Disentangling TB epidemiology: The effects of immune gene diversity, gut microbiota and social networks on disease susceptibility in a natural meerkat model

• Applicant: Professorin Dr. Simone Sommer
• Subject Area: Evolution, Anthropology
• Term: from 2019 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 426141882

Tuberculosis (TB) is a devastating disease that is endemic to humans and many other mammal species, including meerkats (Suricata suricatta). Variation in individual susceptibility and resistance to TB infection exists between individuals, and identifying the underlying causes of this variation has major implications for pathogen epidemiology and disease control. However, the biological drivers that underpin an individual’s susceptibility and resistance to infectious disease (including TB) are not well understood. There is compelling evidence from laboratory studies that host genetics and gut microbes can interact to mediate host immune responses, but the extent of these interactions in natural populations and their consequences for host-pathogen dynamics are unknown. In this project, we will explore the extent to which immune genes and gut microbiota composition together shape individual TB susceptibility in a natural animal population, and integrate social network information to model key transmission routes across the study population during TB outbreaks. We will apply an exceptionally high resolution dataset on 2300 wild meerkats in the Kalahari desert, South Africa, collected over a 25 year period. This multi-layered dataset includes accurate records of behavior and movement, genetic data, and longitudinal fecal samples from virtually all individuals within the study population. Specifically, we will be able to unravel host-TB interactions, lifetime gut microbiota dynamics, the role of immune gene diversity (MHC) in life history decisions and TB resistance. We will start by examining how microbial communities prior to infection interact with host genetics to predict infection outcomes later in life. Later, we will integrate susceptibility data with social network patterns in order to build an epidemiological model aiming at identifying the main drivers of transmission. This project will not only significantly add to our understanding of the biological and social drivers of TB epidemiology, but will generate novel insights into host-microbe interactions that will provide the foundation for future research on microbial and disease ecology.

• DFG Programme: Research Grants