Pathogen detection and transmission in wildlife reservoirs
More than 60% of all human-affecting pathogens are zoonotic (passed between animals and humans) and nearly three fourths of these originate in wildlife. Encroachment into animal habitats and increased urbanization are bringing wildlife into closer contact with human and livestock populations further increasing the odds and severity of zoonotic disease outbreaks. Despite their importance, our understanding of pathogen prevalence and transmission patterns in in many wildlife reservoirs is very limited, largely due to challenges associated with reliable sample access. Our group is working on developing, testing, and implementing accurate and cost-effective bacterial and fungal pathogen detection approaches to enable sustainable long-term monitoring and surveillance of wildlife reservoirs. Our focus is on one such important wild animal order, Chiroptera (bats), which is a very successful mammalian order with more than 1,200 species of bats distributed across all regions of the planet, except the Arctic, Antarctic, and some island chains. Our efforts here are geared towards:
  • Developing high-throughput, accurate, and cost-effective PCR amplicon sequencing based panels for pathogen detection.
  • Using indirect and non-invasive sample types (fecal/buccal/hair) to probe targeted animal populations
  • Understanding the prevalence and transmission patters of zoonotically relevant bat pathogens
  • Understanding the impacts of bat gut microbiota on bat-dominated subterranean ecosystems
Microbial forensics via minority and rare variant profiles
In situations where bacterial pathogens are used in a course of a criminal activity or a bioterrorism event, identification of the exact species and strain used (the "what is it?" question) is reasonably straightforward, provided that a sample with sufficient genetic material can be collected for testing. However, answering the "where did it come from?" question remains difficult, particularly for clonal bacterial pathogens (e.g. B. anthracis, F. tularensis) that are characterized by low genetic variability within bacterial strains. Our work aims to address one of the major questions in microbial forensics: "did query sample A come from source sample B"? Here, we leverage the advances in High Throughput Sequencing technologies to enable sample attribution via rare variants - SNPs and indels present in very low frequencies in bacterial populations (as low as 0.1%).