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Why Environmental Biomarkers Work: Transcriptome–Proteome Correlations and Modeling of Multistressor Experiments in the Marine Bacterium Trichodesmium
Author(s) -
Nathan G. Walworth,
Mak A. Saito,
Michael Lee,
Matthew R. McIlvin,
Dawn M. Moran,
Riss M. Kellogg,
Fei-Xue Fu,
David A. Hutchins,
Eric A. Webb
Publication year - 2021
Publication title -
journal of proteome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.644
H-Index - 161
eISSN - 1535-3907
pISSN - 1535-3893
DOI - 10.1021/acs.jproteome.1c00517
Subject(s) - transcriptome , proteome , biology , computational biology , proteomics , biogeochemical cycle , adaptation (eye) , rna , gene expression , ecology , bioinformatics , genetics , gene , neuroscience
Ocean microbial communities are important contributors to the global biogeochemical reactions that sustain life on Earth. The factors controlling these communities are being increasingly explored using metatranscriptomic and metaproteomic environmental biomarkers. Using published proteomes and transcriptomes from the abundant colony-forming cyanobacterium Trichodesmium (strain IMS101) grown under varying Fe and/or P limitation in low and high CO 2 , we observed robust correlations of stress-induced proteins and RNAs (i.e., involved in transport and homeostasis) that yield useful information on the nutrient status under low and/or high CO 2 . Conversely, transcriptional and translational correlations of many other central metabolism pathways exhibit broad discordance. A cellular RNA and protein production/degradation model demonstrates how biomolecules with small initial inventories, such as environmentally responsive proteins, achieve large increases in fold-change units as opposed to those with a higher basal expression and inventory such as metabolic systems. Microbial cells, due to their immersion in the environment, tend to show large adaptive responses in both RNA and protein that result in transcript-protein correlations. These observations and model results demonstrate multi-omic coherence for environmental biomarkers and provide the underlying mechanism for those observations, supporting the promise for global application in detecting responses to environmental stimuli in a changing ocean.

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