In Arkansas, poultry is not just agriculture. It is a cornerstone of the state’s economy. In 2024, Arkansas produced roughly 1.036 billion broilers, and the broiler industry was associated with about $5.62 billion in production value and nearly 141,000 supported jobs statewide. But like any large-scale livestock sector, the poultry industry faces a constant threat from disease.
At the University of Arkansas Division of Agriculture, Aranyak Goswami uses advanced genomics and machine learning to address that challenge.
Goswami, a computational biologist affiliated with the university’s animal science and poultry science programs, is leading research that aims to predict which bacterial genes are responsible for disease outbreaks in poultry. The work focuses on a bacterium called Enterococcus cecorum, a pathogen that can infect chickens and reduce the health and productivity of poultry flocks.
Even relatively limited disease events can create wider economic consequences in an industry operating at such scale. In commercial poultry, losses are not limited to mortality. They also show up in slower growth, poorer feed efficiency, condemnations at processing, added treatment costs and less stable throughput across the supply chain.
“The goal of the project was to provide predictive markers that industry stakeholders can use,” Goswami said. “By analyzing the whole genome, we can identify genes that are likely responsible for disease.”
Rather than focusing on one gene at a time, Goswami’s team analyzed the complete genetic blueprint of the bacterium. Using publicly available genomic data from more than 200 bacterial samples, the researchers built a computational system capable of scanning bacterial DNA and identifying clusters of genes linked to infection.
The process relies heavily on machine learning, a branch of artificial intelligence that allows computers to detect patterns within large datasets. In this case, the technology searches for what microbiologists call pathogenicity islands, or groups of genes that give bacteria the ability to cause disease.
Traditionally, scientists must test each gene individually to determine whether it contributes to infection. That can mean studying hundreds or even thousands of genes in a painstaking laboratory process. Goswami’s system dramatically reduces that burden.
“Instead of testing thousands of genes experimentally, we can narrow the list down to maybe 30 or 40 candidates,” he said. “That saves an enormous amount of time and resources for the researchers doing the experimental work.”
For Arkansas poultry producers, the benefits are practical, as well as scientific. By identifying disease-causing genes more quickly, researchers and industry partners can respond faster to emerging pathogens, focus validation efforts more efficiently, and potentially develop new interventions or vaccines to prevent infections. Over time, even partial reductions in disease-related losses could translate into meaningful economic value for producers, processors and the broader poultry supply chain.
The research is being conducted in collaboration with Cobb-Vantress, one of the world’s leading poultry genetics companies. That partnership helps connect Goswami’s computational science to real-world industry needs and increases the likelihood that promising findings can be tested, validated and applied in commercial settings.
“This project is directly connected to the poultry industry,” Goswami said. “It started with samples collected from poultry farms in Arkansas, so the work is very much rooted in the state’s agricultural ecosystem.”
While the immediate focus is poultry health, the research may eventually extend far beyond Arkansas farms. Closely related bacteria can infect humans, as well, and Goswami believes the computational pipeline developed in his lab could help scientists identify disease-causing genes in a wide range of pathogens.
“The pipeline we designed is scalable,” he said. “Although we applied it to a poultry pathogen, the same approach can be used to study bacteria that infect humans.”
The project was supported in part by funding from the Arkansas Research Alliance, which provides seed funding for research with potential economic impact. In this case, that support is helping move a research idea toward practical use in an industry that is deeply embedded in Arkansas’ economy. For Goswami, the support helped launch what has become a major milestone for his lab.
“This project helped us accomplish almost everything we originally set out to do,” he said.
In a state where poultry is a major driver of jobs, production and regional economic activity, research that helps identify disease risk earlier and more accurately has value well beyond the lab. It can strengthen producer decision-making, support more stable processing operations, and help position Arkansas as a leader in translating agricultural research into commercial and economic outcomes.
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