Abstract

   2,6-Dichloro-1,4-benzoquinone (2,6-DCBQ) is an emerging chlorinated
   disinfection byproduct (DBP) in bodies of water. However, this compound
   poses an unknown toxic effect on cyanobacteria. In this study, the
   toxicological mechanisms of 2,6-DCBQ in Microcystis aeruginosa (M.
   aeruginosa) were investigated through physiological and nontargeted
   metabolomic assessments. The results show that 2,6-DCBQ inhibited the
   growth of M. aeruginosa, reduced its photosynthetic pigment and protein
   contents, increased the levels of reactive oxygen species, damaged the
   antioxidant defense system, and aggravated the cytomembrane. Meanwhile,
   2,6-DCBQ stimulated the production and release of microcystin-LR
   (MC-LR) and altered the transcripts of genes associated with its
   synthesis (mcyA, mcyD) and transport (mcyH). In addition, nontargeted
   metabolomics of M. aeruginosa cells exposed to 0.1 mg/L 2,6-DCBQ
   identified 208 differential metabolites belonging to 10 metabolic
   pathways and revealed the considerable interference caused by 2,6-DCBQ
   among ABC transporters, the two-component system, and folate
   biosynthesis. This study deepens the understanding of the physiological
   and nontargeted metabolomic responses of M. aeruginosa exposed to
   2,6-DCBQ, offers insights into the toxic effect of 2,6-DCBQ on M.
   aeruginosa, and provides a theoretical basis for the ecological risk
   assessment of emerging DBPs in accordance with water quality criteria.

   Keywords: 2,6-dichloro-1,4-benzoquinone; Microcystis aeruginosa; toxic
   effect; non-targeted metabolomics; water quality criteria

1. Introduction

   The COVID-19 pandemic spread globally and greatly threatened human
   health [[40]1]. The worldwide COVID-19 pandemic has resulted in a
   substantial rise in the use of disinfectants around the globe.
   Excessive use of disinfectants leads to increased concentrations of
   residual chlorine and disinfection byproducts (DBPs) in water bodies
   [[41]2]. Thus far, DBPs have been extensively detected in a variety of
   reclaimed and surface waters [[42]3]. Although the environmental levels
   of DBPs (~µg/L) are typically considerably lower than their effective
   toxic concentrations (~mg/L), recent studies have shown that DBPs at
   environmentally relevant concentrations can also pose environmental
   risks [[43]4,[44]5]. At present, over 900 DBPs have been detected
   [[45]6], but only a limited number have been investigated.

   Halobenzoquinones (HBQs), a new class of DBPs [[46]7,[47]8], have
   garnered research interest due to studies demonstrating their potential
   cytotoxicity, genotoxicity, and carcinogenicity [[48]9,[49]10].
   Toxicological experiments have confirmed the high cytotoxicity of HBQs,
   with toxicity levels approximately 10–1000 times higher than those of
   regulated DBPs, such as trichloromethane and halogenated acetic acids
   [[50]7]. 2,6-Dichloro-1,4-benzoquinone (2,6-DCBQ) is the most
   frequently detected type of HBQs, with the highest detection
   concentration of 274.5 ± 13.0 ng/L [[51]11,[52]12]. The toxic effect of
   2,6-DCBQ is an important issue in the research on DBPs. Previous
   research has indicated that 2,6-DCBQ-induced toxicity is mainly due to
   the presence of reactive oxygen species (ROS) [[53]13]. However, the
   toxicity and potential mechanisms of 2,6-DCBQ have not been explored,
   especially in aquatic ecosystems.

   Cyanobacterial blooms have attracted worldwide attention in the past
   several decades [[54]14]. Cyanobacterial blooms have caused detrimental
   effects on the ecological safety of water environments, including the
   restriction of light penetration, the depletion of dissolved oxygen,
   and the mortality of aquatic organisms [[55]15,[56]16,[57]17]. In
   addition, eutrophic lakes have encountered new challenges due to the
   introduction of emerging contaminants [[58]18,[59]19]. Microcystis
   aeruginosa is the most common type of phytoplankton [[60]20,[61]21]. M.
   aeruginosa, as a primary producer in aquatic habitats, is a major
   contributor to global biogeochemical cycles [[62]22]. However, as a
   potential toxic cyanobacterium, it produces microcystins, which exhibit
   significant toxicity to other aquatic organisms. Cyanobacteria that
   have been exposed to environmental stressors experience physiological
   changes, which can be used in the effective identification of the toxic
   effects of pollutants and the further unveiling of their underlying
   mechanisms. The emerging contaminants (such as DBPs) released into the
   aquatic environment may contribute to the outbreak of cyanobacterial
   blooms through their effects on cyanobacterial growth and metabolism
   [[63]23,[64]24]. Therefore, conducting studies on the impact of
   emerging contaminants, such as 2,6-DCBQ, on M. aeruginosa has profound
   significance.

   This study investigated the physiological response of M. aeruginosa
   exposed to 2,6-DCBQ. The cell density and contents of chlorophyll
   (Chl)-a, carotenoids, adenosine triphosphate (ATP), proteins, and
   glucose were examined. Measurements were conducted for the ROS level,
   microcystin-LR (MC-LR) content, lipid peroxidation, and activities of
   antioxidant-related enzymes in M. aeruginosa. In addition, observations
   were focused on the morphology and ultrastructural characteristics of
   cyanobacteria cells. Finally, nontargeted metabolomics was applied in
   the metabolite analysis and identification of toxicity biomarkers. The
   results can aid in the elucidation of the toxicity mechanisms of
   2,6-DCBQ on M. aeruginosa and provide a theoretical basis for the
   ecological risk assessment of emerging DBPs in accordance with water
   quality criteria.

2. Materials and Methods

2.1. Chemicals and M. aeruginosa Cultivation

   2,6-Dichloro-1,4-benzoquinone (2,6-DCBQ) (CAS No. 697-91-6) was
   obtained from TCL Co., Ltd. (Shanghai, China). An MC-LR standard sample
   (purity ≥ 95%) was obtained from Puhuaren Biological Development Co.,
   Ltd. (Beijing, China).

   M. aeruginosa (FACHB-905) was acquired from the Freshwater Algae
   Culture collection at the Institute of Hydrobiology, Chinese Academy of
   Sciences (Wuhan, China). The cultivation conditions were referenced
   from our previous paper [[65]25]. Based on the preliminary experiments,
   exposure concentrations of 2,6-DCBQ were set as follows: 0.01, 0.05,
   0.1, 0.2, and 0.5 mg/L. According to the OECD Test Guideline No. 201,
   dimethyl sulfoxide (purity ≥ 99.9%) was used as a carrier to dissolve
   2,6-DCBQ, which was added to the M. aeruginosa culture media at a
   volume below 0.01% (v/v).

2.2. Measurements of Growth and the Contents of Chl-a, Carotenoid, and
Protein

   Based on preliminary experiments, five concentrations (0.01, 0.05, 0.1,
   0.2, and 0.5 mg/L) were selected for testing. Guava flow cytometry
   (Luminex, Austin, TX, USA) was used to acquire the standard curve
   correlating the cell density with the optical density. The measurements
   were analyzed using the following equations [[66]25]:
   Cell density = 13.77488 × OD680 + 0.75405 (R^2 = 0.9934) (1)

   We determined the content of chlorophyll a and carotenoids in the M.
   aeruginosa using the N, N-dimethylformamide method. Each group of M.
   aeruginosa cells were collected on days 3, 6, and 9 for the chl-a and
   carotenoid content measurements. The measurements were analyzed using
   the following equations:
   Chl-a = 13.7 × OD665 − 5.76 × OD649 (2)
   Carotenoid = (1000 × OD470 − 1.91chl-a)/225 (3)

   The intracellular protein content was measured according to the
   instructions of the kit (A045-2-2, Jiancheng Bioengineering Institute,
   Nanjing, China) on days 3 and 6, which are based on the basic
   principles of the Bradford method.

2.3. ATP Content and Glucose Content Detection

   The ATP content was determined according to phosphomolybdic acid
   colorimetry. The ATP content was measured according to the instructions
   of the kit (A095-1-1, Jiancheng Bioengineering Institute, Nanjing,
   China) on days 3 and 6. The luminescence intensity was measured at 636
   nm. The glucose content was determined according to the glucose oxidase
   method. The glucose content was measured according to the instructions
   of the kit (F006-1-1, Jiancheng Bioengineering Institute, Nanjing,
   China) on days 3 and 6.

2.4. Determination of Oxidative Stress Biomarkers

   After 24 and 48 h of exposure, the ROS level was measured according to
   the instructions of the kit (A106-1-2), which are based on the basic
   principles of 2′,7′-Dichlorodihydrofluorescein diacetate. After 24 and
   48 h of exposure, the lipid hydroperoxide (LPO) content was measured
   according to the instructions of the kit (A106-1-2), which are based on
   the basic principles of the colorimetric method. The catalase (CAT) and
   superoxide dismutase (SOD) activities were determined according to the
   ammonium molybdate method and a xanthine oxidase assay, respectively.
   The CAT and SOD activities were measured according to the instructions
   of the kits (A007-1-1 and A001-3-2). The operation and calculation
   procedures were conducted in accordance with the instructions provided
   by the kit (Jiancheng Bioengineering Institute, Nanjing, China).

2.5. Scanning Electron Microscope (SEM) and Transmission Electron Microscope
(TEM) Observations

   SEM and TEM observations were conducted according to our previous
   studies [[67]25]. After 72 h of exposure, 1mL of the cell sample was
   centrifuged at 4000× g (4 °C, 8 min), and the precipitated cells were
   collected. The sediment was suspended in 1.5mL PBS. The samples were
   fixed in 25% glutaraldehyde solution at 4 °C in the dark for 12 h, and
   washed three times with 0.1 M PBS (pH = 7.0). Then, the solution was
   dehydrated in different concentration gradients of ethanol for 15 min
   each and treated with 100% ethanol for 20 min. The samples were soaked
   in 100% propylene oxide for 20 min, then treated with a mixture of
   embedding agent and acetone, and embedded in epoxy resin. The surface
   morphology of the cells was observed using SEM at 3.0 kV with an SU8010
   instrument (HITACHI, SU8010, Hitachi, Ltd., Tokyo, Japan), while the
   ultrastructure of the cells was observed using TEM (HITACHI H-7650,
   Hitachi, Ltd., Tokyo, Japan).

2.6. Detection of Microcystin-LR in M. aeruginosa

   The MC-LR content was measured according to our previous studies
   [[68]25]. After 72 and 144 h of exposure, 40 mL of culture media was
   centrifuged at 4000× g (4 °C, 8 min). The supernatant was collected as
   extracellular MC-LR. The pellet was utilized as an intracellular
   solution for MC-LR extraction. The precipitate was dissolved in 10 mL
   of 50% methanol and subjected to sonication at 40% power using an
   ultrasonic cell disruptor in an ice-water bath (below 4 °C) for 8 min.
   The supernatant obtained after centrifugation at 7000× g (4 °C, 10 min)
   was used for further measurement of the intracellular MC-LR.

   The samples gathered underwent solid-phase extraction (SPE) and
   analyzed by HPLC (Shimadzu, TC-20A, Shanghai, China) [[69]26]. The SPE
   cartridge used contained C18 silica gel (TS208-001, Shanghai Titan
   Technology Co., Ltd., Shanghai, China), with a packing material of 500
   mg/6 mL per cartridge. The extraction process was divided into four
   steps: activation (10 mL of pure methanol and 10 mL of distilled
   water), sample injection, leaching (10 mL of 20% methanol), and elution
   (5mL of methanol). After the SPE process, the resulting eluate was
   dried using nitrogen at a temperature of 40 °C until it was almost dry
   and resuspended in 1 mL of chromatography-grade methanol. The eluate
   was then stored at a temperature of −20 °C for analysis. The samples
   were measured by HPLC (UV detector, 238 nm). The mobile phase consisted
   of a mixture of water and methanol at a volumetric ratio of 40:60
   (v:v). The injection volume was 10 μL, with a flow rate of 1.0 mL/min.
   The column temperature was maintained at 35 °C, and each sample was
   analyzed within 15 min. The limit of determination of MC-LR is 100
   μg/L.

2.7. Extraction of Metabolites and Nontargeted Metabolomics Analysis

   Extraction and analysis of the metabolites were conducted by Shanghai
   Luming Biotechnology Co., Ltd. (Shanghai, China). To analyze the
   metabolites, 2 mL of the cultural samples from the CON (control group)
   and the 0.1 mg/L group on day 9 were collected and centrifuged at 100×
   g for 5 min [[70]27,[71]28]. The pellets were gently mixed and washed
   with 1 mL of PBS, and the cells of M. aeruginosa were immediately
   frozen in liquid nitrogen for further analysis. Then, the samples were
   analyzed through ultra-performance liquid chromatography–mass
   spectrometry (ACQUITY UPLC-MS, Waters Corporation, Milford, MA, USA)
   equipped with the ACQUITY UPLC BEN C18 column (100 mm × 2.1 mm, 1.7 μm;
   Waters Corporation). The mobile phases consisted of 0.1% formic acid in
   water/acetonitrile (95/5, v/v, solvent A) and 0.1% formic acid in
   acetonitrile/isopropanol/water (47.5/47.5/5, v/v, solvent B). The
   sample injection volume was 5 μL, and the flow rate was set to 0.4
   mL/min. The column temperature was maintained at 45 °C.

   Metabolites were identified on the metabolome database. The online
   platform OECloud tools ([72]https://cloud.oebiotech.com, accessed on 14
   January 2025) was used to summarize and analyze the data in
   bioinformatics, accessed on 5 March 2024. The roles of these
   metabolites and metabolic pathways were analyzed using the KEGG
   database.

2.8. Quantitative Real-Time PCR Analysis

   Quantitative real-time PCR analysis was conducted according to our
   previous studies [[73]25]. The fold change in gene expression was
   determined using the 2^−ΔΔCt method. Cultural samples from the CON and
   the 0.1 mg/L 2,6-DCBQ treatment were collected on day 3. The primers of
   the target genes (mcyA, mcyD, mcyH, rbcL, ftsH, recA, bchL, pckA, pgk,
   and psaB) are listed in [74]Table S1.

2.9. Reproducibility of the Results and Statistical Analysis

   According to the OECD Test Guideline No. 201, we conducted 3
   independent experiments, each with 3 replicates. Statistical analysis
   was performed using GraphPad Prism 8.0.1 (GraphPad Software, San Diego,
   CA, USA) and SPSS 27.0 (SPSS Inc., Chicago, IL, USA) to determine the
   significance among the treatments. One-way analysis of variance (ANOVA)
   was used to determine the differences between the control and treatment
   groups, and p < 0.05 was considered statistically significant. In
   addition, the statistical methods for nontargeted metabolomics included
   principal component analysis (PCA), partial least squares discriminant
   analysis (OPLS-DA), metabolic pathway enrichment analysis, and heatmap
   clustering analysis.

3. Results

3.1. Physiological Responses of M. aeruginosa Exposed to 2,6-DCBQ

3.1.1. Inhibitions of Growth, Photosynthetic Pigments, and Protein Contents

   [75]Figure 1a shows the response of growing M. aeruginosa to various
   concentrations of 2,6-DCBQ. High concentrations of 2,6-DCBQ (0.2 and
   0.5 mg/L) significantly inhibited the growth of M. aeruginosa.
   Additionally, 0.05 and 0.1 mg/L 2,6-DCBQ also exhibited significant
   inhibition effects on day 4 (p < 0.05). With increasing concentration
   and exposure time, concentration- and time-dependent effects were
   observed.

Figure 1.

   [76]Figure 1
   [77]Open in a new tab

   Cell density (a) of M. aeruginosa treated with 0.01, 0.05, 0.1, 0.2,
   and 0.5 mg/L of 2,6-DCBQ for 9 days. Concentrations of chlorophyll a
   (b) and carotenoids (c) of M. aeruginosa treated with mg/L 2,6-DCBQ on
   days 3, 6, and 9. Protein content (d) of M. aeruginosa treated with
   mg/L 2,6-DCBQ on days 3 and 6. Results are presented as means ±
   standard deviations. * Indicates p < 0.05; ** indicates p < 0.01
   relative to the control by ANOVA.

   Growth inhibition can be indicated by the variation in the content of
   photosynthetic pigments. The 2,6-DCBQ group contained considerably
   decreased chl-a levels after 3 and 6 days of treatment ([78]Figure 1b).
   On the 9th day, 0.1, 0.2, and 0.5 mg/L 2,6-DCBQ substantially inhibited
   chl-a, with inhibition rates of 25.17%, 36.57%, and 92.18%,
   respectively. The results indicate the inhibited or disrupted
   photosynthetic system of M. aeruginosa, which in turn possibly affected
   its growth and proliferation. In addition, the content of carotenoids
   significantly decreased during exposure to 0.1 and 0.5 mg/L 2,6-DCBQ on
   day 3, with inhibition rates of 47.06% and 72.94%, respectively
   ([79]Figure 1c). In addition, 0.5 mg/L 2,6-DCBQ resulted in substantial
   inhibitions in the total soluble protein content, with inhibition rates
   of 15.9% and 35.7% on days 3 and 6, respectively ([80]Figure 1d).

3.1.2. ATP and Glucose Contents

   [81]Figure 2e,f display the ATP and glucose contents of M. aeruginosa
   exposed to 2,6-DCBQ on days 3 and 6, respectively. The contents of ATP
   decreased when M. aeruginosa was exposed to 0.2 mg/L 2,6-DCBQ for 3
   days. In addition, the ATP content significantly increased (p < 0.01)
   when M. aeruginosa was exposed to 0.1 and 0.5 mg/L 2,6-DCBQ for 3 and 6
   days. The glucose content considerably declined with the increase in
   2,6-DCBQ concentrations.

Figure 2.

   [82]Figure 2
   [83]Open in a new tab

   ROS level (a), SOD activity (b), CAT activity (c), and LPO content (d)
   of M. aeruginosa treated with 2,6-DCBQ on 24 and 48 h. ATP (e) and
   glucose (f) of M. aeruginosa treated with 2,6-DCBQ on days 3 and 6.
   Results are presented as means ± standard deviations. * Indicates p <
   0.05; ** indicates p < 0.01 relative to the control by ANOVA.

3.1.3. ROS Level, LPO Content, and Detection of Antioxidant Activities

   The antioxidant activities were evaluated to investigate the oxidative
   stress induced by 2,6-DCBQ in M. aeruginosa. The intracellular ROS
   level of M. aeruginosa increased significantly during exposure to 0.1
   and 0.2 mg/L 2,6-DCBQ ([84]Figure 2a).

   [85]Figure 2b,c show the activities of superoxide dismutase (SOD) and
   catalase (CAT) in M. aeruginosa exposed to 2,6-DCBQ. The activities of
   SOD and CAT presented concentration-related effects. The 0.5 mg/L
   2,6-DCBQ increased the SOD activity on days 1 and 2. During M.
   aeruginosa exposure to 0.01, 0.05, 0.1, 0.2, and 0.5 mg/L 2,6-DCBQ, CAT
   activities were substantially increased by 21.9%, 22.1%, 58.5%, 34.1%,
   and 290% of the control on day 2 ([86]Figure 2c), respectively.
   Similarly, the LPO content revealed a significant increase in M.
   aeruginosa when exposed to 0.5 mg/L of 2,6-DCBQ ([87]Figure 2d).

3.2. Cell Morphology and Ultrastructure Characteristics

   [88]Figure 3a(1) shows that the surface structure of healthy M.
   aeruginosa cells was smooth and plump, without obvious damage or
   rupture. The cell membrane (CM) and cell wall (CW) were intact, and the
   cells exhibited round or oval shapes. However, after the treatment with
   0.1 mg/L 2,6-DCBQ, the cells exhibited a shriveled surface morphology,
   deviating from their normal spherical shape, with a wrinkled and rough
   surface. The SEM images reveal the presence of abundant extracellular
   mucus surrounding the cells ([89]Figure 3a(2)). The TEM images show
   that the CM and CW were rough and fragmented. The thylakoid of M.
   aeruginosa was dispersed ([90]Figure 3b(2),b(3)). These results
   indicate that 2,6-DCBQ exerted acute toxicity effects on M. aeruginosa
   by inhibiting cell growth and photosynthesis. The disruption of CM
   further led to the release of intracellular substances (such as MCs)
   into the aquatic environment, accelerating the death of cells and
   polluting the water environment.

Figure 3.

   [91]Figure 3
   [92]Open in a new tab

   The effects of the CON (a(1),b(1)) and 0.1 mg/L of 2,6-DCBQ on the
   ultrastructure (TEM, (b(2)–b(4))) and surface morphology (SEM,
   (a(2)–a(4))) of M. aeruginosa cells after 3 days of exposure. The
   components pictured include the nucleoid (N), phycobilisome (PBS),
   polyphosphate bodies (PB), thylakoids (T), leucoplast (L), cell wall
   (CW), and cell membrane (CM).

3.3. MC-LR Content

   [93]Figure 4 indicates that 0.1 and 0.2 mg/L 2,6-DCBQ stimulated the
   synthesis of MC-LR (p < 0.01). On days 3 and 6, the content of
   intracellular MC-LR increased when M. aeruginosa was exposed to 0.1 and
   0.2 mg/L 2,6-DCBQ. Similarly, the extracellular MC-LR contents were
   increased when exposed to 0.1 and 0.2 mg/L 2,6-DCBQ. The results
   indicate that 2,6-DCBQ stimulated the production and release of MC-LR
   in M. aeruginosa.

Figure 4.

   [94]Figure 4
   [95]Open in a new tab

   Effects of 2,6-DCBQ on the contents of extracellular (a,b) and
   intracellular (cell quota) (c,d) microcystin-LR in M. aeruginosa.
   Results are presented as means ± standard deviations. * Indicates p <
   0.05; ** indicates p < 0.01; *** indicates p < 0.001 relative to the
   control by ANOVA.

3.4. Nontarget Metabolomics Analysis

3.4.1. Metabolite Detection and Analysis

   We analyzed the changes in the metabolites in M. aeruginosa after
   exposure to 2,6-DCBQ. [96]Figure 5a,b shows the score plots of
   principal component analysis (PCA) and orthogonal partial least squares
   discriminant analysis (OPLS-DA), including those of the quality control
   samples. The scoring plots, which are based on positive ion patterns,
   demonstrate the overall differences between the sample groups and the
   variability within each group. As shown in [97]Figure 5a, PCA revealed
   distinct distributions within each group and effectively distinguished
   the two sample groups. The consistency of the results from the PLS-DA
   further supports these findings ([98]Figure 5b).

Figure 5.

   [99]Figure 5
   [100]Open in a new tab

   Two-dimensional scores plot of principal component analysis (PCA) (a).
   Two-dimensional scores plot of orthogonal partial least squares
   discriminant analysis (OPLS-DA) (b). Volcano plot of different
   metabolites (c). Lollipop map of main differential metabolites (d). The
   level indicates the accuracy of the metabolite identification, with
   smaller level numbers representing higher accuracy. * Indicates p <
   0.05; ** indicates p < 0.01; *** indicates p < 0.001 relative to the
   control by t test.

3.4.2. Identification of Differential Metabolites (DMs) and Metabolic Pathway
Analysis

   The volcano diagram in [101]Figure 5c illustrates the number of
   significantly changed metabolites during the 0.1 mg/L 2,6-DCBQ
   treatment of M. aeruginosa. In addition, the volcano plot visually
   display the overall distribution of the DMs. A total of 63 upregulated
   (red dots) and 145 downregulated (blue dots) metabolites were
   identified during this period ([102]Figure 5c). [103]Figure 5d
   indicates the main differential metabolites; the box plots of relative
   abundance are shown in [104]Figure S1. The upregulated DMs mainly
   comprised organic oxygen compounds and organic nitrogen compounds
   ([105]Figure 6). The downregulated DMs primarily included lipids and
   lipid-like molecules, organic acids, and nucleotides ([106]Figure 6).
   The key enriched pathways included ABC transporters, the two-component
   system, and folate biosynthesis ([107]Figure 7a). Exposure to 2,6-DCBQ
   can affect the KEGG pathway of M. aeruginosa through environmental
   information processing, metabolism, genetic information processing, and
   cellular processes ([108]Figure 7b). ABC transporters and the
   two-component system are involved in environmental information
   processing, while folate biosynthesis is a part of metabolism
   ([109]Table S2). All differential metabolites showed both upregulation
   and downregulation. Quorum sensing is a part of cellular processes
   ([110]Table S2), with all differential metabolites being upregulated.
   The differential metabolites of chloroalkane and chloroalkene
   degradation were all upregulated, while the differential metabolites of
   other metabolic pathways were all downregulated.

Figure 6.

   [111]Figure 6
   [112]Open in a new tab

   Cluster analysis of top 50 differential metabolites.

Figure 7.

   [113]Figure 7
   [114]Open in a new tab

   KEGG pathways with significant enrichment of metabolites (a). Circos
   diagram of KEGG pathways (b).

3.5. Gene Expressions

   The expressions of genes involved in the energy metabolism, MCs, and
   photosynthesis were examined to explore the possible toxic mechanisms
   of 2,6-DCBQ. The results show that 2,6-DCBQ induced alterations in the
   gene expressions of M. aeruginosa ([115]Figure 8). After the exposure
   of M. aeruginosa to 0.1 mg/L 2,6-DCBQ, the expressions of mcyA, mcyD,
   mcyH, ftsH, recA, bchL, pckA, and pkg revealed significant
   downregulation (p < 0.05). Meanwhile, the expressions of rbcL and psaB
   did not change significantly.

Figure 8.

   [116]Figure 8
   [117]Open in a new tab

   Gene expression levels in treatments with 0.1 mg/L 2,6-DCBQ after 3
   days of exposure. Results are presented as means ± standard deviations.
   ** Indicates p < 0.01 relative to the control by ANOVA.

4. Discussion

4.1. Physiological Responses of M. aeruginosa Exposed to 2,6-DCBQ

4.1.1. Growth and Photosynthetic Pigments

   In this study, the results on cell density after exposure to 2,6-DCBQ
   indicate that 2,6-DCBQ exhibits acute toxicity ([118]Figure 1a). recA
   plays a critical role in DNA repair [[119]29,[120]30]. The present
   study reveals that the significantly decreased expression of the recA
   gene suggests DNA damage may also indicate inhibited growth of M.
   aeruginosa due to exposure to 2,6-DCBQ ([121]Figure 8).

   The influence of 2,6-DCBQ on the chl-a and carotenoid contents was
   similar to those on cell growth. Furthermore, the decrease in the chl-a
   content could impair the antioxidant capability of M. aeruginosa,
   resulting in an energy deficit in the cells and reducing their
   resistance to ROS-induced damage [[122]19]. Carotenoids can react with
   lipid peroxides and protect the photosynthetic system of M. aeruginosa
   [[123]31,[124]32]. Tiwari et al. [[125]33] also noted that the heavy
   metal chromium can decrease the contents of chlorophyll and carotenoids
   in paddy-field cyanobacteria.

   The decreases in chl-a ([126]Figure 1b) suggest the impairment or
   disturbance of the photosynthetic system of M. aeruginosa, which
   hindered cell growth. Li et al. [[127]34] confirmed the same phenomenon
   when they exposed Chlorella pyrenoidosa to perfluorooctanoic acid. In
   summary, 2,6-DCBQ restricted the expressions of photosynthesis-related
   genes in M. aeruginosa, which resulted in its decreased photosynthetic
   efficiency and inhibited growth. However, the result of the psaB gene
   suggests that photosystem I of M. aeruginosa was not severely damaged
   by 0.1 mg/L 2,6-DCBQ.

4.1.2. ATP, Glucose, and Protein Contents

   ATP is the direct energy source in organisms, driving various
   biochemical reactions and cellular activities. With prolonged exposure,
   the ATP content in the high-concentration treatment groups (0.1–0.5
   mg/L 2,6-DCBQ) significantly increased, indicating that ATP is
   continuously synthesized to provide energy for repairing stress damage
   and other functions. A previous study also revealed that the chiral
   fragrance carvone affected the ATP production of M. aeruginosa
   [[128]35], which is consistent with our experimental results.

   The glucose and total soluble protein contents were comprehensively
   studied, and the results reveal the time–concentration toxic effect of
   2,6-DCBQ on M. aeruginosa. In this study, reductions in the total
   soluble protein and glucose production were observed, indicating that
   disruptions in energy metabolism during photosynthesis may be involved
   in the growth inhibition of M. aeruginosa caused by 2,6-DCBQ.

   The change in the total soluble protein content is a key response of M.
   aeruginosa under external stress. The total soluble protein content of
   M. aeruginosa decreased continuously under 2,6-DCBQ exposure
   ([129]Figure 1d). The results indicate that the normal physiological
   activities of the cells were disrupted [[130]35]. The ftsH gene plays a
   vital role in the maintenance of the quality of membrane proteins
   during the response to heat shock and in the regulation of cell
   division [[131]36]. Midepogu et al. also found that after 96 h of
   treatment with TiO[2] nanoparticles at a concentration of 20 mg/L, the
   ftsH gene in Chlorella pyrenoidosa decreased to approximately 0.3-fold
   of the control [[132]37]. The downregulation of the cell division
   protein-related ftsH gene may be a direct cause of the inhibitory
   effect on cell growth ([133]Figure 8).

4.1.3. Oxidative Stress and Membrane Permeability

   Excessive ROS production can affect various cellular processes through
   the alteration of nucleic acids, the oxidization of proteins, and the
   triggering of lipid peroxidation [[134]38]. In this study, M.
   aeruginosa exposed to 2,6-DCBQ showed ROS accumulation and subsequent
   lipid peroxidation. In addition, excessive generation of ROS can
   initiate oxidative damage to the cell membrane, which results in
   morphological changes, such as disruption of cellular structures and
   cell death. To investigate the mechanism of oxidative damage, the
   effect of 2,6-DCBQ on lipid peroxidation was analyzed.

   The results on the LPO content indicate that the lipids of M.
   aeruginosa were oxidatively damaged due to exposure to 2,6-DCBQ, and
   antioxidant enzymes cannot completely eliminate ROS [[135]39]. In
   addition, a high concentration of 2,6-DCBQ may possibly induce the rise
   in LPO levels, which can increase cell membrane permeability [[136]40].
   The TEM results also confirm this conclusion ([137]Figure 3b(2)). Our
   previous study further revealed that chloroacetic acid caused oxidative
   stress on M. aeruginosa [[138]25].

   Excessive production of SOD is the primary mechanism underlying the
   protection of thylakoid membranes against organic pollution [[139]41].
   Increased SOD activity protected green algae from the toxic effects of
   a pesticide known as trifloxystrobin [[140]42]. The upregulation of CAT
   activity is considered an adaptation to the stress experienced by M.
   aeruginosa, which is stimulated by various environmental and chemical
   stressors [[141]43].

4.1.4. Production and Release of MC-LR

   MCs are secondary metabolites of cyanobacteria [[142]44]. [143]Figure 4
   indicates that 2,6-DCBQ increased the production and release of MC-LR.
   Exposure to emerging pollutants can upregulate the expressions of
   MC-related genes in M. aeruginosa, which will promote MC-LR secretion
   [[144]45].

   The mcy gene cluster plays a key role in the biosynthesis of MCs in
   various cyanobacterial genera, including M. aeruginosa. Genes mcyA and
   mcyD encode the synthetase of MCs. Gene mcyH encodes the transportation
   of MCs [[145]46]. Numerous studies have verified the relationship
   between the upregulation of the relative transcript abundance of mcy
   gene and the increased contents of MC-LR during production
   [[146]35,[147]47]. In addition, the common contaminant γ-lindane
   upregulates the transcription of mcyD and mcyH genes and improves MC
   production in M. aeruginosa [[148]48]. However, a previous study also
   reported that under external stressors, such as fluoroquinolone
   antibiotics, the extracellular concentration of MCs increased despite
   inhibited M. aeruginosa growth, potentially due to the regulation of
   the mcy cluster [[149]49]. In the present study, genes of mcyA, mcyD,
   and mcyH were substantially decreased compared with the control
   ([150]Figure 8). These results are possibly due to severe damage of the
   cell membrane ([151]Figure 3b(4)), which may result in an increase in
   the extracellular MC-LR content.

4.2. Nontargeted Metabolomics Analysis

   Such metabolites include substances related to antioxidation
   (alpha-lactose, sucrose, and dihydrozeatin-7-N-glucoside), as well as
   nucleosides, nucleotides and their analogues, organic acids,
   derivatives, and lipids, all of which were altered when M. aeruginosa
   was exposed to 2,6-DCBQ ([152]Figure 6).

   Glutamic acid can be transformed into alpha-ketoglutaric acid, which is
   an essential intermediate in the tricarboxylic acid (TCA) cycle,
   through the actions of glutamate dehydrogenase, alanine
   aminotransferase, or aspartate aminotransferase [[153]32]. In
   photosynthetic organisms, the synthesis of chl starts from glutamate,
   which subsequently undergoes a series of intricate biochemical
   reactions that involve a minimum of 17 enzyme reaction steps [[154]50].
   The stress caused by 2,6-DCBQ resulted in downregulated contents of
   L-glutamic acid ([155]Figure 6), which indicates that the TCA cycle was
   inhibited and amino acid metabolism was disrupted. In addition, the
   decline in genes encoding pckA ([156]Figure 8) led to the blockage of
   the TCA cycle. Thus, 2,6-DCBQ can hinder the energy metabolism pathway.

   Lipids are the main components of organelle membranes in cyanobacteria
   [[157]51]. In this study, several fatty acids (such as the potassium
   salts of fatty acids) in the 2,6-DCBQ exposure group were
   downregulated, which indicates the decreased biosynthesis of some fatty
   acids. In addition, the fatty acid composition of M. aeruginosa changes
   under the stress of pollutants [[158]28,[159]52]. Glycerophospholipids
   take part in the development of biological membranes and contribute to
   protein recognition and cell membrane signaling [[160]53]. In this
   study, numerous lipid DMs, such as dodecanamide, carindone, and
   gingerglycolipid, were screened based on the nontargeted metabolomics
   of 2,6-DCBQ-treated M. aeruginosa. This study hypothesized that
   2,6-DCBQ would affect the lipid content, which would consequently alter
   the selective permeability of the biomembrane and lead to the death of
   M. aeruginosa. Consequently, alterations in the types and quantities of
   membrane-bound lipids result in the heightened permeability of the
   biomembrane system. Lipid metabolism is the core pathway for cell
   energy and substance metabolism; it also plays a key role in basic
   physiological processes, such as cell membrane formation and
   intracellular signal transduction. Changes in these pathways inevitably
   lead to disturbances across the entire metabolic network, consistent
   with findings in previous reports. Additionally, heatmap analysis
   revealed the relationship between metabolites and antioxidants
   ([161]Figure 6).

   The pathways significantly downregulated, including ABC transporters
   and the two-component system (p < 0.05) ([162]Figure 7a). ABC
   transporters, particularly ABC transporter BmrD, can participate in the
   absorption, accumulation, and expulsion of endogenous toxins and
   exogenous substances, playing an important role in defense mechanisms
   [[163]51,[164]54]. The two-component system plays a crucial role in
   modulating responses to environmental changes. The results show that
   the related signaling pathways were inhibited. The downregulation of
   folate biosynthesis indicates that the folate cycle was inhibited.
   However, due to the high diversity of metabolism species and a limited
   pathway database, more DMs remain to be further studied in the future.

5. Conclusions

   This work reveals the physiological responses and nontargeted
   metabolomics of M. aeruginosa exposed to various concentrations of
   2,6-DCBQ. The possible mechanisms underlying the mortality of M.
   aeruginosa under 2,6-DCBQ stress can be summarized as follows: (1)
   2,6-DCBQ hampered the synthesis of photosynthetic pigments and further
   influenced photosynthesis and energy metabolism; (2) 2,6-DCBQ increased
   ROS production and reduced the antioxidant capacity of M. aeruginosa;
   (3) 2,6-DCBQ affected the external morphology and cell structure of M.
   aeruginosa cells; (4) 2,6-DCBQ significantly increased the production
   and release of MC-LR while downregulating the expression of mcyA, mcyD,
   and mcyH, possibly due to the cell membrane damage; (5) the nontargeted
   metabolomics analysis identified 208 differential metabolites
   (including antioxidants, substances related to energy metabolism, and
   lipids) belonging to 10 metabolic pathways. Significant metabolic
   enrichment pathways include ABC transporters, two-component systems,
   and folate biosynthesis. This study revealed the inhibitory mechanism
   and key biomarkers of 2,6-DCBQ on M. aeruginosa through in situ
   bioanalytical methods with multiple endpoints and nontargeted
   metabolomics analyses. This study also provides a theoretical basis for
   future research on risk assessments and the development of water
   quality criteria for new pollutants such as DBPs.

Supplementary Materials

   The following supporting information can be downloaded at
   [165]https://www.mdpi.com/article/10.3390/toxics13010064/s1: Figure S1:
   Box plots of relative abundance of C16, Arctiin, Gingerglycolipid A,
   Microcystin-Lr, Halistanol Sulfonic Acid F, Lilopristone,
   1-(2-Methoxy-13-Methyl-6z-Tetradecenyl)-Sn-Glycero-,
   MGMG(18:2(9Z,12)/0:0), Mytilin A, PS(16:0/0:0), Photinus Luciferin,
   Relamorelin, Disodium Phosphate, Beta-D-Fructose 2,6-Bisphosphate,
   Fosfomycin, L-Oxalylalbizziine, Cis-3-Chloro-2-Propene-1-Ol, C16
   Sphingosine, Dibutyl Phthalate, and Dodecanamide; Table S1: PCR primer
   sequences used in the experiment; Table S2: Detailed information of
   Circos diagram.
   [166]toxics-13-00064-s001.zip^ (587.2KB, zip)

Author Contributions

   Conceptualization, J.Y. and T.Z.; methodology, L.M.; software, Z.W.;
   validation, T.Z. and Z.W.; formal analysis, Z.W., C.L. and F.T.;
   investigation, T.Z. and Z.W.; resources, J.Y.; data curation, C.L. and
   F.T.; writing—original draft preparation, T.Z. and Z.W.; writing—review
   and editing, L.W., M.H. and H.L.; visualization, T.Z. and Z.W.;
   supervision, J.Y.; project administration, J.Y.; funding acquisition
   J.Y., L.M. and H.L. All authors have read and agreed to the published
   version of the manuscript.

Institutional Review Board Statement

   Not applicable.

Informed Consent Statement

   Not applicable.

Data Availability Statement

   Data will be made available upon request.

Conflicts of Interest

   The authors declare no conflicts of interest.

Funding Statement

   This research was funded by the National Natural Science Foundation of
   China (42277274 (Jing Ye), 21307082 (Jing Ye), and 41877425 (Liang
   Meng)), the project of the Science and Technology Commission of
   Shanghai Municipality, China (18ZR1438000 (Jing Ye)), and the Study of
   Sources and Influence Mechanism of Nitrogen and Phosphorus Pollution in
   the Nanxijiang River Based on APCS-MLR Analysis (KZX202207006 (Haizhuan
   Lin)).

Footnotes

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References