Using microbiomes as microsensors to forecast toxic algae blooms

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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 changes in 1) the functionality of the water microbiome and/or 2) crucial waterborne metabolites in advance of harmful algal bloom formation, in order to prevent human exposure to bloom toxins, thereby protecting human health.