Comprehensive insights from composition to functional microbe-based biodiversity of the infant human gut microbiota

Gabriele Andrea Lugli1, Leonardo Mancabelli2,3, Christian Milani1,3

  • 1Laboratory of Probiogenomics, Department of Chemistry, Life Sciences, and Environmental Sustainability, University of Parma, Parma, Italy.

Insights

Infant gut microbiome development is key for lifelong health. This study identified distinct infant gut microbial communities (ICSTs) linked to origin and health, revealing complex microbial interactions and metabolic functions.

Area of Science:

  • Microbiology
  • Human Health
  • Genomics

Background:

  • Infant gut microbiota development is critical for establishing long-term microbe-host interactions influencing health.
  • Understanding newborn gut microbial diversity and dynamics is essential for health and disease insights.

Purpose of the Study:

  • To explore microbial biodiversity and dynamics in infants during the first three years of life.
  • To identify microbial population subspecies and their coexistence patterns within different infant groups.
  • To investigate metabolic profiling and enzymatic expression for understanding health-gut microbiota interplay.

Main Methods:

  • Analysis of 10,935 infant shotgun metagenomic datasets for taxonomic and functional classification.
  • Reconstruction of 2390 chromosomal sequences from predominant taxa.
  • Integration of metagenomic and metatranscriptomic data for metabolic profiling.

Main Results:

  • Identification of eight major Infant Community State Types (ICSTs) dominated by 17 bacterial taxa.
  • Correlation of ICST distribution with infant geographical origin and health status.
  • Discovery of multistrain coexistence patterns among microbial Population Subspecies (PS) within ICSTs.
  • Highlighting distinct enzymatic expression patterns through metabolic profiling.

Conclusions:

  • Gut microbiota composition and function in newborns are influenced by origin and health.
  • Investigating the human gut requires integrated multi-omics approaches (metagenomics, metatranscriptomics, metabolomics).
  • Metagenomic data is valuable for microbial classification but may not always fully explain functional insights.

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