Biotransformation of grease waste into fatty acid by Penicillium chrysogenum SNP5 through media engineering and artificial neural network

Degradation of grease waste remains a challenging task. Current work deals with the biotransformation of grease waste into fatty acids under submerged fermentation using Penicillium chrysogenum SNP5 through media formulation and artificial neural network (ANN). Fermentation media was formulated to ameliorate the uptake of hydrocarbon by enhancing alkane hydroxylase (AlkB) activity, extracellular release of fatty acids and inhibiting beta-oxidation of fatty acid by regulating transketolase. Further, the process parameters of fermentation were optimized through Artificial Neural Network (ANN) using three critical variables viz; inoculum size (spores/ml), pH, and incubation time (days) while media engineering was done with the optimal supplementation of various medium components such as glucose, YPD, MnSO₄, tetrahydrobiopterin (THB) and phloretin. The maximum conversion of 66.5% of grease waste into fatty acid was achieved at optimum conditions: inoculums size 3.36 × 10⁷ spores/ml, incubation time 11.5 days, pH 7.2 along with formulated media composed of 1% grease in czapek-dox medium supplemented with 55.5 mM glucose, 0.5% YPD, 16.6 mM hexadecane, 1 mM MnSO₄, 1 mM THB, and 1 mM phloretin. The presence of long-chain fatty acids in purified extracts such as oleic acid and octadecanoic acid as end products has valued the evolved process as another source of alternative fuel.

Application of the solid-state fermentation process and its variations in PHA production: a review

Solid-state fermentation (SSF) is a type of fermentation process with potential to use agro-industrial by-products as a carbon source. Nonetheless, there are few studies evaluating SSF compared to submerged fermentation (SmF) to produce polyhydroxyalkanoates (PHAs). Different methodologies are available associating the two processes. In general, the studies employ a 1st step by SSF to hydrolyze the agro-industrial by-products used as a carbon source, and a 2nd step to produce PHA that can be carried out by SmF or SSF. This paper reviewed and compared the different methodologies described in the literature to assess their potential for use in PHA production. The studies evaluated showed that highest PHA yields (86.2% and 82.3%) were achieved by associating SSF and SmF by Cupriavidus necator. Meanwhile, in methodologies using only SSF, Bacillus produced the highest yields (62% and 56.8%). Since PHA (%) does not necessarily represent a higher production by biomass, the productivity parameter was also compared between studies. We observed that the highest productivity results did not necessarily represent the highest PHA (%). C. necator presented the highest PHA yields associating SSF and SmF, however, is not the most suitable microorganism for PHA production by SSF. Concomitant use of C. necator and Bacillus is suggested for future studies in SSF. Also, it discusses the lack of studies on the association of the two fermentation methodologies, and on the scaling of SSF process for PHA production. In addition to demonstrating the need for standardization of results, for comparison between different methodologies.

Enhanced production of alkane hydroxylase from Penicillium chrysogenum SNP5 (MTCC13144) through feed-forward neural network and genetic algorithm

Alkane hydroxylase (AlkB), a membrane-bound enzyme has high industrial demand; however, its economical production remains challenging due to its intrinsic nature and co-factor dependency. In the current study, various critical process parameters for optimum production of AlkB have been optimized through feed forward neural network (FFNN) and genetic algorithm (GA) models using Penicillium chrysogenum SNP5 (MTCC13144). AlkB specific activity under preliminary un-optimized conditions i.e., 1% hexadecane, 7.4 pH, 11 days incubation time, 28 °C incubation temperature and 1 ml of inoculum size was 100 U/mg. ‘One variable at a time’ (OVAT) strategy was used to identify optimum physicochemical parameters and then its output data was fed to develop a model of FFNN with ‘6-12-1’ topology. Outputs of FFNN were further optimized through GA to minimize errors and intensify search level. This has provided superior predictive performances with 0.053 U/mg overall mean absolute percentage error (MAPE), 6.801 U/mg root mean square errors (RMSE), and 0.987 overall correlation coefficient (R). The AlkB specific activity improved by 3.5-fold, i.e., from 100 U/mg under preliminary un-optimized conditions to 351.32 U/mg under optimum physicochemical conditions obtained through FFNN-GA hybrid method, i.e., hexadecane (carbon source): 1.56% v/v, FeSO₄: 0.63 mM, incubation temperature: 27.40 °C, pH: 7.38, incubation time: 12.35 days and inoculums size: 1.33 ml. The developed process would be a stepping stone to fulfill the high industrial demands of  Alkane hydroxylase.

Bio-catalysis of mango industrial waste by newly isolated Fusarium sp. (PSTF1) for pectinase production

The dried mango fruit processing industrial waste (MIW) used as carbon source for the production of pectinase from fungal strains. Eight fungal strains were isolated from MIW and screened for their ability to produce pectinase by pectin clear zone (PCZ) technique. Fusarium sp. (PSTF1) showed highest PCZ value of 52 mm. The physico-chemical characteristics of the medium were standardized for high production of pectinase. The highest production of pectinase in submerged fermentation observed at temperature—28 °C, pH-6.0, inoculum-size 0.6/25 ml, incubation—72 h, substrate concentration—0.6 g/100 ml, carbon source-fructose (1 %). The effect of different amino acids, vitamins also observed. Under these optimal conditions the highest activity 81.9718 µmol/ml of pectinase was observed. The Fusarium sp. (PSTF1) has been considered as the best pectinase producer in submerged fermentation of MIW. The cheap waste raw material used as best carbon source for high production of high value pectinase.