Gut bacteria reveal hidden evolutionary lineages tied to aging and disease

The human gut harbors a complex ecosystem of trillions of microorganisms (the microbiome), which influences digestion, the immune system and metabolism. A research team led by the University of Vienna has used the “reverse ecology” analytical approach to demonstrate that many known gut bacterial species consist of several evolutionarily distinct groups that have adapted to different conditions in the gut. Some of these populations are associated with advanced age, chronic inflammatory bowel diseases, colorectal cancer and type 2 diabetes. The findings have now been published in Nature and may in future improve the search for biomarkers and, in the long term, enable more precise therapies.

Microbiome studies usually classify bacteria into whole species or genetically similar groups. While these categories are practical, they do not necessarily reflect the populations that have adapted to different conditions within the human body. As a result, it often remains unclear which bacteria are associated with diseases, which are merely incidental—and which may offer protection. This raises a key question: can more precise biological units be identified that have emerged through adaptation and occupy different ecological niches in the gut?

The research team analyzed thousands of bacterial isolates from the human gut, as well as extensive metagenomic data—that is, the complete genetic information of microbial communities in the sample—from people in different countries and across various age and health groups. Using a newly developed bioinformatic method within the framework of “reverse ecology”—an approach that infers ecological adaptations from genomic data—the researchers searched for genetic traces of successful adaptation.

More than one species

Particularly interesting were indications of so-called “genome-wide selective sweeps“—processes in which an individual acquires a beneficial mutation and thereby displaces other, closely related individuals. On the one hand, this leads to a loss of diversity; on the other, it gives rise to populations of individuals that are very homogeneous in terms of both kinship and function, and which therefore stand out clearly from one another in the dataset. The analysis showed that many known gut bacterial species branch into several such lineages. These populations appear to differ in the conditions under which they thrive particularly well.

“If you don’t just count species but take evolutionary adaptation into account, you can identify the biologically relevant units in the microbiome much more accurately,” says lead author Xiaoqian Annie Yu, Centre for Microbiology and Environmental Systems Science (CeMESS), University of Vienna. “Even within the same bacterial species, some populations occur more frequently than others in certain diseases. When all are considered together, this often remains hidden.”

Global spread within a few decades

The researchers also found evidence that highly competitive populations can spread rapidly across continents—in some cases within a few decades. Until now, such a pattern has been observed primarily in pathogens.

“Our findings show that gut bacteria are also more dynamic than previously thought. Well-adapted strains can spread internationally and occupy new ecological niches,” says study leader Martin F. Polz from the University of Vienna.

This suggests that it is not only diet, medication or lifestyle that shape the microbiome, but that transmission processes between people could also play an important role.

New perspectives for medicine and diagnostics

The study opens up new possibilities for microbiome research. Instead of linking entire bacterial species to diseases, it may in future be possible to specifically target those populations that are actually significant. This could improve the search for biomarkers and, in the long term, enable more precise therapies—for example, by specifically promoting beneficial bacterial strains or suppressing problematic ones. As a next step, the team intends to investigate which genes distinguish the identified populations from one another and what biological functions are associated with them.