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Article Abstract
Harmful algal blooms (HABs) have become a worldwide environmental and human health problem, stressing the urgent need for a reliable forecasting tool. Dynamic interactions between algae, including harmful algae, and bacteria play a large role regulating water chemistry. Free-living bacteria quickly respond to small physical and/or chemical environmental changes by adjusting their proteome. We hypothesize that this response is detectable at the peptide level and occurs before rapid phytoplankton growth characteristic of harmful bloom events. To characterize the microbiome's physiological changes preceding bloom onset, we collected and analyzed a high-resolution metaproteomic time series of a free-living microbiome in a coastal ecosystem. We confirm that twelve candidate HAB biomarkers are detectable, quantifiable, and correlated across two pre-bloom periods. This study identifies proteomic shifts in bacterial peptides which may be used as predictive biomarkers for forecasting harmful algal bloom initiation, potentially mitigating detrimental algal bloom outcomes in the future.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12037917 | PMC |
| http://dx.doi.org/10.1038/s41467-025-59250-y | DOI Listing |
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