Language

English

Publication Date

11-13-2025

Journal

Cell

DOI

10.1016/j.cell.2025.08.020

PMID

40930091

Abstract

The human gut microbiome is linked to child malnutrition, yet traditional microbiome approaches lack resolution. We hypothesized that complete metagenome-assembled genomes (cMAGs), recovered through long-read (LR) DNA sequencing, would enable pangenome and microbial genome-wide association study (GWAS) analyses to identify microbial genetic associations with child linear growth. LR methods produced 44-64× more cMAGs per gigabase pair (Gbp) than short-read methods, with PacBio (PB) yielding the most accurate and cost-effective assemblies. In a Malawian longitudinal pediatric cohort, we generated 986 cMAGs (839 circular) from 47 samples and applied this database to an expanded set of 210 samples. Machine learning identified species predictive of linear growth. Pangenome analyses revealed microbial genetic associations with linear growth, while genome instability correlated with declining length-for-age Z score (LAZ). This resource demonstrates the power of comparing cMAGs with health trajectories and establishes a new standard for microbiome association studies.

Keywords

Humans, Metagenomics, Gastrointestinal Microbiome, Metagenome, Genome-Wide Association Study, Child, Preschool, Child, Male, Infant, Female, Malnutrition, Malawi, Longitudinal Studies, Oxford Nanopore Technologies, Pacbio HiFi, childhood undernutrition, human gut microbiome, linear growth faltering, long-read sequencing, metagenomics, microbial GWAS, microbial pangenome, stunting

Published Open-Access

yes

Download

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.