Multi-class secondary metabolites in cyanobacterial blooms from a tropical water body: distribution patterns and real-time prediction
Start Date
23-5-2022 4:45 PM
End Date
23-5-2022 5:02 PM
Abstract
Cyanotoxins produced by cyanobacterial blooms contaminate freshwater bodies worldwide. Yet, the distribution patterns of these secondary metabolites in tropical regions are still not well-understood and predictive models using simple water quality indicators are rarely discussed. Here, we investigated the co-occurrence and spatiotemporal trends of 18 cyanobacterial metabolites (including 11 microcystin varints, anatoxin-a, homoanatoxin-a, cylindrospermospin, nodularin, anabaenopeptins A and B) in a tropical freshwater lake plagued with blooms. Random forest (RF) models were developed to predict microcystins and cylindrospermopsin and assess the relative importance of 22 potential predictors that determined their concentrations. The results showed that microcystins, cylindrospermopsin, anatoxin-a, homoanatoxin-a and anabaenopeptins were found at least once in the studied water body, with microcystin-RR and cylindrospermopsin being most detected. Anabaenopeptins A and B were detected for the first time in tropical freshwaters at low concentrations. The metabolite profiles were highly variable at both temporal and spatial scales. The rapid RF prediction models for microcystins and cylindrospermopsin were successfully developed (i.e., chlorophyll-a, total carbon, rainfall and ammonium for microcystins prediction; and chloride, total carbon, rainfall and nitrate for cylindrospermopsin prediction). The models can help to envisage the relationships between cyanotoxins and environmental variables and provide useful information for making policy decisions.
Multi-class secondary metabolites in cyanobacterial blooms from a tropical water body: distribution patterns and real-time prediction
Cyanotoxins produced by cyanobacterial blooms contaminate freshwater bodies worldwide. Yet, the distribution patterns of these secondary metabolites in tropical regions are still not well-understood and predictive models using simple water quality indicators are rarely discussed. Here, we investigated the co-occurrence and spatiotemporal trends of 18 cyanobacterial metabolites (including 11 microcystin varints, anatoxin-a, homoanatoxin-a, cylindrospermospin, nodularin, anabaenopeptins A and B) in a tropical freshwater lake plagued with blooms. Random forest (RF) models were developed to predict microcystins and cylindrospermopsin and assess the relative importance of 22 potential predictors that determined their concentrations. The results showed that microcystins, cylindrospermopsin, anatoxin-a, homoanatoxin-a and anabaenopeptins were found at least once in the studied water body, with microcystin-RR and cylindrospermopsin being most detected. Anabaenopeptins A and B were detected for the first time in tropical freshwaters at low concentrations. The metabolite profiles were highly variable at both temporal and spatial scales. The rapid RF prediction models for microcystins and cylindrospermopsin were successfully developed (i.e., chlorophyll-a, total carbon, rainfall and ammonium for microcystins prediction; and chloride, total carbon, rainfall and nitrate for cylindrospermopsin prediction). The models can help to envisage the relationships between cyanotoxins and environmental variables and provide useful information for making policy decisions.