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      Temporal development of the gut microbiome in early childhood from the TEDDY study

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          Abstract

          The development of the microbiome from infancy to childhood is dependent on a range of factors, with microbial–immune crosstalk during this time thought to be involved in the pathobiology of later life diseases 19 such as persistent islet autoimmunity and type 1 diabetes 1012. However, to our knowledge, no studies have performed extensive characterization of the microbiome in early life in a large, multi-centre population. Here we analyse longitudinal stool samples from 903 children between 3 and 46 months of age by 16S rRNA gene sequencing (n = 12,005) and metagenomic sequencing (n = 10,867), as part of the The Environmental Determinants of Diabetes in the Young (TEDDY) study. We show that the developing gut microbiome undergoes three distinct phases of microbiome progression: a developmental phase (months 3–14), a transitional phase (months 15–30), and a stable phase (months 31–46). Receipt of breast milk, either exclusive or partial, was the most significant factor associated with the microbiome structure. Breastfeeding was associated with higher levels of Bifidobacterium species (B. breve and B. bifidum), and the cessation of breast milk resulted in faster maturation of the gut microbiome, as marked by the phylum Firmicutes. Birth mode was also significantly associated with the microbiome during the developmental phase, driven by higher levels of Bacteroides species (particularly B. fragilis) in infants delivered vaginally. Bacteroides was also associated with increased gut diversity and faster maturation, regardless of the birth mode. Environmental factors including geographical location and household exposures (such as siblings and furry pets) also represented important covariates. A nested case–control analysis revealed subtle associations between microbial taxonomy and the development of islet autoimmunity or type 1 diabetes. These data determine the structural and functional assembly of the microbiome in early life and provide a foundation for targeted mechanistic investigation into the consequences of microbial–immune crosstalk for long-term health.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Exposure to environmental microorganisms and childhood asthma.

            Children who grow up in environments that afford them a wide range of microbial exposures, such as traditional farms, are protected from childhood asthma and atopy. In previous studies, markers of microbial exposure have been inversely related to these conditions. In two cross-sectional studies, we compared children living on farms with those in a reference group with respect to the prevalence of asthma and atopy and to the diversity of microbial exposure. In one study--PARSIFAL (Prevention of Allergy-Risk Factors for Sensitization in Children Related to Farming and Anthroposophic Lifestyle)--samples of mattress dust were screened for bacterial DNA with the use of single-strand conformation polymorphism (SSCP) analyses to detect environmental bacteria that cannot be measured by means of culture techniques. In the other study--GABRIELA (Multidisciplinary Study to Identify the Genetic and Environmental Causes of Asthma in the European Community [GABRIEL] Advanced Study)--samples of settled dust from children's rooms were evaluated for bacterial and fungal taxa with the use of culture techniques. In both studies, children who lived on farms had lower prevalences of asthma and atopy and were exposed to a greater variety of environmental microorganisms than the children in the reference group. In turn, diversity of microbial exposure was inversely related to the risk of asthma (odds ratio for PARSIFAL, 0.62; 95% confidence interval [CI], 0.44 to 0.89; odds ratio for GABRIELA, 0.86; 95% CI, 0.75 to 0.99). In addition, the presence of certain more circumscribed exposures was also inversely related to the risk of asthma; this included exposure to species in the fungal taxon eurotium (adjusted odds ratio, 0.37; 95% CI, 0.18 to 0.76) and to a variety of bacterial species, including Listeria monocytogenes, bacillus species, corynebacterium species, and others (adjusted odds ratio, 0.57; 95% CI, 0.38 to 0.86). Children living on farms were exposed to a wider range of microbes than were children in the reference group, and this exposure explains a substantial fraction of the inverse relation between asthma and growing up on a farm. (Funded by the Deutsche Forschungsgemeinschaft and the European Commission.).
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              Bifidobacteria and Their Role as Members of the Human Gut Microbiota

              Members of the genus Bifidobacterium are among the first microbes to colonize the human gastrointestinal tract and are believed to exert positive health benefits on their host. Due to their purported health-promoting properties, bifidobacteria have been incorporated into many functional foods as active ingredients. Bifidobacteria naturally occur in a range of ecological niches that are either directly or indirectly connected to the animal gastrointestinal tract, such as the human oral cavity, the insect gut and sewage. To be able to survive in these particular ecological niches, bifidobacteria must possess specific adaptations to be competitive. Determination of genome sequences has revealed genetic attributes that may explain bifidobacterial ecological fitness, such as metabolic abilities, evasion of the host adaptive immune system and colonization of the host through specific appendages. However, genetic modification is crucial toward fully elucidating the mechanisms by which bifidobacteria exert their adaptive abilities and beneficial properties. In this review we provide an up to date summary of the general features of bifidobacteria, whilst paying particular attention to the metabolic abilities of this species. We also describe methods that have allowed successful genetic manipulation of bifidobacteria.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                15 February 2019
                24 October 2018
                October 2018
                24 April 2019
                : 562
                : 7728
                : 583-588
                Affiliations
                [1 ]Alkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA.
                [2 ]Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK.
                [3 ]Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
                [4 ]Broad Institute of MIT and Harvard, Cambridge, MA, USA.
                [5 ]Barbara Davis Center for Childhood Diabetes, University of Colorado, Aurora, CO, USA.
                [6 ]Pacific Northwest Research Institute, Seattle, WA, USA.
                [7 ]Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, University of Turku, Turku, Finland.
                [8 ]Department of Pediatrics, Turku University Hospital, Turku, Finland.
                [9 ]Institute of Diabetes Research, Helmholtz Zentrum München, Munich, Germany.
                [10 ]Forschergruppe Diabetes, Technische Universität München, Klinikum Rechts der Isar, Munich, Germany.
                [11 ]Forschergruppe Diabetes e.V. at Helmholtz Zentrum München, Munich, Germany.
                [12 ]Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA, USA.
                [13 ]National Institute of Diabetes & Digestive & Kidney Diseases, Bethesda, MD, USA.
                [14 ]Department of Clinical Sciences, Lund University/CRC, Skane University Hospital, Malmö, Sweden.
                [15 ]Department of Virology, Faculty of Medicine and Biosciences, University of Tampere, Tampere, Finland.
                [16 ]Fimlab Laboratories, Pirkanmaa Hospital District, Tampere, Finland.
                [17 ]Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, FL, USA.
                [18 ]These authors contributed equally: Christopher J. Stewart, Nadim J. Ajami.
                Author notes

                Author contributions C.J.S., N.J.A., R.E.L., T.V., C.H., R.J.X., M.R., W.H., J.T., A.-G.Z., J.-X.S., B.A., A.L., H.H., K.V., J.P.K. and J.F.P. designed the study; M.R., W.H., J.T., A.-G.Z., J.X.S., B.A., A.L., H.H., K.V. and J.P.K. participated in patient recruitment and diagnosis, sample collection, generation of the metadata; C.J.S., N.J.A., M.C.W., M.C.R., H.D., G.A.M., D.M. and R.A.G. generated and processed the raw sequencing data; C.J.S., N.J.A., J.L.O., D.S.H. and D.P.S. performed the data analysis, data interpretation, and figure generation; C.J.S., N.J.A., J.L.O., D.S.H. and J.F.P. wrote the paper; and all authors contributed to critical revisions and approved the final manuscript. Members of the TEDDY Study Group are listed in the Supplementary Information.

                [* ] Correspondence and requests for materials should be addressed to C.J.S. or J.F.P. christopher.stewart@ 123456ncl.ac.uk ; jpetrosi@ 123456bcm.edu
                Article
                NIHMS1006388
                10.1038/s41586-018-0617-x
                6415775
                30356187
                d42182a4-e9c9-4811-a154-d32d5cb041e6

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