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The process of breastfeeding exposes infants to bioactive substances including a diversity of bacteria from breast milk as well as maternal skin. Knowledge of the character of and variation in these microbial communities, as well as the factors that influence them, is limited. We aimed to identify profiles of breastfeeding-associated microbial communities and their association with maternal and infant factors. Bilateral milk samples were collected from women in the New Hampshire Birth Cohort Study at approximately 6 weeks postpartum without sterilization of the skin in order to capture the infant-relevant exposure. We sequenced the V4-V5 hypervariable region of the bacterial 16S rRNA gene in 155 human milk samples. We used unsupervised clustering (partitioning around medoids) to identify microbial profiles in milk samples, and multinomial logistic regression to test their relation with maternal and infant variables. Associations between alpha diversity and maternal and infant factors were tested with linear models. Four breastfeeding microbiome types (BMTs) were identified, which differed in alpha diversity and in Streptococcus, Staphylococcus, Acinetobacter, and Pseudomonas abundances. Higher maternal pre-pregnancy BMI was associated with increased odds of belonging to BMT1 [OR (95% CI) = 1.13 (1.02, 1.24)] or BMT3 [OR (95% CI) = 1.12 (1.01, 1.25)] compared to BMT2. Independently, increased gestational weight gain was related to reduced odds of membership in BMT1 [OR (95% CI) = 0.66 (0.44, 1.00) per 10 pounds]. Alpha diversity was positively associated with gestational weight gain and negatively associated with postpartum sample collection week. There were no statistically significant associations of breastfeeding microbiota with delivery mode. Our results indicate that the breastfeeding microbiome partitions into four profiles and that its composition and diversity is associated with measures of maternal weight.
Pubmed ID: 31921063 RIS Download
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View all literature mentionsDatabase that provides access to the current and comprehensive 16S rRNA gene sequence alignment for browsing, blasting, probing, and downloading. The data and tools can assist the researcher in choosing phylogenetically specific probes, interpreting microarray results, and aligning/annotating novel sequences. The 16S rRNA gene database provides chimera screening, standard alignment, and taxonomic classification using multiple published taxonomies. ARB users can use Greengenes to update local databases.
View all literature mentionsRepository of raw sequencing data from next generation of sequencing platforms including including Roche 454 GS System, Illumina Genome Analyzer, Applied Biosystems SOLiD System, Helicos Heliscope, Complete Genomics, and Pacific Biosciences SMRT. In addition to raw sequence data, SRA now stores alignment information in form of read placements on reference sequence. Data submissions are welcome. Archive of high throughput sequencing data,part of international partnership of archives (INSDC) at NCBI, European Bioinformatics Institute and DNA Database of Japan. Data submitted to any of this three organizations are shared among them.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 23,2023.Software package for comparison and analysis of microbial communities, primarily based on high-throughput amplicon sequencing data, but also supporting analysis of other types of data. QIMME analyzes and transforms raw sequencing data generated on Illumina or other platforms to publication quality graphics and statistics.
View all literature mentionsSource code that infers approximately-maximum-likelihood phylogenetic trees from alignments of nucleotide or protein sequences. It uses the Jukes-Cantor or generalized time-reversible (GTR) models of nucleotide evolution and the JTT, WAG, or LG models of amino acid evolution.
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