. This study offers large-scale evidence that MBP can improve the soluble expression of previously non-expressing proteins from a variety of eukaryotic and prokaryotic organisms. While the behavior of the cleaved proteins was disappointing, further refinements in MBP tagging may permit the more widespread use of MBP-fusion proteins in crystallographic studies. PMID:21904041

Novel Acoustic Loading of a Mass Spectrometer: Toward Next-Generation High-Throughput MS Screening.

PubMed

Sinclair, Ian; Stearns, Rick; Pringle, Steven; Wingfield, Jonathan; Datwani, Sammy; Hall, Eric; Ghislain, Luke; Majlof, Lars; Bachman, Martin

2016-02-01

High-throughput, direct measurement of substrate-to-product conversion by label-free detection, without the need for engineered substrates or secondary assays, could be considered the "holy grail" of drug discovery screening. Mass spectrometry (MS) has the potential to be part of this ultimate screening solution, but is constrained by the limitations of existing MS sample introduction modes that cannot meet the throughput requirements of high-throughput screening (HTS). Here we report data from a prototype system (Echo-MS) that uses acoustic droplet ejection (ADE) to transfer femtoliter-scale droplets in a rapid, precise, and accurate fashion directly into the MS. The acoustic source can load samples into the MS from a microtiter plate at a rate of up to three samples per second. The resulting MS signal displays a very sharp attack profile and ions are detected within 50 ms of activation of the acoustic transducer. Additionally, we show that the system is capable of generating multiply charged ion species from simple peptides and large proteins. The combination of high speed and low sample volume has significant potential within not only drug discovery, but also other areas of the industry. © 2015 Society for Laboratory Automation and Screening.

Method development in high-performance liquid chromatography for high-throughput profiling and metabonomic studies of biofluid samples.

PubMed

Pham-Tuan, Hai; Kaskavelis, Lefteris; Daykin, Clare A; Janssen, Hans-Gerd

2003-06-15

"Metabonomics" has in the past decade demonstrated enormous potential in furthering the understanding of, for example, disease processes, toxicological mechanisms, and biomarker discovery. The same principles can also provide a systematic and comprehensive approach to the study of food ingredient impact on consumer health. However, "metabonomic" methodology requires the development of rapid, advanced analytical tools to comprehensively profile biofluid metabolites within consumers. Until now, NMR spectroscopy has been used for this purpose almost exclusively. Chromatographic techniques and in particular HPLC, have not been exploited accordingly. The main drawbacks of chromatography are the long analysis time, instabilities in the sample fingerprint and the rigorous sample preparation required. This contribution addresses these problems in the quest to develop generic methods for high-throughput profiling using HPLC. After a careful optimization process, stable fingerprints of biofluid samples can be obtained using standard HPLC equipment. A method using a short monolithic column and a rapid gradient with a high flow-rate has been developed that allowed rapid and detailed profiling of larger numbers of urine samples. The method can be easily translated into a slow, shallow-gradient high-resolution method for identification of interesting peaks by LC-MS/NMR. A similar approach has been applied for cell culture media samples. Due to the much higher protein content of such samples non-porous polymer-based small particle columns yielded the best results. The study clearly shows that HPLC can be used in metabonomic fingerprinting studies.

Bridging the gap between high-throughput genetic and transcriptional data reveals cellular pathways responding to alpha-synuclein toxicity

PubMed Central

Yeger-Lotem, Esti; Riva, Laura; Su, Linhui Julie; Gitler, Aaron D.; Cashikar, Anil; King, Oliver D.; Auluck, Pavan K.; Geddie, Melissa L.; Valastyan, Julie S.; Karger, David R.; Lindquist, Susan; Fraenkel, Ernest

2009-01-01

Cells respond to stimuli by changes in various processes, including signaling pathways and gene expression. Efforts to identify components of these responses increasingly depend on mRNA profiling and genetic library screens, yet the functional roles of the genes identified by these assays often remain enigmatic. By comparing the results of these two assays across various cellular responses, we found that they are consistently distinct. Moreover, genetic screens tend to identify response regulators, while mRNA profiling frequently detects metabolic responses. We developed an integrative approach that bridges the gap between these data using known molecular interactions, thus highlighting major response pathways. We harnessed this approach to reveal cellular pathways related to alpha-synuclein, a small lipid-binding protein implicated in several neurodegenerative disorders including Parkinson disease. For this we screened an established yeast model for alpha-synuclein toxicity to identify genes that when overexpressed alter cellular survival. Application of our algorithm to these data and data from mRNA profiling provided functional explanations for many of these genes and revealed novel relations between alpha-synuclein toxicity and basic cellular pathways. PMID:19234470

Quality controls in cellular immunotherapies: rapid assessment of clinical grade dendritic cells by gene expression profiling.

PubMed

Castiello, Luciano; Sabatino, Marianna; Zhao, Yingdong; Tumaini, Barbara; Ren, Jiaqiang; Ping, Jin; Wang, Ena; Wood, Lauren V; Marincola, Francesco M; Puri, Raj K; Stroncek, David F

2013-02-01

Cell-based immunotherapies are among the most promising approaches for developing effective and targeted immune response. However, their clinical usefulness and the evaluation of their efficacy rely heavily on complex quality control assessment. Therefore, rapid systematic methods are urgently needed for the in-depth characterization of relevant factors affecting newly developed cell product consistency and the identification of reliable markers for quality control. Using dendritic cells (DCs) as a model, we present a strategy to comprehensively characterize manufactured cellular products in order to define factors affecting their variability, quality and function. After generating clinical grade human monocyte-derived mature DCs (mDCs), we tested by gene expression profiling the degrees of product consistency related to the manufacturing process and variability due to intra- and interdonor factors, and how each factor affects single gene variation. Then, by calculating for each gene an index of variation we selected candidate markers for identity testing, and defined a set of genes that may be useful comparability and potency markers. Subsequently, we confirmed the observed gene index of variation in a larger clinical data set. In conclusion, using high-throughput technology we developed a method for the characterization of cellular therapies and the discovery of novel candidate quality assurance markers.

A Perspective on the Future of High-Throughput RNAi Screening: Will CRISPR Cut Out the Competition or Can RNAi Help Guide the Way?

PubMed

Taylor, Jessica; Woodcock, Simon

2015-09-01

For more than a decade, RNA interference (RNAi) has brought about an entirely new approach to functional genomics screening. Enabling high-throughput loss-of-function (LOF) screens against the human genome, identifying new drug targets, and significantly advancing experimental biology, RNAi is a fast, flexible technology that is compatible with existing high-throughput systems and processes; however, the recent advent of clustered regularly interspaced palindromic repeats (CRISPR)-Cas, a powerful new precise genome-editing (PGE) technology, has opened up vast possibilities for functional genomics. CRISPR-Cas is novel in its simplicity: one piece of easily engineered guide RNA (gRNA) is used to target a gene sequence, and Cas9 expression is required in the cells. The targeted double-strand break introduced by the gRNA-Cas9 complex is highly effective at removing gene expression compared to RNAi. Together with the reduced cost and complexity of CRISPR-Cas, there is the realistic opportunity to use PGE to screen for phenotypic effects in a total gene knockout background. This review summarizes the exciting development of CRISPR-Cas as a high-throughput screening tool, comparing its future potential to that of well-established RNAi screening techniques, and highlighting future challenges and opportunities within these disciplines. We conclude that the two technologies actually complement rather than compete with each other, enabling greater understanding of the genome in relation to drug discovery. © 2015 Society for Laboratory Automation and Screening.

Highly specific gene silencing in a monocot species by artificial microRNAs derived from chimeric miRNA precursors

DOE PAGES

Carbonell, Alberto; Fahlgren, Noah; Mitchell, Skyler; ...

2015-05-20

Artificial microRNAs (amiRNAs) are used for selective gene silencing in plants. However, current methods to produce amiRNA constructs for silencing transcripts in monocot species are not suitable for simple, cost-effective and large-scale synthesis. Here, a series of expression vectors based on Oryza sativa MIR390 (OsMIR390) precursor was developed for high-throughput cloning and high expression of amiRNAs in monocots. Four different amiRNA sequences designed to target specifically endogenous genes and expressed from OsMIR390-based vectors were validated in transgenic Brachypodium distachyon plants. Surprisingly, amiRNAs accumulated to higher levels and were processed more accurately when expressed from chimeric OsMIR390-based precursors that include distalmore » stem-loop sequences from Arabidopsis thaliana MIR390a (AtMIR390a). In all cases, transgenic plants displayed the predicted phenotypes induced by target gene repression, and accumulated high levels of amiRNAs and low levels of the corresponding target transcripts. Genome-wide transcriptome profiling combined with 5-RLM-RACE analysis in transgenic plants confirmed that amiRNAs were highly specific. Finally, significance Statement A series of amiRNA vectors based on Oryza sativa MIR390 (OsMIR390) precursor were developed for simple, cost-effective and large-scale synthesis of amiRNA constructs to silence genes in monocots. Unexpectedly, amiRNAs produced from chimeric OsMIR390-based precursors including Arabidopsis thaliana MIR390a distal stem-loop sequences accumulated elevated levels of highly effective and specific amiRNAs in transgenic Brachypodium distachyon plants.« less

RNA-seq analysis of the gonadal transcriptome during Alligator mississippiensis temperature-dependent sex determination and differentiation.

PubMed

Yatsu, Ryohei; Miyagawa, Shinichi; Kohno, Satomi; Parrott, Benjamin B; Yamaguchi, Katsushi; Ogino, Yukiko; Miyakawa, Hitoshi; Lowers, Russell H; Shigenobu, Shuji; Guillette, Louis J; Iguchi, Taisen

2016-01-25

The American alligator (Alligator mississippiensis) displays temperature-dependent sex determination (TSD), in which incubation temperature during embryonic development determines the sexual fate of the individual. However, the molecular mechanisms governing this process remain a mystery, including the influence of initial environmental temperature on the comprehensive gonadal gene expression patterns occurring during TSD. Our characterization of transcriptomes during alligator TSD allowed us to identify novel candidate genes involved in TSD initiation. High-throughput RNA sequencing (RNA-seq) was performed on gonads collected from A. mississippiensis embryos incubated at both a male and a female producing temperature (33.5 °C and 30 °C, respectively) in a time series during sexual development. RNA-seq yielded 375.2 million paired-end reads, which were mapped and assembled, and used to characterize differential gene expression. Changes in the transcriptome occurring as a function of both development and sexual differentiation were extensively profiled. Forty-one differentially expressed genes were detected in response to incubation at male producing temperature, and included genes such as Wnt signaling factor WNT11, histone demethylase KDM6B, and transcription factor C/EBPA. Furthermore, comparative analysis of development- and sex-dependent differential gene expression revealed 230 candidate genes involved in alligator sex determination and differentiation, and early details of the suspected male-fate commitment were profiled. We also discovered sexually dimorphic expression of uncharacterized ncRNAs and other novel elements, such as unique expression patterns of HEMGN and ARX. Twenty-five of the differentially expressed genes identified in our analysis were putative transcriptional regulators, among which were MYBL2, MYCL, and HOXC10, in addition to conventional sex differentiation genes such as SOX9, and FOXL2. Inferred gene regulatory network was constructed, and the gene-gene and temperature-gene interactions were predicted. Gonadal global gene expression kinetics during sex determination has been extensively profiled for the first time in a TSD species. These findings provide insights into the genetic framework underlying TSD, and expand our current understanding of the developmental fate pathways during vertebrate sex determination.

Managing the genomic revolution in cancer diagnostics.

PubMed

Nguyen, Doreen; Gocke, Christopher D

2017-08-01

Molecular tumor profiling is now a routine part of patient care, revealing targetable genomic alterations and molecularly distinct tumor subtypes with therapeutic and prognostic implications. The widespread adoption of next-generation sequencing technologies has greatly facilitated clinical implementation of genomic data and opened the door for high-throughput multigene-targeted sequencing. Herein, we discuss the variability of cancer genetic profiling currently offered by clinical laboratories, the challenges of applying rapidly evolving medical knowledge to individual patients, and the need for more standardized population-based molecular profiling.

Genome-wide analysis of DNA methylation variations caused by chronic glucolipotoxicity in beta-cells.

PubMed

Hu, Y; Xu, X-H; He, K; Zhang, L-L; Wang, S-K; Pan, Y-Q; He, B-S; Feng, T-T; Mao, X-M

2014-02-01

There is a growing body of literature suggesting the role of interactions between genes and the environment in development of type 2 diabetes mellitus (T2DM). However, the interplay between environment and genetic in developing and progressing T2MD is not fully understood. To determine the effects of high-glucose-lipid on the status of DNA methylation in beta cells, and clarify the mechanism of glucolipotoxicity on beta-cell deterioration, the DNA methylation profile was detected in beta-cells cultured with high-glucose-lipid medium.We utilized a high throughput NimbleGen RN34 CpG Island & Promoter Microarray to investigate the DNA methylation profile in beta-cells cultured with high-glucose-lipid medium. To validate the results of microarray, the immunoprecipitation (MeDIP) PCR was used to test the methylation status of some selected genes. The mRNA and protein expression of insulin and Tcf7l2 in these cells were quantified by RT-PCR and western blot, respectively.We have identified a lot of loci which experienced aberrant DNA methylation in beta-cells cultured with high-glucose-lipid medium. The results of MeDIP PCR were consistency to the microarray. An opposite regulation in transcription and translation of Tcf7l2 gene was found. Furthermore, the insulin mRNA and protein expression in beta-cells also decreased after cultured with high-glucose-lipid medium compared with the control cells.We conclude that chronic glucolipotoxicity could induce aberrant DNA methylation of some genes and may affect these genes expression in beta-cells, which might contribute to beta-cell function failure in T2DM and be helpful to explain, at least partially, the mechanism of glucolipotoxicity on beta-cells deterioration. © J. A. Barth Verlag in Georg Thieme Verlag KG Stuttgart · New York.

Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators

PubMed Central

Bodenmiller, Bernd; Zunder, Eli R.; Finck, Rachel; Chen, Tiffany J.; Savig, Erica S.; Bruggner, Robert V.; Simonds, Erin F.; Bendall, Sean C.; Sachs, Karen; Krutzik, Peter O.; Nolan, Garry P.

2013-01-01

The ability to comprehensively explore the impact of bio-active molecules on human samples at the single-cell level can provide great insight for biomedical research. Mass cytometry enables quantitative single-cell analysis with deep dimensionality, but currently lacks high-throughput capability. Here we report a method termed mass-tag cellular barcoding (MCB) that increases mass cytometry throughput by sample multiplexing. 96-well format MCB was used to characterize human peripheral blood mononuclear cell (PBMC) signaling dynamics, cell-to-cell communication, the signaling variability between 8 donors, and to define the impact of 27 inhibitors on this system. For each compound, 14 phosphorylation sites were measured in 14 PBMC types, resulting in 18,816 quantified phosphorylation levels from each multiplexed sample. This high-dimensional systems-level inquiry allowed analysis across cell-type and signaling space, reclassified inhibitors, and revealed off-target effects. MCB enables high-content, high-throughput screening, with potential applications for drug discovery, pre-clinical testing, and mechanistic investigation of human disease. PMID:22902532

High throughput protein production screening

DOEpatents

Beernink, Peter T [Walnut Creek, CA; Coleman, Matthew A [Oakland, CA; Segelke, Brent W [San Ramon, CA

2009-09-08

Methods, compositions, and kits for the cell-free production and analysis of proteins are provided. The invention allows for the production of proteins from prokaryotic sequences or eukaryotic sequences, including human cDNAs using PCR and IVT methods and detecting the proteins through fluorescence or immunoblot techniques. This invention can be used to identify optimized PCR and WT conditions, codon usages and mutations. The methods are readily automated and can be used for high throughput analysis of protein expression levels, interactions, and functional states.

Identification and validation of vesicant therapeutic targets using a high, throughput siRNA screening approach

DTIC Science & Technology

2014-12-24

toxlet.2011.04.007 Rogers JV, Choi YW, Kiser RC et al (2004) Microarray analysis of gene expression in murine skin exposed to sulfur mustard. J Bio...Chemotactic factors released in culture by intact developing and healing skin lesions produced in rabbits by the irritant sulfur mustard. Inflam- mation 21(2...Project ID Number CBM.CUTOC.04.10. RC 00114. ABSTRACT See reprint. 15. SUBJECT TERMS sulfur mustard, cutaneous injury, siRNA, high-throughput screening

Ethoscopes: An open platform for high-throughput ethomics

PubMed Central

Geissmann, Quentin; Garcia Rodriguez, Luis; Beckwith, Esteban J.; French, Alice S.; Jamasb, Arian R.

2017-01-01

Here, we present the use of ethoscopes, which are machines for high-throughput analysis of behavior in Drosophila and other animals. Ethoscopes provide a software and hardware solution that is reproducible and easily scalable. They perform, in real-time, tracking and profiling of behavior by using a supervised machine learning algorithm, are able to deliver behaviorally triggered stimuli to flies in a feedback-loop mode, and are highly customizable and open source. Ethoscopes can be built easily by using 3D printing technology and rely on Raspberry Pi microcomputers and Arduino boards to provide affordable and flexible hardware. All software and construction specifications are available at http://lab.gilest.ro/ethoscope. PMID:29049280

Accurate detection for a wide range of mutation and editing sites of microRNAs from small RNA high-throughput sequencing profiles

PubMed Central

Zheng, Yun; Ji, Bo; Song, Renhua; Wang, Shengpeng; Li, Ting; Zhang, Xiaotuo; Chen, Kun; Li, Tianqing; Li, Jinyan

2016-01-01

Various types of mutation and editing (M/E) events in microRNAs (miRNAs) can change the stabilities of pre-miRNAs and/or complementarities between miRNAs and their targets. Small RNA (sRNA) high-throughput sequencing (HTS) profiles can contain many mutated and edited miRNAs. Systematic detection of miRNA mutation and editing sites from the huge volume of sRNA HTS profiles is computationally difficult, as high sensitivity and low false positive rate (FPR) are both required. We propose a novel method (named MiRME) for an accurate and fast detection of miRNA M/E sites using a progressive sequence alignment approach which refines sensitivity and improves FPR step-by-step. From 70 sRNA HTS profiles with over 1.3 billion reads, MiRME has detected thousands of statistically significant M/E sites, including 3′-editing sites, 57 A-to-I editing sites (of which 32 are novel), as well as some putative non-canonical editing sites. We demonstrated that a few non-canonical editing sites were not resulted from mutations in genome by integrating the analysis of genome HTS profiles of two human cell lines, suggesting the existence of new editing types to further diversify the functions of miRNAs. Compared with six existing studies or methods, MiRME has shown much superior performance for the identification and visualization of the M/E sites of miRNAs from the ever-increasing sRNA HTS profiles. PMID:27229138

High-Throughput Patch Clamp Screening in Human α6-Containing Nicotinic Acetylcholine Receptors

PubMed Central

Armstrong, Lucas C.; Kirsch, Glenn E.; Fedorov, Nikolai B.; Wu, Caiyun; Kuryshev, Yuri A.; Sewell, Abby L.; Liu, Zhiqi; Motter, Arianne L.; Leggett, Carmine S.; Orr, Michael S.

2017-01-01

Nicotine, the addictive component of tobacco products, is an agonist at nicotinic acetylcholine receptors (nAChRs) in the brain. The subtypes of nAChR are defined by their α- and β-subunit composition. The α6β2β3 nAChR subtype is expressed in terminals of dopaminergic neurons that project to the nucleus accumbens and striatum and modulate dopamine release in brain regions involved in nicotine addiction. Although subtype-dependent selectivity of nicotine is well documented, subtype-selective profiles of other tobacco product constituents are largely unknown and could be essential for understanding the addiction-related neurological effects of tobacco products. We describe the development and validation of a recombinant cell line expressing human α6/3β2β3V273S nAChR for screening and profiling assays in an automated patch clamp platform (IonWorks Barracuda). The cell line was pharmacologically characterized by subtype-selective and nonselective reference agonists, pore blockers, and competitive antagonists. Agonist and antagonist effects detected by the automated patch clamp approach were comparable to those obtained by conventional electrophysiological assays. A pilot screen of a library of Food and Drug Administration–approved drugs identified compounds, previously not known to modulate nAChRs, which selectively inhibited the α6/3β2β3V273S subtype. These assays provide new tools for screening and subtype-selective profiling of compounds that act at α6β2β3 nicotinic receptors. PMID:28298165

Virtual Embryo: Systems Modeling in Developmental Toxicity

EPA Science Inventory

High-throughput screening (HTS) studies are providing a rich source of data that can be applied to chemical profiling to address sensitivity and specificity of molecular targets, biological pathways, cellular and developmental processes. EPA’s ToxCast project is testing 960 uniq...

The transcriptional response of Escherichia coli to recombinant protein insolubility.

PubMed

Smith, Harold E

2007-03-01

Bacterial production of recombinant proteins offers several advantages over alternative expression methods and remains the system of choice for many structural genomics projects. However, a large percentage of targets accumulate as insoluble inclusion bodies rather than soluble protein, creating a significant bottleneck in the protein production pipeline. Numerous strategies have been reported that can improve in vivo protein solubility, but most do not scale easily for high-throughput expression screening. To understand better the host cell response to the accumulation of insoluble protein, we determined genome-wide changes in bacterial gene expression upon induction of either soluble or insoluble target proteins. By comparing transcriptional profiles for multiple examples from the soluble or insoluble class, we identified a pattern of gene expression that correlates strongly with protein solubility. Direct targets of the sigma32 heat shock sigma factor, which includes genes involved in protein folding and degradation, were highly expressed in response to induction of insoluble protein. This same group of genes was also upregulated by insoluble protein accumulation under a different growth regime, indicating that sigma32-mediated gene expression is a general response to protein insolubility. This knowledge provides a starting point for the rational design of growth parameters and host strains with improved protein solubility characteristics. Summary Problems with protein solubility are frequently encountered when recombinant proteins are expressed in E. coli. The bacterial host responds to this problem by increasing expression of the protein folding machinery via the heat shock sigma factor sigma32. Manipulation of the sigma32 regulon might provide a general mechanism for improving recombinant protein solubility.

Cell-type-specific profiling of protein-DNA interactions without cell isolation using targeted DamID with next-generation sequencing.

PubMed

Marshall, Owen J; Southall, Tony D; Cheetham, Seth W; Brand, Andrea H

2016-09-01

This protocol is an extension to: Nat. Protoc. 2, 1467-1478 (2007); doi:10.1038/nprot.2007.148; published online 7 June 2007The ability to profile transcription and chromatin binding in a cell-type-specific manner is a powerful aid to understanding cell-fate specification and cellular function in multicellular organisms. We recently developed targeted DamID (TaDa) to enable genome-wide, cell-type-specific profiling of DNA- and chromatin-binding proteins in vivo without cell isolation. As a protocol extension, this article describes substantial modifications to an existing protocol, and it offers additional applications. TaDa builds upon DamID, a technique for detecting genome-wide DNA-binding profiles of proteins, by coupling it with the GAL4 system in Drosophila to enable both temporal and spatial resolution. TaDa ensures that Dam-fusion proteins are expressed at very low levels, thus avoiding toxicity and potential artifacts from overexpression. The modifications to the core DamID technique presented here also increase the speed of sample processing and throughput, and adapt the method to next-generation sequencing technology. TaDa is robust, reproducible and highly sensitive. Compared with other methods for cell-type-specific profiling, the technique requires no cell-sorting, cross-linking or antisera, and binding profiles can be generated from as few as 10,000 total induced cells. By profiling the genome-wide binding of RNA polymerase II (Pol II), TaDa can also identify transcribed genes in a cell-type-specific manner. Here we describe a detailed protocol for carrying out TaDa experiments and preparing the material for next-generation sequencing. Although we developed TaDa in Drosophila, it should be easily adapted to other organisms with an inducible expression system. Once transgenic animals are obtained, the entire experimental procedure-from collecting tissue samples to generating sequencing libraries-can be accomplished within 5 d.

Identification and profiling of novel microRNAs in the Brassica rapa genome based on small RNA deep sequencing

PubMed Central

2012-01-01

Background MicroRNAs (miRNAs) are one of the functional non-coding small RNAs involved in the epigenetic control of the plant genome. Although plants contain both evolutionary conserved miRNAs and species-specific miRNAs within their genomes, computational methods often only identify evolutionary conserved miRNAs. The recent sequencing of the Brassica rapa genome enables us to identify miRNAs and their putative target genes. In this study, we sought to provide a more comprehensive prediction of B. rapa miRNAs based on high throughput small RNA deep sequencing. Results We sequenced small RNAs from five types of tissue: seedlings, roots, petioles, leaves, and flowers. By analyzing 2.75 million unique reads that mapped to the B. rapa genome, we identified 216 novel and 196 conserved miRNAs that were predicted to target approximately 20% of the genome’s protein coding genes. Quantitative analysis of miRNAs from the five types of tissue revealed that novel miRNAs were expressed in diverse tissues but their expression levels were lower than those of the conserved miRNAs. Comparative analysis of the miRNAs between the B. rapa and Arabidopsis thaliana genomes demonstrated that redundant copies of conserved miRNAs in the B. rapa genome may have been deleted after whole genome triplication. Novel miRNA members seemed to have spontaneously arisen from the B. rapa and A. thaliana genomes, suggesting the species-specific expansion of miRNAs. We have made this data publicly available in a miRNA database of B. rapa called BraMRs. The database allows the user to retrieve miRNA sequences, their expression profiles, and a description of their target genes from the five tissue types investigated here. Conclusions This is the first report to identify novel miRNAs from Brassica crops using genome-wide high throughput techniques. The combination of computational methods and small RNA deep sequencing provides robust predictions of miRNAs in the genome. The finding of numerous novel miRNAs, many with few target genes and low expression levels, suggests the rapid evolution of miRNA genes. The development of a miRNA database, BraMRs, enables us to integrate miRNA identification, target prediction, and functional annotation of target genes. BraMRs will represent a valuable public resource with which to study the epigenetic control of B. rapa and other closely related Brassica species. The database is available at the following link: http://bramrs.rna.kr [1]. PMID:23163954

High-throughput sequencing of forensic genetic samples using punches of FTA cards with buccal swabs.

PubMed

Kampmann, Marie-Louise; Buchard, Anders; Børsting, Claus; Morling, Niels

2016-01-01

Here, we demonstrate that punches from buccal swab samples preserved on FTA cards can be used for high-throughput DNA sequencing, also known as massively parallel sequencing (MPS). We typed 44 reference samples with the HID-Ion AmpliSeq Identity Panel using washed 1.2 mm punches from FTA cards with buccal swabs and compared the results with those obtained with DNA extracted using the EZ1 DNA Investigator Kit. Concordant profiles were obtained for all samples. Our protocol includes simple punch, wash, and PCR steps, reducing cost and hands-on time in the laboratory. Furthermore, it facilitates automation of DNA sequencing.

High throughput screening technologies for ion channels

PubMed Central

Yu, Hai-bo; Li, Min; Wang, Wei-ping; Wang, Xiao-liang

2016-01-01

Ion channels are involved in a variety of fundamental physiological processes, and their malfunction causes numerous human diseases. Therefore, ion channels represent a class of attractive drug targets and a class of important off-targets for in vitro pharmacological profiling. In the past decades, the rapid progress in developing functional assays and instrumentation has enabled high throughput screening (HTS) campaigns on an expanding list of channel types. Chronologically, HTS methods for ion channels include the ligand binding assay, flux-based assay, fluorescence-based assay, and automated electrophysiological assay. In this review we summarize the current HTS technologies for different ion channel classes and their applications. PMID:26657056

iGC-an integrated analysis package of gene expression and copy number alteration.

PubMed

Lai, Yi-Pin; Wang, Liang-Bo; Wang, Wei-An; Lai, Liang-Chuan; Tsai, Mong-Hsun; Lu, Tzu-Pin; Chuang, Eric Y

2017-01-14

With the advancement in high-throughput technologies, researchers can simultaneously investigate gene expression and copy number alteration (CNA) data from individual patients at a lower cost. Traditional analysis methods analyze each type of data individually and integrate their results using Venn diagrams. Challenges arise, however, when the results are irreproducible and inconsistent across multiple platforms. To address these issues, one possible approach is to concurrently analyze both gene expression profiling and CNAs in the same individual. We have developed an open-source R/Bioconductor package (iGC). Multiple input formats are supported and users can define their own criteria for identifying differentially expressed genes driven by CNAs. The analysis of two real microarray datasets demonstrated that the CNA-driven genes identified by the iGC package showed significantly higher Pearson correlation coefficients with their gene expression levels and copy numbers than those genes located in a genomic region with CNA. Compared with the Venn diagram approach, the iGC package showed better performance. The iGC package is effective and useful for identifying CNA-driven genes. By simultaneously considering both comparative genomic and transcriptomic data, it can provide better understanding of biological and medical questions. The iGC package's source code and manual are freely available at https://www.bioconductor.org/packages/release/bioc/html/iGC.html .

Distinct Strains of Toxoplasma gondii Feature Divergent Transcriptomes Regardless of Developmental Stage

DOE PAGES

Croken, Matthew; Ma, Yan Fen; Markillie, Lye Meng; ...

2014-11-13

Using high through-put RNA sequencing, we assayed the transcriptomes of three different strains of Toxoplasma gondii representing three common genotypes under both in vitro tachyzoite and in vitro bradyzoite-inducing alkaline stress culture conditions. Strikingly, the differences in transcriptional profiles between the strains, RH, PLK, and CTG, is much greater than differences between tachyzoites and alkaline stressed in vitro bradyzoites. With an FDR of 10%, we identify 241 genes differentially expressed between CTG tachyzoites and in vitro bradyzoites, including 5 putative AP2 transcription factors. We also observe close association between cell cycle regulated genes and differentiation. By Gene Set Enrichment Analysismore » (GSEA), there are a number of KEGG pathways associated with the in vitro bradyzoite transcriptomes of PLK and CTG, including pyrimidine metabolism and DNA replication. These functions are likely associated with cell-cycle arrest. When comparing mRNA levels between strains, we identify 1,526 genes that are differentially expressed regardless of culture-condition as well as 846 differentially expressed only in bradyzoites and 542 differentially expressed only in tachyzoites between at least two strains. Using GSEA, we identify ribosomal proteins as being expressed at significantly higher levels in the CTG strain than in either the RH or PLK strains. This association holds true regardless of life cycle stage.« less

Single cell RNA Seq reveals dynamic paracrine control of cellular variation

PubMed Central

Shalek, Alex K.; Satija, Rahul; Shuga, Joe; Trombetta, John J.; Gennert, Dave; Lu, Diana; Chen, Peilin; Gertner, Rona S.; Gaublomme, Jellert T.; Yosef, Nir; Schwartz, Schraga; Fowler, Brian; Weaver, Suzanne; Wang, Jing; Wang, Xiaohui; Ding, Ruihua; Raychowdhury, Raktima; Friedman, Nir; Hacohen, Nir; Park, Hongkun; May, Andrew P.; Regev, Aviv

2014-01-01

High-throughput single-cell transcriptomics offers an unbiased approach for understanding the extent, basis, and function of gene expression variation between seemingly identical cells. Here, we sequence single-cell RNA-Seq libraries prepared from over 1,700 primary mouse bone marrow derived dendritic cells (DCs) spanning several experimental conditions. We find substantial variation between identically stimulated DCs, in both the fraction of cells detectably expressing a given mRNA and the transcript’s level within expressing cells. Distinct gene modules are characterized by different temporal heterogeneity profiles. In particular, a “core” module of antiviral genes is expressed very early by a few “precocious” cells, but is later activated in all cells. By stimulating cells individually in sealed microfluidic chambers, analyzing DCs from knockout mice, and modulating secretion and extracellular signaling, we show that this response is coordinated via interferon-mediated paracrine signaling. Surprisingly, preventing cell-to-cell communication also substantially reduces variability in the expression of an early-induced “peaked” inflammatory module, suggesting that paracrine signaling additionally represses part of the inflammatory program. Our study highlights the importance of cell-to-cell communication in controlling cellular heterogeneity and reveals general strategies that multicellular populations use to establish complex dynamic responses. PMID:24919153

Miniaturization of High-Throughput Epigenetic Methyltransferase Assays with Acoustic Liquid Handling.

PubMed

Edwards, Bonnie; Lesnick, John; Wang, Jing; Tang, Nga; Peters, Carl

2016-02-01

Epigenetics continues to emerge as an important target class for drug discovery and cancer research. As programs scale to evaluate many new targets related to epigenetic expression, new tools and techniques are required to enable efficient and reproducible high-throughput epigenetic screening. Assay miniaturization increases screening throughput and reduces operating costs. Echo liquid handlers can transfer compounds, samples, reagents, and beads in submicroliter volumes to high-density assay formats using only acoustic energy-no contact or tips required. This eliminates tip costs and reduces the risk of reagent carryover. In this study, we demonstrate the miniaturization of a methyltransferase assay using Echo liquid handlers and two different assay technologies: AlphaLISA from PerkinElmer and EPIgeneous HTRF from Cisbio. © 2015 Society for Laboratory Automation and Screening.

Seasonal differences in the testicular transcriptome profile of free-living European beavers (Castor fiber L.) determined by the RNA-Seq method

PubMed Central

Paukszto, Łukasz; Jastrzębski, Jan P.; Czerwińska, Joanna; Chojnowska, Katarzyna; Kamińska, Barbara; Kurzyńska, Aleksandra; Smolińska, Nina; Giżejewski, Zygmunt; Kamiński, Tadeusz

2017-01-01

The European beaver (Castor fiber L.) is an important free-living rodent that inhabits Eurasian temperate forests. Beavers are often referred to as ecosystem engineers because they create or change existing habitats, enhance biodiversity and prepare the environment for diverse plant and animal species. Beavers are protected in most European Union countries, but their genomic background remains unknown. In this study, gene expression patterns in beaver testes and the variations in genetic expression in breeding and non-breeding seasons were determined by high-throughput transcriptome sequencing. Paired-end sequencing in the Illumina HiSeq 2000 sequencer produced a total of 373.06 million of high-quality reads. De novo assembly of contigs yielded 130,741 unigenes with an average length of 1,369.3 nt, N50 value of 1,734, and average GC content of 46.51%. A comprehensive analysis of the testicular transcriptome revealed more than 26,000 highly expressed unigenes which exhibited the highest homology with Rattus norvegicus and Ictidomys tridecemlineatus genomes. More than 8,000 highly expressed genes were found to be involved in fundamental biological processes, cellular components or molecular pathways. The study also revealed 42 genes whose regulation differed between breeding and non-breeding seasons. During the non-breeding period, the expression of 37 genes was up-regulated, and the expression of 5 genes was down-regulated relative to the breeding season. The identified genes encode molecules which are involved in signaling transduction, DNA repair, stress responses, inflammatory processes, metabolism and steroidogenesis. Our results pave the way for further research into season-dependent variations in beaver testes. PMID:28678806

A time-and-motion approach to micro-costing of high-throughput genomic assays

PubMed Central

Costa, S.; Regier, D.A.; Meissner, B.; Cromwell, I.; Ben-Neriah, S.; Chavez, E.; Hung, S.; Steidl, C.; Scott, D.W.; Marra, M.A.; Peacock, S.J.; Connors, J.M.

2016-01-01

Background Genomic technologies are increasingly used to guide clinical decision-making in cancer control. Economic evidence about the cost-effectiveness of genomic technologies is limited, in part because of a lack of published comprehensive cost estimates. In the present micro-costing study, we used a time-and-motion approach to derive cost estimates for 3 genomic assays and processes—digital gene expression profiling (gep), fluorescence in situ hybridization (fish), and targeted capture sequencing, including bioinformatics analysis—in the context of lymphoma patient management. Methods The setting for the study was the Department of Lymphoid Cancer Research laboratory at the BC Cancer Agency in Vancouver, British Columbia. Mean per-case hands-on time and resource measurements were determined from a series of direct observations of each assay. Per-case cost estimates were calculated using a bottom-up costing approach, with labour, capital and equipment, supplies and reagents, and overhead costs included. Results The most labour-intensive assay was found to be fish at 258.2 minutes per case, followed by targeted capture sequencing (124.1 minutes per case) and digital gep (14.9 minutes per case). Based on a historical case throughput of 180 cases annually, the mean per-case cost (2014 Canadian dollars) was estimated to be $1,029.16 for targeted capture sequencing and bioinformatics analysis, $596.60 for fish, and $898.35 for digital gep with an 807-gene code set. Conclusions With the growing emphasis on personalized approaches to cancer management, the need for economic evaluations of high-throughput genomic assays is increasing. Through economic modelling and budget-impact analyses, the cost estimates presented here can be used to inform priority-setting decisions about the implementation of such assays in clinical practice. PMID:27803594

High-throughput plasmid construction using homologous recombination in yeast: its mechanisms and application to protein production for X-ray crystallography.

PubMed

Mizutani, Kimihiko

2015-01-01

Homologous recombination is a system for repairing the broken genomes of living organisms by connecting two DNA strands at their homologous sequences. Today, homologous recombination in yeast is used for plasmid construction as a substitute for traditional methods using restriction enzymes and ligases. This method has various advantages over the traditional method, including flexibility in the position of DNA insertion and ease of manipulation. Recently, the author of this review reported the construction of plasmids by homologous recombination in the methanol-utilizing yeast Pichia pastoris, which is known to be an excellent expression host for secretory proteins and membrane proteins. The method enabled high-throughput construction of expression systems of proteins using P. pastoris; the constructed expression systems were used to investigate the expression conditions of membrane proteins and to perform X-ray crystallography of secretory proteins. This review discusses the mechanisms and applications of homologous recombination, including the production of proteins for X-ray crystallography.

IAOseq: inferring abundance of overlapping genes using RNA-seq data.

PubMed

Sun, Hong; Yang, Shuang; Tun, Liangliang; Li, Yixue

2015-01-01

Overlapping transcription constitutes a common mechanism for regulating gene expression. A major limitation of the overlapping transcription assays is the lack of high throughput expression data. We developed a new tool (IAOseq) that is based on reads distributions along the transcribed regions to identify the expression levels of overlapping genes from standard RNA-seq data. Compared with five commonly used quantification methods, IAOseq showed better performance in the estimation accuracy of overlapping transcription levels. For the same strand overlapping transcription, currently existing high-throughput methods are rarely available to distinguish which strand was present in the original mRNA template. The IAOseq results showed that the commonly used methods gave an average of 1.6 fold overestimation of the expression levels of same strand overlapping genes. This work provides a useful tool for mining overlapping transcription levels from standard RNA-seq libraries. IAOseq could be used to help us understand the complex regulatory mechanism mediated by overlapping transcripts. IAOseq is freely available at http://lifecenter.sgst.cn/main/en/IAO_seq.jsp.

The Gene Expression Omnibus Database.

PubMed

Clough, Emily; Barrett, Tanya

2016-01-01

The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome-protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/.

The Gene Expression Omnibus database

PubMed Central

Clough, Emily; Barrett, Tanya

2016-01-01

The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome–protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/. PMID:27008011

Genome-wide digital transcript analysis of putative fruitlet abscission related genes regulated by ethephon in litchi

PubMed Central

Li, Caiqin; Wang, Yan; Ying, Peiyuan; Ma, Wuqiang; Li, Jianguo

2015-01-01

The high level of physiological fruitlet abscission in litchi (Litchi chinensis Sonn.) causes severe yield loss. Cell separation occurs at the fruit abscission zone (FAZ) and can be triggered by ethylene. However, a deep knowledge of the molecular events occurring in the FAZ is still unknown. Here, genome-wide digital transcript abundance (DTA) analysis of putative fruit abscission related genes regulated by ethephon in litchi were studied. More than 81 million high quality reads from seven ethephon treated and untreated control libraries were obtained by high-throughput sequencing. Through DTA profile analysis in combination with Gene Ontology and KEGG pathway enrichment analyses, a total of 2730 statistically significant candidate genes were involved in the ethephon-promoted litchi fruitlet abscission. Of these, there were 1867 early-responsive genes whose expressions were up- or down-regulated from 0 to 1 d after treatment. The most affected genes included those related to ethylene biosynthesis and signaling, auxin transport and signaling, transcription factors (TFs), protein ubiquitination, ROS response, calcium signal transduction, and cell wall modification. These genes could be clustered into four groups and 13 subgroups according to their similar expression patterns. qRT-PCR displayed the expression pattern of 41 selected candidate genes, which proved the accuracy of our DTA data. Ethephon treatment significantly increased fruit abscission and ethylene production of fruitlet. The possible molecular events to control the ethephon-promoted litchi fruitlet abscission were prompted out. The increased ethylene evolution in fruitlet would suppress the synthesis and polar transport of auxin and trigger abscission signaling. To the best of our knowledge, it is the first time to monitor the gene expression profile occurring in the FAZ-enriched pedicel during litchi fruit abscission induced by ethephon on the genome-wide level. This study will contribute to a better understanding for the molecular regulatory mechanism of fruit abscission in litchi. PMID:26217356

Derivation and evaluation of putative adverse outcome ...

EPA Pesticide Factsheets

Cyclooxygenase (COX) inhibition is of concern in fish because COX inhibitors (e.g., ibuprofen) are ubiquitous in aquatic systems/fish tissues, and can disrupt synthesis of prostaglandins that modulate a variety of essential biological functions including reproduction. High content (transcriptomic) empirical data and publicly available high throughput toxicity data (actor.epa.gov) were utilized to develop putative adverse outcome pathways (AOPs) for molecular initiating event (MIE) of COX inhibition. Effects of a waterborne, 96h exposure to indomethacin (IN; 100 µg/L), ibuprofen (IB; 200 µg/L) and celecoxib (CX; 20 µg/L) on liver metabolome and ovarian gene expression (using oligonucleotide microarrays) in sexually mature fathead minnows (n=8) were examined. Metabolomic profiles of IN, IB and CX were not significantly different from control or one another. Exposure to IB and CX resulted in differential expression of comparable numbers of genes (IB = 433, CX= 545). In contrast, 2558 genes were differentially expressed in IN-treated fish. Functional analyses (canonical pathway and gene set enrichment) indicated extensive effects of IN on prostaglandin synthesis pathway, oocyte meiosis and several other processes consistent with physiological roles of prostaglandins. Transcriptomic data was congruent with apical endpoint data - IN reduced plasma prostaglandin F2 alpha concentrations, and ovarian COX activity, whereas IB and CX did not. Putative AOPs pathways for

A gene expression signature associated with survival in metastatic melanoma

PubMed Central

Mandruzzato, Susanna; Callegaro, Andrea; Turcatel, Gianluca; Francescato, Samuela; Montesco, Maria C; Chiarion-Sileni, Vanna; Mocellin, Simone; Rossi, Carlo R; Bicciato, Silvio; Wang, Ena; Marincola, Francesco M; Zanovello, Paola

2006-01-01

Background Current clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival. Methods Forty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were analyzed using significance analysis of microarrays (SAM) to identify genes associated with patient survival, and supervised principal components (SPC) to determine survival prediction. Results SAM analysis revealed a set of 80 probes, corresponding to 70 genes, associated with survival, i.e. 45 probes characterizing longer and 35 shorter survival times, respectively. These transcripts were included in a survival prediction model designed using SPC and cross-validation which allowed identifying 30 predicting probes out of the 80 associated with survival. Conclusion The longer-survival group of genes included those expressed in immune cells, both innate and acquired, confirming the interplay between immunological mechanisms and the natural history of melanoma. Genes linked to immune cells were totally lacking in the poor-survival group, which was instead associated with a number of genes related to highly proliferative and invasive tumor cells. PMID:17129373

Increasing transcriptome response of serpins during the ontogenetic stages in the salmon louse Caligus rogercresseyi (Copepoda: Caligidae).

PubMed

Maldonado-Aguayo, W; Gallardo-Escárate, C

2014-06-01

Serine protease inhibitors, or serpins, target serine proteases, and are important regulators of intra- and extracellular proteolysis. For parasite survival, parasite-derived protease inhibitors have been suggested to play essential roles in evading the host's immune system and protecting against exogenous host proteases. The aim of this work was to identify serpins via high throughput transcriptome sequencing and elucidate their potential functions during the lifecycle of the salmon louse Caligus rogercresseyi. Eleven putative, partial serpin sequences in the C. rogercresseyi transcriptome were identified and denoted as Cr-serpins 1 to 11. Comparative analysis of the deduced serpin-like amino acid sequences revealed a highly conserved reactive center loop region. Interestingly, P1 residues suggest putative functions involved with the trypsin/subtilisin, elastase, or subtilisin inhibitors, which evidenced increasing gene expression profiles from the copepodid to adult stage in C. rogercresseyi. Concerning this, Cr-serpin 10 was mainly expressed in the copepodid stage, while Cr-serpins 3, 4, 5, and 11 were mostly expressed in chalimus and adult stages. These results suggest that serpins could be involved in evading the immune response of the host fish. The identification of these serpins furthers the understanding of the immune system in this important ectoparasite species. Copyright © 2014 Elsevier B.V. All rights reserved.

High throughput transcriptome analysis of coffee reveals prehaustorial resistance in response to Hemileia vastatrix infection.

PubMed

Florez, Juan Carlos; Mofatto, Luciana Souto; do Livramento Freitas-Lopes, Rejane; Ferreira, Sávio Siqueira; Zambolim, Eunize Maciel; Carazzolle, Marcelo Falsarella; Zambolim, Laércio; Caixeta, Eveline Teixeira

2017-12-01

We provide a transcriptional profile of coffee rust interaction and identified putative up regulated resistant genes Coffee rust disease, caused by the fungus Hemileia vastatrix, is one of the major diseases in coffee throughout the world. The use of resistant cultivars is considered to be the most effective control strategy for this disease. To identify candidate genes related to different mechanism defense in coffee, we present a time-course comparative gene expression profile of Caturra (susceptible) and Híbrido de Timor (HdT, resistant) in response to H. vastatrix race XXXIII infection. The main objectives were to obtain a global overview of transcriptome in both interaction, compatible and incompatible, and, specially, analyze up-regulated HdT specific genes with inducible resistant and defense signaling pathways. Using both Coffea canephora as a reference genome and de novo assembly, we obtained 43,159 transcripts. At early infection events (12 and 24 h after infection), HdT responded to the attack of H. vastatrix with a larger number of up-regulated genes than Caturra, which was related to prehaustorial resistance. The genes found in HdT at early hours were involved in receptor-like kinases, response ion fluxes, production of reactive oxygen species, protein phosphorylation, ethylene biosynthesis and callose deposition. We selected 13 up-regulated HdT-exclusive genes to validate by real-time qPCR, which most of them confirmed their higher expression in HdT than in Caturra at early stage of infection. These genes have the potential to assist the development of new coffee rust control strategies. Collectively, our results provide understanding of expression profiles in coffee-H. vastatrix interaction over a time course in susceptible and resistant coffee plants.

Liquid chromatography mass spectrometry-based profiling of phosphatidylcholine and phosphatidylethanolamine in the plasma and liver of acetaminophen-induced liver injured mice.

PubMed

Ming, Ya-Nan; Zhang, Jing-Yi; Wang, Xiao-Lin; Li, Chun-Min; Ma, Si-Cong; Wang, Zheng-Yang; Liu, Xiao-Lin; Li, Xiao-Bo; Mao, Yi-Min

2017-08-14

Acetaminophen (APAP) overdose is one of the most common causes of acute liver failure in many countries. The aim of the study was to describe the profiling of phosphatidylcholine (PC) and phosphatidylethanolamine (PE) in the plasma and liver of Acetaminophen -induced liver injured mice. A time course study was carried out using C57BL/6 mice after intraperitoneal administration of 300 mg/kg Acetaminophen 1 h, 3 h, 6 h, 12 h and 24 h. A high-throughput liquid chromatography mass spectrometry (LC-MS) lipidomic method was utilized to detect phosphatidylcholine and phosphatidylethanolamine species in the plasma and liver. The expressions of phosphatidylcholine and phosphatidylethanolamine metabolism related genes in liver were detected by quantitative Reverse transcription polymerase chain reaction (qRT-PCR) and Western-blot. Following Acetaminophen treatment, the content of many PC and PE species in plasma increased from 1 h time point, peaked at 3 h or 6 h, and tended to return to baseline at 24 h time point. The relative contents of almost all PC species in liver decreased from 1 h, appeared to be lowest at 6 h, and then return to normality at 24 h, which might be partly explained by the suppression of phospholipases mRNA expressions and the induction of choline kinase (Chka) expression. Inconsistent with PC profile, the relative contents of many PE species in liver increased upon Acetaminophen treatment, which might be caused by the down-regulation of phosphatidylethanolamine N-methyltransferase (Pemt). Acetaminophen overdose induced dramatic change of many PC and PE species in plasma and liver, which might be caused by damaging hepatocytes and interfering the phospholipid metabolism in Acetaminophen -injured liver.

A High-Throughput Data Mining of Single Nucleotide Polymorphisms in Coffea Species Expressed Sequence Tags Suggests Differential Homeologous Gene Expression in the Allotetraploid Coffea arabica1[W

PubMed Central

Vidal, Ramon Oliveira; Mondego, Jorge Maurício Costa; Pot, David; Ambrósio, Alinne Batista; Andrade, Alan Carvalho; Pereira, Luiz Filipe Protasio; Colombo, Carlos Augusto; Vieira, Luiz Gonzaga Esteves; Carazzolle, Marcelo Falsarella; Pereira, Gonçalo Amarante Guimarães

2010-01-01

Polyploidization constitutes a common mode of evolution in flowering plants. This event provides the raw material for the divergence of function in homeologous genes, leading to phenotypic novelty that can contribute to the success of polyploids in nature or their selection for use in agriculture. Mounting evidence underlined the existence of homeologous expression biases in polyploid genomes; however, strategies to analyze such transcriptome regulation remained scarce. Important factors regarding homeologous expression biases remain to be explored, such as whether this phenomenon influences specific genes, how paralogs are affected by genome doubling, and what is the importance of the variability of homeologous expression bias to genotype differences. This study reports the expressed sequence tag assembly of the allopolyploid Coffea arabica and one of its direct ancestors, Coffea canephora. The assembly was used for the discovery of single nucleotide polymorphisms through the identification of high-quality discrepancies in overlapped expressed sequence tags and for gene expression information indirectly estimated by the transcript redundancy. Sequence diversity profiles were evaluated within C. arabica (Ca) and C. canephora (Cc) and used to deduce the transcript contribution of the Coffea eugenioides (Ce) ancestor. The assignment of the C. arabica haplotypes to the C. canephora (CaCc) or C. eugenioides (CaCe) ancestral genomes allowed us to analyze gene expression contributions of each subgenome in C. arabica. In silico data were validated by the quantitative polymerase chain reaction and allele-specific combination TaqMAMA-based method. The presence of differential expression of C. arabica homeologous genes and its implications in coffee gene expression, ontology, and physiology are discussed. PMID:20864545

The gene expression profile of resistant and susceptible Bombyx mori strains reveals cypovirus-associated variations in host gene transcript levels.

PubMed

Guo, Rui; Wang, Simei; Xue, Renyu; Cao, Guangli; Hu, Xiaolong; Huang, Moli; Zhang, Yangqi; Lu, Yahong; Zhu, Liyuan; Chen, Fei; Liang, Zi; Kuang, Sulan; Gong, Chengliang

2015-06-01

High-throughput paired-end RNA sequencing (RNA-Seq) was performed to investigate the gene expression profile of a susceptible Bombyx mori strain, Lan5, and a resistant B. mori strain, Ou17, which were both orally infected with B. mori cypovirus (BmCPV) in the midgut. There were 330 and 218 up-regulated genes, while there were 147 and 260 down-regulated genes in the Lan5 and Ou17 strains, respectively. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment for differentially expressed genes (DEGs) were carried out. Moreover, gene interaction network (STRING) analyses were performed to analyze the relationships among the shared DEGs. Some of these genes were related and formed a large network, in which the genes for B. mori cuticular protein RR-2 motif 123 (BmCPR123) and the gene for B. mori DNA replication licensing factor Mcm2-like (BmMCM2) were key genes among the common up-regulated DEGs, whereas the gene for B. mori heat shock protein 20.1 (Bmhsp20.1) was the central gene among the shared down-regulated DEGs between Lan5 vs Lan5-CPV and Ou17 vs Ou17-CPV. These findings established a comprehensive database of genes that are differentially expressed in response to BmCPV infection between silkworm strains that differed in resistance to BmCPV and implied that these DEGs might be involved in B. mori immune responses against BmCPV infection.

Prediction of gene expression in embryonic structures of Drosophila melanogaster.

PubMed

Samsonova, Anastasia A; Niranjan, Mahesan; Russell, Steven; Brazma, Alvis

2007-07-01

Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms.

Prediction of Gene Expression in Embryonic Structures of Drosophila melanogaster

PubMed Central

Samsonova, Anastasia A; Niranjan, Mahesan; Russell, Steven; Brazma, Alvis

2007-01-01

Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms. PMID:17658945

Performance of Identifiler Direct and PowerPlex 16 HS on the Applied Biosystems 3730 DNA Analyzer for processing biological samples archived on FTA cards.

PubMed

Laurin, Nancy; DeMoors, Anick; Frégeau, Chantal

2012-09-01

Direct amplification of STR loci from biological samples collected on FTA cards without prior DNA purification was evaluated using Identifiler Direct and PowerPlex 16 HS in conjunction with the use of a high throughput Applied Biosystems 3730 DNA Analyzer. In order to reduce the overall sample processing cost, reduced PCR volumes combined with various FTA disk sizes were tested. Optimized STR profiles were obtained using a 0.53 mm disk size in 10 μL PCR volume for both STR systems. These protocols proved effective in generating high quality profiles on the 3730 DNA Analyzer from both blood and buccal FTA samples. Reproducibility, concordance, robustness, sample stability and profile quality were assessed using a collection of blood and buccal samples on FTA cards from volunteer donors as well as from convicted offenders. The new developed protocols offer enhanced throughput capability and cost effectiveness without compromising the robustness and quality of the STR profiles obtained. These results support the use of these protocols for processing convicted offender samples submitted to the National DNA Data Bank of Canada. Similar protocols could be applied to the processing of casework reference samples or in paternity or family relationship testing. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Identification of Inhibitors in Lignocellulosic Slurries and Determination of Their Effect on Hydrocarbon-Producing Microorganisms

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

Yang, Shihui; Franden, Mary A; Yang, Qing

The aim of this work was to identify inhibitors in pretreated lignocellulosic slurries, evaluate high-throughput screening strategies, and investigate the impact of inhibitors on potential hydrocarbon-producing microorganisms. Compounds present in slurries that could inhibit microbial growth were identified through a detailed analysis of saccharified slurries by applying a combination of approaches of high-performance liquid chromatography, GC-MS, LC-DAD-MS, and ICP-MS. Several high-throughput assays were then evaluated to generate toxicity profiles. Our results demonstrated that Bioscreen C was useful for analyzing bacterial toxicity but not for yeast. AlamarBlue reduction assay can be a useful high-throughput assay for both bacterial and yeast strainsmore » as long as medium components do not interfere with fluorescence measurements. In addition, this work identified two major inhibitors (furfural and ammonium acetate) for three potential hydrocarbon-producing bacterial species that include Escherichia coli, Cupriavidus necator, and Rhodococcus opacus PD630, which are also the primary inhibitors for ethanologens. Here, this study was strived to establish a pipeline to quantify inhibitory compounds in biomass slurries and high-throughput approaches to investigate the effect of inhibitors on microbial biocatalysts, which can be applied for various biomass slurries or hydrolyzates generated through different pretreatment and enzymatic hydrolysis processes or different microbial candidates.« less

Identification of Inhibitors in Lignocellulosic Slurries and Determination of Their Effect on Hydrocarbon-Producing Microorganisms

DOE PAGES

Yang, Shihui; Franden, Mary A; Yang, Qing; ...

2018-04-04

The aim of this work was to identify inhibitors in pretreated lignocellulosic slurries, evaluate high-throughput screening strategies, and investigate the impact of inhibitors on potential hydrocarbon-producing microorganisms. Compounds present in slurries that could inhibit microbial growth were identified through a detailed analysis of saccharified slurries by applying a combination of approaches of high-performance liquid chromatography, GC-MS, LC-DAD-MS, and ICP-MS. Several high-throughput assays were then evaluated to generate toxicity profiles. Our results demonstrated that Bioscreen C was useful for analyzing bacterial toxicity but not for yeast. AlamarBlue reduction assay can be a useful high-throughput assay for both bacterial and yeast strainsmore » as long as medium components do not interfere with fluorescence measurements. In addition, this work identified two major inhibitors (furfural and ammonium acetate) for three potential hydrocarbon-producing bacterial species that include Escherichia coli, Cupriavidus necator, and Rhodococcus opacus PD630, which are also the primary inhibitors for ethanologens. Here, this study was strived to establish a pipeline to quantify inhibitory compounds in biomass slurries and high-throughput approaches to investigate the effect of inhibitors on microbial biocatalysts, which can be applied for various biomass slurries or hydrolyzates generated through different pretreatment and enzymatic hydrolysis processes or different microbial candidates.« less

Use of high-throughput and in vivo data to support read ...

EPA Pesticide Factsheets

Disrupting normal function of mitochondria can culminate in a variety of organ-level toxicities. A number of mechanisms - such as uncoupling of oxidative phosphorylation and inhibition of the electron transport chain - have been implicated in mitochondrial toxicity. The presence of mitochondrial toxicity has led to a number of drugs being withdrawn from the market highlighting the need to identify potential mitochondrial toxicants within the environment. High-throughput screening (HTS) assays provide a means of rapidly gathering toxicity data for a large number of chemicals; however, information as to the associated in vivo effect is typically unknown. The Adverse Outcome Pathway (AOP) concept provides a valuable scaffold onto which mechanistic data from different levels of biological organisation can be arranged.Information pertaining to mitochondrial toxicity from the U.S. EPA’s ToxCast program were integrated with rodent in vivo data from U.S. EPA’s ToxRefDB to connect the high throughput ToxCast assay results with potential adverse outcome data. Previously developed structural alerts were utilized to profile the chemicals with both in vitro mitochondrial toxicity and in vivo rodent data. Structural similarity guided by the toxicity profile as measured in the ToxCast assay battery was then used to group those chemicals which either were not tested in a mitochondrial toxicity assay or were not considered a “hit” and read-across was performed. Subsequen

Quantitative assessment of RNA-protein interactions with high-throughput sequencing-RNA affinity profiling.

PubMed

Ozer, Abdullah; Tome, Jacob M; Friedman, Robin C; Gheba, Dan; Schroth, Gary P; Lis, John T

2015-08-01

Because RNA-protein interactions have a central role in a wide array of biological processes, methods that enable a quantitative assessment of these interactions in a high-throughput manner are in great demand. Recently, we developed the high-throughput sequencing-RNA affinity profiling (HiTS-RAP) assay that couples sequencing on an Illumina GAIIx genome analyzer with the quantitative assessment of protein-RNA interactions. This assay is able to analyze interactions between one or possibly several proteins with millions of different RNAs in a single experiment. We have successfully used HiTS-RAP to analyze interactions of the EGFP and negative elongation factor subunit E (NELF-E) proteins with their corresponding canonical and mutant RNA aptamers. Here we provide a detailed protocol for HiTS-RAP that can be completed in about a month (8 d hands-on time). This includes the preparation and testing of recombinant proteins and DNA templates, clustering DNA templates on a flowcell, HiTS and protein binding with a GAIIx instrument, and finally data analysis. We also highlight aspects of HiTS-RAP that can be further improved and points of comparison between HiTS-RAP and two other recently developed methods, quantitative analysis of RNA on a massively parallel array (RNA-MaP) and RNA Bind-n-Seq (RBNS), for quantitative analysis of RNA-protein interactions.

High-throughput Titration of Luciferase-expressing Recombinant Viruses

PubMed Central

Garcia, Vanessa; Krishnan, Ramya; Davis, Colin; Batenchuk, Cory; Le Boeuf, Fabrice; Abdelbary, Hesham; Diallo, Jean-Simon

2014-01-01

Standard plaque assays to determine infectious viral titers can be time consuming, are not amenable to a high volume of samples, and cannot be done with viruses that do not form plaques. As an alternative to plaque assays, we have developed a high-throughput titration method that allows for the simultaneous titration of a high volume of samples in a single day. This approach involves infection of the samples with a Firefly luciferase tagged virus, transfer of the infected samples onto an appropriate permissive cell line, subsequent addition of luciferin, reading of plates in order to obtain luminescence readings, and finally the conversion from luminescence to viral titers. The assessment of cytotoxicity using a metabolic viability dye can be easily incorporated in the workflow in parallel and provide valuable information in the context of a drug screen. This technique provides a reliable, high-throughput method to determine viral titers as an alternative to a standard plaque assay. PMID:25285536

Functional genomics of lipid metabolism in the oleaginous yeast Rhodosporidium toruloides

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

Coradetti, Samuel T.; Pinel, Dominic; Geiselman, Gina M.

The basidiomycete yeast Rhodosporidium toruloides (also known as Rhodotorula toruloides) accumulates high concentrations of lipids and carotenoids from diverse carbon sources. It has great potential as a model for the cellular biology of lipid droplets and for sustainable chemical production. We developed a method for high-throughput genetics (RB-TDNAseq), using sequence-barcoded Agrobacterium tumefaciens T-DNA insertions. We identified 1,337 putative essential genes with low T-DNA insertion rates. We functionally profiled genes required for fatty acid catabolism and lipid accumulation, validating results with 35 targeted deletion strains. We identified a high-confidence set of 150 genes affecting lipid accumulation, including genes with predicted functionmore » in signaling cascades, gene expression, protein modification and vesicular trafficking, autophagy, amino acid synthesis and tRNA modification, and genes of unknown function. Lastly, these results greatly advance our understanding of lipid metabolism in this oleaginous species and demonstrate a general approach for barcoded mutagenesis that should enable functional genomics in diverse fungi.« less

Functional genomics of lipid metabolism in the oleaginous yeast Rhodosporidium toruloides

PubMed Central

Geiselman, Gina M; Ito, Masakazu; Mondo, Stephen J; Reilly, Morgann C; Cheng, Ya-Fang; Bauer, Stefan; Grigoriev, Igor V; Gladden, John M; Simmons, Blake A; Brem, Rachel B

2018-01-01

The basidiomycete yeast Rhodosporidium toruloides (also known as Rhodotorula toruloides) accumulates high concentrations of lipids and carotenoids from diverse carbon sources. It has great potential as a model for the cellular biology of lipid droplets and for sustainable chemical production. We developed a method for high-throughput genetics (RB-TDNAseq), using sequence-barcoded Agrobacterium tumefaciens T-DNA insertions. We identified 1,337 putative essential genes with low T-DNA insertion rates. We functionally profiled genes required for fatty acid catabolism and lipid accumulation, validating results with 35 targeted deletion strains. We identified a high-confidence set of 150 genes affecting lipid accumulation, including genes with predicted function in signaling cascades, gene expression, protein modification and vesicular trafficking, autophagy, amino acid synthesis and tRNA modification, and genes of unknown function. These results greatly advance our understanding of lipid metabolism in this oleaginous species and demonstrate a general approach for barcoded mutagenesis that should enable functional genomics in diverse fungi. PMID:29521624

Functional genomics of lipid metabolism in the oleaginous yeast Rhodosporidium toruloides

DOE PAGES

Coradetti, Samuel T.; Pinel, Dominic; Geiselman, Gina M.; ...

2018-03-09

The basidiomycete yeast Rhodosporidium toruloides (also known as Rhodotorula toruloides) accumulates high concentrations of lipids and carotenoids from diverse carbon sources. It has great potential as a model for the cellular biology of lipid droplets and for sustainable chemical production. We developed a method for high-throughput genetics (RB-TDNAseq), using sequence-barcoded Agrobacterium tumefaciens T-DNA insertions. We identified 1,337 putative essential genes with low T-DNA insertion rates. We functionally profiled genes required for fatty acid catabolism and lipid accumulation, validating results with 35 targeted deletion strains. We identified a high-confidence set of 150 genes affecting lipid accumulation, including genes with predicted functionmore » in signaling cascades, gene expression, protein modification and vesicular trafficking, autophagy, amino acid synthesis and tRNA modification, and genes of unknown function. Lastly, these results greatly advance our understanding of lipid metabolism in this oleaginous species and demonstrate a general approach for barcoded mutagenesis that should enable functional genomics in diverse fungi.« less

High throughput, cell type-specific analysis of key proteins in human endometrial biopsies of women from fertile and infertile couples

PubMed Central

Leach, Richard E.; Jessmon, Philip; Coutifaris, Christos; Kruger, Michael; Myers, Evan R.; Ali-Fehmi, Rouba; Carson, Sandra A.; Legro, Richard S.; Schlaff, William D.; Carr, Bruce R.; Steinkampf, Michael P.; Silva, Susan; Leppert, Phyllis C.; Giudice, Linda; Diamond, Michael P.; Armant, D. Randall

2012-01-01

BACKGROUND Although histological dating of endometrial biopsies provides little help for prediction or diagnosis of infertility, analysis of individual endometrial proteins, proteomic profiling and transcriptome analysis have suggested several biomarkers with altered expression arising from intrinsic abnormalities, inadequate stimulation by or in response to gonadal steroids or altered function due to systemic disorders. The objective of this study was to delineate the developmental dynamics of potentially important proteins in the secretory phase of the menstrual cycle, utilizing a collection of endometrial biopsies from women of fertile (n = 89) and infertile (n = 89) couples. METHODS AND RESULTS Progesterone receptor-B (PGR-B), leukemia inhibitory factor, glycodelin/progestagen-associated endometrial protein (PAEP), homeobox A10, heparin-binding EGF-like growth factor, calcitonin and chemokine ligand 14 (CXCL14) were measured using a high-throughput, quantitative immunohistochemical method. Significant cyclic and tissue-specific regulation was documented for each protein, as well as their dysregulation in women of infertile couples. Infertile patients demonstrated a delay early in the secretory phase in the decline of PGR-B (P < 0.05) and premature mid-secretory increases in PAEP (P < 0.05) and CXCL14 (P < 0.05), suggesting that the implantation interval could be closing early. Correlation analysis identified potential interactions among certain proteins that were disrupted by infertility. CONCLUSIONS This approach overcomes the limitations of a small sample number. Protein expression and localization provided important insights into the potential roles of these proteins in normal and pathological development of the endometrium that is not attainable from transcriptome analysis, establishing a basis for biomarker, diagnostic and targeted drug development for women with infertility. PMID:22215622

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

USDA-ARS?s Scientific Manuscript database

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

Identification of differentially expressed lncRNAs involved in transient regeneration of the neonatal C57BL/6J mouse heart by next-generation high-throughput RNA sequencing.

PubMed

Chen, Yu-Mei; Li, Hua; Fan, Yi; Zhang, Qi-Jun; Li, Xing; Wu, Li-Jie; Chen, Zi-Jie; Zhu, Chun; Qian, Ling-Mei

2017-04-25

Previous studies have shown that mammalian cardiac tissue has a regenerative capacity. Remarkably, neonatal mice can regenerate their cardiac tissue for up to 6 days after birth, but this capacity is lost by day 7. In this study, we aimed to explore the expression pattern of long noncoding RNA (lncRNA) during this period and examine the mechanisms underlying this process. We found that 685 lncRNAs and 1833 mRNAs were differentially expressed at P1 and P7 by the next-generation high-throughput RNA sequencing. The coding genes associated with differentially expressed lncRNAs were mainly involved in metabolic processes and cell proliferation, and also were potentially associated with several key regeneration signalling pathways, including PI3K-Akt, MAPK, Hippo and Wnt. In addition, we identified some correlated targets of highly-dysregulated lncRNAs such as Igfbp3, Trnp1, Itgb6, and Pim3 by the coding-noncoding gene co-expression network. These data may offer a reference resource for further investigation about the mechanisms by which lncRNAs regulate cardiac regeneration.

An Ultra-High Fluorescence Enhancement and High Throughput Assay for Revealing Expression and Internalization of Chemokine Receptor CXCR4.

PubMed

He, Hua; Wang, Xiaojuan; Cheng, Tiantian; Xia, Yongqing; Lao, Jun; Ge, Baosheng; Ren, Hao; Khan, Naseer Ullah; Huang, Fang

2016-04-18

Revealing chemokine receptor CXCR4 expression, distribution, and internalization levels in different cancers helps to evaluate cancer progression or prognosis and to set personalized treatment strategy. We here describe a sensitive and high-throughput immunoassay for determining CXCR4 expression and distribution in cancer cells. The assay is accessible to a wide range of users in an ordinary lab only by dip-coating poly(styrene-co-N-isopropylacrylamide) spheres on the glass substrate. The self- assembled spheres form three-dimensional photonic colloidal crystals which enhance the fluorescence of CF647 and Alexa Fluor 647 by a factor of up to 1000. CXCR4 in cells is detected by using the sandwich immunoassay, where the primary antibody recognizes CXCR4 and the secondary antibody is labeled with CF647. With the newly established assay, we quantified the total expression of CXCR4, its distribution on the cell membrane and cytoplasm, and revealed their internalization level upon SDF-1α activation in various cancer cells, even for those with extremely low expression level. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Engineering customized TALE nucleases (TALENs) and TALE transcription factors by fast ligation-based automatable solid-phase high-throughput (FLASH) assembly.

PubMed

Reyon, Deepak; Maeder, Morgan L; Khayter, Cyd; Tsai, Shengdar Q; Foley, Jonathan E; Sander, Jeffry D; Joung, J Keith

2013-07-01

Customized DNA-binding domains made using transcription activator-like effector (TALE) repeats are rapidly growing in importance as widely applicable research tools. TALE nucleases (TALENs), composed of an engineered array of TALE repeats fused to the FokI nuclease domain, have been used successfully for directed genome editing in various organisms and cell types. TALE transcription factors (TALE-TFs), consisting of engineered TALE repeat arrays linked to a transcriptional regulatory domain, have been used to up- or downregulate expression of endogenous genes in human cells and plants. This unit describes a detailed protocol for the recently described fast ligation-based automatable solid-phase high-throughput (FLASH) assembly method. FLASH enables automated high-throughput construction of engineered TALE repeats using an automated liquid handling robot or manually using a multichannel pipet. Using the automated approach, a single researcher can construct up to 96 DNA fragments encoding TALE repeat arrays of various lengths in a single day, and then clone these to construct sequence-verified TALEN or TALE-TF expression plasmids in a week or less. Plasmids required for FLASH are available by request from the Joung lab (http://eGenome.org). This unit also describes improvements to the Zinc Finger and TALE Targeter (ZiFiT Targeter) web server (http://ZiFiT.partners.org) that facilitate the design and construction of FLASH TALE repeat arrays in high throughput. © 2013 by John Wiley & Sons, Inc.

Engineering Customized TALE Nucleases (TALENs) and TALE Transcription Factors by Fast Ligation-based Automatable Solid-phase High-throughput (FLASH) Assembly

PubMed Central

Reyon, Deepak; Maeder, Morgan L.; Khayter, Cyd; Tsai, Shengdar Q.; Foley, Jonathan E.; Sander, Jeffry D.; Joung, J. Keith

2013-01-01

Customized DNA-binding domains made using Transcription Activator-Like Effector (TALE) repeats are rapidly growing in importance as widely applicable research tools. TALE nucleases (TALENs), composed of an engineered array of TALE repeats fused to the FokI nuclease domain, have been used successfully for directed genome editing in multiple different organisms and cell types. TALE transcription factors (TALE-TFs), consisting of engineered TALE repeat arrays linked to a transcriptional regulatory domain, have been used to up- or down-regulate expression of endogenous genes in human cells and plants. Here we describe a detailed protocol for practicing the recently described Fast Ligation-based Automatable Solid-phase High-throughput (FLASH) assembly method. FLASH enables automated high-throughput construction of engineered TALE repeats using an automated liquid handling robot or manually using a multi-channel pipet. With the automated version of FLASH, a single researcher can construct up to 96 DNA fragments encoding various length TALE repeat arrays in one day and then clone these to construct sequence-verified TALEN or TALE-TF expression plasmids in one week or less. Plas-mids required to practice FLASH are available by request from the Joung Lab (http://www.jounglab.org/). We also describe here improvements to the Zinc Finger and TALE Targeter (ZiFiT Targeter) webserver (http://ZiFiTBeta.partners.org) that facilitate the design and construction of FLASH TALE repeat arrays in high-throughput. PMID:23821439

A database application for pre-processing, storage and comparison of mass spectra derived from patients and controls

PubMed Central

Titulaer, Mark K; Siccama, Ivar; Dekker, Lennard J; van Rijswijk, Angelique LCT; Heeren, Ron MA; Sillevis Smitt, Peter A; Luider, Theo M

2006-01-01

Background Statistical comparison of peptide profiles in biomarker discovery requires fast, user-friendly software for high throughput data analysis. Important features are flexibility in changing input variables and statistical analysis of peptides that are differentially expressed between patient and control groups. In addition, integration the mass spectrometry data with the results of other experiments, such as microarray analysis, and information from other databases requires a central storage of the profile matrix, where protein id's can be added to peptide masses of interest. Results A new database application is presented, to detect and identify significantly differentially expressed peptides in peptide profiles obtained from body fluids of patient and control groups. The presented modular software is capable of central storage of mass spectra and results in fast analysis. The software architecture consists of 4 pillars, 1) a Graphical User Interface written in Java, 2) a MySQL database, which contains all metadata, such as experiment numbers and sample codes, 3) a FTP (File Transport Protocol) server to store all raw mass spectrometry files and processed data, and 4) the software package R, which is used for modular statistical calculations, such as the Wilcoxon-Mann-Whitney rank sum test. Statistic analysis by the Wilcoxon-Mann-Whitney test in R demonstrates that peptide-profiles of two patient groups 1) breast cancer patients with leptomeningeal metastases and 2) prostate cancer patients in end stage disease can be distinguished from those of control groups. Conclusion The database application is capable to distinguish patient Matrix Assisted Laser Desorption Ionization (MALDI-TOF) peptide profiles from control groups using large size datasets. The modular architecture of the application makes it possible to adapt the application to handle also large sized data from MS/MS- and Fourier Transform Ion Cyclotron Resonance (FT-ICR) mass spectrometry experiments. It is expected that the higher resolution and mass accuracy of the FT-ICR mass spectrometry prevents the clustering of peaks of different peptides and allows the identification of differentially expressed proteins from the peptide profiles. PMID:16953879

A database application for pre-processing, storage and comparison of mass spectra derived from patients and controls.

PubMed

Titulaer, Mark K; Siccama, Ivar; Dekker, Lennard J; van Rijswijk, Angelique L C T; Heeren, Ron M A; Sillevis Smitt, Peter A; Luider, Theo M

2006-09-05

Statistical comparison of peptide profiles in biomarker discovery requires fast, user-friendly software for high throughput data analysis. Important features are flexibility in changing input variables and statistical analysis of peptides that are differentially expressed between patient and control groups. In addition, integration the mass spectrometry data with the results of other experiments, such as microarray analysis, and information from other databases requires a central storage of the profile matrix, where protein id's can be added to peptide masses of interest. A new database application is presented, to detect and identify significantly differentially expressed peptides in peptide profiles obtained from body fluids of patient and control groups. The presented modular software is capable of central storage of mass spectra and results in fast analysis. The software architecture consists of 4 pillars, 1) a Graphical User Interface written in Java, 2) a MySQL database, which contains all metadata, such as experiment numbers and sample codes, 3) a FTP (File Transport Protocol) server to store all raw mass spectrometry files and processed data, and 4) the software package R, which is used for modular statistical calculations, such as the Wilcoxon-Mann-Whitney rank sum test. Statistic analysis by the Wilcoxon-Mann-Whitney test in R demonstrates that peptide-profiles of two patient groups 1) breast cancer patients with leptomeningeal metastases and 2) prostate cancer patients in end stage disease can be distinguished from those of control groups. The database application is capable to distinguish patient Matrix Assisted Laser Desorption Ionization (MALDI-TOF) peptide profiles from control groups using large size datasets. The modular architecture of the application makes it possible to adapt the application to handle also large sized data from MS/MS- and Fourier Transform Ion Cyclotron Resonance (FT-ICR) mass spectrometry experiments. It is expected that the higher resolution and mass accuracy of the FT-ICR mass spectrometry prevents the clustering of peaks of different peptides and allows the identification of differentially expressed proteins from the peptide profiles.

High throughput ion-channel pharmacology: planar-array-based voltage clamp.

PubMed

Kiss, Laszlo; Bennett, Paul B; Uebele, Victor N; Koblan, Kenneth S; Kane, Stefanie A; Neagle, Brad; Schroeder, Kirk

2003-02-01

Technological advances often drive major breakthroughs in biology. Examples include PCR, automated DNA sequencing, confocal/single photon microscopy, AFM, and voltage/patch-clamp methods. The patch-clamp method, first described nearly 30 years ago, was a major technical achievement that permitted voltage-clamp analysis (membrane potential control) of ion channels in most cells and revealed a role for channels in unimagined areas. Because of the high information content, voltage clamp is the best way to study ion-channel function; however, throughput is too low for drug screening. Here we describe a novel breakthrough planar-array-based HT patch-clamp technology developed by Essen Instruments capable of voltage-clamping thousands of cells per day. This technology provides greater than two orders of magnitude increase in throughput compared with the traditional voltage-clamp techniques. We have applied this method to study the hERG K(+) channel and to determine the pharmacological profile of QT prolonging drugs.

Elucidation of Adverse Bioactivity Profiles as Predictors of Toxicity Potential

EPA Science Inventory

Toxicity testing in vitro remains a formidable challenge due to lack of understanding of key molecular targets and pathways underlying many pathological events. The combination of genome sequencing and widespread application of high-throughput screening tools have provided the me...

20180312 - Mechanistic Modeling of Developmental Defects through Computational Embryology (SOT)

EPA Science Inventory

Significant advances in the genome sciences, in automated high-throughput screening (HTS), and in alternative methods for testing enable rapid profiling of chemical libraries for quantitative effects on diverse cellular activities. While a surfeit of HTS data and information is n...

HIGH-THROUGHPUT CHEMICAL SCREENING USING PROTEIN PROFILING OF FISH PLASMA

EPA Science Inventory

Compounds that affect the hormone system, referred to as "endocrine-disrupting chemicals" (EDCs), cause human and animal health problems. It is necessary to test putative EDC chemicals for such deleterious effects, though current testing methodologies are time/animal intensive an...

Advantages of RNA-seq compared to RNA microarrays for transcriptome profiling of anterior cruciate ligament tears.

PubMed

Rai, Muhammad Farooq; Tycksen, Eric D; Sandell, Linda J; Brophy, Robert H

2018-01-01

Microarrays and RNA-seq are at the forefront of high throughput transcriptome analyses. Since these methodologies are based on different principles, there are concerns about the concordance of data between the two techniques. The concordance of RNA-seq and microarrays for genome-wide analysis of differential gene expression has not been rigorously assessed in clinically derived ligament tissues. To demonstrate the concordance between RNA-seq and microarrays and to assess potential benefits of RNA-seq over microarrays, we assessed differences in transcript expression in anterior cruciate ligament (ACL) tissues based on time-from-injury. ACL remnants were collected from patients with an ACL tear at the time of ACL reconstruction. RNA prepared from torn ACL remnants was subjected to Agilent microarrays (N = 24) and RNA-seq (N = 8). The correlation of biological replicates in RNA-seq and microarrays data was similar (0.98 vs. 0.97), demonstrating that each platform has high internal reproducibility. Correlations between the RNA-seq data and the individual microarrays were low, but correlations between the RNA-seq values and the geometric mean of the microarrays values were moderate. The cross-platform concordance for differentially expressed transcripts or enriched pathways was linearly correlated (r = 0.64). RNA-Seq was superior in detecting low abundance transcripts and differentiating biologically critical isoforms. Additional independent validation of transcript expression was undertaken using microfluidic PCR for selected genes. PCR data showed 100% concordance (in expression pattern) with RNA-seq and microarrays data. These findings demonstrate that RNA-seq has advantages over microarrays for transcriptome profiling of ligament tissues when available and affordable. Furthermore, these findings are likely transferable to other musculoskeletal tissues where tissue collection is challenging and cells are in low abundance. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:484-497, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Characterization of transcriptome in the Indian meal moth Plodia interpunctella (Lepidoptera: Pyralidae) and gene expression analysis during developmental stages.

PubMed

Tang, Pei-An; Wu, Hai-Jing; Xue, Hao; Ju, Xing-Rong; Song, Wei; Zhang, Qi-Lin; Yuan, Ming-Long

2017-07-30

The Indian meal moth Plodia interpunctella (Lepidoptera: Pyralidae) is a worldwide pest that causes serious damage to stored foods. Although many efforts have been conducted on this species due to its economic importance, the study of genetic basis of development, behavior and insecticide resistance has been greatly hampered due to lack of genomic information. In this study, we used high throughput sequencing platform to perform a de novo transcriptome assembly and tag-based digital gene expression profiling (DGE) analyses across four different developmental stages of P. interpunctella (egg, third-instar larvae, pupae and adult). We obtained approximate 9gigabyte (GB) of clean data and recovered 84,938 unigenes, including 37,602 clusters and 47,336 singletons. These unigenes were annotated using BLAST against the non-redundant protein databases and then functionally classified based on Gene Ontology (GO), Clusters of Orthologous Groups (COG), and Kyoto Encyclopedia of Genes and Genomes databases (KEGG). A large number of differentially expressed genes were identified by pairwise comparisons among different developmental stages. Gene expression profiles dramatically changed between developmental stage transitions. Some of these differentially expressed genes were related to digestion and cuticularization. Quantitative real-time PCR results of six randomly selected genes conformed the findings in the DGEs. Furthermore, we identified over 8000 microsatellite markers and 97,648 single nucleotide polymorphisms which will be useful for population genetics studies of P. interpunctella. This transcriptomic information provided insight into the developmental basis of P. interpunctella and will be helpful for establishing integrated management strategies and developing new targets of insecticides for this serious pest. Copyright © 2017 Elsevier B.V. All rights reserved.

MetNet: Software to Build and Model the Biogenetic Lattice of Arabidopsis

DOE PAGES

Wurtele, Eve Syrkin; Li, Jie; Diao, Lixia; ...

2003-01-01

MetNet (http://www.botany.iastate.edu/∼mash/metnetex/metabolicnetex.html) is publicly available software in development for analysis of genome-wide RNA, protein and metabolite profiling data. The software is designed to enable the biologist to visualize, statistically analyse and model a metabolic and regulatory network map of Arabidopsis , combined with gene expression profiling data. It contains a JAVA interface to an interactions database (MetNetDB) containing information on regulatory and metabolic interactions derived from a combination of web databases (TAIR, KEGG, BRENDA) and input from biologists in their area of expertise. FCModeler captures input from MetNetDB in a graphical form. Sub-networks can be identified and interpreted using simplemore » fuzzy cognitive maps. FCModeler is intended to develop and evaluate hypotheses, and provide a modelling framework for assessing the large amounts of data captured by high-throughput gene expression experiments. FCModeler and MetNetDB are currently being extended to three-dimensional virtual reality display. The MetNet map, together with gene expression data, can be viewed using multivariate graphics tools in GGobi linked with the data analytic tools in R. Users can highlight different parts of the metabolic network and see the relevant expression data highlighted in other data plots. Multi-dimensional expression data can be rotated through different dimensions. Statistical analysis can be computed alongside the visual. MetNet is designed to provide a framework for the formulation of testable hypotheses regarding the function of specific genes, and in the long term provide the basis for identification of metabolic and regulatory networks that control plant composition and development.« less

High-throughput transformation of Saccharomyces cerevisiae using liquid handling robots.

PubMed

Liu, Guangbo; Lanham, Clayton; Buchan, J Ross; Kaplan, Matthew E

2017-01-01

Saccharomyces cerevisiae (budding yeast) is a powerful eukaryotic model organism ideally suited to high-throughput genetic analyses, which time and again has yielded insights that further our understanding of cell biology processes conserved in humans. Lithium Acetate (LiAc) transformation of yeast with DNA for the purposes of exogenous protein expression (e.g., plasmids) or genome mutation (e.g., gene mutation, deletion, epitope tagging) is a useful and long established method. However, a reliable and optimized high throughput transformation protocol that runs almost no risk of human error has not been described in the literature. Here, we describe such a method that is broadly transferable to most liquid handling high-throughput robotic platforms, which are now commonplace in academic and industry settings. Using our optimized method, we are able to comfortably transform approximately 1200 individual strains per day, allowing complete transformation of typical genomic yeast libraries within 6 days. In addition, use of our protocol for gene knockout purposes also provides a potentially quicker, easier and more cost-effective approach to generating collections of double mutants than the popular and elegant synthetic genetic array methodology. In summary, our methodology will be of significant use to anyone interested in high throughput molecular and/or genetic analysis of yeast.

Comparative transcriptome sequencing and de novo analysis of Vaccinium corymbosum during fruit and color development.

PubMed

Li, Lingli; Zhang, Hehua; Liu, Zhongshuai; Cui, Xiaoyue; Zhang, Tong; Li, Yanfang; Zhang, Lingyun

2016-10-12

Blueberry is an economically important fruit crop in Ericaceae family. The substantial quantities of flavonoids in blueberry have been implicated in a broad range of health benefits. However, the information regarding fruit development and flavonoid metabolites based on the transcriptome level is still limited. In the present study, the transcriptome and gene expression profiling over berry development, especially during color development were initiated. A total of approximately 13.67 Gbp of data were obtained and assembled into 186,962 transcripts and 80,836 unigenes from three stages of blueberry fruit and color development. A large number of simple sequence repeats (SSRs) and candidate genes, which are potentially involved in plant development, metabolic and hormone pathways, were identified. A total of 6429 sequences containing 8796 SSRs were characterized from 15,457 unigenes and 1763 unigenes contained more than one SSR. The expression profiles of key genes involved in anthocyanin biosynthesis were also studied. In addition, a comparison between our dataset and other published results was carried out. Our high quality reads produced in this study are an important advancement and provide a new resource for the interpretation of high-throughput data for blueberry species whether regarding sequencing data depth or species extension. The use of this transcriptome data will serve as a valuable public information database for the studies of blueberry genome and would greatly boost the research of fruit and color development, flavonoid metabolisms and regulation and breeding of more healthful blueberries.

High-Throughput In Vivo Genotoxicity Testing: An Automated Readout System for the Somatic Mutation and Recombination Test (SMART)

PubMed Central

Kwak, Jihoon; Genovesio, Auguste; Kang, Myungjoo; Hansen, Michael Adsett Edberg; Han, Sung-Jun

2015-01-01

Genotoxicity testing is an important component of toxicity assessment. As illustrated by the European registration, evaluation, authorization, and restriction of chemicals (REACH) directive, it concerns all the chemicals used in industry. The commonly used in vivo mammalian tests appear to be ill adapted to tackle the large compound sets involved, due to throughput, cost, and ethical issues. The somatic mutation and recombination test (SMART) represents a more scalable alternative, since it uses Drosophila, which develops faster and requires less infrastructure. Despite these advantages, the manual scoring of the hairs on Drosophila wings required for the SMART limits its usage. To overcome this limitation, we have developed an automated SMART readout. It consists of automated imaging, followed by an image analysis pipeline that measures individual wing genotoxicity scores. Finally, we have developed a wing score-based dose-dependency approach that can provide genotoxicity profiles. We have validated our method using 6 compounds, obtaining profiles almost identical to those obtained from manual measures, even for low-genotoxicity compounds such as urethane. The automated SMART, with its faster and more reliable readout, fulfills the need for a high-throughput in vivo test. The flexible imaging strategy we describe and the analysis tools we provide should facilitate the optimization and dissemination of our methods. PMID:25830368

Defined, serum/feeder-free conditions for expansion and drug screening of primary B-acute lymphoblastic leukemia.

PubMed

Jiang, Zhiwu; Wu, Di; Ye, Wei; Weng, Jianyu; Lai, Peilong; Shi, Pengcheng; Guo, Xutao; Huang, Guohua; Deng, Qiuhua; Tang, Yanlai; Zhao, Hongyu; Cui, Shuzhong; Lin, Simiao; Wang, Suna; Li, Baiheng; Wu, Qiting; Li, Yangqiu; Liu, Pentao; Pei, Duanqing; Du, Xin; Yao, Yao; Li, Peng

2017-12-05

Functional screening for compounds represents a major hurdle in the development of rational therapeutics for B-acute lymphoblastic leukemia (B-ALL). In addition, using cell lines as valid models for evaluating responses to novel drug therapies raises serious concerns, as cell lines are prone to genotypic/phenotypic drift and loss of heterogeneity in vitro . Here, we reported that OP9 cells, not OP9-derived adipocytes (OP9TA), support the growth of primary B-ALL cells in vitro . To identify the factors from OP9 cells that support the growth of primary B-ALL cells, we performed RNA-Seq to analyze the gene expression profiles of OP9 and OP9TA cells. We thus developed a defined, serum/feeder-free condition (FI76V) that can support the expansion of a range of clinically distinct primary B-ALL cells that still maintain their leukemia-initiating ability. We demonstrated the suitability of high-throughput drug screening based on our B-ALL cultured conditions. Upon screening 378 kinase inhibitors, we identified a cluster of 17 kinase inhibitors that can efficiently kill B-ALL cells in vitro . Importantly, we demonstrated the synergistic cytotoxicity of dinaciclib/BTG226 to B-ALL cells. Taken together, we developed a defined condition for the ex vivo expansion of primary B-ALL cells that is suitable for high-throughput screening of novel compounds.

Genomic and Epigenomic Alterations in Cancer.

PubMed

Chakravarthi, Balabhadrapatruni V S K; Nepal, Saroj; Varambally, Sooryanarayana

2016-07-01

Multiple genetic and epigenetic events characterize tumor progression and define the identity of the tumors. Advances in high-throughput technologies, like gene expression profiling, next-generation sequencing, proteomics, and metabolomics, have enabled detailed molecular characterization of various tumors. The integration and analyses of these high-throughput data have unraveled many novel molecular aberrations and network alterations in tumors. These molecular alterations include multiple cancer-driving mutations, gene fusions, amplification, deletion, and post-translational modifications, among others. Many of these genomic events are being used in cancer diagnosis, whereas others are therapeutically targeted with small-molecule inhibitors. Multiple genes/enzymes that play a role in DNA and histone modifications are also altered in various cancers, changing the epigenomic landscape during cancer initiation and progression. Apart from protein-coding genes, studies are uncovering the critical regulatory roles played by noncoding RNAs and noncoding regions of the genome during cancer progression. Many of these genomic and epigenetic events function in tandem to drive tumor development and metastasis. Concurrent advances in genome-modulating technologies, like gene silencing and genome editing, are providing ability to understand in detail the process of cancer initiation, progression, and signaling as well as opening up avenues for therapeutic targeting. In this review, we discuss some of the recent advances in cancer genomic and epigenomic research. Copyright © 2016 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Differential Mobility Spectrometry-Mass Spectrometry (DMS-MS) in Radiation Biodosimetry: Rapid and High-Throughput Quantitation of Multiple Radiation Biomarkers in Nonhuman Primate Urine.

PubMed

Chen, Zhidan; Coy, Stephen L; Pannkuk, Evan L; Laiakis, Evagelia C; Fornace, Albert J; Vouros, Paul

2018-05-07

High-throughput methods to assess radiation exposure are a priority due to concerns that include nuclear power accidents, the spread of nuclear weapon capability, and the risk of terrorist attacks. Metabolomics, the assessment of small molecules in an easily accessible sample, is the most recent method to be applied for the identification of biomarkers of the biological radiation response with a useful dose-response profile. Profiling for biomarker identification is frequently done using an LC-MS platform which has limited throughput due to the time-consuming nature of chromatography. We present here a chromatography-free simplified method for quantitative analysis of seven metabolites in urine with radiation dose-response using urine samples provided from the Pannkuk et al. (2015) study of long-term (7-day) radiation response in nonhuman primates (NHP). The stable isotope dilution (SID) analytical method consists of sample preparation by strong cation exchange-solid phase extraction (SCX-SPE) to remove interferences and concentrate the metabolites of interest, followed by differential mobility spectrometry (DMS) ion filtration to select the ion of interest and reduce chemical background, followed by mass spectrometry (overall SID-SPE-DMS-MS). Since no chromatography is used, calibration curves were prepared rapidly, in under 2 h (including SPE) for six simultaneously analyzed radiation biomarkers. The seventh, creatinine, was measured separately after 2500× dilution. Creatinine plays a dual role, measuring kidney glomerular filtration rate (GFR), and indicating kidney damage at high doses. The current quantitative method using SID-SPE-DMS-MS provides throughput which is 7.5 to 30 times higher than that of LC-MS and provides a path to pre-clinical radiation dose estimation. Graphical Abstract.

Differential Mobility Spectrometry-Mass Spectrometry (DMS-MS) in Radiation Biodosimetry: Rapid and High-Throughput Quantitation of Multiple Radiation Biomarkers in Nonhuman Primate Urine

NASA Astrophysics Data System (ADS)

Chen, Zhidan; Coy, Stephen L.; Pannkuk, Evan L.; Laiakis, Evagelia C.; Fornace, Albert J.; Vouros, Paul

2018-05-01

High-throughput methods to assess radiation exposure are a priority due to concerns that include nuclear power accidents, the spread of nuclear weapon capability, and the risk of terrorist attacks. Metabolomics, the assessment of small molecules in an easily accessible sample, is the most recent method to be applied for the identification of biomarkers of the biological radiation response with a useful dose-response profile. Profiling for biomarker identification is frequently done using an LC-MS platform which has limited throughput due to the time-consuming nature of chromatography. We present here a chromatography-free simplified method for quantitative analysis of seven metabolites in urine with radiation dose-response using urine samples provided from the Pannkuk et al. (2015) study of long-term (7-day) radiation response in nonhuman primates (NHP). The stable isotope dilution (SID) analytical method consists of sample preparation by strong cation exchange-solid phase extraction (SCX-SPE) to remove interferences and concentrate the metabolites of interest, followed by differential mobility spectrometry (DMS) ion filtration to select the ion of interest and reduce chemical background, followed by mass spectrometry (overall SID-SPE-DMS-MS). Since no chromatography is used, calibration curves were prepared rapidly, in under 2 h (including SPE) for six simultaneously analyzed radiation biomarkers. The seventh, creatinine, was measured separately after 2500× dilution. Creatinine plays a dual role, measuring kidney glomerular filtration rate (GFR), and indicating kidney damage at high doses. The current quantitative method using SID-SPE-DMS-MS provides throughput which is 7.5 to 30 times higher than that of LC-MS and provides a path to pre-clinical radiation dose estimation. [Figure not available: see fulltext.