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      Genomic variation and strain-specific functional adaptation in the human gut microbiome during early life

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          Summary

          The human gut microbiome matures toward the adult composition during the first years of life and is implicated in early immune development. Here, we investigate the effects of microbial genomic diversity on gut microbiome development using integrated early childhood datasets collected in the DIABIMMUNE study in Finland, Estonia and Russian Karelia. We show that gut microbial diversity is associated with household location and linear growth of children. Single nucleotide polymorphism (SNP)- and metagenomic assembly-based strain tracking revealed large and highly dynamic microbial pangenomes, especially in the genus Bacteroides, in which we identified evidence of variability deriving from Bacteroides-targeting bacteriophages. Our analyses revealed functional consequences of strain diversity; only 10% of Finnish infants harbored Bifidobacterium longum subsp. infantis, a subspecies specialized in human milk metabolism, whereas Russian infants commonly maintained a probiotic Bifidobacterium bifidum strain in infancy. Groups of bacteria contributing to diverse, characterized metabolic pathways converged to highly subject-specific configurations over the first two years of life. This longitudinal study extends the current view of early gut microbial community assembly based on strain-level genomic variation.

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          Most cited references29

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            The microbiome and innate immunity.

            The intestinal microbiome is a signalling hub that integrates environmental inputs, such as diet, with genetic and immune signals to affect the host's metabolism, immunity and response to infection. The haematopoietic and non-haematopoietic cells of the innate immune system are located strategically at the host-microbiome interface. These cells have the ability to sense microorganisms or their metabolic products and to translate the signals into host physiological responses and the regulation of microbial ecology. Aberrations in the communication between the innate immune system and the gut microbiota might contribute to complex diseases.
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              Is Open Access

              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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                Author and article information

                Journal
                101674869
                44774
                Nat Microbiol
                Nat Microbiol
                Nature microbiology
                2058-5276
                18 December 2018
                17 December 2018
                March 2019
                17 June 2019
                : 4
                : 3
                : 470-479
                Affiliations
                [1 ]Broad Institute of MIT and Harvard, Cambridge MA, U.S.A.
                [2 ]Department of Computer Science, Aalto University, 02150 Espoo, Finland
                [3 ]Department for Computational Biology of Infection Research, Helmholtz Center for Infection Research, 38124 Brunswick, Germany
                [4 ]Max von Pettenkofer-Institute for Hygiene and Clinical Microbiology, Ludwig-Maximilian University of Munich, 80336 Munich, Germany
                [5 ]Analytical Sciences and Imaging, Novartis Institutes for BioMedical Research, Basel, Switzerland
                [6 ]Chemical Biology and Therapeutics, Novartis Institutes for BioMedical Research, Cambridge, MA, U.S.A.
                [7 ]Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, U.S.A.
                [8 ]Children’s Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
                [9 ]Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
                [10 ]Department of Pediatrics, Tampere University Hospital, 33521 Tampere, Finland
                [11 ]Department of Public Health Solutions, National Institute for Health and Welfare, 00271 Helsinki, Finland
                [12 ]Faculty of Social Sciences/Health Sciences, University of Tampere, 33014 Tampere, Finland
                [13 ]Science Centre, Pirkanmaa Hospital District and Research Center for Child Health, University Hospital, 33521 Tampere, Finland
                [14 ]Immunogenetics Laboratory, University of Turku, 20520 Turku, Finland
                [15 ]Clinical Microbiology, Turku University Hospital, 20520 Turku, Finland
                [16 ]Department of Immunology, Institute of Biomedicine and Translational Medicine, University of Tartu, 50411 Tartu, Estonia
                [17 ]Department of Pediatrics, University of Tartu and Tartu University Hospital, 51014 Tartu, Estonia
                [18 ]Ministry of Health and Social Development, Karelian Republic of the Russian Federation, Lenin Street 6, 185035 Petrozavodsk, Russia
                [19 ]Petrozavodsk State University, Department of Family Medicine, Lenin Street 33, 185910 Petrozavodsk, Russia
                [20 ]Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston MA, U.S.A.
                [21 ]Folkhälsan Research Center, 00290 Helsinki, Finland
                [22 ]Gastrointestinal Unit, Center for the Study of Inflammatory Bowel Disease, and Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston MA, U.S.A.
                [23 ]Center for Microbiome Informatics and Therapeutics, MIT, Cambridge MA, U.S.A.
                Author notes

                Author Contributions

                T.V., D.R.P., J.H. and P.C.M. analyzed the sequencing data. T.D.A., S.R., E.J.O., X.K., R.A.Y., H.J.H. and J.A.P. contributed to B. dorei isolate sequencing. A.B.H. and R.K. contributed to bioinformatic analysis. M.Y., K.L. and H.S. contributed to study design. J.I., S.M.V., R.U., V.T., S.M. and N.D. collected clinical samples. A.C.M., H.L., H.V., C.H., M.K. and R.J.X. served as principal investigators. T.V., D.R.P., J.S., P.C.M., H.V., C.H., M.K. and R.J.X drafted the manuscript. All authors discussed the results, contributed to critical revisions and approved the final manuscript.

                [* ]to whom correspondence should be addressed: xavier@ 123456molbio.mgh.harvard.edu
                Correspondence: Correspondence and requests for materials should be addressed to Ramnik J. Xavier ( xavier@ 123456molbio.mgh.harvard.edu ).
                Article
                NIHMS1512780
                10.1038/s41564-018-0321-5
                6384140
                30559407
                db6267aa-01b5-454d-8840-edfbc4eace67

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