Identification of a chitosanase from the marine metagenome and its molecular improvement based on evolution data

MECE: a method for enhancing the catalytic efficiency of glycoside hydrolase based on deep neural networks and molecular evolution

The demand for high efficiency glycoside hydrolases (GHs) is on the rise due to their various industrial applications. However, improving the catalytic efficiency of an enzyme remains a challenge. This investigation showcases the capability of a deep neural network and method for enhancing the catalytic efficiency (MECE) platform to predict mutations that improve catalytic activity in GHs. The MECE platform includes DeepGH, a deep learning model that is able to identify GH families and functional residues. This model was developed utilizing 119 GH family protein sequences obtained from the Carbohydrate-Active enZYmes (CAZy) database. After undergoing ten-fold cross-validation, the DeepGH models exhibited a predictive accuracy of 96.73%. The utilization of gradient-weighted class activation mapping (Grad-CAM) was used to aid us in comprehending the classification features, which in turn facilitated the creation of enzyme mutants. As a result, the MECE platform was validated with the development of CHIS1754-MUT7, a mutant that boasts seven amino acid substitutions. The kcat/Km of CHIS1754-MUT7 was found to be 23.53 times greater than that of the wild type CHIS1754. Due to its high computational efficiency and low experimental cost, this method offers significant advantages and presents a novel approach for the intelligent design of enzyme catalytic efficiency. As a result, it holds great promise for a wide range of applications.

Structure-based mining of a chitosanase with distinctive degradation mode and product specificity

Chitosan derivates with varying degrees of polymerization (DP) have attracted great concern due to their excellent biological activities. Increasing the abundance of chitosanases with different degradation modes contributes to revealing their catalytic mechanisms and facilitating the production of chitosan derivates. However, the identification of endo-chitosanases capable of producing chitobiose and D-glucosamine (GlcN) from chitosan substrates has remained elusive. Herein, an endo-chitosanase (CsnCA) belonging to the GH46 family was identified based on structural analysis in phylogenetic evolution. Moreover, we demonstrate that CsnCA acts in a random endo-acting manner, producing chitosan derivatives with DP ≤ 2. The in-depth analysis of CsnCA revealed that (GlcN)3 serves as the minimal substrate, undergoing cleavage in the mode that occupies the subsites - 2 to + 1, resulting in the release of GlcN. This study succeeded in discovering a chitosanase with distinctive degradation modes, which could facilitate the mechanistic understanding of chitosanases, further empowering the production of chitosan derivates with specific DP. KEY POINTS: • Structural docking and evolutionary analysis guide to mining the chitosanase. • The endo-chitosanase exhibits a unique GlcN-producing cleavage pattern. • The cleavage direction of chitosanase to produce GlcN was identified.

Biochemical Characterization of a GH46 Chitosanase Provides Insights into the Novel Digestion Specificity

Endo-chitosanases (EC 3.2.1.132) are generally considered to selectively release functional chito-oligosaccharides (COSs) with degrees of polymerization (DPs) ≥ 2. Although numerous endo-chitosanases have been characterized, the digestion specificity of endo-chitosanases needs to be further explored. In this study, a GH46 endo-chitosanase OUC-CsnPa was cloned, expressed, and characterized from Paenibacillus sp. 1-18. The digestion pattern analysis indicated that OUC-CsnPa could produce monosaccharides from chitotetraose [(GlcN)₄], the smallest recognized substrate, in a random endo-acting manner. Especially, the enzyme specificities during chitosan digestion including the regulation of product abundance through a transglycosylation reaction were also evaluated. It was hypothesized that an insertion region in OUC-CsnPa may form a strong force to be involved in stabilizing (GlcN)₄ at its negative subsite for efficient hydrolysis. This is the first comprehensive report to reveal the digestion specificity and subsite specificity of monosaccharide production by endo-chitosanases. Overall, OUC-CsnPa described here highlights the previously unknown digestion properties of the endo-acting chitosanases and provides a unique example of possible structure-function relationships.

A temperature-induced chitosanase bacterial cell-surface display system for the efficient production of chitooligosaccharides

OBJECTIVE

To establish a temperature-induced chitosanase bacterial cell-surface display system to produce chitooligosaccharides (COSs) efficiently for industrial applications.

RESULTS

Temperature-inducible chitosanase CSN46A bacterial surface display systems containing one or two copies of ice nucleation protein (InaQ-N) as anchoring motifs were successfully constructed on the basis of Escherichia coli and named as InaQ-N-CSN46A (1 copy) and 2InaQ-N-CSN46A (2 copies). The specific enzyme activity of 2InaQ-N-CSN46A reached 761.34 ± 0.78 U/g cell dry weight, which was 45.6% higher than that of InaQ-N-CSN46A. However, few proteins were detected in the 2InaQ-N-CSN46A hydrolysis system. Therefore, 2InaQ-N-CSN46A had higher hydrolysis efficiency and stability than InaQ-N-CSN46A. Gel permeation chromatography revealed that under the optimum enzymatic hydrolysis temperature, the final products were mainly chitobiose and chitotriose. Chitopentaose accumulated (77.62%) when the hydrolysis temperature reached 60 °C. FTIR and NMR analysis demonstrated that the structures of the two hydrolysis products were consistent with those of COSs.

CONCLUSIONS

In this study, chitosanase was expressed on the surfaces of E. coli by increasing the induction temperature, and chitosan was hydrolysed directly without enzyme purification steps. This study provides a novel strategy for industrial COS production.