Dataset Information

RNA CoMPASS: a dual approach for pathogen and host transcriptome analysis of RNA-seq datasets.

ABSTRACT: High-throughput RNA sequencing (RNA-seq) has become an instrumental assay for the analysis of multiple aspects of an organism's transcriptome. Further, the analysis of a biological specimen's associated microbiome can also be performed using RNA-seq data and this application is gaining interest in the scientific community. There are many existing bioinformatics tools designed for analysis and visualization of transcriptome data. Despite the availability of an array of next generation sequencing (NGS) analysis tools, the analysis of RNA-seq data sets poses a challenge for many biomedical researchers who are not familiar with command-line tools. Here we present RNA CoMPASS, a comprehensive RNA-seq analysis pipeline for the simultaneous analysis of transcriptomes and metatranscriptomes from diverse biological specimens. RNA CoMPASS leverages existing tools and parallel computing technology to facilitate the analysis of even very large datasets. RNA CoMPASS has a web-based graphical user interface with intrinsic queuing to control a distributed computational pipeline. RNA CoMPASS was evaluated by analyzing RNA-seq data sets from 45 B-cell samples. Twenty-two of these samples were derived from lymphoblastoid cell lines (LCLs) generated by the infection of naïve B-cells with the Epstein Barr virus (EBV), while another 23 samples were derived from Burkitt's lymphomas (BL), some of which arose in part through infection with EBV. Appropriately, RNA CoMPASS identified EBV in all LCLs and in a fraction of the BLs. Cluster analysis of the human transcriptome component of the RNA CoMPASS output clearly separated the BLs (which have a germinal center-like phenotype) from the LCLs (which have a blast-like phenotype) with evidence of activated MYC signaling and lower interferon and NF-kB signaling in the BLs. Together, this analysis illustrates the utility of RNA CoMPASS in the simultaneous analysis of transcriptome and metatranscriptome data. RNA CoMPASS is freely available at http://rnacompass.sourceforge.net/.

SUBMITTER: Xu G

PROVIDER: S-EPMC3934900 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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RNA CoMPASS: a dual approach for pathogen and host transcriptome analysis of RNA-seq datasets.

Xu Guorong G Strong Michael J MJ Lacey Michelle R MR Baribault Carl C Flemington Erik K EK Taylor Christopher M CM

PloS one 20140225 2

High-throughput RNA sequencing (RNA-seq) has become an instrumental assay for the analysis of multiple aspects of an organism's transcriptome. Further, the analysis of a biological specimen's associated microbiome can also be performed using RNA-seq data and this application is gaining interest in the scientific community. There are many existing bioinformatics tools designed for analysis and visualization of transcriptome data. Despite the availability of an array of next generation sequencing ...[more]

PMID: 24586784

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Project description:UnlabelledThe ability to adhere and adapt to the human respiratory tract mucosa plays a pivotal role in the pathogenic lifestyle of nontypeable Haemophilus influenzae (NTHi). However, the temporal events associated with a successful colonization have not been fully characterized. In this study, by reconstituting the ciliated human bronchial epithelium in vitro, we monitored the global transcriptional changes in NTHi and infected mucosal epithelium simultaneously for up to 72 h by dual RNA sequencing. The initial stage of colonization was characterized by the binding of NTHi to ciliated cells. Temporal profiling of host mRNA signatures revealed significant dysregulation of the target cell cytoskeleton elicited by bacterial infection, with a profound effect on the intermediate filament network and junctional complexes. In response to environmental stimuli of the host epithelium, NTHi downregulated its central metabolism and increased the expression of transporters, indicating a change in the metabolic regime due to the availability of host substrates. Concurrently, the oxidative environment generated by infected cells instigated bacterial expression of stress-induced defense mechanisms, including the transport of exogenous glutathione and activation of the toxin-antitoxin system. The results of this analysis were validated by those of confocal microscopy, Western blotting, Bio-plex, and real-time quantitative reverse transcription-PCR (qRT-PCR). Notably, as part of our screening for novel signatures of infection, we identified a global profile of noncoding transcripts that are candidate small RNAs (sRNAs) regulated during human host infection in Haemophilus species. Our data, by providing a robust and comprehensive representation of the cross talk between the host and invading pathogen, provides important insights into NTHi pathogenesis and the development of efficacious preventive strategies.ImportanceSimultaneous monitoring of infection-linked transcriptome alterations in an invading pathogen and its target host cells represents a key strategy for identifying regulatory responses that drive pathogenesis. In this study, we report the progressive events of NTHi colonization in a highly differentiated model of ciliated bronchial epithelium. Genome-wide transcriptome maps of NTHi during infection provided mechanistic insights into bacterial adaptive responses to the host niche, with modulation of the central metabolism as an important signature of the evolving milieu. Our data indicate that infected epithelia respond by substantial alteration of the cytoskeletal network and cytokine repertoire, revealing a dynamic cross talk that is responsible for the onset of inflammation. This work significantly enhances our understanding of the means by which NTHi promotes infection on human mucosae and reveals novel strategies exploited by this important pathogen to cause invasive disease.

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Dataset Information

RNA CoMPASS: a dual approach for pathogen and host transcriptome analysis of RNA-seq datasets.

Publications

RNA CoMPASS: a dual approach for pathogen and host transcriptome analysis of RNA-seq datasets.

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