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

Jiahua BiShuhui ChenXianghan ZhaoYao NieYan Xu
Published in: Applied microbiology and biotechnology (2020)
Pullulanases are widely used in food, medicine, and other industries because they specifically hydrolyze α-1,6-glycosidic linkages in starch and oligosaccharides. In addition, high-temperature thermostable pullulanase has multiple advantages, including decreasing saccharification solution viscosity accompanied with enhanced mass transfer and reducing microbial contamination in starch hydrolysis. However, thermophilic pullulanase availability remains limited. Additionally, most do not meet starch-manufacturing requirements due to weak thermostability. Here, we developed a computation-aided strategy to engineer the thermophilic pullulanase from Bacillus thermoleovorans. First, three computational design predictors (FoldX, I-Mutant 3.0, and dDFIRE) were combined to predict stability changes introduced by mutations. After excluding conserved and catalytic sites, 17 mutants were identified. After further experimental verification, we confirmed six positive mutants. Among them, the G692M mutant had the highest thermostability improvement, with 3.8 °C increased Tm and 2.1-fold longer half-life than the wild type at 70 °C. We then characterized the mechanism underlying increased thermostability, such as rigidity enhancement, closer conformation, and strengthened motion correlation using root mean square fluctuation (RMSF), principal component analysis (PCA), dynamic cross-correlation map (DCCM), and free energy landscape (FEL) analysis. KEY POINTS: • A computation-aided strategy was developed to engineer pullulanase thermostability. • Seventeen mutants were identified by combining three computational design predictors. • The G692M mutant was obtained with increased Tmand half-life at 70 °C.
Keyphrases
  • wild type
  • high temperature
  • anaerobic digestion
  • lactic acid
  • risk assessment
  • transcription factor
  • bacillus subtilis
  • drinking water
  • human health
  • single cell
  • mass spectrometry
  • solid state
  • data analysis