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Synergistic and antagonistic interactions among five allelochemicals with antialgal effects on bloom-forming Microcystis aeruginosa
Ecological Engineering 97 (2016) 486–492
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Synergistic and antagonistic interactions among five allelochemicals with antialgal effects on bloom-forming Microcystis aeruginosa Shengpeng Zuo ∗ , Shoubiao Zhou, Liangtao Ye, Sumin Ma College of Environmental Science and Engineering, Anhui Normal University, Wuhu, 241002, PR China
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Article history: Received 24 October 2015 Received in revised form 19 July 2016 Accepted 5 October 2016 Available online 18 October 2016 Keywords: Allelochemical Allelopathic interaction Antialgal effect Laboratory modelling Microcystis aeruginosa
a b s t r a c t In this study, we investigated the allelopathic interactions among five representative allelochemicals at different proportions using bloom-forming Microcystis aeruginosa as the test receptor. Binary or ternary mixtures of allelochemicals obtained three types of allelopathic interactions, i.e., synergistic, antagonistic, and additive effects. However, combinations of four or five allelochemicals only yielded antagonistic effects. Interestingly, the algal inhibition gradually increased with the tested period for all treatments. For instance, the synergistic interaction occurred with the mixture including coumarin + -hydroxybenzoic acid at 80%:20%; the mixture on the 10th day showed 0.80 of algal inhibition. While the mixture comprised protocatechuic acid + stearic acid + -aminobenzene-sulfonic acid at 33.3%:33.3%:33.3%, the additive interactions occurred and then the maximum algal inhibition (0.83) was acquired at the end of tested period. In conclusion, the joint effects of different allelochemicals depend on various factors such as the chemicals used, their respective proportions, the total concentration of the mixture, and the receptor species. Thus, it is necessary to consider the complexity of allelopathic interactions and the field conditions during the control and management of noxious cyanobacteria. © 2016 Elsevier B.V. All rights reserved.
1. Introduction Allelopathy is a chemical cross-talk between plants or microorganisms in their vicinity (Kato-Noguchi and Ino, 2013). For example, the aquatic macrophytes have been shown to suppress phytoplankton growth, but the cyabacterium Microcystis aeruginosa by itself also produces cyanotoxins that have allelopathic effects on the hydrophytes, algae and diatoms (Ger et al., 2016; Nakai et al., 2014). Thus, allelopathic interactions have attracted considerable attention from researchers. At the species level, allelopathic antagonistic interactions are widespread in nature, such as the allelopathic interactions between crops and weeds, or those between woody plants and crops, or macrophytes and water-bloom algae (Oliveros-Bastidas et al., 2014; Kumar and Vimala, 2008; Mulderij et al., 2007). Thus, KatoNoguchi and Ino (2013) discovered that momilactone B in rice can induce and increase allelopathy in barnyard grass; however, barnyard grass also produces defensive chemical(s) in response to allelopathic rice. In addition, Nupur and Trivedi (2011) found that the roots, stems and leaves of Parthenium hysterophorus Linn., Cassia
∗ Corresponding author at: College of Environmental Science and Engineering, Anhui Normal University, 189 South Jiuhua Road, Wuhu, 241002, PR China. E-mail address: [email protected] (S. Zuo). http://dx.doi.org/10.1016/j.ecoleng.2016.10.013 0925-8574/© 2016 Elsevier B.V. All rights reserved.
tora Linn., and Croton bonplandianum Baill. have allelopathic potential, where they have allelopathic effects on each other. Mulderij et al. (2009) discovered that allelopathic interactions between Stratiotes aloides and filamentous algae, mainly Cladophera Kutzing and Spirogyra Link, did occur under natural conditions, but nutrient competition between the two can also be an important influence factor. Moreover, Kirpenko (2009) elucidated the allelopathic interactions between algae in various ecological mixtures, which showed that the allelopathic interactions were influenced by the intensity of growth and photosynthesis by the algae. Therefore, to remove harmful weeds from agricultural ecosystems and noxious algae from eutrophic lakes, it would be useful to consider the specific efficiency of bio-control agents based on allelopathic antagonistic interactions. Many studies have detected allelopathic synergistic interactions in natural ecosystems. For example, Zuo et al. (2015) discovered that predatory zooplankton can enhance the algal inhibition of allelopathic aquatic macrophytes. It resulted from phenotypic and genotypic adaptation and improving tolerance of the zooplankton while increasing exposure to blooms (Ger et al., 2014). In another study, Zuo et al. (2014) performed field and laboratory tests, which showed that many co-existing aquatic plants have synergistic effects on algal inhibition. In addition, Barto et al. (2010) found that arbuscular mycorrhizal fungi can protect the native
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plant Impatiens pallida from the allelopathic effects of an invader Alliaria petiolata. Synergistic interactions may be related to the combined effect of various functional chemicals (Singh et al., 2003), but no previous studies have focused on the additive effects of allelopathic species. In fact, the allelopathic interactions among organisms are actually due to the interactions among allelochemicals. At the allelochemical level, it is necessary to consider the active chemicals produced by species and their allelopathic synergistic interactions. For example, Chugh and Bharti (2014) demonstrated that the combined fractions collected from Emblica officinalis were more effective against two test pathogens (Fusarium oxysporum and Rhizoctonia solani) than each separate fraction. Thus, the isolated bioactive constituents had a synergistic effect when combined with other chemical constituents present in the fraction. Zhu et al. (2010) found that the submerged macrophyte (Myriophyllum spicatum) could produce allelopathic polyphenols, i.e., pyrogallic acid, gallic acid, ellagic acid, and (+)-catechin, which exhibited synergistic interactions as well as additive interactions in suppressing cyanobacteria. Park et al. (2006) detected a synergistic effect on algal growth inhibition when two or three phenolic compounds from rice straw were added. However, there has been little previous research into the allelopathic interactions among four or more allelochemicals. Furthermore, allelochemical interactions depend on many factors such as the receptor, the respective proportions of allelochemicals, and the abiotic or biotic conditions. All of these factors mean that allelochemical interaction profiles are rather complex. Nakai et al. (2012) reported that the addition of the polyphenols and fatty acids would inhibit the growth of M. aeruginosa, and the interaction of the polyphenols and fatty acids was additive. Moreover, when the collective activity of a mixture of the polyphenols, i.e., ellagic, gallic and pyrogallic acids and (+) − catechin, was examined, the synergistic growth inhibition of M. aeruginosa occurred (Nakai et al., 2000). In the present study, we assessed the allelopathic interactions among five typical allelochemicals based on their effects on algal inhibition. In particular, we compared the allelopathic interactions between two, three, four, and five allelochemicals. We also considered the test receptor, the total concentration of the mixture of allelochemicals, the respective proportions of allelochemicals, and the types of allelochemicals.
2. Materials and methods 2.1. Algal species and typical allelochemicals An axenic strain of Microcystis aeruginosa was provided by the Freshwater Algae Culture of Hydrobiology Collection, China. The unialgal inoculants was cultured in sterilized 942 Medium (See the Supplementary material) under irradiance at 70 mol photons/m2 /s, with a photoperiod of 12 h light/12 h dark and a temperature cycle of 25 ◦ C light/20 ◦ C dark in a temperature-conditioned growth chamber. All of the flasks containing microalgae, with the lid by Millipore filter, were shaken manually twice each day at a set time. The microalgae were cultured to the exponential phase before subsequent inoculation. The initial M. aeruginosa cell density used in the experiments was approximately 5.5 × 105 cells/mL. The culture conditions in the following experiments were the same as those described by Ye et al. (2014) unless stated otherwise. In this study, we tested five typical allelochemicals that we identified previously in the allelopathic exotic plant Alternanthera philoxeroides (Mart.) Griseb. (Zuo et al., 2012), i.e., coumarin, CO; -hydroxybenzoic acid, HA; protocatechuic acid, PA; stearic acid,
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SA; -aminobenzene-sulfonic acid; AA). We obtained these five allelochemicals from Bangcheng Chemical Co. Ltd, Shanghai, China. 2.2. Algal treatments with allelochemicals Exponential phase M. aeruginosa was subjected to the following five treatments: (1)–(5). After adding the allelochemical or mixture of allelochemicals only once, the algal density was recorded every 2 days, i.e., 2, 4, 6, 8, and 10 days. No chemical addition was set as the control. All treatments repeat thrice. (1) We added each allelochemical to the algal culture medium, where the concentrations were set at: 0.1, 0.2, 0.4, 0.8, or 1.0 mg/L for CO or HA; and 1, 2, 4, 8, or 10 mg/L for PA, SA, or AA. A positive inhibitory effect of concentration (a dose-response relationship) was detected in the present study. The half maximal inhibitory concentration (IC50 ) was 0.4 mg/L for CO and HA, whereas the IC50 was 4 mg/L for PA, SA, and AA. (2) Two of the five allelochemicals were combined into a mixture, i.e., four mixtures that comprised CO + HA, PA + SA, PA + AA, and SA + AA were tested. Each mixture was tested at five ratios. (3) Three of the five allelochemicals were combined into a mixture, where only one mixture was tested, i.e., PA + SA + AA. This mixture was tested at seven ratios. (4) Four of the five allelochemicals were combined into a mixture, where only one mixture was tested, i.e., CO + HA + SA + AA. The mixture was tested at five ratios. (5) All five allelochemicals were combined into a single mixture, i.e., CO + HA + PA + SA + AA. The mixture was tested at four ratios. All five treatments above mentioned were shown in Table 1. 2.3. Statistical treatments 2.3.1. Actual and theoretical algal inhibition rates The effects of different treatments on the growth of the test microalgae were expressed as the algal inhibition rate (IR), which is defined by the following equation: 1-
N N0
(1)
where N and N0 are the cell density (cells/mL) in the treatment and the control, respectively. For treatment (1), IR was calculated using Eq. (1). For treatment (2), the actual IR value was calculated using the IR formula and the theoretical value was determined with Eq. (2):
2 i=1
2 i=1
IRi,k × Percentagei
(2)
Percentagei = 1
where IRi,k is the actual IR value at concentration k for allelochemical i. In Eq. (3), k = 0.4 for CO + HA, and k = 4 for PA + SA, SA + AA, or AA + PA. For treatment (3), the actual IR value was calculated using the IR formula and the theoretical value was determined with Eq. (3):
3 i=1
3 i=1
IRi,4 × Percentagei
(3)
Percentagei = 1
where IRi,4 is the actual IR value at a concentration of 4 g/L for allelochemical i. In Eq. (3), the theoretical value was determined for PA + SA + AA.
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Table 1 Five treatments applied to exponential phase M. aeruginosa. Treatment
Combination
(1)
HA PA SA CO 1, 2, 4, 8, 10 mg/L 0.1, 0.2, 0.4, 0.8, 1.0 mg/L CO + HA PA + SA PA + AA 80%:20%, 20%:80%, 50%:50%, 60%:40%, 40%:60% 4 mg/L total concentration 0.4 mg/L total concentration PA + SA + AA 20%:40%:40%, 40%:20%:40%, 40%:40%:20%, 50%:25%:25%, 25%:50%:25%, 25%:25%:50%, 33.3%:33.3%:33.3% 4 mg/L total concentration CO + HA + SA + AA (80% + 20%): (50% + 50%): (60% + 40%): (80% + 20%): (80% + 20%) (20% + 80%) (50% + 50%) (60% + 40%) (0.4 mg/L + 4 mg/L) total concentration CO + HA + PA + SA + AA (40% + 60%): (80% + 20%): (80% + 20%):(25% + 50% + 25%) (25% + 50% + 25%) (20% + 40% + 40%) (0.4 mg/L + 4 mg/L) total concentration
(2)
(3)
(4)
(5)
For treatment (4), the actual IR value was calculated using the IR formula and the theoretical value was determined with Eq. (4):
2 i=1
2 i=1
2 j=1
IRi,0.4 × Percentagei +
2 j=1
IRj,4 × Percentagej
i=1
SA + AA
(60% + 40%): (40% + 60%)
(40% + 60%): (20% + 40% + 40%)
or five allelochemicals. These differences between different treatments from the same combination were marked by small letters in the concerned figures.
(4) 3. Results
Percentagei = 1
3.1. Effects of the five individual allelochemicals on algal inhibition
Percentagej = 1
where IRi,0.4 is the actual IR value at a concentration of 0.4 g/L for allelochemical i, e.g., CO and HA. IRj,4 denotes the actual IR value at a concentration of 4 g/L for allelochemical i, e.g., SA and HA. In Eq. (4), the theoretical value was determined for CO-HA- SAAA. For treatment (5), the actual IR value was calculated using the IR formula and the theoretical value was determined with Eq. (5):
2
AA
IRi,0.4 × Percentagei +
3 j=1
IRj,4 × Percentagej
For the five allelochemicals, IR increased with the test concentration and the culture period (Fig. 1). Thus, there was a significant dose-response relationship between the allelochemical concentration and IR (p < 0.05). Based on IC50 , algal inhibition increased in the following order among the five allelochemicals: PA < AA < SA < CO < HA. At the test concentrations, all five allelochemicals obtained strong algal inhibition, which ranged among 8–100%. In particular, at concentrations of 0.4 g/L for CO and HA, and 4 g/L for PA, SA, and AA, the mean IR value was 50% (IC50 ).
(5)
2i=1 Percentagei = 1 3j=1 Percentagej = 1 where IRi,0.4 is the actual IR value at a concentration of 0.4 g/L for allelochemical i, e.g., CO and HA. IRj,4 denotes the actual IR value at a concentration of 4 g/L for allelochemical i, e.g., PA, SA, and HA. In Eq. (5), the theoretical value was determined for CO-HA- PASA-AA. 2.3.2. Allelopathic interactions with combinations of allelochemicals l If the actual IR value > the theoretical IR value, then this indicated an allelopathic synergistic interaction. l If the actual IR value = the theoretical IR value, then this indicated an allelopathic additive interaction. l If the actual IR value < the theoretical IR value, then this indicated an allelopathic antagonistic interaction. 2.3.3. Statistical analyses The results were analyzed using JMP 5.0.1 and SPSS 15.0. We calculated the mean values and standard deviations based on multiple replicates per treatment (n = 3). Significant differences between the treatment mixtures and the control were determined using one-way analysis of variance (p < 0.05). Meanwhile the multiple (post hoc) tests were carried out mainly for the mixtures of four
3.2. Allelopathic interactions among pairs of allelochemicals In the treatments using mixtures of two allelochemicals, the allelopathic interaction depended on the specific chemicals and their proportions (Fig. 2), i.e., (1) the synergistic interactions occurred with mixtures of CO + HA at proportions of 80%:20% and 60%:40%, PA + SA and SA + AA at proportions of 20%:80% and 40%:60%, and PA + AA at proportions of 80%:20% and 40%:60%; (2) the additive interaction occurred with the mixture of PA + AA at 50%:50%; (3) the antagonistic interactions occurred with mixtures of CO + HA at proportions of 20%:80% and 40%:60%, PA + SA and SA + AA at proportions of 80%:20%, 50%:50%, and 60%:40%, and PA + AA at proportions of 20%:80% and 40%:60%. 3.3. Allelopathic interactions among three allelochemicals For the mixtures of three allelochemicals, the allelopathic interaction depended on the chemicals, their proportions, and the culture period (Fig. 3). The allelopathic interactions were synergistic for PA + SA + AA at proportions of 25%:50%:25% and 20%:40%:40%. However, the allelopathic interactions were antagonistic at proportions of 50%:25%:25% and 25%:25%:50%, whereas the additive interaction occurred at a proportion of 33.3%:33.3%:33.3%. The allelopathic interactions with PA-SA-AA were complex at proportions of 40%:20%:40% and 40%:40%:20%, with an antagonistic interaction in the first 4 days after adding the allelochemicals, which was then followed by a synergistic interaction.
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Fig. 1. Algal inhibition potential of individual allelochemical. (a) Coumarin, CO; (b) -hydroxybenzoic acid, HA; (c) protocatechuic acid, PA; (d) stearic acid, SA; (e) aminobenzene-sulfonic acid, AA. The algal inhibition rate is expressed as the mean ± standard deviation.
3.4. Allelopathic interactions among four and five allelochemicals The combinations of four and five allelochemicals yielded only antagonistic interactions. For these allelochemical mixtures, the antagonistic interaction declined gradually throughout the culture period, whereas algal inhibition increased with time (Fig. 4). For the mixtures containing four or five allelochemicals, no proportions caused allelopathic synergistic interactions. Interestingly, although the total concentration was kept constant, the combinations with four allelochemicals obtained stronger algal inhibition than the combinations with five allelochemicals. The maximum algal inhibition occurred using the mixture of four allelochemicals with 50%:50% CO + HA and 50%:50% SA + AA. Similarly, the mixture of five allelochemicals at 40%:60% CO-HA and 25%:50%:25% PA + SA + AA had the weakest antagonistic effect, but the maximum algal inhibition among the four mixtures.
alpha-linolenic acid, and stearic acid to inhibit the growth of M. aeruginosa, Chlorella pyrenoidosa, Scenedesmus obliquus, and Selenastrum capricornutum. However, the inhibitory or stimulatory effects of allelochemicals on phytoplankton depend on the allelochemical type and the corresponding concentration, and other factors like the availability of nutrients. For example, in the present study, at a low dose of 0.4 mg/L, CO and HA obtained 50% algal inhibition, whereas the IC50 was 4 mg/L for PA, SA, and AA. Some studies reported the concerned mechanism of algal inhibition by allelopathic mcarophytes. For instance, polyphenolic acids can suppress the photosystem and thus photosynthesis by algal cells (Leu et al., 2002), whereas ethyl 2-methylacetoacetate causes metal ion leakage from algal cells, thereby decreasing the activities of antioxidant enzymes such as superoxide dismutase and peroxidase (Li and Hu, 2005).
4.2. Allelopathic interactions among two or more allelochemicals 4. Discussion 4.1. Concentration-dependent algal inhibition by allelochemicals In the present study, it was discovered that the algal inhibition potential of allelopathic aquatic plants was related to allelochemicals isolated and identified. Simiarly, Wang et al. (2014) proposed that the submerged macrophyte Elodea nuttallii can release dihydroactinidiolide, beta-ionone, pentadecanoic acid, linoleic acid,
In the present study, we have detected three allelopathic interactions, i.e., synergistic, antagonistic, and additive effects. Jia et al. (2006) also detected three allelopathic interactions based on the combined effects of benzoxazinone derivatives and phenolic acids. Similarly, Barbehenn and Kochmanski (2013) found no support for the hypothesis that combinations of phenolic compounds have synergistic effects. In the present study, we demonstrated that the type of allelopathic interaction depend on various factors such as the
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Fig. 2. Algal inhibition potential using combinations of two allelochemicals. Note: CO: coumarin; HA: -hydroxybenzoic acid; PA: protocatechuic acid; SA: stearic acid; AA: -aminobenzene-sulfonic acid. The algal inhibition rate is expressed as the mean ± standard deviation.
Fig. 3. Algal inhibition potential with combinations of three allelochemicals. Note: CO: coumarin; HA: -hydroxy-benzoic acid; PA: protocatechuic acid; SA: stearic acid; AA: -aminobenzene-sulfonic acid. The algal inhibition rate is expressed as the mean ± standard deviation.
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Fig. 4. Algal inhibition potential using combinations of four and five allelochemicals. Note: CO: coumarin; HA: -hydroxybenzoic acid; PA: protocatechuic acid; SA: stearic acid; AA: -aminobenzene-sulfonic acid. (a) Four allelochemicals: CO + HA + SA + AA; (b) five allelochemicals: CO + HA + PA + SA + AA. Treatments 1, 2, 3, 4, and 5 are: CO + HA: SA + AA at 80% + 20%:80% + 20%, 80% + 20%:20% + 80%, 50% + 50%:50% + 50%, 60% + 40%:60% + 40%, and 60% + 40%:40% + 60%, respectively. Treatments 6, 7, 8, and 9 are CO + HA: PA + SA + AA at 80% + 20%:25% + 50% + 25%, 80% + 20%:20% + 40% + 40%, 40% + 60%:25% + 50% + 25%, and 40% + 60%:20% + 40% + 40%, respectively. The algal inhibition rate is expressed as the mean ± standard deviation. Different small letters indicated significant differences between different treatments from the same combination at some proportion at p < 0.05.
chemicals used, their respective proportions, the total concentration of the mixture, and the receptor species. The efficient control of harmful weeds, insects, and algae has been studied intensively to understand synergistic allelopathic interactions. For example, An et al. (2012) isolated many fractions from the essential oils of Eucalyptus species and found that they had synergistic allelopathic effects on their receptors. Zhang et al. (2009) also demonstrated the synergistic inhibitory effects of a combination of three fatty acids, i.e., (Z, Z)-9,12-octadecadienoic (18:2), tetradecanoic (14:0), and hexadecanoic acids (16:0), on the growth of toxic M. aeruginosa. Interestingly, Leao et al. (2010) found that exudates from the freshwater cyanobacterium Oscillatoria sp. had a synergistic inhibitory effect on the green microalga Chlorella vulgaris.
4.3. Comparison of the laboratory experiments and field studies In eutrophic water bodies, the water bloom may comprise cyanobacteria, green algae, and other organisms (Qin et al., 2015). In the present study, M. aeruginosa was the only receptor and thus the allelopathic interactions between allelochemicals require further study using other species of algae. Furthermore, there is a high diversity of algal species as well as aquatic macrophytes in the field (Thiebaut and Muller, 1998), where these macrophytes release large amounts of bio-active chemicals at different concentrations and proportions in mixtures (Hilt et al., 2006). Thus, allelopathic interactions between algicides from allelochemicals should be fully proved in the microcosm or mesocosm. And then the synergistic or additive effects between allelochemicals were efficiently applied during algal control in the field. The IC 50 is an important indicator for measuring the algal inhibition potential. In our study,
we demonstrated that different allelochemicals had different 50% inhibitory doses for the receptor species during the 10-day culture period and these findings are consistent with those reported by Mardani et al. (2015). In the future, it is very necessary to explore the practical interactions between allelochemicals exuded from representative macrophytes with algal inhibition potential in the field. Acknowledgments We thank Hui Mei and Kun Wan PhD for their assistance with the experiments. We also acknowledge Dr. Duncan E. Jackson for revising and editing our manuscript. This study was supported by the Natural Science Research Project of Anhui Province of China for Universities (KJ2015A122), Key Projects of The Outstanding Young Talents in Colleges and Universities (gxyqZD2016024), and China Scholarship Council ([2012]3022), Anhui Province, and Ministry of Human Resources and Social Security of the People’s Republic of China (MOHRSS) for studying abroad (013). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.ecoleng.2016.10. 013. References An, M., Wu, H., Liu, D.L., Stanton, R., Zhang, J., 2012. Chemical composition of essential oils of four Eucalyptus species and their phytotoxicity on silverleaf
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nightshade (Solanum elaeagnifolium Cav) in Australia. Plant Growth Regul. 68, 231–237. Barbehenn, R.V., Kochmanski, J., 2013. Searching for synergism: effects of combinations of phenolic compounds and other toxins on oxidative stress in Lymantria dispar caterpillars. Chemoecology 23, 219–231. Barto, K., Friese, C., Cipollini, D., 2010. Arbuscular mycorrhizal fungi protect a native plant from allelopathic effects of an invader. J. Chem. Ecol. 36, 351–360. Chugh, C.A., Bharti, D., 2014. Chemical characterization of antifungal constituents of Emblica officinalis. Allelopathy J. 34, 155–178. Ger, K.A., Hansson, L.A., Lurling, M., 2014. Understanding cyanobacteria-zooplankton interactions in a more eutrophic world. Freshw. Biol. 59, 1783–1798. Ger, K.A., Faassen, E.J., Pennino, M.G., Lurling, M., 2016. Effect of the toxin (microcystin) content of Microcystis on copepod grazing. Harmful Algae 52, 34–45. Hilt, S., Ghobrial, M.G.N., Gross, E.M., 2006. In situ allelopathic potential of Myriophyllum verticillatum (Haloragaceae) against selected phytoplankton species. J. Phycol. 42, 1189–1198. Jia, C.H., Kudsk, P., Mathiassen, S.K., 2006. Joint action of benzoxazinone derivatives and phenolic acids. J. Agric. Food Chem. 54, 1049–1057. Kato-Noguchi, H., Ino, T., 2013. The chemical-mediated allelopathic interaction between rice and barnyard grass. Plant Soil 370, 267–275. Kirpenko, N.I., 2009. Allelopathic interaction between algae of various ecological mixtures. Hydrobiol. J. 45, 74–83. Kumar, A.A., Vimala, Y., 2008. Allelopathic interaction of Populus deltoides leaf leachate with some crop plants. J. Ind. Bot. Soc. 87, 237–241. Leao, P.N., Pereira, A.R., Liu, W.T., Ng, J., Pevzner, P.A., Dorrestein, P.C., Konig, G.M., Vasconcelos, V.M., Gerwick, W.H., 2010. Synergistic allelochemicals from a freshwater cyanobacterium. P. Natl. Acad. Sci. U. S. A. 107, 11183–11188. Leu, E., Krieger-Liszkay, A., Goussias, C., Gross, E.M., 2002. Polyphenolic allelochemicals from the aquatic angiosperm Myriophyllum spicatum inhibit photosystem II. Plant Physiol. 130, 2011–2018. Li, F.M., Hu, H.Y., 2005. Isolation and characterization of a novel antialgal allelochemical from Phragmites communis. Appl. Environ. Microb. 71, 6545–6553. Mardani, H., Sekine, T., Azizi, M., Mishyna, M., Fujii, Y., 2015. Identification of safranal as the main allelochemical from saffron (Crocus sativus). Nat. Prod. Commun. 10, 775–777. Mulderij, G., Van Nes, E.H., Van Donk, E., 2007. Macrophyte-phytoplankton interactions: the relative importance of allelopathy versus other factors. Ecol. Modell. 204, 85–92. Mulderij, G., Mau, B., Domis, L.N., Smolders, A.J.P., Van Donk, E., 2009. Interaction between the macrophyte Stratiotes aloides and filamentous algae: does it indicate allelopathy? Aquat. Ecol. 43, 305–312. Nakai, S., Inoue, Y., Hosomi, M., 2000. Myriophyllum spicatum-released allelopathic polyphenols inhibiting growth of blue-green algae Microcystis aeruginosa. Water Res. 34, 3026–3032.
Nakai, S., Zou, G., Okuda, T., Nishijima, W., Hosomi, M., Okada, M., 2012. Polyphenols and fatty acids responsible for anti-cyanobacterial allelopathic effects of submerged macrophyte Myriophyllum spicatum. Water Sci. Technol. 66, 993–999. Nakai, S., Okuda, T., Asaoka, S., 2014. Growth inhibition of Microcystis aeruginosa by allelopathic compounds originally isolated from Myriophyllum spicatum: temperature and light effects and evidence of possible major mechanisms. J. Chem. Eng. Jpn. 47, 488–493. Nupur, N., Trivedi, M.P., 2011. Allelopathic interaction among Parthenium hysterophorus Linn., Cassia tora Linn. and Croton bonplandianum Baill. Biosci. Biotechnol. Res. Asia 8, 265–270. Oliveros-Bastidas, A., Marin, D., Macias, F.A., 2014. Evidence for an allelopathic interaction between rye and wild oats. J. Agric. Food Chem. 62, 9450–9457. Park, M.H., Han, M.S., Ahn, C.Y., Kim, H.S., Yoon, B.D., Oh, H.M., 2006. Growth inhibition of bloom-forming cyanobacterium Microcystis aeruginosa by rice straw extract. Lett. Appl. Microbiol. 43, 307–312. Qin, B.Q., Li, W., Zhu, G.W., Zhang, Y.L., Wu, T.F., Gao, G., 2015. Cyanobacterial bloom management through integrated monitoring and forecasting in large shallow eutrophic Lake Taihu (China). J. Hazard. Mater. 287, 356–363. Singh, H.P., Batish, D.R., Kohli, R.K., 2003. Allelopathic interactions and allelochemicals: new possibilities for sustainable weed management. Crit. Rev. Plant Sci. 22, 239–311. Thiebaut, G., Muller, S., 1998. The impact of eutrophication on aquatic macrophyte diversity in weakly mineralized streams in the Northern Vosges Mountains (NE France). Biodivers. Conserv. 7, 1051–1068. Wang, H.Q., Zhu, H.J., Zhang, L.Y., Xue, W.J., Yuan, B., 2014. Identification of antialgal compounds from the aquatic plant Elodea nuttallii. Allelopathy J. 34, 207–213. Ye, L.T., Qian, J.Z., Jin, S., Zuo, S.P., Mei, H., Ma, S.M., 2014. Algicidal effects of four Chinese herbs extracts on bloom-forming Microcystis aeruginosa and Chlorella pyrenoidosa. Environ. Technol. 35, 1150–1156. Zhang, T.T., He, M., Wu, A.P., Nie, L.W., 2009. Allelopathic effects of submerged macrophyte Chara vulgaris on toxic Microcystis aeruginosa. Allelopathy J. 23, 391–402. Zhu, J.Y., Liu, B.Y., Wang, J., Gao, Y.N., Wu, Z.B., 2010. Study on the mechanism of allelopathic influence on cyanobacteria and chlorophytes by submerged macrophyte (Myriophyllum spicatum) and its secretion. Aquat. Toxicol. 98, 196–203. Zuo, S.P., Ma, Y.Q., Inanaga, S., 2012. Differences in ecological and allelopathic traits among Alternanthera philoxeroides populations. Weed Biol. Manage. 12, 123–130. Zuo, S.P., Wan, K., Ma, S.M., Ye, L.T., 2014. Combined allelopathic potential of aquatic plants species to control algae. Allelopathy J. 34, 315–324. Zuo, S.P., Wan, K., Ma, S.M., 2015. Combined effect of predatory zooplankton and allelopathic aquatic macrophytes on algal suppression. Environ. Technol. 36, 54–59.
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Ecological Engineering journal homepage: www.elsevier.com/locate/ecoleng
Synergistic and antagonistic interactions among five allelochemicals with antialgal effects on bloom-forming Microcystis aeruginosa Shengpeng Zuo ∗ , Shoubiao Zhou, Liangtao Ye, Sumin Ma College of Environmental Science and Engineering, Anhui Normal University, Wuhu, 241002, PR China
a r t i c l e
i n f o
Article history: Received 24 October 2015 Received in revised form 19 July 2016 Accepted 5 October 2016 Available online 18 October 2016 Keywords: Allelochemical Allelopathic interaction Antialgal effect Laboratory modelling Microcystis aeruginosa
a b s t r a c t In this study, we investigated the allelopathic interactions among five representative allelochemicals at different proportions using bloom-forming Microcystis aeruginosa as the test receptor. Binary or ternary mixtures of allelochemicals obtained three types of allelopathic interactions, i.e., synergistic, antagonistic, and additive effects. However, combinations of four or five allelochemicals only yielded antagonistic effects. Interestingly, the algal inhibition gradually increased with the tested period for all treatments. For instance, the synergistic interaction occurred with the mixture including coumarin + -hydroxybenzoic acid at 80%:20%; the mixture on the 10th day showed 0.80 of algal inhibition. While the mixture comprised protocatechuic acid + stearic acid + -aminobenzene-sulfonic acid at 33.3%:33.3%:33.3%, the additive interactions occurred and then the maximum algal inhibition (0.83) was acquired at the end of tested period. In conclusion, the joint effects of different allelochemicals depend on various factors such as the chemicals used, their respective proportions, the total concentration of the mixture, and the receptor species. Thus, it is necessary to consider the complexity of allelopathic interactions and the field conditions during the control and management of noxious cyanobacteria. © 2016 Elsevier B.V. All rights reserved.
1. Introduction Allelopathy is a chemical cross-talk between plants or microorganisms in their vicinity (Kato-Noguchi and Ino, 2013). For example, the aquatic macrophytes have been shown to suppress phytoplankton growth, but the cyabacterium Microcystis aeruginosa by itself also produces cyanotoxins that have allelopathic effects on the hydrophytes, algae and diatoms (Ger et al., 2016; Nakai et al., 2014). Thus, allelopathic interactions have attracted considerable attention from researchers. At the species level, allelopathic antagonistic interactions are widespread in nature, such as the allelopathic interactions between crops and weeds, or those between woody plants and crops, or macrophytes and water-bloom algae (Oliveros-Bastidas et al., 2014; Kumar and Vimala, 2008; Mulderij et al., 2007). Thus, KatoNoguchi and Ino (2013) discovered that momilactone B in rice can induce and increase allelopathy in barnyard grass; however, barnyard grass also produces defensive chemical(s) in response to allelopathic rice. In addition, Nupur and Trivedi (2011) found that the roots, stems and leaves of Parthenium hysterophorus Linn., Cassia
∗ Corresponding author at: College of Environmental Science and Engineering, Anhui Normal University, 189 South Jiuhua Road, Wuhu, 241002, PR China. E-mail address: [email protected] (S. Zuo). http://dx.doi.org/10.1016/j.ecoleng.2016.10.013 0925-8574/© 2016 Elsevier B.V. All rights reserved.
tora Linn., and Croton bonplandianum Baill. have allelopathic potential, where they have allelopathic effects on each other. Mulderij et al. (2009) discovered that allelopathic interactions between Stratiotes aloides and filamentous algae, mainly Cladophera Kutzing and Spirogyra Link, did occur under natural conditions, but nutrient competition between the two can also be an important influence factor. Moreover, Kirpenko (2009) elucidated the allelopathic interactions between algae in various ecological mixtures, which showed that the allelopathic interactions were influenced by the intensity of growth and photosynthesis by the algae. Therefore, to remove harmful weeds from agricultural ecosystems and noxious algae from eutrophic lakes, it would be useful to consider the specific efficiency of bio-control agents based on allelopathic antagonistic interactions. Many studies have detected allelopathic synergistic interactions in natural ecosystems. For example, Zuo et al. (2015) discovered that predatory zooplankton can enhance the algal inhibition of allelopathic aquatic macrophytes. It resulted from phenotypic and genotypic adaptation and improving tolerance of the zooplankton while increasing exposure to blooms (Ger et al., 2014). In another study, Zuo et al. (2014) performed field and laboratory tests, which showed that many co-existing aquatic plants have synergistic effects on algal inhibition. In addition, Barto et al. (2010) found that arbuscular mycorrhizal fungi can protect the native
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plant Impatiens pallida from the allelopathic effects of an invader Alliaria petiolata. Synergistic interactions may be related to the combined effect of various functional chemicals (Singh et al., 2003), but no previous studies have focused on the additive effects of allelopathic species. In fact, the allelopathic interactions among organisms are actually due to the interactions among allelochemicals. At the allelochemical level, it is necessary to consider the active chemicals produced by species and their allelopathic synergistic interactions. For example, Chugh and Bharti (2014) demonstrated that the combined fractions collected from Emblica officinalis were more effective against two test pathogens (Fusarium oxysporum and Rhizoctonia solani) than each separate fraction. Thus, the isolated bioactive constituents had a synergistic effect when combined with other chemical constituents present in the fraction. Zhu et al. (2010) found that the submerged macrophyte (Myriophyllum spicatum) could produce allelopathic polyphenols, i.e., pyrogallic acid, gallic acid, ellagic acid, and (+)-catechin, which exhibited synergistic interactions as well as additive interactions in suppressing cyanobacteria. Park et al. (2006) detected a synergistic effect on algal growth inhibition when two or three phenolic compounds from rice straw were added. However, there has been little previous research into the allelopathic interactions among four or more allelochemicals. Furthermore, allelochemical interactions depend on many factors such as the receptor, the respective proportions of allelochemicals, and the abiotic or biotic conditions. All of these factors mean that allelochemical interaction profiles are rather complex. Nakai et al. (2012) reported that the addition of the polyphenols and fatty acids would inhibit the growth of M. aeruginosa, and the interaction of the polyphenols and fatty acids was additive. Moreover, when the collective activity of a mixture of the polyphenols, i.e., ellagic, gallic and pyrogallic acids and (+) − catechin, was examined, the synergistic growth inhibition of M. aeruginosa occurred (Nakai et al., 2000). In the present study, we assessed the allelopathic interactions among five typical allelochemicals based on their effects on algal inhibition. In particular, we compared the allelopathic interactions between two, three, four, and five allelochemicals. We also considered the test receptor, the total concentration of the mixture of allelochemicals, the respective proportions of allelochemicals, and the types of allelochemicals.
2. Materials and methods 2.1. Algal species and typical allelochemicals An axenic strain of Microcystis aeruginosa was provided by the Freshwater Algae Culture of Hydrobiology Collection, China. The unialgal inoculants was cultured in sterilized 942 Medium (See the Supplementary material) under irradiance at 70 mol photons/m2 /s, with a photoperiod of 12 h light/12 h dark and a temperature cycle of 25 ◦ C light/20 ◦ C dark in a temperature-conditioned growth chamber. All of the flasks containing microalgae, with the lid by Millipore filter, were shaken manually twice each day at a set time. The microalgae were cultured to the exponential phase before subsequent inoculation. The initial M. aeruginosa cell density used in the experiments was approximately 5.5 × 105 cells/mL. The culture conditions in the following experiments were the same as those described by Ye et al. (2014) unless stated otherwise. In this study, we tested five typical allelochemicals that we identified previously in the allelopathic exotic plant Alternanthera philoxeroides (Mart.) Griseb. (Zuo et al., 2012), i.e., coumarin, CO; -hydroxybenzoic acid, HA; protocatechuic acid, PA; stearic acid,
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SA; -aminobenzene-sulfonic acid; AA). We obtained these five allelochemicals from Bangcheng Chemical Co. Ltd, Shanghai, China. 2.2. Algal treatments with allelochemicals Exponential phase M. aeruginosa was subjected to the following five treatments: (1)–(5). After adding the allelochemical or mixture of allelochemicals only once, the algal density was recorded every 2 days, i.e., 2, 4, 6, 8, and 10 days. No chemical addition was set as the control. All treatments repeat thrice. (1) We added each allelochemical to the algal culture medium, where the concentrations were set at: 0.1, 0.2, 0.4, 0.8, or 1.0 mg/L for CO or HA; and 1, 2, 4, 8, or 10 mg/L for PA, SA, or AA. A positive inhibitory effect of concentration (a dose-response relationship) was detected in the present study. The half maximal inhibitory concentration (IC50 ) was 0.4 mg/L for CO and HA, whereas the IC50 was 4 mg/L for PA, SA, and AA. (2) Two of the five allelochemicals were combined into a mixture, i.e., four mixtures that comprised CO + HA, PA + SA, PA + AA, and SA + AA were tested. Each mixture was tested at five ratios. (3) Three of the five allelochemicals were combined into a mixture, where only one mixture was tested, i.e., PA + SA + AA. This mixture was tested at seven ratios. (4) Four of the five allelochemicals were combined into a mixture, where only one mixture was tested, i.e., CO + HA + SA + AA. The mixture was tested at five ratios. (5) All five allelochemicals were combined into a single mixture, i.e., CO + HA + PA + SA + AA. The mixture was tested at four ratios. All five treatments above mentioned were shown in Table 1. 2.3. Statistical treatments 2.3.1. Actual and theoretical algal inhibition rates The effects of different treatments on the growth of the test microalgae were expressed as the algal inhibition rate (IR), which is defined by the following equation: 1-
N N0
(1)
where N and N0 are the cell density (cells/mL) in the treatment and the control, respectively. For treatment (1), IR was calculated using Eq. (1). For treatment (2), the actual IR value was calculated using the IR formula and the theoretical value was determined with Eq. (2):
2 i=1
2 i=1
IRi,k × Percentagei
(2)
Percentagei = 1
where IRi,k is the actual IR value at concentration k for allelochemical i. In Eq. (3), k = 0.4 for CO + HA, and k = 4 for PA + SA, SA + AA, or AA + PA. For treatment (3), the actual IR value was calculated using the IR formula and the theoretical value was determined with Eq. (3):
3 i=1
3 i=1
IRi,4 × Percentagei
(3)
Percentagei = 1
where IRi,4 is the actual IR value at a concentration of 4 g/L for allelochemical i. In Eq. (3), the theoretical value was determined for PA + SA + AA.
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Table 1 Five treatments applied to exponential phase M. aeruginosa. Treatment
Combination
(1)
HA PA SA CO 1, 2, 4, 8, 10 mg/L 0.1, 0.2, 0.4, 0.8, 1.0 mg/L CO + HA PA + SA PA + AA 80%:20%, 20%:80%, 50%:50%, 60%:40%, 40%:60% 4 mg/L total concentration 0.4 mg/L total concentration PA + SA + AA 20%:40%:40%, 40%:20%:40%, 40%:40%:20%, 50%:25%:25%, 25%:50%:25%, 25%:25%:50%, 33.3%:33.3%:33.3% 4 mg/L total concentration CO + HA + SA + AA (80% + 20%): (50% + 50%): (60% + 40%): (80% + 20%): (80% + 20%) (20% + 80%) (50% + 50%) (60% + 40%) (0.4 mg/L + 4 mg/L) total concentration CO + HA + PA + SA + AA (40% + 60%): (80% + 20%): (80% + 20%):(25% + 50% + 25%) (25% + 50% + 25%) (20% + 40% + 40%) (0.4 mg/L + 4 mg/L) total concentration
(2)
(3)
(4)
(5)
For treatment (4), the actual IR value was calculated using the IR formula and the theoretical value was determined with Eq. (4):
2 i=1
2 i=1
2 j=1
IRi,0.4 × Percentagei +
2 j=1
IRj,4 × Percentagej
i=1
SA + AA
(60% + 40%): (40% + 60%)
(40% + 60%): (20% + 40% + 40%)
or five allelochemicals. These differences between different treatments from the same combination were marked by small letters in the concerned figures.
(4) 3. Results
Percentagei = 1
3.1. Effects of the five individual allelochemicals on algal inhibition
Percentagej = 1
where IRi,0.4 is the actual IR value at a concentration of 0.4 g/L for allelochemical i, e.g., CO and HA. IRj,4 denotes the actual IR value at a concentration of 4 g/L for allelochemical i, e.g., SA and HA. In Eq. (4), the theoretical value was determined for CO-HA- SAAA. For treatment (5), the actual IR value was calculated using the IR formula and the theoretical value was determined with Eq. (5):
2
AA
IRi,0.4 × Percentagei +
3 j=1
IRj,4 × Percentagej
For the five allelochemicals, IR increased with the test concentration and the culture period (Fig. 1). Thus, there was a significant dose-response relationship between the allelochemical concentration and IR (p < 0.05). Based on IC50 , algal inhibition increased in the following order among the five allelochemicals: PA < AA < SA < CO < HA. At the test concentrations, all five allelochemicals obtained strong algal inhibition, which ranged among 8–100%. In particular, at concentrations of 0.4 g/L for CO and HA, and 4 g/L for PA, SA, and AA, the mean IR value was 50% (IC50 ).
(5)
2i=1 Percentagei = 1 3j=1 Percentagej = 1 where IRi,0.4 is the actual IR value at a concentration of 0.4 g/L for allelochemical i, e.g., CO and HA. IRj,4 denotes the actual IR value at a concentration of 4 g/L for allelochemical i, e.g., PA, SA, and HA. In Eq. (5), the theoretical value was determined for CO-HA- PASA-AA. 2.3.2. Allelopathic interactions with combinations of allelochemicals l If the actual IR value > the theoretical IR value, then this indicated an allelopathic synergistic interaction. l If the actual IR value = the theoretical IR value, then this indicated an allelopathic additive interaction. l If the actual IR value < the theoretical IR value, then this indicated an allelopathic antagonistic interaction. 2.3.3. Statistical analyses The results were analyzed using JMP 5.0.1 and SPSS 15.0. We calculated the mean values and standard deviations based on multiple replicates per treatment (n = 3). Significant differences between the treatment mixtures and the control were determined using one-way analysis of variance (p < 0.05). Meanwhile the multiple (post hoc) tests were carried out mainly for the mixtures of four
3.2. Allelopathic interactions among pairs of allelochemicals In the treatments using mixtures of two allelochemicals, the allelopathic interaction depended on the specific chemicals and their proportions (Fig. 2), i.e., (1) the synergistic interactions occurred with mixtures of CO + HA at proportions of 80%:20% and 60%:40%, PA + SA and SA + AA at proportions of 20%:80% and 40%:60%, and PA + AA at proportions of 80%:20% and 40%:60%; (2) the additive interaction occurred with the mixture of PA + AA at 50%:50%; (3) the antagonistic interactions occurred with mixtures of CO + HA at proportions of 20%:80% and 40%:60%, PA + SA and SA + AA at proportions of 80%:20%, 50%:50%, and 60%:40%, and PA + AA at proportions of 20%:80% and 40%:60%. 3.3. Allelopathic interactions among three allelochemicals For the mixtures of three allelochemicals, the allelopathic interaction depended on the chemicals, their proportions, and the culture period (Fig. 3). The allelopathic interactions were synergistic for PA + SA + AA at proportions of 25%:50%:25% and 20%:40%:40%. However, the allelopathic interactions were antagonistic at proportions of 50%:25%:25% and 25%:25%:50%, whereas the additive interaction occurred at a proportion of 33.3%:33.3%:33.3%. The allelopathic interactions with PA-SA-AA were complex at proportions of 40%:20%:40% and 40%:40%:20%, with an antagonistic interaction in the first 4 days after adding the allelochemicals, which was then followed by a synergistic interaction.
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Fig. 1. Algal inhibition potential of individual allelochemical. (a) Coumarin, CO; (b) -hydroxybenzoic acid, HA; (c) protocatechuic acid, PA; (d) stearic acid, SA; (e) aminobenzene-sulfonic acid, AA. The algal inhibition rate is expressed as the mean ± standard deviation.
3.4. Allelopathic interactions among four and five allelochemicals The combinations of four and five allelochemicals yielded only antagonistic interactions. For these allelochemical mixtures, the antagonistic interaction declined gradually throughout the culture period, whereas algal inhibition increased with time (Fig. 4). For the mixtures containing four or five allelochemicals, no proportions caused allelopathic synergistic interactions. Interestingly, although the total concentration was kept constant, the combinations with four allelochemicals obtained stronger algal inhibition than the combinations with five allelochemicals. The maximum algal inhibition occurred using the mixture of four allelochemicals with 50%:50% CO + HA and 50%:50% SA + AA. Similarly, the mixture of five allelochemicals at 40%:60% CO-HA and 25%:50%:25% PA + SA + AA had the weakest antagonistic effect, but the maximum algal inhibition among the four mixtures.
alpha-linolenic acid, and stearic acid to inhibit the growth of M. aeruginosa, Chlorella pyrenoidosa, Scenedesmus obliquus, and Selenastrum capricornutum. However, the inhibitory or stimulatory effects of allelochemicals on phytoplankton depend on the allelochemical type and the corresponding concentration, and other factors like the availability of nutrients. For example, in the present study, at a low dose of 0.4 mg/L, CO and HA obtained 50% algal inhibition, whereas the IC50 was 4 mg/L for PA, SA, and AA. Some studies reported the concerned mechanism of algal inhibition by allelopathic mcarophytes. For instance, polyphenolic acids can suppress the photosystem and thus photosynthesis by algal cells (Leu et al., 2002), whereas ethyl 2-methylacetoacetate causes metal ion leakage from algal cells, thereby decreasing the activities of antioxidant enzymes such as superoxide dismutase and peroxidase (Li and Hu, 2005).
4.2. Allelopathic interactions among two or more allelochemicals 4. Discussion 4.1. Concentration-dependent algal inhibition by allelochemicals In the present study, it was discovered that the algal inhibition potential of allelopathic aquatic plants was related to allelochemicals isolated and identified. Simiarly, Wang et al. (2014) proposed that the submerged macrophyte Elodea nuttallii can release dihydroactinidiolide, beta-ionone, pentadecanoic acid, linoleic acid,
In the present study, we have detected three allelopathic interactions, i.e., synergistic, antagonistic, and additive effects. Jia et al. (2006) also detected three allelopathic interactions based on the combined effects of benzoxazinone derivatives and phenolic acids. Similarly, Barbehenn and Kochmanski (2013) found no support for the hypothesis that combinations of phenolic compounds have synergistic effects. In the present study, we demonstrated that the type of allelopathic interaction depend on various factors such as the
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Fig. 2. Algal inhibition potential using combinations of two allelochemicals. Note: CO: coumarin; HA: -hydroxybenzoic acid; PA: protocatechuic acid; SA: stearic acid; AA: -aminobenzene-sulfonic acid. The algal inhibition rate is expressed as the mean ± standard deviation.
Fig. 3. Algal inhibition potential with combinations of three allelochemicals. Note: CO: coumarin; HA: -hydroxy-benzoic acid; PA: protocatechuic acid; SA: stearic acid; AA: -aminobenzene-sulfonic acid. The algal inhibition rate is expressed as the mean ± standard deviation.
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Fig. 4. Algal inhibition potential using combinations of four and five allelochemicals. Note: CO: coumarin; HA: -hydroxybenzoic acid; PA: protocatechuic acid; SA: stearic acid; AA: -aminobenzene-sulfonic acid. (a) Four allelochemicals: CO + HA + SA + AA; (b) five allelochemicals: CO + HA + PA + SA + AA. Treatments 1, 2, 3, 4, and 5 are: CO + HA: SA + AA at 80% + 20%:80% + 20%, 80% + 20%:20% + 80%, 50% + 50%:50% + 50%, 60% + 40%:60% + 40%, and 60% + 40%:40% + 60%, respectively. Treatments 6, 7, 8, and 9 are CO + HA: PA + SA + AA at 80% + 20%:25% + 50% + 25%, 80% + 20%:20% + 40% + 40%, 40% + 60%:25% + 50% + 25%, and 40% + 60%:20% + 40% + 40%, respectively. The algal inhibition rate is expressed as the mean ± standard deviation. Different small letters indicated significant differences between different treatments from the same combination at some proportion at p < 0.05.
chemicals used, their respective proportions, the total concentration of the mixture, and the receptor species. The efficient control of harmful weeds, insects, and algae has been studied intensively to understand synergistic allelopathic interactions. For example, An et al. (2012) isolated many fractions from the essential oils of Eucalyptus species and found that they had synergistic allelopathic effects on their receptors. Zhang et al. (2009) also demonstrated the synergistic inhibitory effects of a combination of three fatty acids, i.e., (Z, Z)-9,12-octadecadienoic (18:2), tetradecanoic (14:0), and hexadecanoic acids (16:0), on the growth of toxic M. aeruginosa. Interestingly, Leao et al. (2010) found that exudates from the freshwater cyanobacterium Oscillatoria sp. had a synergistic inhibitory effect on the green microalga Chlorella vulgaris.
4.3. Comparison of the laboratory experiments and field studies In eutrophic water bodies, the water bloom may comprise cyanobacteria, green algae, and other organisms (Qin et al., 2015). In the present study, M. aeruginosa was the only receptor and thus the allelopathic interactions between allelochemicals require further study using other species of algae. Furthermore, there is a high diversity of algal species as well as aquatic macrophytes in the field (Thiebaut and Muller, 1998), where these macrophytes release large amounts of bio-active chemicals at different concentrations and proportions in mixtures (Hilt et al., 2006). Thus, allelopathic interactions between algicides from allelochemicals should be fully proved in the microcosm or mesocosm. And then the synergistic or additive effects between allelochemicals were efficiently applied during algal control in the field. The IC 50 is an important indicator for measuring the algal inhibition potential. In our study,
we demonstrated that different allelochemicals had different 50% inhibitory doses for the receptor species during the 10-day culture period and these findings are consistent with those reported by Mardani et al. (2015). In the future, it is very necessary to explore the practical interactions between allelochemicals exuded from representative macrophytes with algal inhibition potential in the field. Acknowledgments We thank Hui Mei and Kun Wan PhD for their assistance with the experiments. We also acknowledge Dr. Duncan E. Jackson for revising and editing our manuscript. This study was supported by the Natural Science Research Project of Anhui Province of China for Universities (KJ2015A122), Key Projects of The Outstanding Young Talents in Colleges and Universities (gxyqZD2016024), and China Scholarship Council ([2012]3022), Anhui Province, and Ministry of Human Resources and Social Security of the People’s Republic of China (MOHRSS) for studying abroad (013). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.ecoleng.2016.10. 013. References An, M., Wu, H., Liu, D.L., Stanton, R., Zhang, J., 2012. Chemical composition of essential oils of four Eucalyptus species and their phytotoxicity on silverleaf
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nightshade (Solanum elaeagnifolium Cav) in Australia. Plant Growth Regul. 68, 231–237. Barbehenn, R.V., Kochmanski, J., 2013. Searching for synergism: effects of combinations of phenolic compounds and other toxins on oxidative stress in Lymantria dispar caterpillars. Chemoecology 23, 219–231. Barto, K., Friese, C., Cipollini, D., 2010. Arbuscular mycorrhizal fungi protect a native plant from allelopathic effects of an invader. J. Chem. Ecol. 36, 351–360. Chugh, C.A., Bharti, D., 2014. Chemical characterization of antifungal constituents of Emblica officinalis. Allelopathy J. 34, 155–178. Ger, K.A., Hansson, L.A., Lurling, M., 2014. Understanding cyanobacteria-zooplankton interactions in a more eutrophic world. Freshw. Biol. 59, 1783–1798. Ger, K.A., Faassen, E.J., Pennino, M.G., Lurling, M., 2016. Effect of the toxin (microcystin) content of Microcystis on copepod grazing. Harmful Algae 52, 34–45. Hilt, S., Ghobrial, M.G.N., Gross, E.M., 2006. In situ allelopathic potential of Myriophyllum verticillatum (Haloragaceae) against selected phytoplankton species. J. Phycol. 42, 1189–1198. Jia, C.H., Kudsk, P., Mathiassen, S.K., 2006. Joint action of benzoxazinone derivatives and phenolic acids. J. Agric. Food Chem. 54, 1049–1057. Kato-Noguchi, H., Ino, T., 2013. The chemical-mediated allelopathic interaction between rice and barnyard grass. Plant Soil 370, 267–275. Kirpenko, N.I., 2009. Allelopathic interaction between algae of various ecological mixtures. Hydrobiol. J. 45, 74–83. Kumar, A.A., Vimala, Y., 2008. Allelopathic interaction of Populus deltoides leaf leachate with some crop plants. J. Ind. Bot. Soc. 87, 237–241. Leao, P.N., Pereira, A.R., Liu, W.T., Ng, J., Pevzner, P.A., Dorrestein, P.C., Konig, G.M., Vasconcelos, V.M., Gerwick, W.H., 2010. Synergistic allelochemicals from a freshwater cyanobacterium. P. Natl. Acad. Sci. U. S. A. 107, 11183–11188. Leu, E., Krieger-Liszkay, A., Goussias, C., Gross, E.M., 2002. Polyphenolic allelochemicals from the aquatic angiosperm Myriophyllum spicatum inhibit photosystem II. Plant Physiol. 130, 2011–2018. Li, F.M., Hu, H.Y., 2005. Isolation and characterization of a novel antialgal allelochemical from Phragmites communis. Appl. Environ. Microb. 71, 6545–6553. Mardani, H., Sekine, T., Azizi, M., Mishyna, M., Fujii, Y., 2015. Identification of safranal as the main allelochemical from saffron (Crocus sativus). Nat. Prod. Commun. 10, 775–777. Mulderij, G., Van Nes, E.H., Van Donk, E., 2007. Macrophyte-phytoplankton interactions: the relative importance of allelopathy versus other factors. Ecol. Modell. 204, 85–92. Mulderij, G., Mau, B., Domis, L.N., Smolders, A.J.P., Van Donk, E., 2009. Interaction between the macrophyte Stratiotes aloides and filamentous algae: does it indicate allelopathy? Aquat. Ecol. 43, 305–312. Nakai, S., Inoue, Y., Hosomi, M., 2000. Myriophyllum spicatum-released allelopathic polyphenols inhibiting growth of blue-green algae Microcystis aeruginosa. Water Res. 34, 3026–3032.
Nakai, S., Zou, G., Okuda, T., Nishijima, W., Hosomi, M., Okada, M., 2012. Polyphenols and fatty acids responsible for anti-cyanobacterial allelopathic effects of submerged macrophyte Myriophyllum spicatum. Water Sci. Technol. 66, 993–999. Nakai, S., Okuda, T., Asaoka, S., 2014. Growth inhibition of Microcystis aeruginosa by allelopathic compounds originally isolated from Myriophyllum spicatum: temperature and light effects and evidence of possible major mechanisms. J. Chem. Eng. Jpn. 47, 488–493. Nupur, N., Trivedi, M.P., 2011. Allelopathic interaction among Parthenium hysterophorus Linn., Cassia tora Linn. and Croton bonplandianum Baill. Biosci. Biotechnol. Res. Asia 8, 265–270. Oliveros-Bastidas, A., Marin, D., Macias, F.A., 2014. Evidence for an allelopathic interaction between rye and wild oats. J. Agric. Food Chem. 62, 9450–9457. Park, M.H., Han, M.S., Ahn, C.Y., Kim, H.S., Yoon, B.D., Oh, H.M., 2006. Growth inhibition of bloom-forming cyanobacterium Microcystis aeruginosa by rice straw extract. Lett. Appl. Microbiol. 43, 307–312. Qin, B.Q., Li, W., Zhu, G.W., Zhang, Y.L., Wu, T.F., Gao, G., 2015. Cyanobacterial bloom management through integrated monitoring and forecasting in large shallow eutrophic Lake Taihu (China). J. Hazard. Mater. 287, 356–363. Singh, H.P., Batish, D.R., Kohli, R.K., 2003. Allelopathic interactions and allelochemicals: new possibilities for sustainable weed management. Crit. Rev. Plant Sci. 22, 239–311. Thiebaut, G., Muller, S., 1998. The impact of eutrophication on aquatic macrophyte diversity in weakly mineralized streams in the Northern Vosges Mountains (NE France). Biodivers. Conserv. 7, 1051–1068. Wang, H.Q., Zhu, H.J., Zhang, L.Y., Xue, W.J., Yuan, B., 2014. Identification of antialgal compounds from the aquatic plant Elodea nuttallii. Allelopathy J. 34, 207–213. Ye, L.T., Qian, J.Z., Jin, S., Zuo, S.P., Mei, H., Ma, S.M., 2014. Algicidal effects of four Chinese herbs extracts on bloom-forming Microcystis aeruginosa and Chlorella pyrenoidosa. Environ. Technol. 35, 1150–1156. Zhang, T.T., He, M., Wu, A.P., Nie, L.W., 2009. Allelopathic effects of submerged macrophyte Chara vulgaris on toxic Microcystis aeruginosa. Allelopathy J. 23, 391–402. Zhu, J.Y., Liu, B.Y., Wang, J., Gao, Y.N., Wu, Z.B., 2010. Study on the mechanism of allelopathic influence on cyanobacteria and chlorophytes by submerged macrophyte (Myriophyllum spicatum) and its secretion. Aquat. Toxicol. 98, 196–203. Zuo, S.P., Ma, Y.Q., Inanaga, S., 2012. Differences in ecological and allelopathic traits among Alternanthera philoxeroides populations. Weed Biol. Manage. 12, 123–130. Zuo, S.P., Wan, K., Ma, S.M., Ye, L.T., 2014. Combined allelopathic potential of aquatic plants species to control algae. Allelopathy J. 34, 315–324. Zuo, S.P., Wan, K., Ma, S.M., 2015. Combined effect of predatory zooplankton and allelopathic aquatic macrophytes on algal suppression. Environ. Technol. 36, 54–59.