Harmful algal blooms are preceded by a predictable and quantifiable shift in the oceanic microbiome

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...

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Main Authors: Miranda C. Mudge, Michael Riffle, Gabriella Chebli, Deanna L. Plubell, Tatiana A. Rynearson, William S. Noble, Emma Timmins-Schiffman, Julia Kubanek, Brook L. Nunn
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-025-59250-y
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author Miranda C. Mudge
Michael Riffle
Gabriella Chebli
Deanna L. Plubell
Tatiana A. Rynearson
William S. Noble
Emma Timmins-Schiffman
Julia Kubanek
Brook L. Nunn
author_facet Miranda C. Mudge
Michael Riffle
Gabriella Chebli
Deanna L. Plubell
Tatiana A. Rynearson
William S. Noble
Emma Timmins-Schiffman
Julia Kubanek
Brook L. Nunn
author_sort Miranda C. Mudge
collection DOAJ
description 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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spelling doaj-art-acfeda00d23b456a8de1ecf1fb3eeae42025-08-20T03:52:24ZengNature PortfolioNature Communications2041-17232025-04-0116111410.1038/s41467-025-59250-yHarmful algal blooms are preceded by a predictable and quantifiable shift in the oceanic microbiomeMiranda C. Mudge0Michael Riffle1Gabriella Chebli2Deanna L. Plubell3Tatiana A. Rynearson4William S. Noble5Emma Timmins-Schiffman6Julia Kubanek7Brook L. Nunn8Department of Genome Sciences, University of WashingtonDepartment of Genome Sciences, University of WashingtonSchool of Biological Sciences, Georgia Institute of Technology, Parker H. Petit Institute for Bioengineering and BioscienceDepartment of Genome Sciences, University of WashingtonGraduate School of Oceanography, University of Rhode IslandDepartment of Genome Sciences, University of WashingtonDepartment of Genome Sciences, University of WashingtonSchool of Biological Sciences, Georgia Institute of Technology, Parker H. Petit Institute for Bioengineering and BioscienceDepartment of Genome Sciences, University of WashingtonAbstract 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.https://doi.org/10.1038/s41467-025-59250-y
spellingShingle Miranda C. Mudge
Michael Riffle
Gabriella Chebli
Deanna L. Plubell
Tatiana A. Rynearson
William S. Noble
Emma Timmins-Schiffman
Julia Kubanek
Brook L. Nunn
Harmful algal blooms are preceded by a predictable and quantifiable shift in the oceanic microbiome
Nature Communications
title Harmful algal blooms are preceded by a predictable and quantifiable shift in the oceanic microbiome
title_full Harmful algal blooms are preceded by a predictable and quantifiable shift in the oceanic microbiome
title_fullStr Harmful algal blooms are preceded by a predictable and quantifiable shift in the oceanic microbiome
title_full_unstemmed Harmful algal blooms are preceded by a predictable and quantifiable shift in the oceanic microbiome
title_short Harmful algal blooms are preceded by a predictable and quantifiable shift in the oceanic microbiome
title_sort harmful algal blooms are preceded by a predictable and quantifiable shift in the oceanic microbiome
url https://doi.org/10.1038/s41467-025-59250-y
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