The mammalian gut teems with microbes that interact with each other dynamically to maintain the host’s health. An imbalance, or dysbiosis, in the gut microbiome is linked to diseases ranging from metabolic disorders to cancers.1However, a majority of gut microbiome dysbiosis research focuses only on identifying bacterial taxa that differ between healthy and diseased states, not their interactions.
Now, by looking at community-wide dynamics, researchers discovered that healthy and diseased gut microbiomes behave as distinct ecological states.2 Using this information, the researchers developed a metric, the ecological network balance index (ENBI), that measures whether positive or negative interactions dominate microbial communities. Their findings, published in Science, offer a noninvasive tool to distinguish between healthy and diseased states and track disease progression.
“Instead of asking which bacteria are there, we started asking how they are related to other bacteria,” said study coauthor Juan Bonachela, a bacterial ecologist at Rutgers University in a statement. To do so, Bonachela and his colleagues built theoretical models simulating gut bacterial dynamics. They accounted for the flux of nutrients, new immigrating bacterial species, and metabolic conversions in their framework. This model reliably captured already-established features of complex interactions within real microbiomes.
“At first we were just testing whether the model could reproduce basic features of real microbiomes,” said study coauthor Roberto Corral López, a microbiome researcher at the University of Granada in the statement. “But very early on, we saw that it naturally produced two distinct patterns.”
The researchers observed that the dynamics of the simulated community indicated two different states, likely signifying distinct health statuses: one marked by diverse microbes competing for survival, and the other where only a few lineages dominated. The latter state also exhibited fewer enzymes and metabolites compared to the former, suggesting it was a more tight-knit community as fewer bacteria metabolized resources through just a handful of pathways.
The researchers then compared their model with gut microbe DNA obtained from healthy volunteers and those with intestinal diseases. These patterns mirrored their simulations. While healthy microbiomes exhibited diverse lineages, diseased microbiomes mimicked the second state predicted by the model. “That’s when we realized we were capturing something fundamental about how these communities reorganize in disease,” said Corral López.
Bonachela, Corral López, and their team calculated the differences between the net interactions of bacteria in healthy and dysbiotic states to generate an ENBI . They then measured the ENBI for their model as well as from metagenomic data of healthy people and those with inflammatory bowel disease, colorectal cancer, and other intestinal disorders. Gut microbiome dysbiosis consistently exhibited ENBI values reflecting a shift toward increasingly close-knit communities.
According to Bonachela, studying community-wide microbiome dynamics and their shifts via stool samples could help doctors identify problems noninvasively. Corral López added that this work could improve the efficacy of microbiome-based treatments such as fecal microbiota transplant or probiotics. “Our work opens up the possibility of matching microbial communities based on how their interaction networks fit together, rather than just which species are present,” he said. “That could help us design treatments that are tailored to each patient’s microbiome instead of relying on trial and error.”
- Cho I, Blaser MJ. The human microbiome: At the interface of health and disease. Nat Rev Genet. 2012;13(4):260-270.
- Corral López R, et al. Imbalance in gut microbial interactions as a marker of health and disease. Science. 2026.
