Laccase production by Pleurotus ostreatus 1804: Optimization of submerged culture conditions by Taguchi DOE methodology

Abstract

Submerged culture conditions for laccase production by Pleurotus ostreatus 1804 were optimized by Taguchi orthogonal array (OA) experimental design (DOE) methodology. This approach facilitates the study of interaction of a large number of variables spanned by factors and their settings with a small number of experiments leading to considerable saving in time and cost for the process optimization. The proposed Taguchi DOE methodology consists of four phases viz., planning, conducting, analysis and validation, which were connected sequence wise to achieve the overall process optimization. Eight factors viz., carbon, nitrogen source (urea), 2,5-xylidine (inducer), wheat bran (ligninocellulosic material), inoculum size, fermentation broth pH, yeast extract and phosphate source (KH₂PO₄) at three levels with a OA layout of L18 (2¹ × 3⁷) were selected for the proposed experimental design. Laccase yield obtained from the 18 sets of fermentation experiments performed with the selected factors and levels were further processed with Qualitek-4 software at bigger is better as quality character. The optimized conditions showed an enhanced laccase expression of 32.9% (from 538.8 to 803.3 U). The optimal combinations of factors obtained from the proposed DOE methodology was further validated by conducting fermentation experiments and the obtained results revealed an enhanced laccase yield of 28.3%. Taguchi approach of DOE resulted in evaluating the main and interaction effects of the factors individually and in combination. This methodology facilitated analysis of the experimental data to establish the optimum conditions for the process, understand the contribution of individual factors and to evaluate the response under optimal conditions. Application of Taguchi approach appears to have potential usage in bioprocess optimization.

Introduction

Laccases (EC 1.10.3.2), copper based polyphenol oxidases are diverse group of enzymes having great biotechnological potential and high market potential due to their broad substrate specificity in the diverse fields of industrial applications such as in pulp deliginfication [1], [2], [3], [4], [5], textile dye bleaching [6] wastewater detoxification [2], [7], xenobiotic detoxification [8], [9], [10], detergent manufacturing and transformation of antibiotics and steroids [4]. The genus Pleurotus (pleurotaceae, higher basidiomycetes) is a cosmopolitan group of mushrooms with highly nutritious values, therapeutic properties and various environmental and biotechnological applications [11]. P. ostreatus showed strong laccase activity among the edible mushrooms and is relatively easy to culture in a medium [12]. However, except for traditional edible mushroom cultivation, large-scale practical implementation of the biotechnological potential based on the unique properties and enzymatic system of Pleurotus sp. has not yet been commercially developed [4]. Laccase expression by fungi is found to be influenced by culture conditions such as nature of carbon source, concentration of carbon source, pH of fermentation broth, presence of inducers, presence of lignonocelluose materials and nitrogen source [2], [13], [14], [15]. For effective laccase expression, it is highly essential to optimize all the culture conditions and composition for production media, which further facilitates economic design of the full-scale fermentation operation system. However, practically to optimize all the parameters and to establish the best possible conditions by interrelating all the parameters, numerous experiments have to be carried out with all possible parameter combinations, which is considered to be not economical and practical. For this type of cases, statistical tools and experimental design help to gain more information about the optimization conditions.

Conventional optimization procedures involve altering of one parameter at a time keeping all other parameters constant, which enables to assess the impact of those particular parameters on the process performance. These procedures are time consuming, cumbersome, requires more experimental data sets and can not provide information about the mutual interactions of the parameters [16]. Taguchi method of orthogonal array (OA) experimental design (DOE) involves the study of any given system by a set of independent variables (factors) over a specific region of interest (levels) [17], [18]. Unlike traditional DOE, which focuses on the average process performance characteristics, it concentrates on the effect of variation on the process characteristics [19], [20] and makes the product or process performance insensitive to variation by proper design of parameters. This approach also facilitates to identify the influence of individual factors, establishing the relationship between variables and operational conditions and finally establish the performance at the optimum levels obtained with a few well-defined experimental sets [21]. This method also determines the optimal level of the important controllable factors based on the concept of robustness and S/N ratio [17], [18], [22], [23], [24]. In this methodology, the desired design is sought by selecting the best performance under conditions that produces consistent performance [22] and the conclusions drawn from the small-scale experiments are valid over the entire experimental region spanned by control factors and their setting levels [25]. Analysis of the experimental data using the ANOVA (analysis of variance) and factor effects gives the out put that are statistically significant in finding the optimum levels. This approach not only helps in considerable saving in time and cost but also leads to a more fully developed process by providing systematic, simple and efficient methodology for the optimization of the near optimum design parameters with only a few well defined experimental sets [25], [26], [27]. Its application created significant changes in several industrial organizations in Japan and USA in manufacturing processes and total quality control [20], [27]. More recently, it has been applied for the optimization of a few biochemical techniques [28], [29] and bioprocess applications [30], [31], [32], [33].

The communication presents methodological application of Taguchi DOE for the optimization of submerged culture conditions for laccase production by P. ostreatus 1804. The experiments were designed with eight factors for laccase yield (carbon, nitrogen source, inducer, ligninocellusoic material, inoculum size, pH, yeast extract and phosphate source) at three levels with OA layout of L18 (2¹ × 3⁷).