Nocardia globerula NHB-2 nitrilase catalysed biotransformation of 4-cyanopyridine to isonicotinic acid

Significant improvement in conversion efficiency of isonicotinic acid by immobilization of cells via a novel microsphere preparation instrument

An instrument for the automatic preparation of microspheres was designed and manufactured, and by which cells were immobilized as efficient biocatalyst with small particle diameter, high crosslinking uniformity, and high porosity. The concentration of polymer solution, crosslinking agent and other conditions for preparing the cells microspheres were determined, and the conversion conditions of isonicotinic acid from 4-cyanopyridine were optimized to minimize mass-transfer limitations, and improve thermal and storage stability. The immobilized cells microspheres, which were continuously used for 23 batches, showed a total transformation capacity of 4.6 mol/L 4-cyanopyridine and a cumulative mass of 566.31 g/L of isonicotinic acid, which demonstrated the potential of the durable biocatalyst with efficient conversion capacity.

Nitrilase: a promising biocatalyst in industrial applications for green chemistry

Nitrilases are widely distributed in nature and are able to hydrolyze nitriles into their corresponding carboxylic acids and ammonia. In industry, nitrilases have been used as green biocatalysts for the production of high value-added products. To date, biocatalysts are considered to be important alternatives to chemical catalysts due to increasing environmental problems and resource scarcity. This review provides an overview of recent advances of nitrilases in aspects of distribution, enzyme screening, molecular structure and catalytic mechanism, protein engineering, and their potential applications in industry.

Classifying nitrilases as aliphatic and aromatic using machine learning technique

ProCos (Protein Composition Server, script version), one of the machine learning techniques, was used to classify nitrilases as aliphatic and aromatic nitrilases. Some important feature vectors were used to train the algorithm, which included pseudo-amino acid composition (PAAC) and five-factor solution score (5FSS). This clearly differentiated into two groups of nitrilases, i.e., aliphatic and aromatic, achieving maximum sensitivity of 100.00%, specificity of 90.00%, accuracy of 95.00% and Mathew Correlation Coefficient (MCC) of about 0.90 for the pseudo-amino acid composition. On the other hand, five-factor solution score achieved a sensitivity of 96.00%, specificity of 84.00%, accuracy of 90.00% and Mathew Correlation Coefficient (MCC) of about 0.81. The total count of aliphatic amino acids, Ala (A), Gly (G), Leu (L), Ile (I), Val (V), Met (M) and Pro (P), was found to be higher, i.e., 42.7 in case of aliphatic nitrilases, whereas it was 40.1 in aromatic nitrilases. On the other hand, aromatic amino acids, Tyr (Y), Trp (W), His (H) and Phe (F) number, were found to be higher, i.e., 12.7 in aromatic nitrilases as compared to aliphatic nitrilases which was 10.7. This approach will help in predicting a nitrilase as aromatic or aliphatic nitrilase based on its amino acid sequence. Access to the scripts can be done logging onto GitHub using keyword 'Nitrilase' or 'https://github.com/rover2380/Nitrilase.git'.

Mining of Microbial Genomes for the Novel Sources of Nitrilases

Next-generation DNA sequencing (NGS) has made it feasible to sequence large number of microbial genomes and advancements in computational biology have opened enormous opportunities to mine genome sequence data for novel genes and enzymes or their sources. In the present communication in silico mining of microbial genomes has been carried out to find novel sources of nitrilases. The sequences selected were analyzed for homology and considered for designing motifs. The manually designed motifs based on amino acid sequences of nitrilases were used to screen 2000 microbial genomes (translated to proteomes). This resulted in identification of one hundred thirty-eight putative/hypothetical sequences which could potentially code for nitrilase activity. In vitro validation of nine predicted sources of nitrilases was done for nitrile/cyanide hydrolyzing activity. Out of nine predicted nitrilases, Gluconacetobacter diazotrophicus, Sphingopyxis alaskensis, Saccharomonospora viridis, and Shimwellia blattae were specific for aliphatic nitriles, whereas nitrilases from Geodermatophilus obscurus, Nocardiopsis dassonvillei, Runella slithyformis, and Streptomyces albus possessed activity for aromatic nitriles. Flavobacterium indicum was specific towards potassium cyanide (KCN) which revealed the presence of nitrilase homolog, that is, cyanide dihydratase with no activity for either aliphatic, aromatic, or aryl nitriles. The present study reports the novel sources of nitrilases and cyanide dihydratase which were not reported hitherto by in silico or in vitro studies.

Functional diversity of Nocardia in metabolism

Bacteria affiliated in the genus Nocardia are aerobic and Gram-positive actinomycetes that are widely found in aquatic and terrestrial habitats. As occasional pathogens, several of them cause infection diseases called 'nocardiosis' affecting lungs, central nervous system, cutaneous tissues and others. In addition, members of the genus Nocardia exhibit an enormous metabolic versatility. On one side, many secondary metabolites have been isolated from members of this genus that exhibit various biological activities such as antimicrobial, antitumor, antioxidative and immunosuppressive activities. On the other side, many species are capable of degrading or converting aliphatic and aromatic toxic hydrocarbons, natural or synthetic polymers, and other widespread environmental pollutants. Because of these valuable properties and the application potential, Nocardia species have attracted much interest in academia and industry in recent years. A solid basis of genetic tools including a set of shuttle vectors and an efficient electroporation method for further genetic and metabolic engineering studies has been established to conduct efficient research. Associated with the increasing data of nocardial genome sequences, the functional diversity of Nocardia will be much faster and better understood.