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      New insights from uncultivated genomes of the global human gut microbiome

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          Abstract

          The genome sequences of many species of the human gut microbiome remain unknown, largely owing to challenges in cultivating microorganisms under laboratory conditions. Here we address this problem by reconstructing 60,664 draft prokaryotic genomes from 3,810 faecal metagenomes, from geographically and phenotypically diverse humans. These genomes provide reference points for 2,058 newly identified species-level operational taxonomic units (OTUs), which represents a 50% increase over the previously known phylogenetic diversity of sequenced gut bacteria. On average, the newly identified OTUs comprise 33% of richness and 28% of species abundance per individual, and are enriched in humans from rural populations. A meta-analysis of clinical gut-microbiome studies pinpointed numerous disease associations for the newly identified OTUs, which have the potential to improve predictive models. Finally, our analysis revealed that uncultured gut species have undergone genome reduction that has resulted in the loss of certain biosynthetic pathways, which may offer clues for improving cultivation strategies in the future.

          Abstract

          Draft prokaryotic genomes from faecal metagenomes of diverse human populations enrich our understanding of the human gut microbiome by identifying over two thousand new species-level taxa that have numerous disease associations.

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          Community structure and metabolism through reconstruction of microbial genomes from the environment.

          Microbial communities are vital in the functioning of all ecosystems; however, most microorganisms are uncultivated, and their roles in natural systems are unclear. Here, using random shotgun sequencing of DNA from a natural acidophilic biofilm, we report reconstruction of near-complete genomes of Leptospirillum group II and Ferroplasma type II, and partial recovery of three other genomes. This was possible because the biofilm was dominated by a small number of species populations and the frequency of genomic rearrangements and gene insertions or deletions was relatively low. Because each sequence read came from a different individual, we could determine that single-nucleotide polymorphisms are the predominant form of heterogeneity at the strain level. The Leptospirillum group II genome had remarkably few nucleotide polymorphisms, despite the existence of low-abundance variants. The Ferroplasma type II genome seems to be a composite from three ancestral strains that have undergone homologous recombination to form a large population of mosaic genomes. Analysis of the gene complement for each organism revealed the pathways for carbon and nitrogen fixation and energy generation, and provided insights into survival strategies in an extreme environment.
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            The Black Queen Hypothesis: Evolution of Dependencies through Adaptive Gene Loss

            ABSTRACT Reductive genomic evolution, driven by genetic drift, is common in endosymbiotic bacteria. Genome reduction is less common in free-living organisms, but it has occurred in the numerically dominant open-ocean bacterioplankton Prochlorococcus and “Candidatus Pelagibacter,” and in these cases the reduction appears to be driven by natural selection rather than drift. Gene loss in free-living organisms may leave them dependent on cooccurring microbes for lost metabolic functions. We present the Black Queen Hypothesis (BQH), a novel theory of reductive evolution that explains how selection leads to such dependencies; its name refers to the queen of spades in the game Hearts, where the usual strategy is to avoid taking this card. Gene loss can provide a selective advantage by conserving an organism’s limiting resources, provided the gene’s function is dispensable. Many vital genetic functions are leaky, thereby unavoidably producing public goods that are available to the entire community. Such leaky functions are thus dispensable for individuals, provided they are not lost entirely from the community. The BQH predicts that the loss of a costly, leaky function is selectively favored at the individual level and will proceed until the production of public goods is just sufficient to support the equilibrium community; at that point, the benefit of any further loss would be offset by the cost. Evolution in accordance with the BQH thus generates “beneficiaries” of reduced genomic content that are dependent on leaky “helpers,” and it may explain the observed nonuniversality of prototrophy, stress resistance, and other cellular functions in the microbial world.
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              Functional implications of microbial and viral gut metagenome changes in early stage L-DOPA-naïve Parkinson’s disease patients

              Background Parkinson’s disease (PD) presently is conceptualized as a protein aggregation disease in which pathology involves both the enteric and the central nervous system, possibly spreading from one to another via the vagus nerves. As gastrointestinal dysfunction often precedes or parallels motor symptoms, the enteric system with its vast diversity of microorganisms may be involved in PD pathogenesis. Alterations in the enteric microbial taxonomic level of L-DOPA-naïve PD patients might also serve as a biomarker. Methods We performed metagenomic shotgun analyses and compared the fecal microbiomes of 31 early stage, L-DOPA-naïve PD patients to 28 age-matched controls. Results We found increased Verrucomicrobiaceae (Akkermansia muciniphila) and unclassified Firmicutes, whereas Prevotellaceae (Prevotella copri) and Erysipelotrichaceae (Eubacterium biforme) were markedly lowered in PD samples. The observed differences could reliably separate PD from control with a ROC-AUC of 0.84. Functional analyses of the metagenomes revealed differences in microbiota metabolism in PD involving the ẞ-glucuronate and tryptophan metabolism. While the abundances of prophages and plasmids did not differ between PD and controls, total virus abundance was decreased in PD participants. Based on our analyses, the intake of either a MAO inhibitor, amantadine, or a dopamine agonist (which in summary relates to 90% of PD patients) had no overall influence on taxa abundance or microbial functions. Conclusions Our data revealed differences of colonic microbiota and of microbiota metabolism between PD patients and controls at an unprecedented detail not achievable through 16S sequencing. The findings point to a yet unappreciated aspect of PD, possibly involving the intestinal barrier function and immune function in PD patients. The influence of the parkinsonian medication should be further investigated in the future in larger cohorts. Electronic supplementary material The online version of this article (doi:10.1186/s13073-017-0428-y) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                snayfach@lbl.gov
                nckyrpides@lbl.gov
                Journal
                Nature
                Nature
                Nature
                Nature Publishing Group UK (London )
                0028-0836
                1476-4687
                13 March 2019
                13 March 2019
                2019
                : 568
                : 7753
                : 505-510
                Affiliations
                [1 ]ISNI 0000 0004 0449 479X, GRID grid.451309.a, United States Department of Energy Joint Genome Institute, ; Walnut Creek, CA USA
                [2 ]ISNI 0000 0001 2231 4551, GRID grid.184769.5, Environmental Genomics and Systems Biology Division, , Lawrence Berkeley National Laboratory, ; Berkeley, CA USA
                [3 ]ISNI 0000 0004 0572 7110, GRID grid.249878.8, Gladstone Institutes, ; San Francisco, CA USA
                [4 ]Chan-Zuckerberg Biohub, San Francisco, CA USA
                [5 ]ISNI 0000 0001 2297 6811, GRID grid.266102.1, Institute for Human Genetics, , University of California San Francisco, ; San Francisco, CA USA
                [6 ]ISNI 0000 0001 2297 6811, GRID grid.266102.1, Institute for Computational Health Sciences, , University of California San Francisco, ; San Francisco, CA USA
                [7 ]ISNI 0000 0001 2297 6811, GRID grid.266102.1, Quantitative Biology Institute, , University of California San Francisco, ; San Francisco, CA USA
                [8 ]ISNI 0000 0001 2297 6811, GRID grid.266102.1, Department of Epidemiology and Biostatistics, , University of California San Francisco, ; San Francisco, CA USA
                Article
                1058
                10.1038/s41586-019-1058-x
                6784871
                30867587
                3d44a89a-bb87-4d09-9413-e8fffc427a85
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 8 August 2018
                : 6 March 2019
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                © The Author(s), under exclusive licence to Springer Nature Limited 2019

                Uncategorized
                environmental microbiology,genome informatics
                Uncategorized
                environmental microbiology, genome informatics

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