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      Crowdsourcing Our National Gut

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          Abstract

          The microbes of the human intestinal tract play a profound role in our health. The complex interactions between our gut microbial communities and the external environment, and the resulting functional consequences, can be difficult to disentangle.

          ABSTRACT

          The microbes of the human intestinal tract play a profound role in our health. The complex interactions between our gut microbial communities and the external environment, and the resulting functional consequences, can be difficult to disentangle. To address this problem, McDonald et al. (mSystems 3:e00031-18, 2018, https://doi.org/10.1128/mSystems.00031-18) present the first set of results from the American Gut Project, a citizen science-based data set currently comprised of over 10,000 gut microbiome samples and associated life history data. By combining this extensive data set with other published studies, the authors uncover novel relationships between gut microbiome structure and function. For example, they found that dietary plant diversity and recent antibiotic use predict both microbial and metabolomic diversity. McDonald et al. also demonstrate that there is high diversity across human gut microbiomes, even compared to the diversity of environmental microbiomes. The results from this study illuminate the potential of the citizen science approach to further our knowledge of host-associated microbial communities.

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          Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample.

          The ongoing revolution in high-throughput sequencing continues to democratize the ability of small groups of investigators to map the microbial component of the biosphere. In particular, the coevolution of new sequencing platforms and new software tools allows data acquisition and analysis on an unprecedented scale. Here we report the next stage in this coevolutionary arms race, using the Illumina GAIIx platform to sequence a diverse array of 25 environmental samples and three known "mock communities" at a depth averaging 3.1 million reads per sample. We demonstrate excellent consistency in taxonomic recovery and recapture diversity patterns that were previously reported on the basis of metaanalysis of many studies from the literature (notably, the saline/nonsaline split in environmental samples and the split between host-associated and free-living communities). We also demonstrate that 2,000 Illumina single-end reads are sufficient to recapture the same relationships among samples that we observe with the full dataset. The results thus open up the possibility of conducting large-scale studies analyzing thousands of samples simultaneously to survey microbial communities at an unprecedented spatial and temporal resolution.
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            Engineering Microbiomes to Improve Plant and Animal Health.

            Animal and plant microbiomes encompass diverse microbial communities that colonize every accessible host tissue. These microbiomes enhance host functions, contributing to host health and fitness. A novel approach to improve animal and plant fitness is to artificially select upon microbiomes, thus engineering evolved microbiomes with specific effects on host fitness. We call this engineering approach host-mediated microbiome selection, because this method selects upon microbial communities indirectly through the host and leverages host traits that evolved to influence microbiomes. In essence, host phenotypes are used as probes to gauge and manipulate those microbiome functions that impact host fitness. To facilitate research on host-mediated microbiome engineering, we explain and compare the principal methods to impose artificial selection on microbiomes; discuss advantages and potential challenges of each method; offer a skeptical appraisal of each method in light of these potential challenges; and outline experimental strategies to optimize microbiome engineering. Finally, we develop a predictive framework for microbiome engineering that organizes research around principles of artificial selection, quantitative genetics, and microbial community-ecology.
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              Quantifying free-roaming domestic cat predation using animal-borne video cameras

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                Author and article information

                Journal
                mSystems
                mSystems
                msys
                msys
                mSystems
                mSystems
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2379-5077
                9 May 2018
                May-Jun 2018
                : 3
                : 3
                : e00060-18
                Affiliations
                [a ]Department of Genetics, Cell Biology, and Development, University of Minnesota, Minneapolis, Minnesota, USA
                [b ]Department of Ecology, Evolution, and Behavior, University of Minnesota, Minneapolis, Minnesota, USA
                Author notes
                Address correspondence to Ran Blekhman, blekhman@ 123456umn.edu .

                Citation Grieneisen LE, Blekhman R. 2018. Crowdsourcing our national gut. mSystems 3:e00060-18. https://doi.org/10.1128/mSystems.00060-18.

                Article
                mSystems00060-18
                10.1128/mSystems.00060-18
                5954205
                398037a9-e72a-4498-adf1-048c20da430e
                Copyright © 2018 Grieneisen and Blekhman.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 13, Pages: 3, Words: 1830
                Categories
                Commentary
                Host-Microbe Biology
                Custom metadata
                May/June 2018

                american gut project,citizen science,gut microbiome,metabolome

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