PhD, Brown University (2010)
Postdoctoral training: Harvard University/Marine Biological Laboratory
Postdoctoral training: The University of Connecticut
Bioinformatics and Statistics Core, Wadsworth Center, New York State Department of Health
My research focuses on clarifying the phylogenetic relationships among microbial organisms and understanding microbial genome evolution, including the contributions of horizontal gene transfer and endosymbioses to shaping genomes and accelerating adaptive evolution. As a member of the Bioinformatics and Biostatistics Core at the Wadsworth Center, I am involved in a diverse set of clinical and research projects. I routinely perform molecular analyses with next-generation sequencing data to characterize microbial populations in various environments, determine phylogenetic relationships among microbes, assess transmission dynamics of various pathogens and ascertain their phylogeographic histories, detect mutations associated with drug resistance, and elucidate the evolutionary processes involved in acquiring antibiotic resistance.
- Microbial genome evolution
- Pathogen transmission dynamics
- Evolution of drug resistance
- Genes & Genomes
Current major activities
- SARS-CoV-2 surveillance
Sample of recently completed studies
Russell A, O’Connor C, Lasek-Nesselquist E, Plitnick J, Kelly JP, Lamson DM, et al. Spatiotemporal analyses of 2 co-circulating SARS-CoV-2 variants, New York, USA. Emerg Infect Dis. 2022 Mar. https://doi.org/10.3201/eid2803.211972
Mishra S, Lasek-Nesselquist E, Mathur A, Ma Z, Boonthaworn K, O'Donnell N, Sui H, Pata JD, McDonough KA, Jayachandran P, Malik M. Phenotypic and genetic changes associated with the seesaw effect in MRSA strain N315 in a bioreactor model. J Glob Antimicrob Resist. 2022 Jan 24;. doi: 10.1016/j.jgar.2022.01.013. [Epub ahead of print] PubMed PMID: 35085792
Lasek-Nesselquist E, Johnson, MD.
A phylogenomic approach to clarifying the relationship of Mesodinium within the Ciliophora: a case study in the complexity of mixed-species transcriptome analyses.
Genome Biol Evol. (2019) 11 3218-3232. DOI: 10.1093/gbe/evz233