Jacob Lemieux

The Lemieux laboratory investigates the pathogenesis and epidemiology tick-borne and respiratory pathogens using computational and experimental methods. Our primary focus is defining and characterizing the microbial genetic factors that influence Lyme disease, a bacterial infection caused by Borrelia burgdorferi spirochetes. There is strong evidence that microbial genetic factors influence the clinical course of Lyme disease because clinical manifestations vary markedly depending on the infecting B. burgdorferi genotype; however, the specific microbial genes responsible for these differences are not known. We seek to identify and characterize the genes that contribute to the distinct clinical manifestations of Lyme disease.

We identify B. burgdorferi loci linked to clinical heterogeneity in Lyme disease using comparative genomics and microbial genome wide association (GWAS) studies. To characterize the function of candidate loci, we use bacterial genetics, genetic screens, the murine model of Lyme disease, and human specimens collected from research participants. We are particularly interested in lipoproteins expressed on the surface of the spirochete that are in contact with host tissues and immune defenses. Sequence homology and the results of prior investigations suggest that surface lipoproteins act in part to inactive the host immune system and/or promote adherence to host tissues, making them attractive targets for novel therapeutics and vaccines.

A second focus of the laboratory is linking genomic epidemiology and pathogenesis by exploiting the growing quantity of genome sequence data available on pathogenic microbes. We have developed new methods to conduct approximate phylogenetic inference using millions of SARS-CoV-2 genomes, enabling us to understand the effect of individual amino acid changes on viral fitness. The fundamental idea behind our approaches is to model genomes and lineages as a collection of individual mutations whose effects are individually inferred using model-based analyses of large-scale data. As microbial genomic datasets grow, we are interested in applying such models to other respiratory viruses and bacterial pathogens.

We also use microbial genomics to investigate the evolution and epidemiology of emerging pathogens, particularly those associated with ticks. Previous and ongoing work in the laboratory has defined the genetic basis of resistance to first-line therapy to human babesiosis caused by Babesia microti (a tick-borne Apicomplexan parasite closely related to malaria). We have a project on Powassan virus (POWV), a highly pathogenic tick-borne Flavivirus emerging in New England, to characterize the molecular factors important for infection and identify treatments for POWV infection. We welcome inquiries from graduate students interested in experimental and computational studies in any of those areas.