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Influence of Environmental Factors on Occurrence of Cyanobacteria And water Article Influence of Environmental Factors on Occurrence of Cyanobacteria and Abundance of Saxitoxin-Producing Cyanobacteria in a Subtropical Drinking Water Reservoir in Brazil Munique A. B. Moraes 1 , Raphaella A. M. Rodrigues 1 , Louise Schlüter 2, Raju Podduturi 3, Niels O. G. Jørgensen 3,* and Maria C. Calijuri 1 1 Department of Hydraulics and Sanitation, São Carlos School of Engineering, University of São Paulo, 400 Trabalhador São Carlense Avenue, São Carlos 13566-590, Brazil; [email protected] (M.A.B.M.); [email protected] (R.A.M.R.); [email protected] (M.C.C.) 2 Environment and Toxicology, DHI, Agern Alle 5, 2970 Hørsholm, Denmark; [email protected] 3 Department of Plant and Environmental Sciences, University of Copenhagen, Thorvaldsensvej 40, 1871 Frederiksberg, Denmark; [email protected] * Correspondence: [email protected] Abstract: Blooms of cyanobacteria are frequent in Brazilian water reservoirs used for drinking water. The warning for the presence of potential toxin-producing cyanobacteria is typically based on time- consuming microscopy, rather than specific molecular detection of toxic genes in cyanobacteria. In Citation: Moraes, M.A.B.; Rodrigues, this study, we developed a quantitative PCR assay for the detection of cyanobacteria producing the R.A.M.; Schlüter, L.; Podduturi, R.; neurotoxin saxitoxin (STX). The assay targets the sxtA gene in the sxt gene cluster. Potential and Jørgensen, N.O.G.; Calijuri, M.C. dominant STX-producers in the Itupararanga reservoir were the genera Raphidiopsis, Aphanizomenon Influence of Environmental Factors and Geitlerinema. Numbers of the sxtA gene varied from 6.76 × 103 to 7.33 × 105 cells mL−1 and on Occurrence of Cyanobacteria and correlated positively with SXT concentrations in the water. Concentrations of STX and the sxtA gene Abundance of Saxitoxin-Producing also correlated positively with TN:TP ratio and pH, but correlated negatively with inorganic nutrients Cyanobacteria in a Subtropical and turbidity, confirming that regulation of the SXT production was impacted by environmental Drinking Water Reservoir in Brazil. variables. In contrast, the occurrence of another cyanotoxin, microcystin, did not correlate with any Water 2021, 13, 1716. https:// doi.org/10.3390/w13121716 environmental variables. The developed qPCR assay was found to be a rapid and robust approach for the specific quantification of potential STX-producing cyanobacteria and should be considered in Academic Editor: future investigations on toxic cyanobacteria to provide an early warning of potential toxin episodes. Katarzyna Kowalczewska-Madura Keywords: Itupararanga reservoir; toxic cyanobacteria; cyanotoxins; qPCR; sxtA Received: 14 May 2021 Accepted: 17 June 2021 Published: 21 June 2021 1. Introduction Publisher’s Note: MDPI stays neutral Cyanobacteria may cause a multitude of water quality concerns. Among these con- with regard to jurisdictional claims in cerns is the potential risk of toxin production, since cyanotoxins in drinking water reservoirs published maps and institutional affil- and in recreational water pose a serious risk to human health but also to ecosystem func- iations. tioning [1]. The most studied cyanotoxin is the hepatotoxic microcystin (MC), which consists of more than 240 structural variants and is produced by several cyanobacterial gen- era [2,3], including Dolichospermum (basionym Anabaena)[4], Microcystis and Planktothrix. Another important cyanotoxin is saxitoxin (STX), a neurotoxin that occurs in more than Copyright: © 2021 by the authors. 50 variants, and 15 of these variants have so far not been detected in cyanobacteria [5]. Licensee MDPI, Basel, Switzerland. The STX-producing freshwater genera include, among others, Raphidiopsis (basionym This article is an open access article Cylindrospermopsis)[6], Dolichospermum, and Aphanizomenon. distributed under the terms and The physiological and ecological function of cyanotoxins in cyanobacteria is not clear, conditions of the Creative Commons but some researchers believe that the toxins have a protective function against zooplankton Attribution (CC BY) license (https:// grazing, or are related to interspecies competition for resources, or may improve the cell creativecommons.org/licenses/by/ physiology [7,8]. However, specific factors that stimulate and/or control the production of 4.0/). Water 2021, 13, 1716. https://doi.org/10.3390/w13121716 https://www.mdpi.com/journal/water Water 2021, 13, 1716 2 of 19 cyanotoxin by cyanobacteria remain to be determined [9]. Similarly, the fact that the same cyanobacterial strain is capable of synthesizing more than one toxic metabolite makes it even more difficult to understand a cause-effect relationship [10]. The identification and quantification of cyanobacteria by traditional microscopy is not adequate for the identification of toxic populations, since toxic and nontoxic strains are morphologically identical [11]. For the detection of toxin-producing strains, PCR-targeting genes that encode specific toxins may be a fast and useful approach [12]. If the number of potentially toxin-producing cyanobacteria is needed, e.g., in environmental studies, quantitative PCR (qPCR) can be applied and serve as a powerful and sensitive tool [13–17]. In Brazil, relatively few studies have focused on molecular approaches for the detec- tion of toxic genes for early warning of cyanotoxin episodes, despite the frequent occurrence of cyanobacterial blooms [12,18–21]. In most cases, traditional PCR was used to detect the presence of potentially cyanotoxin-producing strains, but the application of qPCR-targeting genes in the MC synthesis was performed by Lorenzi [19], Pimentel and Giani [11] and Guedes et al. [22] to quantify the mcyA gene in Salto Grande reservoir, the mcyD gene in Furnas reservoir and the mcyB in Funil reservoir, respectively. For production of SXT by cyanobacteria, no qPCR approaches targeting genes in the sxt cluster have so far been applied in Brazilian freshwaters to our knowledge. The Itupararanga reservoir is located in a subtropical urbanized region of São Paulo State, Brazil, and is one of the most important reservoirs of ecological and economic interests in the state. Water from the reservoir serves many purposes, such as a source of drinking water for approximately one million people, for hydroelectric power and for irrigation of crops [23]. The reservoir has suffered from water quality degradation due to growing urbanization, agricultural practices and discharge of untreated wastewater, especially in the tributaries [24–26]. Studies have classified this reservoir as meso-eutrophic [27,28]. Increased nutrient levels have not only contributed to the eutrophication process, they have also introduced a risk of water quality deterioration due to the proliferation of cyanobacteria [29–31]. In an attempt to better understand the dynamics of toxin-producing cyanobacteria in the Itupararanga reservoir, we related concentrations of STX and MC to the abundance of known toxin producers, as well as to important environmental parameters (nutrients, turbidity and pH). In parallel, to obtain actual numbers of STX-producing cells in the reservoir, we developed a qPCR approach that targets the sxtA gene in the sxt gene cluster. Finally, we hypothesize that numbers of the sxtA gene correlate with concentrations of STX in the water and can be used for early warning of health risk by saxitoxins. 2. Materials and Methods 2.1. Study Area and Sampling Environmental samples were collected at the riverine and dam zones in the Itu- pararanga reservoir located in São Paulo State, Brazil (Figure1). The main characteristics of the reservoir and sampling sites are shown in Table S1. Sampling was carried out in May, August, October 2017 and January 2018. Water samples were collected at two depths (100%—surface and 1%—lower limit of euphotic zone) determined by the photo- synthetically active radiation (PAR, µE m−2 s−1) using a light sensor (LI-1400 DataLogger, sensitivity of 400–700 nm, LI-COR Biosciences, Lincoln, NE, USA). Water 2021 13 Water 2021,, 13,, 1716x FOR PEER REVIEW 3 3of of 20 19 Figure 1. Sampling sites in the Itupararanga reservoir, SSãoão PauloPaulo State,State, Brazil.Brazil. ItupararangaItupararanga riverineriverine zonezone (23(23°37◦370′24.824.8”″ S, S, 47°1347◦13′053.453.4”″ W); W); Itupararanga Itupararanga dam dam zone zone (23°36 (23◦36′50.7050.7”″ S, S, 47°23 47◦23′27.3027.3”″ W). W). 2.2.2.2. Environmental Environmental Variables Variables TheThe variables pH, dissolved oxygen (DO,(DO, mgmg LL−−1),), electrical electrical conductivity conductivity (EC, (EC, μµS cmcm−−1),1), turbidity turbidity (NTU) (NTU) and and water water temperature temperature (°C) (◦C) were were determined determined on-site on-site using a HANNAHANNA probeprobe (HANNA (HANNA HI9829, HI9829, Limena, Limena Italy)., WaterItaly). transparencyWater transparency (m) was determined (m) was determinedusing a Secchi using disk anda Secchi the lower disk limitand ofthe euphotic lower zonelimit (Zofeu euphotic, m) was determinedzone (Zeu, asm) 1% was of − determinedPAR. Samples as 1% for dissolvedof PAR. Samples nutrients for (solubledissolved reactive nutrients phosphorus—SRP, (soluble reactive nitrate—NO phosphorus—3 - − − − + + SRP,N, nitrite—NO nitrate—NO2 3-N-N, and nitrite—NO ammonium—NH2 -N and 4ammonium—NH-N) were filtered4 -N) through were 0.7 filteredµm-pore-size through 0.7glass μm-pore-size fiber filters (GEglass Healthcare fiber filters Life (GE Sciences, Healthcare Whatman, Life Sciences,
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