Enzymatic characterization of a thermostable phosphatase from Thermomicrobium roseum and its application for biosynthesis of fructose from maltodextrin

Enhancing Machine-Learning Prediction of Enzyme Catalytic Temperature Optima through Amino Acid Conservation Analysis

Enzymes play a crucial role in various industrial production and pharmaceutical developments, serving as catalysts for numerous biochemical reactions. Determining the optimal catalytic temperature (Topt) of enzymes is crucial for optimizing reaction conditions, enhancing catalytic efficiency, and accelerating the industrial processes. However, due to the limited availability of experimentally determined Topt data and the insufficient accuracy of existing computational methods in predicting Topt, there is an urgent need for a computational approach to predict the Topt values of enzymes accurately. In this study, using phosphatase (EC 3.1.3.X) as an example, we constructed a machine learning model utilizing amino acid frequency and protein molecular weight information as features and employing the K-nearest neighbors regression algorithm to predict the Topt of enzymes. Usually, when conducting engineering for enzyme thermostability, researchers tend not to modify conserved amino acids. Therefore, we utilized this machine learning model to predict the Topt of phosphatase sequences after removing conserved amino acids. We found that the predictive model's mean coefficient of determination (R2) value increased from 0.599 to 0.755 compared to the model based on the complete sequences. Subsequently, experimental validation on 10 phosphatase enzymes with undetermined optimal catalytic temperatures shows that the predicted values of most phosphatase enzymes based on the sequence without conservative amino acids are closer to the experimental optimal catalytic temperature values. This study lays the foundation for the rapid selection of enzymes suitable for industrial conditions.

Functional annotation of haloacid dehalogenase superfamily structural genomics proteins

Haloacid dehalogenases (HAD) are members of a large superfamily that includes many Structural Genomics proteins with poorly characterized functionality. This superfamily consists of multiple types of enzymes that can act as sugar phosphatases, haloacid dehalogenases, phosphonoacetaldehyde hydrolases, ATPases, or phosphate monoesterases. Here, we report on predicted functional annotations and experimental testing by direct biochemical assay for Structural Genomics proteins from the HAD superfamily. To characterize the functions of HAD superfamily members, nine representative HAD proteins and 21 structural genomics proteins are analyzed. Using techniques based on computed chemical and electrostatic properties of individual amino acids, the functions of five structural genomics proteins from the HAD superfamily are predicted and validated by biochemical assays. A dehalogenase-like hydrolase, RSc1362 (Uniprot Q8XZN3, PDB 3UMB) is predicted to be a dehalogenase and dehalogenase activity is confirmed experimentally. Four proteins predicted to be sugar phosphatases are characterized as follows: a sugar phosphatase from Thermophilus volcanium (Uniprot Q978Y6) with trehalose-6-phosphate phosphatase and fructose-6-phosphate phosphatase activity; haloacid dehalogenase-like hydrolase from Bacteroides thetaiotaomicron (Uniprot Q8A2F3; PDB 3NIW) with fructose-6-phosphate phosphatase and sucrose-6-phosphate phosphatase activity; putative phosphatase from Eubacterium rectale (Uniprot D0VWU2; PDB 3DAO) as a sucrose-6-phosphate phosphatase; and hypothetical protein from Geobacillus kaustophilus (Uniprot Q5L139; PDB 2PQ0) as a fructose-6-phosphate phosphatase. Most of these sugar phosphatases showed some substrate promiscuity.

Biomanufacturing by In Vitro Biotransformation (ivBT) Using Purified Cascade Multi-enzymes

In vitro biotransformation (ivBT) refers to the use of an artificial biological reaction system that employs purified enzymes for the one-pot conversion of low-cost materials into biocommodities such as ethanol, organic acids, and amino acids. Unshackled from cell growth and metabolism, ivBT exhibits distinct advantages compared with metabolic engineering, including but not limited to high engineering flexibility, ease of operation, fast reaction rate, high product yields, and good scalability. These characteristics position ivBT as a promising next-generation biomanufacturing platform. Nevertheless, challenges persist in the enhancement of bulk enzyme preparation methods, the acquisition of enzymes with superior catalytic properties, and the development of sophisticated approaches for pathway design and system optimization. In alignment with the workflow of ivBT development, this chapter presents a systematic introduction to pathway design, enzyme mining and engineering, system construction, and system optimization. The chapter also proffers perspectives on ivBT development.

Rapid identification of magnesium ascorbyl phosphate utilizing phosphatase through a chromogenic change-coupled activity assay

In this study, we report a chromogenic reaction between magnesium ascorbyl phosphate (MAP) and ferric chloride to generate a Brown-Red clathrate, while the Treated MAP by phosphatases forms Colorless (BRTC) product with ferric chloride. The BRTC was indicative of phosphatase activity-mediated excision of phosphorous group from MAP and utilized to screen phosphatases from bacterial cell lysates. From ten tested strains, BRTC was observed in the cell lysate of Salmonella enterica subsp. enterica serovar Cerro 87. BRTC was again employed to track phosphatase activity of the resuspensions of the ammonium sulfate graded precipitations of the cell lysate. Two phosphatases, PhoN and YcdX, were identified by LC-MS/MS analysis in the protein fraction giving most obvious BRTC phenotype and validated by examination of in vitro activity of the purified proteins. KEY POINTS: • BRTC is labelling-free, naked-eye visible, and independent of any facilities. • BRTC can directly screen phosphatases from microbial cell lysates. • Using BRTC system, two phosphatases were identified in Salmonella enterica subsp. enterica serovar Cerro 87.