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Two women in lab coats work with a sample in a tube in a laboratory.

Microbiome scientist uses AI to redefine the gut-brain axis and deep-sea ecosystems

By Hannah Ashton

Maude David’s research sits at the crossroads of microbiology, neuroscience and artificial intelligence — an intersection that may hold the key to understanding some of the most complex disorders affecting the human brain and unlocking the secrets of deep-sea ecosystems.

Scientists have long recognized the gut-brain axis as a critical communication pathway, but only recently have they begun to uncover how the trillions of microbes in our gut influence brain function and behavior. David’s research is at the forefront of this field, using microbiome analysis and artificial intelligence to investigate links between gut bacteria and neurological disorders like autism. Her work deepens our understanding of these complex interactions and opens new possibilities for treatments. By applying AI to both human health and environmental microbes, David is pioneering a data-driven approach that could transform neuroscience and microbiology alike.

Microbiome of the human body

The gut-brain axis is a complex, bi-directional communication network linking the gut and central nervous system. The gut doesn’t rely on just microbes to communicate with the brain, but sometimes nutrients also.

For example, when you consume sugar, specialized sensory cells in your gut detect it and send signals to the nervous system, helping to regulate metabolism, appetite and energy balance.

"So, in a millisecond, the bacteria or their metabolites can ‘touch’ your brain.”

Researchers have long known that the gut-brain axis exists, but only recently have they begun to unravel how the trillions of microbes residing in the gut influence brain function and behavior.

“I am fascinated by the complex relationship we have with our microbiome,” David said. “I work specifically on this pathway where the microbes could potentially modulate sensory cells, that’s two synapses in your brain. So, in a millisecond, the bacteria or their metabolites can ‘touch’ your brain.”

Her lab is particularly interested in what role this communication network may play in neurological disorders like autism spectrum disorder (ASD). Using crowdsourced data, David and collaborators discovered that children with ASD have distinct differences in the composition of their gut microbiota compared to their neurotypical siblings. The researchers recruited 111 families that each have two children — one with autism and one without — born within two years of each other and aged two to seven years old.

The researchers collected stool samples from the children at three different time points, two weeks apart. They found eight bacterial genetic sequences that were more likely to be present in the guts of children with autism than in their non-autistic siblings, and three sequences that were less likely.

A follow-up study releasing later in 2025 found further interesting results linked to metabolites, small molecules produced during metabolism. These new findings are exciting because understanding the specific metabolic pathways altered in developmental and neurological disorders could pave the way for novel therapies targeting the gut microbiome.

“There have been very few drugs in the last 20 years focused on neurological disorders. It’s really the etiology, or causes, that are unknown. There is a big gap in understanding, and basic science can help bring solutions,” she said.

A woman in a blue suit jacket holding a stuffed giant microbe.

Maude David holds a stuffed version of lactobacillus bulgarius, the main bacteria used in the production of yogurt. As a beneficial probiotic, it helps maintain a balanced gut flora, which is essential for overall health. The bacteria is produced by the company Giantmicrobes.

Microbiome of the deep sea

Beyond her hands-on lab work, David is pioneering artificial intelligence applications in microbiome research. By training machine learning models on massive datasets, her team is discovering how to predict patterns and identify microbial signatures linked to different conditions.

Her AI approach functions similarly to how a person might read thousands of books to develop a deep understanding of a subject before applying that knowledge to something new. Instead of analyzing each microbiome sample from scratch, her team feeds AI models vast amounts of microbial sequencing data, allowing the system to learn and recognize relationships between the different microbes. These models can then be applied to help classify conditions such as inflammatory bowel disease or colorectal cancer with greater accuracy.

“It is awesome, because the model can remember relationships that us humans might not. It’s finding these complex patterns,” David said.

One of the major challenges in microbiome research is the sheer volume of data involved. Each individual has a unique microbiome comprising thousands of different microbial species, each interacting in complex ways. Traditional methods of analyzing these communities can be time-consuming and require extensive resources. AI provides a way to quickly process and interpret large datasets, identifying patterns that can reveal valuable insights.

Her latest National Science Foundation study continues to push the limits of what AI can do. With a $540K grant, David is applying deep learning to analyze oceanic microbial ecosystems, an extension of her expertise in microbiome research.

The deep sea is a crucial, yet poorly understood driver of global biogeochemical cycles, the movement of essential elements like methane and nitrogen. These cycles regulate ecosystem function, influence climate and support life.

“We are looking at microbes in the ocean and researching how we can use AI to discover what role unknown genes play in methane seeps off the coast of Oregon and Washington,” she said.

Methane seep habitats, areas where methane gas escapes from the sea floor, are unique, diverse areas nourished by methane-consuming microbes. However, many of the genes involved in these deep-sea cycles remain unidentified, limiting our understanding of how these ecosystems function and their impact on global biogeochemical processes.

To analyze these complex environments, researchers will develop two AI models designed to decode gene functions. The first model will categorize genes into pathways by studying how they appear together in microbial communities. The second will use generative AI to predict the functions of unknown genes based on protein sequences and text-based data. Together, these models will help scientists identify genes responsible for each of the cycles identified.

The main outcome will be a scalable approach to artificial intelligence that will advance key questions in earth system science. Understanding the genetic mechanisms behind biogeochemical processes is crucial for predicting how ocean ecosystems respond to environmental changes.

The results of this study will include exhibits by artists involved in the research as well as a documentary about how AI can harness big data to help advance the understanding of earth systems.

As science continues to reveal the hidden influence of the microbiome, one thing is clear: critical solutions lie in understanding the powerful role microorganisms play in our bodies and our environment. David’s research has us on the right path to new understandings.