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  • 1
    Publication Date: 2022-05-25
    Description: © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Microbiome 5 (2017): 50, doi:10.1186/s40168-017-0270-x.
    Description: Fecal microbiota transplantation (FMT) is an effective treatment for recurrent Clostridium difficile infection and shows promise for treating other medical conditions associated with intestinal dysbioses. However, we lack a sufficient understanding of which microbial populations successfully colonize the recipient gut, and the widely used approaches to study the microbial ecology of FMT experiments fail to provide enough resolution to identify populations that are likely responsible for FMT-derived benefits. We used shotgun metagenomics together with assembly and binning strategies to reconstruct metagenome-assembled genomes (MAGs) from fecal samples of a single FMT donor. We then used metagenomic mapping to track the occurrence and distribution patterns of donor MAGs in two FMT recipients. Our analyses revealed that 22% of the 92 highly complete bacterial MAGs that we identified from the donor successfully colonized and remained abundant in two recipients for at least 8 weeks. Most MAGs with a high colonization rate belonged to the order Bacteroidales. The vast majority of those that lacked evidence of colonization belonged to the order Clostridiales, and colonization success was negatively correlated with the number of genes related to sporulation. Our analysis of 151 publicly available gut metagenomes showed that the donor MAGs that colonized both recipients were prevalent, and the ones that colonized neither were rare across the participants of the Human Microbiome Project. Although our dataset showed a link between taxonomy and the colonization ability of a given MAG, we also identified MAGs that belong to the same taxon with different colonization properties, highlighting the importance of an appropriate level of resolution to explore the functional basis of colonization and to identify targets for cultivation, hypothesis generation, and testing in model systems. The analytical strategy adopted in our study can provide genomic insights into bacterial populations that may be critical to the efficacy of FMT due to their success in gut colonization and metabolic properties, and guide cultivation efforts to investigate mechanistic underpinnings of this procedure beyond associations.
    Description: AME was supported by the Frank R. Lillie Research Innovation Award and startup funds from the University of Chicago. This project was supported by the Mutchnik Family Charitable Fund and the University of Chicago Gastro-Intestinal Research Foundation.
    Keywords: Fecal microbiota transplantation ; Colonization ; Metagenomics ; Metagenome-assembled genomes
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    Publication Date: 2022-05-26
    Description: © The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in BMC Bioinformatics 15 (2014): 41, doi:10.1186/1471-2105-15-41.
    Description: The advent of next-generation DNA sequencing platforms has revolutionized molecular microbial ecology by making the detailed analysis of complex communities over time and space a tractable research pursuit for small research groups. However, the ability to generate 105–108 reads with relative ease brings with it many downstream complications. Beyond the computational resources and skills needed to process and analyze data, it is difficult to compare datasets in an intuitive and interactive manner that leads to hypothesis generation and testing. We developed the free web service VAMPS (Visualization and Analysis of Microbial Population Structures, http://vamps.mbl.edu webcite) to address these challenges and to facilitate research by individuals or collaborating groups working on projects with large-scale sequencing data. Users can upload marker gene sequences and associated metadata; reads are quality filtered and assigned to both taxonomic structures and to taxonomy-independent clusters. A simple point-and-click interface allows users to select for analysis any combination of their own or their collaborators’ private data and data from public projects, filter these by their choice of taxonomic and/or abundance criteria, and then explore these data using a wide range of analytic methods and visualizations. Each result is extensively hyperlinked to other analysis and visualization options, promoting data exploration and leading to a greater understanding of data relationships. VAMPS allows researchers using marker gene sequence data to analyze the diversity of microbial communities and the relationships between communities, to explore these analyses in an intuitive visual context, and to download data, results, and images for publication. VAMPS obviates the need for individual research groups to make the considerable investment in computational infrastructure and bioinformatic support otherwise necessary to process, analyze, and interpret massive amounts of next-generation sequence data. Any web-capable device can be used to upload, process, explore, and extract data and results from VAMPS. VAMPS encourages researchers to share sequence and metadata, and fosters collaboration between researchers of disparate biomes who recognize common patterns in shared data.
    Description: Funding provided by the National Science Foundation [grant NSF/BDI 0960626 to SMH] and the Sloan Foundation through a collaborative project with the Microbiology of the Built Environment program.
    Keywords: Microbiome ; Microbial ecology ; Microbial diversity ; Data visualization ; Website ; Bacteria ; SSU rRNA ; Next-generation sequencing
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 3
    Publication Date: 2022-05-26
    Description: © The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Microbiome 4 (2016): 16, doi:10.1186/s40168-016-0161-6.
    Description: The epidemiology of bacterial vaginosis (BV) suggests it is sexually transmissible, yet no transmissible agent has been identified. It is probable that BV-associated bacterial communities are transferred from male to female partners during intercourse; however, the microbiota of sexual partners has not been well-studied. Pyrosequencing analysis of PCR-amplified 16S rDNA was used to examine BV-associated bacteria in monogamous couples with and without BV using vaginal, male urethral, and penile skin specimens. The penile skin and urethral microbiota of male partners of women with BV was significantly more similar to the vaginal microbiota of their female partner compared to the vaginal microbiota of non-partner women with BV. This was not the case for male partners of women with normal vaginal microbiota. Specific BV-associated species were concordant in women with BV and their male partners. In monogamous heterosexual couples in which the woman has BV, the significantly higher similarity between the vaginal microbiota and the penile skin and urethral microbiota of the male partner, supports the hypothesis that sexual exchange of BV-associated bacterial taxa is common.
    Description: This work was supported by National Institute of Health Grant R01 AI079071-01A1.
    Keywords: Bacterial vaginosis ; Microbiome ; Sexual transmission ; Penile skin ; Urethra ; Vagina
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 4
    Publication Date: 2022-05-26
    Description: © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Genome Biology 18 (2017): 181, doi:10.1186/s13059-017-1309-9.
    Description: We introduce DESMAN for De novo Extraction of Strains from Metagenomes. Large multi-sample metagenomes are being generated but strain variation results in fragmentary co-assemblies. Current algorithms can bin contigs into metagenome-assembled genomes but are unable to resolve strain-level variation. DESMAN identifies variants in core genes and uses co-occurrence across samples to link variants into haplotypes and abundance profiles. These are then searched for against non-core genes to determine the accessory genome of each strain. We validated DESMAN on a complex 50-species 210-genome 96-sample synthetic mock data set and then applied it to the Tara Oceans microbiome.
    Description: CQ is funded through a Medical Research Council fellowship (MR/M50161X/1) as part of the Cloud Infrastructure for Microbial Bioinformatics (CLIMB) consortium (MR/L015080/1). GC was supported by a European Research Council Starting Grant (3C-BIOTECH 261330). AME was supported by a Frank R. Lillie Research Innovation Award.
    Keywords: Metagenomes ; Strain ; Niche
    Repository Name: Woods Hole Open Access Server
    Type: Article
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