Document Type

Honors Thesis




Erin Grey

Committee Members

Benjamin King, Michael Kinnison

Graduation Year

May 2023

Publication Date

Spring 2023


Wild Atlantic salmon in the Gulf of Maine (GOM) is a Distinct Population Segment (DPS) that has been listed since 2000 as endangered by the U.S. Fish and Wildlife Service (USFWS) and the National Oceanic and Atmospheric Administration (NOAA). The current challenge is year-over-year decreases in the number of mature salmon returning to the Penobscot River for reproduction. Early detection of pathogen presence could allow for the identification of infection and the application of corrective measures. Environmental DNA (eDNA) is simply DNA that is collected from environmental samples (e.g., water, air, and soils), which consists of whole microorganisms and genetic material shed from macroorganisms (feces, skin, gametes, etc.). Purifying, testing, sequencing, and analyzing eDNA can help us rapidly identify the presence of these organisms in the sample. This project evaluates current methods' ability to detect salmon parasites from eDNA samples. Using computer-based alignment analysis, I first verified the potential of published primer sets to amplify known pathogen sequences in silico. Then, I tested amplification in vitro via quantitative PCR (qPCR) assay with gBlocks of target parasite sequences. Finally, I used DNA metabarcoding data from samples collected along the Maine coast to determine whether these pathogens were present. The metabarcoding analysis results will help identify the presence of these pathogens. Continued monitoring using this novel approach will further the goals of protecting the GOM Atlantic salmon DPS to survive in its native habitat.