K. mikimotoi (MEL22) isolated from coastal Pingtan, Fujian Province and kindly provided to us by Institute of Oceanography, Chinese Academy of Sciences. Cells were cultured in 0.45-μm filtered natural seawater, which had been autoclaved (30min, 121°C) and enriched with f/2 medium (Guillard, 1975). All cultures were incubated at 20±1°C and illuminated under a 12-h light–dark cycle with radiance of 80μmol photon m⁻² s⁻¹ provided by cool white fluorescent tubes in a constant temperature incubator. The pH and salinity were kept constant at 8.10±0.02 and 30±1.0, respectively. Flasks were manually shaken twice a day at a set time to avoid cell sedimentation. Cells in the exponential phase were used in the assays.

The establishment of the acidifying system was based on the methods of our previous study (Hu et al., 2017; Sun et al., 2017). Three pH levels were evaluated in the present study: pH 8.1 (present ambient seawater pH, pCO₂≈390ppm), pH 7.6 (predicted pH in 2100, pCO₂≈1,000ppm), and pH 7.4 (predicted pH in 2300, pCO₂≈2000ppm), obtained by gentle bubbling with 0.22-μm filtered ambient air and air/CO₂ mixtures. The air/CO₂ mixtures were generated by plant CO₂ chambers (HP400G-D, Ruihua Instrument & Equipment Ltd., Wuhan, China) with a variation of less than 5%. The pH values and salinity of the seawater in the flasks were measured by a pH meter (Seven Compact™ S210k, Mettler Toledo, Switzerland) and a handheld salinometer (WY028Y, HUARUI, CHN).

The growth of K. mikimotoi was determined according to the method described by Deng et al. (2017). The cell density was determined and quantitatively simulated using a logistic equation. The specific growth rate (μ, d⁻¹) was calculated and analyzed by using the following equation (OECD, 2011):

where μ_i−j represents the average specific growth rate from time i to j, X_i represents the cell density at time I, and X_j represents the cell density at time j.

We evaluated the growth performance of each strain and regressed the population growth curves using the following logistic growth model (Zhao et al., 2015):

where N_t (cells ml⁻¹) is the algal density at time t, K (cells mL⁻¹) is the carrying capacity, r (d⁻¹) is the maximum specific growth rate, and T_p is the inflection point of population growth curve.

On the 8th and 15th days after exposure, 50mL microalgal medium was sampled from the control and acidification-treated groups and centrifuged at 3000r/min. Then, the collected microalgal cells were fixed on ice with 3.5% glutaraldehyde in phosphate-buffered saline (PBS; 0.1molL⁻¹, pH 7.2). The treated samples were kept at 4°C overnight in fixative liquid and washed 3 times with the same solution. Then, the cells were dehydrated sequentially in graded concentrations of ethanol based on the methods of Zhu et al. (1983), preparing the slides in triplicate. A Hitachi H-7000 (Japan) TEM was utilized to observe the ultrastructure of the algal samples.

The ROS levels were detected by using 2'7'-dichlorofluorescein diacetate (DCFH-DA, Sigma-Aldrich) as a fluorescent probe. Briefly, 2mL culture medium in each treatment was sampled and centrifuged at 3000r/min. The supernatants were discarded, and the microalgal cells were resuspended in PBS buffer (pH 7.2). DCFH-DA was added to this suspension to a final concentration of 10μM and mixed well. The mixture was incubated at 20°C in the dark for 30min and washed twice with PBS (Zhou et al., 2019). The fluorescence value was detected by flow cytometry (Beckman Coulter Inc., CA, United States) in the FL1 channel.

The cytochrome c oxidase (COX) and citrate synthase (CS) activities were measured as described in Xiao et al. (2019) with slight modifications. The collected microalgal cells were homogenized in precooled lysis buffer (4°C) by ultrasonication, the mitochondrial suspension was extracted by centrifugation at 6000r/min, and the enzyme activities of COX and CS were determined by using assay kits (Shanghai Jiemei Gene Pharmaceutical Technology Co., Ltd.; Shanghai Harling Biotechnology Co., Ltd.). The results were all expressed in mg protein/min.

The measurement methods of nitrate reductase (NR) and phosphatase, including alkaline phosphatase (AP) and acid phosphatase (AcP), were conducted as described in Mei et al. (2013) with slight modifications. Microalgal cells were collected onto 0.45μm pore size glass fiber filter membranes (GF/F, Whatman) and homogenized in precooled lysis buffer (4°C) by the ultrasonic crushing method. The suspension was extracted by centrifugation at 6,000r/min, and the enzyme activities of NR, AP, and ACP were determined using the corresponding assay kits (Nanjing Jiancheng Bioengineering Institute, Nanjing, China). The results were all expressed in mg protein/min.

The microalgal culture medium in both the control and acidification-treated groups was mixed with hemocytes of the blue mussel Mytilis edulis according to the method of Li et al. (2018), and the hemolytic activity was evaluated based on the hemolysis rate (Caffrey et al., 1986), which was calculated as:

where C_t (cell/ml) denotes the hemocyte density at time t (hour), C₀ is the initial density of the hemocytes, and t is 24h.

Data analysis was performed using SPSS v. 24, and the data are expressed as the means ± standard deviation (SD). The data under every treatment conformed to a normal distribution (Shapiro–Wilk, p>0.05), and the variances could be considered equal (Levene’s test, p>0.05). The effect of pH was analyzed by one-way ANOVA (LSD test). The effects of pH, nutrient status, and their interactions were analyzed by two-way ANOVA. Moreover, significant effects of the nutrient levels at each fixed pH and significant effects of pH at each time point for each nutrient level were analyzed by one-way ANOVA (LSD test). A bivariate Pearson’s correlation analysis was performed to analyze the relationship among parameters. For all analyses, significance was assigned at the p<0.05 level. Figures were generated using GraphPad Prism 8.0 software.

In the present study, acidification (pH 7.6) promoted a certain increase in algal growth, but there was no significant stimulating effect at pH 7.4, and even inhibited the growth of algal to some extent (p<0.05). There are two possible explanations for this: First, the cells reallocate intercellular energy for other metabolic activities (Shi et al., 2015) and reduce it for cellular division, and second, acidification impairs the cellular structure (Shi et al., 2009), and this results in a disorder of cell physiological functions (Rost et al., 2010). Mitochondria are organelles responsible for energy production that is essential for cell division and growth (Nunes-Nesi et al., 2014). Energy synthesis in plant mitochondria originates from a sequential set of metabolic processes and then undergoes a series of enzymatic and nonenzymatic reactions to synthesize ATP via the tricarboxylic acid cycle (TAC) and oxidative phosphorylation (Jacoby et al., 2012). We measured the activities of two respiratory enzymes, COX and CS, which play key roles in TAC and oxidative phosphorylation and found that pH 7.6 significantly increased their activities (p<0.05). The activation of these enzymes facilitates ATP synthesis and increases ATP production (Xiao et al., 2019). However, pH 7.4 inhibited the activities of COX and CS on the 8th day, indicating an insufficient supply of ATP, which might disrupt cell function (Chivasa et al., 2005). The normal process of cellular biochemical reactions is based on an intact cellular structure, and interference with enzymatic activities could be due to mitochondrial structural damage (Xiao et al., 2019). TEM observations (Figure 2) showed that the mitochondria in K. mikimotoi cells exhibited normal morphological structures when exposed to pH 7.6 conditions (Figure 2C); therefore, the activities of these enzymes were not negatively affected. However, pH 7.4 destroyed the mitochondrial ultrastructure, damaging the bilayer membrane structure and blurring the cristae (Figure 2E). Therefore, changes in the mitochondrial structure at pH 7.4 may affect key mitochondrial enzyme activities and ATP synthesis.

Mitochondria are also responsible for ROS overproduction when aerobic respiration is blocked under stress (Ali et al., 2016; Zhang et al., 2018). It has been reported that acidification stress leads to the accumulation of ROS and results in oxidative damage (Li and Xing, 2011), and we observed similar results in the present study: pH 7.6 induced a slight increase in ROS levels and pH 7.4 stress caused ROS bursts (Figure 8), which is an important response of K. mikimotoi to acidification exposure on the 8th day, suggesting that pH 7.4 induces mitochondrial oxidative stress. The elevated ROS level damaged the mitochondrial ultrastructure and caused mitochondrial dysfunction in K. mikimotoi, which further aggravated the damage. ROS have also been shown to have direct inhibitory effects on a variety of mitochondrial enzymes, including components of the electron transport chain (Chen et al., 2005; Navrot et al., 2007). In this study, ROS were found to have a significantly negative correlation with both COX and CS in all treated groups, and this reached extreme significance (p<0.01) in the pH 7.4 group (Table 5). Specifically, Guedouari et al. (2014) found that temporary oxidative stress is associated with an increase in ROS production, which may constitute a signal for adaptive strategies.

It was speculated that the enzymes COX and CS, which are involved in mitochondrial metabolism, are closely related to physiological adaptability at the individual level (Ren et al., 2010). CS activation drives the TCA cycle toward a more energetic metabolism and is necessary to respond to the energetic needs of the cell. Moreover, a significant increase in COX activity may compensate for the inhibition of mitochondria (Guedouari et al., 2014). In this study, the concomitant activation of COX and CS in the pH 7.4 group reflected a shift of the algal cells toward higher levels of energy production on the 15th day, possibly providing the mitochondrial respiratory chain with a larger number of electrons. In addition, activating the key enzymes in mitochondrial metabolism helped to increase ATP production in the algal cells under acidification conditions to run some energy consumption adaptation mechanisms, including activating antioxidant systems to eliminate excessive ROS (Ali et al., 2016; Zhang et al., 2018), thus alleviating ROS damage to mitochondria. As stated above, we thus speculated that mitochondrial metabolism takes part in the active response of K. mikimotoi to acidification.

We found that a moderate decrease in pH could promote an increase in algal cell density, but a further decrease in pH would damage the cellular structure and function. N and P are the most crucial factors in the growth rate, and algal density increases with increasing N:P ratios in a certain range (Li et al., 2014). It is suggested that high nitrogenous nutrient availability is a prerequisite for K. mikimotoi blooms (Chang and Carpenter, 1985). In our study, the condition of acidification with different nutrient statuses significantly increased the population density of K. mikimotoi. The growth rate of K. mikimotoi was highly sensitive to acidification driven by nutrient alteration, especially under P limitation on the 12th and 15th days (Figure 4). Similar results found that the cell density and growth rate of Conticribra weissflogii and Prorocentrum donghaiense were increased when N/P increase under acidification conditions (Zheng et al., 2016), which was evidenced that the growth rate was controlled not only by the pH but also by the ratio of N to P. Two enzymes closely related to phosphate absorption, AP and AcP, were found to be actively induced simultaneously, and a relatively clear negative correlation was found between the enzymatic activity and the P concentration (Figure 5). This result might be a possible explanation for the population dynamics observation of the abovementioned factors and was also consistent with the following statement: acidification promotes the expression of phytoplankton phosphorus deficiency signals, thereby facilitating the absorption and utilization of phosphorus (Ivančić et al., 2010; Fitzsimons et al., 2020). However, the changes in the activities of the two phosphatases differed when exposed to N limitation conditions with acidification. The results showed that N limitation induced a progressive increase in AP activity in a time-dependent manner but only a slight increase in AcP activity on the 12th day (p<0.05). Therefore, both N and P limitations induced an increase in phosphatase activities in K. mikimotoi cells under acidification.

Increasing the activity of AP and AcP is one of the important adaptive strategies of plants to enhance P acquisition and utilization (Wang et al., 2009). It is reported that K. mikimotoi grows better as nitrate supplied as the only nitrogen source (Lei and Lü, 2011). However, the NR characteristics of different algae are different, which leads to differences in the nitrate utilization efficiency of algae (Berges and Hageman, 1997). In addition, the exact mechanism of nitrate on K. mikimotoi algal cell metabolism is still unknown. Our results showed that NR activities in K. mikimotoi induced by N and P limitations decreased slightly when exposed to acidification, but the difference between the two nutrient limitations was not significant. We suspect that in the process of external nitrate depletion or after exhaustion, K. mikimotoi utilized intracellular reserves of nitrate to maintain a certain NR activity under extremely low nitrate levels in the external environment (Dortch et al., 1979).

Hemolytic toxicity is another effective index indicating the growth status of K. mikimotoi (Li et al., 2019), which varies according to the growth stage and nutrient condition of K. mikimotoi (Lin et al., 2015). Under nutrient-sufficiency conditions, toxin production is often low, while increased production is associated with different types of nutrient limitation stress. The hemocytes of the blue mussel M. edulis were utilized in the present study to determine the hemolytic toxicity, which was different from the routine method that utilizes bovine or rabbit blood cells. We found that the hemolytic activity was increased in a time- and N:P ratio-dependent manner (Figure 7), and a significant elevation was seen under P limitation. These results suggest P limitation is an important factor regulating cellular toxicity and adverse impacts. Acidification (pH) and nutrient alteration (N/P) showed statistically (MANOVA) significant interactive effects on hemolytic activity (Table 3). The algae cells under high CO₂ and P limitation conditions were the most toxic (Figure 7). Similar results showed that cytotoxicity of Alexandrium catenella was observed to be significantly increased under P limitation, while acidification conditions further exacerbated this toxicity (Tatters et al., 2013). Significantly, the increase in hemolytic activity is supported by N released within the cell from protein turnover, which was affected by P limitation, so that hemolytic cytotoxin synthesis was enhanced. Negative significance was also observed between hemolytic toxicity and ROS (p=−0.586*; Table 6). Considering the downregulation of ROS levels over time, we speculated that more energy produced by mitochondrial metabolism was allocated to the accumulation of toxic compounds (Jin et al., 2015), which enhanced the hemolytic activity during exposure to acidification with different nutrient statuses (Wang et al., 2019a). These data further explain why K. mikimotoi becomes the dominant species under red tide conditions by enhancing its absorption rate of nutrients and its toxicity.