e Current infectious disease molecular tests are largely pathogen specific, requiring test selection based on the patient's symptoms. For many syndromes caused by a large number of viral, bacterial, or fungal pathogens, such as respiratory tract infections, this necessitates large panels of tests and has limited yield. In contrast, next-generation sequencing-based metagenomics can be used for unbiased detection of any expected or unexpected pathogen. However, barriers for its diagnostic implementation include incomplete understanding of analytical performance and complexity of sequence data analysis. We compared detection of known respiratory virus-positive (n ‫؍‬ 42) and unselected (n ‫؍‬ 67) pediatric nasopharyngeal swabs using an RNA sequencing (RNA-seq)-based metagenomics approach and Taxonomer, an ultrarapid, interactive, web-based metagenomics data analysis tool, with an FDA-cleared respiratory virus panel (RVP; GenMark eSensor). Untargeted metagenomics detected 86% of known respiratory virus infections, and additional PCR testing confirmed RVP results for only 2 (33%) of the discordant samples. In unselected samples, untargeted metagenomics had excellent agreement with the RVP (93%). In addition, untargeted metagenomics detected an additional 12 viruses that were either not targeted by the RVP or missed due to highly divergent genome sequences. Normalized viral read counts for untargeted metagenomics correlated with viral burden determined by quantitative PCR and showed high intrarun and interrun reproducibility. Partial or full-length viral genome sequences were generated in 86% of RNA-seq-positive samples, allowing assessment of antiviral resistance, strain-level typing, and phylogenetic relatedness. Overall, untargeted metagenomics had high agreement with a sensitive RVP, detected viruses not targeted by the RVP, and yielded epidemiologically and clinically valuable sequence information. L aboratory diagnosis of infectious diseases has historically taken a syndrome-based approach. Culture of appropriate specimens on a combination of relevant media or cell lines enables detection of certain common bacterial, viral, and fungal pathogens. However, culture requires experienced personnel, requires several days to weeks to yield a definitive answer, depends on viability and appropriate culture conditions, and has limited sensitivity. Molecular tests have superior turnaround times, sensitivity, and taxonomic resolution. However, only targeted pathogens can be detected, and differentiation of clinically or epidemiologically relevant strains or genotypes is limited. Moreover, molecular tests need to be updated when new species or strains are recognized to ensure that newly identified genetic variants can be detected.In contrast, next-generation sequencing-based metagenomic testing combines and extends many advantages of molecular tests and culture-based methods. Host-and pathogen-derived nucleic acids are sequenced without a priori knowledge of expected pathogens, allowing simultaneous detection of a virtually ...

BackgroundHigh-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.ResultsWe 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.ConclusionsTaxonomer enables rapid, accurate, and interactive analyses of metagenomics data on personal computers and mobile devices.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-0969-1) contains supplementary material, which is available to authorized users.

Background Community-acquired pneumonia (CAP) is a leading cause of pediatric hospitalization. Pathogen identification fails in approximately 20% of children but is critical for optimal treatment and prevention of hospital-acquired infections. We used two broad-spectrum detection strategies to identify pathogens in test-negative children with CAP and asymptomatic controls. Methods Nasopharyngeal/oropharyngeal (NP/OP) swabs from 70 children <5 years with CAP of unknown etiology and 90 asymptomatic controls were tested by next-generation sequencing (RNA-seq) and pan viral group (PVG) PCR for 19 viral families. Association of viruses with CAP was assessed by adjusted odds ratios (aOR) and 95% confidence intervals controlling for season and age group. Results RNA-seq/PVG PCR detected previously missed, putative pathogens in 34% of patients. Putative viral pathogens included human parainfluenza virus 4 (aOR 9.3, P = .12), human bocavirus (aOR 9.1, P < .01), Coxsackieviruses (aOR 5.1, P = .09), rhinovirus A (aOR 3.5, P = .34), and rhinovirus C (aOR 2.9, P = .57). RNA-seq was more sensitive for RNA viruses whereas PVG PCR detected more DNA viruses. Conclusions RNA-seq and PVG PCR identified additional viruses, some known to be pathogenic, in NP/OP specimens from one-third of children hospitalized with CAP without a previously identified etiology. Both broad-range methods could be useful tools in future epidemiologic and diagnostic studies.

Mycobacterium massiliense is a rapidly growing mycobacterium that is indistinguishable from Mycobacterium chelonae/M. abscessus by partial 16S rRNA gene sequencing. We sequenced rpoB, sodA, and hsp65 genes from isolates previously identified as being M. chelonae/M. abscessus and identified M. massiliense from isolates from two patients with invasive disease representing the first reported cases in the United States.Rapidly growing mycobacterium infections are increasing in the United States (7) and are difficult to speciate by conventional methods. Partial 16S rRNA gene sequencing is the most widely used method for the identification of nontuberculous mycobacteria (6,8,12), but this gene target is often limited by the lack of sequence divergence among closely related Mycobacterium species (15). Mycobacterium chelonae and M. abscessus are two species that share the same 16S rRNA gene sequence, and since distinguishing these two species is clinically relevant, assays targeting base pair differences within the 16S-23S rRNA internal transcribed spacer (ITS) region have been developed (5