Using Whole Genome Sequencing Data to Improve Mycobacterium Bovis Outbreak Investigation Efficiency
Fellow: Kristina Ceres
Mentor: Yrjo Grohn
DESCRIPTION (provided by applicant):
Despite over 100 years of a national eradication program, bovine tuberculosis remains an important cattle disease in the United States and around the world. Mycobacterium bovis, the causative agent of bovine tuberculosis, has a wide host range including humans, making disease control in animal populations a public health priority. Bovine tuberculosis is difficult to control because of a long latency period before infected animals show clinical signs of disease, and because transmission patterns are often ambiguous due to limited animal movement records, cross-species transmission from infected wildlife, and potential zoonotic transmission from humans to animals.
Our central objective is to utilize M. bovis whole genome sequencing data to increase efficiency in outbreak investigations. Our supporting objectives are to: 1) Estimate time since herd infection and investigate drivers of variation in M. bovis evolutionary rate 2) Predict the geographical source of outbreaks by analyzing pan-genomic population structure.
Through close collaboration with partners at the National Veterinary Services Laboratory and the Center for Epidemiology and Animal Health, predictive models developed in this proposal will be incorporated into ongoing and future M. bovis outbreaks to narrow down the source of an outbreak in both time and space. Our project aligns closely with the Farm Bill Priority area: Animal health and production and animal products. Research produced in this project will have a direct impact on production animal health by helping to decrease M. bovis transmission, contributing to the ultimate goal of eliminating bovine tuberculosis from the United States and the world.