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15 pages, 2412 KiB  
Article
Tolerance to a Diet of Toxic Microcystis aeruginosa in Caenorhabditis elegans
by Jordan Balson, Jeffrey R. Boudreau, Ian D. Chin-Sang, Yuxiang Wang and Daniel D. Lefebvre
Toxins 2025, 17(3), 109; https://doi.org/10.3390/toxins17030109 (registering DOI) - 27 Feb 2025
Abstract
Reported incidences of cyanobacterial harmful algal blooms (CHABs) are increasing across the world due to climate change and nutrient loading, dominating freshwater ecosystems and producing dangerous cyanotoxins that cause ecological damage. Microcystis aeruginosa is one of the most common species of cyanobacteria; it [...] Read more.
Reported incidences of cyanobacterial harmful algal blooms (CHABs) are increasing across the world due to climate change and nutrient loading, dominating freshwater ecosystems and producing dangerous cyanotoxins that cause ecological damage. Microcystis aeruginosa is one of the most common species of cyanobacteria; it produces hepatotoxic and neurotoxic microcystin-LR. The ecological and human impact of algal blooms is immense, and traditional CHAB remediation methods are not always adequate in eutrophic regions such as Lake Erie in North America. As a result, a proactive, targeted approach is needed to bioremediate cyanobacteria in their pre-colonial stages. Nematodes, such as the model organism Caenorhabditis elegans, are potential candidates for bioremediating cyanobacteria such as M. aeruginosa. C. elegans have metabolic pathways that could detoxify microcystin-LR and enable tolerance to cyanobacteria in nature. We analyzed C. elegans health and fat accumulation on a diet of toxic M. aeruginosa and found that C. elegans can ingest, digest, metabolize, and survive off of this diet. The mean lifespans of the worm populations were only slightly different at 20.68 ± 0.35 (mean ± S.E.M) and 17.89 ± 0.40 when fed E. coli and toxic M. aeruginosa, respectively. In addition, a diet of toxic M. aeruginosa compared to E. coli did not have any significant impact on C. elegans pharyngeal pumping (304.2 ± 9.3 versus 330.0 ± 10.4 pumps/min), dauer response (86.3 ± 1.0 versus 83.65 ± 1.0% in dauer), mobility (209.25 ± 7.0 versus 210.15 ± 4.4 thrashes/min), or SKN-1 expression based on SKN1::GFP fluorescence measurements. Overall, a diet of toxic M. aeruginosa was able to sustain C. elegans development, and C. elegans was tolerant of it. These results suggest that C. elegans and similar nematodes could be viable candidates for cyanobacterial bioremediation. Full article
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Figure 1
<p>Microcystin-LR concentration in the media on plates seeded with partially lysed toxic <span class="html-italic">M. aeruginosa</span> in the presence and absence of <span class="html-italic">C. elegans</span>; * indicates significance (<span class="html-italic">p</span> &lt; 0.05, X̄ <span class="html-italic">±</span> SE, n = 3).</p>
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<p>Quantification of storage fats in 4-day-old <span class="html-italic">C. elegans</span>. (<b>A</b>) Micrographs of nematodes after neutral lipid staining with Oil-Red O on different diets (Bar = 100 µm). (<b>B</b>) Relative amounts of staining for neutral lipids (X̄ <span class="html-italic">±</span> SE, n = 27).</p>
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<p>Longevity of N2 <span class="html-italic">C. elegans</span> on different diets. * indicates significant difference between the treatments at that time point (<span class="html-italic">p</span> &lt; 0.95; X̄ <span class="html-italic">±</span> SE, n = 9).</p>
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<p>Determination of <span class="html-italic">SKN-1</span> expression as visualized through fluorescence intensity in <span class="html-italic">C. elegans</span> LD1 containing a SKN-1::GFP marker after 3 days in the different treatments. (<b>A</b>) Micrographs of nematodes on different diets (Bar = 100 µm); (<b>B</b>) relative amounts of fluorescence; * indicates significant difference from both other treatments (<span class="html-italic">p</span> &lt; 0.95, X̄ <span class="html-italic">±</span> SE, n = 18).</p>
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2 pages, 318 KiB  
Correction
Correction: Zeng et al. Algicidal Efficiency and Genotoxic Effects of Phanerochaete chrysosporium against Microcystis aeruginosa. Int. J. Environ. Res. Public Health 2020, 17, 4029
by Guoming Zeng, Maolan Zhang, Pei Gao, Jiale Wang and Da Sun
Int. J. Environ. Res. Public Health 2025, 22(3), 347; https://doi.org/10.3390/ijerph22030347 (registering DOI) - 27 Feb 2025
Abstract
In the original publication [...] Full article
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Figure 7

Figure 7
<p>DNA damage in blood cells of <span class="html-italic">F. multistriata</span> tadpoles treated with <span class="html-italic">M. aeruginosa</span>: <span class="html-italic">M. aeruginosa</span> (<b>a</b>) treated with <span class="html-italic">P. chrysosporium</span> (<b>b</b>).</p>
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9 pages, 2180 KiB  
Communication
Virus Infection of a Freshwater Cyanobacterium Contributes Significantly to the Release of Toxins Through Cell Lysis
by Victoria Lee, Isaac Meza-Padilla and Jozef I. Nissimov
Microorganisms 2025, 13(3), 486; https://doi.org/10.3390/microorganisms13030486 - 22 Feb 2025
Viewed by 303
Abstract
Toxic algal-bloom-forming cyanobacteria are a persistent problem globally for many aquatic environments. Their occurrence is attributed to eutrophication and rising temperatures due to climate change. The result of these blooms is often the loss of biodiversity, economic impacts on tourism and fisheries, and [...] Read more.
Toxic algal-bloom-forming cyanobacteria are a persistent problem globally for many aquatic environments. Their occurrence is attributed to eutrophication and rising temperatures due to climate change. The result of these blooms is often the loss of biodiversity, economic impacts on tourism and fisheries, and risks to human and animal health. Of emerging interest is the poorly understood interplay between viruses and toxic species that form blooms. This is because recent studies have suggested that viruses may exacerbate the harmful effects of these blooms by contributing to the release of toxins into a dissolved phase upon cell lysis. However, to date, there is no experimental evidence that explicitly implicates viruses in microcystin release. Here, we show experimentally that a virus infection of the toxin-producing, harmful, algal-bloom-forming cyanobacterium Microcystis aeruginosa results in a 4-fold increase in the toxin microcystin-LR two days post-infection (dpi). We also show that the concentrations of microcystin remain high after culture discoloration and host cell lysis. Collectively, our results directly implicate viruses as major contributors to microcystin release from cyanobacteria and emphasize the importance of taking viruses into account in predictive models and in the assessment of water quality and safety. Full article
(This article belongs to the Special Issue Advances in Research on Cyanobacteria)
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<p>Extracellular cyanotoxin release by cyanobacteria such as Microcystis aeruginosa. (<b>A</b>) The measurable extracellular fraction of cyanotoxins in the absence of a virus infection includes toxins that are typically released upon senescence and/or cell death, with some cyanobacterial species being able to release toxins without cell rupture or death. This is what we measured in our control, uninfected M. aeruginosa NIES-298 treatments. (<b>B</b>) The measurable extracellular fraction of cyanotoxins in the presence of viruses includes intracellular toxins that are typically contained within the cyanobacterial cells and are released upon cell lysis. This is what we measured in our virus-infected M. aeruginosa NIES-298 treatments. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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<p>Cyanophage-infected and uninfected <span class="html-italic">M. aeruginosa</span> NIES-298 cyanobacterial cultures and the subsequent analysis of extracellular microcystin-LR dynamics during infection. (<b>a</b>) 1—Cyanobacterial cells were incubated until the late exponential growth phase (i.e., 2.95 × 10<sup>7</sup> cells mL<sup>−1</sup>); 2—the culture was then split into six replicates at day 0 (dashed line in (<b>b</b>)), three of which were infected with a cyanophage Ma-LMM01 stock that was at a virus particle density of 1.35 × 10<sup>7</sup> mL<sup>−1</sup> and three of which were inoculated with an equal volume of a 0.02 µm filtrate of the Ma-LMM01 stock; and 4—ELISA essays and total NIES-298 cell abundance measurements were performed using spectrophotometry and haemocytometry, respectively. (<b>b</b>) <span class="html-italic">M. aeruginosa</span> NIES-298 growth dynamics (<span class="html-italic">n</span> = 3, ±SD) of Ma-LMM01-infected (grey line) and uninfected (green line) treatments up to seven days post-infection on day 0 (indicated as a dashed line). (<b>c</b>) Average (± SD, <span class="html-italic">n</span> = 3) extracellular microcystin-LR concentrations in parts per billion (ppb) in cyanophage Ma-LMM01-infected (dark grey bars) and uninfected (green bars) treatments. ** and * denote significant differences (<span class="html-italic">p</span> &lt; 0.01 and <span class="html-italic">p</span> &lt; 0.05, respectively; ANOVA) between infected and uninfected treatments at individual time points. (<b>d</b>) Average daily rate of extracellular microcystin-LR decrease in infected treatments, calculated between the highest measured concentration on day 2 and the last day of the experiment on day seven. (<b>e</b>) Culture pigmentation (photographed) of a representative triplicate treatment, which was either infected (V) or uninfected (C) by viruses, 0–7 dpi. Panel (<b>a</b>) was created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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17 pages, 2871 KiB  
Article
Characterization of Five CRISPR Systems in Microcystis aeruginosa FACHB-524 with Focus on the In Vitro Antiviral Activity of One CRISPR System
by Mengjing Zeng, Qi-Ya Zhang and Fei Ke
Int. J. Mol. Sci. 2025, 26(4), 1554; https://doi.org/10.3390/ijms26041554 - 12 Feb 2025
Viewed by 503
Abstract
Microcystis aeruginosa is an important species causing cyanobacterial blooms, which can be effectively infected and lysed by cyanophages. Several strategies have been developed by M. aeruginosa to resist cyanophage infections, including the CRISPR-Cas systems. However, detailed information on the CRISPR-Cas systems in M. [...] Read more.
Microcystis aeruginosa is an important species causing cyanobacterial blooms, which can be effectively infected and lysed by cyanophages. Several strategies have been developed by M. aeruginosa to resist cyanophage infections, including the CRISPR-Cas systems. However, detailed information on the CRISPR-Cas systems in M. aeruginosa is rare. In the present study, the CRISPR-Cas systems of M. aeruginosa FACHB-524 were analyzed by genome re-sequencing, which showed that there are two type I (Cluster 1, I-B1; Cluster 2, I-D) and three type III-B (Cluster 3/4/5) CRISPR-Cas systems in the cyanobacteria. Further comparison revealed that spacer sequences of two type III-B systems targeted several genes of the cyanophage MaMV (M. aeruginosa myovirus) strains. One of the type III systems (Cluster 4) was then cloned and expressed in Escherichia coli BL21 (DE3). Protein purification and mass spectrometry identification revealed that a Cmr-crRNA effector complex formed in the E. coli. Subsequently, T4 phage (T4) was used to infect the E. coli, expressing the Cmr-crRNA complex with or without accessory proteins. The results showed that the Cmr-crRNA effector complex exhibited anti-phage activity and the accessory protein Csx1 enhanced the immune activity of the complex. Collectively, our results comprehensively demonstrate the CRISPR systems encoded by a strain of M. aeruginosa, and for the first time, one of the CRISPR systems was constructed into E. coli, providing a foundation for further in-depth analysis of cyanobacterial CRISPR systems. Full article
(This article belongs to the Section Molecular Microbiology)
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<p>Genome circle diagram of <span class="html-italic">M. aeruginosa</span> FACHB-524 and gene function classifications. (<b>A</b>) Genome circle diagram. The circular diagrams from outside to inside indicate: 1. genome coordinates; 2. genes on the positive strand, with different colors representing different COG functional classifications; 3. genes on the negative strand; 4. rRNAs and tRNAs, with rRNAs being blue and tRNAs being red; 5. GC content curve, with 2000 bp as a sliding window; 6. GC skew curve, with a sliding window of 2000 bp; green indicates that the G content is greater than the C content, and violet indicates that the G content is less than the C content. (<b>B</b>) Gene function classification by COG analysis.</p>
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<p>The CRISPR-Cas systems in the genome of <span class="html-italic">M. aeruginosa</span> FACHB-524. (<b>A</b>) Schematic diagram of the CRISPR-Cas systems. The Cas genes or accessory genes were indicated by arrows with homologous genes highlighted in the same color and that constitutes Cmr-α effector complex was labeled by light orange color box. The numbers indicate the CRISPR-Cas loci in the genome. (<b>B</b>) Phylogenetic analysis of Cas10 homologues in <span class="html-italic">M. aeruginosa</span> FACHB-524. The phylogenetic tree was constructed by neighbor-joining method with 1000 bootstraps.</p>
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<p>Targeting of <span class="html-italic">M. aeruginosa</span> FACHB-524 CRISPR system with genome sequences of MaMVs. (<b>A</b>) Sequences in Cluster 4 that target the MaMV genes. (<b>B</b>) Sequences in Cluster 5 that target the MaMV genes. The red highlighted bases indicate the bases in the spacer sequences differ from the genomes of the six MaMVs.</p>
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<p>Expression and purification of the MaCmr complex in <span class="html-italic">E. coli</span>. (<b>A</b>) The strategies for construction recombinant plasmids. Four spacers were constructed into the P524-S4 plasmid. Arrows indicate the T7 promoter, and 1, 2, and 3 indicate different spacer sequences. (<b>B</b>) SDS-PAGE analysis of the purified protein complex. The composition of the Cmr-α effector complex was Cas10, Cmr1-6, Cmr3, Cmr4, and Cmr5 in descending order. C, lysates before IPTG induction; I, lysates after IPTG induction; E, the purified Cmr-α protein complex.</p>
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<p>The titer of T4 phage in E. coli carrying different prokaryotic expression vectors. (<b>A</b>) Titers of T4 phage in E. coli expressing the Cmr-α-crRNA effector complex. (<b>B</b>) Titers of T4 phage in E. coli expression of both the Cmr-α-crRNA effector complex and the accessory protein Csx1 or CARF. “+” and “−” indicates E. coli was induced with or without IPTG.</p>
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11 pages, 2301 KiB  
Article
The Role of Agricultural Wastes—Peanut Shells in Enhancing Algae–Bacteria Consortia Performance for Efficient Wastewater Treatment
by Yanlin Jiao, Jian Zhao, Nina Sun, Deyang Shi, Dejun Xia, Qingfu Du, Peng Li, Shuqi Mu, Chunxiao Wang, Tangyu Yuan and Meng Cao
Water 2025, 17(4), 485; https://doi.org/10.3390/w17040485 - 8 Feb 2025
Viewed by 470
Abstract
Carbon source limitation is a critical factor restricting the treatment efficiency of domestic wastewater by algae–bacteria consortia. Using agricultural waste as an external carbon source to enhance purification performance holds significant potential. This study investigated the effects of peanut shell powder (PSP) on [...] Read more.
Carbon source limitation is a critical factor restricting the treatment efficiency of domestic wastewater by algae–bacteria consortia. Using agricultural waste as an external carbon source to enhance purification performance holds significant potential. This study investigated the effects of peanut shell powder (PSP) on wastewater treatment in algae–bacteria consortia. The results demonstrated that the optimal PSP dosage (2 mg/L) improved the removal efficiencies of TN, TP, and COD by 29.6%, 40.9%, and 18.7%, respectively. In contrast, excessive PSP reduced the removal performance. The primary mechanism by which PSP influenced the algae–bacteria consortia involved changes in microbial biomass and community structure. An optimal PSP dosage promoted the proliferation of the dominant algal species, Chlorella, enhanced photosynthetic activity, and increased the relative abundance of Rhodanobacter, known for its effective degradation of benzene compounds. Conversely, excessive PSP caused microbial cell rupture, inhibited Chlorella growth and photosynthesis, and elevated the abundance of Microcystis and Brevundimonas, which pose significant health risks. In conclusion, PSP can improve effluent quality and safety in algae–bacteria consortia, which represents a green, economical pathway for optimizing wastewater treatment processes. Full article
(This article belongs to the Special Issue Applications of Microalgae and Macroalgae in Water Treatment)
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<p>Effects of different PSP doses on TN (<b>A</b>), TP (<b>B</b>), and COD (<b>C</b>) removal efficiency in wastewater.</p>
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<p>Impacts of various PSP doses on EEM fluorescence spectra of algae–bacteria consortia.</p>
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<p>Effects of PSP doses on cell membrane permeability (<b>A</b>), chlorophyll-a concentration (<b>B</b>), and maximum fluorescence quantum yield (F<sub>v</sub>/F<sub>m</sub>) (<b>C</b>).</p>
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<p>The impacts of PSP doses on the microbial community structure of algae–bacteria consortia (algae are highlighted in the green font; blue to red in the legend indicates the relative abundance of the microorganisms from low to high).</p>
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<p>Changes in sludge volume during sedimentation (<b>A</b>) and dry weight of supernatant after 48 h (<b>B</b>).</p>
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14 pages, 3541 KiB  
Article
Investigation on Lanthanum Modified Kaolinite for Control of Cyanobacterial Growth and Microcystin Production
by Yige Miao, Songhai Zheng, Xiancai Lu, Kejia Zhang and Jiajia Fan
Water 2025, 17(3), 428; https://doi.org/10.3390/w17030428 - 4 Feb 2025
Viewed by 579
Abstract
Eutrophication and its resultant cyanobacterial blooms are a severe environmental issue in global water bodies, and phosphate is regarded as one of the primary triggers. In this study, the in situ-synthesized heated kaolinite lanthanum hydroxide composite (HKL-LH) was used to treat cyanobacterial blooms [...] Read more.
Eutrophication and its resultant cyanobacterial blooms are a severe environmental issue in global water bodies, and phosphate is regarded as one of the primary triggers. In this study, the in situ-synthesized heated kaolinite lanthanum hydroxide composite (HKL-LH) was used to treat cyanobacterial blooms through phosphate removal. A typical cyanobacteria species—Microcystis aeruginosa—was selected as the target organism. HKL-LH efficiently removed phosphate in the solution with the inoculation of M. aeruginosa over the course of one day. A good performance of HKL-LH on control cyanobacterial blooms with initial cell densities ranging from 104 cells mL−1 to 105 cells mL−1 was observed. Although the genetic expression relating to photosynthesis and cell division was upregulated under the stress of phosphorus deficiency, M. aeruginosa growth was significantly inhibited, i.e., the inhibition rate of up to 98% was achieved by 0.1g L−1 of HKL-LH. In addition to cell growth, the photosynthetic activity and viability of M. aeruginosa cells were decreased by HKL-LH. Furthermore, the production of associated toxins (microcystins) and algal organic matters were effectively inhibited, which can reduce the ecological risk and challenges that follow water treatment. In this study, it is shown that HKL-LH has excellent application potential in the mitigation of cyanobacterial blooms in eutrophic water. Full article
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<p>The changes in phosphate concentrations and the growth of <span class="html-italic">M. aeruginosa</span> by HKL-LH treatments, with different initial phosphate concentrations in the background water: (<b>a</b>,<b>b</b>) 0.6 mg L<sup>−1</sup>, (<b>c</b>,<b>d</b>) 1.2 mg L<sup>−1</sup>, and (<b>e</b>,<b>f</b>) 3.0 mg L<sup>−1</sup>. The initial cell density was approximately 1.0 × 10<sup>5</sup> cells mL<sup>−1</sup>.</p>
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<p>The inhibition rate of <span class="html-italic">M. aeruginosa</span> samples by 0.023–0.2 g L<sup>−1</sup> HKL-LH treatments, with initial cell densities: (<b>a</b>) 2.8 × 10<sup>4</sup> cells mL<sup>−1</sup>, (<b>b</b>) 9.7 × 10<sup>4</sup> cells mL<sup>−1</sup>, and (<b>c</b>) 6.3 × 10<sup>5</sup> cells mL<sup>−1</sup>. The initial phosphate concentration was 0.6 mg L<sup>−1</sup>.</p>
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<p>The effects of HKL and HKL-LH on (<b>a</b>) photosynthetic efficiency and (<b>b</b>) cell integrity of <span class="html-italic">M. aeruginosa</span> samples. The initial cell density was approximately 1.0 × 10<sup>5</sup> cells mL<sup>−1</sup>, and the initial phosphate concentration was 0.6 mg L<sup>−1</sup>.</p>
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<p>The concentrations of MC-LR in the <span class="html-italic">M. aeruginosa</span> samples after exposure to various concentrations of HKL-LH. The initial cell density was approximately 1.0 × 10<sup>5</sup> cells mL<sup>−1</sup>, and the initial phosphate concentration was 0.6 mg L<sup>−1</sup>.</p>
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<p>The functional gene expression in <span class="html-italic">M. aeruginosa</span> samples treated by HKL and HKL-LH. The relative expression of the control is close to 1. The orange color represents the upregulation of the relative expression. The initial cell density was approximately 1.0 × 10<sup>5</sup> cells mL<sup>−1</sup>, and the initial phosphate concentration was 0.6 mg L<sup>−1</sup>.</p>
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<p>The amounts of DOC in the <span class="html-italic">M. aeruginosa</span> samples after exposure to various concentrations of HKL-LH. The initial cell density was approximately 1.0 × 10<sup>5</sup> cells mL<sup>−1</sup>, and the initial phosphate concentration was 0.6 mg L<sup>−1</sup>.</p>
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14 pages, 2999 KiB  
Article
Antialgal Effects of Nonanoic and Palmitic Acids on Microcystis aeruginosa and the Underlying Mechanisms
by Ning Hu, Yaowen Tan, Xian Xiao, Yuexiang Gao, Kaikai Zheng, Wenhan Qian, Yimin Zhang and Yuan Zhao
Sustainability 2025, 17(3), 1207; https://doi.org/10.3390/su17031207 - 2 Feb 2025
Viewed by 768
Abstract
Algal blooms caused by Microcystis aeruginosa are a common occurrence and pose significant threats to freshwater ecosystems. This study investigates the antialgal effects and underlying mechanisms of two plant-derived fatty acids, nonanoic acid and palmitic acid, on Microcystis aeruginosa. The results show [...] Read more.
Algal blooms caused by Microcystis aeruginosa are a common occurrence and pose significant threats to freshwater ecosystems. This study investigates the antialgal effects and underlying mechanisms of two plant-derived fatty acids, nonanoic acid and palmitic acid, on Microcystis aeruginosa. The results show that the inhibitory effects of both fatty acids on M. aeruginosa increase with higher concentrations. Algal recovery occurs when nonanoic acid concentrations are below 0.5 mg/L and palmitic acid concentrations are below 50 mg/L. Acute toxicity tests indicate that the safe concentrations of nonanoic acid and palmitic acid are below 1.87 mg/L and 263.3 mg/L, respectively. The inhibitory effect of nonanoic acid is more pronounced under conditions of pH 5.5, 15 °C temperature, 0.75 mg/L nitrogen, and 2 mg/L phosphorus, with inhibition efficiency remaining unaffected by increased light intensity. Both fatty acids exert their strongest inhibitory effects in the early stages of addition (0–8 days), causing cell death and the release of extracellular organic matter primarily consisting of aromatic compounds and proteins. Oxidative stress analysis reveals that high concentrations of fatty acids can cause irreversible damage to the algae’s antioxidant defense system. These findings provide valuable insights for the prevention and control of cyanobacterial blooms, which can help promote the sustainable development of freshwater ecosystems. Full article
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<p>Inhibition rates of <span class="html-italic">M. aeruginosa</span> induced by varying concentrations of nonanoic acid (<b>a</b>) and palmitic acid (<b>b</b>).</p>
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<p>The influence of environmental factors on the antialgal activity of nonanoic acid. (<b>a</b>) pH; (<b>b</b>) Temperature; (<b>c</b>) Light intensity; (<b>d</b>) Nitrogen concentrations; and (<b>e</b>) Phosphorus concentrations. *, <span class="html-italic">p</span> &lt; 0.05; **, 0.01 &lt; <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>The effect of nonanoic and palmitic acids on the release of extracellular organic matter from <span class="html-italic">M. aeruginosa</span>. (<b>a</b>,<b>b</b>) Dissolved organic carbon concentration and (<b>c</b>,<b>d</b>) UV-visible spectra of the extracellular filtrate of <span class="html-italic">M. aeruginosa</span> treated with nonanoic and palmitic acids.</p>
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<p>Three-dimensional fluorescence spectrum scan of the algal extracellular filtrate. (<b>a</b>–<b>e</b>) The 3D fluorescence spectra of the <span class="html-italic">M. aeruginosa</span> filtrate treated with nonanoic acid on days 0, 4, 8, 12, and 16, respectively; (<b>f</b>–<b>j</b>) The spectra for the filtrate treated with palmitic acid on the same days.</p>
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<p>The influence of nonanoic acid and palmitic acid on the photosynthesis of <span class="html-italic">M. aeruginosa</span> cells. (<b>a</b>,<b>b</b>) Chlorophyll <span class="html-italic">a</span> (Chl-<span class="html-italic">a</span>); (<b>c</b>,<b>d</b>) <span class="html-italic">F</span><sub>v</sub>/<span class="html-italic">F</span><sub>m</sub>; (<b>e</b>,<b>f</b>) Electron transport rate (ETR).</p>
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<p>The influence of nonanoic acid and palmitic acid on the photosynthesis of <span class="html-italic">M. aeruginosa</span> cells. (<b>a</b>,<b>b</b>) Chlorophyll <span class="html-italic">a</span> (Chl-<span class="html-italic">a</span>); (<b>c</b>,<b>d</b>) <span class="html-italic">F</span><sub>v</sub>/<span class="html-italic">F</span><sub>m</sub>; (<b>e</b>,<b>f</b>) Electron transport rate (ETR). *, <span class="html-italic">p</span> &lt; 0.05; **, 0.01 &lt; <span class="html-italic">p</span> &lt; 0.05.</p>
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16 pages, 3527 KiB  
Article
Combining Analytical Strategies to Provide Qualitative and Quantitative Analysis and Risk Assessment on Pharmaceuticals and Metabolites in Hospital Wastewaters
by Lisandro von Mühlen, Marisa Demarco, Carla Sirtori, Renato Zanella and Osmar Damian Prestes
Processes 2025, 13(2), 307; https://doi.org/10.3390/pr13020307 - 23 Jan 2025
Viewed by 638
Abstract
The improper disposal of hospital wastewater (HWW) is a primary source of pharmaceutical pollution in aquatic systems. The complexity of the HWW matrix presents significant challenges for analytical chemists, necessitating meticulous sample preparation as the initial step for the analysis, followed by instrumental [...] Read more.
The improper disposal of hospital wastewater (HWW) is a primary source of pharmaceutical pollution in aquatic systems. The complexity of the HWW matrix presents significant challenges for analytical chemists, necessitating meticulous sample preparation as the initial step for the analysis, followed by instrumental analysis. In the present study, a combination of dispersive solid phase extraction and solid phase extraction was evaluated for the preparation of HWW samples from two hospitals in Porto Alegre, Brazil, both for screening and quantitative analysis. The experiments performed by UHPLC-QTOF MS allowed the identification of 27 compounds and 23 suspected compounds. Furthermore, the UHPLC-QqQ-MS analysis enabled the quantification of 21 compounds, with concentrations ranging from 1.17 µg L−1 to 213.33 µg L−1. Notably, the pharmaceutical ciprofloxacin was detected at a concentration that exceeded the reported risk level for Microcystis aeruginosa. The environmental risk assessment revealed that the risk quotient (RQ) for several of the compounds quantified in the two HWW matrices exceeded 1, with the risk quotient of the mixture of compounds (RQmix) being approximately 30 × 106 for Hospital A and 20 × 106 for Hospital B. According to these findings, the two HWW systems exhibited risk levels for aquatic species and small rodents, thereby contributing to the persistence of pharmaceuticals in the environment. Full article
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<p>Representation of the sample preparation flow.</p>
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<p>Comparison between the TIC results for acetaminophen (<b>A</b>) in simulated wastewater, (<b>B</b>) standard at a concentration of 10 µg·L<sup>−1</sup>, and (<b>C</b>) in real hospital wastewater.</p>
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<p>Classes of compounds found in each HWW screening by UHPLC-QTOF MS and their relative amounts.</p>
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<p>Compilation of RQ results from HA and HB in logarithmical scale for the evaluated ecotoxicological endpoints.</p>
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<p>Heatmaps for the RQ results, in logarithmical scale, of each pharmaceutical detected in HA and HB wastewaters. The color scheme goes from red (higher RQ values), through yellow to green (lower RQ values).</p>
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17 pages, 26606 KiB  
Article
The Effects of Disinfection Byproduct 2,6-Dichloro-1,4-benzoquinone on the Cyanobacterium Microcystis aeruginosa: From the Perspectives of Biochemistry and Non-Targeted Metabolomics
by Tianqi Zhang, Zhaoyang Wang, Liang Wu, Chaonan Liu, Liang Meng, Fuxiang Tian, Meifang Hou, Haizhuan Lin and Jing Ye
Toxics 2025, 13(1), 64; https://doi.org/10.3390/toxics13010064 - 17 Jan 2025
Viewed by 1087
Abstract
2,6-Dichloro-1,4-benzoquinone (2,6-DCBQ) is an emerging chlorinated disinfection byproduct (DBP) in bodies of water. However, this compound poses an unknown toxic effect on cyanobacteria. In this study, the toxicological mechanisms of 2,6-DCBQ in Microcystis aeruginosa (M. aeruginosa) were investigated through physiological and [...] Read more.
2,6-Dichloro-1,4-benzoquinone (2,6-DCBQ) is an emerging chlorinated disinfection byproduct (DBP) in bodies of water. However, this compound poses an unknown toxic effect on cyanobacteria. In this study, the toxicological mechanisms of 2,6-DCBQ in Microcystis aeruginosa (M. aeruginosa) were investigated through physiological and nontargeted metabolomic assessments. The results show that 2,6-DCBQ inhibited the growth of M. aeruginosa, reduced its photosynthetic pigment and protein contents, increased the levels of reactive oxygen species, damaged the antioxidant defense system, and aggravated the cytomembrane. Meanwhile, 2,6-DCBQ stimulated the production and release of microcystin-LR (MC-LR) and altered the transcripts of genes associated with its synthesis (mcyA, mcyD) and transport (mcyH). In addition, nontargeted metabolomics of M. aeruginosa cells exposed to 0.1 mg/L 2,6-DCBQ identified 208 differential metabolites belonging to 10 metabolic pathways and revealed the considerable interference caused by 2,6-DCBQ among ABC transporters, the two-component system, and folate biosynthesis. This study deepens the understanding of the physiological and nontargeted metabolomic responses of M. aeruginosa exposed to 2,6-DCBQ, offers insights into the toxic effect of 2,6-DCBQ on M. aeruginosa, and provides a theoretical basis for the ecological risk assessment of emerging DBPs in accordance with water quality criteria. Full article
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Graphical abstract
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<p>Cell density (<b>a</b>) of <span class="html-italic">M. aeruginosa</span> treated with 0.01, 0.05, 0.1, 0.2, and 0.5 mg/L of 2,6-DCBQ for 9 days. Concentrations of chlorophyll a (<b>b</b>) and carotenoids (<b>c</b>) of <span class="html-italic">M. aeruginosa</span> treated with mg/L 2,6-DCBQ on days 3, 6, and 9. Protein content (<b>d</b>) of <span class="html-italic">M. aeruginosa</span> treated with mg/L 2,6-DCBQ on days 3 and 6. Results are presented as means ± standard deviations. * Indicates <span class="html-italic">p</span> &lt; 0.05; ** indicates <span class="html-italic">p</span> &lt; 0.01 relative to the control by ANOVA.</p>
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<p>ROS level (<b>a</b>), SOD activity (<b>b</b>), CAT activity (<b>c</b>), and LPO content (<b>d</b>) of <span class="html-italic">M. aeruginosa</span> treated with 2,6-DCBQ on 24 and 48 h. ATP (<b>e</b>) and glucose (<b>f</b>) of <span class="html-italic">M. aeruginosa</span> treated with 2,6-DCBQ on days 3 and 6. Results are presented as means ± standard deviations. * Indicates <span class="html-italic">p</span> &lt; 0.05; ** indicates <span class="html-italic">p</span> &lt; 0.01 relative to the control by ANOVA.</p>
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<p>The effects of the CON (<b>a(1)</b>,<b>b(1)</b>) and 0.1 mg/L of 2,6-DCBQ on the ultrastructure (TEM, (<b>b(2)</b>–<b>b(4)</b>)) and surface morphology (SEM, (<b>a(2)</b>–<b>a(4)</b>)) of <span class="html-italic">M. aeruginosa</span> cells after 3 days of exposure. The components pictured include the nucleoid (N), phycobilisome (PBS), polyphosphate bodies (PB), thylakoids (T), leucoplast (L), cell wall (CW), and cell membrane (CM).</p>
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<p>Effects of 2,6-DCBQ on the contents of extracellular (<b>a</b>,<b>b</b>) and intracellular (cell quota) (<b>c</b>,<b>d</b>) microcystin-LR in <span class="html-italic">M. aeruginosa</span>. Results are presented as means ± standard deviations. * Indicates <span class="html-italic">p</span> &lt; 0.05; ** indicates <span class="html-italic">p</span> &lt; 0.01; *** indicates <span class="html-italic">p</span> &lt; 0.001 relative to the control by ANOVA.</p>
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<p>Two-dimensional scores plot of principal component analysis (PCA) (<b>a</b>). Two-dimensional scores plot of orthogonal partial least squares discriminant analysis (OPLS-DA) (<b>b</b>). Volcano plot of different metabolites (<b>c</b>). Lollipop map of main differential metabolites (<b>d</b>). The level indicates the accuracy of the metabolite identification, with smaller level numbers representing higher accuracy. * Indicates <span class="html-italic">p</span> &lt; 0.05; ** indicates <span class="html-italic">p</span> &lt; 0.01; *** indicates <span class="html-italic">p</span> &lt; 0.001 relative to the control by <span class="html-italic">t</span> test.</p>
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<p>Cluster analysis of top 50 differential metabolites.</p>
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<p>KEGG pathways with significant enrichment of metabolites (<b>a</b>). Circos diagram of KEGG pathways (<b>b</b>).</p>
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<p>Gene expression levels in treatments with 0.1 mg/L 2,6-DCBQ after 3 days of exposure. Results are presented as means ± standard deviations. ** Indicates <span class="html-italic">p</span> &lt; 0.01 relative to the control by ANOVA.</p>
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18 pages, 2085 KiB  
Article
Crustacean Zooplankton Ingestion of Potentially Toxic Microcystis: In Situ Estimation Using mcyE Gene Gut Content Detection in a Large Temperate Eutrophic Lake
by Helen Agasild, Margarita Esmeralda Gonzales Ferraz, Madli Saat, Priit Zingel, Kai Piirsoo, Kätlin Blank, Veljo Kisand, Tiina Nõges and Kristel Panksep
Toxins 2025, 17(1), 42; https://doi.org/10.3390/toxins17010042 - 16 Jan 2025
Viewed by 740
Abstract
Grazing by zooplankton can regulate bloom-forming cyanobacteria but can also transfer toxin-producing cells, as well as toxic metabolites, to the food web. While laboratory investigations have provided extensive knowledge on zooplankton and toxic cyanobacteria interactions, information on zooplankton feeding on toxin-producing cyanobacteria in [...] Read more.
Grazing by zooplankton can regulate bloom-forming cyanobacteria but can also transfer toxin-producing cells, as well as toxic metabolites, to the food web. While laboratory investigations have provided extensive knowledge on zooplankton and toxic cyanobacteria interactions, information on zooplankton feeding on toxin-producing cyanobacteria in natural water bodies remains scarce. In this study, we quantified Microcystis-specific mcyE synthase genes from the gut contents of various cladoceran and copepod taxa to assess the in situ crustacean community and taxon-specific ingestion of potentially toxic Microcystis in Lake Peipsi, a large eutrophic lake in Estonia, Northern Europe. Microcystis cells with mcyE genes were found in all crustaceans examined. However, some species, such as the cyclopoid copepod Mesocyclops leuckarti, were more efficient in ingesting potentially toxic Microcystis than other co-occurring cladocerans (Daphnia spp., Bosmina spp., Chydorus sphaericus) and copepods (Eudiaptomus gracilis). The amount of toxigenic Microcystis cells grazed by crustacean population changed temporarily, and copepods were the predominant consumers of toxigenic Microcystis during several months of the 5-month study period. Crustacean ingestion of toxigenic Microcystis was not related to Microcystis biomass or mcyE gene copy numbers in the environment but was instead related to the abundance of major crustacean grazers. Our findings emphasize the close interaction between crustacean zooplankton and toxigenic Microcystis, indicating that some species may play a more significant role in linking toxic cells within the food web than others. Full article
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<p>Location of sampling sites in Peipsi <span class="html-italic">sensu lato</span> (<span class="html-italic">s.l.</span>): P11 and P38 in Peipsi <span class="html-italic">sensu stricto</span> (<span class="html-italic">s.s.</span>) and P17 in Lämmijärv.</p>
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<p>Phytoplankton composition and biomass (<b>A</b>); seasonal dynamics of biomasses of <span class="html-italic">Microcystis</span> species and <span class="html-italic">Microcystis mcyE</span> copy numbers (±SD) (<b>B</b>) in sampling sites P11, P38, and P17 in Lake Peipsi in 2021.</p>
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<p>Seasonal dynamics of abundance (<b>A</b>) and biomass (<b>B</b>) of major crustacean taxa in sampling sites P11, P38, and P17 in Lake Peipsi in 2021.</p>
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<p>Seasonal dynamics of crustacean population feeding on potentially toxic <span class="html-italic">Microcystis</span> cells (based on the detection of <span class="html-italic">mcyE</span>-containing cells in consumer’ guts) in sampling sites P11, P38, and P17 in Lake Peipsi in 2021; ingestion by various cladoceran and copepod taxa (<b>A</b>); proportional contribution (%) of cladoceran and copepod ingestion (<b>B</b>).</p>
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<p>Seasonal dynamics of crustacean population feeding on potentially toxic <span class="html-italic">Microcystis</span> cells (based on the detection of <span class="html-italic">mcyE</span>-containing cells in consumer’ guts) in sampling sites P11, P38, and P17 in Lake Peipsi in 2021; ingestion by various cladoceran and copepod taxa (<b>A</b>); proportional contribution (%) of cladoceran and copepod ingestion (<b>B</b>).</p>
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<p>Principal component analysis plot displaying the association between cladoceran, copepod, and total crustacean population ingestion (<span class="html-italic">mcyE</span> cell/L), <span class="html-italic">Microcystis</span> biomass, <span class="html-italic">McyE</span> copy numbers, and environmental variables in Lake Peipsi in 2021 grouped by month.</p>
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14 pages, 3602 KiB  
Article
Environmental Factors Affecting the Phytoplankton Composition in the Lake of Tibetan Plateau
by Qinghuan Zhang, Zijian Xie, Chunhua Li, Chun Ye, Yang Wang, Zishu Ye, Weiwei Wei and Hao Wang
Diversity 2025, 17(1), 47; https://doi.org/10.3390/d17010047 - 13 Jan 2025
Viewed by 677
Abstract
Due to the high altitude, unique geographical location, difficult accessibility and low temperature, the environmental factors influencing phytoplankton composition have rarely been investigated in the Selin Co Lake, which is the largest lake in the Tibetan Plateau. Phytoplankton composition can indicate aquatic ecosystem [...] Read more.
Due to the high altitude, unique geographical location, difficult accessibility and low temperature, the environmental factors influencing phytoplankton composition have rarely been investigated in the Selin Co Lake, which is the largest lake in the Tibetan Plateau. Phytoplankton composition can indicate aquatic ecosystem conditions, which may be sensitive to environmental factors in the Tibetan Plateau. In this study, we investigated the main environmental factors that influence phytoplankton species in the Selin Co Lake by analyzing the spatial distribution and applying statistical analyses. We also compared the influential environmental factors in this lake with other lakes around the world. The results suggest that the eleven environmental variables can explain about 46.78% of the phytoplankton’s composition. DO and fluoride were the most significant environmental variables, followed by arsenic and COD, and the other variables had comparatively smaller and more insignificant influences on phytoplankton composition. There were five dominant phytoplankton species in the Selin Co Lake, namely, Microcystis sp., Navicula spp., Chlorella vulgaris, Ankistrodesmus falcatus, and Westella sp. Some of these dominant species were also found in other tropical lakes, suggesting that the phytoplankton community could adapt to environmental changes. A clear understanding of the influential environmental variables affecting phytoplankton composition could help us to make proper water quality protection strategies in future climate change scenarios. Full article
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<p>Geographical location of the Selin Co Lake and the sampling points of lake water (S1–S21).</p>
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<p>Spatial distribution of physico-chemical parameters in Selin Co Lake. (<b>a</b>) Water depth, (<b>b</b>) water transparency, (<b>c</b>) dissolved oxygen (DO), (<b>d</b>) water temperature, (<b>e</b>) TN concentrations, (<b>f</b>) TP concentrations, (<b>g</b>) COD<sub>Mn</sub>, (<b>h</b>) Trophic level index, (<b>i</b>) TDS, (<b>j</b>) salt content (salinity), (<b>k</b>) arsenic content, and (<b>l</b>) fluoride content.</p>
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<p>Correlation heatmaps of environmental variables in Selin Co Lake (in the circles, * represents <span class="html-italic">p</span> &lt; 0.05, ** represents <span class="html-italic">p</span> &lt; 0.01, and *** represents <span class="html-italic">p</span> &lt; 0.001; correlation coefficients close to 0 are shown as blank; salt is salinity, and SD is water transparency).</p>
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<p>(<b>a</b>) The relative abundance and (<b>b</b>) the relative biomass of different phytoplankton groups at each sampling point.</p>
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<p>RDA analysis of phytoplankton species abundance and environmental factors in Selin Co Lake. Black circles represent sampling points. Blue arrows represent environmental variables, and red arrows represent phytoplankton groups. The lengths of the arrows indicate how much variance was explained by the corresponding variable. The angles between arrows indicate correlations between individual environmental variables. SD represents water transparency.</p>
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13 pages, 5525 KiB  
Article
Allelopathic Suppression of Cyanobacterial Blooms by the Aquatic Plant Vallisneria natans Enhanced by Red and Blue LED Light Supplementation
by Aimin Hao, Zhouzhou Sun, Xiaoyu Shi, Dong Xia, Xin Liu and Yasushi Iseri
Water 2025, 17(1), 131; https://doi.org/10.3390/w17010131 - 6 Jan 2025
Viewed by 695
Abstract
Using allelochemicals produced by submerged plants to inhibit algal growth is an environmentally friendly approach to controlling harmful algal blooms in eutrophic lakes. This study aimed to evaluate the inhibition of cyanobacterial growth by allelochemicals accumulated by the aquatic plant Vallisneria natans, [...] Read more.
Using allelochemicals produced by submerged plants to inhibit algal growth is an environmentally friendly approach to controlling harmful algal blooms in eutrophic lakes. This study aimed to evaluate the inhibition of cyanobacterial growth by allelochemicals accumulated by the aquatic plant Vallisneria natans, with enhancement through blue and red light-emitting diode (LED) supplementation. We conducted a laboratory experiment to assess the fluorescence parameters, enzyme activities, and phycocyanin contents of cyanobacteria Microcystis aeruginosa grown in different V. natans cultivation media. The fluorescence parameters in the BG-11 medium remained stable, but sharply decreased in both LED treatments, with nearly 100% inhibition observed after 12 h of incubation. Superoxide dismutase (SOD) and peroxidase activities were stable in the BG-11 treatment, but enhanced in both LED treatments, reaching maximum values within 48 h. Higher SOD activities were observed with blue LED compared with red LED, suggesting better performance with blue light. A constant high phycocyanin fluorescence intensity was observed in the BG-11 treatment, while both LED treatments showed lower intensities. These results provided strong evidence that LED supplementation enhances the inhibitory effects of V. natans on M. aeruginosa growth. The combination of aquatic plant growth with underwater LED light supplementation offers a promising approach to controlling cyanobacterial blooms. Full article
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<p>Schematic diagram of the <span class="html-italic">Vallisneria natans</span> cultivation apparatus with fluorescent light (Control), blue LED (LED-Blue), and red LED (LED-Red) supplementation.</p>
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<p>Fluorescence parameters: (<b>a</b>) Yield, (<b>b</b>) α, (<b>c</b>) ETR<sub>max</sub>, and (<b>d</b>) I<sub>K</sub> of <span class="html-italic">Microcystis aeruginosa</span> in different experimental treatments. Error bars indicate standard deviations.</p>
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<p>Inhibition rate (%) of (<b>a</b>) Yield, (<b>b</b>) α, (<b>c</b>) ETR<sub>max</sub>, and (<b>d</b>) I<sub>K</sub> of <span class="html-italic">Microcystis aeruginosa</span> in different experimental treatments.</p>
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<p>Superoxide dismutase (SOD) (<b>a</b>) and peroxidase (POD) (<b>b</b>) activity of <span class="html-italic">Microcystis aeruginosa</span> cells in different experimental treatments. Error bars indicate standard deviations.</p>
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<p>Fluorescence excitation–emission matrix spectra for phycocyanin in <span class="html-italic">Microcystis aeruginosa</span> cells in different experimental treatments: (<b>a</b>) LED-Blue, (<b>b</b>) LED-Red, (<b>c</b>) Control, (<b>d</b>) BG-11.</p>
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18 pages, 7071 KiB  
Article
How Extreme Droughts Change the Impact of Eutrophic Reservoir on Its Outflow, with Special References to Planktonic Cyanobacteria and Their Secondary Metabolites?
by Magdalena Grabowska, Hanna Mazur-Marzec and Adam Więcko
Water 2025, 17(1), 86; https://doi.org/10.3390/w17010086 - 1 Jan 2025
Viewed by 787
Abstract
Increasingly frequent weather extremes induce changes in the quantity and quality of surface waters, complicating their use and resource management. These challenges are particularly relevant to dam reservoirs, designed to provide high-quality water for various recipients. The impact of extreme drought on lowland [...] Read more.
Increasingly frequent weather extremes induce changes in the quantity and quality of surface waters, complicating their use and resource management. These challenges are particularly relevant to dam reservoirs, designed to provide high-quality water for various recipients. The impact of extreme drought on lowland eutrophic reservoir–river systems remains poorly understood. Our research showed that the effects of extreme droughts, resulting in a decrease in the water level in a lowland reservoir and its outflow, are more severe than those of floods. During extreme droughts, reservoir pressure increases because the large load of cyanobacteria released from the reservoir, in conditions of low river discharge, is not diluted. unlike during floods. The increase in the total biomass of potamoplankton and, especially, cyanobacteria responsible for the production of toxic microcystins was positively correlated with reservoir outflow. Additionally, a shift in the dominant cyanobacteria species was observed, from Planktothrix agardhii to Microcystis spp., leading to changes in the oligopeptide profile, including microcystins. Full article
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<p>Map of the study area with the location of the sampling stations.</p>
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<p>River bed at station No. 6 during weather extremes: floods in October 2010 (<b>a</b>) and drought in August 2015 (<b>b</b>).</p>
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<p>Changes of water level in the SDR (<b>a</b>), outflow from SDR (<b>b</b>), and discharge in the Narew River at station No. 3 (<b>c</b>) and No. 5 (<b>d</b>) in 2015, 2018, and 2020; monthly averages with indication of daily averages from the date of sampling; AWL—average water level, ALQ—average low discharge.</p>
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<p>Changes of water level in the SDR (<b>a</b>), outflow from SDR (<b>b</b>), and discharge in the Narew River at station No. 3 (<b>c</b>) and No. 5 (<b>d</b>) in 2015, 2018, and 2020; monthly averages with indication of daily averages from the date of sampling; AWL—average water level, ALQ—average low discharge.</p>
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<p>Comparison of limnoplankton community structure in the surface layer in SDR (st. No. 1S) in 2015, 2018, and 2020; Cyano.—Cyanobacteria, Dino.—Dinophyceae, Bacill.—Bacillariophyceae.</p>
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<p>Limnoplankton and potamoplankton composition, total concentration of microcystins, and their individual variants in: August 2015 (<b>a</b>–<b>c</b>), September 2018 (<b>d</b>–<b>f</b>), July 2020 (<b>g</b>–<b>i</b>), August 2020 (<b>j</b>–<b>l</b>), and September 2020 (<b>m</b>–<b>o</b>).</p>
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<p>Limnoplankton and potamoplankton composition, total concentration of microcystins, and their individual variants in: August 2015 (<b>a</b>–<b>c</b>), September 2018 (<b>d</b>–<b>f</b>), July 2020 (<b>g</b>–<b>i</b>), August 2020 (<b>j</b>–<b>l</b>), and September 2020 (<b>m</b>–<b>o</b>).</p>
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<p>Changes in total phytoplankton biomass (TPB) and cyanobacteria biomass (TCB) at riverine station No. 3 (<b>a</b>), No. 4 (<b>b</b>), and No. 5 (<b>c</b>) in relation to reservoir outflow.</p>
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16 pages, 3491 KiB  
Article
Impact of the UV/H2O2 Process on Assimilable Organic Carbon and Trihalomethane Formation in Cyanobacteria-Contaminated Waters
by Luciana Verissimo Siquerolo, Rúbia Martins Bernardes Ramos, Pablo Inocêncio Monteiro, Guilherme Ferreira Silveira, Fatima de Jesus Bassetti and Lucila Adriani de Almeida Coral
Processes 2025, 13(1), 23; https://doi.org/10.3390/pr13010023 - 26 Dec 2024
Viewed by 736
Abstract
The organic material from cyanobacteria is a significant precursor to the generation of disinfection byproducts. This study’s aim was to evaluate the formation of assimilable organic carbon (AOC) in water contaminated with cyanobacteria. Furthermore, the formation of AOC was related to the generation [...] Read more.
The organic material from cyanobacteria is a significant precursor to the generation of disinfection byproducts. This study’s aim was to evaluate the formation of assimilable organic carbon (AOC) in water contaminated with cyanobacteria. Furthermore, the formation of AOC was related to the generation of trihalomethanes (THMs) and dissolved organic carbon (DOC). The advanced oxidation process was caISOrried out by exposing Microcystis aeruginosa cells (250,000 cells mL−1) to different peroxide dosages (10 to 100 mg L−1) under ultraviolet radiation. Pseudomonas fluorescens (P-17), Spirillum sp. (NOX), and flow cytometry were used to determine the AOC concentration. The formation of AOC and THMs during the UV/H2O2 process was not directly related. The AOC concentration increased with low H2O2 doses and decreased at higher concentrations, while the levels of THMs decreased regardless of the AOC formed. After oxidation, the DOC concentration decreased, along with the concentration of THMs. Additionally, it was observed that the behavior of DOC and AOC is inversely proportional. These results suggest that the oxidation process has a complex effect on organic matter, influencing byproduct formation and AOC availability. Moreover, these findings highlight the importance of carefully monitoring and controlling the oxidation processes to better understand their impact on water treatment and byproduct formation. Full article
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<p>Flow cytometry representing the cell count of the microorganisms P-17 and NOX in liquid medium; area of highest population density (red, yellow, and green); area of lowest population density (light blue and dark blue). (<b>a</b>) Density plot; (<b>b</b>) Dot plot (FSC-A—Cell size, SSC-A—cell complexity).</p>
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<p>Growth curve of microorganisms P-17 and NOX.</p>
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<p>Cell density of microorganisms in the presence and absence of sodium bisulfite through the flow cytometry “density plot” graph. The warm colors (red, yellow, and green) represent areas of higher population density; the cool colors (light blue and dark blue) indicate areas of lower density (After 96 h of growth); FSC-A (cell size); SSC-A (cellular complexity).</p>
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<p>Decomposition curve of H<sub>2</sub>O<sub>2</sub> under UV light over 90 min.</p>
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<p>Concentration of DOC before and after UV/H<sub>2</sub>O<sub>2</sub> oxidative process (Cell density: 250,000 cells mL<sup>−1</sup>).</p>
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<p>Formation of AOC from the UV/H<sub>2</sub>O<sub>2</sub> oxidative process and level of biological stability (Cell density: 250,000 cells mL<sup>−1</sup>).</p>
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<p>AOC and DOC formation during the UV/H<sub>2</sub>O<sub>2</sub> oxidative process (Cell density: 250,000 cells mL<sup>−1</sup>).</p>
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<p>Total THM concentration before and after the UV/H<sub>2</sub>O<sub>2</sub> oxidative process (Cell density: 250,000 cells mL<sup>−1</sup>).</p>
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<p>Concentration of trihalomethane compounds before and after UV/H<sub>2</sub>O<sub>2</sub> treatment (Cell density: 250,000 cells mL<sup>−1</sup>).</p>
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<p>DOC formation related to total THM concentration after UV/H<sub>2</sub>O<sub>2</sub> process (Cell density: 250,000 cells mL<sup>−1</sup>).</p>
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<p>Formation of AOC related to the concentration of total THMs (Cell density: 250,000 cells mL<sup>−1</sup>).</p>
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17 pages, 6300 KiB  
Article
Exploring the Correspondence Between Benthic Algae and Changes in the Aquatic Environment for Biodiversity Development
by Yanhang Hu, Long Yan, Peng Hu, Hongmin Guo, Xinyu Li and Wenhang Su
Sustainability 2024, 16(24), 11287; https://doi.org/10.3390/su162411287 - 23 Dec 2024
Viewed by 581
Abstract
In order to promote the development of biodiversity, the present study conducted three sampling surveys at 26 representative sampling sites selected from the Chishui River, a freshwater river in China, in July (rainy season), November (flat water period), and April 2024 (dry season), [...] Read more.
In order to promote the development of biodiversity, the present study conducted three sampling surveys at 26 representative sampling sites selected from the Chishui River, a freshwater river in China, in July (rainy season), November (flat water period), and April 2024 (dry season), respectively, focusing on the relationship between benthic algae and the response of water environmental factors. The results revealed that a total of 140 species from 48 genera and 7 phyla of benthic algae were identified, with the highest number of species belonging to the diatom phylum (85 species). The average density of benthic algae was highest during the flat water period, followed by the dry season and the flood season. Microcystis sp. was the dominant species during the flood season, while Gomphonema sp., Achnanthes tumescens, and Oscillatoria sp. were common dominant species during the dry and flat water periods. Achnanthes tumescens was the absolute dominant species in the upstream during the dry and flat water periods; Leptolyngbya sp. was the absolute dominant species in the midstream during the flat water period, and Oscillatoria sp. was the absolute dominant species in the middle reaches during the dry season. The Shannon-Wiener index, Margalef index, and species richness of benthic algae during the dry and flat water periods decreased from upstream to downstream. Non-metric multidimensional scaling analysis revealed significant differences in the community structures of benthic algae in the upper, middle, and downstream areas of the Chishui River during different periods, while cluster analysis indicated high similarity among benthic algae communities in locally adjacent areas. The differences in the benthic algae community structure increased with environmental and geographical distance, with environmental distance playing a greater role than geographical distance. RDA (Redundancy Analysis) identified TN (Total Nitrogen), TP (Total Phosphorus), DO (Dissolved Oxygen), EC (Electrical Conductivity), and NH3-N (Ammonia Nitrogen) as key water environmental factors influencing the structure of benthic algal communities in the Chishui River. Full article
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<p>Map of benthic algae sampling points in the Chishui River. 1~26 represent 1. Yudong (Yd), 2. Batou (Bt), 3. Yanjiao (Yj), 4. Banjiujing (Bjj), 5. Yujia Datian (YD), 6. Shuoliaopu (Slp), 7. Xujiahe (Xjh), 8. Chishuihe Zhen (CshZ), 9. Wantan Daqiao (WD), 10. Qingchi Zhen (QZ), 11. Longjing Dukou (LD), 12. Wuma Hekou (WH), 13. Maotai Shuiwen Zhan (MSW), 14. Hema (Hm), 15. Erlangtan (Elt), 16. Qianjiangsi (Qjs), 17. Tucheng (Tc), 18. Yuanhou (Yh), 19. Hushi (Hs), 20. Bing’an (Ba), 21. Fuxing (Fx), 22. Chishui Zhan (CsZ), 23. Chewang (Cw), 24. Yangfang (Yf), 25. Mixixiang (Mxx), 26. Hejiang (Hj). The red color in <a href="#sustainability-16-11287-f001" class="html-fig">Figure 1</a> is a map of China, and the blue color is the Chishui River Basin.</p>
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<p>Physicochemical factors of water in different hydrological periods. Us, Ms, and Ds represent Upstream, Midstream, and Downstream. (<b>a</b>) Temp (Water Temperature), (<b>b</b>) PH (Pondus Hydrogenii), (<b>c</b>) DO (Dissolved Oxygen), (<b>d</b>) EC (Electrical Conductivity), (<b>e</b>) NH<sub>3</sub>-N (Ammonia Nitrogen), (<b>f</b>) TN (Total Nitrogen), and (<b>g</b>) TP (Total Phosphorus).</p>
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<p>Distribution of algal species in the Chishui River. (<b>a</b>) Dry season; (<b>b</b>) Wet season; (<b>c</b>) Flat water period; (<b>d</b>) Three seasons in total.</p>
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<p>Relative abundance, abundance, relative biomass, and biomass of algae in different hydrological peripheries of the Chishui River. Us, Ms, and Ds represent Upstream, Midstream, and Downstream.</p>
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<p>Relative abundance, abundance, relative biomass, and biomass of algae in different hydrological peripheries of the Chishui River. Us, Ms, and Ds represent Upstream, Midstream, and Downstream.</p>
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<p>Violin plot of algal α diversity index and number of species in the Chishui River. (<b>a</b>) Shannon-Wiener diversity index (<span class="html-italic">H</span>′), (<b>b</b>) Pielou evenness index (J′), (<b>c</b>) Margalef richness index (D), and (<b>d</b>) Number of species.</p>
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<p>Violin plot of algal α diversity index and number of species in the Chishui River. (<b>a</b>) Shannon-Wiener diversity index (<span class="html-italic">H</span>′), (<b>b</b>) Pielou evenness index (J′), (<b>c</b>) Margalef richness index (D), and (<b>d</b>) Number of species.</p>
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<p>Non-metric Multidimensional Scale Analysis (NMDS) ranking diagram of the algal community in the Chishui River. (<b>a</b>–<b>d</b>) represent wet season, dry period, flat water period, and three seasons in total. In (<b>a</b>–<b>c</b>), the red diamond is upstream, the blue triangle is midstream, and the green circle is downstream. In (<b>d</b>), the red diamond is dry season, the blue triangle is wet season, and the green circle is flat water period.</p>
Full article ">Figure 6 Cont.
<p>Non-metric Multidimensional Scale Analysis (NMDS) ranking diagram of the algal community in the Chishui River. (<b>a</b>–<b>d</b>) represent wet season, dry period, flat water period, and three seasons in total. In (<b>a</b>–<b>c</b>), the red diamond is upstream, the blue triangle is midstream, and the green circle is downstream. In (<b>d</b>), the red diamond is dry season, the blue triangle is wet season, and the green circle is flat water period.</p>
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<p>Bray-Crutis clustering heat map of algal communities at different hydrological periods in the Chishui River. 1~26 represent 1. Yudong (Yd), 2. Batou (Bt), 3. Yanjiao (Yj), 4. Banjiujing (Bjj), 5. Yujia Datian (YD), 6. Shuoliaopu (Slp), 7. Xujiahe (Xjh), 8. Chishuihe Zhen (CshZ), 9. Wantan Daqiao (WD), 10. Qingchi Zhen (QZ), 11. Longjing Dukou (LD), 12. Wuma Hekou (WH), 13. Maotai Shuiwen Zhan (MSW), 14. Hema (Hm), 15. Erlangtan (Elt), 16. Qianjiangsi (Qjs), 17. Tucheng (Tc), 18. Yuanhou (Yh), 19. Hushi (Hs), 20. Bing’an (Ba), 21. Fuxing (Fx), 22. Chishui Zhan (CsZ), 23. Chewang (Cw), 24. Yangfang (Yf), 25. Mixixiang (Mxx), 26. Hejiang (Hj), (<b>a</b>–<b>c</b>) represent Wet season, Dry period, Flat water period.</p>
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<p>Differences in algal communities in different hydrological periods of the Chishui River in terms of environmental and geographical distances. (<b>a</b>,<b>b</b>) Dry season; (<b>c</b>,<b>d</b>) Wet season; (<b>e</b>,<b>f</b>) Flat water period.</p>
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<p>Redundancy analysis (RDA) plot of algae sampling sites and environmental factors. <span class="html-italic">sp1</span> (<span class="html-italic">Diatoma</span> sp.), <span class="html-italic">sp2</span> (<span class="html-italic">Diatoma vulgare</span>), <span class="html-italic">sp3</span> (<span class="html-italic">Eunotia</span> sp.), <span class="html-italic">sp4</span> (<span class="html-italic">Gomphonema</span> sp.), <span class="html-italic">sp5</span> (<span class="html-italic">Navicula</span> sp.), <span class="html-italic">sp6</span> (<span class="html-italic">Navicula cincta</span>), <span class="html-italic">sp7</span> (<span class="html-italic">Cocconeis placentula var. linearis</span>), <span class="html-italic">sp8</span> (<span class="html-italic">Cocconeis</span> sp.), <span class="html-italic">sp9</span> (<span class="html-italic">Achnanthes inflata</span>), <span class="html-italic">sp10</span> (<span class="html-italic">Achnanthes</span> sp.), <span class="html-italic">sp11</span> (<span class="html-italic">Achnanthes linearis</span>), <span class="html-italic">sp12</span> (<span class="html-italic">Cyclotella</span> sp.), <span class="html-italic">sp13</span> (<span class="html-italic">Microcystis</span> sp.), <span class="html-italic">sp14</span> (<span class="html-italic">Chlorogloea microcystoides</span>), <span class="html-italic">sp15</span> (<span class="html-italic">Entophysalis</span> sp.), <span class="html-italic">sp16</span> (<span class="html-italic">Entophysalis robusta</span>), <span class="html-italic">sp17</span> (<span class="html-italic">Leptolyngbya</span> sp.), <span class="html-italic">sp18</span> (<span class="html-italic">Oscillatoria tenuis</span>), <span class="html-italic">sp19</span> (<span class="html-italic">Oscillatoria</span> sp.), <span class="html-italic">sp20</span> (<span class="html-italic">Chlorella</span> sp.), <span class="html-italic">sp21</span> (<span class="html-italic">Chlamydomonas ovalis</span>), <span class="html-italic">sp22</span> (<span class="html-italic">Cladophora</span> sp.), <span class="html-italic">sp23</span> (<span class="html-italic">Closterium</span> sp.), <span class="html-italic">sp24</span> (<span class="html-italic">Trachelomonas rotunda</span>), <span class="html-italic">sp25</span> (<span class="html-italic">Cryptomonas erosa</span>), (<b>a</b>) Dry season, (<b>b</b>) Wet season, (<b>c</b>) Flat water period.</p>
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