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      Deciphering functional redundancy in the human microbiome

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          Abstract

          Although the taxonomic composition of the human microbiome varies tremendously across individuals, its gene composition or functional capacity is highly conserved — implying an ecological property known as functional redundancy. Such functional redundancy has been hypothesized to underlie the stability and resilience of the human microbiome, but this hypothesis has never been quantitatively tested. The origin of functional redundancy is still elusive. Here, we investigate the basis for functional redundancy in the human microbiome by analyzing its genomic content network — a bipartite graph that links microbes to the genes in their genomes. We find that this network exhibits several topological features that favor high functional redundancy. Furthermore, we develop a simple genome evolution model to generate genomic content network, finding that moderate selection pressure and high horizontal gene transfer rate are necessary to generate genomic content networks with key topological features that favor high functional redundancy. Finally, we analyze data from two published studies of fecal microbiota transplantation (FMT), finding that high functional redundancy of the recipient’s pre-FMT microbiota raises barriers to donor microbiota engraftment. This work elucidates the potential ecological and evolutionary processes that create and maintain functional redundancy in the human microbiome and contribute to its resilience.

          Abstract

          Here, the authors develop a genome evolution model to investigate the origin of functional redundancy in the human microbiome by analyzing its genomic content network and illustrate potential ecological and evolutionary processes that may contribute to its resilience.

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          Most cited references64

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          Structure, Function and Diversity of the Healthy Human Microbiome

          Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin, and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics, and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analyzed the largest cohort and set of distinct, clinically relevant body habitats to date. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families, and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology, and translational applications of the human microbiome.
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            A human gut microbial gene catalogue established by metagenomic sequencing.

            To understand the impact of gut microbes on human health and well-being it is crucial to assess their genetic potential. Here we describe the Illumina-based metagenomic sequencing, assembly and characterization of 3.3 million non-redundant microbial genes, derived from 576.7 gigabases of sequence, from faecal samples of 124 European individuals. The gene set, approximately 150 times larger than the human gene complement, contains an overwhelming majority of the prevalent (more frequent) microbial genes of the cohort and probably includes a large proportion of the prevalent human intestinal microbial genes. The genes are largely shared among individuals of the cohort. Over 99% of the genes are bacterial, indicating that the entire cohort harbours between 1,000 and 1,150 prevalent bacterial species and each individual at least 160 such species, which are also largely shared. We define and describe the minimal gut metagenome and the minimal gut bacterial genome in terms of functions present in all individuals and most bacteria, respectively.
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              A core gut microbiome in obese and lean twins

              The human distal gut harbors a vast ensemble of microbes (the microbiota) that provide us with important metabolic capabilities, including the ability to extract energy from otherwise indigestible dietary polysaccharides1–6. Studies of a small number of unrelated, healthy adults have revealed substantial diversity in their gut communities, as measured by sequencing 16S rRNA genes6–8, yet how this diversity relates to function and to the rest of the genes in the collective genomes of the microbiota (the gut microbiome) remains obscure. Studies of lean and obese mice suggest that the gut microbiota affects energy balance by influencing the efficiency of calorie harvest from the diet, and how this harvested energy is utilized and stored3–5. To address the question of how host genotype, environmental exposures, and host adiposity influence the gut microbiome, we have characterized the fecal microbial communities of adult female monozygotic and dizygotic twin pairs concordant for leanness or obesity, and their mothers. Analysis of 154 individuals yielded 9,920 near full-length and 1,937,461 partial bacterial 16S rRNA sequences, plus 2.14 gigabases from their microbiomes. The results reveal that the human gut microbiome is shared among family members, but that each person’s gut microbial community varies in the specific bacterial lineages present, with a comparable degree of co-variation between adult monozygotic and dizygotic twin pairs. However, there was a wide array of shared microbial genes among sampled individuals, comprising an extensive, identifiable ‘core microbiome’ at the gene, rather than at the organismal lineage level. Obesity is associated with phylum-level changes in the microbiota, reduced bacterial diversity, and altered representation of bacterial genes and metabolic pathways. These results demonstrate that a diversity of organismal assemblages can nonetheless yield a core microbiome at a functional level, and that deviations from this core are associated with different physiologic states (obese versus lean).
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                Author and article information

                Contributors
                yyl@channing.harvard.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                4 December 2020
                4 December 2020
                2020
                : 11
                : 6217
                Affiliations
                [1 ]GRID grid.62560.37, ISNI 0000 0004 0378 8294, Channing Division of Network Medicine, , Brigham and Women’s Hospital and Harvard Medical School, ; Boston, MA 02115 USA
                [2 ]GRID grid.221309.b, ISNI 0000 0004 1764 5980, Department of Physics, , Hong Kong Baptist University, ; Hong Kong SAR, China
                [3 ]GRID grid.221309.b, ISNI 0000 0004 1764 5980, Institute of Computational and Theoretical Studies, , Hong Kong Baptist University, ; Hong Kong SAR, China
                [4 ]GRID grid.221309.b, ISNI 0000 0004 1764 5980, State Key Laboratory of Environmental and Biological Analysis, , Hong Kong Baptist University, ; Hong Kong SAR, China
                [5 ]GRID grid.430387.b, ISNI 0000 0004 1936 8796, Department of Physics and Astronomy, , Rutgers University, ; Piscataway, NJ 08854 USA
                [6 ]GRID grid.168010.e, ISNI 0000000419368956, Department of Bioengineering, , Stanford University, ; Stanford, CA 94305 USA
                [7 ]GRID grid.9619.7, ISNI 0000 0004 1937 0538, Faculty of Agriculture, Food and Environment, Department of Plant Pathology and Microbiology, , The Hebrew University of Jerusalem, ; Jerusalem, Israel
                [8 ]GRID grid.62560.37, ISNI 0000 0004 0378 8294, Division of Infectious Diseases, , Brigham and Women’s Hospital and Harvard Medical School, ; Boston, MA 02115 USA
                [9 ]GRID grid.413575.1, ISNI 0000 0001 2167 1581, Howard Hughes Medical Institute, ; Boston, MA 02115 USA
                [10 ]GRID grid.249880.f, ISNI 0000 0004 0374 0039, The Jackson Laboratory for Genomic Medicine, ; Farmington, CT 06117 USA
                Author information
                http://orcid.org/0000-0001-7670-3544
                http://orcid.org/0000-0002-7018-1674
                http://orcid.org/0000-0001-8476-8030
                http://orcid.org/0000-0003-1843-7000
                http://orcid.org/0000-0002-2997-4592
                http://orcid.org/0000-0003-2728-4907
                Article
                19940
                10.1038/s41467-020-19940-1
                7719190
                33277504
                b2112294-01b5-41b6-86ee-fb183e106d3c
                © The Author(s) 2020

                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
                : 19 December 2019
                : 4 November 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000052, U.S. Department of Health & Human Services | NIH | NIH Office of the Director (OD);
                Award ID: UH3OD023268
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000060, U.S. Department of Health & Human Services | NIH | National Institute of Allergy and Infectious Diseases (NIAID);
                Award ID: U19AI095219
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000050, U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI);
                Award ID: U01HL089856
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                network topology,metagenomics,microbiome
                Uncategorized
                network topology, metagenomics, microbiome

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