Dr. Julio Alvarez

VETMD Vet Population Med
College of Veterinary Medicine
Twin Cities
Project Title: 
WGS Analysis of Foodborne Bacterial Pathogens (Campylobacter, Salmonella, and Escherichia Coli

The Center for Animal Health and Food Safety (CAHFS) at the University of Minnesota has access to both human and animal (cattle, swine, and poultry) Campylobacter and Salmonella isolates, and is deeply involved in work on foodborne zoonoses and antimicrobial resistance (AMR), looking for determinants associated with the emergence and persistence of certain zoonotic strains and AMR phenomena in humans, animals and the food chain in the U.S. Moreover, CAHFS is collaborating with European institutions enabling the comparison of similar collections of isolates with the purpose of gaining valuable insights on the potential causes and impact that the persistence of specific clones of resistant strains will have for the U.S. An ongoing research carried out at CAHFS has suggested a potential European origin of certain epidemic clones thus involving inter-continental transmission.

The objective of this research will be to use whole genome sequencing (WGS) information of isolates coming foodborne bacterial pathogens (CampylobacterSalmonella, and Escherichia coli) recovered from human and animal origin from Europe and the U.S. to perform source attribution modeling studies that could help to determine the most likely sources of infection of certain emerging zoonotic pathogens. The research will include analyses of hundreds of WGS of bacterial isolates collected in the U.S. and Europe. The researchers use the raw reads alignments for reconstructing phylogenies, and use the genome assemblies for detection of different genetic characteristics, such as antimicrobial resistance genes and virulence factors. Moreover, time-scaled phylogeny reconstruction for certain pathogens will be applied using Bayesian Evolutionary Analysis Sampling Trees (BEAST) platform. This platform requires running multiple models with long Markov chain Monte Carlo (MCMC) chains, which can be computationally demanding.

Project Investigators

Dr. Julio Alvarez
Ehud Elnekave
Shivdeep Singh Hayer
Seunghyun Lim
 
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