Directed Evolution to Enhance Secretion Efficiency and Thermostability of Chitosanase fromMitsuaria chitosanitabida3001

Chitosan Oligosaccharide Production Potential of Mitsuaria sp. C4 and Its Whole-Genome Sequencing

Chitooligosaccharide is a kind of functional food, which is the degradation product of chitosan (COS) catalyzed by the endo-chitosanase (COSE) enzyme. A COSE with a molecular weight of 34 kDa was purified and characterized from a newly isolated Mitsuaria sp. C4 (C4), and a 38.46% recovery rate and 4.79-fold purification were achieved. The purified C4 COSE exhibited optimum activity at 40°C and pH 7.2 and was significantly inhibited in the presence of Cu²⁺ and Fe³⁺. The K_m and V_min of the COSE toward COS were 2.449 g/L and 0.042 g/min/L, respectively. The highest COSE activity reached 8.344 U/ml after optimizing, which represented a 1.34-fold of increase. Additionally, chitooligosaccharide obtained by COSE hydrolysis of COS was verified by using thin-layer chromatography and high-performance liquid chromatography analysis. Whole-genome sequencing demonstrated that the C4 strain contains 211 carbohydrate enzymes, our purified COSE belonging to GHs-46 involved in carbohydrate degradation. Phylogenetic analysis showed that the novel COSE obtained from the C4 strain was clustered into the degree of polymerization = two to three groups, which can perform catalysis in a similar manner to produce (GlcN)₂ and (GlcN)₃. This work indicates that the C4 strain could be a good resource for enhancing carbohydrate degradation and might represent a useful tool for chitooligosaccharide production in the functional food industry.

Efficient Preparation of Chitooligosaccharide With a Potential Chitosanase Csn-SH and Its Application for Fungi Disease Protection

Chitosanase plays a vital role in bioactive chitooligosaccharide preparation. Here, we characterized and prepared a potential GH46 family chitosanase from Bacillus atrophaeus BSS. The purified recombinant enzyme Csn-SH showed a molecular weight of 27.0 kDa. Csn-SH displayed maximal activity toward chitosan at pH 5.0 and 45°C. Thin-layer chromatography and electrospray ionization–mass spectrometry indicated that Csn-SH mainly hydrolyzed chitosan into (GlcN)₂, (GlcN)₃, and (GlcN)₄ with an endo-type cleavage pattern. Molecular docking analysis demonstrated that Csn-SH cleaved the glycoside bonds between subsites −2 and + 1 of (GlcN)₆. Importantly, the chitosan hydrolysis rate of Csn-SH reached 80.57% within 40 min, which could reduce time and water consumption. The hydrolysates prepared with Csn-SH exhibited a good antifungal activity against Magnaporthe oryzae and Colletotrichum higginsianum. The above results suggested that Csn-SH could be used to produce active chitooligosaccharides efficiently that are biocontrol agents applicable for safe and sustainable agricultural production.

Thermostability enhancement of chitosanase CsnA by fusion a family 5 carbohydrate-binding module

OBJECTIVE

To determine the effects of carbohydrate-binding modules (CBMs) on the thermostability and catalytic efficiency of chitosanase CsnA.

RESULTS

Three CBMs (BgCBM5, PfCBM32-2 and AoCBM35) were engineered at the C-terminus of chitosanase CsnA to create hybrid enzymes CsnA-CBM5, CsnA-CBM32 and CsnA-CBM35. K _m values of all the hybrid enzymes were lower than that of the wild type (WT) enzyme; however, only CsnA-CBM5 had an elevated specific activity and catalytic efficiency. The fusion of BgCBM5 enhanced the thermostability of the enzyme, which exhibited a 8.9 °C higher T₅₀ and a 2.9 °C higher T_m than the WT. Secondary structural analysis indicated that appending BgCBM5 at the C-terminus considerably changed the secondary structure content.

CONCLUSIONS

The fusion of BgCBM5 improved the thermal stability of CsnA, and the obtained hybrid enzyme (CsnA-CBM5) is a useful candidate for industrial application.

Mitsuaria chitosanase with unrevealed important amino acid residues: characterization and enhanced production in Pichia pastoris

A chitosan plate assay was employed to screen for chitosanase-producing bacterial strains and isolate 141 was found to exhibit high activity. Characterization of this isolate revealed that it belonged to Mitsuaria (designated as Mitsuaria sp. 141). The encoded chitosanase (choA) gene was then cloned by PCR and the deduced amino acid sequence showed 98% identity to a formerly described Mitsuaria chitosanitabida 3001 ChoA (McChoA). Surprisingly, the ChoA encoded by Mitsuaria sp. 141 (MsChoA) appeared to have a much higher optimum temperature compared to McChoA. Site-directed mutagenesis was then employed to generate five MschoA mutant genes encoding MsChoA K204Q, R216K, T222N, R216K/T222N, or K204Q/R216K/T222N. All the ChoA mutants exhibited a much lower specific activity and a lower optimum temperature. The results confirmed that the substitution of three non-conserved amino acids accounts for the major reduction of the enzyme activity in MsChoA. Furthermore, the MschoA gene was cloned for over-expression in Pichia pastoris after coding sequence optimization. One of the P. pastoris transformants with Mut(S) phenotype was found to produce 1,480.2 ± 340.9 U ChoA mL(-1) of cell culture by high-cell-density fermentation. This represents the highest yield of recombinant ChoA production that has ever been reported thus far. The recombinant P. pastoris strain should therefore be well suited for industrial-scale production of chitosanase.

In silico modelling of directed evolution: Implications for experimental design and stepwise evolution

We model the process of directed evolution (DE) in silico using genetic algorithms. Making use of the NK fitness landscape model, we analyse the effects of mutation rate, crossover and selection pressure on the performance of DE. A range of values of K, the epistatic interaction of the landscape, are considered, and high- and low-throughput modes of evolution are compared. Our findings suggest that for runs of or around ten generations' duration-as is typical in DE-there is little difference between the way in which DE needs to be configured in the high- and low-throughput regimes, nor across different degrees of landscape epistasis. In all cases, a high selection pressure (but not an extreme one) combined with a moderately high mutation rate works best, while crossover provides some benefit but only on the less rugged landscapes. These genetic algorithms were also compared with a "model-based approach" from the literature, which uses sequential fixing of the problem parameters based on fitting a linear model. Overall, we find that purely evolutionary techniques fare better than do model-based approaches across all but the smoothest landscapes.