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      Maternal Diet Shapes the Breast Milk Microbiota Composition and Diversity: Impact of Mode of Delivery and Antibiotic Exposure

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          ABSTRACT

          Background

          Breast milk is a complex biofluid that provides nutrients and bioactive agents, including bacteria, for the development of the infant gut microbiota. However, the impact of maternal diet and other factors, such as mode of delivery and antibiotic exposure, on the breast milk microbiota has yet to be understood.

          Objectives

          This study aimed to examine the association between maternal diet and breast milk microbiota and to ascertain the potential role of mode of delivery and antibiotic exposure.

          Methods

          In a cross-sectional study of the MAMI cohort, breast milk microbiota profiling was assessed in 120 samples from healthy mothers by 16S rRNA gene sequencing. Maternal dietary information was recorded through an FFQ, and clinical characteristics, including mode of delivery, antibiotic exposure, and exclusive breastfeeding, were collected.

          Results

          Maternal diet was grouped into 2 clusters: Cluster I (high intake of plant protein, fiber, and carbohydrates), and Cluster II (high intake of animal protein and lipids). Breast milk microbiota was shaped by maternal dietary clusters. Staphylococcus and Bifidobacterium were associated with carbohydrate intake whereas the Streptococcus genus was associated with intakes of the n–3 PUFAs [EPA and docosapentaenoic acid (22:5ω-3)]. Mode of delivery and antibiotic exposure influenced breast milk microbiota in a diet cluster–dependent manner. Differences between/among the maternal dietary clusters were found in the milk microbiota of the cesarean-section (C-section)/antibiotic group, whereas no differences were observed in vaginal births. Lower abundances of Lactobacillus, Bacteroides, and Sediminibacterium genera were observed in Cluster II/C-section/antibiotic exposure compared with the other groups.

          Conclusions

          Maternal diet shapes the composition and diversity of breast milk microbiota, with the most important contributions coming from dietary fiber and both plant and animal protein intakes. The relation between the maternal diet and the milk microbiota needs further research because it has a key impact on infant microbiota development and contributes to infant health outcomes in the short and long term.

          This trial was registered at clinicaltrials.gov as NCT03552939.

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          Most cited references62

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          DADA2: High resolution sample inference from Illumina amplicon data

          We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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            The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

            SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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              phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

              Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
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                Author and article information

                Contributors
                Journal
                J Nutr
                J Nutr
                jn
                The Journal of Nutrition
                Oxford University Press
                0022-3166
                1541-6100
                February 2021
                13 November 2020
                13 November 2020
                : 151
                : 2
                : 330-340
                Affiliations
                Institute of Agrochemistry and Food Technology (IATA-CSIC), National Research Council , Valencia, Spain
                Institute of Agrochemistry and Food Technology (IATA-CSIC), National Research Council , Valencia, Spain
                Institute of Agrochemistry and Food Technology (IATA-CSIC), National Research Council , Valencia, Spain
                Institute of Agrochemistry and Food Technology (IATA-CSIC), National Research Council , Valencia, Spain
                Department of Functional Biology, Faculty of Medicine, University of Oviedo , Oviedo, Spain
                Diet, Microbiota and Health Group, Instituto de Investigación Sanitaria del Principado de Asturias (DIMISA, ISPA) , Oviedo, Spain
                Department of Pediatrics, School of Medicine, University of Valencia , Valencia, Spain
                Pediatric Gastroenterology and Nutrition Section, Hospital Clínico Universitario Valencia, INCLIVA , Valencia, Spain
                Institute of Agrochemistry and Food Technology (IATA-CSIC), National Research Council , Valencia, Spain
                Author notes
                Address correspondence to MCC (e-mail: mcolam@ 123456iata.csic.es )
                Author information
                http://orcid.org/0000-0002-4258-947X
                http://orcid.org/0000-0003-2118-3187
                http://orcid.org/0000-0003-3592-3377
                http://orcid.org/0000-0003-1347-7521
                http://orcid.org/0000-0002-6204-4864
                Article
                nxaa310
                10.1093/jn/nxaa310
                7850106
                33188413
                b5f277fa-3212-4580-b12f-6c38767e2eb6
                © The Author(s) 2020. Published by Oxford University Press on behalf of the American Society for Nutrition.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 01 May 2020
                : 21 July 2020
                : 16 September 2020
                Page count
                Pages: 11
                Funding
                Funded by: European Research Council, DOI 10.13039/100010663;
                Award ID: 639226
                Funded by: Generalitat Valenciana—European Social Fund;
                Award ID: GRISOLÍA2019
                Award ID: ASCII2016
                Categories
                Nutrition and Disease
                AcademicSubjects/MED00060
                AcademicSubjects/SCI00960

                Nutrition & Dietetics
                maternal diet,breast milk,microbiota,plant protein,animal protein
                Nutrition & Dietetics
                maternal diet, breast milk, microbiota, plant protein, animal protein

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