Two UCSB-led projects selected for DOE’s Genesis Mission

Teaching AI how communities of microbes work

O’Malley’s project, “Precision Microbiome Engineering in Anaerobic Communities: From Deconstruction to Bioproduction,” seeks to predict how communities of microorganisms behave, a challenge that becomes increasingly complex as species interact, compete and respond to changing conditions. 

“Biology is incredibly unpredictable,” said O’Malley, the Cliff R. Scholle Endowed Chair of Chemical Engineering. “Once you bring many organisms together, it becomes very difficult to know what they will do. We want to collect enough high-quality data that AI can begin to recognize the patterns and help us design microbial communities that produce a result we want.”

Her team will study anaerobic microbes, organisms that live without oxygen. In nature, these communities help break down tough plant material. The researchers want to learn how to direct them to convert plant waste into medium-chain fatty acids, or MCFAs, which are chemical building blocks used to make products including fuels, bioplastics, detergents, medicines, personal-care products and advanced materials. Natural sources are limited, so finding an efficient way to produce them from waste could offer a more sustainable alternative.

The long-term goal is simple to describe, even if it is difficult to achieve: start with a waste material, choose a useful chemical, and assemble the right microbial community to make it.

“We are trying to discover the rules for building a microbiome,” O’Malley said. “Which microbes should be combined? What should they be fed? What conditions help them produce the chemical we want? AI can help us sort through far more possibilities than people could test by hand.”

A faster way to conduct biological experiments

The experimental work will take place in UCSB’s BioFoundry for Extreme and Exceptional Fungi, Archaea and Bacteria, known as ExFAB, a center funded by the National Science Foundation. Its automated anaerobic chamber is a specialized environment that allows robots and scientific instruments to conduct thousands of experiments without exposing the microbes to oxygen. 

ExFAB’s ability to combine large-scale automation with an oxygen-free environment is a capability O’Malley said is not available at any other academic facility. Without it, researchers would have to handle samples individually inside smaller chambers, sharply limiting the number and complexity of experiments they could perform.

“These microbiomes are entirely anaerobic, so this project could not really be done anywhere else,” O’Malley said. “ExFAB gives us the ability to study them at a scale and with a level of control that simply was not possible before.”

In a traditional laboratory, researchers often grow cells in individual flasks or vials, which requires space and time, limiting how many experiments can be performed at once. ExFAB miniaturizes experiments into small wells arranged on plates, allowing robots housed within the anaerobic chamber to test many samples at the same time. For this project, researchers estimate that the platform can screen about 8,000 individual microbes or microbial communities each week, generating more than 100,000 microbes during the first four months. 

An AI system will analyze the results, recommend the next experiments and learn from each round of testing to identify promising combinations of microbes, nutrients and growing conditions. 

“AI cannot replace the experiment or take the measurement,” O’Malley said. “It needs reliable data from the real world. What excites me is that we are creating a platform that can generate that data at a scale that has not been possible before and then use it to make the next experiment smarter.”

The project also reflects UCSB’s broader philosophy of investing in shared research infrastructure in anticipation of future applications. By building facilities such as ExFAB around emerging scientific needs, the university creates capabilities that researchers can use to pursue questions and compete for national initiatives like the Genesis Mission.

“You build the right core instrumentation at the right time, in the right place and around the right people, and it opens doors,” O’Malley said. “UCSB is well positioned for this kind of work because it has invested in foundries and shared facilities that allow us to do things other institutions cannot.” 

Bringing together the right expertise

The project combines ExFAB’s distinctive experimental capabilities with expertise in machine learning, genome modeling and genetic engineering from UCSB, Lawrence Berkeley National Laboratory, UC Berkeley and Cerebras Systems. O’Malley will lead the overall project and direct the experiments conducted with ExFAB’s automated anaerobic platform.

Hector Garcia Martin of Lawrence Berkeley National Laboratory will lead the use of a machine-learning system called the Automated Recommendation Tool, or ART, to analyze data from ExFAB and identify future experiments. At UC Berkeley, Ben Rubin will model bacterial genomes, and Brady Cress will test whether changing specific genes can increase production of the desired fatty acids. Michael James of Cerebras Systems will support the use of large-scale AI analysis. 

“This is a problem that no one laboratory could solve alone,” O’Malley said. “Our collaborators bring different pieces of the puzzle, from machine learning and genome modeling to genetic editing. By connecting those capabilities to ExFAB, we can test what the AI predicts and learn from what actually happens.”

Phase I will concentrate on guiding microbes to make MCFAs. A second phase could expand on the processes of breaking down plant waste and could explore additional products, starting materials and microbial communities.