Appropriate development of the intestinal microbiota during infancy is known to be important for human health. In fact, aberrant alterations of the microbial composition during childhood may cause short- and/or long-term negative health effects. Many factors influence the initial assembly and subsequent progression of the gut microbiota of a neonate, such as feeding type, delivery mode, gestational age, maternal metabolic status and antibiotic exposure. In the current study, the composition of the infant gut core-microbiota was explored, revealing particular variations of this core-microbiota during the first three years as influenced by delivery mode and feeding type. A multi-population cohort meta-analysis was performed by selecting 15 publicly available datasets pertaining to taxonomic profiles of 1035 fecal samples of healthy infants, as obtained by means of a 16S rRNA gene-based profiling approach. Interestingly, this multi-population cohort meta-analysis revealed great microbial complexity and specific taxonomic shifts in children older than six months, suggesting a major impact by the introduction of solid foods which prompts progression of infant gut microbiota towards that typical of adults. The taxonomic data sets employed in this multi-population cohort meta-analysis possess the statistical robustness to allow the identification of infant community state types (ICSTs). Our analysis therefore reveals the existence of specific taxonomic patterns that correspond to particular nutritional and developmental stages of early life, and that had previously been obscured by the high variability typical of such infant gut microbiota.

Multi-population cohort meta-analysis of human intestinal microbiota in early life reveals the existence of infant community state types (ICSTs) / Mancabelli, L.; Tarracchini, C.; Milani, C.; Lugli, G. A.; Fontana, F.; Turroni, F.; van Sinderen, D.; Ventura, M.. - In: COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL. - ISSN 2001-0370. - 18:(2020), pp. 2480-2493. [10.1016/j.csbj.2020.08.028]

Multi-population cohort meta-analysis of human intestinal microbiota in early life reveals the existence of infant community state types (ICSTs)

Mancabelli L.;Milani C.;Turroni F.;van Sinderen D.;Ventura M.
2020

Abstract

Appropriate development of the intestinal microbiota during infancy is known to be important for human health. In fact, aberrant alterations of the microbial composition during childhood may cause short- and/or long-term negative health effects. Many factors influence the initial assembly and subsequent progression of the gut microbiota of a neonate, such as feeding type, delivery mode, gestational age, maternal metabolic status and antibiotic exposure. In the current study, the composition of the infant gut core-microbiota was explored, revealing particular variations of this core-microbiota during the first three years as influenced by delivery mode and feeding type. A multi-population cohort meta-analysis was performed by selecting 15 publicly available datasets pertaining to taxonomic profiles of 1035 fecal samples of healthy infants, as obtained by means of a 16S rRNA gene-based profiling approach. Interestingly, this multi-population cohort meta-analysis revealed great microbial complexity and specific taxonomic shifts in children older than six months, suggesting a major impact by the introduction of solid foods which prompts progression of infant gut microbiota towards that typical of adults. The taxonomic data sets employed in this multi-population cohort meta-analysis possess the statistical robustness to allow the identification of infant community state types (ICSTs). Our analysis therefore reveals the existence of specific taxonomic patterns that correspond to particular nutritional and developmental stages of early life, and that had previously been obscured by the high variability typical of such infant gut microbiota.
Multi-population cohort meta-analysis of human intestinal microbiota in early life reveals the existence of infant community state types (ICSTs) / Mancabelli, L.; Tarracchini, C.; Milani, C.; Lugli, G. A.; Fontana, F.; Turroni, F.; van Sinderen, D.; Ventura, M.. - In: COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL. - ISSN 2001-0370. - 18:(2020), pp. 2480-2493. [10.1016/j.csbj.2020.08.028]
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11381/2881432
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