Bacterial vaginosis (BV) is a common condition that is associated with numerous adverse health outcomes and is characterized by poorly understood changes in the vaginal microbiota. We sought to ...describe the composition and diversity of the vaginal bacterial biota in women with BV using deep sequencing of the 16S rRNA gene coupled with species-level taxonomic identification. We investigated the associations between the presence of individual bacterial species and clinical diagnostic characteristics of BV.
Broad-range 16S rRNA gene PCR and pyrosequencing were performed on vaginal swabs from 220 women with and without BV. BV was assessed by Amsel's clinical criteria and confirmed by Gram stain. Taxonomic classification was performed using phylogenetic placement tools that assigned 99% of query sequence reads to the species level. Women with BV had heterogeneous vaginal bacterial communities that were usually not dominated by a single taxon. In the absence of BV, vaginal bacterial communities were dominated by either Lactobacillus crispatus or Lactobacillus iners. Leptotrichia amnionii and Eggerthella sp. were the only two BV-associated bacteria (BVABs) significantly associated with each of the four Amsel's criteria. Co-occurrence analysis revealed the presence of several sub-groups of BVABs suggesting metabolic co-dependencies. Greater abundance of several BVABs was observed in Black women without BV.
The human vaginal bacterial biota is heterogeneous and marked by greater species richness and diversity in women with BV; no species is universally present. Different bacterial species have different associations with the four clinical criteria, which may account for discrepancies often observed between Amsel and Nugent (Gram stain) diagnostic criteria. Several BVABs exhibited race-dependent prevalence when analyzed in separate groups by BV status which may contribute to increased incidence of BV in Black women. Tools developed in this project can be used to study microbial ecology in diverse settings at high resolution.
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Classifying individual bacterial species comprising complex, polymicrobial patient specimens remains a challenge for culture-based and molecular microbiology techniques in common clinical use. We ...therefore adapted practices from metagenomics research to rapidly catalog the bacterial composition of clinical specimens directly from patients, without need for prior culture. We have combined a semiconductor deep sequencing protocol that produces reads spanning 16S ribosomal RNA gene variable regions 1 and 2 (∼360 bp) with a de-noising pipeline that significantly improves the fraction of error-free sequences. The resulting sequences can be used to perform accurate genus- or species-level taxonomic assignment. We explore the microbial composition of challenging, heterogeneous clinical specimens by deep sequencing, culture-based strain typing, and Sanger sequencing of bulk PCR product. We report that deep sequencing can catalog bacterial species in mixed specimens from which usable data cannot be obtained by conventional clinical methods. Deep sequencing a collection of sputum samples from cystic fibrosis (CF) patients reveals well-described CF pathogens in specimens where they were not detected by standard clinical culture methods, especially for low-prevalence or fastidious bacteria. We also found that sputa submitted for CF diagnostic workup can be divided into a limited number of groups based on the phylogenetic composition of the airway microbiota, suggesting that metagenomic profiling may prove useful as a clinical diagnostic strategy in the future. The described method is sufficiently rapid (theoretically compatible with same-day turnaround times) and inexpensive for routine clinical use.
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High-throughput sequencing of the taxonomically informative 16S rRNA gene provides a powerful approach for exploring microbial diversity. Here we compare the performances of two common "benchtop" ...sequencing platforms, Illumina MiSeq and Ion Torrent Personal Genome Machine (PGM), for bacterial community profiling by 16S rRNA (V1-V2) amplicon sequencing. We benchmarked performance by using a 20-organism mock bacterial community and a collection of primary human specimens. We observed comparatively higher error rates with the Ion Torrent platform and report a pattern of premature sequence truncation specific to semiconductor sequencing. Read truncation was dependent on both the directionality of sequencing and the target species, resulting in organism-specific biases in community profiles. We found that these sequencing artifacts could be minimized by using bidirectional amplicon sequencing and an optimized flow order on the Ion Torrent platform. Results of bacterial community profiling performed on the mock community and a collection of 18 human-derived microbiological specimens were generally in good agreement for both platforms; however, in some cases, results differed significantly. Disparities could be attributed to the failure to generate full-length reads for particular organisms on the Ion Torrent platform, organism-dependent differences in sequence error rates affecting classification of certain species, or some combination of these factors. This study demonstrates the potential for differential bias in bacterial community profiles resulting from the choice of sequencing platform alone.
Bacterial vaginosis (BV) is characterized by shifts in the vaginal microbiota from Lactobacillus dominant to a microbiota with diverse anaerobic bacteria. Few studies have linked specific metabolites ...with bacteria found in the human vagina. Here, we report dramatic differences in metabolite compositions and concentrations associated with BV using a global metabolomics approach. We further validated important metabolites using samples from a second cohort of women and a different platform to measure metabolites. In the primary study, we compared metabolite profiles in cervicovaginal lavage fluid from 40 women with BV and 20 women without BV. Vaginal bacterial representation was determined using broad-range PCR with pyrosequencing and concentrations of bacteria by quantitative PCR. We detected 279 named biochemicals; levels of 62% of metabolites were significantly different in women with BV. Unsupervised clustering of metabolites separated women with and without BV. Women with BV have metabolite profiles marked by lower concentrations of amino acids and dipeptides, concomitant with higher levels of amino acid catabolites and polyamines. Higher levels of the signaling eicosanoid 12-hydroxyeicosatetraenoic acid (12-HETE), a biomarker for inflammation, were noted in BV. Lactobacillus crispatus and Lactobacillus jensenii exhibited similar metabolite correlation patterns, which were distinct from correlation patterns exhibited by BV-associated bacteria. Several metabolites were significantly associated with clinical signs and symptoms (Amsel criteria) used to diagnose BV, and no metabolite was associated with all four clinical criteria. BV has strong metabolic signatures across multiple metabolic pathways, and these signatures are associated with the presence and concentrations of particular bacteria.
Bacterial vaginosis (BV) is a common but highly enigmatic condition that is associated with adverse outcomes for women and their neonates. Small molecule metabolites in the vagina may influence host physiology, affect microbial community composition, and impact risk of adverse health outcomes, but few studies have comprehensively studied the metabolomics profile of BV. Here, we used mass spectrometry to link specific metabolites with particular bacteria detected in the human vagina by PCR. BV was associated with strong metabolic signatures across multiple pathways affecting amino acid, carbohydrate, and lipid metabolism, highlighting the profound metabolic changes in BV. These signatures were associated with the presence and concentrations of particular vaginal bacteria, including some bacteria yet to be cultivated, thereby providing clues as to the microbial origin of many metabolites. Insights from this study provide opportunities for developing new diagnostic markers of BV and novel approaches for treatment or prevention of BV.
Identification and analysis of clinically relevant strains of bacteria increasingly relies on whole-genome sequencing. The downstream bioinformatics steps necessary for calling variants from ...short-read sequences are well-established but seldom validated against haploid genomes. We devised an
workflow to introduce single nucleotide polymorphisms (SNP) and indels into bacterial reference genomes, and computationally generate sequencing reads based on the mutated genomes. We then applied the method to Mycobacterium tuberculosis H37Rv, Staphylococcus aureus NCTC 8325, and Klebsiella pneumoniae HS11286, and used the synthetic reads as truth sets for evaluating several popular variant callers. Insertions proved especially challenging for most variant callers to correctly identify, relative to deletions and single nucleotide polymorphisms. With adequate read depth, however, variant callers that use high quality soft-clipped reads and base mismatches to perform local realignment consistently had the highest precision and recall in identifying insertions and deletions ranging from1 to 50 bp. The remaining variant callers had lower recall values associated with identification of insertions greater than 20 bp.
Microbiome studies commonly use 16S rRNA gene amplicon sequencing to characterize microbial communities. Errors introduced at multiple steps in this process can affect the interpretation of the data. ...Here we evaluate the accuracy of operational taxonomic unit (OTU) generation, taxonomic classification, alpha- and beta-diversity measures for different settings in QIIME, MOTHUR and a pplacer-based classification pipeline, using a novel software package: DECARD.
In-silico we generated 100 synthetic bacterial communities approximating human stool microbiomes to be used as a gold-standard for evaluating the colligative performance of microbiome analysis software. Our synthetic data closely matched the composition and complexity of actual healthy human stool microbiomes. Genus-level taxonomic classification was correctly done for only 50.4-74.8% of the source organisms. Miscall rates varied from 11.9 to 23.5%. Species-level classification was less successful, (6.9-18.9% correct); miscall rates were comparable to those of genus-level targets (12.5-26.2%). The degree of miscall varied by clade of organism, pipeline and specific settings used. OTU generation accuracy varied by strategy (closed, de novo or subsampling), reference database, algorithm and software implementation. Shannon diversity estimation accuracy correlated generally with OTU-generation accuracy. Beta-diversity estimates with Double Principle Coordinate Analysis (DPCoA) were more robust against errors introduced in processing than Weighted UniFrac. The settings suggested in the tutorials were among the worst performing in all outcomes tested.
Even when using the same classification pipeline, the specific OTU-generation strategy, reference database and downstream analysis methods selection can have a dramatic effect on the accuracy of taxonomic classification, and alpha- and beta-diversity estimation. Even minor changes in settings adversely affected the accuracy of the results, bringing them far from the best-observed result. Thus, specific details of how a pipeline is used (including OTU generation strategy, reference sets, clustering algorithm and specific software implementation) should be specified in the methods section of all microbiome studies. Researchers should evaluate their chosen pipeline and settings to confirm it can adequately answer the research question rather than assuming the tutorial or standard-operating-procedure settings will be adequate or optimal.
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Laboratories performing clinical high-throughput sequencing for oncology and germline testing are increasingly migrating their data storage to cloud-based solutions. Cloud-based storage has several ...advantages, such as low per-GB prices, scalability, and minimal fixed costs; however, while these solutions tout ostensibly simple usage-based pricing plans, practical cost analysis of cloud storage for NGS data storage is not straightforward.
We developed an easy-to-use tool designed specifically for cost and usage estimation for laboratories performing clinical NGS testing (https://ngscosts.info). Our tool enables quick exploration of dozens of storage options across three major cloud providers, and provides complex cost and usage forecasts over 1–20 year timeframes. Parameters include current test volumes, growth rate, data compression, data retention policies, and case re-access rates. Outputs include an easy-to-visualize chart of total data stored, yearly and lifetime costs, and a “cost per test” estimate.
Two factors were found to markedly decrease the average cost per test: 1) reducing total file size, including through the use of compression, 2) rapid transfer to “cold” or archival storage. In contrast, re-access of data from archival storage tiers was not found to dramatically increase the cost of storage per test.
Steady declines in cloud storage pricing, as well as new options for storage and retrieval, make storing clinical NGS data on the cloud economical and friendly to laboratory workflows. Our web-based tool makes it possible to explore and compare cloud storage solutions and provide forecasts specifically for clinical NGS laboratories.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
A format for phylogenetic placements Matsen, Frederick A; Hoffman, Noah G; Gallagher, Aaron ...
PloS one,
02/2012, Volume:
7, Issue:
2
Journal Article
Peer reviewed
Open access
We have developed a unified format for phylogenetic placements, that is, mappings of environmental sequence data (e.g., short reads) into a phylogenetic tree. We are motivated to do so by the growing ...number of tools for computing and post-processing phylogenetic placements, and the lack of an established standard for storing them. The format is lightweight, versatile, extensible, and is based on the JSON format, which can be parsed by most modern programming languages. Our format is already implemented in several tools for computing and post-processing parsimony- and likelihood-based phylogenetic placements and has worked well in practice. We believe that establishing a standard format for analyzing read placements at this early stage will lead to a more efficient development of powerful and portable post-analysis tools for the growing applications of phylogenetic placement.
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Abstract
Background
Healthcare workers (HCWs) who serve on the front lines of the coronavirus disease 2019 (COVID-19) pandemic have been at increased risk for infection due to severe acute ...respiratory syndrome coronavirus 2 (SARS-CoV-2) in some settings. Healthcare-acquired infection has been reported in similar epidemics, but there are limited data on the prevalence of COVID-19 among HCWs and their associated clinical outcomes in the United States.
Methods
We established 2 high-throughput employee testing centers in Seattle, Washington, with drive-through and walk-through options for symptomatic employees in the University of Washington Medicine system and its affiliated organizations. Using data from these testing centers, we report the prevalence of SARS-CoV-2 infection among symptomatic employees and describe the clinical characteristics and outcomes among employees with COVID-19.
Results
Between 12 March 2020 and 23 April 2020, 3477 symptomatic employees were tested for COVID-19 at 2 employee testing centers; 185 (5.3%) employees tested positive for COVID-19. The prevalence of SARS-CoV-2 was similar when comparing frontline HCWs (5.2%) with nonfrontline staff (5.5%). Among 174 positive employees reached for follow-up at least 14 days after diagnosis, 6 reported COVID-related hospitalization; all recovered.
Conclusions
During the study period, we observed that the prevalence of positive SARS-CoV-2 tests among symptomatic HCWs was comparable to that of symptomatic nonfrontline staff. Reliable and rapid access to testing for employees is essential to preserve the health, safety, and availability of the healthcare workforce during this pandemic and to facilitate the rapid return of SARS-CoV-2–negative employees to work.
In this retrospective review of 3477 symptomatic employees tested at high-throughput testing centers, 185 (5.3%) tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Of those, 6 reported coronavirus disease 2019–related hospitalization. The prevalence of SARS-CoV-2 among symptomatic healthcare workers was comparable to that of symptomatic nonfrontline staff.
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