Dataset Information

Taxonomer: an interactive metagenomics analysis portal for universal pathogen detection and host mRNA expression profiling.

ABSTRACT:

Background

High-throughput sequencing enables unbiased profiling of microbial communities, universal pathogen detection, and host response to infectious diseases. However, computation times and algorithmic inaccuracies have hindered adoption.

Results

We present Taxonomer, an ultrafast, web-tool for comprehensive metagenomics data analysis and interactive results visualization. Taxonomer is unique in providing integrated nucleotide and protein-based classification and simultaneous host messenger RNA (mRNA) transcript profiling. Using real-world case-studies, we show that Taxonomer detects previously unrecognized infections and reveals antiviral host mRNA expression profiles. To facilitate data-sharing across geographic distances in outbreak settings, Taxonomer is publicly available through a web-based user interface.

Conclusions

Taxonomer enables rapid, accurate, and interactive analyses of metagenomics data on personal computers and mobile devices.

SUBMITTER: Flygare S

PROVIDER: S-EPMC4880956 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Publications

Taxonomer: an interactive metagenomics analysis portal for universal pathogen detection and host mRNA expression profiling.

Flygare Steven S Simmon Keith K Miller Chase C Qiao Yi Y Kennedy Brett B Di Sera Tonya T Graf Erin H EH Tardif Keith D KD Kapusta Aurélie A Rynearson Shawn S Stockmann Chris C Queen Krista K Tong Suxiang S Voelkerding Karl V KV Blaschke Anne A Byington Carrie L CL Jain Seema S Pavia Andrew A Ampofo Krow K Eilbeck Karen K Marth Gabor G Yandell Mark M Schlaberg Robert R

Genome biology 20160526 1

<h4>Background</h4>High-throughput sequencing enables unbiased profiling of microbial communities, universal pathogen detection, and host response to infectious diseases. However, computation times and algorithmic inaccuracies have hindered adoption.<h4>Results</h4>We present Taxonomer, an ultrafast, web-tool for comprehensive metagenomics data analysis and interactive results visualization. Taxonomer is unique in providing integrated nucleotide and protein-based classification and simultaneous ...[more]

PMID: 27224977

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Project description:PurposeThe etiology of conjunctivitis is often misdiagnosed. An ideal diagnostic test would identify all possible infectious causes. In this study, we apply unbiased metagenomic RNA deep sequencing (MDS) to identify pathogens causing conjunctivitis.DesignMolecular study of prospectively collected conjunctival swabs from patients with presumed infectious conjunctivitis.ParticipantsPatients with presumed acute infectious conjunctivitis.MethodsConjunctival swabs were collected from patients presenting with acute conjunctivitis. Swabs were processed for MDS. Pathogens were identified using a rapid computational pipeline to analyze the nonhost sequences obtained from MDS. Differential gene expression analysis was performed to evaluate for host transcriptome signatures for infectious types. Clinical samples were deidentified, and laboratory personnel handling the samples and interpreting the data were masked.Main outcome measuresPathogens and differential transcripts identified by MDS.ResultsMetagenomic RNA deep sequencing detected pathogens in 86% (12/14) of the patients tested. Swabs from 10 of 14 patients were positive for human adenovirus (HAdV) while swabs from 2 of 14 patients were positive for Vittaforma corneae (a parasitic fungal species of the microsporidia group). Samples positive for HAdV by RNA-seq were independently verified in a CLIA-certified laboratory. Pathogen-directed polymerase chain reaction confirmed the presence of V. corneae genome in the samples positive by RNA-seq. Local host transcriptome analysis identified 12 differentially expressed genes that provided distinct expression signatures for patients infected with HAdV compared with V. corneae.ConclusionsMetagenomic RNA deep sequencing can reliably detect and quantify common and rare pathogens causing conjunctivitis, and identify strains. The unbiased nature of metagenomic RNA deep sequencing allowed an expanded scope of pathogen detection, including fungal species not commonly associated with acute conjunctivitis. In addition, the identification of infection type-specific local host transcriptome signatures may allow for pathogen detection even when the pathogen load is too low for direct identification.

Dataset Information

Taxonomer: an interactive metagenomics analysis portal for universal pathogen detection and host mRNA expression profiling.

Background

Results

Conclusions

Publications

Taxonomer: an interactive metagenomics analysis portal for universal pathogen detection and host mRNA expression profiling.

Similar Datasets

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