Bromoform is a chemical that acts to significantly reduce enteric methane production levels in ruminant animals.
The molecule is found naturally in a range of seaweeds. Trial work has already confirmed that bromofrom can act to reduce methane production levels in cattle by between 80 and 90%.
However, there is one major drawback – the molecule is a carcinogen, totally limiting its inclusion in cattle rations on human food safety grounds.
As a result, the search is now on to find bromoform-equivalent chemistries that are safe to include in the farming and food change.
Significantly, research scientists working in the Agricultural Research Service (ARS) of the United States Department of Agriculture (USDA), in tandem with colleagues at Iowa State University, have identified the role for combined generative artificial intelligence (AI) technologies in this context.
“We are using advanced molecular simulations and AI to identify novel methane inhibitors based on the properties of previously investigated inhibitors, such as bromoform.
“We are leading the computer simulation and AI work, while ARS is taking the lead in identifying compounds and truth testing them using a combination of laboratory and live cattle studies,” confirmed Matthew Beck from Iowa State University.
Methane production levels
Publicly available databases that contained scientific data collected from previous studies on the cows’ rumen have been used to build large computational models.
AI, along with these models, was used to predict the behaviour of molecules and to identify those that can be further tested in a laboratory.
The results from the laboratory tests feed the computer models for AI in order to make more accurate predictions, creating a feedback loop process known as a graph neural network.
Prof. Ratul Chowdhury, from Iowa State University explained:
“Our graph neural network is a machine learning model, which learns the properties of molecules, including details of the atoms and the chemical bonds that hold them, while retaining useful information about the molecules’ properties to help us study how they are likely to behave in the cow’s stomach.
“We studied their biochemical fingerprint to identify what makes them do the job successfully as opposed to the other 50,000 molecules that are lurking around in the cow’s rumen but don’t actively stop the production of methane.
“This study successfully demonstrated that 15 molecules cluster very close to each other in what we call a functional methanogenesis inhibition space, meaning they seem to contain the same enteric methane inhibition potential, chemical similarity, and cell permeability as bromoform.”
Scientists believe AI can play a significant role in understanding how known molecules interact with both proteins and the microbial community of the rumen and thereby discover novel molecules and potentially key interactions within the rumen microbiome.
This type of predictive modelling can be particularly helpful for animal nutritionists.
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