Next Article in Journal
Venom Ontogeny in the Mexican Lance-Headed Rattlesnake (Crotalus polystictus)
Next Article in Special Issue
Effects of Dietary Astaxanthin Supplementation on Energy Budget and Bioaccumulation in Procambarus clarkii (Girard, 1852) Crayfish under Microcystin-LR Stress
Previous Article in Journal
The Antioxidant Gallic Acid Inhibits Aflatoxin Formation in Aspergillus flavus by Modulating Transcription Factors FarB and CreA
Previous Article in Special Issue
Development of Time-Resolved Fluoroimmunoassay for Detection of Cylindrospermopsin Using Its Novel Monoclonal Antibodies
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Toxins
Volume 10
Issue 7
10.3390/toxins10070269
toxins-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Presence of Toxic and Non-Toxic Cyanobacteria in the Sediments of the Limpopo River Basin: Implications for Human Health

by
Murendeni Magonono
1,
Paul Johan Oberholster
2,
Addmore Shonhai
3,
Stanley Makumire
3 and
Jabulani Ray Gumbo
1,*
1
Department of Hydrology and Water Resources, School of Environmental Sciences, University of Venda, Thohoyandou 0950, South Africa
2
Council for Scientific and Industrial Research, Natural Resources and the Environment, Stellenbosch 7600, South Africa
3
Department of Biochemistry, School of Mathematical and Natural Sciences, University of Venda, Thohoyandou 0950, South Africa
*
Author to whom correspondence should be addressed.
Toxins 2018, 10(7), 269; https://doi.org/10.3390/toxins10070269
Submission received: 10 May 2018 / Revised: 19 June 2018 / Accepted: 21 June 2018 / Published: 3 July 2018
(This article belongs to the Special Issue Cyanobacteria and Cyanotoxins: New Advances and Future Challenges)
Browse Figures
Versions Notes

Abstract

:
The presence of harmful algal blooms (HABs) and cyanotoxins in drinking water sources poses a great threat to human health. The current study employed molecular techniques to determine the occurrence of non-toxic and toxic cyanobacteria species in the Limpopo River basin based on the phylogenetic analysis of the 16S rRNA gene. Bottom sediment samples were collected from selected rivers: Limpopo, Crocodile, Mokolo, Mogalakwena, Nzhelele, Lephalale, Sand Rivers (South Africa); Notwane (Botswana); and Shashe River and Mzingwane River (Zimbabwe). A physical-chemical analysis of the bottom sediments showed the availability of nutrients, nitrates and phosphates, in excess of 0.5 mg/L, in most of the river sediments, while alkalinity, pH and salinity were in excess of 500 mg/L. The FlowCam showed the dominant cyanobacteria species that were identified from the sediment samples, and these were the Microcystis species, followed by Raphidiopsis raciborskii, Phormidium and Planktothrix species. The latter species were also confirmed by molecular techniques. Nevertheless, two samples showed an amplification of the cylindrospermopsin polyketide synthetase gene (S3 and S9), while the other two samples showed an amplification for the microcystin/nodularin synthetase genes (S8 and S13). Thus, these findings may imply the presence of toxic cyanobacteria species in the studied river sediments. The presence of cyanobacteria may be hazardous to humans because rural communities and farmers abstract water from the Limpopo river catchment for human consumption, livestock and wildlife watering and irrigation.
Keywords:
cyanobacteria; cyanotoxins; nutrient enrichment; akinetes; harmful algal blooms; PCR; phylogenetic analyses
Key Contribution: Presence of viable cyanobacteria akinetes and cysts in river sediments; a source of inoculum of cyanobacteria growth in the Limpopo river basin. Some of the cyanobacteria species are toxic.

1. Introduction

Toxic and non-toxic cyanobacteria species are on the increase in most parts of the world, including in South Africa. The emergence and resurgence of harmful algal blooms (HABS) is due to eutrophication. The toxic cyanobacteria are known to carry genes that produce cyanotoxins which are lethal to humans. However, the toxic and non-toxic cyanobacteria species merely differ in the mcy gene content, which is the peptide synthetase producing microcystin [1]. This may explain the observation of non-detectable microsystin toxin despite the presence of mcy gene [2]. A study by Frazao et al. [3] used the PCR method to determine molecular analysis of genes involved in the production of known cyanotoxins, microcystins, nodularins and cylindrospermopsin. The toxic strains of the cyanobacteria genera, Leptolyngbya, Oscillatoria, Microcystis, Planktothrix and Anabaena are known to have in common the mcy (A–E, G, J) genes that are involved in the biosynthesis of microcystin [1,3]. The nodularin cyanotoxin is linked to the nda synthetase gene, a polyketide synthase (PKS) and nonribosomal peptide synthetase (NRPS) and biosynthesized by Nodularia spumigena NSOR10 cyanobacteria [4]. The review studies carried out by Pearson et al. [4] and Sinha [5] showed that cyanotoxin cylindrospermopsin is linked to the genes aoa or cyr (A–O) and is now known to be biosynthesized by a number of cyanobacteria genera, such as Cylindrospermopsis and Umezakia natans in Japan; Aphanizomenon ovalisporum in Israel, Australia, USA and Spain; Anabaena bergii in Australia; Raphidiopsis raciborskii in Thailand, China and Australia; Raphidiopsis curvata in China; Aphanizomenon flos-aquae in Germany; Anabaena lapponica in Finland; Lyngbya wollei in Australia; Aphanizomenon gracile in Germany; Oscillatoria sp. in the USA Aphanizomenon sp. in Germany; and Raphidiopsis mediterranea, Dolichospermum mendotae and Chrysosporum ovalisporum in Turkey.
The emergence of toxic cyanobacteria species during a bloom period is linked to environmental factors such as light, nutrient enrichment or nutrient depletion, and the presence or non-presence of predators [4]. Eutrophication, a build-up of organic matter produced by phototrophs, such as cyanobacteria [6,7], is often seen as algal blooms and driven by inputs of nitrogen and phosphorus. Cyanobacteria blooms are a major concern worldwide due to the production of cyanotoxins which are harmful to humans [8]. Cyanobacteria tend to proliferate during the summer when concentrations of total phosphorus fall to 100–1000 µg/L [9]. A variety of hypotheses explain why cyanobacteria blooms are becoming increasingly prevalent [10,11,12]. The most common hypotheses focus on nutrient conditions [10,11,13,14,15,16,17] and nutrient cycling [18] within a water body, as well as aspects of cyanobacteria cell physiology, such as their ability to migrate vertically within the water column, fix atmospheric nitrogen and to produce cyanotoxins [19,20,21,22].
Cyanobacterial blooms are often associated with eutrophic conditions [23,24,25]. Various studies have documented the relationship between nitrogen and phosphorus concentrations, speciation and stoichiometry, and cyanobacteria occurrence [10,13]. A recent study reported that Microcystis growth response increases in relation to nitrogen over phosphorus [26]. The same study [26] also reported that the growth response of toxic Microcystis to nitrogen was greater than non-toxic strains. Some species of cyanobacteria are known for their ability to fix nitrogen and thus giving them high chances of producing cyanotoxins [27]. Other studies have shown that microcystin toxicity is also influenced by changes in pH, temperature and light intensity [28,29,30]. A study conducted by Beversdorf et al., [27] indicated that some of the non-nitrogen fixing cyanobacteria may produce toxins because of nitrogen stress events.
However, a review of the available literature shows that there is limited information on the occurrence of toxic and non-toxic cyanobacteria species in relationship with river basin sediments on the African continent [31]. Thus, the main objectives of the study were to: (1) assess the physical-chemical characteristics of river sediments and how these contribute to the resurgence and growth of cyanobacteria species should ideal river flow conditions return; (2) use the FlowCam and molecular techniques to identify toxic and non-toxic cyanobacteria genes in the river sediments; and (3) to use the 16S rRNA in identifying the cyanobacteria species and explore relationships among the cyanobacteria species in the river sediments.

2. Results

2.1. The Physical-Chemical Characteristics of the River Sediments

The physical characteristics of the river sediments drawn from the different tributaries of the Limpopo River basin and the Limpopo River itself showed considerable variation (Figure 1). The electrical conductivity (EC) and total dissolved solids (TDS) values in the river sediments ranged between 21.2 and 1269 μS cm−1 throughout the sampling sites. The pH values were between 6.4 and 8.5, while the total phosphorus concentration values in the river sediments ranged from 0.5 mg/L to 6.3 mg/L (Figure 2). The highest total phosphorus value was recorded for the sediments from the Nzhelele River (S12) near the Mphephu Resort and downstream of the Siloam oxidation ponds. The second highest phosphorus concentrations were measured at the Shashe River (S13), with the total phosphorus measuring 1.2 ± 0.5 mg/L at sample point S18.
Finally, the nitrogen concentration values in the river sediments ranged from 1.5 mg/L to 6.5 mg/L (Figure 3). The highest concentrations were recorded for the sample from the Nzhelele River (S12) near the Mphephu Resort and downstream of the Siloam Hospital oxidation ponds, while the total nitrogen at site S18 was 6.25 mg/L.

2.2. The Presence of Cyanobacteria in the River Sediments

Table 1 shows the presence of toxic and non-toxic cyanobacteria species that were detected in the Limpopo River basin. The dominant cyanobacteria observed is the filamentous Leptolyngbya species, followed by the Synechocystis species (non-toxic and toxic strains), toxigenic Microcystis species, and toxigenic Raphidiopsis raciborskii species. The FlowCam showed the presence of the different cyanobacteria species in the Limpopo River basin, as shown in Table 1 and Figure 4. The dominant cyanobacteria species identified from the samples were the Microcystis species, followed by the Raphidiopsis raciborskii, Calothrix, Phormidium and Planktothrix species. Finally, no cyanobacteria species were detected in the Mokolo River (S7).

2.3. PCR Analysis of the 16S rRNA Gene

Multiple fragments were obtained for each sample by sequencing with both forward and reverse primers, and these samples were edited and assembled using the Staden package [32]. All assembled sequences were aligned in BioEdit v7.0.9 [33]. However, the sample collected from the Limpopo River (S1) was not shown in Figure 5, since it was used as the test sample. It was also noted that the amplified fragment from the test sample only produced 100 bp, while around 650 bp was expected. Other samples, such as the samples Limpopo River (S15), Limpopo River (S17) and Musina borehole abstraction point (S16), did amplify, but failed to assemble in the Staden package [32]. The assembled sequences were run on the BLAST algorithm [34] to identify closely similar sequences already deposited in GenBank via NCBI, and the outcomes are shown in Table 2.
It must be understood from the BLAST algorithm [34] that more than 98% similarity obtained matches the sample to the correct species, more than 90% similarity obtained matches the sample to the correct genus, while more than 80% similarity obtained matches the sample at the Family level. The PCR products that were separated by gel electrophoresis are shown in Figure 5. The presence of the different bands indicated a positive amplification, whereas a blank sample indicated a negative amplification. The blank samples where repeated several times and failed to amplify. Almost all of the samples showed positive amplification, which confirmed the presence of cyanobacterial DNA in the samples. The two samples which showed no amplification were drawn from the Mogalakwena (S4) and Lephalale Rivers (S6). The BLAST algorithm [34] showed that more than 98% similarity obtained matches the sample to the correct species, more than 90% similarity obtained matches the sample to the correct genus, while more than 80% similarity obtained matches the sample to the correct family.
BLAST data from the samples drawn from the Mokolo River (S7), Crocodile River downstream of Hartbeespoort Dam (S8) and the Shashe River (S14) did not identify the cyanobacteria up to the species level. However, the cyanobacteria from the samples drawn from the Notwane River (S2), Sand River upstream (S3), Mawoni River (S5), Nzhelele River downstream (S9), Sand river downstream and the Limpopo River (S18) (abstraction point at 1.68 m) were identified up to genus level. Lastly, the cyanobacteria from the sampled Limpopo River (S16) (abstraction point at 0.0 m) was identified up to the family level. Furthermore, the samples from Crocodile River downstream (S11) (near bridge on road D1235), Nzhelele River upstream (S12) and Mzingwane River (S13) showed similarities and there were no families that could be detected for these samples.

2.4. Detection of Genes Involved in Toxin Production

The detection of cyanotoxins was done through detecting genes for the proteins that make toxins. This was achieved with PCR by amplification of microcystin/nodularin synthetase using the HEP primer pairs and cylindrospermopsin polyketide synthetase genes using a PKS primer pair. It must be noted that the detection of the genes involved in the biosynthesis of toxins does not confirm the production of the toxins in the field. The mcyA-C primer pair and M13 and M14 primer pair were also used to determine the presence of the genes that contain the proteins for toxins production. However, the genes were not detected, as there was no amplification in most of the samples of any of the genes associated with the proteins that produce toxins. Nevertheless, a few samples, such as the Sand River (S3) upstream and Nzhelele River (S9) downstream (Figure 6), showed the amplification of the cylindrospermopsin polyketide synthetase gene. This confirmed the presences of cyanotoxin, cylindrospermopsin in the sediment samples and was attributed to the cyanobacteria species, Raphidiopsis raciborskii (Table 3).
The HEP primer pair produced two positive results for samples from Crocodile River (S8) and Mzingwane River (S13). Both positive results were attributed to the presence of toxigenic Microcystis sp. (Table 3). The latter is an important finding, since water supplies from the Limpopo River basin are used by water utilities for drinking water supplies, and by commercial and subsistence irrigation farmers for the production of food crops and livestock watering (Figure 7).

2.5. Phylogenetic Relationship

The relationship between the samples and their most similar species, as noted from the BLAST search, was confirmed by the phylogenetic tree, and the relationships between some cyanobacteria species from different samples (Figure 8). The first confirmation was on the similarity of samples from the Crocodile River (S8) downstream Hartbeespoort Dam and the Shashe River (S14) to Leptolyngbya boryana with 99% bootstrap confidence. Secondly the similarity of the Musina borehole extraction (S16) sample to Alkalinema pantanalense, with 98% bootstrap, and the similarity of the samples from Sand River (S3) upstream. Another similarity was evident in the Nzhelele River (S9) downstream near Tshipise and Mokolo River to Synechocystis sp. PCC 6803. The other similarity was Mawoni River (S5) downstream of Makhado oxidation pond to Leptolyngbya sp. with 97% bootstrap confidence, with the Notwane River (S2) to uncultured Leptolyngbya sp. with 99% bootstrap confidence, and lastly the Sand River (S10) downstream to the filamentous cyanobacterial species Spirulina laxissima with 100% bootstrap confidence.
However, the detection of cyanobacteria at the Musina borehole extraction (S16) and the Sand River (S3) may suggest that there were aquatic animals such as fish, dispersal or transportation of cyanobacterial cells from the entrance (mouth) of Sand River towards the Musina abstraction point (Figure 9). In simple terms, there was an upstream transport of cyanobacteria species that was facilitated by aquatic animals, but this requires further investigation. The other matches from the BLAST search include the Musina Borehole extraction point (S16) to Leptolyngbya sp., as well as the Crocodile River (S11) near bridge on road D1235 and upstream of Thabazimbi town to uncultured Cyanobacteria clone. However, the latter bootstrap confidence levels were between 55 and 61%, respectively. It was evident from the data that a divergence matrix can be used to verify the truth of both the BLAST search and phylogenetic tree. The divergence matrix confirmed that cyanobacteria from the Crocodile River (S8) downstream of Hartbeespoort Dam and from Shashe River (S14) were the same Leptolyngbya boryana species, since they both showed at least 98% similarity to this species.
Thus, the current study indicates that there is DNA evidence to suggest a similarity between the cyanobacteria at the Musina abstract point and that from the Crocodile River system. The possibility thereof lies in the fact that the Musina abstraction point was downstream from the Crocodile River, which flows into the Limpopo River (Figure 7). However, samples from the Nzhelele River upstream near the Mphephu Resort and Mzingwane River (Zimbabwe) did not match. Nevertheless, the relationship between the cyanobacteria species from specific locations were identified by a Divergence Matrix (Table 4). In addition, the same species were detected by the difference co-efficient of 0.00, whereas completely unrelated species were detected by the co-efficient of 1.00.
The cyanobacteria species from the Crocodile River (S8) were the same species as the cyanobacteria from the sampled Shashe River (S14), since they had less than 1% difference (0.006). This may have been expected, since the Shashe River is downstream of the Crocodile River (Figure 9). The cyanobacteria species from the Mokolo River (S7) and the Nzhelele River (S9) share undetectable differences. However, a comparison shows that there was a difference between the cyanobacteria species from the Notwane (S2) and Mawoni Rivers (S5). The cyanobacteria which differed the most from the other species were the cyanobacteria species from the Notwane River (S2) and Limpopo River (S16). The latter sampling sites’ species also differed from each other, with 28%, while their comparison co-efficient range from 0.17 to 0.28. Furthermore, the Nzhelele River upstream (S12) and Limpopo River (S16) species differed from each other with 28%, while their comparison co-efficient ranged between 0.312 to 0.492, which was the highest for all species.
The first observation was that Uncultured Cyanobacterium clone HQ189039.1 could not be used for the phylogenetic tree because of its length (about 480 bp). This is because the t complete deletion option of gaps and missing information in MEGA 7 [35] was used. The second observation was that two outgroup sequences had been used in phylogenetic alignment.

3. Discussion

The physical chemical data generated in the current study shows that there were large variations in sediment EC between the different sampling sites while the sediment temperature was ≥22 °C during all the sampling trips. High temperatures arising from climate change have been reported as an important factor in the global expansion of harmful algal bloom worldwide [36]. Rising temperature exceeding 20 °C can promote the growth rate of cyanobacteria, whereas the growth rate other freshwater eukaryotic phytoplankton decreases, which is regarded as a competitive advantage for cyanobacteria [37]. A study by O’Neil et al. [9] reported that higher temperatures promote the dominance of cyanobacteria and favor the production of microcystins, as well as resulting in an increase in their concentration.
The high pH value measured during the current study may have a competitive advantage for many cyanobacteria, because of their strong carbon-concentrating abilities compared to eukaryotic phytoplankton species [38]. A laboratory experiment carried out by Jahnichen et al. [39] on Microcystis aeruginosa showed that microcystin production started when pH exceeded 8.4, thus indicating a lack of free carbon dioxide (CO2).
The increased input of nutrients into the surface water is the main factor responsible for massive proliferations of cyanobacteria in fresh water, brackish and coastal marine ecosystems. However, phosphorus and nitrogen nutrients in high levels lead to accelerated growth of cyanobacteria [40,41].
Thus, the higher concentration of phosphorus measured in the current study downstream of the Siloam oxidation ponds may be due to the discharge of sewage effluent [42]. The low concentration of phosphorus measured in the Lephalale River (S6) is possibly related to less anthropogenic land use activities upstream of this sample site [43]. Phosphorus has been implicated more widely than nitrogen as a limiting nutrient of phytoplankton and cyanobacteria in freshwater systems [44]. A minimum amount of phosphorus entering or becoming soluble in a water body can trigger a significant algal bloom [45]. The impact of excess phosphorus on receiving rivers or streams is evident from the green coloration of surface water owing to the presence of phytoplankton or cyanobacteria. The Limpopo River (S1) receives inflows from both the Notwane and Crocodile Rivers, and these contribute significantly to the phosphorus loading of the Limpopo River. Furthermore, the main source of phosphorus in the Notwane River (S2) is the municipal discharge from the Glen Valley sewage plant and agricultural runoff from irrigated farms and livestock ranching in the river’s catchment [23,46]. The Crocodile River receives sewage effluent from upstream catchment land use activities such as the discharge of sewage effluent into tributaries of the Crocodile River, discharge into Crocodile River itself and agricultural runoff [47,48]. The Sand River (S3) receives municipal nutrient discharge from the Polokwane sewage plants and rainwater runoff that would contain fertilizer from agricultural activities in the river sub catchment [49]. The sample point on the Mogalakwena River (S4) was downstream of the Mokopane, Modimolle and Mookgophong towns’ sewage plants, golf courses, game farming, livestock farming and irrigated farmlands [50]. After the town of Mokopane, the Nyl River is renamed to the Mogalakwena River. The Mzingwane River (S13) receives municipal discharge from the Filabusi, Gwanda and West Nicholson sewage plants and agricultural runoff from irrigated farms and livestock ranching in these areas [51], and this may be attributed to sewage plants upstream in Francistown and agricultural runoff from irrigated farms and livestock ranching [48,52]. These rivers are part of the Limpopo River’s tributaries and contribute to the successive loading of phosphorus in the Limpopo River (S15–S16) [53].
The highest value of nitrogen was recorded in the Nzhelele River (S12) near the Mphephu Resort and downstream of Siloam hospital oxidation ponds. The reason for the detection of these high nitrogen values is possibly related to the discharge of sewage effluent from the Siloam hospital [42]. Filamentous cyanobacteria can obtain nitrogen by fixing the atmospheric nitrogen gas and converting it to nitrate for their growth [54]. Nitrogen is a common gas (79%) that is found in the atmosphere. Thus, cyanobacteria genera such as Anabaena are able to utilize atmospheric nitrogen in addition to nitrate originating from the river sediments [54,55]. The other sample sites with nitrates in excess of 2 mg/L are Sand River (S4), Mawoni River (S5), Crocodile River (S11), Mzingwane River (S13), and Limpopo River (S16 to S18). All these tributaries have one in common source of pollution upstream, namely, a municipal sewage plant, and are also surrounded by farmland where commercial irrigation farming is practiced, as in the case of the Crocodile, Notwane, Shashe, Mzingwane and Sand rivers. Subsistence agriculture is practiced in the case of the Mawoni and Mzingwane rivers [46,48,49,50,51,52]. The Crocodile River also receives inflows from eutrophic Hartbeespoort Dam [47]. The Limpopo River (S16) is downstream of all the sample points, and this shows the cumulative discharge of nitrates originating from the tributaries, causing an increase in concentration of nitrogen. The Musina local municipality has drilled 8 boreholes in the Limpopo river bed, and most of these boreholes are located close to S16, and thus there is a possibility of cyanotoxin contamination of the borehole water [56]. Thus, further research is required to determine if there is cyanotoxin contamination of borehole water.
Botha and Oberholster [57] performed a survey of South African freshwater bodies between 2004 and 2007, using RT-PCR and PCR technology to distinguish toxic and non-toxic Microcystis strains bearing mcy genes, which correlate with their ability to synthesize the cyanotoxin microcystin. The study revealed that 99% of South Africa’s major impoundments contained toxicogenic strains of Microcystis. The study by Su et al. [58] in the Shanzi impoundment, China showed that the sediments were the source of cyanobacteria inoculum. This implies that the cyanobacteria flocculates in the sediments during periods of adverse environmental conditions, such as cessation in river flows. These cyanobacteria cysts or spores then reactivate during periods of river flow. The cyanobacteria cysts and spores are related to the summer environmental conditions in the Limpopo river basin, where the majority of tributaries are perennial and river flows commence during the period of summer rainfall. The river flows disturb the sediments, thus bringing into the water column the cyanobacteria cysts or spores [58]. The source of nutrients in the Limpopo river basin may be attributed directly to sewage discharge of municipal waste water plants such as Glen Valley and Mahalpye on the Botswana side, and on the South Africa side, the western and northern parts of the city of Johannesburg to the town of Musina and indirectly to the agricultural practices of fertilizer application and animal waste [46,48,49,50,51,52].
Cyanobacteria undergo distinct developmental stages [59]. For example, they differentiate into resting cells, spores, akinetes and cysts which represent a survival strategy under unfavorable environmental conditions [55,60]. Under favorable conditions, the cell will germinate again [61]. The ability of cyanobacteria to adapt to adverse dry periods allows them to inhabit the river sediments, as shown by studies by Perez at al. [60], Kim et al. [55] and this study (Figure 10). The study of Kim et al. [55] further illustrated the viable nature of cysts and akinetes in providing the next inoculum of Microcystis, Anabaena, Aphanizomenon and Oscillatoria is Bukhan, Namhan Rivers and Lake Paldang and Kyeongan stream, in South Korea.
As expected, the toxigenic Microcystis species was found in the Crocodile River, downstream of the Hartbeespoort Dam, a eutrophic water impoundment known for the regular occurrence of Microcystis dominated harmful algal blooms [40]. However, our two toxigenic Microcystis strains were different from the seventeen toxigenic Microcystis strains studied by Mbukwa et al. [24] from the Hartbeespoort Dam. The differences may be explained by the different use of mcy primers in identifying the genes expressing toxicity and differences in experimental approach. Our study on the mcyA-Cd primer did not amplify, whereas Mbukwa et al. [24] reported the amplification of the mcyA-Cd genes, showing seventeen toxigenic Microcystis strains. However, during our study, the mcyE genes were positively expressed with the HEP primer and did amplify, but the outcomes were also different from the toxigenic Microcystis strains studies by Mbukwa et al. [24]. During our study, the total genomic DNA was not extracted directly from the sediments, but from cyanobacteria that was cultured in the laboratory. Laboratory culture conditions have been known to alter the toxicity of Microcystis species, as shown by the study of Scherer et al. [62]. In the latter study, the authors mimicked a temperature increase of 10 °C. Under these increased temperature conditions, Microcystis was able to express mcyB gene related to production of toxicity instead of the mcyD gene. This may imply the biodiversity of toxigenic Microcystis strains in Hartbeespoort Dam and the Crocodile River and the Limpopo River basin.
Mbukwa et al. [24] used DNA molecular techniques to identify the two species of Microcystis as M. aeruginosa (origins from Hartbeespoort Dam, South Africa) and M. novacekii (origins from Phakalane effluent, Gaborone, Botswana). The molecular techniques showed the presence of the mcy genes responsible for microcystin encoding, thus confirming that the two Microcystis species did have the potential to produce toxins. The Phakalane pond effluent is discharged into the Notwane River, a tributary of the Limpopo [23]. An earlier study by Basima [51] upstream of the Mzingwane S13 sample point showed the abundance of cyanobacteria genera dominated by Microcystis species followed by Anabaena and Nostoc species in water impoundments situated inside the Mzingwane River. In the lower Limpopo River, situated in Mozambique, at the Chokwe irrigation scheme, which receives irrigation waters from Maccaretane Dam, Pedro et al. [25] reported the presence of Microcystis species and microcystin-LR concentrations of 0.68 ppb. The latter concentrations were linked to the presence of the mcyB and mcyA genes in collected water samples. Mikalsen et al. [63] identified eleven Microcystis species containing different variants of the mcyABC (toxic species), and seven Microcystis species that lacked the mcyABC gene (non-toxic species). A study by Davies et al. [64] on four temperate lakes in the northwest of the USA showed that the increase in water temperature contributed to an increase in toxic Microcystis species (possessing the mcyD gene). Yamamoto [65] and Oberholster et al. [66] have shown that the Microcystis species adopt survival strategies to mitigate harsh external environments such as reduced river flow, a major characteristic of the Limpopo River, by sinking into the sediments.
The Limpopo river basin is characterized by extreme weather events such as heatwaves, floods and drought [67]. Could the latter, including extreme heatwaves, possibly have contributed to toxic or non-toxic Microcystis species? The presence of microcystins in the rivers may constitute a health risk, especially for the communities that may be in contact or drink the polluted water without any form of treatment or suitable treatment that is able to remove the toxins in the water. The convectional method for water treatment is not convenient for the removal of microcystins in water [68]. Drinking water treatment processes might trigger the release of hepatoxin into drinking water by disrupting the trichomes of cyanobacteria [69]. Thus, the presence of cyanotoxins can also poison the livestock and game animals (wildlife) in transfrontier parks such as Kruger National Park, Gona-re-zhou National Park and Mapungubwe National Park [70]. Microcystins have already been implicated in the death of wildlife in the Kruger National Park [71]. Cyanotoxins have been implicated in the negative growth (stunting) of plants, and this may have serious repercussions for irrigation farmers [72].
The evolutionary tree constructed could not be used for phylogenetic purposes because of two important reasons: (1) the number of samples used for PCR per river site was not enough to make a conclusive argument; and (2) the cyanobacteria were the expected products which needed to be identified. Hence the tree was used to verify the identification as done by BLAST search; however, the phylogenetic relationship was basically done by divergence matrix, and combined discussion followed the divergence matrix.

4. Conclusions

Many countries in Africa have reported cases of intoxication and death of animals that may have been caused by cyanobacterial toxins. Monitoring and or reducing the nutrient loads into the river system will decrease the threat of cyanobacteria blooms to human and animal health. The results obtained in the current study indicated the presence of toxic and non-toxic cyanobacteria species in the bottom sediments of the Limpopo River and its tributaries. Molecular tools were used in the present study to determine non-toxic and toxic cyanobacteria based on genes that produce proteins related to cyanotoxins. The presence of nutrients, phosphates and nitrates in the river sediments did stimulate the growth of the cyanobacteria during summer river flow periods. Furthermore, the expression of genes that have the potential to produce toxins, for example cylindrospermopsin and microcystin/nodularin in the river sediments indicate a potential risk to the environment and human health. The cyanotoxins are harmful to humans who consume the water originating from boreholes located inside the Limpopo River basin or drilled along the Limpopo River basin. Secondly, the water supplies from the Limpopo River basin are used by commercial and subsistence irrigation farmers for growing food crops and livestock watering. Thus, presence of cyanotoxins can also adversely affect the livestock and game animals (wildlife) in transfrontier parks. Furthermore, cyanotoxins have been implicated in the negative growth (stunting) of plants, and this may have serious repercussions for the irrigation farmers in this region.

5. Future Research Work

Further studies are required to determine the level and types of cyanotoxins in the Limpopo river basin, since water resources are used for a variety of purposes, such as human consumption, irrigation, livestock and wildlife watering and impact if any on aquatic biodiversity.

6. Materials and Methods

6.1. The Study Area

The study area is the Limpopo River and its major tributaries (Figure 11). The Limpopo River basin consists of four countries: Botswana, South Africa, Zimbabwe and Mozambique [73].
The Limpopo River basin is an arid to semi-arid region where water is of strategic importance to development. Water has a potential limiting effect on all future development in the region. The Limpopo River basin is home to almost 14 million people in four riparian states [74].

6.2. Sampling Sites and Sampling Methods

Sampling sites were selected with the following in mind: (a) accessibility, biotype, e.g., sandy bottom sediment; (b) canopy cover and depth, and (c) river sites receiving inflows of municipal sewage discharges. The 18 grab river sediment samples were collected in October and November 2014. The river sediment samples (~500 g) were collected in sterile glass containers from rivers and tributaries of the Limpopo River (Table 5). The use of river sediments was chosen because most suspended material, including cyanobacteria spores and cysts, settles at the river bottom, where they become part of the sediments in river systems.

6.3. Physical-Chemical Measurements

In the laboratory, the physical measurement of pH, Total dissolved solids (TDS) and electric conductivity (EC) was carried out using Portable pH meter Crison MM40 (Crison Instruments SA, Alella, Spain) on the river sediments. It was first calibrated as per the manufacturer’s guidelines. The pH, TDS and EC of the sediments were determined by the method of Islam et al. [75], in which 50 g of sediment was mixed with 50 mL of distilled water in a 100 mL beaker to produce a ratio of 1:1. The mixture was stirred with a stirring rod to homogenize the mixture and was then left for 30 min to settle. EC, pH and TDS were then measured by inserting the electrodes in the soil solution and readings were taken.

6.4. Nutrient Analysis

The air-dried sediments were subjected to nutrient analysis, and this involved determining Total Phosphate (TP) and Total Nitrogen (TN). The analyses were done in duplicates and the aliquot of all digested samples was analyzed with Merck Spectroquant® Pharo 100 spectrophotometer with a wavelength of 320–1100 nm purchased from Merck (Darmstadt, Germany).

6.4.1. Total Phosphorus Analysis

Total phosphorus was determined by using the perchloric acid digestion method as described by American Public Health Association (APHA) [76]: 2 g of air-dried sediment was acidified to methyl orange with concentrated HNO3, another 5 mL of concentrated HNO3 was added and evaporated on a hotplate until dense fumes appeared. 10 mL each of concentrated HNO3 and HClO4 was added and evaporated gently until dense white fumes of HClO4 appeared. The solution was then neutralized with 6N NaOH and made up to 100 mL with distilled water. Aliquots of the samples were then analyzed with spectrophotometer using phosphate cell test kit (Merck, Darmstadt, Germany).

6.4.2. Total Nitrogen Analysis

Total nitrogen was determined per APHA [76] as ammonia: 1 g of each air-dried sediment sample was treated with 2 mL of sulphuric acid. The sample was heated on a hotplate for 2 h. Aliquots of 50 mL of deionized water were added to each sample. The sample was filtrated through No. 41 Whatman filter paper. The filtrate of each sample was made up to 250 mL with deionized water and 55 mL of 1 M sodium hydroxide solution. Aliquots of the samples were then analyzed with spectrophotometer using a nitrate cell test kit (Merck, Darmstadt, Germany).

6.5. Data Analysis

The physico-chemical and cyanotoxin measurements were conducted in duplicates, and the standard deviation and mean were calculated, using a Microsoft (MS) Excel 2010 spreadsheet for each sampling point. The graphs were plotted using MS Excel.

6.6. The Culture of Cyanobacteria Species in River Sediments

The modified BG11 medium was laboratory-prepared as per Gumbo et al. [77] for cyanobacteria culturing. The 200 mL sterile modified BG11 medium was transferred to sterile 250 mL laboratory jars under sterile conditions and then 200 g of river sediments was added. A total of 18 laboratory jars were incubated for 30 days under continuous light (1100 lux) fluorescent lamps at room temperature. The harvested cyanobacteria cells were subsequently used for identification and molecular characterization.

6.7. The Identification of Cyanobacterial Species Using the FlowCam

The harvested cyanobacteria cells were used to identify cyanobacterial species present in the samples, a bench top FlowCam (Model vs. IV) was used. In the FlowCam system, the sample is drawn into the flow chamber by a pump. Using the laser in trigger mode, the photomultiplier and scatter detector monitor the fluorescence and light scatter of the passing particles. When the particles passing through the laser fan have sufficient fluorescence values and/or scatter, the camera is triggered to take an image of the field of view. The fluorescence values were then saved by the Visual Spreadsheet. The computer, digital signal processor, and trigger circuitry work together to initiate, retrieve and process images of the field of view. Groups of pixels that represented the particles were then segmented out of each raw image and saved as a separate collage image. The image was then captured and compared to the image of cyanobacteria as per the procedure of van Vuuren et al. [78].

6.8. The Identification of Cyanobacterial Species Using Molecular Characterization

The cyanobacteria cells were harvested and used for molecular characterization as per the following procedures, as outlined below:

6.8.1. DNA Extraction and Purification

Samples were freeze-dried and stored at −20 °C for DNA extraction. Total genomic DNA was extracted using the ZR-DuetTM DNA/RNA Miniprep DNA extraction kit from Inqaba Biotech Laboratories South Africa (Pretoria, South Africa). Sample preparation and DNA extraction was carried out following the protocol supplied by the manufacturer.

6.8.2. Detection and Amplification of 16S rRNA by Polymerase Chain Reaction

The PCR method was performed for detection and amplification of 16S rRNA as described briefly by Frazao et al. [3]. The PCR amplification of the cyanobacteria 16S rRNA gene was determined using set of primers 27F/809R (Table 2). Thermal cycling conditions were 1 cycle at 95 °C for 5 min, 35 cycles at 95 °C for 30 s, 55.4 °C for 30 s and 72 °C for 60 s and 1 cycle at 72 °C for 10 min. Reactions were carried out in a 50 μL reaction volume that consisted of 0.5 pmol of each primer (10 pM/μL), 25 μL of Dream Taq master mix (Inqaba Biotech), 19 μL sterile ultra-pure water and 5 μL of DNA sample.

6.8.3. Toxin Gene Detection

The presence of cyanotoxins was determined by PCR using primers that were used for detection of genes involved in the production of nodularins (NOD), microcystins (MC) and cylindrospermopsin (CYN) (Table 6). The NOD gene cluster, nda, consists of nine open reading frames (ndaA-I) [79]. The MC gene cluster, mcy, comprises 10 genes in two transcribed operons, mcyA-C and mcyD-J [80]. The HEP primer pair was used for detection of genes involved in MC and NOD production.
These primers are responsible for sequencing the aminotransferase (AMT) domain, which is located on the modules mcyE and ndaF of the MC and NOD synthetase enzyme complexes, respectively [80,81]. Primers mcyA-C were used to detect the mcyA, mcyB and mcyC genes [82,83]. For detection of CYN production (cyr) genes, the polyketide synthase PKS M4 and M5 primers and the peptide synthetase M13 and M14 primers were used as designed by Schembri et al. [84], who demonstrated a direct link between the presence of the peptide synthetase and polyketide synthase genes and the ability of cyanobacteria to produce CYN.
The PCR reaction conditions that were used were those described for the amplification of the 16S rRNA gene [81]. Concerning the cycling conditions, for mcyA-Cd genes, the thermal cycling conditions were 1 cycle at 95 °C for 2 min, 35 cycles at 95 °C for 90 s, 56 °C for 30 s and 72 °C for 50 s and 1 cycle at 72 °C for 7 min. For HEP and CYN as genes, the thermal cycling conditions were as those for the amplification of the 16S rRNA with an exception for HEP gene annealing temperature of 58.15 °C for 30 s. Positive control was used.

Electrophoresis

PCR products were electrophoresed in 0.8% agarose gel by adding prepared 1.2 g of agarose powder into 150 mL 1X TAE buffer (48.4 g Tris, 11.4 mL Glacial acetic acid, 3.7 g EDTA disodium salt topped up to 1000 mL with deionized water). The mixture was heated until there was complete dissolution. Exactly 10 µL of ethidium bromide was added and mixed thoroughly. The mixture was transferred to the gel-casting tray with the comb already in position and allowed to solidify. The solidified gel was transferred to the running trays. The gel in the tray was covered with 1X TAE buffer. In the first well 3 µL 100 bp of the molecular weight marker was loaded and the samples were loaded from the second well onwards. The gel was run at 100 V and 250 mA for 60 min. The gel was viewed using the Gel doc (Biorad, Hercules, CA, USA) and the picture was taken.

6.8.4. PCR Purification and Sequencing

PCR products were purified using the GeneJet Gel Extraction Kit Thermo Scientific (Pretoria, South Africa) under room temperature as per the protocol provided by the kit manufacturer. The purified DNA was stored at −20 °C. PCR products were sent for sequencing at Inqaba biotech laboratory (Pretoria, South Africa). Sequences were analyzed using the BLAST system (http://www.ncbi.nlm.nih.gov/BLAST/).

Primers

Primers used for PCR amplification were synthesized at Inqaba Biotech (Pretoria, South Africa). Details of primer sequences, their specific targets and amplicon sizes are summarized (Table 6) below.

6.8.5. Phylogenetic Relationship

Additional sequences were downloaded in FASTA format from GenBank through NCBI and combined with assembled sequences. The evolutionary history was inferred using the Neighbor-Joining method [87]. The bootstrap consensus tree inferred from 1000 replicates [88] is taken to represent the evolutionary history of the taxa analyzed [88]. Branches corresponding to partitions reproduced in fewer than 50% bootstrap replicates are collapsed. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) is shown next to the branches [88]. The evolutionary distances were computed using the Kimura 2-parameter method [35] and are in the units of the number of base substitutions per site. The analysis involved 25 nucleotide sequences. Codon positions included were 1st + 2nd + 3rd + Noncoding. All positions containing gaps and missing data were eliminated. There were a total of 640 positions in the final dataset. Evolutionary analyses were conducted in MEGA7 [34].

6.8.6. Divergence Matrix

PCR products for the 16S rRNA gene, identified on agarose gels, were selected for subsequent identification by sequencing (Inqaba Biotech, Pretoria, South Africa). The obtained sequenced data were used to conduct homology searches on GenBank using BLAST (http://blast.ncbi.nlm.nih.gov/blast.cgi) [89], and for further bioinformatic analyses to perform divergence matrix using BioEdit v7.0.9 [33]). Sequences were exported to and analyzed with the MEGA 7 package [34].

Author Contributions

M.M., P.J.O., J.R.G. conceived and designed the study; M.M., J.R.G. collected samples and performed the study; M.M., A.S., S.M., J.R.G. analyzed the data; M.M., P.J.O., J.R.G., A.S., S.M. wrote the paper.

Acknowledgments

We acknowledge financial support from National Research Foundation (NRF) and University of Venda Research and Publication Committee (RPC) and Eskom Tertiary Support Program (TESP) for the research study.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Christiansen, G.; Molitor, C.; Philmus, B.; Kurmayer, R. Nontoxic strains of cyanobacteria are the result of major gene deletion events induced by a transposable element. Mol. Biol. Evol. 2008, 25, 1695–1704. [Google Scholar] [CrossRef] [PubMed]
  2. Janse, I.; Kardinaal, W.E.A.; Meima, M.; Fastner, J.; Visser, P.M.; Zwart, G. Toxic and nontoxic Microcystis colonies in natural populations can be differentiated on the basis of rRNA gene internal transcribed spacer diversity. Appl. Environ. Microbiol. 2004, 70, 3979–3987. [Google Scholar] [CrossRef] [PubMed]
  3. Frazao, B.; Martins, R.; Vasconcelos, V. Are Known Cyanotoxins Involved in the Toxicity of Picoplanktonic and Filamentous North Atlantic Marine Cyanobacteria? Mar. Drugs 2010, 8, 1908–1919. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Pearson, L.A.; Dittmann, E.; Mazmouz, R.; Ongley, S.E.; D’Agostino, P.M.; Neilan, B.A. The genetics, biosynthesis and regulation of toxic specialized metabolites of cyanobacteria. Harmful Algae 2016, 54, 98–111. [Google Scholar] [CrossRef] [PubMed]
  5. Sinha, R.; Pearson, L.A.; Davis, T.W.; Muenchhoff, J.; Pratama, R.; Jex, A.; Neilan, B.A. Comparative genomics of Cylindrospermopsis raciborskii strains with differential toxicities. BMC Genom. 2014, 15, 83. [Google Scholar] [CrossRef] [PubMed]
  6. Gumbo, R.J.; Ross, G.; Cloete, E.T. Biological control of Microcystis dominated harmful algal blooms. Afr. J. Biotechnol. 2008, 7, 4765–4773. [Google Scholar]
  7. Paerl, H.W.; Fulton, R.S.; Moisander, P.H.; Dyble, J. Harmful freshwater algal blooms with an emphasis on cyanobacteria. Sci. World 2001, 1, 76–113. [Google Scholar] [CrossRef] [PubMed]
  8. Boyer, G.L. Toxic Cyanobacteria in the Great Lakes: More than just the Western Basin of Lake Erie. GLRC Great Lakes Res. Rev. 2006, 7, 2–7. [Google Scholar]
  9. O’Neil, J.M.; Davis, T.W.; Burford, M.A.; Gobler, C.J. The rise of harmful cyanobacteria blooms: The potential roles of eutrophication and climate change. Harmful Algae 2012, 14, 313–334. [Google Scholar] [CrossRef]
  10. Vitousek, P.M.J.; Aber, R.W.; Howarth, G.E.; Likens, P.A.; Matson, D.W.; Schindler, W.H.; Tilman, G.D. Human alteration of the global nitrogen cycle: Causes and consequences. Issues Ecol. 1997, 1, 1–17. [Google Scholar]
  11. Scheffer, M. The story of some shallow lakes. In Ecology of Shallow Lakes; Springer: Dordrecht, The Netherlands, 2004; pp. 1–19. [Google Scholar]
  12. Reynolds, C.S. Ecology of Phytoplankton; Cambridge University Press: Cambridge, UK, 2006; 550p. [Google Scholar]
  13. Smith, V.H. Low nitrogen to phosphorus ratios favor dominance by blue-green algae in lake Phytoplankton. Science 1983, 221, 669–671. [Google Scholar] [CrossRef] [PubMed]
  14. Hyenstrand, P. Factors Influencing the Success of Pelagic Cyanobacteria; Uppsala University: Uppsala, Sweden, 1999. [Google Scholar]
  15. Berman, T. The role of DON and the effect of N: P ratios on occurrence of cyanobacterial blooms: Implications from the outgrowth of Aphanizomenon in Lake Kinneret. Limnol. Oceanogr. 2001, 46, 443–447. [Google Scholar] [CrossRef]
  16. Downing, J.A.; Watson, S.B.; McCauley, E. Predicting cyanobacteria dominance in lakes. Can. J. Fish. Aquat. Sci. 2001, 58, 1905–1908. [Google Scholar] [CrossRef]
  17. Von Ruckert, G.; Giani, A. Effect of nitrate and ammonium on the growth and protein concentration of Microcystis viridis Lemmermann (Cyanobacteria). Rev. Brasiliera Bot. 2004, 27, 325–331. [Google Scholar]
  18. McCarthy, M.J.; Gardner, W.S.; Lavrentyev, P.J.; Moats, K.M.; Joehem, F.J.; Klarer, D.M. Effects of hydrological flow regime on sediment-water interface and water column nitrogen dynamics in a great lakes coastal wetland (Old Woman Creek, Lake Erie). J. Great Lakes Res. 2007, 33, 219–231. [Google Scholar] [CrossRef]
  19. Andersen, K.; Shanmugam, K. Energetics of biological nitrogen fixation: Determination of the ratio of formation of H2 to NH4+ catalyzed by nitrogenase of Klebsiella pneumoniae in vivo. J. Gen. Microbiol. 1977, 103, 107–122. [Google Scholar] [CrossRef] [PubMed]
  20. Visser, P.M. Growth and Vertical Movement of the Cyanobacterium Microcystis in Stable and Artificially Mixed Water Columns. Ph.D. Thesis, University of Amsterdam, Amsterdam, The Netherland, 1995. [Google Scholar]
  21. Thiel, T.; Pratte, B. Effect on heterocyst differentiation of nitrogen fixation in vegetative cells of the cyanobacterium Anabaena variabilis ATCC 29413. J. Bacteriol. 2001, 183, 280–286. [Google Scholar] [CrossRef] [PubMed]
  22. Chan, F.; Pace, M.L.; Howarth, R.W.; Marino, R.M. Bloom formation in heterocystic nitrogen-fixing cyanobacteria: The dependence on colony size and zooplankton grazing. Limnol. Oceanogr. 2004, 49, 2171–2178. [Google Scholar] [CrossRef] [Green Version]
  23. Mbukwa, E.; Msagati, T.A.; Mamba, B.B.; Boussiba, S.; Wepener, V.; Leu, S.; Kaye, Y. Toxic Microcystis novacekii T20-3 from Phakalane Ponds, Botswana: PCR Amplifications of Microcystin Synthetase (mcy) Genes, Extraction and LC-ESI-MS Identification of Microcystins. J. Environ. Anal. Toxicol. 2015. [Google Scholar] [CrossRef]
  24. Mbukwa, E.A.; Boussiba, S.; Wepener, V.; Leu, S.; Kaye, Y.; Msagati, T.A.; Mamba, B.B. PCR amplification and DNA sequence of mcyA gene: The distribution profile of a toxigenic Microcystis aeruginosa in the Hartbeespoort Dam, South Africa. J. Water Health 2013, 11, 563–572. [Google Scholar] [CrossRef] [PubMed]
  25. Pedro, O.; Rundberget, T.; Lie, E.; Correia, D.; Skaare, J.U.; Berdal, K.G.; Neves, L.; Sandvik, M. Occurrence of microcystins in freshwater bodies in Southern Mozambique. J. Res. Environ. Sci. Toxicol. 2012, 1, 58–65. [Google Scholar]
  26. Vézie, C.; Rapala, J.; Vaitomaa, J.; Seitsonen, J.; Sivonen, K. Effect of nitrogen and phosphorus on growth of toxic and nontoxic Microcystis strains and on intracellular microcystin concentrations. Microb. Ecol. 2002, 43, 443–454. [Google Scholar] [CrossRef] [PubMed]
  27. Beversdorf, L.J.; Miller, T.R.; McMahon, K.D. The role of nitrogen fixation in cyanobacterial bloom toxicity in a temperate, eutrophic lake. PLoS ONE 2013, 8, e56103. [Google Scholar] [CrossRef] [PubMed]
  28. Celeste, C.M.M.; Lorena, R.; Oswaldo, A.J.; Sandro, G.; Daniela, S.; Dario, A.; Leda, G. Mathematical modeling of Microcystis aeruginosa growth and [D-Leu1] microcystin-LR production in culture media at different temperatures. Harmful Algae 2017, 67, 13–25. [Google Scholar] [CrossRef] [PubMed]
  29. Van der Westhuizen, A.J.; Eloff, J.N. Effect of temperature and light on the toxicity and growth of the blue-green alga Microcystis aeruginosa (UV-006). Planta 1985, 163, 55–59. [Google Scholar] [CrossRef] [PubMed]
  30. Geada, P.; Pereira, R.N.; Vasconcelos, V.; Vicente, A.A.; Fernandes, B.D. Assessment of synergistic interactions between environmental factors on Microcystis aeruginosa growth and microcystin production. Algal Res. 2017, 27, 235–243. [Google Scholar] [CrossRef]
  31. Ndlela, L.L.; Oberholster, P.J.; Van Wyk, J.H.; Cheng, P.H. An overview of cyanobacterial bloom occurrences and research in Africa over the last decade. Harmful Algae 2016, 60, 11–26. [Google Scholar] [CrossRef] [PubMed]
  32. Staden, R.; Judge, D.P.; Bonfield, J.K. Analysing sequences using the Staden package and EMBOSS. In Introduction to Bioinformatics. A Theoretical and Practical Approach; Human Press Inc.: Totawa, NJ, USA, 2003. [Google Scholar]
  33. Hall, T.A. BioEdit: A user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp. Ser. 1990, 41, 95–98. [Google Scholar]
  34. Kumar, S.; Stecher, G.; Tamura, K. MEGA7: Molecular Evolutionary Genetics Analysis version 7.0 for bigger datasets. Mol. Biol. Evol. 2016, 33, 1870–1874. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Kimura, M. A simple method for estimating evolutionary rate of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol. 1980, 16, 111–120. [Google Scholar] [CrossRef] [PubMed]
  36. Oberholster, P.J.; Botha, A.M.; Myburgh, J.G. Linking climate change and progressive eutrophication to incidents of clustered animal mortalities in different geographical regions of South Africa. Afr. J. Biotechnol. 2009, 8, 5825–5832. [Google Scholar]
  37. Peperzak, L. Climate change and harmful algal bllom in the North Sea. Acta Oecol. 2003, 24, 139–144. [Google Scholar] [CrossRef]
  38. Rantala, A.; Rajaniemi-Wacklin, P.; Lyra, C.; Lepisto, L.; Rintala, J.; Mankiewiez-Boczek, J.; Sivonen, K. Detection of microcystin-producing cyanobacteria in Finnish Lakes with genus-specific microcystin synthetase Gene E (mcyE) PCR and associations with environmental factors. Appl. Environ. Microbiol. 2006, 72, 6101–6110. [Google Scholar] [CrossRef] [PubMed]
  39. Jahnichen, S.; Petzoldt, T.; Benndorf, J. Evidence for control of microcystin dynamics in BautzenReservoir (Germany) by cyanobacterial population growth rates and dissolved inorganic carbon. Arch. Hydrobiol. 2001, 150, 177–196. [Google Scholar] [CrossRef]
  40. Bartram, J.; Chorus, I.; Carmichael, W.W.; Jones, G.; Skulberg, O.M. Toxic Cyanobacteria in Water. A Guide to Their Public Health Consequences, Monitoring and Management; Chorus, I., Bartram, J., Eds.; World Health Organization: Geneva, Switzerland, 1999; pp. 1–14. [Google Scholar]
  41. Xu, H.; Paerl, H.W.; Qin, B.; Zhu, G.; Gaoa, G. Nitrogen and phosphorus inputs control phytoplankton growth in eutrophic Lake Taihu, China. Limnol. Oceanogr. 2010, 55, 420–432. [Google Scholar] [CrossRef]
  42. Edokpayi, J.N.; Odiyo, J.O.; Popoola, E.O.; Msagati, T.A. Evaluation of Microbiological and Physicochemical Parameters of Alternative Source of Drinking Water: A Case Study of Nzhelele River, South Africa. Open Microbiol. J. 2018, 12, 18–27. [Google Scholar] [CrossRef] [PubMed]
  43. Burne, C. Macro-Nutrient and Hydrological Trends in Some Streams of the Waterberg, Limpopo: Investigating the Effects of Land-Use Change on Catchment Water Quality. Master’s Dissertation, University of Witwatersrand, Johannesburg, South Africa, 2016. [Google Scholar]
  44. Correll, D.L. Phosphorus: A rate limiting nutrient in surface waters. Poultry Sci. 1999, 78, 674–682. [Google Scholar] [CrossRef] [PubMed]
  45. Oberholster, P.J.; Dabrowski, J.; Botha, A.M. Using modified multiple phosphorus sensitivity indices for mitigation and management of phosphorus loads on a catchment level. Fundam. Appl. Limnol. Arch. Hydrobiol. 2013, 182, 1–16. [Google Scholar] [CrossRef] [Green Version]
  46. Mosimanegape, K. Integration of Physicochemical Assessment of Water Quality with Remote Sensing Techniques for the Dikgathong Damin Botswana. Master’s Dissertation, University of Zimbabwe, Harare, Zimbabwe, 2016. [Google Scholar]
  47. Matthews, M.W. Eutrophication and cyanobacterial blooms in South African inland waters: 10 years of MERIS observations. Remote Sens. Environ. 2014, 155, 161–177. [Google Scholar] [CrossRef]
  48. Swanepoel, A.; Du Preez, H.H.; Cloete, N. The occurrence and removal of algae (including cyanobacteria) and their related organic compounds from source water in Vaalkop Dam with conventional and advanced drinking water treatment processes. Water SA 2017, 43, 67–80. [Google Scholar] [CrossRef]
  49. Seanego, K.G.; Moyo, N.A.G. The effect of sewage effluent on the physico-chemical and biological characteristics of the Sand River, Limpopo, South Africa. Phys. Chem. Earth Parts A/B/C 2013, 66, 75–82. [Google Scholar] [CrossRef]
  50. Musa, R.; Greenfield, R. Nutrient loads on an important watercourse. Pre-and Post-Acid spill. In Proceedings of the 7th International Toxicology Symposium, Johannesburg, South Africa, 31 August 2015; p. 89. [Google Scholar]
  51. Basima, L.B. An Assessment of Plankton Diversity as a Water Quality Indicator in Small Man-m Ade Reservoirs in the Mzingwane Catchment, Limpopo Basin, Zimbabwe. Master’s Dissertation, University of Zimbabwe, Harare, Zimbabwe, 2005. [Google Scholar]
  52. Mupfiga, E.T.; Munkwakwata, R.; Mudereri, B.; Nyatondo, U.N. Assessment of sedimentation in Tuli Makwe Dam using remotely sensed data. J. Soil Sci. Environ. Manag. 2016, 7, 230–238. [Google Scholar]
  53. Mavhunga, M. The Presence of Cyanobacteria & Diatoms in Limpopo River Sediment Profile: Implications for Human Health. Unpublished Hons mini Thesis, University of Venda, Johannesburg, South Africa, 2015. [Google Scholar]
  54. Oberholster, P.J.; Jappie, S.; Cheng, P.H.; Botha, A.M.; Matthews, M.W. First report of an Anabaena Bory strain containing microcystin-LR in a freshwater body in Africa. Afr. J. Aquat. Sci. 2015, 40, 21–36. [Google Scholar] [CrossRef]
  55. Kim, Y.J.; Baek, J.S.; Youn, S.J.; Kim, H.N.; Lee, B.C.; Kim, G.; Park, S.; You, K.A.; Lee, J.K. Cyanobacteria Community and Growth Potential Test in Sediment of Lake Paldang. J. Korean Soc. Water Environ. 2016, 32, 261–270. [Google Scholar] [CrossRef]
  56. Dzebu, W. Statement in Relation to Water Supply Challenges in Musina, 14 March 2017. Available online: www.musina.gov.za/index.php/public-notices?download=1028...in...to...musina (accessed on 26 March 2014).
  57. Botha, A.M.; Oberholster, P.J. PCR-Based Markers for Detection and Identification of Toxic Cyanobacteria; WRC Report No. K5/1502/01/07; Water Research Commission: Pretoria, South Africa, 2007; p. 70. [Google Scholar]
  58. Su, Y.; You, X.; Lin, H.; Zhuang, H.; Weng, Y.; Zhang, D. Recruitment of cyanobacteria from the sediments in the eutrophic Shanzi Reservoir. Environ. Technol. 2016, 37, 641–651. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  59. Maldener, I.; Summers, M.L.; Sukenik, A. Cellular differentiation in filamentous cyanobacteria. In The Cell Biology of Cyanobacteria; Flores, E., Herrero, A., Eds.; Caister Academic Press: Norwich, UK, 2014; pp. 263–291. [Google Scholar]
  60. Perez, R.; Forchhammer, K.; Salerno, G.; Maldener, I. Clear differences in metabolic and morphological adaptations of akinetes of two Nostocales living in different habitats. Microbiology 2016, 162, 214–223. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  61. Adam, D.G.; Duggan, P.S. Heterocyst and akinete differentiation in cyanobacteria. New Phytol. 1999, 144, 3–33. [Google Scholar] [CrossRef]
  62. Scherer, P.I.; Raeder, U.; Geist, J.; Zwirglmaier, K. Influence of temperature, mixing, and addition of microcystin-LR on microcystin gene expression in Microcystis aeruginosa. Microbiol. Open 2017, 6. [Google Scholar] [CrossRef] [PubMed]
  63. Mikalsen, B.; Boison, G.; Skulberg, O.M.; Fastner, J.; Davies, W.; Gabrielsen, T.M.; Rudi, K.; Jakobsen, K.S. Natural variation in the microcystin synthetase operon mcyABC and impact on microcystin production in Microcystis strains. J. Bacteriol. 2003, 185, 2774–2785. [Google Scholar] [CrossRef] [PubMed]
  64. Davis, T.W.; Berry, D.L.; Boyer, G.L.; Gobler, C.J. The effects of temperature and nutrients on the growth and dynamics of toxic and non-toxic strains of Microcystis during cyanobacteria blooms. Harmful Algae 2009, 8, 715–725. [Google Scholar] [CrossRef]
  65. Yamamoto, Y. Effect of temperature on recruitment of cyanobacteria from the sediment and bloom formation in a shallow pond. Plankton Benthos Res. 2009, 4, 95–103. [Google Scholar] [CrossRef] [Green Version]
  66. Oberholster, P.J.; Botha, A.-M.; Cloete, T.E. Use of molecular markers as indicators for winter zooplankton grazing on toxic benthic cyanobacteria colonies in an urban Colorado lake. Harmful Algae 2006, 5, 705–716. [Google Scholar] [CrossRef] [Green Version]
  67. Mosase, E.; Ahiablame, L. Rainfall and Temperature in the Limpopo River Basin, Southern Africa: Means, Variations, and Trends from 1979 to 2013. Water 2018, 10, 364. [Google Scholar] [CrossRef]
  68. Hoeger, S.J.; Dietrick, D.R.; Hitzfeld, B.C. Effect of ozonation on the removal of cyanobacteria toxins during drinking water treatment. Environ. Health Perspect. 2002, 110, 1127–1132. [Google Scholar] [CrossRef] [PubMed]
  69. Brittain, S.M.; Wang, J.; Babcock-Jackson, L.; Carmichael, W.W.; Rinehart, K.L.; Culver, D.A. Isolation and characterization of microcystins, cyclic heptapeptide hepatotoxins from Lake Erie strain of Microcystis aeruginosa. J. Great Lakes Res. 2000, 26, 241–249. [Google Scholar] [CrossRef]
  70. Andersson, J.A.; de Garine-Wichatitsky, M.; Cumming, D.H.; Dzingirai, V.; Giller, K.E. People at wildlife frontiers in Southern Africa. In Transfrontier Conservation Area: People Living on the Edge; Routledge: Abingdon-on-Thames, UK, 2013; pp. 1–11. [Google Scholar]
  71. Oberholster, P.J.; Myburgh, J.G.; Govender, D.; Bengis, R.; Botha, A.M. Identification of toxigenic Microcystis strains after incidents of wild animal mortalities in the Kruger National Park, South Africa. Ecotoxicol. Environ. Saf. 2009, 72, 1177–1182. [Google Scholar] [CrossRef] [PubMed]
  72. McCollough, B. Toxic Algae and Other Marine Biota: Detection, Mitigation, Prevention and Effects on the Food Industry. Master’s Dissertation, Kansas State University, Manhattan, KS, USA, 2016. [Google Scholar]
  73. Zhu, T.; Ringler, C. Climate change impacts on water availability and use in the Limpopo River Basin. Water 2012, 4, 63–84. [Google Scholar] [CrossRef]
  74. Department of Water Affairs. Joint Water Quality Baseline Report for Limpopo Basin between Botswana and South Africa; Department of Water Affairs: Pretoria, South Africa, 2011. [Google Scholar]
  75. Islam, M.S.; Ahmed, M.K.; Raknuzzaman, M.; Habibullah-Al-Mamun, M.; Islam, M.K. Heavy metal pollution in surface water and sediment: A preliminary assessment of an urban river in a developing country. Ecol. Indic. 2015, 48, 282–291. [Google Scholar] [CrossRef]
  76. APHA; AWWA; WPCF. Standard Methods for Examination of Water and Wastewater, 20th ed.; American Publishing Health Association: Washington, DC, USA, 1998. [Google Scholar]
  77. Gumbo, J.R.; Ross, G.; Cloete, T.E. The Isolation and identification of Predatory Bacteria from a Microcystis algal Bloom. Afr. J. Biotechnol. 2010, 9, 663–671. [Google Scholar]
  78. Van Vuuren, S.J.; Taylor, J.; Gerber, A. A Guide for the Identification of Microscopic Algae in South Africa Freshwaters; Department of Water Affairs and Forestry, North-West University: Potchefstroom, South Africa, 2006. [Google Scholar]
  79. Moffitt, M.C.; Neilan, B.A. Characterization of the nodularin synthetase gene cluster and proposed theory of the evolution of cyanobacterial hepatotoxins. Appl. Environ. Microbiol. 2004, 70, 6353–6362. [Google Scholar] [CrossRef] [PubMed]
  80. Pearson, L.A.; Neilan, B.A. The molecular genetics of cyanobacterial toxicity as a basis for monitoring water quality and public health risk. Curr. Opin. Biotechnol. 2008, 19, 281–288. [Google Scholar] [CrossRef] [PubMed]
  81. Jungblut, A.D.; Neilan, B.A. Molecular identification and evolution of the cyclic peptide hepatotoxins, microcystin and nodularin, synthetase genes in three orders of cyanobacteria. Arch. Microbiol. 2006, 185, 107–114. [Google Scholar] [CrossRef] [PubMed]
  82. Fergusson, K.M.; Saint, C.P. Multiplex PCR assay for Cylindrospermopsis raciborskii and cylindrospermopsin-producing cyanobacteria. Environ. Toxicol. 2003, 18, 120–125. [Google Scholar] [CrossRef] [PubMed]
  83. Hisbergues, M.; Christiansen, G.; Rouhiainen, L.; Sivonen, K.; Borner, T. PCR-based identification of microcystin-producing genotypes of different cyanobacterial genera. Arch. Microbiol. 2003, 180, 402–410. [Google Scholar] [CrossRef] [PubMed]
  84. Schembri, M.A.; Neilan, B.A.; Saint, C.P. Identification of genes implicated in toxin production in the cyanobacterium Cylindrospermopsis raciborskii. Environ. Toxicol. 2001, 16, 413–421. [Google Scholar] [CrossRef] [PubMed]
  85. Neilan, B.A.; Jacobs, D.; Del Dot, T.; Blackall, L.L.; Hawkins, P.R.; Cox, P.T.; Goodman, A.E. rRNA sequences and evolutionary relationships among toxic and nontoxic cyanobacteria of the genus Microcystis. Int. J. Syst. Bacteriol. 1997, 47, 693–697. [Google Scholar] [CrossRef] [PubMed]
  86. Jungblut, A.D.; Hawes, I.; Mountfort, D.; Hitzfeld, B.; Dietrich, D.R.; Burns, B.P.; Neilan, B.A. Diversity within cyanobacterial mat communities in variable salinity meltwater ponds of McMurdo Ice Shelf, Antarctica. Environ. Microbiol. 2005, 7, 519–529. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  87. Saitou, N.; Nei, M. The neighbor-joining method: A new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 1987, 4, 406–425. [Google Scholar] [PubMed]
  88. Felsenstein, J. Confidence limits on phylogenies: An approach using the bootstrap. Evolution 1985, 39, 783–791. [Google Scholar] [CrossRef] [PubMed]
  89. Altschul, S.F.; Gish, W.; Miller, W.; Myers, E.W.; Lipman, D.J. “Gapped Blast and PSI-BLAST” A generation of protein database search programs. Nucleic Acids Res. 1997, 25, 3389–3402. [Google Scholar] [CrossRef] [PubMed]
Toxins 10 00269 g001 550
Figure 1. Average values of the physical characteristics of the river sediments of the 18 sampling sites. Whiskers reflect standard error. EC: electrical conductivity; TDS: total dissolved solids.
Figure 1. Average values of the physical characteristics of the river sediments of the 18 sampling sites. Whiskers reflect standard error. EC: electrical conductivity; TDS: total dissolved solids.
Toxins 10 00269 g001
Toxins 10 00269 g002 550
Figure 2. Average values of total phosphorus in the river sediments of the 18 sampling sites. Whiskers reflect standard error.
Figure 2. Average values of total phosphorus in the river sediments of the 18 sampling sites. Whiskers reflect standard error.
Toxins 10 00269 g002
Toxins 10 00269 g003 550
Figure 3. Average values of total nitrogen in the river sediments. Whiskers reflect standard error.
Figure 3. Average values of total nitrogen in the river sediments. Whiskers reflect standard error.
Toxins 10 00269 g003
Toxins 10 00269 g004 550
Figure 4. The (A) Microcystis, (B) Anabaena and (C) Oscillatoria species in the river sediments. Red scale bar = 20 µm.
Figure 4. The (A) Microcystis, (B) Anabaena and (C) Oscillatoria species in the river sediments. Red scale bar = 20 µm.
Toxins 10 00269 g004
Toxins 10 00269 g005 550
Figure 5. PCR amplification using 27F and 740R primer pair for 16S rRNA gene. ES (estimated fragments); M (Standard Marker), 2–18 Sample numbers. Lane 2 = Notwane River; 3 = Sand River upstream; 4 = Mogalakwena River; 5 = Mawoni River; 6 = Lephalale River; 7 = Mokolo River; 8 = Crocodile River downstream of Hartbeespoort Dam; 9 = Nzhelele River downstream; 10 = Sand River downstream; 11 = Crocodile River downstream (near the bridge on road D1235); 12 = Nzhelele River upstream; 13 = Mzingwane River; 14 = Shashe River; 15 = Limpopo River (next to Thuli Coalmine); 16 = Limpopo River (abstraction point at 0.0 m); 17 = Limpopo River (abstraction point at 1.0 m); 18 = Limpopo River (abstraction point at 1.68 m).
Figure 5. PCR amplification using 27F and 740R primer pair for 16S rRNA gene. ES (estimated fragments); M (Standard Marker), 2–18 Sample numbers. Lane 2 = Notwane River; 3 = Sand River upstream; 4 = Mogalakwena River; 5 = Mawoni River; 6 = Lephalale River; 7 = Mokolo River; 8 = Crocodile River downstream of Hartbeespoort Dam; 9 = Nzhelele River downstream; 10 = Sand River downstream; 11 = Crocodile River downstream (near the bridge on road D1235); 12 = Nzhelele River upstream; 13 = Mzingwane River; 14 = Shashe River; 15 = Limpopo River (next to Thuli Coalmine); 16 = Limpopo River (abstraction point at 0.0 m); 17 = Limpopo River (abstraction point at 1.0 m); 18 = Limpopo River (abstraction point at 1.68 m).
Toxins 10 00269 g005
Toxins 10 00269 g006 550
Figure 6. PCR products using PKS primers for cylindrospermopsin polyketide synthetase gene. ES (estimated fragment); M (Standard Marker), 2–18 Samples number. Lane 2 = Notwane River; 3 = Sand River upstream; 4 = Mogalakwena River; 5 = Mawoni River; 6 = Lephalale River; 7 = Mokolo River; 8 = Crocodile River downstream of Hartbeespoort Dam; 9 = Nzhelele River downstream; 10 = Sand River downstream; 11 = Crocodile River downstream (near the bridge on road D1235); 12 = Nzhelele River upstream; 13 = Mzingwane River; 14 = Shashe River; 15 = Limpopo River (next to Thuli Coal Mine).
Figure 6. PCR products using PKS primers for cylindrospermopsin polyketide synthetase gene. ES (estimated fragment); M (Standard Marker), 2–18 Samples number. Lane 2 = Notwane River; 3 = Sand River upstream; 4 = Mogalakwena River; 5 = Mawoni River; 6 = Lephalale River; 7 = Mokolo River; 8 = Crocodile River downstream of Hartbeespoort Dam; 9 = Nzhelele River downstream; 10 = Sand River downstream; 11 = Crocodile River downstream (near the bridge on road D1235); 12 = Nzhelele River upstream; 13 = Mzingwane River; 14 = Shashe River; 15 = Limpopo River (next to Thuli Coal Mine).
Toxins 10 00269 g006
Toxins 10 00269 g007 550
Figure 7. A scenario involving boreholes drilled inside the Limpopo river channel and contamination with cyanobacteria (green dots) cysts and akinetes for (A) irrigation farmers & (B) water utility raw water supply for human consumption.
Figure 7. A scenario involving boreholes drilled inside the Limpopo river channel and contamination with cyanobacteria (green dots) cysts and akinetes for (A) irrigation farmers & (B) water utility raw water supply for human consumption.
Toxins 10 00269 g007
Toxins 10 00269 g008 550
Figure 8. The evolutionary history was inferred using the Neighbor-Joining method. U: upstream; UM: Upstream; DT: Downstream; DB: Downstream; DM: downstream; PCC: Pasteur Culture Collection of Cyanobacteria
Figure 8. The evolutionary history was inferred using the Neighbor-Joining method. U: upstream; UM: Upstream; DT: Downstream; DB: Downstream; DM: downstream; PCC: Pasteur Culture Collection of Cyanobacteria
Toxins 10 00269 g008
Toxins 10 00269 g009 550
Figure 9. A scenario involving the movement of cyanobacteria species during water flows in the Limpopo River (red arrow) towards the Musina abstraction borehole (White Square). The possible upstream movement (yellow arrow) from the Sand River (S3) to the Musina borehole (S16) may involve cyanobacteria ‘hitching a ride’ on aquatic animals such as fish and crocodiles.
Figure 9. A scenario involving the movement of cyanobacteria species during water flows in the Limpopo River (red arrow) towards the Musina abstraction borehole (White Square). The possible upstream movement (yellow arrow) from the Sand River (S3) to the Musina borehole (S16) may involve cyanobacteria ‘hitching a ride’ on aquatic animals such as fish and crocodiles.
Toxins 10 00269 g009
Toxins 10 00269 g010 550
Figure 10. Scenario involving sedimentation of cyanobacteria (green dots) cysts and akinetes (A) during flood and flow conditions in Limpopo River and (B) during non-flow (DRY) conditions in the Limpopo River and (C) growth of cyanobacteria under continuous lighting and provision of BG medium at room temperature.
Figure 10. Scenario involving sedimentation of cyanobacteria (green dots) cysts and akinetes (A) during flood and flow conditions in Limpopo River and (B) during non-flow (DRY) conditions in the Limpopo River and (C) growth of cyanobacteria under continuous lighting and provision of BG medium at room temperature.
Toxins 10 00269 g010
Toxins 10 00269 g011 550
Figure 11. The location of sediment sample sites on some of the tributaries of the Limpopo River.
Figure 11. The location of sediment sample sites on some of the tributaries of the Limpopo River.
Toxins 10 00269 g011
Table
Table 1. Summary of toxic and non-toxic cyanobacteria species in the Limpopo river basin.
Table 1. Summary of toxic and non-toxic cyanobacteria species in the Limpopo river basin.
Cyanobacteria Species/Sample SitesS1S2S3S4S5S6S7S8S9S10S11S12S13S14S15S16S17S18
Aphanizomenon sp. + *
Raphidiopsis curvata + *
Microcystis aeruginosa+ +++ ++ * +++++ *++ +
Microcystis panniformis + *
Synechocystis PCC 6803 + * + +
Cylindrospermopsis sp. + * + *
Lyngbya sp.+
Leptolyngbya sp. + +
Leptolyngbya boryana + +
Calothrix sp. + +++ * ++
Oscillatoria sp. ++ ++ *
Phormidium sp. + + + +
Phormidium uncinatum +
Nostoc sp. + * + + *
Anabaena circinalis +
Anabaena oscillarioides +
Chroococcus +
Anabaechopsis circularis +
Spirulina laxissima SAG 256.80 +
Planktothrix rubescens + * + * +
Alkalinema pantanalense +
Gloeocapsa sp. + * +
Arthrospira sp. str PCC8005 + *
Notes: + FlowCam analysis and + Molecular techniques with toxic genes * expression.
Table
Table 2. Results from the BLAST search showing the similarity between the GenBank sequences and the sample sequences from this study. The families of each species are shown in a separate column.
Table 2. Results from the BLAST search showing the similarity between the GenBank sequences and the sample sequences from this study. The families of each species are shown in a separate column.
SamplesSimilarity %Species Similar toFamilyAccession No
S293Uncultured Leptolyngbya sp. CloneLeptolyngbyaceaeKM108695.1
S394Synechocystis PCC 6803OscillatoriophycideaeCP012832.1
S597Anabaena oscillarioidesNostocaceaeAJ630428.1
S799Synechocystis sp. PCC 6803OscillatoriophycideaeCP012832.1
S899Leptolyngbya boryanaLeptolyngbyaceaeAP014642.1
S997Synechocystis PCC 6803OscillatoriophycideaeCP012832.1
S9100Cylindrospermopsis raciborskii CHAB3438OscillatoriophycideaeKJ139743.1
S9100Aphanizomenon sp.NostocaceaeGQ385961.1
S9100Raphidiopsis curvataNostocaceaeKJ139745.1
S1096Spirulina laxissima SAG 256.80SpirulinaceaeDQ393278.1
S1187Uncultured Cyanobacterium clone-AM159315.1
S1283Uncultured Cyanobacterium clone-HQ189039.1
S1390Uncultured Cyanobacterium clone-JX041703.1
S1498Leptolyngbya boryanaLeptolyngbyaceaeAP014642.1
S1683LeptolyngbyaLeptolyngbyaceaeKJ654311.1
S1896Alkalinema pantanalensePseudanabaenaceaeKF246497.2
Table
Table 3. Results from the BLAST search showing the similarity between the GenBank sequences and sample sequenced using PKS and HEP primers for toxin gene identification.
Table 3. Results from the BLAST search showing the similarity between the GenBank sequences and sample sequenced using PKS and HEP primers for toxin gene identification.
PrimersSample NoSimilarity %Species Similar toAccession No
PKSS3100Aphanizomenon sp. 10E6GQ385961.1
S3100Raphidiopsis curvataKJ139745.1
S3100Cylindrospermopsis raciborskiiAF160254.1
S3100Arthrospira sp. str. PCC 8005FO818640.1
S3100Nostoc sp. NIES-4103AP018288.1
S993Calothrix sp. 336/3CP011382.1
S989Oscillatoria nigro-viridis PCC 7112CP003614.1
S9100Gloeocapsa sp. PCC 7428,CP003646.1
S9100Cylindrospermum sp. NIES-4074AP018269.1
HEPS8100Uncultured Microcystis sp. clone msp microcystin synthetase E (mcyE) gene, partial cdsKF687998
S8100Microcystis panniformis FACHB-1757CP011339.1
S8100Microcystis aeruginosa PCC 7806AF183408.1
S8100Nostoc sp. 152KC699835.1
S8100Planktothrix rubescens NIVA-CYA 98AM990462.1
S13100Nostoc sp. 152KC699835.1
S13100Planktothrix rubescens NIVA-CYA 98AM990462.1
S13100Uncultured Microcystis sp. from UgandaFJ429839.2
S13100Microcystis aeruginosa PCC 7806SLCP020771.1
S13100Uncultured Microcystis sp. clone mw microcystin synthetase E (mcyE) gene, partial cdsKF687997.1
Table
Table 4. Divergence matrix for reflection of similarity.
Table 4. Divergence matrix for reflection of similarity.
S2S3S5S7S8S9S10S11S12S13S14S16S18
Notwane River (S2)‒
Sand River (S3)0.216‒
Nzhelele River (S5)0.1910.187‒
Mokolo River (S7)0.1670.0640.130‒
Crocodile River (S8)0.1660.1600.1490.119‒
Nzhelele River (S9)0.1840.0950.1520.0280.140‒
Sand River (S10)0.1550.2160.1530.1560.1690.169‒
Crocodile River (S11)0.2570.2950.2800.2440.2780.2540.236‒
Nzhelele River (S12)0.3910.3940.3650.3510.3500.3610.3640.492‒
Mzingwane River (S13)0.1900.1800.1840.1300.1340.1390.1680.2670.377‒
Shashe River (S14)0.1730.1630.1560.1190.0060.1400.1730.2780.3550.134‒
Musina borehole (S16)0.3760.3590.3120.3140.3420.3210.3430.4140.5550.3710.347‒
Musina borehole (S18)0.1830.1840.1790.1360.1280.1500.1860.2850.3660.1730.1310.348‒
Table
Table 5. The location of sample sites and sample codes.
Table 5. The location of sample sites and sample codes.
River NamesSamples Numbers
Limpopo River (Groblers’ bridge)S1
Notwane River (Odi Bridge-Matabeleng)S2
Sand River upstreamS3
Mogalakwena River next to TolweS4
Mawoni River downstream Makhado oxidation pondsS5
Lephalale riverS6
Mokolo RiverS7
Crocodile River downstream Hartbeespoort damS8
Nzhelele River downstream near TshipiseS9
Sand River downstream (at bridge on N1 road towards Musina)S10
Crocodile River downstream (near bridge on road D1235) near ThabazimbiS11
Nzhelele River upstream near Mphephu resort (downstream of Siloam oxidation ponds)S12
Mzingwane River (Zimbabwe)S13
Shashe River (near Irrigation scheme, Zimbabwe)S14
Limpopo River next to Thuli coal mineS15
Limpopo River abstraction point @ 0.0 mS16
Limpopo River abstraction point @ 1.0 mS17
Limpopo River abstraction point @ 1.68 mS18
Table
Table 6. The PCR primers used for amplification of 16S rRNA gene for cyanobacteria identification and for the amplification of genes related to cyanotoxins production. A—Individual annealing temperature, B—Reference annealing temperature, bp = base pairs.
Table 6. The PCR primers used for amplification of 16S rRNA gene for cyanobacteria identification and for the amplification of genes related to cyanotoxins production. A—Individual annealing temperature, B—Reference annealing temperature, bp = base pairs.
PrimersTarget GenesSequence (5′-3′)ABSize (bp)Amplified GeneRef.
27F
809R		-AGAGTTTGATCCTGGCTCAG
GCTTCGGCACGGCTCGGGTCGATA		52
64		6078016S rRNA[85,86]
mcyA-Cd F
mcyA-Cd R		mcyAAAAATTAAAAGCCGTATCAAA
AAAAGTGTTTTATTAGCGGCTCAT		51
43		59297Microcystin synthetase[83]
HEPF
HEPR		mcyE/ndaFTTTGGGGTTAACTTTTTTGGGCATAGTC
AATTCTTGAGGCTGTAAATCGGGTTT		57
55		52472Microcystin/nodularin synthetase[81]
PKS M4
PKS M5		cyrGAAGCTCTGGAATCCGGTAA
AATCCTTACGGGATCCGGTGC		52
56		55650Cylindrospermopsin polypeptide synthase[84]
M13
M14		psGGCAAATTGTGATAGCCACGAGC
GATGGAACATCGCTCACTGGTG		57
57		55597Cylindrospermopsin peptide synthetase[84]

Share and Cite

MDPI and ACS Style

Magonono, M.; Oberholster, P.J.; Shonhai, A.; Makumire, S.; Gumbo, J.R. The Presence of Toxic and Non-Toxic Cyanobacteria in the Sediments of the Limpopo River Basin: Implications for Human Health. Toxins 2018, 10, 269. https://doi.org/10.3390/toxins10070269

AMA Style

Magonono M, Oberholster PJ, Shonhai A, Makumire S, Gumbo JR. The Presence of Toxic and Non-Toxic Cyanobacteria in the Sediments of the Limpopo River Basin: Implications for Human Health. Toxins. 2018; 10(7):269. https://doi.org/10.3390/toxins10070269

Chicago/Turabian Style

Magonono, Murendeni, Paul Johan Oberholster, Addmore Shonhai, Stanley Makumire, and Jabulani Ray Gumbo. 2018. "The Presence of Toxic and Non-Toxic Cyanobacteria in the Sediments of the Limpopo River Basin: Implications for Human Health" Toxins 10, no. 7: 269. https://doi.org/10.3390/toxins10070269

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop