2271 © IWA Publishing 2019 Water Science & Technology | 79.12 | 2019
Application of Agaricus bisporus industrial wastewater to produce the biomass of Pichia burtonii Jiafu Huang
ABSTRACT
By using Plackett–Burman combined with Box–Behnken design, the fermentation conditions of Jiafu Huang Engineering Technological Center of Mushroom Pichia burtonii using Agaricus bisporus industrial wastewater as culture medium were optimized. The Industry, fl Minnan Normal University, biomass of P. burtonii in the fermentation broth was analyzed by multispectral imaging ow Zhangzhou, Fujian 363000, cytometry. Plackett–Burman design was used to screen out three factors from six factors affecting China and the biomass of P. burtonii as major factors. The Box–Behnken response surface method was used to School of Life Sciences & Biotechnology College, Minnan Normal University, optimize the interaction of the three main factors to predict the optimal fermentation conditions. The Zhangzhou, Fujian 363000, fi China signi cant factors affecting the biomass of P. burtonii, such as shaking speed, solubility and culture E-mail: [email protected] temperature, were screened. The optimum conditions for P. burtonii were as follows: a shaking speed of 265 rmp, a solubility of 8%, a culture temperature of 25 C, an initial pH of 6.0, an inoculation amount of 8%, and an amount of 30 mL liquid in 250 mL, and the total living yeast can reach 1.27 ± 0.02 × 108 Obj/mL, which was within the 95% confidence interval of the predicted model (1.08–1.32 × 108 Obj/mL). Key words | Agaricus bisporus industrial wastewater, multispectral imaging flow cytometry, Pichia burtonii, Plackett–Burman design, response surface
INTRODUCTION
Edible fungi are mainly produced in China, the United P. burtonii belongs to the genus Pichia, which is widely States, the Netherlands and Japan, and according to the distributed (Zhou et al. ; Middelhoven ; Rai et al. ; data of the FAO (Food and Agriculture Organization), the Ghosh et al. ), has a simple nutrient type and is easy to cul- yield of edible mushroom in China ranks first in the word. ture. It is often used in the fields of fermentation, animal feed Among the edible mushrooms, Agaricus bisporus, Lentinus additives and bacteriostatics (Chen et al. b; Wang et al. edodes and parts of wild fungus, viz., Tricholoma matsutake, ). Therefore, the industrial wastewater can be used as a natu- are the main trade products in the world, and more, due to ral medium for P. burtonii, which would provide theoretical the short storage period of fresh edible mushroom, the main support for microbial fertilizer fermentation and the form of mushroom in international trade is canned pro- development of the downstream industry of A. bisporus. ducts. Therefore a large amount of industrial wastewater is produced during canned processing each year in China. The discharge of the wastewater into the surrounding MATERIALS AND METHODS areas is a cause of environmental pollution. However, the wastewater contains a large amount of soluble components Microorganisms and culture conditions from the mushroom. According to the reports there are 0.65% protein, 0.17% total sugar, 0.08% reducing sugar, P. burtonii (GIM 2.179) was purchased from the Guangdong and 0.04% amino acid nitrogen in the industrial wastewater Culture Collection Center. Seed medium: glucose 10 g, pep- (Duan et al. ; Chen et al. ), which could provide suf- tone 5 g, malt extract 3 g, yeast powder 3 g, distilled water ficient carbon and nitrogen sources for microorganisms 1 L, pH 6.2, sterilized at 121 C for 15 min. Preparation of (Huang et al. a, b) or plants (Zhan et al. ). seed suspension: activated P. burtonii was put into sterilized
doi: 10.2166/wst.2019.228
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seed liquid medium and shaken in a shaker (28 C, 150 rpm) investigated by steepest ascent design and Box–Behnken for 48 h. A. bisporus processing wastewater was collected design of response surface methodology. from processing enterprises (Fujian KEREN Biological Co., Ltd), filtered, concentrated, and sterilized according to differ- Steepest ascent design ent experimental requirements. After the three most significant variables were identified through the Box–Behnken design, the steepest ascent exper- Plackett–Burman design iment was performed to move the experimental region of the response in the direction of the optimum, by appropriately Plackett–Burman design was applied to evaluate the relative changing the range of the selected variables. The path was importance of several fermentation parameters that influence initiated from the design center of the factorial design (the the desired response, and enabled one to screen N variables screening design) and receded when no further improve- in at least N þ 1 experiments (Ekpenyong et al. ). To ment in the response could be achieved. When the increase the response, each factor selected was tested at maximum value was gained, the point could be considered two levels, high levels (þ1) and low levels ( 1). A Plackett– as the center point for the optimization experimental Burman design of the experiments was formulated for six fac- design (Chen et al. a). Table 2 summarizes the steepest tors that affect the total number of viable bacteria using the ascent experimental design, the variables, and their values. Design-Expert version 8.0.6 software (Stat-Ease, Inc., Min- neapolis, MN, USA). For the present study, the selected Box–Behnken design factors included the levels of industrial wastewater solubility, initial pH, inoculum dose, loaded liquid, culture temperature The response surface methodology is a collection of statisti- and shaking speed. The levels of each factor shown in Table 1 cal tools and techniques for constructing and exploring a were determined based on prior experience. Each trial run putative functional relationship between a response variable was performed in triplicate, and the biomass of P. burtonii (i.e., the total number of living yeast) and a set of design vari- in the fermentation broth was taken as the response. Pareto ables (i.e., shaking speed, solubility, culture temperature). chart analysis was used to evaluate the variables, which It is possible to derive an expression for performance presents the impact of each variable on the total number of measurement on the basis of the response values obtained living yeast, and the most significant variables were further from experiments using a particular combination of input
Table 1 | Experimental design and results of Plackett–Burman
C (Inoculation D (Load liquid E (Temperature A (Solubility (%)) B (pH) dose (%)) (mL/250 mL)) ( C)) F (Speed (rmp)) Total number of live Run Levels Values Levels Values Levels Values Levels Values Levels Values Levels Values P. burtonii(107 Obj/mL)
1 1 4 1 7.0 12 190 1 24 1 200 1.65 ± 0.05 2 1 4 1 7.0 1 8 190 124 1 100 0.74 ± 0.04 31 4 1 6.0 12 1901 32 1 100 0.17 ± 0.02 4 1 0.25 1 7.0 1 8 1 150 124 1 100 0.32 ± 0.03 51 4 1 6.0 1 8 1 150 1 24 1 200 1.01 ± 0.01 6 1 0.25 1 7.0 1 8 1 90 1 32 1 200 0.48 ± 0.04 7 1 0.25 1 6.0 12 190 124 1 100 0.34 ± 0.02 8 1 0.25 1 6.0 1 2 1 150 1 24 1 200 0.62 ± 0.01 9 1 4 1 7.0 1 2 1 150 1 32 1 200 1.22 ± 0.03 10 1 4 1 6.0 1 8 1 150 1 32 1 100 0.0638 ± 0.001 11 1 0.25 1 6.0 1 8 1 90 1 32 1 200 0.0126 ± 0.002 12 1 0.25 1 7.0 1 2 1 150 1 32 1 100 0.234 ± 0.04
Data are expressed as the mean ± standard deviation (SD) of three batches of independent experiments.
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Table 2 | Experimental design and results of steepest ascent design Table 3 | Experimental design and results of Box–Behnken design
Shaking Concentration Culture Total number of live X1: Speed X2: Solubility X3: Temperature Run speed (rmp) (%) temperature ( C) P. burtonii (107 Obj/mL) (rmp) (%) ( C) ± 1 100 1 36 0.0136 0.004 Code Real Code Real Code Real Total number of live 7 2 150 2 32 4.32 ± 0.02 Run level level level level level level P. burtonii (10 Obj/mL) 3 200 4 28 7.26 ± 0.04 1 0 250 1 4 1 28 7.44 ± 0.02 4 250 6 24 9.68 ± 0.03 2 1 300 0 6 1 20 2.54 ± 0.01 5 300 8 20 8.28 ± 0.02 3 0 250 14 1 20 7.81 ± 0.03 ± Data are expressed as the mean ± standard deviation (SD) of three batches of independent 4 0 250 1 8 1 20 7.23 0.02 experiments. 5 1 300 0 6 1 28 7.68 ± 0.01 6 0 250 0 6 0 24 10.49 ± 0.03 variables (Wu et al. ). In the present study, by employing 7 1 200 1 4 0 24 11.23 ± 0.03 Box–Behnken design and response surface methodology, 8 0 250 0 6 0 24 11.03 ± 0.03 the effects of the three independent variables (shaking 9 1 200 1 8 0 24 9.7 ± 0.02 speed, 200–300 rmp; solubility, 4–8%; culture temperature, 10 1 200 0 6 1 28 6.45 ± 0.01 20–28 C) and three levels (high, middle, and low) on the 11 0 250 1 8 1 28 9.85 ± 0.03 response (the total number of living yeast) were investigated ± to determine the optimal conditions, which maximized the 12 1 200 0 6 1 20 6.95 0.02 ± total number of living P. burtonii from shake cultivation. 13 0 250 0 6 0 24 10.52 0.04 Each independent variable was coded at three levels: 1, 0, 14 0 250 0 6 0 24 10.07 ± 0.03 and þ1. The Box–Behnken design comprised 17 experiments 15 0 250 0 6 0 24 10.84 ± 0.02 with five center points (to allow for estimation of pure error) 16 1 300 1 8 0 24 10.63 ± 0.03 and facilitated calculations of response function at intermedi- 17 1 300 1 4 0 24 7.68 ± 0.01 ate levels, fitting a second-order response surface. Table 3 Data are expressed as the mean ± standard deviation (SD) of three batches of independent shows the variables and their values and the experimental experiments. design.
identified and gated (Figure 1(a)). The SYTO 9 stain generally P. burtonii Determination of the total number of living labels all yeast, including both those with intact and with damaged membranes. By contrast, PI penetrates only yeast The fermentation broth was diluted ten times with PBS, and with damaged membranes, causing a reduction in SYTO 9 μ 1 mL diluted solution was mixed with 3 L LIVE/DEAD stain fluorescence when both dyes are present. Therefore, TM Baclight (L7012, Thermo) staining reagent (containing when using a combination of SYTO 9 and PI stains, yeast SYTO 9 and propidium iodide (PI)) and incubated for with intact cell membrane stains fluorescent green, whereas 30 min in the dark, followed by analysis with multispectral yeast with damaged membrane stains fluorescent red. Dead fl imaging ow cytometry (Calvert et al. ). PBS was used yeast had PI fluorescent signals or both SYTO 9 and PI sig- fl as a ow sheath, the SYTO 9 signal was the X axis, the PI nals (Figure 1(b)). Yeast with only the SYTO 9 fluorescent signal was the Y axis, and the scatter plot was made to dis- signal was considered living (Figure 1(c)). tinguish the numbers of dead and living bacteria.
Plackett–Burman experiment RESULTS AND DISCUSSION The Plackett–Burman experimental design matrix and Total number of living P. burtonii in the fermentation results are shown in Table 1. Plackett–Burman design liquid analyzed by multispectral imaging flow cytometry methods can be used in the screening of the key influential factors compared with other statistical designs on the A scatter plot comparing fluorescence intensities of SYTO 9 experimental response. Six variables were selected in the in the green channel and PI in the red channel was generated screening approach with the Plackett–Burman experimental for the in-focus population. Two segregated regions were design, suggesting 12 trial runs. The total number of viable
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Steepest ascent design
According to the positive and negative effects of the three factors in Figure 2, the rotational speed and solubility exhib- ited positive effects and temperature exhibited negative effects. Five sets of experiments of the steepest ascent and the corresponding experimental results are shown in Table 2. The total number of living P. burtonii peaked at the fourth step and no further improvement could be achieved in the response; when the speed was 250 rmp, the solubility of the pre-boiling liquid was 6% and the cul- ture temperature was 24 C, which suggested that it was proximal to the region of maximum response. Accordingly, these levels of the three factors in the fourth set were considered the center point of the Box–Behnken design.
Figure 1 | (a) From the collected images, live and dead P. burtonii were visually identified Optimization of fermentation parameters by response (as indicated by channels) and the tagged populations were gated on the original plot; (b) images of dead P. burtonii in the fermented liquid; (c) images surface methodology of living P. burtonii in the fermented liquid. Note: Images from each region were chosen at random. From left to right, bright-field, SYTO 9, and PI channel images are displayed. In the present analysis, experiments were designed to obtain a second-order polynomial equation consisting of 12 trials plus five central points. The design matrix of the variables yeast was selected as the observed response to determine the is shown in Table 3 along with the experimental values of effects of the variables studied. Pareto analysis was used to the response. Through multiple regression analysis of the determine the contribution of the screened variables experimental data, shown in Table 4, the following second- (Figure 2), which showed that the shaking speed had the order polynomial equation was derived for the total number highest positive effect on the total number of living yeast, of living P. burtonii by considering only the significant followed by solubility, while culture temperature was a negative factor. These three factors were determined to be of the highest relative importance in influencing the total Table 4 | Variance analysis of Box–Behnken experiment regression model number of living yeast compared with the other fermenta- Source Sum of squares df Mean squares F value p-value prob > F tion parameters tested and, hence, each was selected for Model 82.22 9 9.14 48.61 <0.0001 further optimization. X1 4.20 1 4.20 22.37 0.0021
X2 1.32 1 1.32 7.02 0.0329
X3 5.93 1 5.93 31.57 0.0008
X1X2 5.02 1 5.02 26.70 0.0013
X1X3 7.95 1 7.95 42.31 0.0003
X2X3 2.24 1 2.24 11.89 0.0107 2 X1 9.21 1 9.21 48.99 0.0002 2 X2 2.06 1 2.06 10.94 0.0130 2 X3 43.28 1 43.28 230.30 <0.0001 Residual 1.32 7 0.19 Lack of fit 0.77 3 0.26 1.91 0.2699 Pure error 0.54 4 0.14 Cor total 83.54 16 Figure 2 | Pareto chart of each factor standard effect on the total number of living 2 ¼ 2 ¼ ¼ ¼ P. burtonii. R 0.9843, RAdj 0.9640, adequate precision 25.083, CV 4.98%.
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terms: Y ¼ 10.59 0.72X1 þ 0.41X2 þ 0.86X3 þ 1.12X1X2 þ at the same time, the analysis of variance shows that the 2 2 2 1.41X1X3 þ 0.75X2X3 1.48X1 þ 0.70X2 3.21X3,whereY interaction between speed and pre-cooking liquid solubility is the predicted response of the total number of living is significant (p < 0.05). When the culture temperature was P. burtonii,andX1, X2,andX3 are the coded values of shak- 24 C (the temperature test level is 0), the change of the ing speed, wastewater solubility, and culture temperature, total number of living bacteria gradually decreased with respectively. Statistical significance of the second-order the increase of shaking speed and the solubility of the pre- modelandallthecoefficient estimates were assessed using cooking liquid; when the shaking speed was 250 rmp, the ANOVA, and the data are shown in Table 4.Thep < 0.0001 solubility of the pre-cooking liquid was 6%, and the culture of the regression model shows that when the regression temperature was 24 C, the total number of living bacteria equation is used to describe the relationship between every gradually increased and reached the actual maximum factor and response value, the linear relationships between close to the design points. dependent variable and all independent variables are very sig- From Figure 3(c) and 3(d), it is known that the response nificant, that is, the experimental method is reliable. The value surface is steep, indicating that the influence of speed and of adj-R2 (0.9640) suggests that the total variation of 96.40% solubility on the total number of living bacteria is obvious; for the biomass of P. burtonii was attributable to the indepen- the contour line is oval, and the interaction between speed dent variables. The determination coefficient (R2 ¼ 0.9843), and temperature is significant. Under the condition of con- which is commonly used to assess the goodness of the stant solubility, the biomass of P. burtonii increased first model, exhibited an excellent correlation between the exper- and then decreased with the increase of rotational speed imental and predicted response values. A low CV (CV ¼ and temperature, and the vertex of the surface is the maxi- 4.98%) value clearly revealed that the deviations between mum point of the biomass. experimental and predicted values were low and it displayed From Figure 3(e) and 3(f), the effect of solubility and not only a high degree of precision but also a high reliability temperature on the total number of living bacteria was in the conducted experiments. Adequate precision measures obvious. At the same time, the interaction between solubility the signal-to-noise ratio, and a ratio greater than 4 is desirable. and temperature was significant by the analysis of variance In this study, a ratio of 25.083 indicated an adequate signal. (p < 0.05). When the shaking speed was 250 rmp, that is, Therefore, the quadratic model was selected in this optimiz- the test level is 0, the total number of living yeast increased ation study. first and then decreased with the increase of temperature; This multiple nonlinear model resulted in three the change trend of the total number of living yeast tended response surface graphs through canonical analysis of the to be gentle with increase of solubility. Under a constant response surface. Interpretation of the response surface 3D shaking speed (the level is 0), the total number of living bac- model and contour plot were as the graphical represen- teria first increased and then decreased as the temperature, tations of the regression equation. They provided visual and the vertex of the surface indicates the maximum interpretations of the relationship between responses and amount of total living yeast. experimental levels of each variable, and the type of inter- These observations were also verified through canonical actions between two test variables (Long et al. ). analysis of the response surface. By solving the inverse Figure 3 shows the fitted response surface 3D models and matrix from the second-order polynomial equation, the their corresponding contour plots for the total number of optimum values of the test variables were shaking speed living P. burtonii produced by the predicted model. As can 264.16 rmp, wastewater solubility 8%, culture temperature be seen from Figure 3,theresponsesurfacemapofthe 25.25 C, and the predictive value of the total number of speed and temperature, and the response surface between viable P. burtonii was 1.20 × 108 Obj/mL. To confirm the val- the solubility and temperature are all convex downward idity of the model for predicting the maximum total number curved surfaces, indicating that the total number of viable of viable P. burtonii, an additional experiment using these bacteria of P. burtonii has a high value. The contour centers optimum operation conditions was performed under shake- of the three response surfaces are located within the set flask culture. The total number of viable P. burtonii was range, which indicates that the optimal design conditions 1.27 ± 0.02 × 108 Obj/mL (N ¼ 3), which was within the exist within the designed level of factors. 95% confidence interval of the predicted model (1.08– From Figure 3(a) and 3(b), it is known that the response 1.32 × 108 Obj/mL), suggesting that the model was adequate surface is steep, indicating that the influence of speed and for reflecting the expected optimization, and the response solubility on the total number of living bacteria is obvious; surface methodology model was satisfactory and accurate.
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Figure 3 | The effect of cross-interaction among shaking speed, different concentration and culture temperature on total number of living P. burtonii: (a) response surface plot of effects of interaction between shaking speed and different concentrations on total number of live P. burtonii; (b) contour line of effects of interaction between shaking speed and different concentrations on total number of live P. burtonii; (c) response surface plot of effects of interaction between shaking speed and culture temperature on total number of live P. burtonii; (d) contour line of effects of interaction between shaking speed and culture temperature on total number of live P. burtonii; (e) response surface plot of effects of interaction between different concentrations and culture temperature on total number of live P. burtonii; (f) contour line of effects of interaction between different concentrations and culture temperature on total number of live P. burtonii.
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Response surface methodology is one more effective produced during the growth of the aerobic decomposition method that reduces development costs, optimizes exper- consuming strain and greatly reduces the yield of the bacteria; imental conditions, improves production efficiency and when the speed is too high, the amount of dissolved oxygen solves practical production problems. Compared with one- increases rapidly, and it produces a large number of metab- factor-at-a-time experiments, statistically designed exper- olites, which also affect the growth of the bacteria. iments are able to describe the effect of the interactions Therefore, P. burtonii is one kind of facultative aerobe that between the factors in linear and quadratic terms (Rane forms large aggregates when the shaking speed is at a high et al. ). In the present study, the optimization of fermenta- level. tion conditions for P. burtonii was divided into two phases: a In the course of production and processing, A. bisporus screening of the main effects of the selected variables and a is treated with hot water many times, so that some of its response optimization. Reduction in the initial number of water-soluble nutrients are lost into the processing waste- variables was carried out through Plackett–Burman design water. Although the amount is small, after the wastewater that was used to screen out three factors from six factors was further concentrated, it is sufficient to meet the (industrial wastewater solubility, initial pH, inoculum dose, growth requirement of bacteria, yeast and other microorgan- loaded liquid, culture temperature and shaking speed) affect- isms. Temperature influences microbial life mainly by ing the total number of viable bacteria as major factors, which affecting the mobility of the microbial cell membrane and were the shaking speed, wastewater solubility, and culture the activity of biological macromolecules (Baweja et al. temperature. They were taken for the Box–Behnken design ; Taniguchi et al. ). As temperature increases, the of response surface methodology to assess their effects on rates of intracellular enzymatic reactions increase, resulting the biomass of P. burtonii. We used response surface method- in an increase in cell metabolism and growth. However, ology to further optimize the biomass of P. burtonii by Box– once the temperature becomes too high, bioactive sub- Behnken design. Response surface methodology not only stances become denatured, resulting in decreased cell helped locate the optimum levels of the most significant fac- functions and even death (Kunze et al. ). In accordance tors but also proved to be useful and satisfactory in this with this, the total number of viable P. burtonii first process-optimizing practice. Through these optimization increased and then decreased as the temperature increased. experiments, the maximum biomass of P. burtonii at 1.27 ± The most suitable temperature range was 24–32 C with an 0.02 × 108 Obj/mL was obtained under the optimum con- optimal incubation temperature of 26 C. ditions of speed 264 rmp, pre-cooking liquid solubility 8%, temperature 25 C, initial pH 6, inoculum 8%, and liquid volume 30 mL/250 mL, after 48 hours. CONCLUSIONS SYTO 9 and PI were used for double staining of viable and dead cells. With an appropriate mixture of SYTO 9 In this paper, three major influencing factors including shak- and PI stains, bacteria with intact cell membranes stain ing speed, wastewater solubility and culture temperature fluorescent green, scored as viable; and bacteria with injured were screened by a Plackett–Burman design test, and the membranes stain fluorescent red, scored as non-viable optimal fermentation conditions of P. burtonii were designed (Leuko et al. ; Hu et al. ). The fluorescent staining by Box–Behnken: speed 264 rmp, pre-cooking liquid solubi- of bacterial cells was quantified with multispectral imaging lity 8%, temperature 25 C, initial pH 6, inoculum 8%, flow cytometry by fluorescent signals and microscopic liquid volume 30 mL/250 mL; after 48 hours, the total images (Berney et al. ; Jenner et al. ). Therefore, the number of viable bacteria reached 1.27 ± 0.02 × 108 Obj/mL, P. burtonii viable and dead cells and particles in the fermen- reaching the requirements of agricultural microbial inocu- ted liquid were quickly and accurately identified and lants, which could be used as the best fermentation quantified by flow cytometry in a statistically sound manner. conditions to ferment P. burtonii by using wastewater from There is a positive correlation between the shaker speed A. bisporus processing. and the amount of dissolved oxygen, and the amount of the dissolved oxygen can also reflect the growth of the bacteria from the side. When the speed is too low, the dissolved ACKNOWLEDGEMENTS oxygen is not enough, resulting in uneven mixing of the various substances in the fermentation system, which can This study was funded by the Fujian Provincial Department not normally utilize the large amount of organic acids of Science and Technology (No. 2019N0018) and the 2018
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First received 14 April 2019; accepted in revised form 25 June 2019. Available online 29 June 2019
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