Optimization of Lignocellulolytic Enzyme Cocktail Production from Cotylidia Pannosa and its Application in Bioethanol Production and Dye Decolorization

Abstract

A successful biomasstobiofuel bioprocessing requires the efficient hydrolysis and saccharification of biomass followed by efficient conversion of hydrolysates into biofuel. The bioprocessing largely depends on the inherent recalcitrant characteristics of biomass and the repositories of the enzymes used. The low efficiencies and higher cost of existing enzymes for this bioconversion is still a bottleneck in the technology. In this context the bioprospecting activities can aid in tapping vast sources of microorganisms with superior and efficient key enzymes. Therefore the present investigation was aimed at evaluation of different fungal cultures for their lignocellulolytic potential. Subjecting to qualitative and quantitative screening assays for nineteen different fungal strains the fungal strain F6 identified as Cotylidia pannosa C. pannosa was recognized as the most efficient producer of all three lignocellulolytic enzymes. Followed by initial screening the lignocellulolytic enzyme activities were further optimized to identify process parameters that supported maximum enzyme activities. Using one factor at a time approach cellulase xylanase and laccase activity of 8.44 UmL 6.74 UmL and 10.0 UmL respectively were obtained using wheat bran 2percent as substrate when the fermentation was conducted at a pH of 5.0 for 56 to 72 hrs at a temperature of 30°C under submerged fermentation. The optimization of enzyme activities was also conducted using solid state fermentation which resulted in cellulase xylanase and laccase activity of 4.33 UmL 5.23 UmL and 7.1 UmL respectively using the parameters as described for submerged fermentation. Based on the results of one factor at a time approach the lignocellulolytic enzyme production by C. pannosa was further optimized under submerged fermentation by a multifactorial approach involving Response surface methodology RSM. As compared to one factor at a time approach optimization via RSM further enhanced the cellulase xylanase.