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Impact of Early Feeding: Metagenomics Analysis of the Infant Gut Microbiome
BACKGROUND: Different feeding regimens in infancy alter the gastrointestinal (gut) microbial environment. The fecal microbiota in turn influences gastrointestinal homeostasis including metabolism, immune function, and extra-/intra-intestinal signaling. Advances in next generation sequencing (NGS) ha...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8931315/ https://www.ncbi.nlm.nih.gov/pubmed/35310842 http://dx.doi.org/10.3389/fcimb.2022.816601 |
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author | Di Guglielmo, Matthew D. Franke, Karl R. Robbins, Alan Crowgey, Erin L. |
author_facet | Di Guglielmo, Matthew D. Franke, Karl R. Robbins, Alan Crowgey, Erin L. |
author_sort | Di Guglielmo, Matthew D. |
collection | PubMed |
description | BACKGROUND: Different feeding regimens in infancy alter the gastrointestinal (gut) microbial environment. The fecal microbiota in turn influences gastrointestinal homeostasis including metabolism, immune function, and extra-/intra-intestinal signaling. Advances in next generation sequencing (NGS) have enhanced our ability to study the gut microbiome of breast-fed (BF) and formula-fed (FF) infants with a data-driven hypothesis approach. METHODS: Next generation sequencing libraries were constructed from fecal samples of BF (n=24) and FF (n=10) infants and sequenced on an Illumina HiSeq 2500. Taxonomic classification of the NGS data was performed using the Sunbeam/Kraken pipeline and a functional analysis at the gene level was performed using publicly available algorithms, including BLAST, and custom scripts. Differentially represented genera, genes, and NCBI Clusters of Orthologous Genes (COG) were determined between cohorts using count data and R (statistical packages edgeR and DESeq2). RESULTS: Thirty-nine genera were found to be differentially represented between the BF and FF cohorts (FDR ≤ 0.01) including Parabacteroides, Enterococcus, Haemophilus, Gardnerella, and Staphylococcus. A Welch t-test of the Shannon diversity index for BF and FF samples approached significance (p=0.061). Bray-Curtis and Jaccard distance analyses demonstrated clustering and overlap in each analysis. Sixty COGs were significantly overrepresented and those most significantly represented in BF vs. FF samples showed dichotomy of categories representing gene functions. Over 1,700 genes were found to be differentially represented (abundance) between the BF and FF cohorts. CONCLUSIONS: Fecal samples analyzed from BF and FF infants demonstrated differences in microbiota genera. The BF cohort includes greater presence of beneficial genus Bifidobacterium. Several genes were identified as present at different abundances between cohorts indicating differences in functional pathways such as cellular defense mechanisms and carbohydrate metabolism influenced by feeding. Confirmation of gene level NGS data via PCR and electrophoresis analysis revealed distinct differences in gene abundances associated with important biologic pathways. |
format | Online Article Text |
id | pubmed-8931315 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89313152022-03-19 Impact of Early Feeding: Metagenomics Analysis of the Infant Gut Microbiome Di Guglielmo, Matthew D. Franke, Karl R. Robbins, Alan Crowgey, Erin L. Front Cell Infect Microbiol Cellular and Infection Microbiology BACKGROUND: Different feeding regimens in infancy alter the gastrointestinal (gut) microbial environment. The fecal microbiota in turn influences gastrointestinal homeostasis including metabolism, immune function, and extra-/intra-intestinal signaling. Advances in next generation sequencing (NGS) have enhanced our ability to study the gut microbiome of breast-fed (BF) and formula-fed (FF) infants with a data-driven hypothesis approach. METHODS: Next generation sequencing libraries were constructed from fecal samples of BF (n=24) and FF (n=10) infants and sequenced on an Illumina HiSeq 2500. Taxonomic classification of the NGS data was performed using the Sunbeam/Kraken pipeline and a functional analysis at the gene level was performed using publicly available algorithms, including BLAST, and custom scripts. Differentially represented genera, genes, and NCBI Clusters of Orthologous Genes (COG) were determined between cohorts using count data and R (statistical packages edgeR and DESeq2). RESULTS: Thirty-nine genera were found to be differentially represented between the BF and FF cohorts (FDR ≤ 0.01) including Parabacteroides, Enterococcus, Haemophilus, Gardnerella, and Staphylococcus. A Welch t-test of the Shannon diversity index for BF and FF samples approached significance (p=0.061). Bray-Curtis and Jaccard distance analyses demonstrated clustering and overlap in each analysis. Sixty COGs were significantly overrepresented and those most significantly represented in BF vs. FF samples showed dichotomy of categories representing gene functions. Over 1,700 genes were found to be differentially represented (abundance) between the BF and FF cohorts. CONCLUSIONS: Fecal samples analyzed from BF and FF infants demonstrated differences in microbiota genera. The BF cohort includes greater presence of beneficial genus Bifidobacterium. Several genes were identified as present at different abundances between cohorts indicating differences in functional pathways such as cellular defense mechanisms and carbohydrate metabolism influenced by feeding. Confirmation of gene level NGS data via PCR and electrophoresis analysis revealed distinct differences in gene abundances associated with important biologic pathways. Frontiers Media S.A. 2022-03-04 /pmc/articles/PMC8931315/ /pubmed/35310842 http://dx.doi.org/10.3389/fcimb.2022.816601 Text en Copyright © 2022 Di Guglielmo, Franke, Robbins and Crowgey https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cellular and Infection Microbiology Di Guglielmo, Matthew D. Franke, Karl R. Robbins, Alan Crowgey, Erin L. Impact of Early Feeding: Metagenomics Analysis of the Infant Gut Microbiome |
title | Impact of Early Feeding: Metagenomics Analysis of the Infant Gut Microbiome |
title_full | Impact of Early Feeding: Metagenomics Analysis of the Infant Gut Microbiome |
title_fullStr | Impact of Early Feeding: Metagenomics Analysis of the Infant Gut Microbiome |
title_full_unstemmed | Impact of Early Feeding: Metagenomics Analysis of the Infant Gut Microbiome |
title_short | Impact of Early Feeding: Metagenomics Analysis of the Infant Gut Microbiome |
title_sort | impact of early feeding: metagenomics analysis of the infant gut microbiome |
topic | Cellular and Infection Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8931315/ https://www.ncbi.nlm.nih.gov/pubmed/35310842 http://dx.doi.org/10.3389/fcimb.2022.816601 |
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