Gradients in Functional Capabilities in the Sargasso Sea as determined by Metaproteomes collected by the Biogeochemical AUV Clio

Mak A Saito1, Matthew R McIlvin1, Eric W Chan2, Dawn M Moran1, Brian Searle3, Natalie Cohen4, Marissa Morgan Kellogg1, Rebecca Chmiel1, Paloma Lopez5, Fernando Pacheco5, Zachary Anderson6, Rodney J Johnson7, Michael Jakuba8 and John A Breier Jr9, (1)Woods Hole Oceanographic Institution, Woods Hole, MA, United States, (2)University of Rochester, Rochester, NY, United States, (3)Institute for Systems Biology, Seattle, United States, (4)Woods Hole Oceanographic Institution, Falmouth, MA, United States, (5)Bermuda Institute of Ocean Sciences, St.George's, Bermuda, (6)Bermuda Institute of Ocean Sciences, St. George's, Bermuda, (7)BIOS, St Georges, Bermuda, (8)Woods Hole Oceanographic Inst., Woods Hole, MA, United States, (9)University of Texas Rio Grande Valley, Edinburg, TX, United States
Abstract:
Many microorganisms harbor significant genetic potential to respond to changes in their environment, for example through changes in membrane transporter abundance or through the modification of their cellular metabolism to compensate for chemical scarcities or surpluses. The measurement of microbial proteins directly in natural communities, or metaproteomics, allows the direct observation of the result of these “decisions” made by microbes as to which aspects of their genetic potential to deploy. In June of 2019 we conducted an ocean section from Bermuda to Woods Hole across the Sargasso Sea deploying the new AUV Clio in the upper kilometer for its first ocean section. In addition, surface transects of proteins have been collected on the BVAL Bermuda – Puerto Rico transect. Together these samples allow a large scale gradient of observations regarding the influence of environmental gradients on the proteome composition of abundant prokaryotic marine microbes in this region. Multidimensional HPLC chromatography was used to generate a spectral libraries, and protein identifications and quantitations were conducted through a combination of data-dependent acquisition and data-independent acquisition. The distribution of key nutrient and micronutrient acquisition systems and related enzymes for N, P, and Fe metabolism will be explored and discussed within spatial and temporal environmental contexts.