Credit: Julia Pollack, University of Illinois.
The human gut consists of a complex community of microbes that consume and secrete hundreds of small molecules – a phenomenon called cross feeding. However, these processes are difficult to study experimentally. A new study published in Nature Communications, Uses models to predict cross-feeding interactions between microbial species in the gut. Predictions from such computational methods could ultimately help clinicians gain a more comprehensive understanding of bowel health.
It is known that the microbial community or microbiome in the gut affects human health. Previous studies have focused on identifying the types of microbes present. Unfortunately, this information is not enough to understand the microbiome.
“The gut environment is formed by small molecules known as metabolites, which are secreted by microbial communities,” said Sergey Maslov (BCXT / CABBI), professor of bioengineering and scientist at Bliss College. “Although these metabolites can be measured experimentally, they are cumbersome and costly.”
The researchers had previously published a study in which they used experimental data from other studies to model the fate of metabolites as they pass through the gut microbiome. In the new study, they used the same model to predict previously unidentified new bacterial processes.
“What we eat passes into our intestines, and there is a chain of microbes that release their metabolites,” said Akshet Goyal, a postdoctoral fellow at the Massachusetts Institute of Technology and collaborator in Maslov’s lab. “Biologists have measured these molecules in human faeces, and we have shown that you can use mathematical models to predict the levels of some of them.”
Measuring each metabolite and trying to understand which microbe it may trigger can be difficult. “There is a huge world of possible cross-feeding interactions. Using this model, we can help conduct experiments by predicting which experiences are most likely to occur in the gut,” Goyal said.
The model was also supported by the genomic annotations, which explain the microbial genes responsible for processing the metabolites. “We are confident in our modeling predictions because we also examined whether microbes contain the genes needed to carry out the associated interactions with them. About 65% of our predictions were supported by this information,” said Veronica Dupinkina, a PhD student in bioengineering.
The researchers are now working to refine the model by including more experimental data. Different people have different strains of the gut microbiome. Although these different strains share many genes, they differ in their capabilities. “We need to collect more data from patients to understand how different microbial communities behave in different hosts.”
“We are also interested in determining how quickly microbes consume and excrete metabolites,” said Tong Wang, PhD student in physics. The model currently assumes that all microbes consume metabolites at the same rate. In fact, rates vary and we need to understand them to capture the metabolite composition in the gut. “
Study “Environment-directed prediction of cross-reactions”
In the human gut microbiome “at https: /
Funding: Akshet Garg is supported by the Gordon and Betty Moore Foundation as a Fellow in Physics of Living Systems.