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      Delivery Mode Affects Stability of Early Infant Gut Microbiota

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          Summary

          Mode of delivery strongly influences the early infant gut microbiome. Children born by cesarean section (C-section) lack Bacteroides species until 6–18 months of age. One hypothesis is that these differences stem from lack of exposure to the maternal vaginal microbiome. Here, we re-evaluate this hypothesis by comparing the microbial profiles of 75 infants born vaginally or by planned versus emergent C-section. Multiple children born by C-section have a high abundance of Bacteroides in their first few days of life, but at 2 weeks, both C-section groups lack Bacteroides (primarily according to 16S sequencing), despite their difference in exposure to the birth canal. Finally, a comparison of microbial strain profiles between infants and maternal vaginal or rectal samples finds evidence for mother-to-child transmission of rectal rather than vaginal strains. These results suggest differences in colonization stability as an important factor in infant gut microbiome composition rather than birth canal exposure.

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          Highlights

          • Week 1 gut microbiota does not differ between infants born vaginally versus C-section

          • Week 2 gut microbiota of C-section infants lacks Bacteroides

          • Microbiota of infants born by C-section after labor resembles scheduled C-section

          • Bacterial strains in infants match maternal rectal rather than vaginal strains

          Abstract

          Mitchell et al. compare early-life infant gut microbiota by delivery mode, suggesting early colonization by Bacteroides regardless of delivery mode, but loss of Bacteroides by 2 weeks in C-section-delivered infants, whether or not exposed to the vagina in labor. Infant strains matched maternal rectal rather vaginal strains.

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          QIIME allows analysis of high-throughput community sequencing data.

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            Human gut microbiome viewed across age and geography

            Gut microbial communities represent one source of human genetic and metabolic diversity. To examine how gut microbiomes differ between human populations when viewed from the perspective of component microbial lineages, encoded metabolic functions, stage of postnatal development, and environmental exposures, we characterized bacterial species present in fecal samples obtained from 531 individuals representing healthy Amerindians from the Amazonas of Venezuela, residents of rural Malawian communities, and inhabitants of USA metropolitan areas, as well as the gene content of 110 of their microbiomes. This cohort encompassed infants, children, teenagers and adults, parents and offspring, and included mono- and dizygotic twins. Shared features of the functional maturation of the gut microbiome were identified during the first three years of life in all three populations, including age-associated changes in the representation of genes involved in vitamin biosynthesis and metabolism. Pronounced differences in bacterial species assemblages and functional gene repertoires were noted between individuals residing in the USA compared to the other two countries. These distinctive features are evident in early infancy as well as adulthood. In addition, the similarity of fecal microbiomes among family members extends across cultures. These findings underscore the need to consider the microbiome when evaluating human development, nutritional needs, physiological variations, and the impact of Westernization.
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              An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea

              Reference phylogenies are crucial for providing a taxonomic framework for interpretation of marker gene and metagenomic surveys, which continue to reveal novel species at a remarkable rate. Greengenes is a dedicated full-length 16S rRNA gene database that provides users with a curated taxonomy based on de novo tree inference. We developed a ‘taxonomy to tree' approach for transferring group names from an existing taxonomy to a tree topology, and used it to apply the Greengenes, National Center for Biotechnology Information (NCBI) and cyanoDB (Cyanobacteria only) taxonomies to a de novo tree comprising 408 315 sequences. We also incorporated explicit rank information provided by the NCBI taxonomy to group names (by prefixing rank designations) for better user orientation and classification consistency. The resulting merged taxonomy improved the classification of 75% of the sequences by one or more ranks relative to the original NCBI taxonomy with the most pronounced improvements occurring in under-classified environmental sequences. We also assessed candidate phyla (divisions) currently defined by NCBI and present recommendations for consolidation of 34 redundantly named groups. All intermediate results from the pipeline, which includes tree inference, jackknifing and transfer of a donor taxonomy to a recipient tree (tax2tree) are available for download. The improved Greengenes taxonomy should provide important infrastructure for a wide range of megasequencing projects studying ecosystems on scales ranging from our own bodies (the Human Microbiome Project) to the entire planet (the Earth Microbiome Project). The implementation of the software can be obtained from http://sourceforge.net/projects/tax2tree/.
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                Author and article information

                Contributors
                Journal
                Cell Rep Med
                Cell Rep Med
                Cell Reports Medicine
                Elsevier
                2666-3791
                22 December 2020
                22 December 2020
                22 December 2020
                : 1
                : 9
                : 100156
                Affiliations
                [1 ]Vincent Obstetrics & Gynecology Department, Massachusetts General Hospital, Boston, MA 02114, USA
                [2 ]Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 91121, Israel
                [3 ]Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
                [4 ]Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
                [5 ]Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
                [6 ]Department of Systems Biology, Harvard Medical School, Boston, MA 02125, USA
                [7 ]Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
                [8 ]Gastrointestinal Unit, Center for the Study of Inflammatory Bowel Disease, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
                [9 ]The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
                Author notes
                []Corresponding author moranya@ 123456mail.huji.ac.il
                [10]

                Lead Contact

                Article
                S2666-3791(20)30203-2 100156
                10.1016/j.xcrm.2020.100156
                7762768
                33377127
                86a9b14a-5c41-4e66-b3fe-306bf8835980
                © 2020 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 29 January 2020
                : 29 September 2020
                : 19 November 2020
                Categories
                Article

                infant gut microbiota, caesarean delivery, bacteroides, delivery mode, transmission of maternal strains

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