Cellular response in the resilience of Microcystis aeruginosa under polyaluminum chloride exposure

Cellular response in the resilience of Microcystis aeruginosa under polyaluminum chloride exposure | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Cellular response in the resilience of Microcystis aeruginosa under polyaluminum chloride exposure Seong-il Eyun, Eun-jeong Kim, Yeon-jeong Park, Jae Hak Lee, Heesuk Lee, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5278810/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Polyaluminum chloride (PAC) is a flocculant commonly used to remove microalgal cells from blooming reservoir. However, some cells exposed to PAC can survive and remain suspended at the surface of eutrophic lakes, potentially reblooming in high-temperature conditions. This study investigated the cellular responses underlying the survival resilience of Microcystis in response to PAC treatment. During cell growth, we observed that exposure to low levels of PAC led to a growth pattern resembling normal conditions, whereas cells exposed to high levels of PAC experienced immediate growth inhibition, followed by cell death. Therefore, we employed RNA sequencing to investigate dynamic gene expression. At the transcriptomic level, 264 distinct genes exhibited differential expression under low PAC exposure, significantly affecting the bacterial secretion system and photosynthesis. Changes in the expression of the photosystem II antenna complex phycobilisome were subsequently reflected in changes in phycocyanin pigment production. Furthermore, we identified 223 unique genes under high PAC exposure. Notably, in type II toxin–antitoxin systems, which serve as a prokaryotic defense mechanism, several toxin genes were expressed at higher levels than antitoxin genes, promoting cell death or apoptosis. These findings bridge a gap in the understanding of cyanobacterial ecotoxicology and environmental responses, potentially enhancing biotechnological and clinical applications. Earth and environmental sciences/Ecology/Ecological genetics Biological sciences/Microbiology/Environmental microbiology/Water microbiology Microcystis aeruginosa Doubling time RNA-seq PSII antenna protein bacterial secretion system toxin–antitoxin system Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Highlights • PAC chemical stress targeted photosystem II antenna proteins in Microcystis . • Bacterial secretion systems enhanced stress resilience with low PAC levels. • Upregulated transposases were observed with high PAC levels. • PAC stress triggered the activation of toxin–antitoxin systems. 1. Introduction In recent decades, harmful cyanobacterial blooms have increased in frequency, intensity, and duration, primarily driven by eutrophication and climate change 1 , 2 . Severe cyanobacterial blooms during summer can contaminate drinking and recreational water sources, reducing the water quality 3 – 5 . The removal of cyanobacterial biomass from water bodies used for drinking water and from treatment plants is thus a major challenge 6 , 7 . In this context, flocculation is considered an effective strategy for managing microalgal biomass in deep and stratified lakes and water treatment plants 8 . For example, a microbial bio-flocculation efficiency of > 98% has been achieved with freshwater microalgae at both a pilot scale and a bench scale 9 . Polyaluminum chloride (PAC) is an inorganic flocculant that is commonly used to eliminate Microcystis biomass in eutrophic lakes and water treatment facilities 7 , 10 , 11 . Laboratory analysis has also revealed that PAC can most effectively remove Microcystis biomass using nano-Fe 3 O 4 particles as a coagulant aid (Arruda et al., 2021). However, it has been demonstrated that, despite undergoing chemical flocculation, some cells exposed to PAC can survive and remain suspended at the surface of eutrophic lakes, potentially reblooming in high-temperature conditions 12 , 13 . In another recent study, cyanobacterial chlorophyll- a was reported to be reduced by 90% after PAC treatment, but elevated cyanobacterial concentrations were observed one week later 8 . It is thus important to understand the molecular mechanisms by which cells develop tolerance to chemical exposure, but current understanding of the various biological and physiological processes involved in resisting chemical stress remains limited. Transcriptomics has proven to be an invaluable tool for linking physiology with ecology in aquatic microbes. Examples of this include an analysis of the temporal dynamics in the global transcriptomic patterns of Microcystis 14 and the analysis of early RNA-seq data to determine the specific effects of nutrient limitations, including nitrogen, phosphate, and urea, on microcystin in Microcystis 14 – 16 . This advanced sequencing technology has also allowed the analysis of transcriptional dynamics in response to the bacterial community or phage infection in Microcystis blooms 17 – 19 . More recent RNA-seq studies have focused on chemical, drug, or nano-plastic exposure to understand biological processes for biotechnological, toxicological, and medical applications using Microcystis cells 20 – 23 . In order to address the re-emergence of Microcystis blooms following PAC treatment in the field, we employed RNA sequencing technology to identify intracellular tolerance mechanisms during the initial and post-reaction phases following PAC exposure in M. aeruginosa . To the best of our knowledge, this is the first study reporting transcript dynamics in response to PAC treatment. We observed changes in photosynthetic antenna pigments within 48 h of low PAC exposure, resulting in a cell generation time that was 12 h longer after eight days. Under low PAC exposure, the cell numbers initially reduced by only 20%, with phenotypic growth returning to normal after three days; however, long-term observations revealed a 50% reduction in cell numbers by the 23rd day (Table S1 ). Under high PAC exposure, all of the cells were dead by the 23rd day. This experiment demonstrates that cells exposed to PAC can regrow and rebloom after one week under appropriate growth conditions in the field. We also examined the biological mechanisms that contribute to the resilience of Microcystis cells in response to PAC exposure in laboratory-scale experiments. 2. Materials and methods 2.1. Culture conditions and frozen cells The M. aeruginosa strain KW (KCTC 18162P) was obtained from the Korean Collection for Type Cultures 24 . This strain was grown in a 500 ml flask with 300 ml of BG-11 medium (Fig. 1 ). The cells were cultured under a light intensity of 30 ± 1 µmol m - 2 s - 1 at 25℃ using a shaker. The strain was precultured for one week and collected using centrifugation at 4000 rpm for 5 min. The cells were washed three times with fresh BG-11 and then resuspended in the same medium. The cells were reinoculated at a density of 6 × 10 6 cells/ml into either a 40 ppm or 400 ppm PAC solution, representing low and high PAC exposure, respectively. After incubation for 3, 6, and 24 h, each sample was washed and centrifuged, and the supernatant was removed. The pellets were immediately frozen in liquid nitrogen and stored in a freezer at − 70℃. RNA isolation was conducted within one week, and the samples were sent for RNA sequencing. 2.2. PAC solutions PAC is an inorganic polymer flocculant commonly used for microalgal coagulation in the field and wastewater treatment as an EPA standard 25 . Microalgae in a colloidal state in water move via electrostatic repulsion. The addition of a coagulant with a charge opposite to that of the microalgal cell wall consequently leads to flocculation 26 . The stock PAC solution was prepared in distilled water and stored at room temperature. Two flasks were dosed with a concentration of 40 mg/L and 400 mg/L from the PAC stock solution. 2.3. Growth curves and doubling time calculation Three flasks, including a control with no treatment, low PAC treatment, and high PAC treatment, were incubated for 3 h, 6 h, 24 h, 1 day, 2 days, 3 days, and 8 days (Fig. 1 ). Following incubation, these samples were stained with Lugol’s iodine, and the cells were counted using a Hemocytometer C-Chip (NCYTO ® ), with the counts repeated 15 times. The average cell number was used for growth curve analysis (Fig. 2 A). The doubling time for the cultures was calculated using the growth rate (Table S1 ). $$\:\text{G}\text{r}\text{o}\text{w}\text{t}\text{h}\:\text{r}\text{a}\text{t}\text{e}\:\left(r\right)=\frac{\text{I}\text{n}\:\left(N\right(t)\:/\:N0)}{\:t}$$ where N ( t ) is the number of cells at time t , N 0 is the number of cells at time 0, and t is the time (h). $$\:\text{D}\text{o}\text{u}\text{b}\text{l}\text{i}\text{n}\text{g}\:\text{t}\text{i}\text{m}\text{e}\:\left(dt\right)=\frac{\text{I}\text{n}\:\left(2\right)}{r}$$ In addition, microscopic images were taken to observe phenotypic changes such as cell pigment fading, cell wall rupture, and apoptosis (Fig. 2 B). 2.4. Photosynthetic pigment content After the 3-h, 6-h, 24-h, 1-day, 2-day, and 3-day incubation periods (Fig. 1 ), the samples were centrifuged for 10 min at 4000 rpm, and the pellets were extracted with 1 ml of 90% acetone. Chlorophyll- a levels were measured based on the optical density at 750, 663, 645, and 630 nm, with 90% acetone used as a blank 27 . PC was extracted via freezing at − 20℃ and thawing at room temperature for four cycles and then measured based on the optical density at 615 and 652 nm 28 . All photosynthetic pigments were quantified using a spectrophotometer (Fig. 2 D and 2 E). 2. 5. Illumina sequencing and transcriptome analysis The frozen pellets from Section 2.1 were used for total RNA isolation using a Maxwell 16-cell LEV RNA purification kit for plants, following the manufacturer’s instructions (Promega). The library was prepared according to Illumina’s specifications. The quality and integrity of the RNA were determined using an Agilent Technologies 2100 Bioanalyzer (Agilent, Germany). The samples were sequenced on an Illumina NovaSeq 6000 Sequencing Platform (Table S2), and the clean reads were mapped to M. aeruginosa KW as a reference genome 24 . Transcript abundance was normalized in terms of the fragment per kilobase of transcript per million mapped reads (FPKM) and the normalized log2 (FPKM + 0.1) values were used (Fig. S1 ). Differential expression analysis was conducted using the HTseq packages to compare between samples. A log2 fold change of |fc| ≥ 1 and a p -value < 0.05 were set as the criteria for identifying statistically significant changes in gene expression levels. Time series analysis of the transcriptional response was conducted using k -means cluster analysis 29 . This method partitions fold-change patterns into k clusters, with each fold-change time series added to the cluster with the nearest mean and the clusters iteratively refined. This form of analysis has been used to identify dynamic expression patterns for large numbers of genes. Clusters of orthologous groups (COGs) of proteins are classified into different functional categories based on their predicted biological roles, thus helping to understand the functional roles and biological processes of genes and proteins 30 , 31 . Additionally, a hypergeometric distribution was used to determine if any differentially expressed genes (DEGs) were significantly enriched in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. For gene enrichment analysis, we employed the online ShinyGO 0.80 tool with M. aeruginosa NIES-843 as the reference organism ( http://bioinformatics.sdstate.edu/go/ ). We integrated the ggplot2 package into the R studio environment to produce volcano plots and Venn diagrams and to visualize the KEGG enrichment analysis. 3. Results 3.1 Effects of PAC on the growth of M. aeruginosa After eight days of PAC exposure, the Microcystis cell numbers in the control, low PAC exposure, and high PAC exposure groups were 3.2 × 10 6 cell/ml, 2.6 × 10 6 cell/ml, and 0.08 × 10 6 cell/ml, respectively (Fig. 2 A), representing an 18.75% and 97.5% reduction under low and high PAC exposure, respectively, compared to the control. Based on the growth curves, the doubling time was calculated to be 3.75 days for the control and 4.25 days for low PAC exposure. Under high PAC exposure, phenotypic photographic images revealed a larger cell size after 3 h and disrupted cells after 3 days. Conversely, under low PAC exposure, the Microcystis cells grew well and were similar in appearance to those in the control after 24 h (Fig. 2 B). A lower pH was measured for the high PAC treatment, while the other two groups were not considerably different (Fig. 2 C). The trends in the levels of chlorophyll- a and phycocyanin (PC) were consistent with the growth curves (Fig. 2 D and 2 E). After three days, the PC concentration fell by 11.9% (1.11 × 10 2 mg/m 3 ) and 88.1% (8.21 × 10 2 mg/m 3 ) under low and high PAC exposure compared to the control, respectively (Fig. 2 E). The cells exposed to high PAC levels entered the death stage after three days. 3.2 DEGs and gene enrichment under low PAC exposure To understand how M. aeruginosa gene expression responded to low PAC exposure over time, we exposed the cells to low PAC for 3 h, 6 h, and 24 h and identified DEGs that appeared in at least two samples (Fig. S2A). Volcano plots were used to visualize the upregulated and downregulated genes for each sample, with a total of 358 DEGs identified (Fig. S2B). In terms of upregulated genes, there were 111 DEGs for 3 h after initial exposure, compared to only 38 after 24 h. In contrast, the number of downregulated genes after 24 h (90 DEGs) was higher than that during the initial 3 h (23 DEGs). Overall, a total of 264 unique DEGs were identified during low PAC exposure after 3 h, 6 h, and 24 h (Fig. S2C). We also conducted cluster analysis of the DEGs using the k -means algorithm. In this analysis, half of the 264 DEGs were excluded because they had domains of unknown function, were annotated as hypothetical proteins, or were pseudogenes. The expression patterns of 84% (111 out of 132 DEGs) of the retained genes were categorized into Clusters A to D (Fig. 3 and S3). Nearly half of the functionally annotated genes assigned to Cluster A exhibited elevated expression levels in the early stages of exposure, followed by lower expression levels in the later stages. Cluster D also exhibited reduced expression levels in the later stages, but their expression levels were also slightly lower early in the exposure period (Fig. 3 A). Clusters B and C displayed only slight changes in their gene expression dynamics. Furthermore, we analyzed the gene enrichment of Clusters A and D and set a cut-off for statistical significance at a false discovery rate (FDR) of less than 0.05. In each cluster, we identified the top 8 KEGG pathways that were the most enriched under low PAC exposure (Fig. 3 B). In Cluster A, the majority of the gene enrichment was related to fatty acid biogenesis and the secretion system, while photosynthesis pathways were significantly enriched in Cluster D. 3.3 KEGG metabolic pathways under low PAC exposure The results from the gene cluster and enrichment analyses presented in Section 3.2 revealed that DEGs associated with the bacterial secretion system and photosynthesis pathway were downregulated after 24 h of PAC exposure. In Cluster A, the type I and II bacterial secretion systems were significantly upregulated in the early stages of exposure (i.e., after 3 h; Fig. 4 A). Most of the enriched genes assigned to the KEGG pathway for the HlyD secretion protein and fatty acid biosynthesis were listed with their expression levels in the right panel of Fig. 4 A. Interestingly, HlyD belongs to the membrane fusion protein (MFP) family, and cell membranes are composed of fatty acids 32 . After 24 h of PAC exposure, photosystems I and II (PSI and PSII, respectively), which were part of Cluster D, were downregulated compared to the control (Fig. 4 B). In particular, it is notable that PAC exposure significantly affected PSII antenna proteins located on the surface of the thylakoid membrane 33 . 3.4. Functional analysis of high PAC exposure To investigate their response to high levels of chemical stimuli, Microcystis cells were exposed to high levels of PAC and subjected to RNA sequencing. The DEGs were screened based on a log 2 fold change of |fc| ≥ 1 and a p -value < 0.05 (Fig. 5 A). Under high PAC exposure, a total of 302 DEGs were identified, with 119 genes upregulated and 183 genes downregulated (Fig. 5 B). Gene enrichment analysis revealed that upregulated DEGs associated with putative transposase and ribonuclease Z/hydroxyacylglutathione hydrolase (Z/HAGH)-like proteins were enriched in KEGG pathways shown in the top panel of Fig. 5 C. Interestingly, the high levels of PAC exposure promoted the pathway related to detoxification, specifically involving ribonuclease Z/HAGH-like proteins to remove toxic metabolites 34 . Furthermore, enriched pathways related to photosynthesis were downregulated, which was consistent with the results for low PAC exposure in the bottom panel of Fig. 5 C. Functional analysis of the COGs revealed a distinct increase in the mobilome (prophages and transposons; category X, indicated by a red plus sign), which was consistent with the upregulation of enriched DEGs observed under high PAC exposure in the top panel of Fig. 5 C (Fig. 5 D). Functional analysis also revealed a decrease in energy production and conversion (category C, **) and cell wall/membrane/envelope biogenesis (category M, **). In contrast, the upregulated categories included post-translational modification, protein turnover, and chaperone functions (category O, *) and defense mechanisms (category V, *). Surprisingly, high PAC exposure enhanced the expression of toxin–antitoxin (TA) systems, a key component of prokaryotic defense mechanisms (left panel of Fig. 6 ). The degradation of the antitoxin occurs with the production of protease, and a stable toxin leads to cell death or the suppression of growth 35 . Both the antitoxin and/or TA complex have the ability to negatively regulate their own transcription by identifying and binding to palindromic sequences within their operators 36 , 37 . The BrnA-BrnT and HicA-HicB TA systems were identified in the initial stage of high PAC exposure. The toxin components of the TA module included ParE/RelE-like and MazF/Pemk-like proteins, while the antitoxin components included MqsA-like, CcdA-like, and prevent-host-death-like proteins (right panel of Fig. 6 ). The upregulated antitoxin genes were associated with neutralizing toxins, stress response modulation, and survival mechanisms 37 , 38 . Furthermore, the Clp protease ATP-binding subunit ClpA was upregulated more than 2.2-fold compared to low PAC exposure (Fig. 6 ). 4. Discussion Chemical remediation is a key method for controlling biomass from microalgal blooms. In the present study, PAC was found to inhibit the growth and development of Microcystis cells by disrupting photosynthesis-related pathways (Fig. 2 B and 5 C). The levels of PC, which is responsible for absorbing light energy in cyanobacteria, were reduced more than those of chlorophyll- a (Fig. 2 D and 2 E). In addition, the higher expression of pigment-producing genes was correlated with greater pigment production, indicating that gene expression directly influences pigment levels. This evidence helps to explain how genetic regulation affects pigment synthesis at a molecular level (Fig. 2 E and 3 A, Cluster D). Exposure to low levels of PAC resulted in a growth curve similar to the normal pattern, though it caused an approximate 12 h delay in the doubling time compared to the control (Fig. 2 A and Table S1 ). The observed phenotype of cells exposed to low PAC, including gas vesicles resembling those of the control cells, indirectly indicated normal growth conditions (Fig. 2 B). However, cells exposed to high levels of PAC exhibited suppressed growth, fewer gas vesicles, and damage to the cell wall after three days of exposure (Fig. 2 A and B). This is in line with past research, which has shown that high PAC concentrations reduce the pH, which can negatively affect growth, reduce photosynthetic efficiency, and disrupt cell membrane integrity 39 , 40 (Fig. 2 C). Under high PAC exposure, all of the cells were dead by day 23 (Table S1 ). In contrast, under low PAC exposure, cell numbers initially decreased by only 20.8% after 8 days, but long-term observations revealed a 50.3% reduction after 23 days (Table S1 ). Although this experiment has limitations in reflecting actual environmental fluctuations due to the limited nutrients and constant light intensity, the findings support previous observations that cyanobacteria regrow after PAC treatment in the field 8 . 4.1. Photosynthetic damage caused by organic chemical stress To identify the genes associated with the observed cell growth dynamics, we analyzed RNA sequencing data to link phenotypic changes with transcriptomic dynamics. Many organic chemicals that target PSII directly bind to the D1 protein of PSII, blocking electron transport and preventing the conversion of light energy into chemical energy 41 . For example, the response of Microcystis to allelochemical ethyl 2-methyl acetoacetate (EMA) indicates damage to the photosynthetic apparatus, with the degradation of allophycocyanin (AP), phycoerythrin (PE), and carotenoid, while chlorophyll- a levels increased 42 . In this study, the exposure of M. aeruginosa to PAC can significantly reduce its ability to convert light energy into chemical energy by directly targeting PSII systems, including antenna proteins such as AP, pycocyanin (PC)/phycocerythrocyanin (PEC). Photosynthesis antenna proteins were enriched (Fig. 3 B), while AP-related genes ApcA–D and AP/PEC-related genes CpcA–D and CpcG were downregulated (Fig. 4 ). Some organic pollutants also interfere with the biosynthesis of chlorophyll, the primary pigment involved in photosynthesis 43 . In the present study, lower PC content led to reduced light absorption and energy capture (Fig. 2 A and E). The thylakoid membrane also houses the components of the photosynthetic electron transport chain 44 . The enrichment of electron transport and thylakoid membrane-related genes suggests potential negative effects on photosynthesis (Fig. 3 B). Organic chemicals can also generate reactive oxygen species (ROS) and oxidative stress, damaging cellular components 45 . This study revealed that the oxidation–reduction process was enriched (Fig. 3 B). In addition, some organic chemicals interfere with photosynthetic electron transport by accepting electrons from PSI and transferring them to molecular oxygen, generating superoxide radicals and causing oxidative damage 46 . PAC triggered the reduction of PSI, including PsaA/D/E/I/J/K/L, and the cytochrome b6/f complex-related gene PetM was enriched (Fig. 4 B). As a result, most PSII antenna proteins and PS I-related genes were downregulated in gene expression and were enriched in the photosynthesis pathway (Fig. 3 B and 4 B). PAC exposure thus potentially affects photosynthetic efficiency, leading to a reduction in the growth of Microcystis . 4.2. Bacterial type I/II secretion systems in minimizing intracellular damage Bacteria secretion systems play a vital role in survival under stress conditions by secreting proteins and enzymes that can neutralize harmful substances or repair damage 47 . The type I secretion system, which consists of an MFP, an ATP-binding cassette (ABC) transporter, and an outer membrane protein (OMP), directly transports proteins from the cytoplasm to the extracellular space without a periplasmic intermediate 48 . In this study, the MFP (HlyD; B1L_RS28235) and ABC transporter (HlyB; B1L04_RS28230) were significantly enriched in gene expression, indicating activation of the type I secretion system in response to PAC (Fig. 4 A). In addition, AcrAB-TolC in E. coli is an intrinsic RND-type multidrug efflux transporter that functions as a tripartite complex of the inner membrane transporter (IMP) AcrB, the outer membrane channel TolC, and the adaptor protein AcrA 49 . The upregulated expression of efflux pump subunits AcrA (B1L04_RS20330) and AcrB (B1L04_RS20325) was also observed in the present study (Fig. 4 A). The type II secretion system is a more complex, two-step process that first translocates proteins into the periplasm via the Sec or Tat pathway, followed by their secretion across the outer membrane 50 . The type II secretion system secretes enzymes such as proteases, lipases, and nucleases that can degrade extracellular toxins before they can cause intracellular damage 51 . IMP GspH, which is related to the type II secretion system, was also upregulated and enriched in the cellular pathways in this study (Fig. 4 A). Therefore, in the early stages of low PAC exposure, the activated type I and II secretion systems served as an adequate defense mechanism (Fig. 4 A and B). 4.3. Toxin–antitoxin systems as a stress response in M. aeruginosa TA systems in cyanobacteria are an important mechanism for managing stress by modulating cell growth, inducing dormancy, and facilitating biofilm formation 52 , 53 . In a TA system, the toxin is a stable protein that can interfere with vital cellular processes such as DNA replication, RNA stability, or protein synthesis, regulating cell growth or killing the cell. With exposure to high levels of PAC, the activation of the toxin may lead to programmed cell death, releasing nutrients from dying cells that can be used by surviving cells. The antitoxin is typically less stable and binds to the toxin, neutralizing its activity, and is regulated by environmental conditions 35 , 37 . In this study, eight superfamilies of type II TA systems were significantly expressed in response to high PAC exposure (Fig. 6 ). Both BrnT-BrnA and HicA-HicB TA systems were identified, while other TA systems were only recognized as either toxin or antitoxin-like families (right panel of Fig. 6 ). Previous research has reported that the transcription of BrnT-BrnA is upregulated in the presence of stressors such as low pH and antibiotics 54 . Similarly, the HicA-HicB module is involved in virulence in bacteria and adaptation to extracellular stresses in E. coli 55 . The ParD-ParE TA system for protection against antibiotics has been characterized in plasmid RK2 as a plasmid stabilization element 36 . In addition, the toxin MzxF neutralizes the activity of MaxE, which is degraded more rapidly under stress conditions 37 , while Clp ATPases (K03696), which are a component of TA modules, are required for stress tolerance 53 . Additionally, many TA systems that were not detected under high PAC exposure were expressed in response to low PAC exposure (Table S3). However, it is important to note that the mechanisms of action and biological roles of bacterial TA systems can vary depending on the bacterial species. Further research into these systems can thus help to clarify the survival strategies of cyanobacteria and their ecological impact. 5. Conclusion To understand the stress resilience of M. aeruginosa in response to the organic coagulant PAC, the present study integrated phenotypic phenomena with transcriptome dynamics. In this study, phenotypic analysis revealed lower growth rates and a reduction in photosynthetic pigment levels, while transcriptomic analysis identified upregulated genes, including those involved in the secretion system and fatty acid biogenesis. In particular, in the early stages of exposure, exporting toxic compounds and secreting protective enzymes helped to minimize intracellular damage. Fatty acids released from cell membrane phospholipids were also involved in Microcystis tolerance to abiotic and biotic stresses. Therefore, further analysis is required to understand the relationship between fatty acid accumulation and stress defense mechanisms in response to PAC by combining proteomics with lipid production analysis. The proposed approach allowed for a comprehensive understanding of the stress resilience of molecular mechanisms in response to low PAC exposure in Microcystis . However, the results of high PAC exposure are expected to be of greater interest for future medical research. Under high levels of PAC exposure, we found that the detoxification process helps to neutralize or remove toxic compounds and mitigate the harmful effects of environmental stressors, contributing to the use of cellular hemostasis for medical applications. In addition, we also identified transposable elements, also known as jumping genes, that can change their position within the genome, facilitating the analysis of the genomic adaptation of Microcystis to PAC stress in future research. Declarations CRediT authorship contribution statement Eun-jeong Kim : Conceptualization, Data curation, Formal analysis, Methodology, Visualization, Writing – Original Draft and Reviewing & Editing. Yeon-jeong Park : Data curation, Formal analysis, Methodology, Writing – Original Draft and Reviewing & Editing. Jae Hak Lee : Data curation, Methodology. Heesuk Lee : Data curation, Funding acquisition, Methodology. Jihye Yang : Data curation. Han Soon Kim : Conceptualization, Data curation. Seong-il Eyun : Funding acquisition, Supervision, Writing – Reviewing & Editing. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Data availability Raw reads corresponding to transcriptome analyses have been deposited in the NCBI Sequence Read Archive under the BioProject identification number PRJNA1142213. Acknowledgements The authors gratefully acknowledge Dr. Chi-Yong Ahn and Hee-Mock Oh, Cell factory Research Center, KRIBB, Daejeon 34350, Korea, for generously providing the Microcystis aeruginosa KW strain. This work was supported by the National Research Foundation of Korea [2022R1A2C4002058]; Korea Institute of Marine Science & Technology Promotion [RS-2022-KS221676] funded by the Ministry of Oceans and Fisheries; National Research Council of Science & Technology (NST) grant by the Korea government (MSIT) [CAP-18-07-KICT]. References Glibert, P. M. Harmful algae at the complex nexus of eutrophication and climate change. Harmful Algae 91, 101583, doi: 10.1016/j.hal.2019.03.001 (2020). Miranda, M. et al. The efficiency of combined coagulant and ballast to remove harmful cyanobacterial blooms in a tropical shallow system. Harmful Algae 65, 27–39, doi: https://doi.org/10.1016/j.hal.2017.04.007 (2017). Yan, X. et al. Climate warming and cyanobacteria blooms: Looks at their relationships from a new perspective. Water Research 125, 449–457, doi: https://doi.org/10.1016/j.watres.2017.09.008 (2017). Wilhelm Steven, W., Bullerjahn George, S. & McKay, R. M. L. 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What compound inside biocoagulants/bioflocculants is contributing the most to the coagulation and flocculation processes? Science of The Total Environment 806, 150902, doi: https://doi.org/10.1016/j.scitotenv.2021.150902 (2022). Rice, E. W., Bridgewater, L., Association, A. P. H., Association, A. W. W. & Federation, W. E. Standard Methods for the Examination of Water and Wastewater . (American Public Health Association, 2012). Bennett, A. & Bogorad, L. Complementary chromatic adaptation in a filamentous blue-green alga. The Journal of cell biology 58, 419 (1973). MacQueen, J. in Proceedings of the fifth Berkeley symposium on mathematical statistics and probability. 281–297 (Oakland, CA, USA). Galperin, M. Y., Makarova, K. S., Wolf, Y. I. & Koonin, E. V. Expanded microbial genome coverage and improved protein family annotation in the COG database. Nucleic Acids Res 43, D261-269, doi: 10.1093/nar/gku1223 (2015). Kang, J. et al. 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Li, M. et al. Type II Toxin–Antitoxin Systems in Pseudomonas aeruginosa. Toxins 15, 164 (2023). Page, R. & Peti, W. Toxin-antitoxin systems in bacterial growth arrest and persistence. Nat Chem Biol 12, 208–214, doi: 10.1038/nchembio.2044 (2016). Zhang, S.-P. et al. Type II toxin–antitoxin system in bacteria: activation, function, and mode of action. Biophysics Reports 6, 68–79, doi: 10.1007/s41048-020-00109-8 (2020). Huang, Y., Pan, H., Liu, H., Xi, Y. & Ren, D. Characteristics of growth and microcystin production of Microcystis aeruginosa exposed to low concentrations of naphthalene and phenanthrene under different pH values. Toxicon 169, 103–108, doi: https://doi.org/10.1016/j.toxicon.2019.09.004 (2019). Zhang, Y., Tang, C. Y. & Li, G. The role of hydrodynamic conditions and pH on algal-rich water fouling of ultrafiltration. Water Res 46, 4783–4789, doi: 10.1016/j.watres.2012.06.020 (2012). Antonacci, A. et al. Photosystem-II D1 protein mutants of Chlamydomonas reinhardtii in relation to metabolic rewiring and remodelling of H-bond network at Q(B) site. Sci Rep 8, 14745, doi: 10.1038/s41598-018-33146-y (2018). Hong, Y., Huang, J. J. & Hu, H. Y. Effects of a novel allelochemical ethyl 2-methyl acetoacetate (EMA) on the ultrastructure and pigment composition of cyanobacterium Microcystis aeruginosa. Bull Environ Contam Toxicol 83, 502–508, doi: 10.1007/s00128-009-9795-4 (2009). Moura, K. A. F. et al. Physiological and thylakoid ultrastructural changes in cyanobacteria in response to toxic manganese concentrations. Ecotoxicology 28, 1009–1021, doi: 10.1007/s10646-019-02098-y (2019). Mullineaux, C. W. & Liu, L. N. Membrane Dynamics in Phototrophic Bacteria. Annu Rev Microbiol 74, 633–654, doi: 10.1146/annurev-micro-020518-120134 (2020). Shimakawa, G. et al. Diverse strategies of O(2) usage for preventing photo-oxidative damage under CO(2) limitation during algal photosynthesis. Sci Rep 7, 41022, doi: 10.1038/srep41022 (2017). Moore, K. A. et al. Mechanical regulation of photosynthesis in cyanobacteria. Nat Microbiol 5, 757–767, doi: 10.1038/s41564-020-0684-2 (2020). Luo, Y. et al. The Love and Hate Relationship between T5SS and Other Secretion Systems in Bacteria. Int J Mol Sci 25, doi: 10.3390/ijms25010281 (2023). Kanonenberg, K., Spitz, O., Erenburg, I. N., Beer, T. & Schmitt, L. Type I secretion system-it takes three and a substrate. FEMS Microbiol Lett 365, doi: 10.1093/femsle/fny094 (2018). Hayashi, K. et al. AcrB-AcrA Fusion Proteins That Act as Multidrug Efflux Transporters. J Bacteriol 198, 332–342, doi: 10.1128/jb.00587-15 (2016). Naskar, S., Hohl, M., Tassinari, M. & Low, H. H. The structure and mechanism of the bacterial type II secretion system. Mol Microbiol 115, 412–424, doi: 10.1111/mmi.14664 (2021). Korotkov, K. V. & Sandkvist, M. Architecture, Function, and Substrates of the Type II Secretion System. EcoSal Plus 8, doi: 10.1128/ecosalplus.ESP-0034-2018 (2019). Fei, Q., Gao, E. B., Liu, B., Wei, Y. & Ning, D. A Toxin-Antitoxin System VapBC15 from Synechocystis sp. PCC 6803 Shows Distinct Regulatory Features. Genes (Basel) 9, doi: 10.3390/genes9040173 (2018). Frees, D. et al. Clp ATPases are required for stress tolerance, intracellular replication and biofilm formation in Staphylococcus aureus. Molecular Microbiology 54, 1445–1462, doi: https://doi.org/10.1111/j.1365-2958.2004.04368.x (2004). Heaton, B. E., Herrou, J., Blackwell, A. E., Wysocki, V. H. & Crosson, S. Molecular structure and function of the novel BrnT/BrnA toxin-antitoxin system of Brucella abortus. J Biol Chem 287, 12098–12110, doi: 10.1074/jbc.M111.332163 (2012). Thomet, M., Trautwetter, A., Ermel, G. & Blanco, C. Characterization of HicAB toxin-antitoxin module of Sinorhizobium meliloti. BMC Microbiol 19, 10, doi: 10.1186/s12866-018-1382-6 (2019). Additional Declarations There is NO Competing Interest. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5278810","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":371626015,"identity":"cd6a1c34-30d1-4542-b277-453254e9e760","order_by":0,"name":"Seong-il Eyun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAr0lEQVRIiWNgGAWjYLCCD1CasYFYHYwzSNbCzEOSFn6JHLPHNjV2iQ3shx8wztxDhBbJGTnmxjnHkhMbeNIMGDc8I0KLwY0cM+ncBubEBoYcBsYHB4jQYg/SYtlQn9jA/4ZILQZAv0gzNhxObJAA2rKBGC0SZ56VSfYcO27cJvHM4OAMYrTwtydvk/hRUy3bz5/88GEPMVoYBBIgNBsQE6UBaA2R6kbBKBgFo2AEAwDQbjN5m2a8cgAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-4687-1066","institution":"Chung-Ang University","correspondingAuthor":true,"prefix":"","firstName":"Seong-il","middleName":"","lastName":"Eyun","suffix":""},{"id":371626016,"identity":"ea4fb884-7ea8-4741-8f4f-482c780d3968","order_by":1,"name":"Eun-jeong Kim","email":"","orcid":"https://orcid.org/0000-0003-3322-9314","institution":"Chung-Ang University","correspondingAuthor":false,"prefix":"","firstName":"Eun-jeong","middleName":"","lastName":"Kim","suffix":""},{"id":371626017,"identity":"e6b70ea5-7f40-4f43-abb8-2a1ecab4f8ae","order_by":2,"name":"Yeon-jeong Park","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yeon-jeong","middleName":"","lastName":"Park","suffix":""},{"id":371626018,"identity":"3746d007-c17a-4600-a573-2c19aa8c0713","order_by":3,"name":"Jae Hak Lee","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Jae","middleName":"Hak","lastName":"Lee","suffix":""},{"id":371626019,"identity":"b920d833-9289-4b9f-a44f-12701debffd2","order_by":4,"name":"Heesuk Lee","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Heesuk","middleName":"","lastName":"Lee","suffix":""},{"id":371626020,"identity":"531a7a2e-4756-4b16-832a-9682ad9f2c0a","order_by":5,"name":"Jihye Yang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Jihye","middleName":"","lastName":"Yang","suffix":""},{"id":371626021,"identity":"a31208ab-a29e-481e-acc8-f246654da85d","order_by":6,"name":"Han Soon Kim","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Han","middleName":"Soon","lastName":"Kim","suffix":""}],"badges":[],"createdAt":"2024-10-17 01:20:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5278810/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5278810/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":68546345,"identity":"0a771806-070c-4947-a379-5e2565e6d3ff","added_by":"auto","created_at":"2024-11-08 11:41:23","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":436365,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of the experimental process. Step 1: Cell culture and PAC treatment. Step 2: Chemical and transcriptome analyses.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5278810/v1/1db89b030981e033fe9152c3.jpeg"},{"id":68546347,"identity":"db6416b3-ae29-470c-a664-a73e9f1e4f9b","added_by":"auto","created_at":"2024-11-08 11:41:23","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":179332,"visible":true,"origin":"","legend":"\u003cp\u003eGrowth curves and photosynthetic pigment analysis of \u003cem\u003eMicrocystis aeruginosa\u003c/em\u003e. A) Growth curves for the control, low PAC exposure, and high PAC exposure groups over eight days. The doubling time (\u003cem\u003edt\u003c/em\u003e) was calculated to be 3.75 days and 4.25 days for the control and low PAC treatment, respectively. B) Microscopic images showing phenotypic changes to the \u003cem\u003eMicrocystis\u003c/em\u003e cells. C–E) Chemical analysis of pH, chlorophyll-\u003cem\u003ea\u003c/em\u003e, and phycocyanin over three days.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5278810/v1/be2f47dfc6c7008e08ffba5d.jpeg"},{"id":68546351,"identity":"1408394f-ed81-44dd-895e-e5ed406c786d","added_by":"auto","created_at":"2024-11-08 11:41:23","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":202260,"visible":true,"origin":"","legend":"\u003cp\u003eTranscriptomic dynamics and pathway enrichment analysis in response to low PAC exposure in \u003cem\u003eM. aeruginosa\u003c/em\u003e. A) Cluster analysis of DEGs using the \u003cem\u003ek\u003c/em\u003e-means algorithm. Only genes with a \u003cem\u003ep\u003c/em\u003e-value of less than 0.05 and a log\u003csub\u003e2\u003c/sub\u003e fold change of [fc] ≥ 1 were included in the analysis. On the \u003cem\u003ex\u003c/em\u003e-axis, each time point represents a comparison of the low PAC treatment vs. the control, while the log\u003csub\u003e2 \u003c/sub\u003efold change in gene expression levels is presented on the \u003cem\u003ey\u003c/em\u003e-axis. B) Functional enrichment analysis associated with Clusters A and D, which contain 53 and 28 genes, respectively. The cut-off criteria include a false discovery ratio (FDR) threshold of less than 0.05 and more than five genes.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5278810/v1/a7f7cbea16d7f9e16c5e92bb.jpeg"},{"id":68547684,"identity":"1f740d49-daca-4564-8b30-b0d7c9231e63","added_by":"auto","created_at":"2024-11-08 11:57:23","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":554716,"visible":true,"origin":"","legend":"\u003cp\u003eKEGG pathway modules for bacterial secretion systems and photosynthesis. The KEGG pathway map for bacterial type I and type II secretion systems is derived from map03070, and photosynthesis and photosynthesis antenna proteins are derived from map00195 and map00196, respectively.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5278810/v1/d3ded41386c1d01ab539dc62.jpeg"},{"id":68546346,"identity":"720d239a-467d-4c37-93ff-d49c542478dd","added_by":"auto","created_at":"2024-11-08 11:41:23","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":198001,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential expression analysis under high PAC exposure for 3 h. A) Venn diagram of unique and overlapping DEGs for low and high PAC exposure. B) Volcano plot depicting upregulated genes in red and downregulated genes in blue. The numbers for each color represent only DEGs with a \u003cem\u003ep\u003c/em\u003e-value of \u0026lt; 0.05 and a log\u003csub\u003e2\u003c/sub\u003e fold change of [fc] ≥ 1. C) Gene enrichment under high PAC exposure. The cut-off criteria include an FDR threshold of less than 0.05. D) Functional classification of clusters of orthologous groups (COGs). The plus symbol (+) indicates unique upregulated genes with a frequency greater than 5. Both upregulated and downregulated classes with a frequency greater than 5 and a frequency difference of more than 2.5 times are marked with * and **, respectively. COG classes; C: Energy production and conversion, D: Cell cycle control and mitosis, E: Amino acid metabolism and transport, F: Nucleotide metabolism and transport, G: Carbohydrate metabolism and transport, H: Coenzyme metabolism, J: Translation, K: Transcription, L: Replication and repair, M: Cell wall biogenesis, O: Post-translational modification, protein turnover, and chaperone functions, P: Inorganic ion transport and metabolism, Q: Secondary structure, T: Signal transduction, U: Intracellular trafficking and secretion, V: Defense mechanisms, X: Mobilome, R: General functional prediction only, S: Function unknown.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5278810/v1/ae3668c10a5b6111fab9b453.jpeg"},{"id":68546665,"identity":"f42673ac-c1e8-4522-820e-0cabc1e813b0","added_by":"auto","created_at":"2024-11-08 11:49:23","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":274383,"visible":true,"origin":"","legend":"\u003cp\u003eEight superfamilies of type II toxin‑antitoxin (TA) systems significantly expressed in response to high PAC exposure. The left panel displays a model of type II TA systems, represented in yellow and orange, respectively. This model is derived from \u003ca href=\"#_ENREF_36\" title=\"Li, 2023 #1156\"\u003e\u003csup\u003e36\u003c/sup\u003e\u003c/a\u003e\u003csup\u003e,\u003c/sup\u003e\u003ca href=\"#_ENREF_37\" title=\"Page, 2016 #1113\"\u003e\u003csup\u003e37\u003c/sup\u003e\u003c/a\u003e. The right panel lists the significantly expressed genes along with their transcript levels. The green up-directed arrows indicate upregulated fold changes, while the red down-directed arrows represent downregulated fold changes. The gene (B1L04_RS14120) in the box indicates the levels of Clp protease expression.\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5278810/v1/fb8a0a172dc255cd45f67d8c.jpeg"},{"id":76842233,"identity":"a66ab8b5-2b3f-4f50-955a-f57c879a9c6e","added_by":"auto","created_at":"2025-02-21 10:21:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2663819,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5278810/v1/1c90c48e-4ba9-4f0c-b4ac-1c268573ec38.pdf"},{"id":68546667,"identity":"4c88bf74-acdc-440e-8496-44f5781bbd02","added_by":"auto","created_at":"2024-11-08 11:49:23","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":873377,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"R0Supplymentarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-5278810/v1/e4319974805843209702e1f7.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Cellular response in the resilience of Microcystis aeruginosa under polyaluminum chloride exposure","fulltext":[{"header":"Highlights","content":"\u003cp\u003e\u0026bull; PAC chemical stress targeted photosystem II antenna proteins in \u003cem\u003eMicrocystis\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u0026bull; Bacterial secretion systems enhanced stress resilience with low PAC levels.\u003c/p\u003e\n\u003cp\u003e\u0026bull; Upregulated transposases were observed with high PAC levels.\u003c/p\u003e\n\u003cp\u003e\u0026bull; PAC stress triggered the activation of toxin\u0026ndash;antitoxin systems.\u003c/p\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eIn recent decades, harmful cyanobacterial blooms have increased in frequency, intensity, and duration, primarily driven by eutrophication and climate change \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Severe cyanobacterial blooms during summer can contaminate drinking and recreational water sources, reducing the water quality \u003csup\u003e\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. The removal of cyanobacterial biomass from water bodies used for drinking water and from treatment plants is thus a major challenge \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. In this context, flocculation is considered an effective strategy for managing microalgal biomass in deep and stratified lakes and water treatment plants \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. For example, a microbial bio-flocculation efficiency of \u0026gt;\u0026thinsp;98% has been achieved with freshwater microalgae at both a pilot scale and a bench scale \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePolyaluminum chloride (PAC) is an inorganic flocculant that is commonly used to eliminate \u003cem\u003eMicrocystis\u003c/em\u003e biomass in eutrophic lakes and water treatment facilities \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Laboratory analysis has also revealed that PAC can most effectively remove \u003cem\u003eMicrocystis\u003c/em\u003e biomass using nano-Fe\u003csub\u003e3\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e particles as a coagulant aid (Arruda et al., 2021). However, it has been demonstrated that, despite undergoing chemical flocculation, some cells exposed to PAC can survive and remain suspended at the surface of eutrophic lakes, potentially reblooming in high-temperature conditions \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. In another recent study, cyanobacterial chlorophyll-\u003cem\u003ea\u003c/em\u003e was reported to be reduced by 90% after PAC treatment, but elevated cyanobacterial concentrations were observed one week later \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. It is thus important to understand the molecular mechanisms by which cells develop tolerance to chemical exposure, but current understanding of the various biological and physiological processes involved in resisting chemical stress remains limited.\u003c/p\u003e \u003cp\u003eTranscriptomics has proven to be an invaluable tool for linking physiology with ecology in aquatic microbes. Examples of this include an analysis of the temporal dynamics in the global transcriptomic patterns of \u003cem\u003eMicrocystis\u003c/em\u003e \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e and the analysis of early RNA-seq data to determine the specific effects of nutrient limitations, including nitrogen, phosphate, and urea, on microcystin in \u003cem\u003eMicrocystis\u003c/em\u003e \u003csup\u003e\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. This advanced sequencing technology has also allowed the analysis of transcriptional dynamics in response to the bacterial community or phage infection in \u003cem\u003eMicrocystis\u003c/em\u003e blooms \u003csup\u003e\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. More recent RNA-seq studies have focused on chemical, drug, or nano-plastic exposure to understand biological processes for biotechnological, toxicological, and medical applications using \u003cem\u003eMicrocystis\u003c/em\u003e cells \u003csup\u003e\u003cspan additionalcitationids=\"CR21 CR22\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn order to address the re-emergence of \u003cem\u003eMicrocystis\u003c/em\u003e blooms following PAC treatment in the field, we employed RNA sequencing technology to identify intracellular tolerance mechanisms during the initial and post-reaction phases following PAC exposure in \u003cem\u003eM. aeruginosa\u003c/em\u003e. To the best of our knowledge, this is the first study reporting transcript dynamics in response to PAC treatment. We observed changes in photosynthetic antenna pigments within 48 h of low PAC exposure, resulting in a cell generation time that was 12 h longer after eight days. Under low PAC exposure, the cell numbers initially reduced by only 20%, with phenotypic growth returning to normal after three days; however, long-term observations revealed a 50% reduction in cell numbers by the 23rd day (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Under high PAC exposure, all of the cells were dead by the 23rd day. This experiment demonstrates that cells exposed to PAC can regrow and rebloom after one week under appropriate growth conditions in the field. We also examined the biological mechanisms that contribute to the resilience of \u003cem\u003eMicrocystis\u003c/em\u003e cells in response to PAC exposure in laboratory-scale experiments.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Culture conditions and frozen cells\u003c/h2\u003e \u003cp\u003eThe \u003cem\u003eM. aeruginosa\u003c/em\u003e strain KW (KCTC 18162P) was obtained from the Korean Collection for Type Cultures \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. This strain was grown in a 500 ml flask with 300 ml of BG-11 medium (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The cells were cultured under a light intensity of 30\u0026thinsp;\u0026plusmn;\u0026thinsp;1 \u0026micro;mol m\u003csup\u003e-\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e s\u003csup\u003e-\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e at 25℃ using a shaker. The strain was precultured for one week and collected using centrifugation at 4000 rpm for 5 min. The cells were washed three times with fresh BG-11 and then resuspended in the same medium. The cells were reinoculated at a density of 6 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells/ml into either a 40 ppm or 400 ppm PAC solution, representing low and high PAC exposure, respectively. After incubation for 3, 6, and 24 h, each sample was washed and centrifuged, and the supernatant was removed. The pellets were immediately frozen in liquid nitrogen and stored in a freezer at \u0026minus;\u0026thinsp;70℃. RNA isolation was conducted within one week, and the samples were sent for RNA sequencing.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. PAC solutions\u003c/h2\u003e \u003cp\u003ePAC is an inorganic polymer flocculant commonly used for microalgal coagulation in the field and wastewater treatment as an EPA standard \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Microalgae in a colloidal state in water move via electrostatic repulsion. The addition of a coagulant with a charge opposite to that of the microalgal cell wall consequently leads to flocculation \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. The stock PAC solution was prepared in distilled water and stored at room temperature. Two flasks were dosed with a concentration of 40 mg/L and 400 mg/L from the PAC stock solution.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Growth curves and doubling time calculation\u003c/h2\u003e \u003cp\u003eThree flasks, including a control with no treatment, low PAC treatment, and high PAC treatment, were incubated for 3 h, 6 h, 24 h, 1 day, 2 days, 3 days, and 8 days (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Following incubation, these samples were stained with Lugol\u0026rsquo;s iodine, and the cells were counted using a Hemocytometer C-Chip (NCYTO\u003csup\u003e\u0026reg;\u003c/sup\u003e), with the counts repeated 15 times. The average cell number was used for growth curve analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The doubling time for the cultures was calculated using the growth rate (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv id=\"Equa\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\text{G}\\text{r}\\text{o}\\text{w}\\text{t}\\text{h}\\:\\text{r}\\text{a}\\text{t}\\text{e}\\:\\left(r\\right)=\\frac{\\text{I}\\text{n}\\:\\left(N\\right(t)\\:/\\:N0)}{\\:t}$$\u003c/div\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003ewhere \u003cem\u003eN\u003c/em\u003e\u003csub\u003e(\u003cem\u003et\u003c/em\u003e)\u003c/sub\u003e is the number of cells at time \u003cem\u003et\u003c/em\u003e, \u003cem\u003eN\u003c/em\u003e\u003csub\u003e\u003cem\u003e0\u003c/em\u003e\u003c/sub\u003e is the number of cells at time 0, and \u003cem\u003et\u003c/em\u003e is the time (h).\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:\\text{D}\\text{o}\\text{u}\\text{b}\\text{l}\\text{i}\\text{n}\\text{g}\\:\\text{t}\\text{i}\\text{m}\\text{e}\\:\\left(dt\\right)=\\frac{\\text{I}\\text{n}\\:\\left(2\\right)}{r}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eIn addition, microscopic images were taken to observe phenotypic changes such as cell pigment fading, cell wall rupture, and apoptosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Photosynthetic pigment content\u003c/h2\u003e \u003cp\u003eAfter the 3-h, 6-h, 24-h, 1-day, 2-day, and 3-day incubation periods (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), the samples were centrifuged for 10 min at 4000 rpm, and the pellets were extracted with 1 ml of 90% acetone. Chlorophyll-\u003cem\u003ea\u003c/em\u003e levels were measured based on the optical density at 750, 663, 645, and 630 nm, with 90% acetone used as a blank \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. PC was extracted via freezing at \u0026minus;\u0026thinsp;20℃ and thawing at room temperature for four cycles and then measured based on the optical density at 615 and 652 nm \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. All photosynthetic pigments were quantified using a spectrophotometer (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e2. 5. Illumina sequencing and transcriptome analysis\u003c/h3\u003e\n\u003cp\u003eThe frozen pellets from Section \u003cspan refid=\"Sec3\" class=\"InternalRef\"\u003e2.1\u003c/span\u003e were used for total RNA isolation using a Maxwell 16-cell LEV RNA purification kit for plants, following the manufacturer\u0026rsquo;s instructions (Promega). The library was prepared according to Illumina\u0026rsquo;s specifications. The quality and integrity of the RNA were determined using an Agilent Technologies 2100 Bioanalyzer (Agilent, Germany). The samples were sequenced on an Illumina NovaSeq 6000 Sequencing Platform (Table S2), and the clean reads were mapped to \u003cem\u003eM. aeruginosa\u003c/em\u003e KW as a reference genome \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Transcript abundance was normalized in terms of the fragment per kilobase of transcript per million mapped reads (FPKM) and the normalized log2 (FPKM\u0026thinsp;+\u0026thinsp;0.1) values were used (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDifferential expression analysis was conducted using the HTseq packages to compare between samples. A log2 fold change of |fc| \u0026ge; 1 and a \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were set as the criteria for identifying statistically significant changes in gene expression levels. Time series analysis of the transcriptional response was conducted using \u003cem\u003ek\u003c/em\u003e-means cluster analysis \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. This method partitions fold-change patterns into \u003cem\u003ek\u003c/em\u003e clusters, with each fold-change time series added to the cluster with the nearest mean and the clusters iteratively refined. This form of analysis has been used to identify dynamic expression patterns for large numbers of genes. Clusters of orthologous groups (COGs) of proteins are classified into different functional categories based on their predicted biological roles, thus helping to understand the functional roles and biological processes of genes and proteins \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Additionally, a hypergeometric distribution was used to determine if any differentially expressed genes (DEGs) were significantly enriched in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. For gene enrichment analysis, we employed the online ShinyGO 0.80 tool with \u003cem\u003eM. aeruginosa\u003c/em\u003e NIES-843 as the reference organism (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bioinformatics.sdstate.edu/go/\u003c/span\u003e\u003cspan address=\"http://bioinformatics.sdstate.edu/go/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). We integrated the ggplot2 package into the R studio environment to produce volcano plots and Venn diagrams and to visualize the KEGG enrichment analysis.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Effects of PAC on the growth of M. aeruginosa\u003c/h2\u003e \u003cp\u003eAfter eight days of PAC exposure, the \u003cem\u003eMicrocystis\u003c/em\u003e cell numbers in the control, low PAC exposure, and high PAC exposure groups were 3.2 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cell/ml, 2.6 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cell/ml, and 0.08 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cell/ml, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), representing an 18.75% and 97.5% reduction under low and high PAC exposure, respectively, compared to the control. Based on the growth curves, the doubling time was calculated to be 3.75 days for the control and 4.25 days for low PAC exposure. Under high PAC exposure, phenotypic photographic images revealed a larger cell size after 3 h and disrupted cells after 3 days. Conversely, under low PAC exposure, the \u003cem\u003eMicrocystis\u003c/em\u003e cells grew well and were similar in appearance to those in the control after 24 h (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). A lower pH was measured for the high PAC treatment, while the other two groups were not considerably different (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). The trends in the levels of chlorophyll-\u003cem\u003ea\u003c/em\u003e and phycocyanin (PC) were consistent with the growth curves (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). After three days, the PC concentration fell by 11.9% (1.11 \u0026times; 10\u003csup\u003e2\u003c/sup\u003e mg/m\u003csup\u003e3\u003c/sup\u003e) and 88.1% (8.21 \u0026times; 10\u003csup\u003e2\u003c/sup\u003e mg/m\u003csup\u003e3\u003c/sup\u003e) under low and high PAC exposure compared to the control, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). The cells exposed to high PAC levels entered the death stage after three days.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 DEGs and gene enrichment under low PAC exposure\u003c/h2\u003e \u003cp\u003eTo understand how \u003cem\u003eM. aeruginosa\u003c/em\u003e gene expression responded to low PAC exposure over time, we exposed the cells to low PAC for 3 h, 6 h, and 24 h and identified DEGs that appeared in at least two samples (Fig. S2A). Volcano plots were used to visualize the upregulated and downregulated genes for each sample, with a total of 358 DEGs identified (Fig. S2B). In terms of upregulated genes, there were 111 DEGs for 3 h after initial exposure, compared to only 38 after 24 h. In contrast, the number of downregulated genes after 24 h (90 DEGs) was higher than that during the initial 3 h (23 DEGs). Overall, a total of 264 unique DEGs were identified during low PAC exposure after 3 h, 6 h, and 24 h (Fig. S2C).\u003c/p\u003e \u003cp\u003eWe also conducted cluster analysis of the DEGs using the \u003cem\u003ek\u003c/em\u003e-means algorithm. In this analysis, half of the 264 DEGs were excluded because they had domains of unknown function, were annotated as hypothetical proteins, or were pseudogenes. The expression patterns of 84% (111 out of 132 DEGs) of the retained genes were categorized into Clusters A to D (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and S3). Nearly half of the functionally annotated genes assigned to Cluster A exhibited elevated expression levels in the early stages of exposure, followed by lower expression levels in the later stages. Cluster D also exhibited reduced expression levels in the later stages, but their expression levels were also slightly lower early in the exposure period (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Clusters B and C displayed only slight changes in their gene expression dynamics. Furthermore, we analyzed the gene enrichment of Clusters A and D and set a cut-off for statistical significance at a false discovery rate (FDR) of less than 0.05. In each cluster, we identified the top 8 KEGG pathways that were the most enriched under low PAC exposure (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). In Cluster A, the majority of the gene enrichment was related to fatty acid biogenesis and the secretion system, while photosynthesis pathways were significantly enriched in Cluster D.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 KEGG metabolic pathways under low PAC exposure\u003c/h2\u003e \u003cp\u003eThe results from the gene cluster and enrichment analyses presented in Section \u003cspan refid=\"Sec10\" class=\"InternalRef\"\u003e3.2\u003c/span\u003e revealed that DEGs associated with the bacterial secretion system and photosynthesis pathway were downregulated after 24 h of PAC exposure. In Cluster A, the type I and II bacterial secretion systems were significantly upregulated in the early stages of exposure (i.e., after 3 h; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Most of the enriched genes assigned to the KEGG pathway for the HlyD secretion protein and fatty acid biosynthesis were listed with their expression levels in the right panel of Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA. Interestingly, HlyD belongs to the membrane fusion protein (MFP) family, and cell membranes are composed of fatty acids \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. After 24 h of PAC exposure, photosystems I and II (PSI and PSII, respectively), which were part of Cluster D, were downregulated compared to the control (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). In particular, it is notable that PAC exposure significantly affected PSII antenna proteins located on the surface of the thylakoid membrane \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Functional analysis of high PAC exposure\u003c/h2\u003e \u003cp\u003eTo investigate their response to high levels of chemical stimuli, \u003cem\u003eMicrocystis\u003c/em\u003e cells were exposed to high levels of PAC and subjected to RNA sequencing. The DEGs were screened based on a log\u003csub\u003e2\u003c/sub\u003e fold change of |fc| \u0026ge; 1 and a \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Under high PAC exposure, a total of 302 DEGs were identified, with 119 genes upregulated and 183 genes downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Gene enrichment analysis revealed that upregulated DEGs associated with putative transposase and ribonuclease Z/hydroxyacylglutathione hydrolase (Z/HAGH)-like proteins were enriched in KEGG pathways shown in the top panel of Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC. Interestingly, the high levels of PAC exposure promoted the pathway related to detoxification, specifically involving ribonuclease Z/HAGH-like proteins to remove toxic metabolites \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Furthermore, enriched pathways related to photosynthesis were downregulated, which was consistent with the results for low PAC exposure in the bottom panel of Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC. Functional analysis of the COGs revealed a distinct increase in the mobilome (prophages and transposons; category X, indicated by a red plus sign), which was consistent with the upregulation of enriched DEGs observed under high PAC exposure in the top panel of Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). Functional analysis also revealed a decrease in energy production and conversion (category C, **) and cell wall/membrane/envelope biogenesis (category M, **). In contrast, the upregulated categories included post-translational modification, protein turnover, and chaperone functions (category O, *) and defense mechanisms (category V, *).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSurprisingly, high PAC exposure enhanced the expression of toxin\u0026ndash;antitoxin (TA) systems, a key component of prokaryotic defense mechanisms (left panel of Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The degradation of the antitoxin occurs with the production of protease, and a stable toxin leads to cell death or the suppression of growth \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Both the antitoxin and/or TA complex have the ability to negatively regulate their own transcription by identifying and binding to palindromic sequences within their operators \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. The BrnA-BrnT and HicA-HicB TA systems were identified in the initial stage of high PAC exposure. The toxin components of the TA module included ParE/RelE-like and MazF/Pemk-like proteins, while the antitoxin components included MqsA-like, CcdA-like, and prevent-host-death-like proteins (right panel of Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The upregulated antitoxin genes were associated with neutralizing toxins, stress response modulation, and survival mechanisms \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Furthermore, the Clp protease ATP-binding subunit ClpA was upregulated more than 2.2-fold compared to low PAC exposure (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eChemical remediation is a key method for controlling biomass from microalgal blooms. In the present study, PAC was found to inhibit the growth and development of \u003cem\u003eMicrocystis\u003c/em\u003e cells by disrupting photosynthesis-related pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). The levels of PC, which is responsible for absorbing light energy in cyanobacteria, were reduced more than those of chlorophyll-\u003cem\u003ea\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). In addition, the higher expression of pigment-producing genes was correlated with greater pigment production, indicating that gene expression directly influences pigment levels. This evidence helps to explain how genetic regulation affects pigment synthesis at a molecular level (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, Cluster D). Exposure to low levels of PAC resulted in a growth curve similar to the normal pattern, though it caused an approximate 12 h delay in the doubling time compared to the control (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The observed phenotype of cells exposed to low PAC, including gas vesicles resembling those of the control cells, indirectly indicated normal growth conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). However, cells exposed to high levels of PAC exhibited suppressed growth, fewer gas vesicles, and damage to the cell wall after three days of exposure (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and B). This is in line with past research, which has shown that high PAC concentrations reduce the pH, which can negatively affect growth, reduce photosynthetic efficiency, and disrupt cell membrane integrity \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Under high PAC exposure, all of the cells were dead by day 23 (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). In contrast, under low PAC exposure, cell numbers initially decreased by only 20.8% after 8 days, but long-term observations revealed a 50.3% reduction after 23 days (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Although this experiment has limitations in reflecting actual environmental fluctuations due to the limited nutrients and constant light intensity, the findings support previous observations that cyanobacteria regrow after PAC treatment in the field \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Photosynthetic damage caused by organic chemical stress\u003c/h2\u003e \u003cp\u003eTo identify the genes associated with the observed cell growth dynamics, we analyzed RNA sequencing data to link phenotypic changes with transcriptomic dynamics. Many organic chemicals that target PSII directly bind to the D1 protein of PSII, blocking electron transport and preventing the conversion of light energy into chemical energy \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. For example, the response of \u003cem\u003eMicrocystis\u003c/em\u003e to allelochemical ethyl 2-methyl acetoacetate (EMA) indicates damage to the photosynthetic apparatus, with the degradation of allophycocyanin (AP), phycoerythrin (PE), and carotenoid, while chlorophyll-\u003cem\u003ea\u003c/em\u003e levels increased \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this study, the exposure of \u003cem\u003eM. aeruginosa\u003c/em\u003e to PAC can significantly reduce its ability to convert light energy into chemical energy by directly targeting PSII systems, including antenna proteins such as AP, pycocyanin (PC)/phycocerythrocyanin (PEC). Photosynthesis antenna proteins were enriched (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB), while AP-related genes ApcA\u0026ndash;D and AP/PEC-related genes CpcA\u0026ndash;D and CpcG were downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Some organic pollutants also interfere with the biosynthesis of chlorophyll, the primary pigment involved in photosynthesis \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. In the present study, lower PC content led to reduced light absorption and energy capture (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and E). The thylakoid membrane also houses the components of the photosynthetic electron transport chain \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. The enrichment of electron transport and thylakoid membrane-related genes suggests potential negative effects on photosynthesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eOrganic chemicals can also generate reactive oxygen species (ROS) and oxidative stress, damaging cellular components \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. This study revealed that the oxidation\u0026ndash;reduction process was enriched (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). In addition, some organic chemicals interfere with photosynthetic electron transport by accepting electrons from PSI and transferring them to molecular oxygen, generating superoxide radicals and causing oxidative damage \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. PAC triggered the reduction of PSI, including PsaA/D/E/I/J/K/L, and the cytochrome b6/f complex-related gene PetM was enriched (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). As a result, most PSII antenna proteins and PS I-related genes were downregulated in gene expression and were enriched in the photosynthesis pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). PAC exposure thus potentially affects photosynthetic efficiency, leading to a reduction in the growth of \u003cem\u003eMicrocystis\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Bacterial type I/II secretion systems in minimizing intracellular damage\u003c/h2\u003e \u003cp\u003eBacteria secretion systems play a vital role in survival under stress conditions by secreting proteins and enzymes that can neutralize harmful substances or repair damage \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. The type I secretion system, which consists of an MFP, an ATP-binding cassette (ABC) transporter, and an outer membrane protein (OMP), directly transports proteins from the cytoplasm to the extracellular space without a periplasmic intermediate \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. In this study, the MFP (HlyD; B1L_RS28235) and ABC transporter (HlyB; B1L04_RS28230) were significantly enriched in gene expression, indicating activation of the type I secretion system in response to PAC (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). In addition, AcrAB-TolC in \u003cem\u003eE. coli\u003c/em\u003e is an intrinsic RND-type multidrug efflux transporter that functions as a tripartite complex of the inner membrane transporter (IMP) AcrB, the outer membrane channel TolC, and the adaptor protein AcrA \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. The upregulated expression of efflux pump subunits AcrA (B1L04_RS20330) and AcrB (B1L04_RS20325) was also observed in the present study (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eThe type II secretion system is a more complex, two-step process that first translocates proteins into the periplasm via the Sec or Tat pathway, followed by their secretion across the outer membrane \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. The type II secretion system secretes enzymes such as proteases, lipases, and nucleases that can degrade extracellular toxins before they can cause intracellular damage \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. IMP GspH, which is related to the type II secretion system, was also upregulated and enriched in the cellular pathways in this study (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Therefore, in the early stages of low PAC exposure, the activated type I and II secretion systems served as an adequate defense mechanism (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and B).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Toxin\u0026ndash;antitoxin systems as a stress response in \u003cem\u003eM. aeruginosa\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eTA systems in cyanobacteria are an important mechanism for managing stress by modulating cell growth, inducing dormancy, and facilitating biofilm formation \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. In a TA system, the toxin is a stable protein that can interfere with vital cellular processes such as DNA replication, RNA stability, or protein synthesis, regulating cell growth or killing the cell. With exposure to high levels of PAC, the activation of the toxin may lead to programmed cell death, releasing nutrients from dying cells that can be used by surviving cells. The antitoxin is typically less stable and binds to the toxin, neutralizing its activity, and is regulated by environmental conditions \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this study, eight superfamilies of type II TA systems were significantly expressed in response to high PAC exposure (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Both BrnT-BrnA and HicA-HicB TA systems were identified, while other TA systems were only recognized as either toxin or antitoxin-like families (right panel of Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Previous research has reported that the transcription of BrnT-BrnA is upregulated in the presence of stressors such as low pH and antibiotics \u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. Similarly, the HicA-HicB module is involved in virulence in bacteria and adaptation to extracellular stresses in \u003cem\u003eE. coli\u003c/em\u003e \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. The ParD-ParE TA system for protection against antibiotics has been characterized in plasmid RK2 as a plasmid stabilization element \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. In addition, the toxin MzxF neutralizes the activity of MaxE, which is degraded more rapidly under stress conditions \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, while Clp ATPases (K03696), which are a component of TA modules, are required for stress tolerance \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Additionally, many TA systems that were not detected under high PAC exposure were expressed in response to low PAC exposure (Table S3). However, it is important to note that the mechanisms of action and biological roles of bacterial TA systems can vary depending on the bacterial species. Further research into these systems can thus help to clarify the survival strategies of cyanobacteria and their ecological impact.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eTo understand the stress resilience of \u003cem\u003eM. aeruginosa\u003c/em\u003e in response to the organic coagulant PAC, the present study integrated phenotypic phenomena with transcriptome dynamics. In this study, phenotypic analysis revealed lower growth rates and a reduction in photosynthetic pigment levels, while transcriptomic analysis identified upregulated genes, including those involved in the secretion system and fatty acid biogenesis. In particular, in the early stages of exposure, exporting toxic compounds and secreting protective enzymes helped to minimize intracellular damage. Fatty acids released from cell membrane phospholipids were also involved in \u003cem\u003eMicrocystis\u003c/em\u003e tolerance to abiotic and biotic stresses. Therefore, further analysis is required to understand the relationship between fatty acid accumulation and stress defense mechanisms in response to PAC by combining proteomics with lipid production analysis. The proposed approach allowed for a comprehensive understanding of the stress resilience of molecular mechanisms in response to low PAC exposure in \u003cem\u003eMicrocystis\u003c/em\u003e. However, the results of high PAC exposure are expected to be of greater interest for future medical research. Under high levels of PAC exposure, we found that the detoxification process helps to neutralize or remove toxic compounds and mitigate the harmful effects of environmental stressors, contributing to the use of cellular hemostasis for medical applications. In addition, we also identified transposable elements, also known as jumping genes, that can change their position within the genome, facilitating the analysis of the genomic adaptation of \u003cem\u003eMicrocystis\u003c/em\u003e to PAC stress in future research.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003eCRediT authorship contribution statement\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEun-jeong Kim\u003c/strong\u003e: Conceptualization, Data curation, Formal analysis, Methodology, Visualization, \u0026nbsp;Writing – Original Draft and Reviewing \u0026amp; Editing. \u003cstrong\u003eYeon-jeong Park\u003c/strong\u003e: Data curation, Formal analysis, Methodology, Writing – Original Draft and Reviewing \u0026amp; Editing. \u003cstrong\u003eJae Hak Lee\u003c/strong\u003e: Data curation, Methodology. \u003cstrong\u003eHeesuk Lee\u003c/strong\u003e: Data curation, Funding acquisition, Methodology. \u003cstrong\u003eJihye Yang\u003c/strong\u003e: Data curation. \u003cstrong\u003eHan Soon Kim\u003c/strong\u003e: Conceptualization, Data curation. \u003cstrong\u003eSeong-il Eyun\u003c/strong\u003e: Funding acquisition, Supervision, Writing – Reviewing \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003eDeclaration of competing interest\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003eData availability\u003c/p\u003e\n\u003cp\u003eRaw reads corresponding to transcriptome analyses have been deposited in the NCBI Sequence Read Archive under the BioProject identification number PRJNA1142213.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThe authors gratefully acknowledge Dr. Chi-Yong Ahn and Hee-Mock Oh, Cell factory Research Center, KRIBB, Daejeon 34350, Korea, for generously providing the \u003cem\u003eMicrocystis aeruginosa\u003c/em\u003e KW strain. This work was supported by the National Research Foundation of Korea [2022R1A2C4002058]; Korea Institute of Marine Science \u0026amp; Technology Promotion [RS-2022-KS221676] funded by the Ministry of Oceans and Fisheries; National Research Council of Science \u0026amp; Technology (NST) grant by the Korea government (MSIT) [CAP-18-07-KICT].\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGlibert, P. M. Harmful algae at the complex nexus of eutrophication and climate change. 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Characterization of HicAB toxin-antitoxin module of Sinorhizobium meliloti. BMC Microbiol 19, 10, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12866-018-1382-6\u003c/span\u003e\u003cspan address=\"10.1186/s12866-018-1382-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Microcystis aeruginosa, Doubling time, RNA-seq, PSII antenna protein, bacterial secretion system, toxin–antitoxin system","lastPublishedDoi":"10.21203/rs.3.rs-5278810/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5278810/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePolyaluminum chloride (PAC) is a flocculant commonly used to remove microalgal cells from blooming reservoir. However, some cells exposed to PAC can survive and remain suspended at the surface of eutrophic lakes, potentially reblooming in high-temperature conditions. This study investigated the cellular responses underlying the survival resilience of \u003cem\u003eMicrocystis\u003c/em\u003e in response to PAC treatment. During cell growth, we observed that exposure to low levels of PAC led to a growth pattern resembling normal conditions, whereas cells exposed to high levels of PAC experienced immediate growth inhibition, followed by cell death. Therefore, we employed RNA sequencing to investigate dynamic gene expression. At the transcriptomic level, 264 distinct genes exhibited differential expression under low PAC exposure, significantly affecting the bacterial secretion system and photosynthesis. Changes in the expression of the photosystem II antenna complex phycobilisome were subsequently reflected in changes in phycocyanin pigment production. Furthermore, we identified 223 unique genes under high PAC exposure. Notably, in type II toxin\u0026ndash;antitoxin systems, which serve as a prokaryotic defense mechanism, several toxin genes were expressed at higher levels than antitoxin genes, promoting cell death or apoptosis. These findings bridge a gap in the understanding of cyanobacterial ecotoxicology and environmental responses, potentially enhancing biotechnological and clinical applications.\u003c/p\u003e","manuscriptTitle":"Cellular response in the resilience of Microcystis aeruginosa under polyaluminum chloride exposure","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-08 11:41:18","doi":"10.21203/rs.3.rs-5278810/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e86d2baf-d420-4a7a-bad4-a7a61d866ffb","owner":[],"postedDate":"November 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":39546947,"name":"Earth and environmental sciences/Ecology/Ecological genetics"},{"id":39546948,"name":"Biological sciences/Microbiology/Environmental microbiology/Water microbiology"}],"tags":[],"updatedAt":"2025-02-21T10:13:04+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-08 11:41:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5278810","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5278810","identity":"rs-5278810","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}