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Gut bacteria reveal ancient ties to human migrations across continents, genetic analysis suggests

Gut bacteria reveal ancient ties to human migrations across continents, genetic analysis suggests

phys.org 07.10.2026 17:01 7 views
As waves of humans left Africa tens of thousands of years ago, eventually populating the entire planet, they were joined on their world-conquering ride by the trillions of microorganisms that compose the gut microbiome.

This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: As waves of humans left Africa tens of thousands of years ago, eventually populating the entire planet, they were joined on their world-conquering ride by the trillions of microorganisms that compose the gut microbiome. These bacteria, viruses and fungi in our intestines play essential roles in enabling our bodies to function properly, from digesting fibrous food to making vitamins and training our immune systems.

The microbiome has emerged as a focus of intense study due to evidence that lifestyle affects its composition, which in turn can affect health. People living in industrialized countries show a profound loss of microbiome diversity compared with people living nonindustrialized lifestyles. People in industrialized countries suffer from autoimmune diseases, type 2 diabetes, obesity and other chronic conditions that are rare among nonindustrialized groups, raising the important but still unresolved question of whether microbiome loss contributes to these diseases.

A new study led by Stanford University researchers and scheduled for publication Oct. 7 in Nature has attempted to answer the question of whether Homo sapiens hosted a characteristic and diverse microbiome going back millennia. Gaining insight into which, if any, long-term residents of the microbiome coevolved with humans could point to ways to investigate how the loss of microbial diversity through industrialization affects human biology. For their study, the researchers conducted the first deep comparison of the microbiomes of the Hadza in Tanzania—one of the world's few remaining hunter-gatherer groups—and the Tsimane, Indigenous forager-horticulturalists living in the Bolivian Amazon whose lifestyles have had comparatively limited exposure to industrialization.

Although the ancestral human populations that gave rise to the two groups became geographically separated tens of thousands of years ago, the Hadza and Tsimane share over 1,200 bacterial species, nearly 90% of which were identified in the highly diverse Tsimane microbiomes. Most of those species—about 60%—are rare or completely absent in industrialized populations' microbiomes. Using several complementary population genetics analysis techniques, the researchers estimated when microbial strains separated.

For many species, those estimates correspond to the time frame of major prehistoric human migrations out of Africa and into the Americas. The ultimate takeaway: Many microbial lineages in these contemporary populations have deep evolutionary roots extending back through ancient human migrations. "Our study establishes that the hundreds of bacterial species that are rare or missing in industrialized microbiomes were ancient companions of ours as we migrated around the globe, likely passed from generation to generation for millennia," said Justin Sonnenburg, Ph.D., a professor of microbiology and immunology, the Alex and Susie Algard Endowed Professor and the study's senior author.

"This long-term association has implications for how such recent biodiversity loss in our microbiome may impact our biology and thus our health." For the study, the researchers used deep metagenomic sequencing, a method that characterizes the microbes present in a sample by reading all the letters representing the building blocks of DNA in that sample. Millions of small sequences of DNA are generated, with overlapping stretches of letters indicating where the small sequences match up into longer sequences. Those long sequences are then compared with databases of microbial genomes to identify the detected organisms.

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