# Using microbiomes as microsensors to forecast toxic algae blooms

> **NIH NIH R21** · UNIVERSITY OF WASHINGTON · 2022 · $286,961

## Abstract

Project Summary
 Harmful algal blooms (HABs) are becoming one of the greatest coastal and inland water quality threats to
public health. They last longer, occur more frequently and produce a wider range of toxic chemicals that
negatively impact human health than in past decades, yet we cannot forecast when an algal population will
bloom or produce toxins. As avoidance is the only public health strategy, there is a critical need to 1) develop
early warning detection systems to inform the public before (>24 hours) a harmful algae bloom, and 2) identify
chemical or physical cues in the water column that forecast HAB initiation for eventual biomarker development.
 Co-occurring marine microbial communities (i.e., the microbiome) respond to light-driven circadian rhythms
of local photosynthetic algal populations and changes in water chemistry. This results in a detectable shift in
the microbiome’s expressed functions (i.e., molecular phenotype) that correlate to algal behavior and chemical
perturbations. We hypothesize that the time-dependent, molecular phenotype of the microbiome responds to
environmental perturbations that precede a toxic algal bloom, providing early detection of HAB formation.
 The overall objective for this project is to track a) peptides expressed by the microbiome, and b) waterborne
metabolites associated with changing water chemistry in Eastsound, WA, the only known location that has
predictably timed HABs twice every year. No other HABs can currently be spatially or temporally predicted
even within a 1 to 2-week window. To capture the microbiome’s molecular signature of pre-bloom conditions,
we will conduct two field collections in year 1 timed to precede bloom initiation. For the next year only, we have
been granted 24hr access to a private dock in Eastsound, enabling the first-ever pre-bloom sample collection
to understand HAB formation. Our established high-resolution environmental samplers will collect the
microbiome and surrounding water every 4 hrs. Since cells tightly regulate protein abundance, changes in
protein levels associated with circadian patterns can be systematically quantified using novel mass
spectrometry-based peptide analyses. We will assess >20,000 peptides and test for rhythmicity and the loss
thereof, revealing critical timepoints that precede HAB formation and indicate a significant change in the local
water or physical conditions. Using the timing knowledge gained, we will then quantify metabolites in those,
and adjacent, archived timepoints using untargeted mass spectrometric metabolomics, connecting modulations
in peptide rhythmicity directly to microbiome metabolism and their chemical cues. The major outcome of the
proposed work will be the identification of peptide and metabolite biomarkers that precede HAB formation and
a fundamental understanding of chemical controls on bloom formation and toxin production. Our long-term goal
is to develop a rapid molecular assay that detects the identified chang...

## Key facts

- **NIH application ID:** 10497336
- **Project number:** 1R21ES034337-01
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Brook Leanne Nunn
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $286,961
- **Award type:** 1
- **Project period:** 2022-05-10 → 2024-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10497336

## Citation

> US National Institutes of Health, RePORTER application 10497336, Using microbiomes as microsensors to forecast toxic algae blooms (1R21ES034337-01). Retrieved via AI Analytics 2026-06-16 from https://api.ai-analytics.org/grant/nih/10497336. Licensed CC0.

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