Effects of Phenolic Pollution on Interspecific Competition between Microcystis aeruginosa and Chlorella pyrenoidosa and their Photosynthetic Responses

Abstract

The demand for phenolic compounds has been increasing rapidly, which has intensified the production and usage of phenol at a commercial scale. In some polluted water bodies, phenol has become one of the typical aromatic contaminants. Such water bodies are inescapably influenced by nutrients from human activities, and also suffer from nuisance cyanobacterial blooms. While phenolic pollution threatens water safety and ecological balance, algal cells are ubiquitous and sensitive to pollutants. Therefore, effects of phenolic pollution on interspecific competition between a bloom-forming cyanobacterium and other common alga merit quantitative investigation. In this study, the effects of phenol on Microcystis aeruginosa (M. aeruginosa, a bloom-forming cyanobacterium) and Chlorella pyrenoidosa (C. pyrenoidosa, a ubiquitous green alga) were analyzed in mono- and co-cultures. The two species were exposed to a series of phenol treatments (0, 2, 20, and 200 μg mL⁻¹). Population dynamics were measured by a flow cytometer and analyzed by the Lotka-Volterra model. The results showed that M. aeruginosa was more sensitive to phenol (EC₅₀ = 80.8 ± 0.16 μg mL⁻¹) compared to C. pyrenoidosa (EC₅₀ = 631.4 ± 0.41 μg mL⁻¹) in mono-cultures. M. aeruginosa won in the co-cultures when phenol was below or equal to 20 μg mL⁻¹, while C. pyrenoidosa became the dominant species in the 200 μg mL⁻¹ treatment. Photosynthetic activity was measured by a fluometer. Results showed phenol significantly impacted the photosynthetic activity of M. aeruginosa by inhibiting the acceptor side of its photosystem II (PSII), while such inhibition in C. pyrenoidosa was only observed in the highest phenol treatment (200 μg mL⁻¹). This study provides a better understanding for predicting the succession of algal community structure in water bodies susceptible to phenolic contamination. Moreover, it reveals the mechanism on photosynthetic responses of these two species under phenolic stress.

Highlights:M. aeruginosa was dominant in co-cultures with C. pyrenoidosa at a lower concentration of phenol (below or equal to 20 μg mL⁻¹). A higher concentration of phenolic pollution (up to 200 μg mL⁻¹) facilitated the dominance of C. pyrenoidosa in co-cultures with M. aeruginosa. Phenol inhibits the acceptor side of electron transport chain and reduces the number of active reaction centers of photosystem II in M. aeruginosa cells.

1. Introduction

Phenol is a common aromatic organic compound in surface waters [1,2,3], and mainly originates with wastewaters from various industries, including the coal mining, phenol production, and textile industries [4,5]. In China, phenol is generally at 0.2 to 12 μg L⁻¹ in unpolluted lakes [6,7]. However, its concentration can be much higher in wastewater from petroleum refineries (13–88 μg mL⁻¹) and in coke wastewater (180 μg mL⁻¹) from steel facilities [3]. In 2005, in Tonglu County (China), the concentration of phenol reached 243 μg mL⁻¹ in the polluted water area [8]. More recently, with the increasing production and usage of phenol, large numbers of lakes and rivers suffer from phenolic pollution.

The presence of phenol in water bodies generally poses severe risks to human health (corrosive and carcinogenic toxicity) and water safety. Moreover, phenolic pollution can threaten the balance of aquatic ecosystems. Algal cells are ubiquitous, and are sensitive to aromatic pollutants. Therefore, greater insights into their damaging effects on phytoplankton are crucial, given their role on primary productivity in ecosystems. Several studies have reported that the structure of algal cells can be affected by the existence of phenol; for instance, the membranes of algal cells may be damaged by hydrophobic interaction with lipid bilayer structures [9,10]. Additionally, photosynthetic systems of algal cells might be damaged by phenol, as recent studies have shown that phenol changes their PSII structures and functions [10,11]. However, most studies have focused on the effects of phenol on the growth and physiology of single algal species in mono-cultures [11,12,13], while there is a lack of information on its influence on interspecific competition and dominance establishment. Such knowledge is of critical significance in relation to predicting and protecting the stability of aquatic ecosystems.

In recent years, some studies have shown that organic pollutants (such as alkylbenzene sulfonate and pentachlorophenol) have the potential to overturn algal community structure [14,15]. For example, M. aeruginosa competed over Scenedesmus obliquus in co-cultures without alkylbenzene sulfonate (LAS), while the result was opposite when LAS (20 μg mL⁻¹) was added in co-cultures [15]. Similarly, the effects of pentachlorophenol (PCP) on M. aeruginosa and Chlorella vulgaris were studied in co-cultures [16]. Results showed that the effect of PCP on M. aeruginosa was concentration-specific, where low levels of PCP promoted the growth of M. aeruginosa, while high concentrations of PCP significantly inhibited its growth. However, no toxic effect of PCP on C. vulgaris was observed. This suggests that exogenous pollutants can affect the interspecific competition between M. aeruginosa and S. obliquus, thereby influencing the community structure. Moreover, it has been reported that polycyclic aromatic hydrocarbons (PAHs) could also affect the algal interspecific competition [14,17]. Despite the potential influences of organic pollutants on the interspecific relationships, the mechanism involved in the competitive process still remain open for further investigation, which merits quantitative analysis to better understand such phenomena under polluted conditions.

Cyanobacterial blooms threaten drinking water supplies, fisheries, and recreational activities. Competition between cyanobacteria and green algae affects phytoplankton succession and the formation of blooms [18]. In China, Microcystis is a very common bloom-forming cyanobacterium. Some organic compounds could influence the growth of Microcystis [15,19], while the detailed information about the competition between Microcystis and other algae under the stress of phenol is still unclear. Therefore, in this study, two common species of phytoplankton (M. aeruginosa and C. pyrenoidosa) were chosen to investigate the effects of phenol in mono- and co-cultures. Their growth and photosynthetic parameters were measured to analyze their competitive relationships and photosynthetic responses to various concentrations of phenol. We aimed to provide some useful information for predicting the succession of algal community structure in water bodies susceptible to phenolic contamination.

2. Materials and Methods

2.1. Preparation of Chemical Reagents

Phenol was purchased from Aladdin Industrial Corporation of Shanghai, with a purity > 99.0%, which was pre-dissolved in dimethyl sulfoxide (DMSO). The concentration of DMSO was lower than 0.5 mL L⁻¹ to ensure DMSO was nontoxic to algal cells [20]. The phenol-DMSO solution was stored in an airtight bottle and was protected from light.

2.2. Strains and Culture Conditions

M. aeruginosa (PCC-7806) and C. pyrenoidosa (FACHB-11) were purchased from the Institute of Hydrobiology, Chinese Academy of Science. The two strains were cultured in sterilized BG11 media [21] at 25 ± 0.5 °C, with a light: dark cycle of 12 h: 12 h at 65 μmol photons m⁻² s⁻¹ (FSL, China). Algal cells in the mid-exponential growth phase were used for the experiments.

2.3. Experimental Design

To evaluate the effects of phenol on growth, photosynthesis, and interspecific competition between M. aeruginosa and C. pyrenoidosa, their mono-cultures and co-cultures were designed. Experiments were carried out in 250 mL Erlenmeyer flasks containing 100 mL algal suspension. Phenol was set at four treatment groups (0, 2, 20, and 200 μg mL⁻¹), to reflect its concentrations in polluted water bodies in China mentioned above. In this study, the initial biomass ratio of M. aeruginosa to C. pyrenoidosa was set at 1:1, and the initial cell concentration was adjusted based on the volume of individual cells [22]. Therefore, the cell concentrations of M. aeruginosa and C. pyrenoidosa were set at 1.0 × 10⁵ and 2.0 × 10⁵ cells mL⁻¹ at the beginning, respectively. Experiments were carried out in triplicate.

2.4. Cell Counting

Cells of the two species are similar in size and morphology, which are difficult to be distinguished and enumerated accurately by an optical microscope. Therefore, flow cytometry (Accuri C6 plus, BD) was employed to analyze cell concentrations every two days. Replicated samples (2 mL) from the different treatment groups were analyzed. For the quantification of cell concentration, an aliquot of a calibrated solution of fluorescent beads (1 μm diameter, BD) was added in each sample as an internal standard. Two species were differentiated by auto-fluorescent signals of chlorophyll and phycocyanin.

2.5. Measurement of In Vivo Chlorophyll-a Fluorescence

To monitor photosynthetic activity responses to phenol, photosynthetic efficiencies of monocultured M. aeruginosa and C. pyrenoidosa were determined by in vivo chlorophyll-a (Chl a) fluorescence. Firstly, 2 mL of algal cells were kept in the dark for 15 min. Then a series of chlorophyll-a fluorescence parameters and the induction curves were recorded by a FluorPen fluorometer (AquaPen C100, Photon Systems Instruments, Czech) at room temperature [23,24,25]. This fluorometer was equipped with two types of excitation wavelength at 455 nm and 620 nm. The OJIP test (Fluorescence response curves detection) was conducted to analyze the changes in these fluorescent parameters, which can provide adequate information about the structure, conformation, and the function of photosynthetic apparatus. From the OJIP transient, the measured parameters (F₀, F_m, F_300μs, F_J, F_I and so on) were used to calculate new parameters, which are displayed in

Table 1. Formulae or terms of the OJIP transient [24,25].

Formulae or terms	Description
F0	Minimum fluorescence
Fm	Maximum fluorescence
VJ = (F2ms − F0)/(Fm − F0)	Relative variable fluorescence at 2 ms
M0 = 4 (F300μs − F0)/(Fm − F0)	Approximated initial slope (in ms −1) of the fluorescence transient V = f (t); It is a measure of the rate of the primary photochemistry
VK = (F300μs − F0)/(Fm − F0)	Relative variable fluorescence at 300 μs
Fv/Fm	The maximum quantum yield of primary photochemistry at t = 0
ET0/TR0 = 1 − VJ	Probability (at time 0) that a trapped exciton moves an electron into the electron transport chain beyond QA−
ET0/RC = (M0/VJ) × (1 − VJ)	Electron transport from QA to QB flux per RC (reaction center)
ABS/RC = [M0 (1/VJ)/(Fv/Fm)]	Absorption flux per RC
Fv/F0	An indicator of the efficiency in the primary photochemical reaction
Fraction of OEC = [1 − (VK/VJ)]treated/[1 − (VK/VJ)]control	The fraction of OEC (oxygen-evolving complex) in comparison with the control
DI0/RC = ABS/RC − TR0/RC	Dissipated energy flux per RC at t = 0

[24,25].

2.6. Measurement of Dissolved Phenol Concentration

The concentration of dissolved phenol was determined every two days after filtration (using GF/F membrane, Whatman) based on the standard method [26]. Phenol concentrations were measured via a spectrophotometer (Shimadzu UV-2450, Japan) after chloroform extraction. The absorbance of the colored complex of phenol with 4- amino antipyrine was detected at 460 nm [26]. Moreover, to detect the abiotic degradation of phenol during the experiment, a blank control (BG11 medium with phenol and without algal cells) was designed to measure the concentration of phenol every two days.

2.7. Statistical Analyses

Statistical analyses were performed using SPSS 19.0 (IBM, Armonk, NY, USA). One-way analysis of variance (ANOVA) was applied to determine the significance of differences among the different treatments and least significant difference (LSD) multiple comparison was performed (p < 0.05 was considered as the level of significance). Data were expressed as mean ± standard deviation (SD). Logistic growth model was used to fit the data and describe the population dynamics of M. aeruginosa and C. pyrenoidosa.

Based on the growth curves, half-maximal effective concentration (EC₅₀) was estimated at 96 h in terms of interpolated concentration that would inhibit growth by 50% over a specific period (96 h). EC₅₀ was estimated using a dose-response model for probit analysis on the fourth day [27].

Growth curves were fitted according to the following logistic function:

$${{\displaystyle N}}_{(t)}=K/(1+{{\displaystyle e}}^{a-rt})$$

(1)

where N_(t) is the cell concentration (10⁵ cells mL⁻¹) at t; K is the carrying capacity (10⁵ cells mL⁻¹) of the population, defined as maximum sustainable population biomass in a given space; a is the coefficient indicating the intercept of growth curves; r is the intrinsic growth rate, and t is the duration of culture [14,17].

The occurrence of inflection on growth curves reflects the initiation of inhibition, which was calculated using the following formula:

$${{\displaystyle T}}_p=a/r$$

(2)

where T_p is the initiation of inhibition, a is coefficient indicating the intercept of the growth curves, and r is the intrinsic growth rate.

The Lotka-Volterra competitive model [28] was used to calculate the population dynamics of the two species under the stress of organic compounds in co-cultures [14,15], which was calculated using the following formula:

$$\frac{Nmn-Nmn-1}{tn-tn-1}=\frac{rmnNmn-1\left(Kmn-Nmn-1-\alpha Ncn-1\right)}{Kmn}$$

(3)

$$\frac{Ncn-Ncn-1}{tn-tn-1}=\frac{rcnNcn-1\left(Kcn-Ncn-1-\beta Nmn-1\right)}{Kcn}$$

(4)

where N_mn (N_mn−1) and N_cn (N_cn−1) represent the cell concentrations of M. aeruginosa and C. pyrenoidosa, respectively, when they were co-cultured at day t_n (t_n−1); r_mn and r_cn are the intrinsic growth rates of M. aeruginosa and C. pyrenoidosa, respectively, which are calculated according to the mono-cultures; K_mn and K_cn are the carrying capacity of each unit of cell concentrations of M. aeruginosa and C. pyrenoidosa respectively in mono-cultures; α and β are the competition coefficients in co-cultures; α indicates the inhibition of C. pyrenoidosa on M. aeruginosa; and β represents the inhibition of M. aeruginosa on C. pyrenoidosa.

3. Results and Discussion

3.1. Effects of Phenol on Algal Growth in Mono- and Co-Cultures

In this study, data were calculated and fitted by the equation to estimate the EC₅₀ on the fourth day, because aromatic pollutants decreased the population growth and biomass of microalgae after three days [27]. Therefore, the endpoint biomass measurement for dose-response analysis after 96 h exposure was more convincing. Growth rates varied with species and culture types after 96 h of exposure to phenol, and the EC₅₀ of M. aeruginosa was 80.8 ± 0.16 μg mL⁻¹ in mono-cultures, which dropped to 54.7 ± 0.25 μg mL⁻¹ in co-cultures (

Table 2. EC₅₀ of phenol for M. aeruginosa and C. pyrenoidosa in mono- and co-cultures.

Species	Culture Type	EC50 (μg mL−1)	Probit Regression Equation i
			a	b	r2
M. aeruginosa	mono-culture	80.8 ± 0.16	1.16	2.2	0.979
	co-culture	54.7 ± 0.25	1.03	1.58	0.996
C. pyrenoidosa	mono-culture	565.9 ± 0.41	0.49	1.36	0.980
	co-culture	NC	NC	NC	NC

i: Probit regression equation is in the form of y = ax + b, where y = probit (% control), x = lg [phenol concentration (in μg mL⁻¹)], a is the slope, and b is the y-intercept. NC refers to no calculation because the data were not fit to the dose-response model.

). This reflected that interspecific competition increased the toxicant sensitivity of M. aeruginosa to phenol [29,30]. However, C. pyrenoidosa showed high resistance to phenol, as its EC₅₀ was as high as 565.9 ± 0.41 μg mL⁻¹ in mono-cultures. A previous work studied four nitrophenolics (o-nitrophenol, p-nitrophenol, m-nitrophenol, 2, 4-dinitrosophenol) toward the growth of C. vulgaris and two cyanobacteria (Nostoc muscorum and Nostoc linckia), and the EC₅₀ of C. vulgaris was in the range of 55 to 128 μg mL⁻¹, while the EC₅₀ values of two cyanobacteria were 32 to 82 μg mL⁻¹ [31]. These data were similar to our results, but the nitrophenolic compound is more toxic than phenol to Chlorella sp..

As for quantitative analyses, M. aeruginosa unicells were much more accessible for enumeration than colonies. Population dynamics and interspecific competition between the two species can be analyzed accurately by flow cytometry and ecological models. It was the reason unicellular M. aeruginosa was chosen for this study.

Growth curves of M. aeruginosa and C. pyrenoidosa in mono- and co-cultures are displayed in Figure 1. In mono-cultures, the growth of M. aeruginosa was markedly inhibited by high concentration (200 μg mL⁻¹) of phenol in the beginning (Figure 1d), while the cell concentration of C. pyrenoidosa increased by 61% and 54% in 20 and 200 μg mL⁻¹ treatment groups, respectively (Figure 1c,d). Growth hormesis was observed in some algae after exposure to chemicals, based on the findings of previous studies that conducted the dose-response experiments [12,32]. Hormesis is a term for the stimulatory effects caused by a low concentration of the toxic agent. Hormesis phenomenon in M. aeruginosa was also observed in this study at low concentrations of phenol, but it exhibited a dose-response effect when phenolic concentration increased, showing a significant inhibition in growth rate. However, C. pyrenoidosa grew well despite the increase in phenolic concentration. The ecotoxicity of phenol occurs from the damage to cell membranes via hydrophobic interaction with lipid bilayer structures [33], and phenol could also penetrate cells and damage inner systems, such as endoplasmic reticulum, nuclei, and their components [10]. Moreover, the reactivity of phenol with biomolecules is related to the ease with which it donates free electrons to oxidized substrates and the oxidative stress caused by free radicals and reactive oxygen species (ROS), such as superoxide radicals or hydrogen peroxide [10].

In co-cultures, the growth of M. aeruginosa was inhibited even at low concentration (20 μg mL⁻¹) of phenol, and its EC₅₀ is shown in Table 2. After 22 days, M. aeruginosa established dominance in 0, 2, and 20 μg mL⁻¹ treatment groups. In contrast, cell concentrations of C. pyrenoidosa were significantly higher than those in the control in all but the 2 μg mL⁻¹ treatment group. Moreover, its cell concentration in 200 μg mL⁻¹ group was about twice that in the co-cultures without phenol. Thus, C. pyrenoidosa showed high resistance and strong competitiveness under phenolic stress (Figure 1).

3.2. Growth Parameters and Inflection Points

Growth parameters of M. aeruginosa and C. pyrenoidosa in mono-cultures and co-cultures are presented in

Table 3. Logistic equation parameters for two species in mono- and co-cultures.

Species	Culture Type	Phenol Treatment (μg mL−1)	K (* 105 cells mL−1)	a	r	R2	Tp (day)
M. aeruginosa	mono-culture	0	408.1	5.73	0.41	0.96	13.9
		2	433.6	5.71	0.41	0.95	13.9
		20	401.2	5.71	0.43	0.98	13.3
		200	128.6	5.78	0.40	0.98	14.5
	co-culture	0	348.8	5.55	0.37	0.98	15.0
		2	268.8	5.17	0.37	0.96	14.0
		20	283.6	5.52	0.38	0.98	14.5
		200	41.4	4.00	0.22	0.95	18.2
C. pyrenoidosa	mono-culture	0	281.8	4.25	0.43	0.96	9.8
		2	301.6	4.44	0.45	0.98	9.9
		20	450.6	4.98	0.49	0.98	10.2
		200	433.6	5.36	0.48	0.97	11.2
	co-culture	0	133.4	3.22	0.41	0.95	7.9
		2	139.6	3.25	0.36	0.98	9.0
		20	153.2	3.61	0.37	0.97	9.8
		200	279.1	4.28	0.39	0.92	11.0

Note: R² is the determinant coefficient of regression, K is the carrying capacity, a is a constant, and r is the intrinsic growth rate.

. Given that the coefficient of determination (R²) exceeded 0.9 for each treatment for both culture types, it implies that the logistic equation (Equation (1)) nicely fitted the growth curves in Figure 1. The carrying capacity (K), intrinsic growth rate (r), and initiation of inhibition (T_p) of C. pyrenoidosa in co-cultures were lower than those in mono-cultures. For M. aeruginosa, the carrying capacity (K) and the intrinsic growth rate (r) in mono-cultures were higher than those in co-cultures of all groups (Table 3). However, the T_p for M. aeruginosa in co-cultures appeared sooner than that in mono-cultures (Table 3).

In co-cultures, the competitive inhibition parameters α (C. pyrenoidosa against M. aeruginosa) and β (M. aeruginosa against C. pyrenoidosa) were calculated based on the data in Table 3, according to Equations (3) and (4). Averages of the competitive inhibition parameters after the occurrence of inflection points are shown in

Table 4. Competitive coefficients of M. aeruginosa and C. pyrenoidosa in co-cultures.

Phenol Treatment (μg mL−1)	α	β
0	−1.26 ± 0.12	1.75 ± 0.07
2	−0.84 ± 0.08 n	1.58 ± 0.22
20	−0.94 ± 0.18 n	−0.60 ± 0.05
200	−1.12 ± 0.26	−2.19 ± 0.32

Note: α is the competitive parameter of C. pyrenoidosa against M. aeruginosa, while β is that of M. aeruginosa against C. pyrenoidosa; n means there is no significant difference between the treatment and the control.

. The value of β was 1.75 ± 0.07 (while α was -1.26 ± 0.12) in the co-cultures with no phenol. Interestingly, β slightly dropped when phenol was added. Furthermore, when phenol reached 20 μg mL⁻¹, β was below zero. This indicated that the interspecific competition between M. aeruginosa and C. pyrenoidosa had been altered by phenol. In co-cultures, M. aeruginosa established dominance in 0, 2, and 20 μg mL⁻¹ treatment groups, but C. pyrenoidosa became the dominant species in the 200 μg mL⁻¹ group. In the low-concentration groups (0, 2, and 20 μg mL⁻¹), phenol concentration was lower than EC₅₀ of M. aeruginosa (80.8 ± 0.16 μg mL⁻¹) and far less than EC₅₀ of C. pyrenoidosa (565.9 ± 0.41 μg mL⁻¹). Under these conditions, M. aeruginosa could maintain a higher growth rate and longer exponential phase compared with C. pyrenoidosa (Figure 1 and Table 3). While, in the highest group (200 μg mL⁻¹), phenol inhibited the growth of M. aeruginosa markedly, but C. pyrenoidosa vigorously resisted phenolic stress. Phenol could be metabolized as an organic carbon source for C. pyrenoidosa [3]. Thus, a high concentration of phenol overturned their interspecific competition.

3.3. Photosynthetic Activities of Two Algae in Mono-Cultures

To further investigate the different responses of two algae to phenol, photosynthetic activities were analyzed in mono-cultures. Algal Chl a fluorescence is one of the sensitive, non-invasive, and efficient methods to detect cellular responses to pollutants. Analyses on Chl a fluorescence induction curves contributed to the evaluation on photosynthetic electron transport chain, which provides valuable information between the inflow and outflow of energy flux in PSII [34,35,36]. In this study, Chl a fluorescence was measured in mono-cultures on the fourth day. JIP-test parameters of M. aeruginosa (Figure 2a) showed considerable changes compared to the parameters of C. pyrenoidosa (Figure 2b).

F_v/F_m is a useful parameter to indicate the maximal photochemical efficiency of PSII in algal cells after dark adaptation, which is related to the probability that an absorbed photon would be trapped by the reaction center (RC), resulting in the reduction of primary plastoquinone (Q_A) pool [23]. Values of F_v/F_m in M. aeruginosa cells were significantly reduced (p < 0.05) in 20 and 200 μg mL⁻¹ treatment groups, with the 200 μg mL⁻¹ group showing a decreasing of more than 50%. However, for C. pyrenoidosa, F_v/F_m value decreased slightly in the 200 μg mL⁻¹ group only (Figure 2).

Under normal conditions, reactive oxygen species (ROS) are produced at a lower rate. However, some pollutants lead to a dramatic increase in ROS production, which reduces the number of active reaction centers or causes the light-harvesting complexes (LHCs) to detach from the core of PSII [24,37]. For M. aeruginosa, ABS/RC, a measurement of the average absorption per active RC or the average amount of absorbing chlorophylls per active RC [23], significantly increased at 200 μg mL⁻¹ phenol. It has been suggested that the inactivation of RC can account for the increase of ABS/RC [38]. Moreover, we found that the sharpest decrease of F_v/F₀ (44%) resulted from the reduction in the ratio of active and inactive reaction centers of PSII (Figure 2a). This might have occurred due to the transformation, which turned some of the active RC to ‘silent RC’ (RC ^si). The RC ^si have two characteristics: (a) these centers can neither reduce Q_A nor back transfer their excitation energy to the antenna. Hence the corresponding PSII units do not contribute to the variable fluorescence, and their fluorescence yield constantly remains at low levels and is equal to those of units with open RC; and (b) they are re-activated as soon as the stress that provoked the conformational modification ceases [34]. The percentage of treated algae’s RC^si compared to the control group was calculated using the following equation [23].

$${{\displaystyle RC}}^{si}=[1-\frac{{(ABS/RC)}^c}{(ABS/RC)}]\times 100\%=\{1-\frac{{(M_0/V_j)}^c}{(M_0/V_j)}\times \frac{[1-(F_0/F_m)]}{{[1-(F_0/F_m)]}^c}\}\times 100\%$$

(5)

where RC is the reaction center (RC in the control is signed with a superscript ‘c’, inactive or silent RC is shown with a superscript ‘si’). Other terms in the equation are listed in Table 1.

For M. aeruginosa, the percentage of RC ^si increased with the concentration of phenol, and there were significant differences between the treatments and the control (p < 0.05; Figure 3). Therefore, the reduction of active RC contributed to the decrease of F_v/F₀ ratio. Meanwhile, the increased RC^si could explain the significant augmentation of ABS/RC and DI₀/RC, as it increased by 37% and 62% in the 200 μg mL⁻¹ group, respectively (Figure 2a). However, the percentage of RC^si in C. pyrenoidosa cells only increased by 13.2% in 200 μg mL⁻¹ group (Figure 3). Similarly, the electron transport from Q_A to Q_B flux per RC (ET₀/RC) and the electron transport probability (ET₀/TR₀) decreased under the stress of phenol [38]. As to M. aeruginosa, the ET₀/RC and ET₀/TR₀ decreased significantly in 20 and 200 μg mL⁻¹ groups (Figure 2a). For C. pyrenoidosa, there was a significant difference (p < 0.05) between the 200 μg mL⁻¹ treatment and the control group, as for the 200 μg mL⁻¹ group, ET₀/RC and ET₀/TR₀ decreased by 20% and 10%, respectively (Figure 2b).

To determine the inhibiting site in the electron transport chain, the fraction of oxygen-evolving complex (OEC) of the treated samples was calculated, and results showed that fraction of OEC remained unchanged in all treated groups. This suggests that electron transport on the donor side of PSII was not affected by phenol. In addition, the decrease of the parameter F_v/F₀ also indicates an alteration in the acceptor side of the PSII complex [39]. Therefore, the acceptor side of PSII in electron transport action was inhibited by phenol, which was similar to the detrimental effects of polycyclic aromatic hydrocarbon on wheat [24]. Furthermore, the decrease of ET₀/RC indicated an inhibition on Q_A⁻, which was similar to artemisinine (act as a kind of algicide to control Microcystis), an inhibitor of the electron flow beyond Q_A⁻ [40,41]. The effects of phenol on PSII were comparable to those of aromatic herbicides (ioxynil). Ioxynil can interact with different amino acid residues on the D1 protein of PSII in cyanobacterium (Synechocystis salina), and inhibit the electron transport from Q_A⁻ to Q_B [39].

Moreover, cyanobacterial cells exhibit an internal thylakoid system organized as a series of roughly parallel double-membrane layers distributed within the cytoplasm, whereas green algae have chloroplasts, which contain an inner membrane system formed by bands of stacked thylakoids (grana) and thylakoids running singly in the stroma [39]. It has also been confirmed that there are differences in the polypeptides composition of OEC and peripheral light-harvesting antenna of PSII between cyanobacteria and green algae [42]. These differences can influence photosynthetic activity and toxicant sensitivity to phenolic contamination.

During the experiment, the abiotic degradation or volatilization of phenol was very slow in the blank control during the experiment (Table S1). However, in treatment groups, the measured values were significantly lower than designed values (p < 0.01), which was due to the cellular adsorption or digestion by physiological metabolism [3]. Especially in C. pyrenoidosa mono-cultures and co-cultures, the dissolved phenol concentrations were markedly lower than those in M. aeruginosa mono-cultures (p < 0.05). A previous study found that phenol could be metabolized as an organic carbon source for C. pyrenoidosa [3]. Further studies will focus on the distribution and digestion of phenol in C. pyrenoidosa cells.

4. Conclusions

In this study, M. aeruginosa established dominance in co-cultures with C. pyrenoidosa when phenol was below or equal to 20 μg mL⁻¹. However, C. pyrenoidosa was the dominant species at 200 μg mL⁻¹ of phenol. This means that phenolic pollution could overturn the competition between M. aeruginosa and C. pyrenoidosa. M. aeruginosa was more sensitive to phenol because its photosynthetic activity was inhibited in the acceptor side of electron transport chain and the number of active reaction centers reduced significantly.