TY - JOUR
T1 - Early life microbial succession in the gut follows common patterns in humans across the globe
AU - Fahur Bottino, Guilherme
AU - Bonham, Kevin S.
AU - Patel, Fadheela
AU - McCann, Shelley
AU - Zieff, Michal
AU - Naspolini, Nathalia
AU - Ho, Daniel
AU - Portlock, Theo
AU - Joos, Raphaela
AU - Midani, Firas S.
AU - Schüroff, Paulo
AU - Das, Anubhav
AU - Shennon, Inoli
AU - Wilson, Brooke C.
AU - O’Sullivan, Justin M.
AU - Britton, Robert A.
AU - Murray, Deirdre M.
AU - Kiely, Mairead E.
AU - Taddei, Carla R.
AU - Beltrão-Braga, Patrícia C.B.
AU - Campos, Alline C.
AU - Polanczyk, Guilherme V.
AU - Huttenhower, Curtis
AU - Donald, Kirsten A.
AU - Klepac-Ceraj, Vanja
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/12
Y1 - 2025/12
N2 - Characterizing the dynamics of microbial community succession in the infant gut microbiome is crucial for understanding child health and development, but no normative model currently exists. Here, we estimate child age using gut microbial taxonomic relative abundances from metagenomes, with high temporal resolution (±3 months) for the first 1.5 years of life. Using 3154 samples from 1827 infants across 12 countries, we trained a random forest model, achieving a root mean square error of 2.56 months. We identified key taxonomic predictors of age, including declines in Bifidobacterium spp. and increases in Faecalibacterium prausnitzii and Lachnospiraceae. Microbial succession patterns are conserved across infants from diverse human populations, suggesting universal developmental trajectories. Functional analysis confirmed trends in key microbial genes involved in feeding transitions and dietary exposures. This model provides a normative benchmark of “microbiome age” for assessing early gut maturation that may be used alongside other measures of child development.
AB - Characterizing the dynamics of microbial community succession in the infant gut microbiome is crucial for understanding child health and development, but no normative model currently exists. Here, we estimate child age using gut microbial taxonomic relative abundances from metagenomes, with high temporal resolution (±3 months) for the first 1.5 years of life. Using 3154 samples from 1827 infants across 12 countries, we trained a random forest model, achieving a root mean square error of 2.56 months. We identified key taxonomic predictors of age, including declines in Bifidobacterium spp. and increases in Faecalibacterium prausnitzii and Lachnospiraceae. Microbial succession patterns are conserved across infants from diverse human populations, suggesting universal developmental trajectories. Functional analysis confirmed trends in key microbial genes involved in feeding transitions and dietary exposures. This model provides a normative benchmark of “microbiome age” for assessing early gut maturation that may be used alongside other measures of child development.
UR - https://www.scopus.com/pages/publications/85215758390
U2 - 10.1038/s41467-025-56072-w
DO - 10.1038/s41467-025-56072-w
M3 - Article
C2 - 39809768
AN - SCOPUS:85215758390
SN - 2041-1723
VL - 16
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 660
ER -