Dataset Information

Exploration and retrieval of whole-metagenome sequencing samples.

ABSTRACT:

Motivation

Over the recent years, the field of whole-metagenome shotgun sequencing has witnessed significant growth owing to the high-throughput sequencing technologies that allow sequencing genomic samples cheaper, faster and with better coverage than before. This technical advancement has initiated the trend of sequencing multiple samples in different conditions or environments to explore the similarities and dissimilarities of the microbial communities. Examples include the human microbiome project and various studies of the human intestinal tract. With the availability of ever larger databases of such measurements, finding samples similar to a given query sample is becoming a central operation.

Results

In this article, we develop a content-based exploration and retrieval method for whole-metagenome sequencing samples. We apply a distributed string mining framework to efficiently extract all informative sequence k-mers from a pool of metagenomic samples and use them to measure the dissimilarity between two samples. We evaluate the performance of the proposed approach on two human gut metagenome datasets as well as human microbiome project metagenomic samples. We observe significant enrichment for diseased gut samples in results of queries with another diseased sample and high accuracy in discriminating between different body sites even though the method is unsupervised.

Availability and implementation

A software implementation of the DSM framework is available at https://github.com/HIITMetagenomics/dsm-framework.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Seth S

PROVIDER: S-EPMC4230234 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Exploration and retrieval of whole-metagenome sequencing samples.

Seth Sohan S Välimäki Niko N Kaski Samuel S Honkela Antti A

Bioinformatics (Oxford, England) 20140519 17

<h4>Motivation</h4>Over the recent years, the field of whole-metagenome shotgun sequencing has witnessed significant growth owing to the high-throughput sequencing technologies that allow sequencing genomic samples cheaper, faster and with better coverage than before. This technical advancement has initiated the trend of sequencing multiple samples in different conditions or environments to explore the similarities and dissimilarities of the microbial communities. Examples include the human micr ...[more]

PMID: 24845653

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Project description:IntroductionAdvancements in DNA extraction and sequencing technologies have been fundamental in deciphering the significance of the microbiome related to human health and pathology. Whole metagenome shotgun sequencing (WMS) is gaining popularity in use compared to its predecessor (i.e., amplicon-based approaches). However, like amplicon-based approaches, WMS is subject to bias from DNA extraction methods that can compromise the integrity of sequencing and subsequent findings. The purpose of this study was to evaluate systematic differences among four commercially available DNA extraction kits frequently used for WMS analysis of the microbiome.MethodsOral, vaginal, and rectal swabs were collected in replicates of four by a healthcare provider from five participants and randomized to one of four DNA extraction kits. Two extraction blanks and three replicate mock community samples were also extracted using each extraction kit. WMS was completed with NovaSeq 6000 for all samples. Sequencing and microbial communities were analyzed using nonmetric multidimensional scaling and compositional bias analysis.ResultsExtraction kits differentially biased the percentage of reads attributed to microbial taxa across samples and body sites. The PowerSoil Pro kit performed best in approximating expected proportions of mock communities. While HostZERO was biased against gram-negative bacteria, the kit outperformed other kits in extracting fungal DNA. In clinical samples, HostZERO yielded a smaller fraction of reads assigned to Homo sapiens across sites and had a higher fraction of reads assigned to bacterial taxa compared to other kits. However, HostZERO appears to bias representation of microbial communities and demonstrated the most dispersion by site, particularly for vaginal and rectal samples.ConclusionsSystematic differences exist among four frequently referenced DNA extraction kits when used for WMS analysis of the human microbiome. Consideration of such differences in study design and data interpretation is imperative to safeguard the integrity of microbiome research and reproducibility of results.

Project description:BackgroundVariation of microorganism communities in the rumen of cattle (Bos taurus) is of great interest because of possible links to economically or environmentally important traits, such as feed conversion efficiency or methane emission levels. The resolution of studies investigating this variation may be improved by utilizing untargeted massively parallel sequencing (MPS), that is, sequencing without targeted amplification of genes. The objective of this study was to develop a method which used MPS to generate "rumen metagenome profiles", and to investigate if these profiles were repeatable among samples taken from the same cow. Given faecal samples are much easier to obtain than rumen fluid samples; we also investigated whether rumen metagenome profiles were predictive of faecal metagenome profiles.ResultsRather than focusing on individual organisms within the rumen, our method used MPS data to generate quantitative rumen micro-biome profiles, regardless of taxonomic classifications. The method requires a previously assembled reference metagenome. A number of such reference metagenomes were considered, including two rumen derived metagenomes, a human faecal microflora metagenome and a reference metagenome made up of publically available prokaryote sequences. Sequence reads from each test sample were aligned to these references. The "rumen metagenome profile" was generated from the number of the reads that aligned to each contig in the database. We used this method to test the hypothesis that rumen fluid microbial community profiles vary more between cows than within multiple samples from the same cow. Rumen fluid samples were taken from three cows, at three locations within the rumen. DNA from the samples was sequenced on the Illumina GAIIx. When the reads were aligned to a rumen metagenome reference, the rumen metagenome profiles were repeatable (P?<?0.00001) by cow regardless of location of sampling rumen fluid. The repeatability was estimated at 9%, albeit with a high standard error, reflecting the small number of animals in the study. Finally, we compared rumen microbial profiles to faecal microbial profiles. Our hypothesis, that there would be a stronger correlation between faeces and rumen fluid from the same cow than between faeces and rumen fluid from different cows, was not supported by our data (with much greater significance of rumen versus faeces effect than animal effect in mixed linear model).ConclusionsWe have presented a simple and high throughput method of metagenome profiling to assess the similarity of whole metagenomes, and illustrated its use on two novel datasets. This method utilises widely used freeware. The method should be useful in the exploration and comparison of metagenomes.

Project description:BackgroundMicrobial eukaryotes are found alongside bacteria and archaea in natural microbial systems, including host-associated microbiomes. While microbial eukaryotes are critical to these communities, they are challenging to study with shotgun sequencing techniques and are therefore often excluded.ResultsHere, we present EukDetect, a bioinformatics method to identify eukaryotes in shotgun metagenomic sequencing data. Our approach uses a database of 521,824 universal marker genes from 241 conserved gene families, which we curated from 3713 fungal, protist, non-vertebrate metazoan, and non-streptophyte archaeplastida genomes and transcriptomes. EukDetect has a broad taxonomic coverage of microbial eukaryotes, performs well on low-abundance and closely related species, and is resilient against bacterial contamination in eukaryotic genomes. Using EukDetect, we describe the spatial distribution of eukaryotes along the human gastrointestinal tract, showing that fungi and protists are present in the lumen and mucosa throughout the large intestine. We discover that there is a succession of eukaryotes that colonize the human gut during the first years of life, mirroring patterns of developmental succession observed in gut bacteria. By comparing DNA and RNA sequencing of paired samples from human stool, we find that many eukaryotes continue active transcription after passage through the gut, though some do not, suggesting they are dormant or nonviable. We analyze metagenomic data from the Baltic Sea and find that eukaryotes differ across locations and salinity gradients. Finally, we observe eukaryotes in Arabidopsis leaf samples, many of which are not identifiable from public protein databases.ConclusionsEukDetect provides an automated and reliable way to characterize eukaryotes in shotgun sequencing datasets from diverse microbiomes. We demonstrate that it enables discoveries that would be missed or clouded by false positives with standard shotgun sequence analysis. EukDetect will greatly advance our understanding of how microbial eukaryotes contribute to microbiomes. Video abstract.

Project description:Sexual transmission of the urogenital microbiota may contribute to adverse sexual and reproductive health outcomes. The extent of sexual transmission of the urogenital microbiota is unclear as prior studies largely investigated specific pathogens. We used epidemiologic data and whole metagenome sequencing to characterize urogenital microbiota strain concordance between participants of a sexual network study. Individuals who screened positive for genital Chlamydia trachomatis were enrolled and referred their sexual contacts from the prior 60-180 days. Snowball recruitment of sexual contacts continued for up to four waves. Vaginal swabs and penile urethral swabs were collected for whole metagenome sequencing. We evaluated bacterial strain concordance using inStrain and network analysis. We defined concordance as ≥99.99% average nucleotide identity over ≥50% shared coverage; we defined putative sexual transmission as concordance between sexual contacts with <5 single-nucleotide polymorphisms per megabase. Of 138 participants, 74 (54%) were female; 120 (87%) had genital chlamydia; and 43 (31%) were recruited contacts. We identified 115 strain-concordance events among 54 participants representing 25 bacterial species. Seven events (6%) were between sexual contacts including putative heterosexual transmission of Fannyhessea vaginae, Gardnerella leopoldii, Prevotella amnii, Sneathia sanguinegens, and Sneathia vaginalis (one strain each), and putative sexual transmission of Lactobacillus iners between female contacts. Most concordance events (108, 94%) were between non-contacts, including eight female participants connected through 18 Lactobacillus crispatus and 3 Lactobacillus jensenii concordant strains, and 14 female and 2 male participants densely interconnected through 52 Gardnerella swidsinskii concordance events.IMPORTANCEEpidemiologic evidence consistently indicates bacterial vaginosis (BV) is sexually associated and may be sexually transmitted, though sexual transmission remains subject to debate. This study is not capable of demonstrating BV sexual transmission; however, we do provide strain-level metagenomic evidence that strongly supports heterosexual transmission of BV-associated species. These findings strengthen the evidence base that supports ongoing investigations of concurrent male partner treatment for reducing BV recurrence. Our data suggest that measuring the impact of male partner treatment on F. vaginae, G. leopoldii, P. amnii, S. sanguinegens, and S. vaginalis may provide insight into why a regimen does or does not perform well. We also observed a high degree of strain concordance between non-sexual-contact female participants. We posit that this may reflect limited dispersal capacity of vaginal bacteria coupled with individuals' comembership in regional transmission networks where transmission may occur between parent and child at birth, cohabiting individuals, or sexual contacts.

Dataset Information

Exploration and retrieval of whole-metagenome sequencing samples.

Motivation

Results

Availability and implementation

Supplementary information

Publications

Exploration and retrieval of whole-metagenome sequencing samples.

Similar Datasets

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