A research team at the University of California San Diego (UCSD) has introduced coralME, a computational tool designed to build genome-scale models of microbial metabolism, gene expression, and protein expression. The approach links genomic content to phenotype at a pace that far exceeds manual curation. It also supports investigations into how gut microbes respond to changing environmental and nutritional conditions.
The tool constructs “ME-models” for microbial species by integrating genomic, metabolic, and expression data. These models help identify how microbes acquire essential metabolites and how shifts in nutrient availability alter growth or metabolic output. “For example, we see from the models that a microbe needs a certain amino acid, but it cannot make this amino acid itself, so it either gets it from another microbe, from the human host, or from the diet the human is eating,” said Karsten Zengler, professor at UCSD. He noted that these models offer a mechanistic view of microbial activity in complex systems.
Using coralME, the team generated 495 ME-models that represent common gut bacteria. Simulations based on these models showed how diet composition influences microbial behavior. Low-iron or low-zinc diets permitted certain harmful species to persist, while diets enriched in specific macronutrients supported microbes associated with a balanced gut environment.
The researchers also incorporated microbial expression data from patients with inflammatory bowel disease. This allowed the tool to extract real-time microbial activity. “This shows what the microbes are eating, what products they are making and how they interact with other microbes and the host,” Zengler said. He compared the framework to a city map integrated with traffic information. It provides an updated view of microbial flux.
The analysis identified less acidic gut conditions in inflammatory bowel disease and reduced production of short-chain fatty acids. The models also pointed to specific taxa and interactions that contribute to these chemical shifts.
Publication Details
Tibocha-Bonilla JD, Santibáñez-Palominos R, Weng Y, Kumar M, Zengler K. Metabolism and gene expression models for the microbiome reveal how diet and metabolic dysbiosis impact disease. Cell Systems. doi:10.1016/j.cels.2025.101451
The tool constructs “ME-models” for microbial species by integrating genomic, metabolic, and expression data. These models help identify how microbes acquire essential metabolites and how shifts in nutrient availability alter growth or metabolic output. “For example, we see from the models that a microbe needs a certain amino acid, but it cannot make this amino acid itself, so it either gets it from another microbe, from the human host, or from the diet the human is eating,” said Karsten Zengler, professor at UCSD. He noted that these models offer a mechanistic view of microbial activity in complex systems.
Using coralME, the team generated 495 ME-models that represent common gut bacteria. Simulations based on these models showed how diet composition influences microbial behavior. Low-iron or low-zinc diets permitted certain harmful species to persist, while diets enriched in specific macronutrients supported microbes associated with a balanced gut environment.
The researchers also incorporated microbial expression data from patients with inflammatory bowel disease. This allowed the tool to extract real-time microbial activity. “This shows what the microbes are eating, what products they are making and how they interact with other microbes and the host,” Zengler said. He compared the framework to a city map integrated with traffic information. It provides an updated view of microbial flux.
The analysis identified less acidic gut conditions in inflammatory bowel disease and reduced production of short-chain fatty acids. The models also pointed to specific taxa and interactions that contribute to these chemical shifts.
Publication Details
Tibocha-Bonilla JD, Santibáñez-Palominos R, Weng Y, Kumar M, Zengler K. Metabolism and gene expression models for the microbiome reveal how diet and metabolic dysbiosis impact disease. Cell Systems. doi:10.1016/j.cels.2025.101451