Utilization of Leek (Allium ampeloprasum var. porrum) for Inulinase Production

Inulinase production by Rhodotorula glutinis was carried out in this study, using leek (Allium ampeloprasum var. porrum) as an alternative carbon source due to its high inulin content and easy availability. Taguchi orthogonal array (OA) design of experiment (DOE) was used to optimize fermentation conditions. For this purpose, five influential factors (leek concentration, pH, incubation temperature, agitation speed, and fermentation time) related to inulinase production were selected at four convenient levels. The results showed that maximum inulinase activity was obtained as 30.89 U/mL, which was close to the predicted result (30.24 U/mL). To validate the obtained results, analysis of variance (ANOVA) was employed. Consequently, leek has a great potential as an effective and economical carbon source for inulinase production, and the use of Taguchi DOE enhanced enzyme activity about 2.87-fold when compared with the unoptimized condition.     

Computerized study of interactions among factors and their optimization through response surface methodology for the production of tannin acyl hydrolase by Aspergillus niger PKL 104 under solid state fermentation

Optimization of five parameters (initial moisture, initial pH, incubation temperature, inoculum ratio and fermentation period), as per central composite rotable design falling under the response surface methodology, was attempted in a total of 32 experimental sets, after fitting the experimental data to the polynomial model of a suitable degree, for tannin acyl hydrolase production by Aspergillus niger PKL 104 in solid state fermentation system. The quantitative relation between the enzyme production and different levels of these factors was exploited to work out optimized levels of these parameters by flexible polyhedron search method and confirmed by further experimentations. The best set required 5% inoculum, 6.5 initial pH, 28 °C fermentation temperature, 62% initial moisture and 3 days fermentation time. The optima were worked out under the additional constraints for temperature ( 30 °C) and fermentation time (not more than 3 days) which are essential from industrial conditions and to pre-empt contamination, respectively. The best set resulted in 1.34 times more enzyme production than that was obtained before this optimization. Three dimensional plots, relating the enzyme production to paired factors (when other three factors were kept at their optimal levels) best described the behaviour of solid state fermentation system and the interactions between factors under optimized conditions. The model showed that the enzyme production was affected by all the five factors studied. The initial pH exhibited a positive interaction with moisture but no interaction with other factors. Initial moisture level and inoculum ratio showed negative interaction in contrast to positive interaction between inoculum ratio and fermentation period. It is thus apparent that the response surface methodology not only gives valuable information on interactions between the factors but also leads to identification of feasible optimum values of the studied factors, in addition to 99% (or more) savings on resources as compared to a full factorial traditional optimization method. Response surface methods have not been used earlier for optimizing parameters in solid state fermentation system.The authors thank Dr. S. R. Bhowmik, Director, CFTRI for the interest shown in the work. P. K. Lekha is thankful to the Council of Scientific and Industrial Research, New Delhi, India, for the award of a research fellowship.     

Optimization of fermentation parameters in phage production using response surface methodology

Previously, we used computer-controlled fermentation technology to improve the yield of filamentous phage produced in Escherichia coli by 10-fold (Grieco et?al., Bioprocess Biosyst Eng 32:773-779, 2009). In the current study, three major fermentation parameters (temperature, dissolved oxygen [DO], and pH) were investigated using design of experiments (DOE) methodology. Response surface methodology (RSM) was employed to create a process model and determine the optimal conditions for maximal phage production. The experimental data fitted best to a quadratic model (p?相似文献   

Modelling and optimization of fermentation factors for enhancement of alkaline protease production by isolated Bacillus circulans using feed-forward neural network and genetic algorithm

Aim: Modelling and optimization of fermentation factors and evaluation for enhanced alkaline protease production by Bacillus circulans. Methods and Results: A hybrid system of feed‐forward neural network (FFNN) and genetic algorithm (GA) was used to optimize the fermentation conditions to enhance the alkaline protease production by B. circulans. Different microbial metabolism regulating fermentation factors (incubation temperature, medium pH, inoculum level, medium volume, carbon and nitrogen sources) were used to construct a ‘6‐13‐1’ topology of the FFNN for identifying the nonlinear relationship between fermentation factors and enzyme yield. FFNN predicted values were further optimized for alkaline protease production using GA. The overall mean absolute predictive error and the mean square errors were observed to be 0·0048, 27·9, 0·001128 and 22·45 U ml^?1 for training and testing, respectively. The goodness of the neural network prediction (coefficient of R²) was found to be 0·9993. Conclusions: Four different optimum fermentation conditions revealed maximum enzyme production out of 500 simulated data. Concentration‐dependent carbon and nitrogen sources, showed major impact on bacterial metabolism mediated alkaline protease production. Improved enzyme yield could be achieved by this microbial strain in wide nutrient concentration range and each selected factor concentration depends on rest of the factors concentration. The usage of FFNN–GA hybrid methodology has resulted in a significant improvement (>2·5‐fold) in the alkaline protease yield. Significance and Impact of the Study: The present study helps to optimize enzyme production and its regulation pattern by combinatorial influence of different fermentation factors. Further, the information obtained in this study signifies its importance during scale‐up studies.     

Culture condition improvement for whole-cell lipase production in submerged fermentation by Rhizopus chinensis using statistical method

Rhizopus chinensis CCTCC M201021 was a versatile strain capable of producing whole-cell lipase with synthetic activity in submerged fermentation. In order to improve the production of whole-cell lipase and study the culture conditions systematically, the combination of taguchi method and response surface methodology was performed. Taguchi method was used for the initial optimization, and eight factors viz., maltose, olive oil, peptone, K2HPO4, agitation, inoculum size, fermentation volume and pH were selected for this study. The whole-cell lipase activity yield was two times higher than the control experiment under initial optimal conditions, and four significant factors (inoculum, olive oil, fermentation volume and peptone) were selected to test the effect on the lipase production using response surface methodology. The optimal fermentation parameters for enhanced whole-cell lipase yield were found to be: inoculum 4.25 x 10(8) spores/L, olive oil 2.367% (w/v), fermentation volume 18 mL/250 mL flask, peptone 4.06% (w/v). Subsequent experimental trails confirmed the validity of the model. These optimal culture conditions in the shake flask led to a lipase yield of 13875 U/L, which 120% increased compare with the non-optimized conditions.     

Enhanced β-fructofuranosidase biosynthesis by Rhodotorula glutinis using Taguchi robust design method

The aim of this study was to produce β-fructofuranosidase enzyme by Rhodotorula glutinis SO28, using sugar beet (Beta vulgaris) as carbon source due to its high sucrose content and easy availability. β-Fructofuranosidase production was carried out in submerged fermentation. Taguchi orthogonal array (OA) design of experiment (DOE) method was employed for optimization process of β-fructofuranosidase production by R. glutinis SO28. An OA layout of L16 was constructed with five influential factors on β-fructofuranosidase biosynthesis namely, carbon source (sugar beet), initial pH, incubation temperature, agitation speed and incubation time. The average results of β-fructofuranosidase yield obtained from the determined 16 batches were processed with Minitab^® 16.2.3 software at “larger is better” as quality character. The results showed that the maximum β-fructofuranosidase activity was obtained as 21.11?±?0.47?U/mL, which was close to the predicted result (21.78?±?0.43?U/mL). Consequently, sugar beet can be suggested as an economical substrate for β-fructofuranosidase production. Besides, use of Taguchi DOE enhanced enzyme activity about 3-fold when compared with unoptimized condition.     

Chitinase Production in Solid-State Fermentation by Enterobacter sp. NRG4 Using Statistical Experimental Design

The optimization of nutrient levels for chitinase production by Enterobacter sp. NRG4 in solid-state fermentation conditions (SSF) was carried out using response surface methodology (RSM) based on central composite design (CCD). The design was employed by selecting wheat bran-to-flake chitin ratio, moisture level, inoculum size, and incubation time as model factors. The results of first-order factorial design experiments showed that all four independent variables have significant effects on chitinase production. The optimum concentrations for chitinase production were wheat bran-to-flake chitin ratio, 1; moisture level, 80%; inoculum size, 2.6 mL; and incubation time, 168 h. Using this statistical optimization method, chitinase production was found to increase from 616 U · g⁻¹ dry weight of solid substrate to 1475 U · g⁻¹ dry weight of solid substrate.     

Enhancement of acid amylase production by an isolated Aspergillus awamori

AIMS: Evaluation of the influence of fermentation components on extracellular acid amylase production by an isolated fungal strain Aspergillus awamori. METHODS AND RESULTS: Eight fungal metabolic influential factors, viz. soluble starch, corn steep liquor (CSL), casein, potassium dihydrogen phosphate (KH(2)PO(4)) and magnesium sulfate (MgSO(4) x 7H(2)O), pH, temperature and inoculum level were selected to optimize amylase production by A. awamori using fractional factorial design of Taguchi methodology. Significant improvement in acid amylase enzyme production (48%) was achieved. The optimized medium composition consisted of soluble starch--3%; CSL--0.5%; KH(2)PO(4)--0.125%; MgSO(4) x 7H(2)O--0.125%; casein--1.5% at pH 4.0 and temperature at 31 degrees C. CONCLUSION: Optimization of the components of the fermentation medium was carried out using fractional factorial design of Taguchi's L-18 orthogonal array. Based on the influence of interaction components of fermentation, these could be classified as the least significant and the most significant at individual and interaction levels. Least significant factors of individual level have higher interaction severity index and vice versa at enzyme production in this fungal strain. The pH of the medium and substrate (soluble starch) showed maximum production impact (60%) at optimized environment. Temperature and CSL were the least influential factors for acid amylase production. SIGNIFICANCE AND IMPACT OF THE STUDY: Acid amylase production by isolated A. awamori is influenced by the interaction of fermentation factors with fungal metabolism at individual and interaction levels. The pH of the fermentation medium and substrate concentration regulates maximum enzyme production process in this fungal strain.     

Design of experiments applications in bioprocessing: Chromatography process development using split design of experiments

Development of a chromatographic step in a time and resource efficient manner remains a serious bottleneck in protein purification. Chromatographic performance typically depends on raw material attributes, feed material attributes, process factors, and their interactions. Design of experiments (DOE) based process development is often chosen for this purpose. A challenge is, however, in performing a DOE with such a large number of process factors. A split DOE approach based on process knowledge in order to reduce the number of experiments is proposed. The first DOE targets optimizing factors that are likely to significantly impact the process and their effect on process performance is unknown. The second DOE aims to fine-tune another set of interacting process factors, impact of whom on process performance is known from process understanding. Furthermore, modeling of a large set of output response variables has been achieved by fitting the output responses to an empirical equation and then using the parametric constants of the equation as output response variables for regression modeling. Two case studies involving hydrophobic interaction chromatography for removal of aggregates and cation exchange chromatography for separation of charge variants and aggregates have been utilized to illustrate the proposed approach. Proposed methodology reduced total number of experiments by 25% and 72% compared to a single DOE based on central composite design and full factorial design, respectively. The proposed approach is likely to result in a significant reduction in resources required as well as time taken during process development. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2730, 2019     

Optimization of alkaline protease production by batch culture of Bacillus sp. RKY3 through Plackett-Burman and response surface methodological approaches

The proteolytic enzymes are the most important group of commercially produced enzymes. The production of alkaline protease was optimized using a newly isolated Bacillus sp. RKY3. The fermentation variables were selected in accordance with the Plackett-Burman design and were further optimized via response surface methodological approach. Four significant variables (corn starch, yeast extract, corn steep liquor, and inoculum size) were selected for the optimization studies. The statistical model was constructed via central composite design (CCD) using three screened variables (corn starch, corn steep liquor, and inoculum size). An overall 2.3-fold increase in protease production was achieved in the optimized medium as compared with the unoptimized basal medium. Enzyme activity increased significantly with optimized medium (939 u ml(-1)) when compared with unoptimized medium (417 u ml(-1)).     

Statistical optimization of medium components for extracellular protease production by an extreme haloarchaeon, Halobacterium sp. SP1(1)

Aims:  Optimization of medium components for extracellular protease production by Halobacterium sp. SP1(1) using statistical approach.
Methods and Results:  The significant factors influencing the protease production as screened by Plackett–Burman method were identified as soybean flour and FeCl₃. Response surface methodology such as central composite design was applied for further optimization studies. The concentrations of medium components for higher protease production as optimized using this approach were (g l⁻¹): NaCl, 250; KCl, 2; MgSO₄, 10; tri-Na-citrate, 1·5; soybean flour, 10 and FeCl₃, 0·16. This statistical optimization approach led to production of 69·44 ± 0·811 U ml⁻¹ of protease.
Conclusions:  Soybean flour and FeCl₃ were identified as important factors controlling the production of extracellular protease by Halobacterium sp. SP1(1). The statistical approach was found to be very effective in optimizing the medium components in manageable number of experimental runs with overall 3·9-fold increase in extracellular protease production.
Significance and Impact of the Study:  The present study is the first report on statistical optimization of medium components for production of haloarchaeal protease. The study also explored the possibility of using extracellular protease produced by Halobacterium sp. SP1(1) for various applications like antifouling coatings and fish sauce preparation using cheaper raw material.     

OPTIMIZATION OF SOLID-STATE FERMENTATION FOR PHYTASE PRODUCTION BY Thermomyces lanuginosus USING RESPONSE SURFACE METHODOLOGY

A strain of Thermomyces lanuginosus, isolated from hot spring water in Turkey, was studied for optimization of phytase production using solid-state fermentation. Effects on fermentation of different production parameters such as substrate type, moisture, culture time, and inoculum size were investigated using a one-factor-at-a-time approach. Central composite design (CCD) of response surface methodology was applied for the optimization of four factors (culture temperature, initial pH, aeration area, age of seeding culture) that were affecting phytase production by Thermomyces lanuginosus in rice bran. Maximum phytase activity was achieved by using rice bran. The optimum levels of variables that supported maximum enzyme activity were moisture 70%, culture time 7 days, inoculum size 40%, culture temperature 55°C, initial pH 7.5, aeration area 30%, age of seeding culture 5 days, sucrose 1%, and ZnSO₄ 2.5 mM. An overall 10.83-fold enhancement in phytase activity (0.30 to 3.248 U) was attained due to the optimization.     

Influence of experimental conditions on visco-hyperelastic properties of skeletal muscle tissue using a Box–Behnken design

The Mechanical characterization of skeletal muscles is strongly dependent on numerous experimental design factors. Nevertheless, significant knowledge gaps remain on the characterization of muscle mechanics and a large number of experiments should be implemented to test the influence of a large number of factors. In this study, we propose a design of experiment method (DOE) to study the parameter sensitivity while minimizing the number of tests. A Box-Behnken design was then implemented to study the influence of strain rate, preconditioning and preloading conditions on visco-hyperelastic mechanical parameters of two rat forearm muscles. The results show that the strain rate affects the visco-hyperelastic parameters for both muscles. These results are consistent with previous work demonstrating that stiffness and viscoelastic contributions increase with strain rate. Thus, DOE has been shown to be a valid method to determine the effect of the experimental conditions on the mechanical behaviour of biological tissues such as skeletal muscle. This method considerably reduces the number of experiments. Indeed, the presented study using 3 parameters at 3 levels would have required at least 54 tests per muscle against 14 for the proposed DOE method.     

Anaerobic treatment of complex chemical wastewater in a sequencing batch biofilm reactor: process optimization and evaluation of factor interactions using the Taguchi dynamic DOE methodology

The Taguchi robust experimental design (DOE) methodology has been applied on a dynamic anaerobic process treating complex wastewater by an anaerobic sequencing batch biofilm reactor (AnSBBR). For optimizing the process as well as to evaluate the influence of different factors on the process, the uncontrollable (noise) factors have been considered. The Taguchi methodology adopting dynamic approach is the first of its kind for studying anaerobic process evaluation and process optimization. The designed experimental methodology consisted of four phases--planning, conducting, analysis, and validation connected sequence-wise to achieve the overall optimization. In the experimental design, five controllable factors, i.e., organic loading rate (OLR), inlet pH, biodegradability (BOD/COD ratio), temperature, and sulfate concentration, along with the two uncontrollable (noise) factors, volatile fatty acids (VFA) and alkalinity at two levels were considered for optimization of the anae robic system. Thirty-two anaerobic experiments were conducted with a different combination of factors and the results obtained in terms of substrate degradation rates were processed in Qualitek-4 software to study the main effect of individual factors, interaction between the individual factors, and signal-to-noise (S/N) ratio analysis. Attempts were also made to achieve optimum conditions. Studies on the influence of individual factors on process performance revealed the intensive effect of OLR. In multiple factor interaction studies, biodegradability with other factors, such as temperature, pH, and sulfate have shown maximum influence over the process performance. The optimum conditions for the efficient performance of the anaerobic system in treating complex wastewater by considering dynamic (noise) factors obtained are higher organic loading rate of 3.5 Kg COD/m3 day, neutral pH with high biodegradability (BOD/COD ratio of 0.5), along with mesophilic temperature range (40 degrees C), and low sulfate concentration (700 mg/L). The optimization resulted in enhanced anaerobic performance (56.7%) from a substrate degradation rate (SDR) of 1.99 to 3.13 Kg COD/m3 day. Considering the obtained optimum factors, further validation experiments were carried out, which showed enhanced process performance (3.04 Kg COD/m3-day from 1.99 Kg COD/m3 day) accounting for 52.13% improvement with the optimized process conditions. The proposed method facilitated a systematic mathematical approach to understand the complex multi-species manifested anaerobic process treating complex chemical wastewater by considering the uncontrollable factors.     

响应面法优化枯草芽孢杆菌产脂肪酶的合成培养基

对枯草芽孢杆菌(Bacillus subtilis)CICC20034利用合成培养基液体发酵产脂肪酶的条件进行了优化。首先采用单因子实验筛选出最适诱导剂为三丁酸甘油酯,氮源为尿素,碳源为葡萄糖,无机盐为MgSO4。在此基础上,利用Plackett-Burman设计对影响产酶因素的效应进行评价,筛选出具有显著效应的三丁酸甘油酯、尿素、KH2PO4和培养基起始pH值4个最显著的因素。用最陡爬坡路径逼近最大产酶区域后,利用响应面中心组合设计对显著因素进行优化,获得最适合成培养基组分为:葡萄糖8g/L,尿素8.57g/L,三丁酸甘油酯2.62%,KH2PO42.59g/L,MgSO4.7H2O0.5g/L,TritonX-1000.5g/L,pH9.47。优化后的B.subtilis CICC 20034胞外脂肪酶活力达0.483U/ml,比初始酶活力0.072U/ml提高了6.7倍。     

南极交替单胞菌R11-5产卡拉胶酶的发酵条件优化

【背景】极地寒冷环境中发现了大量具有潜在应用前景的冷适应酶,同时也存在种类繁多的海藻多糖降解菌,因此极端环境微生物是筛选获得新颖、高效多糖降解酶的重要新源泉。由于筛选培养基通常并非野生菌发酵产酶的最优条件,为了使野生菌的产酶效率达到最高,需要对其培养条件进行优化,从而为其深入研究及开发利用提供依据。【目的】对一株产卡拉胶酶的南极菌株进行种属鉴定,并采用响应面法对该菌的发酵产酶条件进行优化。【方法】通过16SrRNA基因对产卡拉胶酶的南极菌株进行种属鉴定,采用响应面法优化南极菌株产酶发酵条件。【结果】该南极菌属于交替单胞菌属(Alteromonas),命名为交替单胞菌R11-5。发酵条件优化结果显示,7个环境因子影响交替单胞菌R11-5的产酶量。利用Design-Expert软件中的Plackett-Burman设计实验,筛选出影响交替单胞菌R11-5产酶量的4个主要因素分别为培养温度、牛肉膏浓度、卡拉胶浓度和Ca~(2+)浓度。通过Box-Behnken设计和响应面分析得到交替单胞菌R11-5最佳产酶发酵条件为:温度15.0°C,牛肉膏浓度11.0 g/L,卡拉胶浓度3.0 g/L,Ca~(2+)浓度5.0 mmol/L。优化后发酵上清液酶产量达到87.193 U/mL,与优化前相比提高了1.8倍。【结论】响应面法提高了南极交替单胞菌R11-5卡拉胶酶的产量,为其开发应用提供了科学依据。     

Optimization of laccase production from a novel strain-Streptomyces psammoticus using response surface methodology

Response surface methodology was employed for the optimization of different nutritional and physical parameters for the production of laccase by the filamentous bacteria Streptomyces psammoticus MTCC 7334 in submerged fermentation. Initial screening of production parameters was performed using a Plackett - Burman design and the variables with statistically significant effects on laccase production were identified. Incubation temperature, incubation period, agitation rate, concentrations of yeast extract, MgSO(4)7H(2)O, and trace elements were found to influence laccase production significantly. These variables were selected for further optimization studies using a Box-Behnken design. The statistical optimization by response surface methodology resulted in a three-fold increase in the production of laccase by S. psammoticus MTCC 7334.     

单因子-响应面法优化白地霉Y162产脂肪酶条件

对白地霉Y162液体发酵产脂肪酶的条件进行了优化。首先采用单因子实验筛选出最适碳源为橄榄油,氮源为黄豆粉和NH4Cl,无机盐为BaCl2和MgCl2。在此基础上,利用Plackett-Burman设计对影响产酶因素的效应进行评价,筛选出具有显著效应的橄榄油、BaCl2和NH4Cl三个最显著的因素。用最陡爬坡路径逼近最大产酶区域后,利用响应面中心组合设计对显著因素进行优化,得出橄榄油、BaCl2和NH4Cl最佳浓度分别为2.35％,0.36％,1.35％。优化后液体发酵液中脂肪酶活力提高到31.85 U/mL,比初始酶活力14.16 U/mL提高了2.25倍,表明单因子-响应面结合法可显著优化白地霉Y162液体发酵产脂肪酶条件。     

Optimization of protease production by Streptomyces sp. A6 using statistical approach for reclamation of shellfish waste

Protease producing Streptomyces sp. A6 was isolated from intertidal zone of the coast of Diu (Gujarat, India). Plackett–Burman method was applied to identify important factors (shrimp waste, FeCl₃, ZnSO₄ and pH) influencing protease production by Streptomyces sp. A6. Further optimization was done by response surface methodology using central composite design. The concentrations of medium components for higher protease production as optimized using the above approach were (g l^?1): Shrimp waste, 14; FeCl₃, 0.035; ZnSO₄, 0.065 and pH, 8.0. This statistical optimization approach led to production of 129.02 ± 2.03 U ml^?1 of protease which was 4.96 fold higher compared to that obtained using the unoptimized medium. The protease production was scaled to 3 l in a 5-l bench fermenter using optimized medium which further increased the production by 63.4%. Deproteinization and chitin recovery obtained at the end of fermentation was 85.12 ± 4.7 and 70.58 ± 1.33%, respectively. The present study is the first report on statistical optimization of medium components for production of protease by Streptomyces species using cheaper raw material such as shrimp waste. The study also explored the possibility Streptomyces sp. A6 for reclamation of shrimp wastes.     

常压室温等离子体诱变选育L-精氨酸生产菌及发酵条件优化

【目的】通过常压室温等离子体诱变技术选育L-精氨酸高产菌株,利用响应面设计探索突变菌株生产L-精氨酸的最佳发酵条件。【方法】采用常压室温等离子体生物诱变系统对实验室保藏的Corynebacterium glutamicum GUI089进行系列诱变,选育L-高精氨酸和8-氮鸟嘌呤抗性菌株。在单因子实验的基础上,应用Plackett-Burman设计从7个因素中筛选出对L-精氨酸合成具有显著效应的(NH4)2SO4、葡萄糖和尿素3个因素。基于上述结果,进一步采用响应面设计优化出主要影响因素的最佳参数水平。【结果】经过一系列的诱变和筛选,选育出一株L-高精氨酸(15 g/L)和8-氮鸟嘌呤(0.7 g/L)抗性菌株,并将此菌株命名为C.glutamicum ARG 3-16。此菌株的L-精氨酸产量比出发菌株提高了49.79%,且发酵液中杂酸的浓度明显降低,特别是L-脯氨酸、L-谷氨酸和L-缬氨酸。在经响应面优化后的最佳发酵条件下,L-精氨酸的产量达到39.72±0.75 g/L,比优化前提高了10.49%。【结论】通过常压室温等离子体诱变技术成功选育出一株L-精氨酸高产菌株,利用响应面法有效地优化了发酵条件,实验结果表明突变株ARG 3-16具有潜在的生产应用价值。