UTMB researchers awarded USDA funding for projects focused on screwworm detection and response

Two University of Texas Medical Branch (UTMB) projects have been selected for funding as part of a $105 million national effort supporting research to support research aimed at strengthening U.S. defenses against the New World screwworm (NWS). The announcement comes as the parasite has reappeared in Texas, highlighting the urgent need for faster, more modern detection and response tools.

The funding is part of the U.S. Department of Agriculture's New World Screwworm Grand Challenge, for which 226 applications requesting a total of $664 million were reviewed. Projects were selected based on their innovation, scientific rigor, and potential to transform national preparedness. Both projects submitted by UTMB were chosen for funding.

Project 1, led by Maureen Laroche, MS, PhD, FRES, in collaboration with Scott Weaver, MS, PhD, aims to strengthen Texas' ability to respond to NWS and evaluate the efficiency of that response. It combines advanced surveillance tools and field-driven preparedness modeling.

Two medical entomologists at UTMB proposed a multipronged approach to address two cornerstones of NWS response:

• Surveillance - UTMB will develop improved rearing protocols for the NWS flies using a local surrogate species and will use the reared flies to develop a high-throughput, affordable protein-based test to distinguish wild flies from the sterile flies released for population control. Once validated, this tool will improve the state's ability to control the efficiency of fly release programs.
• Preparedness - In collaboration with East Foundation, South Texas ranchers, and USDA collaborators, UTMB will gather field data on livestock, wildlife movement, and local environmental conditions to guide targeted effective surveillance and fly release strategies in Texas. These data will help model how NWS could spread further across different areas.

"UTMB is leveraging its position as a leader in medical and veterinary entomology and outbreak response to propose a uniquely integrated approach to respond to NWS and build preparedness for the future," Laroche said. "Our strategy is designed not only to strengthen Texas' ability to respond to NWS outbreaks but also to respond to other pests and vector-borne diseases that may threaten our producers and our food supply. In doing so, this project directly contributes to strengthening the national security of Texas and the United States."

Project 2, led by Gene Olinger, PhD, director of the Galveston National Laboratory (GNL), and George Babuadze, PhD, assistant professor in the Department of Microbiology & Immunology, is an AI-enabled rapid detection system designed to protect Texas livestock and wildlife from NWS. The effort combines a 15-minute field test, highly specific, AI-designed biosensors, and a smartphone app that interprets results and supports real-time reporting.

Over the past year, UTMB has strategically invested startup funds to build the Generative Experimental Network for Emergent System Intelligence and Synthesis (GENESIS), a secure AI environment at the GNL that powers agentic AI-assisted target discovery, protein and nanobody design, and next-generation biosensor development.

"These capabilities enable UTMB to rapidly identify high-value diagnostic targets for NWS and develop more elegant detection strategies than originally envisioned," Olinger said. "GENESIS is already supporting additional UTMB research on H5N1, mpox, and protein-binding challenges such as Alzheimer's tau protein."

Olinger said that within the screwworm project, GENESIS is specifically being used to identify optimal nanobody sequences targeting larval-derived proteases, combining structure prediction, epitope mapping, and expression optimization in E. coli. These computationally designed nanobodies serve as highly specific binding reagents for the AI-powered field diagnostic biosensor.

"As we begin the next phase of this effort, we plan to further automate these capabilities through emerging cloud-based laboratory platforms that integrate robotic instrumentation for protein synthesis and functional testing," he said.

Babuadze said these technologies have the potential to significantly reduce the time and cost required to experimentally validate AI-generated hypotheses and accelerate the transition from computational discovery to laboratory confirmation.

"The integration of AI with cloud-based robotic laboratories is ushering in a new era of biomedical research, enabling discovery cycles that once took months to be completed in weeks," he said. "This approach is already being operationalized in the screwworm project, where nanobody candidates designed computationally are being synthesized, expressed, and functionally characterized through fully automated cloud-based expression and purification platforms. This integration is reducing development timelines from months to weeks, which is critical for responding to emerging threats like the recent screwworm resurgence in Texas."

UTMB is leading the next generation of agricultural biosecurity by combining artificial intelligence with laboratory science to detect biological threats faster, protect producers, safeguard the food supply, and strengthen America's national security."

USDA's Grand Challenge

The 40 funded projects - including those from UTMB - support the USDA's four core priorities:

• Enhancing sterile fly production
• Developing modern traps and early warning systems
• Advancing therapeutics and treatments
• Strengthening preparedness through modeling and wildlife surveillance

These efforts complement ongoing USDA work at Texas A&M AgriLife Research and the University of Florida on next-generation sterilization technologies.