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Bacteria play a crucial role in driving ecological processes in aquatic ecosystems. Studies have shown that bacteria-cyanobacteria interactions contributed significantly to phytoplankton dynamics. However, information on the contribution of bacterial communities to blooms remains scarce. Here, we tracked changes in the bacterial community during the development of a cyanobacterial bloom in an equatorial estuarine reservoir. Two forms of blooms were observed simultaneously corresponding to the lotic and lentic characteristics of the sampling sites where significant spatial variabilities in physicochemical water quality, cyanobacterial biomass, secondary metabolites, and cyanobacterial/bacterial compositions were detected. Microcystis dominated the upstream sites during peak periods and were succeeded by Synechococcus when the bloom subsided. For the main body of the reservoir, a mixed bloom featuring coccoid and filamentous cyanobacteria ( Microcystis , Synechococcus , Planktothricoides , Nodosilinea , Raphidiopsis , and Prochlorothrix ) was observed. Concentrations of the picocyanobacteria Synechococcus remained high throughout the study, and their positive correlations with cylindrospermopsin and anatoxin-a suggested that they could produce cyanotoxins, which pose more damaging impacts than previously supposed. Succession of different cyanobacteria ( Synechococcus and Microcystis ) following changes in nutrient composition and ionic strength was demonstrated. The microbiomes associated with blooms were unique to the dominant cyanobacteria. Generic and specialized bloom biomarkers for the Microcystis and downstream mixed blooms were also identified. Microscillaceae, Chthoniobacteraceae, and Roseomonas were the major heterotrophic bacteria associated with Microcystis bloom, whereas Phycisphaeraceae and Methylacidiphilaceae were the most prominent groups for the Synechococcus bloom. Collectively, bacterial community can be greatly deviated by the geological condition, monsoon season, cyanobacterial density, and dominant cyanobacteria.

Cyanobacterial blooms that produce toxins occur in freshwaters worldwide and yet, the occurrence and distribution patterns of many cyanobacterial secondary metabolites particularly in tropical regions are still not fully understood. Moreover, predictive models for these metabolites by using easily accessible water quality indicators are rarely discussed. In this study, we investigated the co-occurrence and spatiotemporal trends of 18 well-known and less-studied cyanobacterial metabolites (including [D-Asp3] microcystin-LR (DM-LR), [D-Asp3] microcystin-RR (DM-RR), microcystin-HilR (MC-HilR), microcystin-HtyR (MC-HtyR), microcystin-LA (MC-LA), microcystin-LF (MC-LF), microcystin-LR (MC-LR), microcystin-LW (MC-LW), microcystin-LY (MC-LY), microcystin-RR (MC-RR) and microcystin-WR (MC-WR), Anatoxin-a (ATX-a), homoanatoxin-a (HATX-a), cylindrospermospin (CYN), nodularin (NOD), anabaenopeptin A (AptA) and anabaenopeptin B (AptB)) in a tropical freshwater lake often plagued with blooms. Random forest (RF) models were developed to predict MCs and CYN and assess the relative importance of 22 potential predictors that determined their concentrations. The results showed that 11 MCs, CYN, ATX-a, HATX-a, AptA and AptB were found at least once in the studied water body, with MC-RR and CYN being the most frequently occurring, intracellularly and extracellularly. AptA and AptB were detected for the first time in tropical freshwaters at low concentrations. The metabolite profiles were highly variable at both temporal and spatial scales, in line with spatially different phytoplankton assemblages. Notably, MCs decreased with the increase of CYN, possibly revealing interspecific competition of cyanobacteria. The rapid RF prediction models for MCs and CYN were successfully developed using 4 identified drivers (i.e., chlorophyll-a, total carbon, rainfall and ammonium for MCs prediction; and chloride, total carbon, rainfall and nitrate for CYN prediction). The established models can help to better understand the potential relationships between cyanotoxins and environmental variables as well as provide useful information for making policy decisions., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Microcystin is an algal toxin that is commonly found in eutrophic freshwaters throughout the world. Many studies have been conducted to elucidate the factors affecting its production, but few studies have attempted mechanistic models of its production to aid water managers in predicting its occurrence. Here, a mechanistic model was developed based on microcystin production by Microcystis spp. under laboratory culture and ambient field conditions. The model was built on STELLA, a dynamic modelling software, and is based on constitutive cell quota that varies with nitrogen, phosphorus, and temperature. In addition to these factors, varying the decay rate of microcystin according to its proportion in the intracellular and extracellular phase was important for the model's performance. With all these effects, the model predicted most of the observations with a model efficiency that was >0.72 and >0.45 for the lab and field conditions respectively. However, some large discrepancies were observed. These may have arisen from the non-constitutive microcystin production that appear to have a precondition of nitrogen abundance. Another reason for the large root mean square error is that cell quota is affected by factors differently between strains.

Analytical methods based on direct injection (DI) and solid phase extraction (SPE) coupled with ultrahigh performance liquid chromatography-tandem mass spectrometry (UPLC- MS/MS) were developed for the determination of anatoxin-a (ATX-a), cylindrospermopsin (CYN), and homoanatoxin-a (HATX-a) in freshwater samples impacted with cyanobacterial blooms. The presence of CYN in freshwater samples was detected and quantified based on direct injection method, while ATX-a and HATX-a could be determined by both DI and SPE-based methods. Matrix effects (ME) on the signal intensity of the cyanotoxins were systematically evaluated for both direct injection and SPE extract samples. CYN, ATX-a, and HATX-a suffered a significant suppression during UPLC-MS/MS. The selection of internal standards (ISs) for compensating/correcting the losses of target cyanotoxins during sample preparation and matrix effects in UPLC-MS/MS analyses were systematically evaluated. Acetaminophen-d 4 (an isotopically labelled acetaminophen) is a suitable internal standard for correcting the ME on the signal intensity of ATX-a and HATX-a, while the use of L-phenylalanine-d 5 or caffeine-d 9 as IS for correcting ME of these toxins was not efficient, as expected. The method detection limit (MDL) for the target cyanotoxins ranged from 0.6 to 15 ng/L, which is sensitive enough to detect the presence of these toxins in cyanobacterial bloom freshwater. The developed methods were successfully applied for routine monitoring of the occurrence of these cyanotoxins in a local water body. Monitoring results depicted that ATX-a, CYN and HATX-a were ubiquitously detected in water samples, at concentrations ranging from 70 to 24,600 ng/L., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)