Function over form: Using metaproteomics to identify the rates of functional and compositional changes within two Arctic microbiomes

Brook L Nunn1, Molly Mikan2, Emma Timmins-Schiffman3, Michael Riffle4, William S Noble3 and H. Rodger Harvey2, (1)University of Washington, Department of Genome Sciences, Seattle, United States, (2)Old Dominion University, Ocean, Earth and Atmospheric Sciences, Norfolk, VA, United States, (3)University of Washington, Department of Genome Sciences, Seattle, WA, United States, (4)University of Washington Seattle Campus, Department of Biochemistry, Seattle, WA, United States
Abstract:
The ability to measure cellular functions of in situ and largely uncultured marine microbiomes and to link these functions to biogeochemical processes and carbon cycling has been a research goal for decades. Although proteomic analyses are tethered to the genome, both active functions and taxonomic composition of the microbiome can be learned at the time of harvest. If we are able to track how, when, and the rate at which functions and composition change, proteomics has the potential to be linked to in situ chemical measurements. The development of a universal method could allow molecular information to be linked to traditional metrics to then generate predictive biogeochemical models. We have taken the first steps in developing and testing a statistically rigorous proteomic method that yields real-time ecosystem expressed functions, allowing investigators to explore the rate of changing functionality or community composition. Using this novel metaproteomic approach, we monitored ocean incubations in two Arctic microbiomes (sub-surface and benthic) over 10 days with native or non-native organic matter input to identify specific bacterial responses and determine the rate at which their functions change in the ecosystem compared to the rate of change for community taxonomic composition. Although 24 functional terms were shared between organic input treatments, the timing and degree of the functional responses were highly variable. Using a peptide- enrichment strategy we discovered that the microbiome that received native organic matter responded by changing expressed functions rather than changing the composition of the different taxonomic groups present. The deep water microbiome that received non-native organic matter, however, changed community composition at a faster rate than the expressed functions. We anticipate that the results and methods presented here can guide the selection of key, site-specific microbiome functions to track and link to chemical metrics for the purpose of forecasting oceanic biogeochemistry.