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Dynamic transcriptional signatures and network responses for clinical symptoms in influenza-infected human subjects using systems biology approaches.

ABSTRACT: Recent studies demonstrate that human blood transcriptional signatures may be used to support diagnosis and clinical decisions for acute respiratory viral infections such as influenza. In this article, we propose to use a newly developed systems biology approach for time course gene expression data to identify significant dynamically response genes and dynamic gene network responses to viral infection. We illustrate the methodological pipeline by reanalyzing the time course gene expression data from a study with healthy human subjects challenged by live influenza virus. We observed clear differences in the number of significant dynamic response genes (DRGs) between the symptomatic and asymptomatic subjects and also identified DRG signatures for symptomatic subjects with influenza infection. The 505 common DRGs shared by the symptomatic subjects have high consistency with the signature genes for predicting viral infection identified in previous works. The temporal response patterns and network response features were carefully analyzed and investigated.

SUBMITTER: Linel P

PROVIDER: S-EPMC4449157 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature

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Dynamic transcriptional signatures and network responses for clinical symptoms in influenza-infected human subjects using systems biology approaches.

Linel Patrice P Wu Shuang S Deng Nan N Wu Hulin H

Journal of pharmacokinetics and pharmacodynamics 20141001 5

Recent studies demonstrate that human blood transcriptional signatures may be used to support diagnosis and clinical decisions for acute respiratory viral infections such as influenza. In this article, we propose to use a newly developed systems biology approach for time course gene expression data to identify significant dynamically response genes and dynamic gene network responses to viral infection. We illustrate the methodological pipeline by reanalyzing the time course gene expression data ...[more]

PMID: 25015847

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Project description:Background: Clostridium thermocellum is a Gram-positive, anaerobic, thermophilic bacterium with a great potential to be a consolidated bioprocessing biocatalyst that can ferment cellulose to ethanol. To understand its physiology and genetic targets for future strain development, we have carried out several studies including ethanol-tolerant mutant resequencing and ethanol shock experiments. Methods: In this study, several approaches were applied to enrich mRNA for next-generation sequencing based RNA-Seq and the transcriptomic profiling of C. thermocellum ethanol shock responses was investigated using high-density tiling array and RNA-Seq. Correlations among different transcriptomic platforms of expression array, tiling array, and RNA-Seq were then compared, and data generated from systems biology studies were used for transcriptional architecture improvement. Results: Our results indicate that cloning-based Sanger sequencing can be used for mRNA enrichment ratio determination, and low-copy number plasmid performed better than high-copy one for cDNA library construction. In addition, high correlations were observed among same array platform using different analyses as well as those between two different array platforms of tiling and expression array when probe intensity was compared. Correlations between RNA-Seq and array results especially the one between RNA-Seq and tiling array are also high. Moreover, combining both RNA-Seq and microarray data the transcriptional architecture of C. thermocellum including the prediction and verification of novel transcript (gene), transcriptional start site (TSS), CAZyme genes, ncRNA, and operon were systematically updated and improved. Conclusions: RNA-seq has high correlation with array-based transcriptomic platforms and can provide additional information for transcriptional architecture and genome annotation improvement, which will facilitate future omics-based studies. A twelve array study using total RNA recovered from wild-type cultures of Clostridium thermocellum at different time points of 30, 60, and 120 min post-inoculation with 3.95 g/L [0.5% (v/v)] treatment compred to that of control without ethanol supplementation. Two biological replicates for treatment and control condition.

Dataset Information

Dynamic transcriptional signatures and network responses for clinical symptoms in influenza-infected human subjects using systems biology approaches.

Publications

Dynamic transcriptional signatures and network responses for clinical symptoms in influenza-infected human subjects using systems biology approaches.

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