Occurrence of Harmful Algal Blooms in Freshwater Sources of Mindu and Nyumba ya Mungu Dams, Tanzania

Harmful algal blooms (HABs) pose a significant threat to aquatic ecosystems and human health due to the production of toxins. The identification and quantification of these toxins are crucial for water quality management decisions. This study used DNA analysis (PCR techniques) to identify toxin-producing strains and liquid-chromatography-tandem mass spectrometry (LC-MS/MS) to quantify microcystins in samples from Mindu and Nyumba ya Mungu Dams in Tanzania. The results showed that HABs were detected in both dams. The BLAST results revealed that the 16S gene sequences of uncultured samples were very similar to an Antarctic cyanobacterium, Leptolyngbya sp, Anabaena sp, and Microcystis aeruginosa. Sequences of the cultured samples were most similar to Nodularia spumigena, Amazoninema brasiliense, Anabaena sp, and Microcystis aeruginosa. Further analyses showed that the nucleotide sequence similarity of uncultured isolates from this study and those from the GenBank ranged from 85 to 100%. For cultured isolates from this study and others from the GenBank, nucleotide identity ranged from 81 to 100%. The molecular identification of Microcystis aeruginosa confirmed the presence of HABs in both Mindu and Nyumba ya Mungu Dams in Tanzania. At Mindu Dam, the mean concentrations (± standard deviation) of microcystin-LR, -RR, and -YR were 1.08 ± 0.749 ppm, 0.120 ± 0.0211 ppm, and 1.37 ± 0.862 ppm, respectively. Similarly, at Nyumba ya Mungu Dam, the concentrations of microcystin-LR, -RR, and -YR were 1.07 ± 0.499 ppm, 0.124 ± 0.0224 ppm, and 0.961 ± 0.408 ppm, respectively. This paper represents the first application of PCR and LC-MS/MS to study microcystins in small freshwater reservoirs in Tanzania. This study confirms the presence of toxin-producing strains of Microcystis aeruginosa in both dams and also provides evidence of the occurrence of microcystins from these strains. These findings contribute in improving the monitoring of HABs contamination and their potential impact on water quality in Tanzanian reservoirs.


Introduction
Globally, anthropogenic activities and climate change have negatively afected freshwater ecosystems, leading to a decline in water quality, biodiversity loss, and a reduction in ecosystem services [1].Human pressure on land has been linked to increased eutrophication, which has deleterious efects on water bodies such as lakes and small reservoirs.Anthropogenic activities causing an increase in nutrients such as agricultural runof and wastewater discharges contribute to eutrophication, which leads to an increase in HABs [1][2][3][4].Te growth of blue-green algae is facilitated by nitrogen and phosphorus inputs into waterbodies [5,6], which has a signifcant negative impact on water quality and poses severe threats to aquatic life and public health [7].Te occurrence of HABs has been reported in diferent countries worldwide, including Tanzania [8][9][10][11][12][13].Small inland waterbodies are especially vulnerable to nutrient enrichment and the eutrophication process due to their shallowness and relative isolation.Tey can develop strong physical-chemical gradients which make them susceptible to the growth of harmful blue-green algal blooms compared to large water bodies [14][15][16][17][18]. Te Nyumba ya Mungu Dam and Mindu Dam are important man-made reservoirs in Tanzania but have been afected by eutrophication [19,20].
Algal blooms are diverse and consist of a rapidly growing dominant group of organisms in freshwater environments [21,22].Many naturally occurring algal blooms in marine and freshwater habitats produce a range of toxins that can harm aquatic ecosystems and humans [23,24].Algal toxins produced by blue-green algae and their efect on human health are increasingly prevalent in freshwater systems worldwide [13,23,25].Te toxic bloom-forming species include the genera Microcystis, Nodularia, Aphanizomenon, Anabaena, Cylindrospermopsis, and Oscillaroria [23,[26][27][28].Teir toxins are classifed according to their mode of action in vertebrates as hepatotoxins, cytotoxins, neurotoxins, dermatotoxins, and irritants [24,27,29].Among all cyanotoxins, microcystin and nodularin are the most common hepatotoxins produced by a wide range of blue-green algae [29,30].Te hepatotoxins have been reported to be potent protein phosphatase 1 (PP1) and 2A (PP2A) inhibitors.It has been revealed to have long-term cumulative toxic efects on potential tumour formation [31][32][33].Local climate and weather strongly infuence the occurrence, extent, and adaptations of blue-green algae to climatic fuctuations [12,34].
Identifcation of HABs and their toxin levels is vital to water quality management decisions.Various methods have been employed for the detection of HABs.Microscopic analysis is a common method for identifying diferent algal species based on their morphological characteristics.However, this method can be time-consuming and labourintensive, and it cannot distinguish between toxic and nontoxic algal strains [35][36][37].Molecular techniques, such as DNA sequencing and polymerase chain reaction (PCR), are utilised to analyse the genetic material of collected samples.Tese methods can aid in identifying specifc HAB species and strains by targeting and amplifying specifc DNA markers [38][39][40][41][42][43][44][45][46].PCR has proven to be a powerful method for detecting HAB species, as it can diferentiate between toxic and nontoxic strains of Microcystis spp.[36].Molecular techniques based on the presence or absence of genes necessary for toxin production have also been used to characterise toxic and nontoxic blue-green algae [47].DNA isolation and gene amplifcation studies are commonly employed in molecular identifcation of species and phylogeny studies [48][49][50].Tese methods enhance the accuracy and speed of organism identifcation [51].
Among the ten genes (mcyA-J) involved in microcystin production in blue-green algae, the mcyE of the microcystin synthetase enzyme plays a crucial role in synthesising all forms of microcystins [47,52].Tis area has been useful for detecting potential microcystin-producing blue-green algae in numerous algal blooms [53].Using PCR, researchers have developed molecular-based techniques for identifying harmful Microcystis species in water [52,54].Te method involves amplifying the microcystin synthetase (mcy) gene using universal and specifc PCR primers [9,55].Partial sequences of the 16S rRNA gene determine the dominant species among blue-green algal communities in a particular habitat [47].
In terms of toxin quantifcation, several methods are utilised.Enzyme-linked immunosorbent assay (ELISA) utilises specifc antibodies that bind to the target toxin, allowing for its detection and quantifcation.However, this method may have lower accuracy and sensitivity [35].Highperformance liquid chromatography (HPLC) is another commonly used technique, which separates and detects toxins based on their chemical properties such as molecular size and polarity.However, HPLC requires sophisticated instruments and involves complex analytical processes, which may limit its implementation [35].Liquid chromatography-mass spectrometry (LC-MS) is gaining popularity due to its sensitivity [56][57][58][59].It separates and detects toxins based on their mass and charge, enabling accurate quantifcation of multiple toxins in a sample [58].
Despite existing studies on the blue-green algae in freshwater reservoirs [12,20,[60][61][62][63][64], there is limited information on the specifc types of blue-green algae present, which can potentially cause HAB in Tanzania.In this study, the researchers used DNA analysis techniques (PCR and sequencing) to identify Microcystis strains and LC-MS/MS to quantify microcystins in the blooms and water samples from Mindu and Nyumba ya Mungu Dams.Tis study will help improve the monitoring of HABs contamination to ensure water safety for aquatic organisms, animals, and humans.

Study Area.
Tis study was conducted in two locations: the Mindu Dam in Morogoro and the Nyumba ya Mungu reservoir in Kilimanjaro (Figure 1).Te reservoirs are used for agriculture, fshery, supply of raw potable water for domestic use, and recreational activities.Mindu Dam's area is approximately 3.8 km 2 , and that of its catchment is 303 km 2 [65].Nyumba ya Mungu Dam (140 km 2 ) is the largest water body in the basin, and its catchment occupies a total land and water area of about 12,000 km 2 .

Sample Collection and Preparation.
Water samples were randomly collected from Mindu and Nyumba ya Mungu Dams during the dry seasons from 2019 to 2021.In Mindu Dam, algal blooms were collected using polyethylene bags while in Nyumba ya Mungu Dam, water samples containing algal cells were collected by dipping sterile 500 mL amber glass sampling bottles into the surface water.All water samples for physical-chemical parameters from both dams were collected by using plastic bottles and preserved as per [66].All samples were collected in triplicate from each of the sampling points.Te bottles containing water samples and polyethylene bags containing algal blooms were packed into a cooler box containing ice blocks and transported to the Water Quality Laboratory at the Water Institute for further analysis.Other water quality variables measured to characterise the bloom 2 Journal of Toxicology conditions included temperature, dissolved oxygen (DO), electrical conductivity (EC), chlorophyll-a (Chl-a), nitrate (NO 3 ), phosphate (PO 4 ), pH, total dissolved solids (TDS), and turbidity were collected as per APHA [66].
Water samples from Nyumba ya Mungu Dam did not contain a high cell concentration by algal blooms as those from Mindu Dam.Terefore, they were frst cultured for 21 days in laboratory environments using BG11 liquid media before DNA extraction.Tis allowed the algal cells to grow and multiply, making it easier to collect enough DNA for analysis.Te BG11 liquid media were prepared using methods and conditions described by Kilulya and Msagati [67].Five (5) millilitres of water containing algal cells were inoculated into the BG11 media.Te fasks were incubated on a shaker at room temperature and in natural sunlight with 12-hour light and dark cycles for 21 days.Te pH was maintained in the optimal range of 7.5 to 8.5 by adding sodium carbonate and citric acid bufers in controlled amounts to regulate the pH whenever it changed.Te pH and temperature of the solution were measured daily to ensure that the conditions were optimal for algal growth.

Genomic DNA Extraction, PCR, and Sequencing.
DNA was extracted using the cetyl trimethyl ammonium bromide (CTAB) method [68] from all uncultured samples (Mindu Dam) and cultured cells (Nyumba ya Mungu Dam).A Nanodrop 2000/2000C spectrophotometer (Termo Scientifc, Lagos Park, Porto Salvo) was used to measure the concentration and purity at 260 and 280 nm.Te integrity of the isolated DNA in the samples was assessed by using agarose gel electrophoresis (1.2%) and staining with 0.1 g/ml ethidium bromide.Te 16S rRNA genes of cultured water algal cells and uncultured algal bloom samples were frst amplifed from the genomic DNA using universal bacterial primers for the region.Universal 16S rRNA primers used were forward primer 27F: (5′-AGA GTT TGA TCC TGG CTC AG-3′) and reverse primer 1492R: (5′-TAC GCG CTA CCT TGT TAC GAC-3′) [69].Te mcyE gene region was amplifed using the specifc forward primer HEPF: (5′TTT GGG GTT AAC TTT TTT GGG CAT AGTC-3′) and reverse primer HEPR: (5′AAT TCT TGA GGC TGT AAA TCG GGT TT-3′) [53,70].Te expected PCR fragment sizes were approximately 1.5 kb for the 16S rRNA gene and 472 bp for the microcystin mcyE gene.PCR reactions for all DNA samples were done using TEMpase Hot Start 2x Master Mix A as follows: 12.5 μl of the master mix, 2 μl of each forward and reverse primer (10 μM), and 2 μl of genomic DNA template in a fnal reaction volume of 25 μl.Te thermocycler conditions for TEMpase Hot Start 2x Master Mix A were as follows: initial denaturation at 95 °C for 15 minutes followed by 35 cycles of 95 °C for 30 seconds, 55 °C for 45 seconds, 72 °C for 1 minute, and fnally extended at 72 °C for 10 minutes.PCR conditions for specifc microcystin genes were the same as for amplifying the 16S rRNA gene, except for the annealing time, which was shortened to 30 seconds.Te amplicons were analysed on a 1.5% agarose gel and visualised using a UV light (BioDoc-ItTmImaging system, Cambridge, UK).After that, PCR products were sequenced at Inqaba Biotec (South Africa).

Sequence Analyses.
Te nucleotide sequences of the 16S rRNA and microcystin genes acquired from Sanger sequencing were checked for quality using the BioEdit program and aligned with other sequences obtained from GenBank (Table 1) using ClustaIW in MEGA X [71].Te maximum likelihood method based on the Tamura-Nei model and 1000 bootstrap replications were employed in the statistical analysis [72,73].Te total number of positions in the fnal dataset for the 16S gene was 964, and for the mcyE gene, it was 472.Te p-distance method was used to compute the evolutionary distances (expressed as numbers of base changes per site) [74].Te positions containing gaps and missing data were deleted entirely.Te identities of nucleotide sequences were determined using the BioEdit sequence alignment editor [75].Te cleaned sequences were deposited in GenBank to get the accession numbers.

Quantifcation of Toxins in Microcystin-Producing Blue-
Green Algae.Microcystin (MC) reference standards and prepared samples were analysed using the liquid-chromatography-tandem mass spectroscopy (LC-MS/MS) instrument.Freeze-dried algal bloom samples (0.5 g) were extracted twice with 70% methanol (v/v) by sonication for 10 minutes.Te extracts were centrifuged at 4000 rpm for 10 minutes before solid-phase extraction (SPE).Supernatants were collected under vacuum at a fow rate of 1-2 mL/min and dried under a gentle nitrogen fow at 40 °C.Te residues were reconstituted with 0.5 mL of pure methanol.Te samples were analysed by liquid-chromatography-electrospray ionization mass spectrometry (LC-ESI-MS/MS) using a Termo Scientifc ™ Q Exactive Orbi- trap instrument (Termo Scientifc, USA).Separation was achieved using a C18 Hypersil Gold column (100 mm × 2.1 mm, 1.9 μm, TermoScientifc) kept at 35 °C.Te fow rate was set at 0.3 mL/min and sample injection volumes were 10 μL.Te mobile phases were water (mobile phase A) and acetonitrile (mobile phase B), both acidifed with 0.1% formic acid (v/v).Te gradient program started at 5% B (held for 2 minutes), increased to 100% B in 15 minutes, returned to initial conditions in 5 minutes, and equilibrated until 25 minutes.Te ion source was operated in both positive and negative electrospray ionization modes for all experiments.Data were processed using Xcalibur version 4.1.31.9 software.Microcystins were quantifed using the peak-area method described by Lawton and Edwards (2008).Te retention time of standards was used to identify the peaks, and quantifcation was accomplished by using standard calibration curves.
2.6.Data Analysis.Data were tested for normality using the Shapiro-Wilks test.Upon confrmation of the normality assumption, a two-way ANOVA was conducted to test whether the diferent blue-green algae toxins difered signifcantly between the two study sites.A post hoc test (Tukey) was conducted to identify which pairs difered signifcantly.All the statistical analyses were conducted in the R STATS package.Te results were considered signifcant at p < 0.05.
Te identity of Tanzanian sequences from this study and other sequences from GenBank ranged from 85 to 100%.Four sequences from this study and six additional sequences from GenBank (representing various species of cyanobacteria and noncyanobacteria) were subjected to phylogenetic analysis.Te accession numbers for sequences subjected to phylogenetic analysis of samples collected from Mindu Dam are shown in Table 2.

4
Journal of Toxicology Four uncultured sequences from this study and six additional sequences from the database (representing various species of cyanobacteria and noncyanobacteria) were subjected to phylogenetic analysis.Te results confrmed that the species from this study were related to four species from the database (Figure 2).Te frst group contains species from this study related to the uncultured Antarctic cyanobacterium with Accession no.AY151723.1;the second group contains species from this study related to the uncultured bacterium with Accession no.LC257556.1;and the third group contains species belonging to the genus Anabaena with Accession no.HE975015.Te fourth group contains species from this study related to Microcystis aeruginosa with Accession no.LC557463.1.

Genetic Variation and Phylogenetic Relationships.
Te nucleotide sequence of the microcystin mcyE gene of TZ: MO-MDS1g_Hep (Accession no.OP339494) showed a 96.77% identity to the sequence from Microcystis aeruginosa (Accession no.LC557463.1)based on BLAST results and GenBank sequences.A phylogenetic tree of the microcystin gene sequences confrmed that they were closely related to Microcystis aeruginosa (Accession no LC557463.1)and distantly related to Cylindrospermopsis raciborskii (Accession no.MH476352.1 (Figure 4).

Water Quality Variables and Teir Infuence on Algal
Bloom.Te results of various water quality parameters collected from the two study sites are presented in Table 5. Te analysis revealed statistically signifcant spatial variations between the two sites (p < 0.05) for all parameters except total phosphates (p > 0.05).Nyumba ya Mungu Dam exhibited signifcantly higher temperature values, dissolved oxygen (DO), and electrical conductivity (EC) than the Mindu Dam.Conversely, the Mindu Dam displayed signifcantly higher levels of chlorophyll-a (Chl-a), nitrate (NO 3 ), pH, and turbidity than the Nyumba ya Mungu Dam.

6
Journal of Toxicology

Correlations among Water Quality Parameters.
Correlations among the water quality parameters were analysed using Spearman's correlation test.Te results (Figure 5) revealed that the nature of the correlations varied between the two sites.At Mindu Dam, signifcant positive correlations (p < 0.05) were observed between Chl-a and DO, TDS and pH, and EC and pH, as well as temperature and turbidity.A signifcant negative correlation was observed between EC and turbidity, as well as DO and NO 3 .On the other hand, at Nyumba ya Mungu Dam, a statistically signifcant positive correlation was observed between PO 4 and NO 3 , PO 4 and turbidity, as well as NO 3 and turbidity (p < 0.05).A signifcant negative correlation was found between Chl-a and pH, temperature and PO4, and NO 3 and turbidity.

Discussion
Tis study aimed to identify toxin-forming blue-green algae and quantify the levels of toxins, specifcally focusing on Microcystis aeruginosa.Our fndings confrm the presence of Microcystis species in both the Mindu and Nyumba ya Mungu Dams, indicating the occurrence of toxin-forming blue-green algae in these environments.Te maximum likelihood tree derived from the analysis of the 16S rRNA uncultured algal bloom sequences from Mindu Dam exhibited distinct and accurately identifed species (Figure 2).All species in the tree were categorised as blue-green algae, except for TZ: MO-MDS2 (Accession no.OP297380), which showed a close relation to an uncultured bacterium species.In the phylogenetic tree, TZ: MO-MDS5 Tese fndings are consistent with those of Kimambo et al. [2], who characterised common species of blue-green algal blooms.
A polymerase chain reaction (PCR) test was used to screen for the presence of genes associated with the production of toxins.Te mcyE gene was detected, which is the gene responsible for the production of toxic genes.Te use of gene-specifc primers confrmed the presence of toxic genes in the dams.Te phylogenetic trees for the amplifed microcystin gene (Figure 4) indicate a close relationship with Microcystis aeruginosa (Accession no.LC557463.1).Chemical analysis further confrmed that toxic genes were present in the dams.Tese fndings agree with those of Benredjem et al. [70].Te presence of diferent species of blue-green algae (cyanobacteria), noncyanobacteria, and Microcystis species in this study reveals high genetic diversity, as these species cluster with diferent species reported in previous studies by Kimambo et al. [2]; Yuan et al. [35]; Yadav et al. [76]; and Karan et al. [69].
We also quantifed the blue-green algal toxins microcystin-LR, -RR, and -YR during this study.Te concentrations of all toxins were within the WHO advisory     Journal of Toxicology reported the presence of Microcystis species in Tanzanian freshwater, supporting our fndings.Furthermore, Mchau et al. [63] quantifed Microcystins in Lake Victoria, Tanzania, further supporting our results.Tese consistencies suggest a shared occurrence of Microcystis species and their toxin production in various Tanzanian freshwater bodies.

Journal of Toxicology
A study of water quality in two dams found that there were signifcant diferences between the two sites.Te Mindu Dam had higher levels of chlorophyll-a, DO, TDS, EC, temperature, and turbidity.Te Nyumba ya Mungu Dam had lower levels of chlorophyll-a and only showed weak positive associations with PO 4 , NO 3 , and turbidity.Tese fndings highlight the complex interplay between chlorophyll-a and other water quality variables.Te prevailing environmental conditions in the two reservoirs are likely to play a signifcant role in supporting and enhancing the production of toxins through algal blooms.Our study did not fnd a clear link between chlorophylla and nutrient levels.Tis could be due to the timing of our sampling.Te fndings are inline with those of Pérez-Ruzafa et al. [79] that reported low correlation of chlorophyll-a to nutrients in small areas and over short periods time.In addition, it is important to note that the growth of chlorophyll-a is not solely determined by nitrate and phosphate levels.Other factors, such as light availability [80] and various micronutrients [81], exert considerable infuence on the dynamics of chlorophyll-a.Tese nuanced factors were regrettably not taken into account within the scope of this particular study.Te study provides valuable insights into the connections between water quality variables and algal blooms, but it has some limitations.It is important to note that the complex nature of natural systems makes it difcult to isolate individual factors that contribute to bloom dynamics.Te study did not delve into the precise mechanisms that trigger toxin production by algae.In addition, the correlations that were found do not necessarily prove causation.Additional research, including controlled experiments, is needed to uncover the exact interplay between water quality variables and bloom dynamics.10 Journal of Toxicology Despite the stated limitations, our results contribute to understanding the genetic diversity and toxin production of cyanobacteria in Tanzanian water bodies.Te fndings can guide future studies on the occurrence, distribution, and potential risks associated with toxin-forming cyanobacteria in freshwater ecosystems.Te practical applications of this study are signifcant, as they underscore the importance of regular monitoring and assessment of water bodies for the presence of toxin-forming blue-green algae.Tis study highlights the need to implement efective water quality management strategies and public health protection, particularly in areas with prevalent blue-green algal blooms.Furthermore, our fndings can provide valuable insights for crafting focused mitigation and control strategies aimed at minimizing the risks linked to blue-green algal toxins.Tis can be achieved through the formulation of site-specifc management plans that comprehensively address the factors that contribute to both bloom formation and toxin production.
Overall, our study extends previous research fndings by providing molecular identifcation of toxin-forming bluegreen algae and quantifying toxin levels in selected strains, with a focus on Microcystis aeruginosa.By comparing our results with other studies, we gain a broader understanding of blue-green algal diversity, toxin production, and potential variations across diferent water bodies.However, further investigations are warranted to explore additional genetic markers and conduct comprehensive assessments to enhance our understanding of bluegreen algal dynamics and their associated toxins in diverse aquatic environments.

Conclusion
In conclusion, this study provides valuable insights into the presence and genetic diversity of blue-green algae (cyanobacteria) in Tanzanian waterbodies, shedding light on their potential risks and implications for water quality management and public health protection.By confrming the occurrence of Microcystis species and their toxin production in the Mindu and Nyumba ya Mungu Dams, we contribute to the understanding of blue-green algal dynamics in these environments.Te consistent fndings with previous studies confrm the robustness of our results and support the shared occurrence of Microcystis species in Tanzanian freshwater.
Identifying specifc genetic markers and quantifying blue-green algal toxins highlight the importance of regular monitoring and assessment to mitigate the risks associated with blue-green algal blooms.Te study emphasises the need for implementing efective strategies for water quality management and underscores the signifcance of targeted mitigation measures to safeguard public health.Te fndings contribute to a broader understanding of blue-green algal dynamics and their associated toxins in Tanzanian water bodies and freshwater ecosystems worldwide.Tis study is a stepping stone for future research, encouraging further investigations into additional genetic markers and comprehensive assessments to enhance our understanding of blue-green algal ecology and their potential impacts.

Figure 1 :
Figure 1: Map of Tanzania showing the study area and sampling points at Mindu Dam (right) and Nyumba ya Mungu Dam (left) (data source: own feld data).
bloom; 2 MD: Mindu Dam; 3 refers to accession numbers issued by NCBI following the submission of the nucleotide sequences; 4 the automatically generated identities obtained using BLAST in GenBank hosted by NCBI.

Figure 2 :
Figure2: Maximum likelihood tree based on the 16S rRNA gene of uncultured algal bloom sequences (1500 bp) (sequences from other species were retrieved from GenBank).Te coloured dots are the data from this study.Te uncultured archaeon clone (JQ989431.1)was used as an out-group.1000 bootstrap replications test was used to determine the nodes' robustness.

1 Figure 3 : 1 Uncultured 1 Uncultured 1 Uncultured
Figure 3: Maximum likelihood tree based on cultured water algal cell sequences of 16S rRNA gene (1500 bp).Sequences from other species were obtained from GenBank.Te dots are the data of this study from Tanzania.Pseudomonas sp.(MW578905.1)was used as an out-group.Node robustness was assessed by performing 1000 bootstrap replications.

Figure 4 :
Figure 4: Maximum likelihood tree based on microcystin gene sequences (472 bp).GenBank was used to get sequences from other species.Te red dot is the data of this study from Tanzania.Te uncultured bacterium sp.(Accession no.LC257556.1),indicated with a black colour, was used as an out-group.Node robustness was assessed by performing 1000 bootstrap replications.

Figure 5 :
Figure 5: Correlations among the water quality parameters.Positive correlations are represented in blue, while negative correlations are shown in red.Te colour's intensity and the circles size are proportional to the correlation coefcients.Crosses denote correlations considered statistically insignifcant (p value >0.05).

Table 1 :
Te list of taxa and their GenBank accession numbers used for phylogenetic analysis of the 10 sequences obtained from this study.

Table 2 :
Identities of the 16S rRNA gene for blue-green algae obtained from Mindu Dam samples.

Table 3 :
Identities of partial nucleotides sequence of blue-green algae obtained from Nyumba ya Mungu Dam samples.

Table 4 :
Summary statistics for diferent types of blue-green algae toxins at Nyumba ya Mungu and Mindu Dam.

Table 5 :
Descriptive statistics for water quality parameters in Nyumba ya Mungu and Mindu Dams.Rows sharing the same letter within each parameter are not signifcantly diferent from each other (p > 0.05).