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  • 1
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    SeaBase : a multispecies transcriptomic resource and platform for gene network inference (2014)
    Details
    Publication Date: 2022-05-25
    Description: Author Posting. © The Author(s), 2014. This is the author's version of the work. It is posted here by permission of Oxford University Press for personal use, not for redistribution. The definitive version was published in Integrative and Comparative Biology 54 (2014): 250-263, doi: 10.1093/icb/icu065.
    Description: Marine and aquatic animals are extraordinarily useful as models for identifying mechanisms of development and evolution, regeneration, resistance to cancer, longevity and symbiosis, among many other areas of research. This is due to the great diversity of these organisms and their wide-ranging capabilities. Genomics tools are essential for taking advantage of these “free lessons” of nature. However, genomics and transcriptomics are challenging in emerging model systems. Here, we present SeaBase, a tool for helping to meet these needs. Specifically, SeaBase provides a platform for sharing and searching transcriptome data. More importantly, SeaBase will support a growing number of tools for inferring gene network mechanisms. The first dataset available on SeaBase is a developmental transcriptome profile of the sea anemone Nematostella vectensis (Anthozoa, Cnidaria). Additional datasets are currently being prepared and we are aiming to expand SeaBase to include user-supplied data for any number of marine and aquatic organisms, thereby supporting many potentially new models for gene network studies.
    Description: 2015-06-06
    Repository Name: Woods Hole Open Access Server
    Type: Preprint
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  • 2
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    The gut microbiota of rural Papua New Guineans : composition, diversity patterns, and ecological processes (2015)
    Cell Press
    Details
    Publication Date: 2022-05-25
    Description: © The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Cell Reports 11 (2015): 1-12, doi:10.1016/j.celrep.2015.03.049.
    Description: Although recent research revealed an impact of westernization on diversity and composition of the human gut microbiota, the exact consequences on metacommunity characteristics are insufficiently understood, and the underlying ecological mechanisms have not been elucidated. Here, we have compared the fecal microbiota of adults from two non-industrialized regions in Papua New Guinea (PNG) with that of United States (US) residents. Papua New Guineans harbor communities with greater bacterial diversity, lower inter-individual variation, vastly different abundance profiles, and bacterial lineages undetectable in US residents. A quantification of the ecological processes that govern community assembly identified bacterial dispersal as the dominant process that shapes the microbiome in PNG but not in the US. These findings suggest that the microbiome alterations detected in industrialized societies might arise from modern lifestyle factors limiting bacterial dispersal, which has implications for human health and the development of strategies aimed to redress the impact of westernization.
    Description: This study was partly funded by BioGaia AB. BioGaia had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. A portion of this research is part of the Microbiomes in Transition Initiative at Pacific Northwest National Laboratory (PNNL). This research was conducted under the Laboratory Directed Research and Development Program at PNNL, a multi-program national laboratory operated by Battelle for the US Department of Energy under contract DE-AC05-76RL01830.
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 3
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    Sewage reflects the microbiomes of human populations (2015)
    American Society for Microbiology
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    Publication Date: 2022-05-25
    Description: © The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in mBio 6 (2015): e02574-14, doi:10.1128/mBio.02574-14.
    Description: Molecular characterizations of the gut microbiome from individual human stool samples have identified community patterns that correlate with age, disease, diet, and other human characteristics, but resources for marker gene studies that consider microbiome trends among human populations scale with the number of individuals sampled from each population. As an alternative strategy for sampling populations, we examined whether sewage accurately reflects the microbial community of a mixture of stool samples. We used oligotyping of high-throughput 16S rRNA gene sequence data to compare the bacterial distribution in a stool data set to a sewage influent data set from 71 U.S. cities. On average, only 15% of sewage sample sequence reads were attributed to human fecal origin, but sewage recaptured most (97%) human fecal oligotypes. The most common oligotypes in stool matched the most common and abundant in sewage. After informatically separating sequences of human fecal origin, sewage samples exhibited ~3× greater diversity than stool samples. Comparisons among municipal sewage communities revealed the ubiquitous and abundant occurrence of 27 human fecal oligotypes, representing an apparent core set of organisms in U.S. populations. The fecal community variability among U.S. populations was significantly lower than among individuals. It clustered into three primary community structures distinguished by oligotypes from either: Bacteroidaceae, Prevotellaceae, or Lachnospiraceae/Ruminococcaceae. These distribution patterns reflected human population variation and predicted whether samples represented lean or obese populations with 81 to 89% accuracy. Our findings demonstrate that sewage represents the fecal microbial community of human populations and captures population-level traits of the human microbiome.
    Description: Funding for this work was provided by the NIH grant R01AI091829-01A1 to S.L.M. and M.L.S.
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 4
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    Tracking microbial colonization in fecal microbiota transplantation experiments via genome-resolved metagenomics (2017)
    BioMed Central
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    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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  • 5
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    DRISEE overestimates errors in metagenomic sequencing data (2013)
    Oxford University Press
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    Publication Date: 2022-05-25
    Description: © The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Briefings in Bioinformatics 15 (2014): 783-787, doi:10.1093/bib/bbt010.
    Description: The extremely high error rates reported by Keegan et al. in ‘A platform-independent method for detecting errors in metagenomic sequencing data: DRISEE’ (PLoS Comput Biol 2012;8:e1002541) for many next-generation sequencing datasets prompted us to re-examine their results. Our analysis reveals that the presence of conserved artificial sequences, e.g. Illumina adapters, and other naturally occurring sequence motifs accounts for most of the reported errors. We conclude that DRISEE reports inflated levels of sequencing error, particularly for Illumina data. Tools offered for evaluating large datasets need scrupulous review before they are implemented.
    Description: National Institutes of Health [1UH2DK083993 to M.L.S.]; National Science Foundation [BDI- 096026 to S.M.H.].
    Keywords: Next-generation sequencing ; Sequencing error ; Adapter ligation ; PCR ; Quality score
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 6
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    Oligotyping : differentiating between closely related microbial taxa using 16S rRNA gene data (2014)
    John Wiley & Sons
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    Publication Date: 2022-05-25
    Description: © The Authors. Methods in Ecology and Evolution © 2013 British Ecological Society.. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Methods in Ecology and Evolution 4 (2013): 1111–1119, doi:10.1111/2041-210X.12114.
    Description: Bacteria comprise the most diverse domain of life on Earth, where they occupy nearly every possible ecological niche and play key roles in biological and chemical processes. Studying the composition and ecology of bacterial ecosystems and understanding their function are of prime importance. High-throughput sequencing technologies enable nearly comprehensive descriptions of bacterial diversity through 16S ribosomal RNA gene amplicons. Analyses of these communities generally rely upon taxonomic assignments through reference data bases or clustering approaches using de facto sequence similarity thresholds to identify operational taxonomic units. However, these methods often fail to resolve ecologically meaningful differences between closely related organisms in complex microbial data sets. In this paper, we describe oligotyping, a novel supervised computational method that allows researchers to investigate the diversity of closely related but distinct bacterial organisms in final operational taxonomic units identified in environmental data sets through 16S ribosomal RNA gene data by the canonical approaches. Our analysis of two data sets from two different environments demonstrates the capacity of oligotyping at discriminating distinct microbial populations of ecological importance. Oligotyping can resolve the distribution of closely related organisms across environments and unveil previously overlooked ecological patterns for microbial communities. The URL http://oligotyping.org offers an open-source software pipeline for oligotyping.
    Description: This work was supported by the National Institutes of Health [1UH2DK083993 to M.L.S.] and the Alfred P. Sloan Foundation.
    Keywords: 16S ; Bacterial taxonomy ; Microbial diversity ; OTU clustering ; Shannon entropy
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 7
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    Minimum entropy decomposition : unsupervised oligotyping for sensitive partitioning of high-throughput marker gene sequences (2015)
    Nature Publishing Group
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    Publication Date: 2022-05-25
    Description: © The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in ISME Journal 9 (2015): 968–979, doi:10.1038/ismej.2014.195.
    Description: Molecular microbial ecology investigations often employ large marker gene datasets, for example, ribosomal RNAs, to represent the occurrence of single-cell genomes in microbial communities. Massively parallel DNA sequencing technologies enable extensive surveys of marker gene libraries that sometimes include nearly identical sequences. Computational approaches that rely on pairwise sequence alignments for similarity assessment and de novo clustering with de facto similarity thresholds to partition high-throughput sequencing datasets constrain fine-scale resolution descriptions of microbial communities. Minimum Entropy Decomposition (MED) provides a computationally efficient means to partition marker gene datasets into ‘MED nodes’, which represent homogeneous operational taxonomic units. By employing Shannon entropy, MED uses only the information-rich nucleotide positions across reads and iteratively partitions large datasets while omitting stochastic variation. When applied to analyses of microbiomes from two deep-sea cryptic sponges Hexadella dedritifera and Hexadella cf. dedritifera, MED resolved a key Gammaproteobacteria cluster into multiple MED nodes that are specific to different sponges, and revealed that these closely related sympatric sponge species maintain distinct microbial communities. MED analysis of a previously published human oral microbiome dataset also revealed that taxa separated by less than 1% sequence variation distributed to distinct niches in the oral cavity. The information theory-guided decomposition process behind the MED algorithm enables sensitive discrimination of closely related organisms in marker gene amplicon datasets without relying on extensive computational heuristics and user supervision.
    Description: AME was supported by a G. Unger Vetlesen Foundation grant to the Marine Biological Laboratory and the Alfred P Sloan Foundation.
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 8
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    A few Pseudomonas oligotypes dominate in the meat and dairy processing environment (2017)
    Frontiers Media
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    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 Frontiers in Microbiology 8 (2017): 264, doi:10.3389/fmicb.2017.00264.
    Description: The occurrence of bacteria in the food processing environments plays a key role in food contamination and development of spoilage. Species of the genus Pseudomonas are recognized as major food spoilers and the capability to actually determine spoilage can be species- as well as strain-dependent. In order to improve the taxonomic resolution of 16S rRNA gene amplicons, in this study we used oligotyping to investigate the diversity of Pseudomonas populations in meat and dairy processing environments. Sequences of the V1–V3 regions from previous studies were used, including environmental swabs and food samples from both meat and dairy processing plants. We showed that the most frequently found oligotypes belonged to Pseudomonas fragi and P. fluorescens, that the most abundant oligotypes co-occurred, and were shared between the meat and dairy datasets. All the oligotypes occurring in foods were also identified in the environmental samples of the corresponding plants, highlighting the important role of the environment as a source of strains for food contamination. Oligotypes of the same species showed different levels depending on food processing and type of sample, suggesting that different strains of the same species can have different adaptation efficiency, leading to resilient bacterial associations.
    Keywords: Pseudomonas fragi ; Food contamination ; Food processing environment ; Oligotyping ; 16S rRNA gene sequencing
    Repository Name: Woods Hole Open Access Server
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  • 9
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    Anvi’o : an advanced analysis and visualization platform for ‘omics data (2015)
    PeerJ
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    Publication Date: 2022-05-25
    Description: © The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in PeerJ 3 (2015): e1319, doi:10.7717/peerj.1319.
    Description: Advances in high-throughput sequencing and ‘omics technologies are revolutionizing studies of naturally occurring microbial communities. Comprehensive investigations of microbial lifestyles require the ability to interactively organize and visualize genetic information and to incorporate subtle differences that enable greater resolution of complex data. Here we introduce anvi’o, an advanced analysis and visualization platform that offers automated and human-guided characterization of microbial genomes in metagenomic assemblies, with interactive interfaces that can link ‘omics data from multiple sources into a single, intuitive display. Its extensible visualization approach distills multiple dimensions of information about each contig, offering a dynamic and unified work environment for data exploration, manipulation, and reporting. Using anvi’o, we re-analyzed publicly available datasets and explored temporal genomic changes within naturally occurring microbial populations through de novo characterization of single nucleotide variations, and linked cultivar and single-cell genomes with metagenomic and metatranscriptomic data. Anvi’o is an open-source platform that empowers researchers without extensive bioinformatics skills to perform and communicate in-depth analyses on large ‘omics datasets.
    Description: AME was supported by the G. Unger Vetlesen Foundation. The project was supported by the Frank R. Lillie Research Innovation Award given by the University of Chicago and the Marine Biological Laboratory.
    Keywords: Metagenomics ; Assembly ; Genome binning ; Visualization ; SNP profiling ; Metatranscriptomics
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 10
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    Extensive modulation of the fecal metagenome in children With Crohn’s disease during exclusive enteral nutrition (2016)
    Nature Publishing Group
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    Publication Date: 2022-05-25
    Description: © The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in American Journal of Gastroenterology 110 (2015): 1718–1729, doi:10.1038/ajg.2015.357.
    Description: Exploring associations between the gut microbiota and colonic inflammation and assessing sequential changes during exclusive enteral nutrition (EEN) may offer clues into the microbial origins of Crohn’s disease (CD). Fecal samples (n=117) were collected from 23 CD and 21 healthy children. From CD children fecal samples were collected before, during EEN, and when patients returned to their habitual diets. Microbiota composition and functional capacity were characterized using sequencing of the 16S rRNA gene and shotgun metagenomics. Microbial diversity was lower in CD than controls before EEN (P=0.006); differences were observed in 36 genera, 141 operational taxonomic units (OTUs), and 44 oligotypes. During EEN, the microbial diversity of CD children further decreased, and the community structure became even more dissimilar than that of controls. Every 10 days on EEN, 0.6 genus diversity equivalents were lost; 34 genera decreased and one increased during EEN. Fecal calprotectin correlated with 35 OTUs, 14 of which accounted for 78% of its variation. OTUs that correlated positively or negatively with calprotectin decreased during EEN. The microbiota of CD patients had a broader functional capacity than healthy controls, but diversity decreased with EEN. Genes involved in membrane transport, sulfur reduction, and nutrient biosynthesis differed between patients and controls. The abundance of genes involved in biotin (P=0.005) and thiamine biosynthesis decreased (P=0.017), whereas those involved in spermidine/putrescine biosynthesis (P=0.031), or the shikimate pathway (P=0.058), increased during EEN. Disease improvement following treatment with EEN is associated with extensive modulation of the gut microbiome.
    Description: The IBD team at Royal Hospital for Children, Glasgow, is supported by the Catherine McEwan Foundation and the Yorkhill IBD fund.
    Repository Name: Woods Hole Open Access Server
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