Computation-aided engineering of starch-debranching pullulanase from Bacillus thermoleovorans for enhanced thermostability

Bi, Jiahua; Chen, Shuhui; Zhao, Xianghan; Nie, Yao; Xu, Yan

doi:10.1007/s00253-020-10764-z

Cited by 48 publications

(27 citation statements)

References 57 publications

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“…However, the enzyme activity of B. subtilis 168-pMA5-A344E/S302I was at a low level. Xiao et al [ 31 ] designed a 5′ untranslated region (UTR) sequence that effectively increased the protein yield of the industrial strain B. licheniformis DW2. This sequence contains only about 30 nt and forms a hairpin structure before the open reading frame.…”

Section: Resultsmentioning

confidence: 99%

Heterologous Expression and Rational Design of l-asparaginase from Rhizomucor miehei to Improve Thermostability

Zhang

Wang

et al. 2021

Biology

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l-asparaginase (EC 3.5.1.1) hydrolyzes l-asparagine to produce l-aspartate and ammonia and is widely found in microorganisms, plants, and some rodent sera. l-asparaginase used for industrial production should have good thermostability. We heterologously expressed l-asparaginase from Rhizomucor miehei, selected nine loci for site-directed mutagenesis by rational design, and obtained two mutants with significantly improved thermostability. The optimal temperature of mutants S302I and S302M was 50 °C. After incubating the mutant and wild-type enzymes at 45 °C for 35 h, the residual activity of the wild-type enzyme (WT) was only about 10%. In contrast, the residual activity of S302I and S302M was more than 50%. After combination mutagenesis, Bacillus subtilis 168-pMA5-A344E/S302I was constructed using the food-safe host strain B. subtilis 168. Additionally, a 5′ untranslated region (UTR) modification strategy was adopted to enhance the expression level of R. miehei-derived l-asparaginase in B. subtilis. In a 5-L fermenter scale-up experiment, the enzyme activity of recombinant B. subtilis 168-pMA5-UTR-A344E/S302I reached 521.9 U·mL−1 by fed-batch fermentation.

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Section: Resultsmentioning

confidence: 99%

Heterologous Expression and Rational Design of l-asparaginase from Rhizomucor miehei to Improve Thermostability

Zhang

Wang

et al. 2021

Biology

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“…For an increased credibility of machine learning based methods, several such tools, i.e. I-Mutant 3.0, dFire and FoldX) have even been simultaneously used to improve the thermostability of thermophilic pullulanase of Bacillus thermoleovorans [57]. Through the detailed molecular dynamics simulation of this modelled protein, the study validates 6 of the 17 highly stable mutants at non-conserved and non-catalytic sites.…”

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confidence: 76%

“…g. Identify structural preferences of increased stability [56,57]: As accurate assessment of mutations on the stability of proteins is key to functionally understand their catalytic mechanism and improve their stability, a set of 21 usually deployed protein stability prediction algorithms, also including the machine-learning strategies, are analyzed to evaluate their stabilizing effect against the experimentally benchmarked dataset [56].…”

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confidence: 99%

Accurate computational evolution of proteins and its dependence on deep learning and machine learning strategies

Narayanan

Runthala

2022

Biocatalysis and Biotransformation

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Enzyme is the major workhorse to carry out the diverse cellular functions. It catalyzes the biological reactions with a high specificity, with its topology playing a crucial role. For ecologically safe production of numerous bioproducts including drugs and chemicals, we have been striving to design the industrially useful enzyme molecules with highly improved catalytic capability. As the sequence space is enormous for an enzyme, its quick and effective exploration is quite improbable for the mutagenesis studies whose accuracy is greatly reliant on the prior information of the mutated sites and the extent of rigorous screening of the mutant libraries.Although directed evolution methods significantly aid the construction of a functionally improved molecule, their credibility depends on the successful excavation of the functionally similar sequence space in the available databases, encompassing billions of proteins. As deep learning methods aid us to extensively uncover the underlying network of all the key catalytic positions without any experimental data, their implementation has reliably increased the accuracy of directed evolution. The chapter comprehensively explains data mining and deep learning methods to further showcase their importance in enzyme engineering methods. The key biological and algorithmic limitations of these deep learning methodologies are lastly highlighted.

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“…Glucoamylase is an exo-acting enzyme that mainly hydrolyzes α–1, 4–glycosidic linkages from the non-reducing ends of starch chains, which leads to the production of glucose [ 22 ]. Pullulanase can specifically hydrolyze α–1, 6-glycosidic linkages in starch and oligosaccharides [ 23 ]. In the small intestine, maltase can catalyze the digestion of maltose, which were metabolite from disaccharidases [ 24 ].…”

Section: Discussionmentioning

confidence: 99%

Optimization of exogenous carbohydrases supplemented in broiler diets using in vitro simulated gastrointestinal digestion and response surface methodology

Liu

Liu²,

Jiang

et al. 2021

PLoS ONE

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The present study aimed to explore the optimal zymogram of combination of 6 carbohydrases (glucoamylase, pullulanase, maltase, thermostable α-amylase, medium temperature α-amylase, and cold-active α-amylase) supplemented in corn-soybean based diet of broilers aged 1 to 3 wk for the maximum starch digestibility, by using in vitro simulated gastrointestinal digestion and response surface method. The third generation of simulated monogastric animal digestion system was used for in vitro digestion experiment. By using single factor completely random design, the optimal supplement levels of single carbohydras were determined by the reducing sugar release amount and improved dry matter digestibility, which were the parameters representing the starch digestibility of the diet. Additionally, Box-Behnken response surface method was used to predict the optimal combination of 6 carbohydrases. The results showed that the optimistic zymogram of 6 carbohydrases in corn-soybean based diet for broilers aged 1 to 3 wk were 297.39 U/g glucoamylase, 549.72 U/g pullulanase, 3.01 U/g maltase, 1,455.73 U/g thermostable α-amylase, 278.64 U/g medium temperature α-amylase, and 1,985.97 U/g cold-active α-amylase, and the associated reduced sugar release amount and improved dry matter digestibility were 215.98 mg/g, and 6.23%, respectively. Furthermore, we conducted in vitro digestion experiments with diets supplemented with the predicted optimistic zymogram and found that the experimental reduced sugar release amount and improved dry matter digestibility were 219.26 mg/g and 6.31% respectively, whose errors to the predicted optimistic reducing sugar release amount and the improved dry matter digestibility were 1.05% and 1.02%. To sum up, the predicted optimal zymogram of 6 carbohydrases in the present study were capable to improve the starch digestibility in diet for broilers aged 1 to 3 wk, which were represented by increased reduced sugar release amount and improved dry matter digestibility.

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Computation-aided engineering of starch-debranching pullulanase from Bacillus thermoleovorans for enhanced thermostability

Cited by 48 publications

References 57 publications

Heterologous Expression and Rational Design of l-asparaginase from Rhizomucor miehei to Improve Thermostability

Heterologous Expression and Rational Design of l-asparaginase from Rhizomucor miehei to Improve Thermostability

Accurate computational evolution of proteins and its dependence on deep learning and machine learning strategies

Optimization of exogenous carbohydrases supplemented in broiler diets using in vitro simulated gastrointestinal digestion and response surface methodology

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