Researchers at the University of Galway, in collaboration with world-leading SFI research center APC Microbiome Ireland, have created a resource of more than 7,000 digital microbes – enabling computer simulations of how drug treatments work and how patients respond. The resource is a milestone in the scientific understanding of human response to drug treatments, as it opens up opportunities for computer simulations and predictions of metabolic differences between individuals, including diseases such as inflammatory bowel disease, Parkinson’s disease and colorectal cancer.
The database – called AGORA2 – builds on expertise developed when creating the first digital microbial resource called AGORA1. AGORA2 contains 7,203 digital microorganisms created from experimental knowledge in scientific publications, with a special focus on drug metabolism.
Want more breaking news?
subscription technology network‘ The daily newsletter, delivering breaking science news straight to your inbox each day.
free subscription
The resource was established by a team of scientists from the Molecular Systems Physiology Group at the University of Galway, led by Professor Ines Thiele, Principal Investigator of the APC Microbiome in Ireland.
The team’s research aims to advance precision medicine through the use of computational models.
Professor Tiller explained: “AGORA2 is a milestone towards personalized, predictive in silico simulations capable of analyzing human-microbiome-drug interactions for precision medicine applications.
“Humans are inhabited by countless microbes. Just like us, these microbes eat and interact with our environment. Given that we are all unique, each of us has an individual microbiome, and our metabolism is expected to vary from person to person.” .
“Compared to the current more prevalent ‘one-size-fits-all’ approach, the insights provided by digital microbiome databases present an opportunity for healthcare to exploit individual differences in metabolism to deliver personalized, improved ‘precision medicine’ treatments.
“In addition to our food, our individual microbiomes also metabolize the drugs we take. Therefore, the same drug may affect different people differently because of different metabolisms in different microbiomes.”
Using the digital microbial resource AGORA2, computer simulations showed that drug metabolism differs dramatically between individuals, driven by their own microbiomes.
Uniquely, AGORA2-based computer simulations were able to identify the microbial and metabolic processes of individual drugs in relation to observations in the clinical setting.
The study was published today in Nature Biotechnology.
A team at the University of Galway demonstrated that AGORA2 enabled personalized, strain-resolved modeling by predicting the drug-translating potential of the gut microbiome from 616 colorectal cancer patients and controls, which was highly variable between individuals. Large differences were observed and correlated with age, sex, body mass index and disease stage. This means the team can create numerical representations and predictions specific to different microbes.
Professor Thiele added: “Understanding our individual microbiomes and their ability to metabolize drugs represents an opportunity for precision medicine to tailor drug treatments to individuals to maximize health benefits while minimizing side effects.
“By using AGORA2 in computer simulations, our team has shown that the resulting metabolic predictions enable superior performance compared to what has been possible so far.”
Prof. Paul Ross, Director of Microbiology, APC IrelandSay: “This study perfectly illustrates the power of computational methods to enhance our understanding of the role of microbes in health and disease – and importantly, this digital platform will be an excellent resource that can lead to the development of new personalities chemotherapeutic approaches that take the microbiome into account.”
refer to: Heinken A, Hertel J, Acharya G, et al. Genome-scale metabolic reconstruction of 7,302 human microbiomes for personalized medicine. Nat Biotechnology. 2023:1-12. Two: 10.1038/s41587-022-01628-0
This article is reproduced from the following Material. NOTE: Material may have been edited for length and content. For more information, please contact the cited source.
