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      The first microbial environment of infants born by C-section: the operating room microbes

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          Abstract

          Background

          Newborns delivered by C-section acquire human skin microbes just after birth, but the sources remain unknown. We hypothesized that the operating room (OR) environment contains human skin bacteria that could be seeding C-section born infants.

          Results

          To test this hypothesis, we sampled 11 sites in four operating rooms from three hospitals in two cities. Following a C-section procedure, we swabbed OR floors, walls, ventilation grids, armrests, and lamps. We sequenced the V4 region of the 16S rRNA gene of 44 samples using Illumina MiSeq platform. Sequences were analyzed using the QIIME pipeline. Only 68 % of the samples (30/44, >1000 sequences per site) yielded sufficient DNA reads to be analyzed. The bacterial content of OR dust corresponded to human skin bacteria, with dominance of Staphylococcus and Corynebacterium. Diversity of bacteria was the highest in the ventilation grids and walls but was also present on top of the surgery lamps. Beta diversity analyses showed OR dust bacterial content clustering first by city and then by hospital ( t test using unweighted UniFrac distances, p < 0.05).

          Conclusions

          We conclude that the dust from ORs, collected right after a C-section procedure, contains deposits of human skin bacteria. The OR microbiota is the first environment for C-section newborns, and OR microbes might be seeding the microbiome in these babies. Further studies are required to identify how this OR microbiome exposure contributes to the seeding of the neonatal microbiome. The results might be relevant to infant health, if the current increase in risk of immune and metabolic diseases in industrialized societies is related to lack of natural exposure to the vaginal microbiome during labor and birth.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s40168-015-0126-1) contains supplementary material, which is available to authorized users.

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          Most cited references 30

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          QIIME allows analysis of high-throughput community sequencing data.

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            Metagenomic biomarker discovery and explanation

            This study describes and validates a new method for metagenomic biomarker discovery by way of class comparison, tests of biological consistency and effect size estimation. This addresses the challenge of finding organisms, genes, or pathways that consistently explain the differences between two or more microbial communities, which is a central problem to the study of metagenomics. We extensively validate our method on several microbiomes and a convenient online interface for the method is provided at http://huttenhower.sph.harvard.edu/lefse/.
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              Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms

              DNA sequencing continues to decrease in cost with the Illumina HiSeq2000 generating up to 600 Gb of paired-end 100 base reads in a ten-day run. Here we present a protocol for community amplicon sequencing on the HiSeq2000 and MiSeq Illumina platforms, and apply that protocol to sequence 24 microbial communities from host-associated and free-living environments. A critical question as more sequencing platforms become available is whether biological conclusions derived on one platform are consistent with what would be derived on a different platform. We show that the protocol developed for these instruments successfully recaptures known biological results, and additionally that biological conclusions are consistent across sequencing platforms (the HiSeq2000 versus the MiSeq) and across the sequenced regions of amplicons.
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                Author and article information

                Contributors
                646-501-0703 , Maria.Dominguez-Bello@nyumc.org
                Journal
                Microbiome
                Microbiome
                Microbiome
                BioMed Central (London )
                2049-2618
                1 December 2015
                1 December 2015
                2015
                : 3
                Affiliations
                [ ]Division of Translational Medicine, New York University School of Medicine, 550 1st Avenue, BCD 690, New York, NY 10016 USA
                [ ]Department of Veterans Affairs New York Harbor Healthcare System, New York, NY USA
                [ ]Hospital Universitario, Medical Science Campus, University of Puerto Rico, Puerto Rico, USA
                [ ]School of Architecture, University of Puerto Rico, Puerto Rico, USA
                Article
                126
                10.1186/s40168-015-0126-1
                4665759
                26620712
                © Shin et al. 2015

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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                © The Author(s) 2015

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