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      Mothers Secretor Status Affects Development of Childrens Microbiota Composition and Function: A Pilot Study

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          Abstract

          Background

          One mechanism by which early life environment may influence long term health is through modulation of the gut microbiota. It is widely accepted that the optimal source of nutrition in early life is breast milk, with Human Milk Oligosaccharides (HMOs) thought to play an important role in nourishing the developing microbiota. However, mothers with inactive secretor genes have altered HMO composition and quantities in their breast milk. In this pilot study we examine the influence of secretor status and breast-feeding on microbiota composition at 2 to 3 years of age.

          Methods

          37 children and 17 eligible mothers were recruited. Secretor status was determined from blood and saliva samples using hemagglutination inhibition technique and faecal microbiota composition was examined by 16S rRNA gene sequencing.

          Results

          Secretor status was determined for 28 eligible children with 20 being secretors (S, 71.4%). Eleven of the 17 mothers were secretors (S, 64.7%). Unweighted UniFrac distances were significantly associated with child secretor status (R 2 = 0.069, p = 0.030) and with mother secretor status in children exclusively breastfed for at least 4 months (R 2 = 0.167, p = 0.028), suggesting an influence on the presence/absence of microbes, with Prevotella not detected in samples from secretor children and children of secretor mothers. In children who were exclusively breast-fed for at least 4 months of life the abundance of the known HMO consumers Bifidobacterium were increased in the children of secretor mothers compared to non-secretor mothers. The relative abundance of an OTU related to Bacteroides plebeius, a bacterium noted for its capacity to utilise sulphated polysaccharides for growth, was decreased in these children.

          Conclusions

          Child and mothers’ secretor status have an impact on childrens’ microbiota composition at 2 to 3 years of age.

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          Most cited references22

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          Meta-analyses of human gut microbes associated with obesity and IBD.

          Recent studies have linked human gut microbes to obesity and inflammatory bowel disease, but consistent signals have been difficult to identify. Here we test for indicator taxa and general features of the microbiota that are generally consistent across studies of obesity and of IBD, focusing on studies involving high-throughput sequencing of the 16S rRNA gene (which we could process using a common computational pipeline). We find that IBD has a consistent signature across studies and allows high classification accuracy of IBD from non-IBD subjects, but that although subjects can be classified as lean or obese within each individual study with statistically significant accuracy, consistent with the ability of the microbiota to experimentally transfer this phenotype, signatures of obesity are not consistent between studies even when the data are analyzed with consistent methods. The results suggest that correlations between microbes and clinical conditions with different effect sizes (e.g. the large effect size of IBD versus the small effect size of obesity) may require different cohort selection and analysis strategies.
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            Establishment of intestinal microbiota during early life: a longitudinal, explorative study of a large cohort of Danish infants.

            Fecal samples were obtained from a cohort of 330 healthy Danish infants at 9, 18, and 36 months after birth, enabling characterization of interbacterial relationships by use of quantitative PCR targeting 31 selected bacterial 16S rRNA gene targets representing different phylogenetic levels. Nutritional parameters and measures of growth and body composition were determined and investigated in relation to the observed development in microbiota composition. We found that significant changes in the gut microbiota occurred, particularly from age 9 to 18 months, when cessation of breastfeeding and introduction of a complementary feeding induce replacement of a microbiota characterized by lactobacilli, bifidobacteria, and Enterobacteriaceae with a microbiota dominated by Clostridium spp. and Bacteroides spp. Classification of samples by a proxy enterotype based on the relative levels of Bacteroides spp. and Prevotella spp. showed that enterotype establishment occurs between 9 and 36 months. Thirty percent of the individuals shifted enterotype between 18 and 36 months. The composition of the microbiota was most pronouncedly influenced by the time of cessation of breastfeeding. From 9 to 18 months, a positive correlation was observed between the increase in body mass index and the increase of the short-chain-fatty-acid-producing clostridia, the Clostridum leptum group, and Eubacterium hallii. Considering previously established positive associations between rapid infant weight gain, early breastfeeding discontinuation, and later-life obesity, the corresponding microbial findings seen here warrant attention.
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              The function of our microbiota: who is out there and what do they do?

              Current meta-omics developments provide a portal into the functional potential and activity of the intestinal microbiota. The comparative and functional meta-omics approaches have made it possible to get a molecular snap shot of microbial function at a certain time and place. To this end, metagenomics is a DNA-based approach, metatranscriptomics studies the total transcribed RNA, metaproteomics focuses on protein levels and metabolomics describes metabolic profiles. Notably, the metagenomic toolbox is rapidly expanding and has been instrumental in the generation of draft genome sequences of over 1000 human associated microorganisms as well as an astonishing 3.3 million unique microbial genes derived from the intestinal tract of over 100 European adults. Remarkably, it appeared that there are at least 3 clusters of co-occurring microbial species, termed enterotypes, that characterize the intestinal microbiota throughout various continents. The human intestinal microbial metagenome further revealed unique functions carried out in the intestinal environment and provided the basis for newly discovered mechanisms for signaling, vitamin production and glycan, amino-acid and xenobiotic metabolism. The activity and composition of the microbiota is affected by genetic background, age, diet, and health status of the host. In its turn the microbiota composition and activity influence host metabolism and disease development. Exemplified by the differences in microbiota composition and activity between breast- as compared to formula-fed babies, healthy and malnourished infants, elderly and centenarians as compared to youngsters, humans that are either lean or obese and healthy or suffering of inflammatory bowel diseases (IBD). In this review we will focus on our current understanding of the functionality of the human intestinal microbiota based on all available metagenome, metatranscriptome, and metaproteome results
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                19 September 2016
                2016
                : 11
                : 9
                : e0161211
                Affiliations
                [1 ]Children’s Nutrition Research Centre, Child Health Research Centre, The University of Queensland, Brisbane, QLD, Australia
                [2 ]The University of Queensland Diamantina Institute, Translational Research Institute, The University of Queensland, Brisbane, QLD, Australia
                Colorado State University, UNITED STATES
                Author notes

                Competing Interests: PSB received a Ph.D. living allowance stipend from Danone Nutricia, Australia. This does not alter the authors' adherence to PLOS ONE policies on sharing data and materials.

                • Conceptualization: PSB.

                • Data curation: PSB.

                • Formal analysis: PSB LK.

                • Funding acquisition: PSB PSWD.

                • Investigation: PSB.

                • Methodology: PSB MM LK PSWD.

                • Project administration: PSB PSWD.

                • Supervision: PSB MM LK PSWD.

                • Visualization: PSB.

                • Writing - original draft: PSB.

                • Writing - review & editing: MM LK PSWD.

                Article
                PONE-D-16-04805
                10.1371/journal.pone.0161211
                5028039
                27644050
                a8c87ebc-3122-4df4-950d-507ac99ded11
                © 2016 Smith-Brown et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 2 February 2016
                : 1 August 2016
                Page count
                Figures: 1, Tables: 3, Pages: 13
                Funding
                PSB received Ph.D. living allowance stipend from Danone Nutricia, Australia, and data analysis funded by Danone Nutricia, Australia (PSB, PSWD). No grant number associated with this funding. URL: www.nutricia.com.au. The Translation Research Institute is supported by a grant from the Australian Government (LK, MM). No grant number supplied. The funders had no role in study design, data collection, and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbiome
                Biology and Life Sciences
                Genetics
                Genomics
                Microbial Genomics
                Microbiome
                Biology and Life Sciences
                Microbiology
                Microbial Genomics
                Microbiome
                Biology and Life Sciences
                Anatomy
                Body Fluids
                Milk
                Breast Milk
                Medicine and Health Sciences
                Anatomy
                Body Fluids
                Milk
                Breast Milk
                Biology and Life Sciences
                Physiology
                Body Fluids
                Milk
                Breast Milk
                Medicine and Health Sciences
                Physiology
                Body Fluids
                Milk
                Breast Milk
                Biology and Life Sciences
                Organisms
                Bacteria
                Gut Bacteria
                Bifidobacterium
                Biology and Life Sciences
                Organisms
                Bacteria
                Gut Bacteria
                Bacteroides
                Biology and Life Sciences
                Behavior
                Parenting Behavior
                Biology and Life Sciences
                Organisms
                Bacteria
                Prevotella
                People and Places
                Population Groupings
                Age Groups
                Children
                Infants
                People and Places
                Population Groupings
                Families
                Children
                Infants
                Biology and Life Sciences
                Organisms
                Bacteria
                Gut Bacteria
                Custom metadata
                All data and related metadata underlying the findings reported in this manuscript are deposited in the Qiita ( qiita.ucsd.edu) public repository (EBI Accession Number ERP016646).

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                Uncategorized

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