MCA Pilot PUI: Identification of Key Regulators of Innate Immunity to Rabies Virus in Bats

This project aims to understand how bats defend against the rabies virus, a deadly pathogen that infects the brain. While some bats can survive rabies infection, the reasons behind this resilience are poorly understood. This research seeks to uncover the immune responses and specific brain cell types that help bats fight off rabies.

Dr. William Carr, an expert in human innate immunity, will lead this effort, bringing his experience to the emerging field of bat immunology. With additional training in computational biology, Dr.

Carr will use computers and machine learning to analyze genetic data from infected and healthy bats. This study is significant for several reasons. It will provide new insights into how bat immune systems work, which could help scientists understand how other animals, including humans, respond to viral infections.

The innovative use of computational tools and high-tech methods will set a new standard for studying complex biological interactions. These tools include explainable artificial intelligence and advanced genetic analysis techniques to predict disease outcomes in bats. The broader impacts of this research extend to society as well.

By training in computational biology and developing new courses, Dr. Carr will equip undergraduates, especially those from underrepresented groups, with cutting-edge research skills. This project also aims to foster collaboration and share its findings with the scientific community, contributing to better models for studying viral immunity.

Ultimately, the work could lead to breakthroughs in preventing and treating viral diseases, benefiting public health and advancing scientific knowledge.

This project addresses significant gaps in understanding bat immunity by identifying key regulators of innate immunity to the rabies virus in bats. Despite the lethal nature of rabies, some bats survive infection, but the mechanisms behind this resilience are unclear. Dr.

William Carr, with extensive experience in human HIV immunology, will pivot his research focus to bat immunology, gaining expertise in computational biology. This research will utilize -omics-based approaches, including genomic and transcriptomic analyses, to identify key differences in bat immunity compared to other mammals. Traditional single-gene approaches fall short in addressing the complexity of host-pathogen interactions.

This study will employ explainable artificial intelligence (XAI) and network topology mining to identify predictors of disease outcomes in rabies-infected bats. Single-nuclei RNA-seq (snRNA-seq) will generate comprehensive profiles of brain cells from control and rabies-infected bats. This research includes two primary aims: (i) Generate snRNA-seq profiles in bat brains from control and rabies-infected bats to understand the complexity of immune responses. (ii) Use differential statistics and multiplex network analyses to identify mechanistic networks derived from snRNA-seq profiles in bat brains associated with rabies virus disease outcomes.

This project addresses the need for immunologists trained in computational biology to study bat immune responses. The broader impacts include developing new courses in computational biology, mentoring underrepresented minority students, and fostering collaborations. The findings will contribute to better models for studying viral immunity, potentially leading to breakthroughs in preventing and treating viral diseases.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.