A cloud-compatible bioinformatics pipeline for ultrarapid pathogen identification from next-generation sequencing of clinical samples

A novel outbreak enterovirus D68 strain associated with acute flaccid myelitis cases in the USA (2012-14): a retrospective cohort study

BACKGROUND

Enterovirus D68 was implicated in a widespread outbreak of severe respiratory illness across the USA in 2014 and has also been reported sporadically in patients with acute flaccid myelitis. We aimed to investigate the association between enterovirus D68 infection and acute flaccid myelitis during the 2014 enterovirus D68 respiratory outbreak in the USA.

METHODS

Patients with acute flaccid myelitis who presented to two hospitals in Colorado and California, USA, between Nov 24, 2013, and Oct 11, 2014, were included in the study. Additional cases identified from Jan 1, 2012, to Oct 4, 2014, via statewide surveillance were provided by the California Department of Public Health. We investigated the cause of these cases by metagenomic next-generation sequencing, viral genome recovery, and enterovirus D68 phylogenetic analysis. We compared patients with acute flaccid myelitis who were positive for enterovirus D68 with those with acute flaccid myelitis but negative for enterovirus D68 using the two-tailed Fisher's exact test, two-sample unpaired t test, and Mann-Whitney U test.

FINDINGS

48 patients were included: 25 with acute flaccid myelitis, two with enterovirus-associated encephalitis, five with enterovirus-D68-associated upper respiratory illness, and 16 with aseptic meningitis or encephalitis who tested positive for enterovirus. Enterovirus D68 was detected in respiratory secretions from seven (64%) of 11 patients comprising two temporally and geographically linked acute flaccid myelitis clusters at the height of the 2014 outbreak, and from 12 (48%) of 25 patients with acute flaccid myelitis overall. Phylogenetic analysis revealed that all enterovirus D68 sequences associated with acute flaccid myelitis grouped into a clade B1 strain that emerged in 2010. Of six coding polymorphisms in the clade B1 enterovirus D68 polyprotein, five were present in neuropathogenic poliovirus or enterovirus D70, or both. One child with acute flaccid myelitis and a sibling with only upper respiratory illness were both infected by identical enterovirus D68 strains. Enterovirus D68 viraemia was identified in a child experiencing acute neurological progression of his paralytic illness. Deep metagenomic sequencing of cerebrospinal fluid from 14 patients with acute flaccid myelitis did not reveal evidence of an alternative infectious cause to enterovirus D68.

INTERPRETATION

These findings strengthen the putative association between enterovirus D68 and acute flaccid myelitis and the contention that acute flaccid myelitis is a rare yet severe clinical manifestation of enterovirus D68 infection in susceptible hosts.

FUNDING

National Institutes of Health, University of California, Abbott Laboratories, and the Centers for Disease Control and Prevention.

Bacterial and viral identification and differentiation by amplicon sequencing on the MinION nanopore sequencer

Background

The MinION™ nanopore sequencer was recently released to a community of alpha-testers for evaluation using a variety of sequencing applications. Recent reports have tested the ability of the MinION™ to act as a whole genome sequencer and have demonstrated that nanopore sequencing has tremendous potential utility. However, the current nanopore technology still has limitations with respect to error-rate, and this is problematic when attempting to assemble whole genomes without secondary rounds of sequencing to correct errors. In this study, we tested the ability of the MinION™ nanopore sequencer to accurately identify and differentiate bacterial and viral samples via directed sequencing of characteristic genes shared broadly across a target clade.

Results

Using a 6 hour sequencing run time, sufficient data were generated to identify an E. coli sample down to the species level from 16S rDNA amplicons. Three poxviruses (cowpox, vaccinia-MVA, and vaccinia-Lister) were identified and differentiated down to the strain level, despite over 98% identity between the vaccinia strains. The ability to differentiate strains by amplicon sequencing on the MinION™ was accomplished despite an observed per-base error rate of approximately 30%.

Conclusions

While nanopore sequencing, using the MinION™ platform from Oxford Nanopore in particular, continues to mature into a commercially available technology, practical uses are sought for the current versions of the technology. This study offers evidence of the utility of amplicon sequencing by demonstrating that the current versions of MinION™ technology can accurately identify and differentiate both viral and bacterial species present within biological samples via amplicon sequencing.

Electronic supplementary material

The online version of this article (doi:10.1186/s13742-015-0051-z) contains supplementary material, which is available to authorized users.

RIEMS: a software pipeline for sensitive and comprehensive taxonomic classification of reads from metagenomics datasets

BACKGROUND

Fuelled by the advent and subsequent development of next generation sequencing technologies, metagenomics became a powerful tool for the analysis of microbial communities both scientifically and diagnostically. The biggest challenge is the extraction of relevant information from the huge sequence datasets generated for metagenomics studies. Although a plethora of tools are available, data analysis is still a bottleneck.

RESULTS

To overcome the bottleneck of data analysis, we developed an automated computational workflow called RIEMS - Reliable Information Extraction from Metagenomic Sequence datasets. RIEMS assigns every individual read sequence within a dataset taxonomically by cascading different sequence analyses with decreasing stringency of the assignments using various software applications. After completion of the analyses, the results are summarised in a clearly structured result protocol organised taxonomically. The high accuracy and performance of RIEMS analyses were proven in comparison with other tools for metagenomics data analysis using simulated sequencing read datasets.

CONCLUSIONS

RIEMS has the potential to fill the gap that still exists with regard to data analysis for metagenomics studies. The usefulness and power of RIEMS for the analysis of genuine sequencing datasets was demonstrated with an early version of RIEMS in 2011 when it was used to detect the orthobunyavirus sequences leading to the discovery of Schmallenberg virus.

Geospatial Resolution of Human and Bacterial Diversity with City-Scale Metagenomics

The panoply of microorganisms and other species present in our environment influence human health and disease, especially in cities, but have not been profiled with metagenomics at a city-wide scale. We sequenced DNA from surfaces across the entire New York City (NYC) subway system, the Gowanus Canal, and public parks. Nearly half of the DNA (48%) does not match any known organism; identified organisms spanned 1,688 bacterial, viral, archaeal, and eukaryotic taxa, which were enriched for harmless genera associated with skin (e.g., Acinetobacter). Predicted ancestry of human DNA left on subway surfaces can recapitulate U.S. Census demographic data, and bacterial signatures can reveal a station’s history, such as marine-associated bacteria in a hurricane-flooded station. Some evidence of pathogens was found (Bacillus anthracis), but a lack of reported cases in NYC suggests that the pathogens represent a normal, urban microbiome. This baseline metagenomic map of NYC could help long-term disease surveillance, bioterrorism threat mitigation, and health management in the built environment of cities.

Field pathogenomics reveals the emergence of a diverse wheat yellow rust population

BACKGROUND

Emerging and re-emerging pathogens imperil public health and global food security. Responding to these threats requires improved surveillance and diagnostic systems. Despite their potential, genomic tools have not been readily applied to emerging or re-emerging plant pathogens such as the wheat yellow (stripe) rust pathogen Puccinia striiformis f. sp. tritici (PST). This is due largely to the obligate parasitic nature of PST, as culturing PST isolates for DNA extraction remains slow and tedious.

RESULTS

To counteract the limitations associated with culturing PST, we developed and applied a field pathogenomics approach by transcriptome sequencing infected wheat leaves collected from the field in 2013. This enabled us to rapidly gain insights into this emerging pathogen population. We found that the PST population across the United Kingdom (UK) underwent a major shift in recent years. Population genetic structure analyses revealed four distinct lineages that correlated to the phenotypic groups determined through traditional pathology-based virulence assays. Furthermore, the genetic diversity between members of a single population cluster for all 2013 PST field samples was much higher than that displayed by historical UK isolates, revealing a more diverse population of PST.

CONCLUSIONS

Our field pathogenomics approach uncovered a dramatic shift in the PST population in the UK, likely due to a recent introduction of a diverse set of exotic PST lineages. The methodology described herein accelerates genetic analysis of pathogen populations and circumvents the difficulties associated with obligate plant pathogens. In principle, this strategy can be widely applied to a variety of plant pathogens.

Field pathogenomics reveals the emergence of a diverse wheat yellow rust population

Background

Emerging and re-emerging pathogens imperil public health and global food security. Responding to these threats requires improved surveillance and diagnostic systems. Despite their potential, genomic tools have not been readily applied to emerging or re-emerging plant pathogens such as the wheat yellow (stripe) rust pathogen Puccinia striiformis f. sp. tritici (PST). This is due largely to the obligate parasitic nature of PST, as culturing PST isolates for DNA extraction remains slow and tedious.

Results

To counteract the limitations associated with culturing PST, we developed and applied a field pathogenomics approach by transcriptome sequencing infected wheat leaves collected from the field in 2013. This enabled us to rapidly gain insights into this emerging pathogen population. We found that the PST population across the United Kingdom (UK) underwent a major shift in recent years. Population genetic structure analyses revealed four distinct lineages that correlated to the phenotypic groups determined through traditional pathology-based virulence assays. Furthermore, the genetic diversity between members of a single population cluster for all 2013 PST field samples was much higher than that displayed by historical UK isolates, revealing a more diverse population of PST.

Conclusions

Our field pathogenomics approach uncovered a dramatic shift in the PST population in the UK, likely due to a recent introduction of a diverse set of exotic PST lineages. The methodology described herein accelerates genetic analysis of pathogen populations and circumvents the difficulties associated with obligate plant pathogens. In principle, this strategy can be widely applied to a variety of plant pathogens.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0590-8) contains supplementary material, which is available to authorized users.

VERSE: a novel approach to detect virus integration in host genomes through reference genome customization

Fueled by widespread applications of high-throughput next generation sequencing (NGS) technologies and urgent need to counter threats of pathogenic viruses, large-scale studies were conducted recently to investigate virus integration in host genomes (for example, human tumor genomes) that may cause carcinogenesis or other diseases. A limiting factor in these studies, however, is rapid virus evolution and resulting polymorphisms, which prevent reads from aligning readily to commonly used virus reference genomes, and, accordingly, make virus integration sites difficult to detect. Another confounding factor is host genomic instability as a result of virus insertions. To tackle these challenges and improve our capability to identify cryptic virus-host fusions, we present a new approach that detects Virus intEgration sites through iterative Reference SEquence customization (VERSE). To the best of our knowledge, VERSE is the first approach to improve detection through customizing reference genomes. Using 19 human tumors and cancer cell lines as test data, we demonstrated that VERSE substantially enhanced the sensitivity of virus integration site detection. VERSE is implemented in the open source package VirusFinder 2 that is available at http://bioinfo.mc.vanderbilt.edu/VirusFinder/.

An ensemble strategy that significantly improves de novo assembly of microbial genomes from metagenomic next-generation sequencing data

Next-generation sequencing (NGS) approaches rapidly produce millions to billions of short reads, which allow pathogen detection and discovery in human clinical, animal and environmental samples. A major limitation of sequence homology-based identification for highly divergent microorganisms is the short length of reads generated by most highly parallel sequencing technologies. Short reads require a high level of sequence similarities to annotated genes to confidently predict gene function or homology. Such recognition of highly divergent homologues can be improved by reference-free (de novo) assembly of short overlapping sequence reads into larger contigs. We describe an ensemble strategy that integrates the sequential use of various de Bruijn graph and overlap-layout-consensus assemblers with a novel partitioned sub-assembly approach. We also proposed new quality metrics that are suitable for evaluating metagenome de novo assembly. We demonstrate that this new ensemble strategy tested using in silico spike-in, clinical and environmental NGS datasets achieved significantly better contigs than current approaches.

Diagnosis of neuroinvasive astrovirus infection in an immunocompromised adult with encephalitis by unbiased next-generation sequencing

Metagenomic next-generation sequencing (NGS) was used to diagnose an unusual and fatal case of progressive encephalitis in an immunocompromised adult presenting at disease onset as bilateral hearing loss. The sequencing and confirmatory studies revealed neuroinvasive infection of the brain by an astrovirus belonging to a recently discovered VA/HMO clade.

Clinical detection and characterization of bacterial pathogens in the genomics era

The availability of genome sequences obtained using next-generation sequencing (NGS) has revolutionized the field of infectious diseases. Indeed, more than 38,000 bacterial and 5,000 viral genomes have been sequenced to date, including representatives of all significant human pathogens. These tremendous amounts of data have not only enabled advances in fundamental biology, helping to understand the pathogenesis of microorganisms and their genomic evolution, but have also had implications for clinical microbiology. Here, we first review the current achievements of genomics in the development of improved diagnostic tools, including those that are now available in the clinic, such as the design of PCR assays for the detection of microbial pathogens, virulence factors or antibiotic-resistance determinants, or the design of optimized culture media for 'unculturable' pathogens. We then review the applications of genomics to the investigation of outbreaks, either through the design of genotyping assays or the direct sequencing of the causative strains. Finally, we discuss how genomics might change clinical microbiology in the future.

NCBI viral genomes resource

Recent technological innovations have ignited an explosion in virus genome sequencing that promises to fundamentally alter our understanding of viral biology and profoundly impact public health policy. Yet, any potential benefits from the billowing cloud of next generation sequence data hinge upon well implemented reference resources that facilitate the identification of sequences, aid in the assembly of sequence reads and provide reference annotation sources. The NCBI Viral Genomes Resource is a reference resource designed to bring order to this sequence shockwave and improve usability of viral sequence data. The resource can be accessed at http://www.ncbi.nlm.nih.gov/genome/viruses/ and catalogs all publicly available virus genome sequences and curates reference genome sequences. As the number of genome sequences has grown, so too have the difficulties in annotating and maintaining reference sequences. The rapid expansion of the viral sequence universe has forced a recalibration of the data model to better provide extant sequence representation and enhanced reference sequence products to serve the needs of the various viral communities. This, in turn, has placed increased emphasis on leveraging the knowledge of individual scientific communities to identify important viral sequences and develop well annotated reference virus genome sets.

MetaGeniE: characterizing human clinical samples using deep metagenomic sequencing

With the decreasing cost of next-generation sequencing, deep sequencing of clinical samples provides unique opportunities to understand host-associated microbial communities. Among the primary challenges of clinical metagenomic sequencing is the rapid filtering of human reads to survey for pathogens with high specificity and sensitivity. Metagenomes are inherently variable due to different microbes in the samples and their relative abundance, the size and architecture of genomes, and factors such as target DNA amounts in tissue samples (i.e. human DNA versus pathogen DNA concentration). This variation in metagenomes typically manifests in sequencing datasets as low pathogen abundance, a high number of host reads, and the presence of close relatives and complex microbial communities. In addition to these challenges posed by the composition of metagenomes, high numbers of reads generated from high-throughput deep sequencing pose immense computational challenges. Accurate identification of pathogens is confounded by individual reads mapping to multiple different reference genomes due to gene similarity in different taxa present in the community or close relatives in the reference database. Available global and local sequence aligners also vary in sensitivity, specificity, and speed of detection. The efficiency of detection of pathogens in clinical samples is largely dependent on the desired taxonomic resolution of the organisms. We have developed an efficient strategy that identifies “all against all” relationships between sequencing reads and reference genomes. Our approach allows for scaling to large reference databases and then genome reconstruction by aggregating global and local alignments, thus allowing genetic characterization of pathogens at higher taxonomic resolution. These results were consistent with strain level SNP genotyping and bacterial identification from laboratory culture.

Actionable diagnosis of neuroleptospirosis by next-generation sequencing

A 14-year-old boy with severe combined immunodeficiency presented three times to a medical facility over a period of 4 months with fever and headache that progressed to hydrocephalus and status epilepticus necessitating a medically induced coma. Diagnostic workup including brain biopsy was unrevealing. Unbiased next-generation sequencing of the cerebrospinal fluid identified 475 of 3,063,784 sequence reads (0.016%) corresponding to leptospira infection. Clinical assays for leptospirosis were negative. Targeted antimicrobial agents were administered, and the patient was discharged home 32 days later with a status close to his premorbid condition. Polymerase-chain-reaction (PCR) and serologic testing at the Centers for Disease Control and Prevention (CDC) subsequently confirmed evidence of Leptospira santarosai infection.