Abstract:
Background
People living in industrialized and non-industrialized settings harbor distinct gut microbiomes shaped by differences in diet, lifestyle, and environment. Understanding these variations and their correlations with demographic and health factors is essential for interpreting microbiome function across populations. Metagenomic sequencing provides valuable insights into microbial communities, but traditional workflows often lack consistency and strain-level resolution, limiting their ability to reveal fine-scale differences. High-resolution analysis is therefore necessary to capture subtle lifestyle-related influences on microbial diversity.
Methodology
We analyzed 149 metagenomic studies comprising over 40,000 samples, applying established computational tools for strain-level resolution and species-level classification. DADA2 was used for Amplicon Sequence Variant (ASV) inference, while SPINGO enabled species-level taxonomic assignment. To assess microbial diversity, we employed Shannon indices (alpha diversity), Euclidean distances with PCoA (beta diversity), and CLR normalization for compositional correction. Procrustes and Mantel tests were further used to examine associations between microbial community structure, lifestyle groups, and health- related variables.
Findings
Across the datasets, distinct patterns in microbial diversity and taxonomic composition were observed between industrialized and non-industrialized cohorts. Certain species showed lifestyle-linked differences in abundance and diversity, while interspecies associations appeared consistent across populations. These patterns suggest lifestyle exerts a measurable influence on microbiome structure without erasing underlying microbial relationships.
Conclusions
This study highlights how industrialization and lifestyle factors shape microbial diversity and community composition. By systematically applying advanced analytical methods across diverse datasets, we provide insights into correlations between lifestyle, microbial variation, and health-related factors. These findings contribute to a broader understanding of the interplay between environment, lifestyle, and the gut microbiome, offering directions for future microbiome research.
