Eco-friendly and safe alternatives for the valorization of shrimp farming waste.

The seafood industry generates waste, including shells, bones, intestines, and wastewater. The discards are nutrient-rich, containing varying concentrations of carotenoids, proteins, chitin, and other minerals. Thus, it is imperative to subject seafood waste, including shrimp waste (SW), to secondary processing and valorization for demineralization and deproteination to retrieve industrially essential compounds. Although several chemical processes are available for SW processing, most of them are inherently ecotoxic. Bioconversion of SW is cost-effective, ecofriendly, and safe. Microbial fermentation and the action of exogenous enzymes are among the significant SW bioconversion processes that transform seafood waste into valuable products. SW is a potential raw material for agrochemicals, microbial culture media, adsorbents, therapeutics, nutraceuticals, and bio-nanomaterials. This review comprehensively elucidates the valorization approaches of SW, addressing the drawbacks of chemically mediated methods for SW treatments. It is a broad overview of the applications associated with nutrient-rich SW, besides highlighting the role of major shrimp-producing countries in exploring SW to achieve safe, ecofriendly, and efficient bio-products.

Immobilized lipases-based nano-biocatalytic systems - A versatile platform with incredible biotechnological potential.

Lipases belong to α/ß hydrolases that cause hydrolytic catalysis of triacylglycerols to release monoacylglycerols, diacylglycerols, and glycerol with free fatty acids. Lipases have a common active site that contains three amino acid residues in a conserved Gly-X-Ser-X-Gly motif: a nucleophilic serine residue, an acidic aspartic or glutamic acid residue, and a basic histidine residue. Lipase plays a significant role in numerous industrial and biotechnological processes, including paper, food, oleochemical and pharmaceutical applications. However, its instability and aqueous solubility make application expensive and relatively challenging. Immobilization has been considered as a promising approach to improve enzyme stability, reusability, and survival under extreme temperature and pH environments. Innumerable supporting material in the form of natural polymers and nanostructured materials is a crucial aspect in the procedure of lipase immobilization used to afford biocompatibility, stability in physio-chemical belongings, and profuse binding positions for enzymes. This review outlines the unique structural and functional properties of a large number of polymers and nanomaterials as robust support matrices for lipase immobilization. Given these supporting materials, the applications of immobilized lipases in different industries, such as biodiesel production, polymer synthesis, additives, detergent, textile, and food industry are also discussed.

Fungal biosynthesis of lignin-modifying enzymes from pulp wash and Luffa cylindrica for azo dye RB5 biodecolorization using modeling by response surface methodology and artificial neural network.

This study demonstrates the evaluation between the artificial neural network technique coupled to the genetic algorithm (ANN-GA) and the response surface methodology (RSM) for prediction of Reactive Black 5 (RB5) decolorization by crude enzyme from Pleurotus. sajor-caju. Fungal lignin-modifying enzymes (FLME) were synthesized using pulp wash (PW) as an inducing substrate, and L. cylindrica (L.C) for cell immobilization. When grown in PW, the fungus showed higher Lac activity (126.5 IU. mL-1), whereas when immobilized a higher MnP activity was achieved (22.79 IU. mL-1), but both methods were capable of decolorizing the dye in about 89.4 % and 75 %, respectively. This indicates applicability of PW as an alternative substrate for FLME induction and viability of immobilization for MnP synthesis. For RB5 decolorization, the action of the crude enzyme extract was considered as a function of pH, dye concentration, temperature, and reaction time. The models are well adjusted to predict the efficiency of biodecolorization, with no statistical difference between ANN-GA and RSM, which indicates potential for green enzymes prospecting application in bioprocess industry.