Mel Grillo

As I enter the second year of my PhD at the University of Connecticut, I bring with me developed techniques for analyzing large, untargeted metabolomics datasets.

During my first year, I attended a workshop for the Collaborative Microbial Metabolite Center where I learned about free software options for students and presented to peers and professionals about my early findings on how parasitic infection influenced metabolomic variation of Vancouver Island stickleback populations. I coauthored a paper recently approved for publication that used these same techniques to identify population-level variation in Alaska populations, which demonstrates my efficiency and experience. This paper concluded that both ancestry and habitat likely influence metabolomic variation between populations.

Metabolomics research is broadly applicable, and the evolutionary biology angle is lacking. As the metabolome forms a tight connection with phenotype, candidate metabolites associated with disease, stress, and other phenotypes can be identified. This has implications for ecosystem conservation, as knowing pathways associated with environmental stressors may aid early identification of ecosystem stress. It can further understanding of biodiversity, and how metabolic expression differs between populations and individuals.

As the metabolome can be assessed using many types of biological specimens, this offers the potential for less invasive methods of disease and contaminant testing. For example, if you could sample a less threatened fish like a stickleback to identify stresses on a threatened species.

Using the metabolome to solidfy the connection between genotype and phenotype will help climate prediction, disease prediction, and establish a more comprehensive understanding of the biochemical processes maintaining organismal phenotypes.

October 2026