Genomic Science Program
U.S. Department of Energy | Office of Science | Biological and Environmental Research Program

2024 Abstracts

Cyanobacteria-Cyanophage Environmental Sampling in the Salish Sea

Authors:

Noelani Boise1* ([email protected]), Scott Edmundson1, Owen Leiser1, David Pollock1,2, Margaret Cheung1 (PI)

Institutions:

1Pacific Northwest National Laboratory; 2University of Colorado–Anschutz Medical Campus

Abstract

Marine picocyanobacteria are a ubiquitous component of phytoplankton and play an outsized role in global primary production. As part of a larger project to use cyanobacteria and cyanophage as a model system to understand molecular mechanisms of pathogenesis and disease transmission, this team is performing sampling, metadata collection, and sequencing to understand their complex natural host-parasite relationships in relation to environmental factors. To achieve this, the group sampling coastal Salish Sea waters along the northern Olympic Peninsula at various times of day, times of year, depths, and tidal flow conditions. Here, the poster describes preliminary sampling, sequencing results, and metadata analysis results. Sampling involved collecting surface-level serial filtration samples from the Pacific Northwest National Laboratory Sequim floating dock, in-line filtration of a raw seawater line, and cultured specimens.

Filtering was performed to collect whole plankton, picocyanobacteria, and viral fractions, the last two to enrich sequencing efforts to focus on the target organisms. Preprocessed sequence reads were aligned to known cyanophage as well as the cyanobacteria Prochlorococcus marinus and Synechococcus elongatus genomes, demonstrating the presence of organismal targets but at low frequency, as expected during the cold, low light winter months. These initial survey results provide a promising foundation to establish standard sampling and metadata collection protocols to sample over the next three years to better understand cyanobacterial-cyanophage coevolution. Further steps will integrate genomic, multimodal structural and proteomic data with evolutionary models to better understand cyanobacteria-cyanophage ecotypes and coevolutionary interactions.