Improving high-degree-polymerization GOS synthesis of a marine cold-active β-galactosidase via semi-rational design

Improving high-degree-polymerization GOS synthesis of a marine cold-active β-galactosidase via semi-rational design | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Improving high-degree-polymerization GOS synthesis of a marine cold-active β-galactosidase via semi-rational design Lin Pan, Yali Zhang, Zhe Wang, Chenxu Fan, Qionghui You, Jiahong Wu, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9561301/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 25 You are reading this latest preprint version Abstract Cold-active β-galactosidase has significant application value in the enzymatic synthesis of galacto-oligosaccharides (GOS), but its industrial application is limited by low transglycosylation efficiency and poor selectivity for high-degree-polymerization products. In this study, the cold-active β-galactosidase K3-β-gal was cloned and expressed from marine Bacillus sp. K-3. Four mutants (R252M, F261W, Y281R, F355K) were constructed via semi-rational design, among which mutant R252M showed substantially enhanced transglycosylation activity. This mutant fully retained the favorable temperature and pH adaptability of the wild-type enzyme (optimal temperature 20°C, optimal pH 6.0, and good stability under low-temperature and weakly acidic conditions). The total GOS conversion yield increased from 13.73% to 24.89% (an 81.29% increase), and the DP4/DP3 ratio rose from 0.95 to 1.53. Kinetic analysis revealed that the hydrolytic activity of R252M decreased by approximately 44%, suggesting that the catalytic equilibrium shifted from hydrolysis toward transglycosylation. Molecular dynamics simulations demonstrated that R252M remodeled the hydrogen bond network in the active pocket, enhanced overall protein rigidity, and reduced dynamic perturbations around the active site, thereby optimizing substrate binding and glycosyl transfer efficiency. This study provides a novel strategy for the efficient molecular engineering of cold-active β-galactosidases, and mutant R252M holds good promise for the green synthesis of high-DP GOS. Cold-active β-galactosidase Semi-rational design High-DP galacto-oligosaccharides Transglycosylation efficiency Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 1. Introduction Galacto-oligosaccharides (GOS) are functional oligosaccharides composed of galactose units linked by β-1,4- or β-1,6-glycosidic bonds. They possess significant prebiotic properties,promoting the growth of bifidobacteria and lactobacilli, thereby improving gut microbiota, and exerting effects such as immune regulation and enhanced calcium absorption (Shipkowski et al. 2006;Weng et al. 2014 ;Marles et al. 2017 ). With the growing market demand for high-function prebiotics, the anti-inflammatory activity of GOS, which is dependent on its degree of polymerization, has garnered considerable attention, particularly highlighting its application value in chronic enteritis and immune-enhancing foods (He et al. 2021 ;Ordás et al. 2012 ).Market data show that the annual production of GOS increased from 14,000 tons in 1995 to 21,000 tons in 2009, and the compound annual growth rate is projected to reach 7.9% from 2021 to 2028, which is closely related to its expanding applications in infant formula, elderly nutritional products, and other fields (Marín-Manzano et al. 2013 ). Currently, the industrial production of GOS primarily relies on the transglycosylation reaction catalyzed by β-galactosidases. However, traditional processes face limitations, mainly due to insufficient thermal stability of the enzymes and an imbalance between their transglycosylation and hydrolytic activities, resulting in low GOS yields(Gomes et al. 2021 ;Higuera-Ciapara et al. 2017 ). In contrast, low-temperature β-galactosidases circumvent thermal stability bottlenecks by operating at lower reaction temperatures. They can catalyze reactions efficiently under cold conditions, avoiding protein denaturation and flavor loss in dairy products caused by high temperatures, making them particularly suitable for lactose-free dairy production and cold-chain processes (Wang et al. 2019;Husain et al. 2010).Industry empirical studies have shown that every 10°C reduction in processing temperature can save 8–12% of thermal management energy consumption. Compared with traditional mesophilic enzyme systems (ΔT = 33°C), enzyme preparations adapted to low-temperature processes can theoretically achieve a 15–20% energy saving (Kaviani et al. 2022 ).Therefore, discovering and developing low-temperature β-galactosidases with high activity and transglycosylation efficiency is crucial for advancing the functional food industry and low-temperature biocatalysis technologies. Despite their advantage in low-temperature activity, naturally occurring cold-active enzymes often exhibit limited inherent transglycosylation capacity, which struggles to meet the high efficiency and product specificity demands of industrial production. To enhance enzyme catalytic performance, protein engineering has become a key strategy. Among these, semi-rational design, which combines rational structural analysis with experimental screening, has emerged as a mainstream approach for industrial enzyme optimization (Chica et al. 2005 ;Zhou et al. 2024 ). This method involves targeting key sites (e.g., substrate-binding pockets or catalytic microenvironments) for limited mutagenesis, significantly reducing library complexity while increasing the probability of positive mutations. For instance, by analyzing enzyme three-dimensional structures (e.g., using AlphaFold2 predictions) and performing molecular docking, key residues influencing substrate binding and catalytic efficiency can be identified. Subsequently, small, focused mutant libraries can be designed and screened for precise enzyme optimization (Reetz et al. 2007;Reetz et al. 2006 ). Studies have shown that rational or semi‑rational modification of residues in the active site of β‑galactosidase can effectively improve its transglycosylation efficiency and product specificity. For example, A. Rico‑Díaz et al. (Rico-Díaz et al. 2017 ) performed structural analysis and engineering of β‑galactosidase from Aspergillus niger, successfully increasing the GOS conversion yield from 16% for the wild‑type enzyme to 27%. Liang Li et al. (Li et al. 2015 ) constructed a homology model of BG‑Bgal1‑3 derived from a marine metagenomic library and mutated hydrophobic sites in its active center, ultimately raising the GOS conversion yield from 45.3% to 59.1%. These previous studies provide important methodological references and theoretical foundations for the semi‑rational design approach adopted in this study to optimize the transglycosylation capability of a cold‑active β‑galactosidase. This research is based on the laboratory-preserved, low-temperature, high-yield β-galactosidase-producing strain Bacillus sp. K-3, isolated from Bohai Sea deep-sea sediment. Initially, the β-galactosidase gene K3-β-gal from this strain will be cloned and heterologously expressed in E. coli BL21(DE3). Systematic expression, purification, and enzymatic characterization will be conducted to elucidate its catalytic properties. Building upon this foundation, this study aims to employ a semi-rational design strategy for the molecular engineering of this enzyme to improve its transglycosylation activity. Based on the enzyme's structural model and substrate molecular docking analysis, key amino acid residues affecting catalytic performance will be identified. Site-directed mutagenesis libraries will be constructed to screen for mutants with significantly enhanced transglycosylation capabilities. Finally, through a systematic comparison of the enzymatic properties between the wild-type and the mutants, combined with molecular dynamics simulations, the molecular mechanism by which the mutations affect the catalytic efficiency—particularly the balance between transglycosylation and hydrolysis—will be elucidated at the atomic level. This work not only provides an effective protein engineering paradigm for the directed improvement of low-temperature β-galactosidases for industrial applications but also contributes fundamental knowledge to understanding the structure-function relationships within this enzyme family. Ultimately, it lays a theoretical foundation for the development and utilization of this enzyme in the dairy industry, biomedicine, and other fields requiring low-temperature enzymatic applications. 2. Materials and Methods 2.1 Source of Samples The experimental strain Bacillus sp. K-3 was obtained from the University College of Life Science and Technology (Liaoning Provincial Marine Microbial Engineering Technology Research Center). It was originally isolated from deep-sea mud in the Bohai Sea. The strain is currently preserved at the China Center for Type Culture Collection (CCTCC) in Wuhan, China, with the deposition number M2024513. 2.2 Amplification of the β-Galactosidase Gene K3-β-gal Using the genomic DNA of the marine psychrotrophic strain Bacillus sp. K-3 as a template, degenerate primers were designed based on BLAST alignment against homologous sequences of β-galactosidase genes in the NCBI database. The target gene fragment was amplified by PCR, and its size was verified by agarose gel electrophoresis. The purified product was sent to Sangon Biotech Co., Ltd. for sequencing validation. 2.3 Protein Structure Prediction and Molecular Docking The amino acid sequence of K3-β-gal was subjected to BLAST analysis using the UniProt database ( https://www.uniprot.org ) to retrieve homologous proteins with high similarity and to reference their crystal structures. The three-dimensional structure of K3-β-gal was predicted using the AlphaFold2 online platform ( https://alphafold.ebi.ac.cn/ ), and the predicted structure was aligned with homologous proteins to identify the active pocket. The molecular structure file of GOS3 was downloaded from the PubChem database ( https://pubchem.ncbi.nlm.nih.gov/ ). The receptor protein K3-β-gal was preprocessed using AutoDockTools software for hydrogen addition and charge balancing, and both the receptor and the ligand GOS3 were converted to pdbqt format. Finally, molecular docking was performed using AutoDock Vina 1.1.2 software, and the conformation with the lowest binding free energy was selected for subsequent analysis (Trott et al. 2010). 2.4 Screening of Mutation Sites Based on the high-confidence K3-β-gal structure predicted by AlphaFold2 and the optimal GOS3 conformation obtained from molecular docking, systematic virtual mutagenesis scanning was performed on amino acid residues within the active pocket (within a 5 Å radius of GOS3) using the CHARMm force field. The mutation free energy change (ΔΔG) for each amino acid substitution was calculated. Potential beneficial mutations with ΔΔG < -0.5 kcal/mol were preliminarily screened (Pancotti et al. 2022 ). Subsequently, the initially screened mutants were subjected to re-docking with GOS3 using AutoDock Vina to calculate the binding free energy (ΔGvina), which was comprehensively evaluated together with the mutation energy ( Trott et al. 2010). Meanwhile, sequences of high-transglycosylation-activity enzyme families were retrieved from the NCBI database, and multiple sequence alignment was performed using Clustal Omega to exclude highly conserved catalytic functional regions, ensuring that the final selected mutation sites were located in non-conserved regions. 2.5 Construction and Transformation of Expression Vectors for Wild-Type and Mutants Based on the sequencing-validated wild-type K3-β-gal gene sequence and the mutation schemes determined by semi-rational design, full-length synthesis of wild-type and mutant genes was commissioned to Sangon Biotech Co., Ltd. To facilitate subsequent cloning, XbaI and XhoI restriction sites were introduced at both ends of the coding region. The synthesized gene fragments and the pET28a(+) expression vector were double-digested with XbaI and XhoI, verified by agarose gel electrophoresis, and purified. The digested fragments were ligated using T4 DNA ligase to successfully construct the recombinant expression plasmids pET28a-K3-β-gal (WT) and the respective mutants. The ligation products were transformed into E. coli BL21(DE3) competent cells via heat shock and plated onto LB agar plates containing 50 µg/mL kanamycin, followed by incubation at 37°C for 12–16 hours. Single colonies were picked and subjected to colony PCR and plasmid double digestion for preliminary identification. Positive clones were further confirmed by Sanger sequencing to verify the correct gene sequence and mutation sites. The resulting recombinant strains were preserved in LB medium containing 50% glycerol at -80°C for future use. 2.6 Protein Expression and Purification Recombinant plasmids carrying the wild-type or mutant β-galactosidase genes were separately transformed into E. coli BL21(DE3) competent cells. Positive single colonies were inoculated into LB liquid medium containing 50 µg/mL kanamycin and cultured overnight at 37°C with shaking. The overnight culture was then transferred (1:100) into fresh LB medium (containing 50 µg/mL kanamycin) and grown until OD600 reached 0.6–0.8. Protein expression was induced by adding isopropyl-β-D-thiogalactopyranoside (IPTG) to a final concentration of 0.2 mM, and the culture was further incubated at 15°C and 100 r/min for 16–18 h. Cells were harvested by centrifugation, resuspended in binding buffer (20 mM Tris-HCl, pH 8.0), and disrupted by ultrasonication. After centrifugation, the supernatant was collected and mixed with Ni-NTA affinity resin. Unbound proteins were washed away with binding buffer, and the target protein was eluted stepwise with elution buffers (20 mM Tris-HCl, pH 8.0) containing 80 mM and 150 mM imidazole, respectively. The fraction eluted with 150 mM imidazole was collected. The purified enzyme was concentrated and desalted using a 10 kDa cutoff ultrafiltration tube. 2.7 Enzyme Activity Assay One unit of enzyme activity was defined as the amount of enzyme required to hydrolyze oNPG to produce 1 µmol of o-nitrophenol (oNP) per minute. The reaction mixture consisted of 50.0 µL of 4 mg/mL oNPG in phosphate buffer (pH 7.0) and 50.0 µL of appropriately diluted enzyme solution (in 0.1 mol/L phosphate buffer, pH 7.0). The mixture was incubated at 15°C for 15 min (or at 37°C for 10 min), and the reaction was terminated by adding 200.0 µL of pre-cooled 0.5 mol/L Na₂CO₃. After thorough mixing, the absorbance at OD 420 was measured. Each sample was tested in triplicate, and a blank control was included (Greenberg et al. 1982). 2.8 Evaluation of Transglycosylation Activity and Analysis of Enzymatic Properties of the Wild‑Type and Mutant Enzymes 2.8.1 Preliminary screening of transglycosylation activity by thin-layer chromatography (TLC) Using lactose as a substrate, reactions were catalyzed by the wild-type and mutant enzymes (R252M, F261W, Y281R, F355K). The reaction mixtures were spotted onto an activated silica gel TLC plate. The plate was developed with a solvent system consisting of isopropanol, n-butanol, acetic acid, and water (3:1:1:1, by volume), air-dried, and visualized using 5% sulfuric acid-ethanol solution. Positive mutants were identified based on the formation of oligosaccharide (DP3, DP4) spots. 2.8.2 Determination of enzymatic properties (1) Optimum temperature and temperature stability: Using oNPG as a substrate, enzyme activity was measured in a pH 7.0 buffer system over a temperature gradient from − 20°C to 70°C to determine the optimum reaction temperature. For thermostability assessment, the enzyme solution was pre-incubated at various temperatures for 3 h, and the residual activity was measured at 20°C. (2) Optimum pH and pH stability: Enzyme activity was measured at 20°C in buffer systems ranging from pH 3.0 to 12.0 (1.0 intervals) to determine the optimum pH. For pH stability assessment, the enzyme solution was pre-treated at different pH values for 3 h, then adjusted to pH 6.0, and the residual activity was measured. (3) Enzyme kinetics: Under conditions of pH 6.0 and 20°C, initial reaction rates were determined using oNPG as a substrate at concentrations ranging from 0.1 to 5 µmol/mL. Kinetic parameters (K m , K cat , and K cat /K m ) were calculated using the Lineweaver-Burk double-reciprocal plot method. (4) Transglycosylation activity and GOS yield determination: The reaction was carried out with 100 g/L lactose in 20 mM Tris-HCl buffer (pH 6.0) at an enzyme loading of 5 U/g, under 20°C and 120 r/min for 12 h. The reaction mixture was then incubated in boiling water for 20 min to inactivate the enzyme, followed by centrifugation. The supernatant was collected, deproteinized by the Savage method, and filtered through a 0.22 µm membrane. The resulting sugar solution was analyzed by an HPLC system equipped with a refractive index detector (35°C) and a TSKgel Amide-80 column (4.6 mm × 25 cm, 5 µm). The mobile phase was acetonitrile-water (60:40, V/V) at a flow rate of 0.6 mL/min. The yields of DP3, DP4, and total GOS were quantified using an external standard method. 2.9 Molecular Dynamics Simulation Based on the docking results of the wild-type (WT) and the R252M mutant with GOS₃, the complexes with the most favorable conformations were selected for molecular dynamics (MD) simulations. MD simulations were performed using the GROMACS 5.0 software package with the CHARMM36 force field under periodic boundary conditions(Huang et al. 2013). The ligand topology files were generated using the CHARMM general force field (CGenFF)(Vanommeslaeghe et al. 2010 ). Ions were added to neutralize the system charge. Energy minimization was carried out using the steepest descent algorithm to eliminate close contacts. Electrostatic and van der Waals interactions were calculated using the particle mesh Ewald (PME) method. The system was first equilibrated in the NVT ensemble for 50,000 steps, followed by a second equilibration in the NPT ensemble for 50,000 steps. Finally, a 100 ns MD simulation was performed at 300 K with a time step of 2.0 fs, and coordinates were saved every picosecond for subsequent analysis (Dolezal et al. 2016 ;Childers et al. 2018). Based on the simulation trajectories, the root-mean-square deviation (RMSD) of the protein backbone, the root-mean-square fluctuation (RMSF), and the hydrogen bond dynamics of the enzyme-substrate complex were analyzed. 3. Results and discussion 3.1 Amplification of β-Galactosidase K3-β-gal Specific primers were designed to amplify the β-galactosidase K3-β-gal coding sequence from the genomic DNA of Bacillus sp. K-3 using PCR. The amplified fragment was double-digested with NdeI and XhoI, and agarose gel electrophoresis revealed a distinct band of approximately 2,000 bp ( Figure. 1 ), which was consistent with the expected product size. DNA sequencing confirmed that the obtained gene sequence was 2,115 bp in length, matching the theoretical prediction exactly, thereby verifying the successful amplification of the target gene. 3.2 Protein Structure Prediction and Molecular Docking BLAST analysis identified a resolved structural protein (PDB ID: 5dfa) sharing 72% sequence homology with the target protein. Based on the literature, the catalytic residues of the homologous protein were determined as Glu323 (nucleophile) and Glu159 (acid/base). As shown in Figure. 2a , the three-dimensional structure of the target protein was predicted using A-fold2, and superposition with 5dfa identified the corresponding catalytic sites as Glu154 and Glu317. Subsequently, GOS3 was docked into the active pocket defined by these residues. As illustrated in Figure. 2b , hydrogen-bonding interactions were observed between GOS3 and ARG115, Glu154, ARG252, SER156, ASP254, TRP325, and GLU365 of the target protein. 3.3 Screening of Mutation Sites Using the amino acid residues defined in Fig. 2 b as the active pocket, the substrate GOS3 was docked into this pocket. The results showed that GOS3 formed hydrogen-bonding interactions with residues ARG115, Glu154, ARG252, SER156, ASP254, TRP325, and GLU365 of the protein. Further analysis of amino acid residues within 5 Å of the active pocket identified 20 key sites, namely: ARG115, HIS116, SER156, GLU154, GLN262, ARG252, ALA253, ASP254, THR255, PHE261, ASP279, TYR281, GLU317, TRP325, PHE355, GLU365, HIS368, SER263, ARG102, and GLY157 ( Figure. 3a ). All possible single-point mutations were simulated for the above 20 sites, and the change in free energy (ΔΔG) was calculated for each mutation scheme. As a result, 24 stabilizing mutations were identified (Figure. 3a). By further integrating the ΔG vina values for docking of each mutant with GOS3 ( Figure. 3b ), candidate mutation schemes including R252M, D279K, Y281R, D279N, D254E, W325Q, F355K, D279I, D279H, and F261W were preliminarily selected. To evaluate the evolutionary conservation of these sites, multiple sequence alignment was performed using previously reported β-galactosidases with strong transglycosylation activity ( Figure. 4 ). The results revealed that ASP254, ASP279, and TRP325 were highly conserved; introducing mutations at these sites might significantly affect the biological function of the enzyme, and therefore they were not included in the subsequent mutation design. Based on the above analysis, R252M, F261W, Y281R, and F355K were finally selected as the mutation schemes for further study. 3.4 Expression and Purification of Wild-Type and Mutant Proteins Recombinant expression strains of the wild-type and mutants (R252M, F261W, Y281R, F355K) were successfully constructed. Following induced expression and purification by Ni-NTA affinity chromatography, SDS-PAGE analysis revealed a distinct protein band at approximately 72 kDa for each protein, which was highly consistent with the expected molecular weight of 78 kDa (Fig. 5 ). The target proteins from all five strains were successfully purified, providing reliable experimental materials for subsequent enzymatic characterization and transglycosylation activity evaluation. 3.5 Screening of Positive Mutants and Comparative Biochemical Characterization of WT and Mutants As shown in Fig. 6 , significant differences were observed in the hydrolytic and transglycosylation activities of different mutants toward lactose and oligosaccharides. In the control group, the spots of sugars remained unchanged, indicating no hydrolysis occurred. The wild-type (WT) enzyme exhibited strong hydrolytic activity, with only weak generation of oligosaccharide spots. In contrast, mutant R252M showed higher transglycosylation activity: upon lactose hydrolysis, it not only produced monosaccharides but also generated more oligosaccharides (e.g., DP3 and DP4), with increased spot intensities, suggesting that this mutant favors transglycosylation over complete hydrolysis. Compared with the WT, the other mutants (F261W, Y281R, F355K) exhibited weaker lactose hydrolysis and produced fewer oligosaccharides, demonstrating no advantage in enhancing transglycosylation activity. Therefore, mutant R252M was selected for subsequent enzymatic characterization and kinetic analysis. High-performance liquid chromatography (HPLC) was used to quantitatively analyze the products of lactose catalysis by the wild-type K3-β-gal and the mutant R252M. As shown in Fig. 7 , the total GOS conversion rate of the wild-type enzyme was 13.73%, with DP3 and DP4 conversion rates of 11.10% and 10.58%, respectively. The ratio of DP4 to DP3 conversion was approximately 1:1 (slightly below 1), indicating that the wild-type enzyme had comparable abilities to synthesize tri- and tetrasaccharides. Under the same conditions, the total GOS conversion rate of the R252M mutant increased to 24.89%, with DP3 and DP4 conversion rates of 10.60% and 16.19%, respectively. Compared with the wild-type, the mutant exhibited an 81.29% increase in total GOS conversion. Notably, the DP4/DP3 conversion ratio increased from below 1 for the wild-type to 1.53 for the mutant, suggesting that the mutation significantly enhanced the enzyme's ability to synthesize higher-degree-of-polymerization galacto-oligosaccharides (especially DP4), while the DP3 conversion rate remained largely unchanged. These results indicate that the R252M mutation effectively improves the transglycosylation activity of the enzyme and alters the product distribution, favoring tetrasaccharide synthesis. As shown in Fig. 8 , the optimal reaction temperature and optimal pH of the mutant R252M were consistent with those of the wild-type (WT) enzyme, being 20°C and pH 6.0, respectively. The WT enzyme retained approximately 80% of its relative activity at 30°C, decreased to below 70% after 40°C, and remained less than 50% above 60°C. After incubation at − 20°C to 40°C for 3 h, the WT enzyme maintained about 90% of its activity, while activity rapidly diminished above 55°C (< 60%). Regarding pH, the activity of the WT enzyme decreased to about 50% at pH 4.0 and dropped below 20% at pH 12.0. The WT enzyme retained more than 80% of its activity after 3 h of treatment in the pH range of 4.0–8.0, whereas its stability sharply declined at pH ≥ 10.0. The temperature and pH response profiles of R252M were highly consistent with those of the WT, indicating that the mutation did not alter the intrinsic sensitivity of the enzyme to these environmental parameters. Based on the Lineweaver‑Burk plot analysis in Fig. 9 and the comparison of enzymatic kinetic parameters in Table 1 , the kinetic parameters of β‑galactosidase K3‑β‑gal (WT) were as follows: K m = 1.789 mM, K cat = 17.093 min⁻¹, and K cat /K m = 9.554 mM⁻¹·min⁻¹. In contrast, the R252M mutant exhibited a K m of 2.361 mM, K cat of 12.65 min⁻¹, and K cat /K m of 5.358 mM⁻¹·min⁻¹. Both K cat and K cat /K m decreased, indicating that the mutation reduced the enzyme's affinity for the substrate oNPG, weakened its catalytic efficiency (decreased K cat , slower hydrolysis rate), and lowered the overall hydrolytic activity toward oNPG (approximately 44% decrease in K cat /K m ). It is speculated that the R252M mutation alters the active site conformation, potentially disrupting the hydrogen bond network or adjusting the charge distribution, thereby impairing the binding stability with oNPG and reducing substrate conversion efficiency. These results suggest that the mutation may limit certain aspects of enzyme function through a combination of local active site destabilization and global conformational dynamics, providing important experimental insights for understanding mutation‑function relationships and for directed enzyme engineering. Table 1 Comparison of enzymatic kinetics parameters between K3-β-gal and R252M 3.6 Molecular Dynamics Simulation 3.6.1 Simulation of the binding modes of WT and R252M mutant with GOS₃ Type of enzyme K m (mM) K cat (min -1 ) K cat /K m (min -1 ·mM -1 ) WT 1.789 17.093 9.554 R252M 2361 12.65 5.358 As shown in Fig. 10 , comparison of the binding modes of the wild‑type (WT) enzyme and the R252M mutant with GOS₃ revealed that the WT enzyme relies on key residues including SER156, ARG115, ARG252, ASP254, GLU154, GLU365, and TRP325 to form a tight network through hydrogen bonds and weak interactions, thereby stabilizing the substrate and maintaining the function of the β‑galactosidase active site to sustain the transglycosylation reaction. In contrast, in the R252M mutant, ARG252 and SER156 are replaced by GLN262 and SER263, and additionally ASP279 and HIS368 are introduced to participate in binding, leading to remodeling of the active site architecture. The mutant forms a new hydrogen bond between HIS368 and ASP279, which enhances the accessibility of the active site while preserving the stability of the core region (e.g., GLU154). This not only does not disrupt substrate binding but may also improve substrate binding flexibility through optimized charge distribution and spatial accommodation, facilitating the entry of higher‑degree‑of‑polymerization oligosaccharides into the active center (Noriega et al. 2024 ). These observations suggest that the catalytic adaptability and capacity for transglycosylation to produce long‑chain galacto‑oligosaccharides of the mutant may be superior to those of the WT enzyme. 3.6.2 Hydrogen bond dynamics analysis of WT and R252M mutant with GOS₃ As shown in Fig. 11 , hydrogen bond dynamics analysis of the wild-type (WT) and R252M mutant enzymes with GOS₃ revealed significant differences in both the number and stability of hydrogen bonds. The number of hydrogen bonds in the WT enzyme fluctuated considerably over different simulation periods. Overall, the hydrogen bond count was relatively low and exhibited breakage or reduction at various time points. In the early stage of the simulation (0–20,000 ps), the WT enzyme formed strong hydrogen bonds with GOS₃ (6–8 bonds). During the middle stage (20,000–60,000 ps), the hydrogen bond number stabilized at 4–6, but showed clear instability in the mid-to-late period. In the late stage (60,000–100,000 ps), the hydrogen bond count decreased significantly, even approaching zero, indicating weakening of the enzyme-substrate interaction, possibly due to substrate dissociation or enzyme conformational changes. In contrast, the R252M mutant enzyme exhibited much higher stability in hydrogen bond number throughout the simulation. In the early stage (0–20,000 ps), similar to the WT enzyme, the hydrogen bond count was high with small fluctuations, indicating more consistent enzyme-substrate interactions. During the middle stage (20,000–60,000 ps), the hydrogen bond number remained stable at 4–6 with relatively uniform fluctuations. In the late stage (60,000–100,000 ps), although the hydrogen bond count decreased, it remained at a higher level than that of the WT enzyme, suggesting that the R252M mutant binds the substrate more stably. The stability of hydrogen bonds directly affects the transglycosylation activity of the enzyme. The reduction in hydrogen bonds during the middle stage and the significant bond breakage and substrate dissociation in the late stage of the WT enzyme led to weaker binding stability with GOS₃. This unstable binding caused frequent detachment or repositioning of the substrate at the active site, shortening the effective binding time and thereby reducing transglycosylation efficiency. In contrast, the relatively stable hydrogen bonds of the R252M mutant, particularly in the late stage, enabled more effective maintenance of the enzyme-substrate complex stability, thereby enhancing transglycosylation efficiency. Therefore, the R252M mutation may promote stronger enzyme-substrate binding by improving hydrogen bond stability, thus increasing transglycosylation capacity (Huyghues-Despointes et al. 2001 ). 3.6.3 RMSD analysis of WT and R252M mutant with GOS₃ As shown in Fig. 12 , the RMSD analysis of WT‑GOS₃ revealed that the RMSD value gradually increased from 0.1 nm to nearly 0.25 nm over the simulation period of 0 to 100 ns, reaching a relatively high fluctuation range after 80 ns. This indicates that the WT protein became increasingly unstable during the molecular dynamics simulation, potentially leading to structural changes in the substrate binding site, which is unfavorable for the binding and transfer of long‑chain oligosaccharides and consequently reduces the transglycosylation efficiency. In contrast, the RMSD analysis of R252M‑GOS₃ showed that the RMSD value remained within a low range of 0.1 nm to 0.2 nm throughout the 100 ns simulation, with overall small fluctuations. The consistently lower RMSD value of the R252M mutant during the entire simulation suggests that the mutant protein structure is more stable, and the mutation enhanced the overall rigidity and stability of the protein. Higher structural stability may provide a more favorable environment, leading to a more stable substrate binding site and thereby enhancing transglycosylation efficiency. The RMSD fluctuation of a protein reflects the flexibility of its overall structure (da Fonseca et al. 2024 ). Appropriate flexibility is crucial for enzyme function: an overly rigid structure may restrict substrate access to the active site, whereas an overly loose structure may lead to unstable substrate binding. Compared with the linear increase in RMSD of WT, the RMSD of R252M changed more smoothly, indicating that the mutant maintained moderate flexibility and balance throughout the simulation, which is conducive to substrate binding and reaction progression. 3.6.4 RMSF analysis of WT and R252M mutant with GOS₃ As shown in Fig. 13 , the analysis of the binding dynamics of the wild-type (WT) and R252M mutant with GOS₃ based on RMSF revealed the following. The RMSF profile of the WT enzyme exhibited significant fluctuation peaks near the active site and in the mid-to-late regions, which may lead to unstable substrate binding and limit transglycosylation efficiency. In contrast, the overall RMSF fluctuations of the R252M mutant were reduced. Lower RMSF fluctuations indicate that the corresponding regions are more rigid and stable. Moreover, the decrease in RMSF values of residues near the active site suggests that the active site structure becomes more stable after mutation. This rigidification not only consolidates the GOS₃ binding site but also provides more precise spatial positioning for the transfer of long-chain galacto-oligosaccharide groups, thereby optimizing the catalytic microenvironment by reducing unproductive conformational fluctuations and further enhancing transglycosylation efficiency. 4. Conclusion In this study, mutant R252M completely retained the favorable temperature and pH adaptability of the wild-type enzyme (optimal temperature 20°C, optimal pH 6.0, and good stability in the ranges of − 20°C to 40°C and pH 4.0–8.0), while its transglycosylation activity was significantly enhanced: the total GOS conversion yield increased from 13.73% (WT) to 24.89% (a 81.29% increase), and the synthesis of high-degree-of-polymerization product DP4 was particularly prominent, with the DP4/DP3 ratio rising from 0.95 to 1.53. Notably, kinetic analysis using oNPG as substrate showed that the Kcat/Km of R252M decreased by approximately 44% (from 9.554 to 5.358 min⁻¹·mM⁻¹) compared with WT, indicating that the mutation also attenuated the hydrolytic activity of the enzyme. This opposite trend of “decreased hydrolysis but increased transglycosylation” suggests that the R252M mutation may redirect the catalytic equilibrium from the hydrolysis pathway toward the transglycosylation pathway by reshaping the active site conformation. Molecular dynamics simulations further revealed the structural basis: the mutant replaced ARG252 with MET and introduced new residues ASP279 and HIS368, which remodeled the hydrogen bond network in the active pocket, resulting in substantially higher stability of the enzyme–substrate complex hydrogen bonds than that of WT; meanwhile, the overall RMSD value decreased and the RMSF fluctuation around the active site was reduced, indicating enhanced protein rigidity and diminished catalytic microenvironment perturbation. These mechanisms jointly optimized substrate binding and glycosyl transfer efficiency, providing a molecular explanation for the efficient synthesis of high-DP galacto-oligosaccharides by R252M under low-temperature conditions. Given the prominent prebiotic value of high-DP GOS in anti-inflammation, immune regulation, and gut health, this mutant holds promise as a novel enzyme preparation for functional food and pharmaceutical applications. Future work may further increase transglycosylation yield and product specificity through combinatorial mutagenesis (e.g., the R252M/Y281R double mutant) or iterative saturation mutagenesis; determination of the three-dimensional structure of the mutant by cryo-EM or X-ray crystallography will elucidate the precise relationship between conformational changes and catalytic preference switching. Moreover, validation of its low-temperature process adaptability in real dairy matrices and the development of immobilized or whole-cell catalytic systems will promote the industrial translation of this enzyme. Declarations Conflict of interest The authors declare no competing interests. Author Contribution L.P. drafted the main manuscript text; L.P., Y.Z., and Z.W. jointly designed the experimental protocols; C.F., Q.Y., J.W., and F.F. performed the experiments; all authors reviewed and revised the manuscript. Acknowledgement This work was supported by the Youth Science Fund Project of the National Natural Science Foundation of China (Grant No. 31500039), the Dalian Youth Science and Technology Star Project (Grant No. 2017RQ155), and the Natural Science Foundation of Liaoning Province (Grant No. 20180550728). Data availability No new datasets were generated or analyzed during this study. References Shipkowski S, Brenchley JE (2006) Bioinformatic, genetic, and biochemical evidence that some glycoside hydrolase family 42 beta-galactosidases are arabinogalactan type I oligomer hydrolases[J]. Appl Environ Microbiol 72(12):7730–7738. https://doi.org/10.1128/AEM.01306-06 Weng W, Tang L, Wang B, Chen J, Su W, Osako K, Tanaka M (2014) Antioxidant properties of fractions isolated from blue shark (Prionace glauca) skin gelatin hydrolysates[J]. J Funct Foods 11:342–351. https://doi.org/10.1016/j.jff.2014.10.021 Marles RJ, Roe AL, Oketch-Rabah HA (2017) US Pharmacopeial Convention safety evaluation of menaquinone-7, a form of vitamin K[J]. Nutr Rev 75(7):553–578. https://doi.org/10.1093/nutrit/nux022 He N, Chen H, Zhou Z et al (2021) Enzymatically synthesized α-galactooligosaccharides attenuate metabolic syndrome in high-fat diet induced mice in association with the modulation of gut microbiota[J]. Food Funct 12(11):4960–4971. https://doi.org/10.1039/d0fo03113e Ordás I, Eckmann L, Talamini M, Baumgart DC, Sandborn WJ (2012) Ulcerative colitis[J]. Lancet 380(9853):1606–1619. https://doi.org/10.1016/S0140-6736(12)60150-0 Marín-Manzano MD, Abecia L, Hernández-Hernández O, Sanz ML, Montilla A, Olano A, Rubio LA, Moreno FJ, Clemente A (2013) Galacto-oligosaccharides derived from lactulose exert a selective stimulation on the growth of Bifidobacterium animalis in the large intestine of growing rats[J]. J Agric Food Chem 61(31):7560–7567. https://doi.org/10.1021/jf402218z Gomes HO, Cardoso RS, da Costa JGM, Andrade da Silva VP, Nobre CA, Pereira Teixeira RN, do Nascimento RF (2021) Statistical evaluation of analytical curves for quantification of pesticides in bananas[J]. Food Chem 345:128768. https://doi.org/10.1016/j.foodchem.2020.128768 Higuera-Ciapara I, Virués C, Jiménez-Chávez M et al (2017) 1H NMR studies of molecular interaction of D-glucosamine and N-acetyl-D-glucosamine with capsaicin in aqueous and non-aqueous media[J]. Carbohydr Res 452:6–16. https://doi.org/10.1016/j.carres.2017.09.014 Wang X (2019) Strategy for improving L-isoleucine production efficiency in Corynebacterium glutamicum[J]. Appl Microbiol Biotechnol 103(5):2101–2111. https://doi.org/10.1007/s00253-019-09632-2 Husain Q (2010) Beta galactosidases and their potential applications: a review[J]. Crit Rev Biotechnol 30(1):41–62. https://doi.org/10.3109/07388550903330497 Kaviani A, Aslani A, Zahedi R, Ahmadi H, Malekli MR (2022) A new approach for energy optimization in dairy industry[J]. Clean Eng Technol 8:100498. https://doi.org/10.1016/j.clet.2022.100498 Chica RA, Doucet N, Pelletier JN (2005) Semi-rational approaches to engineering enzyme activity: combining the benefits of directed evolution and rational design[J]. Curr Opin Biotechnol 16(4):378–384. https://doi.org/10.1016/j.copbio.2005.06.004 Zhou L, Tao C, Shen X, Sun X, Wang J, Yuan Q (2024) Unlocking the potential of enzyme engineering via rational computational design strategies[J]. Biotechnol Adv 73:108376. https://doi.org/10.1016/j.biotechadv.2024.108376 Reetz MT, Carballeira JD (2007) Iterative saturation mutagenesis (ISM) for rapid directed evolution of functional enzymes[J]. Nat Protoc 2(4):891–903. https://doi.org/10.1038/nprot.2007.72 Reetz MT, Carballeira JD, Vogel A (2006) Iterative saturation mutagenesis on the basis of B factors as a strategy for increasing protein thermostability[J]. Angew Chem Int Ed 45(45):7745–7751. https://doi.org/10.1002/anie.200602795 Rico-Díaz A, Ramírez-Escudero M, Vizoso-Vázquez Á, Cerdán ME, Becerra M, Sanz-Aparicio J (2017) Structural features of Aspergillus niger β-galactosidase define its activity against glycoside linkages[J]. FEBS J 284(12):1815–1829. https://doi.org/10.1111/febs.14083 Li L, Li G, Cao LC et al (2015) Characterization of the cross-linked enzyme aggregates of a novel β-galactosidase, a potential catalyst for the synthesis of galacto-oligosaccharides[J]. J Agric Food Chem 63(3):894–901. https://doi.org/10.1021/jf504473k Trott O, Olson AJ (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading[J]. J Comput Chem 31(2):455–461. https://doi.org/10.1002/jcc.21334 Pancotti C, Benevenuta S, Birolo G et al (2022) Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset[J]. Brief Bioinform 23(1):bbab555. https://doi.org/10.1093/bib/bbab555 Trott O, Olson AJ (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading[J]. J Comput Chem 31(2):455–461. https://doi.org/10.1002/jcc.21334 Greenberg NA, Mahoney RR (1982) Production and characterization of β-galactosidase from Streptococcus thermophilus[J]. J Food Sci 47(6):1824–1835. https://doi.org/10.1111/j.1365-2621.1982.tb12891.x Huang J, MacKerell AD Jr (2013) CHARMM36 all-atom additive protein force field: validation based on comparison to NMR data[J]. J Comput Chem 34(25):2135–2145. https://doi.org/10.1002/jcc.23354 Vanommeslaeghe K, Hatcher E, Acharya C et al (2010) CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields[J]. J Comput Chem 31(4):671–690. https://doi.org/10.1002/jcc.21367 Dolezal R, Soukup O, Malinak D et al (2016) Towards understanding the mechanism of action of antibacterial N-alkyl-3-hydroxypyridinium salts: Biological activities, molecular modeling and QSAR studies[J]. Eur J Med Chem 121:699–711. https://doi.org/10.1016/j.ejmech.2016.05.058 Childers MC, Daggett V (2018) Validating Molecular Dynamics Simulations against Experimental Observables in Light of Underlying Conformational Ensembles[J]. J Phys Chem B 122(26):6673–6689. https://doi.org/10.1021/acs.jpcb.8b02144 Noriega MA, Rico-Rodríguez F, Rosales JD, Serrato-Bermúdez JC (2024) Kinetics of galactooligosaccharides (GOS) production with two β-galactosidases: Metallic ion effect and mathematical model[J]. Chem Eng Res Des 212:341–348. https://doi.org/10.1016/j.cherd.2024.11.001 Huyghues-Despointes A, Pace CN, Englander SW, Scholtz JM (2001) Measuring the conformational stability of a protein by hydrogen exchange[M]. In: Murphy KP (ed) Protein Structure, Stability, and Folding, Methods in Molecular Biology, vol 168. Humana, Totowa, NJ, pp 69–94. https://doi.org/10.1385/1-59259-193-0:069 da Fonseca AM, Caluaco BJ, Madureira JMC et al (2024) Screening of potential inhibitors targeting the main protease structure of SARS-CoV-2 via molecular docking, and approach with molecular dynamics, RMSD, RMSF, H-bond, SASA and MMGBSA[J]. Mol Biotechnol 66(8):1919–1933. https://doi.org/10.1007/s12033-023-00831-x Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9561301","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":637613611,"identity":"053f044a-5ea3-47be-9e0f-8922be9df070","order_by":0,"name":"Lin Pan","email":"","orcid":"","institution":"Dalian University","correspondingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"Pan","suffix":""},{"id":637613612,"identity":"252d3f9b-fe95-4ee5-8fb3-a4b0a0e24b0b","order_by":1,"name":"Yali Zhang","email":"","orcid":"","institution":"Dalian University","correspondingAuthor":false,"prefix":"","firstName":"Yali","middleName":"","lastName":"Zhang","suffix":""},{"id":637613613,"identity":"b7c5c2fd-b39e-49eb-b533-84d731362ab0","order_by":2,"name":"Zhe Wang","email":"","orcid":"","institution":"Dalian University","correspondingAuthor":false,"prefix":"","firstName":"Zhe","middleName":"","lastName":"Wang","suffix":""},{"id":637613614,"identity":"3718cedd-83ec-4665-b374-43c8c26e5833","order_by":3,"name":"Chenxu Fan","email":"","orcid":"","institution":"Dalian University","correspondingAuthor":false,"prefix":"","firstName":"Chenxu","middleName":"","lastName":"Fan","suffix":""},{"id":637613615,"identity":"fc521e7b-f9aa-428c-a7ab-2851c67475c6","order_by":4,"name":"Qionghui You","email":"","orcid":"","institution":"Dalian University","correspondingAuthor":false,"prefix":"","firstName":"Qionghui","middleName":"","lastName":"You","suffix":""},{"id":637613616,"identity":"9a27edd0-f20a-499a-9eda-e99bbb23829c","order_by":5,"name":"Jiahong Wu","email":"","orcid":"","institution":"Dalian University","correspondingAuthor":false,"prefix":"","firstName":"Jiahong","middleName":"","lastName":"Wu","suffix":""},{"id":637613617,"identity":"2d50f614-2738-4609-a573-57f48af512a3","order_by":6,"name":"Fangqi Feng","email":"","orcid":"","institution":"Dalian University","correspondingAuthor":false,"prefix":"","firstName":"Fangqi","middleName":"","lastName":"Feng","suffix":""},{"id":637613618,"identity":"7eced8a5-432c-4547-9e5a-b9afc08d2b72","order_by":7,"name":"Xiaohui Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIiWNgGAWjYNACAxBibHzAUwDiJRCvpdmAx4BoLRBdbBJEaTE4fvbwa54COzlzieS2ijcGhxn42XMMGH7uwKPlTF6a5QyDZGPLGYltN+cAtUj2vDFg7D2DW4vZgRwzgw8GzIkbbiS23eYBajG4kWPAzNiGR8v5N2YGCQb1YC3FIC32BLXcyDF+8MHgMFgLM9gWCQJa7G+8MWOcYXDc2ODMw2bJOQbpPBJnnhUc7MWjRbI/x/gzz59qOYPj6Q8/vKmwluNvT9744CceLQyg6EDm8YCIA3g1MDAwfyCgYBSMglEwCkY6AAA8vVHeVehY7AAAAABJRU5ErkJggg==","orcid":"","institution":"Dalian University","correspondingAuthor":true,"prefix":"","firstName":"Xiaohui","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2026-04-29 06:38:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9561301/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9561301/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108954794,"identity":"226f4109-563b-4bed-8cd6-255753bbedf8","added_by":"auto","created_at":"2026-05-11 07:59:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":79410,"visible":true,"origin":"","legend":"\u003cp\u003ePCR amplification results of \u003cem\u003eBacillus\u003c/em\u003e sp. K3-β-gal gene.Note: Lanes 1 and 2 both represent the double‑digested fragment of the K3-β-gal gene; Lane 2 is the DNA marker, with molecular sizes (in bp) indicated on the right.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9561301/v1/498684393b07a5e57f1c6634.png"},{"id":108954773,"identity":"84ba1b3f-3d2a-4d3b-b7b9-c133a1c4056b","added_by":"auto","created_at":"2026-05-11 07:59:19","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":411068,"visible":true,"origin":"","legend":"\u003cp\u003ePrediction of the K3-β-gal protein structure and molecular docking results. a: K3-βgal enzyme gene is superimposed with 5dfa structure (green is 5dfa); b: K3-βgal enzyme gene docking results with GOS3\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9561301/v1/7d7c85a1b1f1b451550e6ba5.png"},{"id":108954777,"identity":"878d4e6c-b9cb-4609-a704-6cf6c1e673b8","added_by":"auto","created_at":"2026-05-11 07:59:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":217141,"visible":true,"origin":"","legend":"\u003cp\u003eComputational screening of mutation sites based on predicted stability changes (ΔΔG) and docking affinity (ΔG_vina).(a) ΔΔG values of all single-point mutations at the 20 active-site residues. (b) ΔG_vina values of mutants with ΔΔG \u0026lt; –0.5 upon docking with GOS3.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9561301/v1/72578a5c1a94d13efe6d3780.png"},{"id":108954677,"identity":"ddf9d018-be45-49ce-a251-cca85b6182ac","added_by":"auto","created_at":"2026-05-11 07:58:55","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":558180,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of conserved sites between K3-β-Gal and β-galactosidases with high transglycosylation capacity.Note: Green boxes indicate conserved regions, and red boxes indicate non-conserved regions.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9561301/v1/746f10a75438aa72fcbf8beb.png"},{"id":108954778,"identity":"936ec5cd-212a-4c39-a9e3-b165a5a1411c","added_by":"auto","created_at":"2026-05-11 07:59:22","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":117969,"visible":true,"origin":"","legend":"\u003cp\u003eSDS-PAGE analysis of purified recombinant β-galactosidase K3-β-gal (WT and mutants).Note: Lanes 1-6:Marker;WT; R252M; F261W; Y281R; F355K.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-9561301/v1/1e0c5d1307982cc4873ab4c5.png"},{"id":108954781,"identity":"b7000011-93ac-4b50-9a2f-68932bad5260","added_by":"auto","created_at":"2026-05-11 07:59:23","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":343832,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of thin layer chromatography.Note: A: lactose; B: galactose; C: glucose; D: GOS; E: DP3; F: DP4; G: control group; H: WT; I: R252M; J: F261W; K: Y281R; L: F355K.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-9561301/v1/df76972ae35c80c34693a56f.png"},{"id":108954675,"identity":"7ba34182-f845-4112-a16d-d62d01dd164f","added_by":"auto","created_at":"2026-05-11 07:58:54","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":200441,"visible":true,"origin":"","legend":"\u003cp\u003eHPLC chromatographic analysis of lactose degradation products by WT and R252M\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-9561301/v1/37d088bfe5ed108367b72902.png"},{"id":108954747,"identity":"4a130294-a2d3-4028-99ff-5c00c65fab18","added_by":"auto","created_at":"2026-05-11 07:59:10","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":163258,"visible":true,"origin":"","legend":"\u003cp\u003eTemperature and pH activity and stability profiles of wild-type (WT) and mutant R252M.(a) Temperature activity and stability profiles of WT;(b) pH activity and stability profiles of WT;(c) Temperature activity and stability profiles of R252M;(d) pH activity and stability profiles of R252M.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-9561301/v1/8a76e2baea418c87b8196717.png"},{"id":108954782,"identity":"57344148-a97f-4959-a739-ebdfe1be04e6","added_by":"auto","created_at":"2026-05-11 07:59:23","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":37278,"visible":true,"origin":"","legend":"\u003cp\u003eEnzymatic reaction kinetics of WT with R252M\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-9561301/v1/fe7d7aeb2953972bae00c280.png"},{"id":108954678,"identity":"4e2b9fde-76b7-4004-9a78-b1a697015702","added_by":"auto","created_at":"2026-05-11 07:58:56","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":520339,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular docking of wild‑type K3‑β‑gal and R252M mutant with GOS₃.(a) Diagram of K3‑β‑gal docking with GOS₃; (b) Diagram of R252M docking with GOS₃.\u003c/p\u003e","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-9561301/v1/bc3c3cb1751b6e2cd76c4077.png"},{"id":108954769,"identity":"23f4d1dd-c9e5-4054-8e1b-8d24b9d8b77b","added_by":"auto","created_at":"2026-05-11 07:59:12","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":75881,"visible":true,"origin":"","legend":"\u003cp\u003eDynamic analysis of hydrogen bonds.Note: (a) K3-β-gal-GOS₃; (b) R252M-GOS₃.\u003c/p\u003e","description":"","filename":"floatimage11.png","url":"https://assets-eu.researchsquare.com/files/rs-9561301/v1/9166e711f49664bc93be6810.png"},{"id":108954779,"identity":"a1cdc724-ccc6-4b2d-91fd-b12e173a9d8c","added_by":"auto","created_at":"2026-05-11 07:59:22","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":100861,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular dynamics simulation of RMSD.Note: (a) K3-β-gal-GOS₃; (b) R252M-GOS₃.\u003c/p\u003e","description":"","filename":"floatimage12.png","url":"https://assets-eu.researchsquare.com/files/rs-9561301/v1/a6618b045fbbe47b54234345.png"},{"id":108954780,"identity":"c66f9260-2b86-4d2c-a3a7-0bbc3e6915ce","added_by":"auto","created_at":"2026-05-11 07:59:22","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":130619,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular dynamics simulation of RMSF.Note: (a) K3-β-gal-GOS₃; (b) R252M-GOS₃.\u003c/p\u003e","description":"","filename":"floatimage13.png","url":"https://assets-eu.researchsquare.com/files/rs-9561301/v1/bd4f5cd028d67ba621710442.png"},{"id":108954864,"identity":"980f9555-50e5-49cf-b158-7ad374be0fe8","added_by":"auto","created_at":"2026-05-11 08:00:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3380178,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9561301/v1/ce7213ac-ced2-4c3a-97c2-59d261f5955f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Improving high-degree-polymerization GOS synthesis of a marine cold-active β-galactosidase via semi-rational design","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eGalacto-oligosaccharides (GOS) are functional oligosaccharides composed of galactose units linked by β-1,4- or β-1,6-glycosidic bonds. They possess significant prebiotic properties,promoting the growth of bifidobacteria and lactobacilli, thereby improving gut microbiota, and exerting effects such as immune regulation and enhanced calcium absorption (Shipkowski et al. 2006;Weng et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2014\u003c/span\u003e;Marles et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). With the growing market demand for high-function prebiotics, the anti-inflammatory activity of GOS, which is dependent on its degree of polymerization, has garnered considerable attention, particularly highlighting its application value in chronic enteritis and immune-enhancing foods (He et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e;Ord\u0026aacute;s et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).Market data show that the annual production of GOS increased from 14,000 tons in 1995 to 21,000 tons in 2009, and the compound annual growth rate is projected to reach 7.9% from 2021 to 2028, which is closely related to its expanding applications in infant formula, elderly nutritional products, and other fields (Mar\u0026iacute;n-Manzano et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Currently, the industrial production of GOS primarily relies on the transglycosylation reaction catalyzed by β-galactosidases. However, traditional processes face limitations, mainly due to insufficient thermal stability of the enzymes and an imbalance between their transglycosylation and hydrolytic activities, resulting in low GOS yields(Gomes et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e;Higuera-Ciapara et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In contrast, low-temperature β-galactosidases circumvent thermal stability bottlenecks by operating at lower reaction temperatures. They can catalyze reactions efficiently under cold conditions, avoiding protein denaturation and flavor loss in dairy products caused by high temperatures, making them particularly suitable for lactose-free dairy production and cold-chain processes (Wang et al. 2019;Husain et al. 2010).Industry empirical studies have shown that every 10\u0026deg;C reduction in processing temperature can save 8\u0026ndash;12% of thermal management energy consumption. Compared with traditional mesophilic enzyme systems (ΔT\u0026thinsp;=\u0026thinsp;33\u0026deg;C), enzyme preparations adapted to low-temperature processes can theoretically achieve a 15\u0026ndash;20% energy saving (Kaviani et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).Therefore, discovering and developing low-temperature β-galactosidases with high activity and transglycosylation efficiency is crucial for advancing the functional food industry and low-temperature biocatalysis technologies.\u003c/p\u003e \u003cp\u003eDespite their advantage in low-temperature activity, naturally occurring cold-active enzymes often exhibit limited inherent transglycosylation capacity, which struggles to meet the high efficiency and product specificity demands of industrial production. To enhance enzyme catalytic performance, protein engineering has become a key strategy. Among these, semi-rational design, which combines rational structural analysis with experimental screening, has emerged as a mainstream approach for industrial enzyme optimization (Chica et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2005\u003c/span\u003e;Zhou et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This method involves targeting key sites (e.g., substrate-binding pockets or catalytic microenvironments) for limited mutagenesis, significantly reducing library complexity while increasing the probability of positive mutations. For instance, by analyzing enzyme three-dimensional structures (e.g., using AlphaFold2 predictions) and performing molecular docking, key residues influencing substrate binding and catalytic efficiency can be identified. Subsequently, small, focused mutant libraries can be designed and screened for precise enzyme optimization (Reetz et al. 2007;Reetz et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Studies have shown that rational or semi‑rational modification of residues in the active site of β‑galactosidase can effectively improve its transglycosylation efficiency and product specificity. For example, A. Rico‑D\u0026iacute;az et al. (Rico-D\u0026iacute;az et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) performed structural analysis and engineering of β‑galactosidase from Aspergillus niger, successfully increasing the GOS conversion yield from 16% for the wild‑type enzyme to 27%. Liang Li et al. (Li et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) constructed a homology model of BG‑Bgal1‑3 derived from a marine metagenomic library and mutated hydrophobic sites in its active center, ultimately raising the GOS conversion yield from 45.3% to 59.1%. These previous studies provide important methodological references and theoretical foundations for the semi‑rational design approach adopted in this study to optimize the transglycosylation capability of a cold‑active β‑galactosidase.\u003c/p\u003e \u003cp\u003eThis research is based on the laboratory-preserved, low-temperature, high-yield β-galactosidase-producing strain \u003cem\u003eBacillus\u003c/em\u003e sp. K-3, isolated from Bohai Sea deep-sea sediment. Initially, the β-galactosidase gene K3-β-gal from this strain will be cloned and heterologously expressed in \u003cem\u003eE. coli\u003c/em\u003e BL21(DE3). Systematic expression, purification, and enzymatic characterization will be conducted to elucidate its catalytic properties. Building upon this foundation, this study aims to employ a semi-rational design strategy for the molecular engineering of this enzyme to improve its transglycosylation activity. Based on the enzyme's structural model and substrate molecular docking analysis, key amino acid residues affecting catalytic performance will be identified. Site-directed mutagenesis libraries will be constructed to screen for mutants with significantly enhanced transglycosylation capabilities. Finally, through a systematic comparison of the enzymatic properties between the wild-type and the mutants, combined with molecular dynamics simulations, the molecular mechanism by which the mutations affect the catalytic efficiency\u0026mdash;particularly the balance between transglycosylation and hydrolysis\u0026mdash;will be elucidated at the atomic level. This work not only provides an effective protein engineering paradigm for the directed improvement of low-temperature β-galactosidases for industrial applications but also contributes fundamental knowledge to understanding the structure-function relationships within this enzyme family. Ultimately, it lays a theoretical foundation for the development and utilization of this enzyme in the dairy industry, biomedicine, and other fields requiring low-temperature enzymatic applications.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Source of Samples\u003c/h2\u003e \u003cp\u003eThe experimental strain \u003cem\u003eBacillus\u003c/em\u003e sp. K-3 was obtained from the University College of Life Science and Technology (Liaoning Provincial Marine Microbial Engineering Technology Research Center). It was originally isolated from deep-sea mud in the Bohai Sea. The strain is currently preserved at the China Center for Type Culture Collection (CCTCC) in Wuhan, China, with the deposition number M2024513.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Amplification of the β-Galactosidase Gene K3-β-gal\u003c/h2\u003e \u003cp\u003eUsing the genomic DNA of the marine psychrotrophic strain \u003cem\u003eBacillus\u003c/em\u003e sp. K-3 as a template, degenerate primers were designed based on BLAST alignment against homologous sequences of β-galactosidase genes in the NCBI database. The target gene fragment was amplified by PCR, and its size was verified by agarose gel electrophoresis. The purified product was sent to Sangon Biotech Co., Ltd. for sequencing validation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Protein Structure Prediction and Molecular Docking\u003c/h2\u003e \u003cp\u003eThe amino acid sequence of K3-β-gal was subjected to BLAST analysis using the UniProt database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.uniprot.org\u003c/span\u003e\u003cspan address=\"https://www.uniprot.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to retrieve homologous proteins with high similarity and to reference their crystal structures. The three-dimensional structure of K3-β-gal was predicted using the AlphaFold2 online platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://alphafold.ebi.ac.cn/\u003c/span\u003e\u003cspan address=\"https://alphafold.ebi.ac.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and the predicted structure was aligned with homologous proteins to identify the active pocket. The molecular structure file of GOS3 was downloaded from the PubChem database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The receptor protein K3-β-gal was preprocessed using AutoDockTools software for hydrogen addition and charge balancing, and both the receptor and the ligand GOS3 were converted to pdbqt format. Finally, molecular docking was performed using AutoDock Vina 1.1.2 software, and the conformation with the lowest binding free energy was selected for subsequent analysis (Trott et al. 2010).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Screening of Mutation Sites\u003c/h2\u003e \u003cp\u003eBased on the high-confidence K3-β-gal structure predicted by AlphaFold2 and the optimal GOS3 conformation obtained from molecular docking, systematic virtual mutagenesis scanning was performed on amino acid residues within the active pocket (within a 5 \u0026Aring; radius of GOS3) using the CHARMm force field. The mutation free energy change (ΔΔG) for each amino acid substitution was calculated. Potential beneficial mutations with ΔΔG \u0026lt; -0.5 kcal/mol were preliminarily screened (Pancotti et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Subsequently, the initially screened mutants were subjected to re-docking with GOS3 using AutoDock Vina to calculate the binding free energy (ΔGvina), which was comprehensively evaluated together with the mutation energy (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eTrott\u003c/span\u003e et al. 2010). Meanwhile, sequences of high-transglycosylation-activity enzyme families were retrieved from the NCBI database, and multiple sequence alignment was performed using Clustal Omega to exclude highly conserved catalytic functional regions, ensuring that the final selected mutation sites were located in non-conserved regions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Construction and Transformation of Expression Vectors for Wild-Type and Mutants\u003c/h2\u003e \u003cp\u003eBased on the sequencing-validated wild-type K3-β-gal gene sequence and the mutation schemes determined by semi-rational design, full-length synthesis of wild-type and mutant genes was commissioned to Sangon Biotech Co., Ltd. To facilitate subsequent cloning, XbaI and XhoI restriction sites were introduced at both ends of the coding region. The synthesized gene fragments and the pET28a(+) expression vector were double-digested with XbaI and XhoI, verified by agarose gel electrophoresis, and purified. The digested fragments were ligated using T4 DNA ligase to successfully construct the recombinant expression plasmids pET28a-K3-β-gal (WT) and the respective mutants. The ligation products were transformed into \u003cem\u003eE. coli\u003c/em\u003e BL21(DE3) competent cells via heat shock and plated onto LB agar plates containing 50 \u0026micro;g/mL kanamycin, followed by incubation at 37\u0026deg;C for 12\u0026ndash;16 hours. Single colonies were picked and subjected to colony PCR and plasmid double digestion for preliminary identification. Positive clones were further confirmed by Sanger sequencing to verify the correct gene sequence and mutation sites. The resulting recombinant strains were preserved in LB medium containing 50% glycerol at -80\u0026deg;C for future use.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Protein Expression and Purification\u003c/h2\u003e \u003cp\u003eRecombinant plasmids carrying the wild-type or mutant β-galactosidase genes were separately transformed into \u003cem\u003eE. coli\u003c/em\u003e BL21(DE3) competent cells. Positive single colonies were inoculated into LB liquid medium containing 50 \u0026micro;g/mL kanamycin and cultured overnight at 37\u0026deg;C with shaking. The overnight culture was then transferred (1:100) into fresh LB medium (containing 50 \u0026micro;g/mL kanamycin) and grown until OD600 reached 0.6\u0026ndash;0.8. Protein expression was induced by adding isopropyl-β-D-thiogalactopyranoside (IPTG) to a final concentration of 0.2 mM, and the culture was further incubated at 15\u0026deg;C and 100 r/min for 16\u0026ndash;18 h. Cells were harvested by centrifugation, resuspended in binding buffer (20 mM Tris-HCl, pH 8.0), and disrupted by ultrasonication. After centrifugation, the supernatant was collected and mixed with Ni-NTA affinity resin. Unbound proteins were washed away with binding buffer, and the target protein was eluted stepwise with elution buffers (20 mM Tris-HCl, pH 8.0) containing 80 mM and 150 mM imidazole, respectively. The fraction eluted with 150 mM imidazole was collected. The purified enzyme was concentrated and desalted using a 10 kDa cutoff ultrafiltration tube.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Enzyme Activity Assay\u003c/h2\u003e \u003cp\u003eOne unit of enzyme activity was defined as the amount of enzyme required to hydrolyze oNPG to produce 1 \u0026micro;mol of o-nitrophenol (oNP) per minute. The reaction mixture consisted of 50.0 \u0026micro;L of 4 mg/mL oNPG in phosphate buffer (pH 7.0) and 50.0 \u0026micro;L of appropriately diluted enzyme solution (in 0.1 mol/L phosphate buffer, pH 7.0). The mixture was incubated at 15\u0026deg;C for 15 min (or at 37\u0026deg;C for 10 min), and the reaction was terminated by adding 200.0 \u0026micro;L of pre-cooled 0.5 mol/L Na₂CO₃. After thorough mixing, the absorbance at OD\u003csub\u003e420\u003c/sub\u003e was measured. Each sample was tested in triplicate, and a blank control was included (Greenberg et al. 1982).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Evaluation of Transglycosylation Activity and Analysis of Enzymatic Properties of the Wild‑Type and Mutant Enzymes\u003c/h2\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.8.1 Preliminary screening of transglycosylation activity by thin-layer chromatography (TLC)\u003c/h2\u003e \u003cp\u003eUsing lactose as a substrate, reactions were catalyzed by the wild-type and mutant enzymes (R252M, F261W, Y281R, F355K). The reaction mixtures were spotted onto an activated silica gel TLC plate. The plate was developed with a solvent system consisting of isopropanol, n-butanol, acetic acid, and water (3:1:1:1, by volume), air-dried, and visualized using 5% sulfuric acid-ethanol solution. Positive mutants were identified based on the formation of oligosaccharide (DP3, DP4) spots.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e2.8.2 Determination of enzymatic properties\u003c/h2\u003e \u003cp\u003e(1) Optimum temperature and temperature stability: Using oNPG as a substrate, enzyme activity was measured in a pH 7.0 buffer system over a temperature gradient from \u0026minus;\u0026thinsp;20\u0026deg;C to 70\u0026deg;C to determine the optimum reaction temperature. For thermostability assessment, the enzyme solution was pre-incubated at various temperatures for 3 h, and the residual activity was measured at 20\u0026deg;C.\u003c/p\u003e \u003cp\u003e(2) Optimum pH and pH stability: Enzyme activity was measured at 20\u0026deg;C in buffer systems ranging from pH 3.0 to 12.0 (1.0 intervals) to determine the optimum pH. For pH stability assessment, the enzyme solution was pre-treated at different pH values for 3 h, then adjusted to pH 6.0, and the residual activity was measured.\u003c/p\u003e \u003cp\u003e(3) Enzyme kinetics: Under conditions of pH 6.0 and 20\u0026deg;C, initial reaction rates were determined using oNPG as a substrate at concentrations ranging from 0.1 to 5 \u0026micro;mol/mL. Kinetic parameters (K\u003csub\u003em\u003c/sub\u003e, K\u003csub\u003ecat\u003c/sub\u003e, and K\u003csub\u003ecat\u003c/sub\u003e/K\u003csub\u003em\u003c/sub\u003e) were calculated using the Lineweaver-Burk double-reciprocal plot method.\u003c/p\u003e \u003cp\u003e(4) Transglycosylation activity and GOS yield determination: The reaction was carried out with 100 g/L lactose in 20 mM Tris-HCl buffer (pH 6.0) at an enzyme loading of 5 U/g, under 20\u0026deg;C and 120 r/min for 12 h. The reaction mixture was then incubated in boiling water for 20 min to inactivate the enzyme, followed by centrifugation. The supernatant was collected, deproteinized by the Savage method, and filtered through a 0.22 \u0026micro;m membrane. The resulting sugar solution was analyzed by an HPLC system equipped with a refractive index detector (35\u0026deg;C) and a TSKgel Amide-80 column (4.6 mm \u0026times; 25 cm, 5 \u0026micro;m). The mobile phase was acetonitrile-water (60:40, V/V) at a flow rate of 0.6 mL/min. The yields of DP3, DP4, and total GOS were quantified using an external standard method.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.9 Molecular Dynamics Simulation\u003c/h2\u003e \u003cp\u003eBased on the docking results of the wild-type (WT) and the R252M mutant with GOS₃, the complexes with the most favorable conformations were selected for molecular dynamics (MD) simulations. MD simulations were performed using the GROMACS 5.0 software package with the CHARMM36 force field under periodic boundary conditions(Huang et al. 2013). The ligand topology files were generated using the CHARMM general force field (CGenFF)(Vanommeslaeghe et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Ions were added to neutralize the system charge. Energy minimization was carried out using the steepest descent algorithm to eliminate close contacts. Electrostatic and van der Waals interactions were calculated using the particle mesh Ewald (PME) method. The system was first equilibrated in the NVT ensemble for 50,000 steps, followed by a second equilibration in the NPT ensemble for 50,000 steps. Finally, a 100 ns MD simulation was performed at 300 K with a time step of 2.0 fs, and coordinates were saved every picosecond for subsequent analysis (Dolezal et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e;Childers et al. 2018). Based on the simulation trajectories, the root-mean-square deviation (RMSD) of the protein backbone, the root-mean-square fluctuation (RMSF), and the hydrogen bond dynamics of the enzyme-substrate complex were analyzed.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and discussion","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Amplification of β-Galactosidase K3-β-gal\u003c/h2\u003e \u003cp\u003eSpecific primers were designed to amplify the β-galactosidase K3-β-gal coding sequence from the genomic DNA of \u003cem\u003eBacillus\u003c/em\u003e sp. K-3 using PCR. The amplified fragment was double-digested with NdeI and XhoI, and agarose gel electrophoresis revealed a distinct band of approximately 2,000 bp (\u003cb\u003eFigure. 1\u003c/b\u003e), which was consistent with the expected product size. DNA sequencing confirmed that the obtained gene sequence was 2,115 bp in length, matching the theoretical prediction exactly, thereby verifying the successful amplification of the target gene.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Protein Structure Prediction and Molecular Docking\u003c/h2\u003e \u003cp\u003eBLAST analysis identified a resolved structural protein (PDB ID: 5dfa) sharing 72% sequence homology with the target protein. Based on the literature, the catalytic residues of the homologous protein were determined as Glu323 (nucleophile) and Glu159 (acid/base). As shown in \u003cb\u003eFigure. 2a\u003c/b\u003e, the three-dimensional structure of the target protein was predicted using A-fold2, and superposition with 5dfa identified the corresponding catalytic sites as Glu154 and Glu317. Subsequently, GOS3 was docked into the active pocket defined by these residues. As illustrated in \u003cb\u003eFigure. 2b\u003c/b\u003e, hydrogen-bonding interactions were observed between GOS3 and ARG115, Glu154, ARG252, SER156, ASP254, TRP325, and GLU365 of the target protein.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Screening of Mutation Sites\u003c/h2\u003e \u003cp\u003eUsing the amino acid residues defined in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb as the active pocket, the substrate GOS3 was docked into this pocket. The results showed that GOS3 formed hydrogen-bonding interactions with residues ARG115, Glu154, ARG252, SER156, ASP254, TRP325, and GLU365 of the protein. Further analysis of amino acid residues within 5 \u0026Aring; of the active pocket identified 20 key sites, namely: ARG115, HIS116, SER156, GLU154, GLN262, ARG252, ALA253, ASP254, THR255, PHE261, ASP279, TYR281, GLU317, TRP325, PHE355, GLU365, HIS368, SER263, ARG102, and GLY157 (\u003cb\u003eFigure. 3a\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eAll possible single-point mutations were simulated for the above 20 sites, and the change in free energy (ΔΔG) was calculated for each mutation scheme. As a result, 24 stabilizing mutations were identified (Figure. 3a). By further integrating the ΔG\u0026thinsp;\u0026lt;\u0026thinsp;sub\u0026gt;vina\u0026lt;/sub\u0026gt; values for docking of each mutant with GOS3 (\u003cb\u003eFigure. 3b\u003c/b\u003e), candidate mutation schemes including R252M, D279K, Y281R, D279N, D254E, W325Q, F355K, D279I, D279H, and F261W were preliminarily selected.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo evaluate the evolutionary conservation of these sites, multiple sequence alignment was performed using previously reported β-galactosidases with strong transglycosylation activity (\u003cb\u003eFigure. 4\u003c/b\u003e). The results revealed that ASP254, ASP279, and TRP325 were highly conserved; introducing mutations at these sites might significantly affect the biological function of the enzyme, and therefore they were not included in the subsequent mutation design. Based on the above analysis, R252M, F261W, Y281R, and F355K were finally selected as the mutation schemes for further study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Expression and Purification of Wild-Type and Mutant Proteins\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eRecombinant expression strains of the wild-type and mutants (R252M, F261W, Y281R, F355K) were successfully constructed. Following induced expression and purification by Ni-NTA affinity chromatography, SDS-PAGE analysis revealed a distinct protein band at approximately 72 kDa for each protein, which was highly consistent with the expected molecular weight of 78 kDa (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The target proteins from all five strains were successfully purified, providing reliable experimental materials for subsequent enzymatic characterization and transglycosylation activity evaluation.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Screening of Positive Mutants and Comparative Biochemical Characterization of WT and Mutants\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, significant differences were observed in the hydrolytic and transglycosylation activities of different mutants toward lactose and oligosaccharides. In the control group, the spots of sugars remained unchanged, indicating no hydrolysis occurred. The wild-type (WT) enzyme exhibited strong hydrolytic activity, with only weak generation of oligosaccharide spots. In contrast, mutant R252M showed higher transglycosylation activity: upon lactose hydrolysis, it not only produced monosaccharides but also generated more oligosaccharides (e.g., DP3 and DP4), with increased spot intensities, suggesting that this mutant favors transglycosylation over complete hydrolysis. Compared with the WT, the other mutants (F261W, Y281R, F355K) exhibited weaker lactose hydrolysis and produced fewer oligosaccharides, demonstrating no advantage in enhancing transglycosylation activity. Therefore, mutant R252M was selected for subsequent enzymatic characterization and kinetic analysis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eHigh-performance liquid chromatography (HPLC) was used to quantitatively analyze the products of lactose catalysis by the wild-type K3-β-gal and the mutant R252M. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, the total GOS conversion rate of the wild-type enzyme was 13.73%, with DP3 and DP4 conversion rates of 11.10% and 10.58%, respectively. The ratio of DP4 to DP3 conversion was approximately 1:1 (slightly below 1), indicating that the wild-type enzyme had comparable abilities to synthesize tri- and tetrasaccharides. Under the same conditions, the total GOS conversion rate of the R252M mutant increased to 24.89%, with DP3 and DP4 conversion rates of 10.60% and 16.19%, respectively. Compared with the wild-type, the mutant exhibited an 81.29% increase in total GOS conversion. Notably, the DP4/DP3 conversion ratio increased from below 1 for the wild-type to 1.53 for the mutant, suggesting that the mutation significantly enhanced the enzyme's ability to synthesize higher-degree-of-polymerization galacto-oligosaccharides (especially DP4), while the DP3 conversion rate remained largely unchanged. These results indicate that the R252M mutation effectively improves the transglycosylation activity of the enzyme and alters the product distribution, favoring tetrasaccharide synthesis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, the optimal reaction temperature and optimal pH of the mutant R252M were consistent with those of the wild-type (WT) enzyme, being 20\u0026deg;C and pH 6.0, respectively. The WT enzyme retained approximately 80% of its relative activity at 30\u0026deg;C, decreased to below 70% after 40\u0026deg;C, and remained less than 50% above 60\u0026deg;C. After incubation at \u0026minus;\u0026thinsp;20\u0026deg;C to 40\u0026deg;C for 3 h, the WT enzyme maintained about 90% of its activity, while activity rapidly diminished above 55\u0026deg;C (\u0026lt;\u0026thinsp;60%). Regarding pH, the activity of the WT enzyme decreased to about 50% at pH 4.0 and dropped below 20% at pH 12.0. The WT enzyme retained more than 80% of its activity after 3 h of treatment in the pH range of 4.0\u0026ndash;8.0, whereas its stability sharply declined at pH\u0026thinsp;\u0026ge;\u0026thinsp;10.0. The temperature and pH response profiles of R252M were highly consistent with those of the WT, indicating that the mutation did not alter the intrinsic sensitivity of the enzyme to these environmental parameters.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBased on the Lineweaver‑Burk plot analysis in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e and the comparison of enzymatic kinetic parameters in \u003cb\u003eTable\u0026nbsp;1\u003c/b\u003e, the kinetic parameters of β‑galactosidase K3‑β‑gal (WT) were as follows: K\u003csub\u003em\u003c/sub\u003e = 1.789 mM, K\u003csub\u003ecat\u003c/sub\u003e = 17.093 min⁻\u0026sup1;, and K\u003csub\u003ecat\u003c/sub\u003e/K\u003csub\u003em\u003c/sub\u003e = 9.554 mM⁻\u0026sup1;\u0026middot;min⁻\u0026sup1;. In contrast, the R252M mutant exhibited a K\u003csub\u003em\u003c/sub\u003e of 2.361 mM, K\u003csub\u003ecat\u003c/sub\u003e of 12.65 min⁻\u0026sup1;, and K\u003csub\u003ecat\u003c/sub\u003e/K\u003csub\u003em\u003c/sub\u003e of 5.358 mM⁻\u0026sup1;\u0026middot;min⁻\u0026sup1;. Both K\u003csub\u003ecat\u003c/sub\u003e and K\u003csub\u003ecat\u003c/sub\u003e/K\u003csub\u003em\u003c/sub\u003e decreased, indicating that the mutation reduced the enzyme's affinity for the substrate oNPG, weakened its catalytic efficiency (decreased K\u003csub\u003ecat\u003c/sub\u003e, slower hydrolysis rate), and lowered the overall hydrolytic activity toward oNPG (approximately 44% decrease in K\u003csub\u003ecat\u003c/sub\u003e/K\u003csub\u003em\u003c/sub\u003e). It is speculated that the R252M mutation alters the active site conformation, potentially disrupting the hydrogen bond network or adjusting the charge distribution, thereby impairing the binding stability with oNPG and reducing substrate conversion efficiency. These results suggest that the mutation may limit certain aspects of enzyme function through a combination of local active site destabilization and global conformational dynamics, providing important experimental insights for understanding mutation‑function relationships and for directed enzyme engineering.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;1 Comparison of enzymatic kinetics parameters between K3-β-gal and R252M\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Molecular Dynamics Simulation\u003c/h2\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e3.6.1 Simulation of the binding modes of WT and R252M mutant with GOS₃\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of enzyme\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eK\u003csub\u003em\u003c/sub\u003e(mM)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eK\u003csub\u003ecat\u003c/sub\u003e (min\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eK\u003csub\u003ecat\u003c/sub\u003e/K\u003csub\u003em\u003c/sub\u003e(min\u003csup\u003e-1\u003c/sup\u003e\u0026middot;mM\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.554\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR252M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.358\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e, comparison of the binding modes of the wild‑type (WT) enzyme and the R252M mutant with GOS₃ revealed that the WT enzyme relies on key residues including SER156, ARG115, ARG252, ASP254, GLU154, GLU365, and TRP325 to form a tight network through hydrogen bonds and weak interactions, thereby stabilizing the substrate and maintaining the function of the β‑galactosidase active site to sustain the transglycosylation reaction. In contrast, in the R252M mutant, ARG252 and SER156 are replaced by GLN262 and SER263, and additionally ASP279 and HIS368 are introduced to participate in binding, leading to remodeling of the active site architecture. The mutant forms a new hydrogen bond between HIS368 and ASP279, which enhances the accessibility of the active site while preserving the stability of the core region (e.g., GLU154). This not only does not disrupt substrate binding but may also improve substrate binding flexibility through optimized charge distribution and spatial accommodation, facilitating the entry of higher‑degree‑of‑polymerization oligosaccharides into the active center (Noriega et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These observations suggest that the catalytic adaptability and capacity for transglycosylation to produce long‑chain galacto‑oligosaccharides of the mutant may be superior to those of the WT enzyme.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section3\"\u003e \u003ch2\u003e3.6.2 Hydrogen bond dynamics analysis of WT and R252M mutant with GOS₃\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e, hydrogen bond dynamics analysis of the wild-type (WT) and R252M mutant enzymes with GOS₃ revealed significant differences in both the number and stability of hydrogen bonds. The number of hydrogen bonds in the WT enzyme fluctuated considerably over different simulation periods. Overall, the hydrogen bond count was relatively low and exhibited breakage or reduction at various time points. In the early stage of the simulation (0\u0026ndash;20,000 ps), the WT enzyme formed strong hydrogen bonds with GOS₃ (6\u0026ndash;8 bonds). During the middle stage (20,000\u0026ndash;60,000 ps), the hydrogen bond number stabilized at 4\u0026ndash;6, but showed clear instability in the mid-to-late period. In the late stage (60,000\u0026ndash;100,000 ps), the hydrogen bond count decreased significantly, even approaching zero, indicating weakening of the enzyme-substrate interaction, possibly due to substrate dissociation or enzyme conformational changes.\u003c/p\u003e \u003cp\u003eIn contrast, the R252M mutant enzyme exhibited much higher stability in hydrogen bond number throughout the simulation. In the early stage (0\u0026ndash;20,000 ps), similar to the WT enzyme, the hydrogen bond count was high with small fluctuations, indicating more consistent enzyme-substrate interactions. During the middle stage (20,000\u0026ndash;60,000 ps), the hydrogen bond number remained stable at 4\u0026ndash;6 with relatively uniform fluctuations. In the late stage (60,000\u0026ndash;100,000 ps), although the hydrogen bond count decreased, it remained at a higher level than that of the WT enzyme, suggesting that the R252M mutant binds the substrate more stably.\u003c/p\u003e \u003cp\u003eThe stability of hydrogen bonds directly affects the transglycosylation activity of the enzyme. The reduction in hydrogen bonds during the middle stage and the significant bond breakage and substrate dissociation in the late stage of the WT enzyme led to weaker binding stability with GOS₃. This unstable binding caused frequent detachment or repositioning of the substrate at the active site, shortening the effective binding time and thereby reducing transglycosylation efficiency. In contrast, the relatively stable hydrogen bonds of the R252M mutant, particularly in the late stage, enabled more effective maintenance of the enzyme-substrate complex stability, thereby enhancing transglycosylation efficiency. Therefore, the R252M mutation may promote stronger enzyme-substrate binding by improving hydrogen bond stability, thus increasing transglycosylation capacity (Huyghues-Despointes et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e3.6.3 RMSD analysis of WT and R252M mutant with GOS₃\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e, the RMSD analysis of WT‑GOS₃ revealed that the RMSD value gradually increased from 0.1 nm to nearly 0.25 nm over the simulation period of 0 to 100 ns, reaching a relatively high fluctuation range after 80 ns. This indicates that the WT protein became increasingly unstable during the molecular dynamics simulation, potentially leading to structural changes in the substrate binding site, which is unfavorable for the binding and transfer of long‑chain oligosaccharides and consequently reduces the transglycosylation efficiency. In contrast, the RMSD analysis of R252M‑GOS₃ showed that the RMSD value remained within a low range of 0.1 nm to 0.2 nm throughout the 100 ns simulation, with overall small fluctuations. The consistently lower RMSD value of the R252M mutant during the entire simulation suggests that the mutant protein structure is more stable, and the mutation enhanced the overall rigidity and stability of the protein. Higher structural stability may provide a more favorable environment, leading to a more stable substrate binding site and thereby enhancing transglycosylation efficiency. The RMSD fluctuation of a protein reflects the flexibility of its overall structure (da Fonseca et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Appropriate flexibility is crucial for enzyme function: an overly rigid structure may restrict substrate access to the active site, whereas an overly loose structure may lead to unstable substrate binding. Compared with the linear increase in RMSD of WT, the RMSD of R252M changed more smoothly, indicating that the mutant maintained moderate flexibility and balance throughout the simulation, which is conducive to substrate binding and reaction progression.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e \u003ch2\u003e3.6.4 RMSF analysis of WT and R252M mutant with GOS₃\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e, the analysis of the binding dynamics of the wild-type (WT) and R252M mutant with GOS₃ based on RMSF revealed the following. The RMSF profile of the WT enzyme exhibited significant fluctuation peaks near the active site and in the mid-to-late regions, which may lead to unstable substrate binding and limit transglycosylation efficiency. In contrast, the overall RMSF fluctuations of the R252M mutant were reduced. Lower RMSF fluctuations indicate that the corresponding regions are more rigid and stable. Moreover, the decrease in RMSF values of residues near the active site suggests that the active site structure becomes more stable after mutation. This rigidification not only consolidates the GOS₃ binding site but also provides more precise spatial positioning for the transfer of long-chain galacto-oligosaccharide groups, thereby optimizing the catalytic microenvironment by reducing unproductive conformational fluctuations and further enhancing transglycosylation efficiency.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eIn this study, mutant R252M completely retained the favorable temperature and pH adaptability of the wild-type enzyme (optimal temperature 20\u0026deg;C, optimal pH 6.0, and good stability in the ranges of \u0026minus;\u0026thinsp;20\u0026deg;C to 40\u0026deg;C and pH 4.0\u0026ndash;8.0), while its transglycosylation activity was significantly enhanced: the total GOS conversion yield increased from 13.73% (WT) to 24.89% (a 81.29% increase), and the synthesis of high-degree-of-polymerization product DP4 was particularly prominent, with the DP4/DP3 ratio rising from 0.95 to 1.53. Notably, kinetic analysis using oNPG as substrate showed that the Kcat/Km of R252M decreased by approximately 44% (from 9.554 to 5.358 min⁻\u0026sup1;\u0026middot;mM⁻\u0026sup1;) compared with WT, indicating that the mutation also attenuated the hydrolytic activity of the enzyme. This opposite trend of \u0026ldquo;decreased hydrolysis but increased transglycosylation\u0026rdquo; suggests that the R252M mutation may redirect the catalytic equilibrium from the hydrolysis pathway toward the transglycosylation pathway by reshaping the active site conformation. Molecular dynamics simulations further revealed the structural basis: the mutant replaced ARG252 with MET and introduced new residues ASP279 and HIS368, which remodeled the hydrogen bond network in the active pocket, resulting in substantially higher stability of the enzyme\u0026ndash;substrate complex hydrogen bonds than that of WT; meanwhile, the overall RMSD value decreased and the RMSF fluctuation around the active site was reduced, indicating enhanced protein rigidity and diminished catalytic microenvironment perturbation. These mechanisms jointly optimized substrate binding and glycosyl transfer efficiency, providing a molecular explanation for the efficient synthesis of high-DP galacto-oligosaccharides by R252M under low-temperature conditions. Given the prominent prebiotic value of high-DP GOS in anti-inflammation, immune regulation, and gut health, this mutant holds promise as a novel enzyme preparation for functional food and pharmaceutical applications. Future work may further increase transglycosylation yield and product specificity through combinatorial mutagenesis (e.g., the R252M/Y281R double mutant) or iterative saturation mutagenesis; determination of the three-dimensional structure of the mutant by cryo-EM or X-ray crystallography will elucidate the precise relationship between conformational changes and catalytic preference switching. Moreover, validation of its low-temperature process adaptability in real dairy matrices and the development of immobilized or whole-cell catalytic systems will promote the industrial translation of this enzyme.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eConflict of interest\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eL.P. drafted the main manuscript text; L.P., Y.Z., and Z.W. jointly designed the experimental protocols; C.F., Q.Y., J.W., and F.F. performed the experiments; all authors reviewed and revised the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis work was supported by the Youth Science Fund Project of the National Natural Science Foundation of China (Grant No. 31500039), the Dalian Youth Science and Technology Star Project (Grant No. 2017RQ155), and the Natural Science Foundation of Liaoning Province (Grant No. 20180550728).\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eNo new datasets were generated or analyzed during this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eShipkowski S, Brenchley JE (2006) Bioinformatic, genetic, and biochemical evidence that some glycoside hydrolase family 42 beta-galactosidases are arabinogalactan type I oligomer hydrolases[J]. Appl Environ Microbiol 72(12):7730\u0026ndash;7738. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/AEM.01306-06\u003c/span\u003e\u003cspan address=\"10.1128/AEM.01306-06\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeng W, Tang L, Wang B, Chen J, Su W, Osako K, Tanaka M (2014) Antioxidant properties of fractions isolated from blue shark (Prionace glauca) skin gelatin hydrolysates[J]. J Funct Foods 11:342\u0026ndash;351. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jff.2014.10.021\u003c/span\u003e\u003cspan address=\"10.1016/j.jff.2014.10.021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarles RJ, Roe AL, Oketch-Rabah HA (2017) US Pharmacopeial Convention safety evaluation of menaquinone-7, a form of vitamin K[J]. Nutr Rev 75(7):553\u0026ndash;578. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/nutrit/nux022\u003c/span\u003e\u003cspan address=\"10.1093/nutrit/nux022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHe N, Chen H, Zhou Z et al (2021) Enzymatically synthesized α-galactooligosaccharides attenuate metabolic syndrome in high-fat diet induced mice in association with the modulation of gut microbiota[J]. Food Funct 12(11):4960\u0026ndash;4971. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1039/d0fo03113e\u003c/span\u003e\u003cspan address=\"10.1039/d0fo03113e\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOrd\u0026aacute;s I, Eckmann L, Talamini M, Baumgart DC, Sandborn WJ (2012) Ulcerative colitis[J]. Lancet 380(9853):1606\u0026ndash;1619. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0140-6736(12)60150-0\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(12)60150-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMar\u0026iacute;n-Manzano MD, Abecia L, Hern\u0026aacute;ndez-Hern\u0026aacute;ndez O, Sanz ML, Montilla A, Olano A, Rubio LA, Moreno FJ, Clemente A (2013) Galacto-oligosaccharides derived from lactulose exert a selective stimulation on the growth of Bifidobacterium animalis in the large intestine of growing rats[J]. J Agric Food Chem 61(31):7560\u0026ndash;7567. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/jf402218z\u003c/span\u003e\u003cspan address=\"10.1021/jf402218z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGomes HO, Cardoso RS, da Costa JGM, Andrade da Silva VP, Nobre CA, Pereira Teixeira RN, do Nascimento RF (2021) Statistical evaluation of analytical curves for quantification of pesticides in bananas[J]. Food Chem 345:128768. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.foodchem.2020.128768\u003c/span\u003e\u003cspan address=\"10.1016/j.foodchem.2020.128768\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHiguera-Ciapara I, Viru\u0026eacute;s C, Jim\u0026eacute;nez-Ch\u0026aacute;vez M et al (2017) 1H NMR studies of molecular interaction of D-glucosamine and N-acetyl-D-glucosamine with capsaicin in aqueous and non-aqueous media[J]. Carbohydr Res 452:6\u0026ndash;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.carres.2017.09.014\u003c/span\u003e\u003cspan address=\"10.1016/j.carres.2017.09.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang X (2019) Strategy for improving L-isoleucine production efficiency in Corynebacterium glutamicum[J]. Appl Microbiol Biotechnol 103(5):2101\u0026ndash;2111. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00253-019-09632-2\u003c/span\u003e\u003cspan address=\"10.1007/s00253-019-09632-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHusain Q (2010) Beta galactosidases and their potential applications: a review[J]. Crit Rev Biotechnol 30(1):41\u0026ndash;62. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3109/07388550903330497\u003c/span\u003e\u003cspan address=\"10.3109/07388550903330497\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaviani A, Aslani A, Zahedi R, Ahmadi H, Malekli MR (2022) A new approach for energy optimization in dairy industry[J]. Clean Eng Technol 8:100498. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.clet.2022.100498\u003c/span\u003e\u003cspan address=\"10.1016/j.clet.2022.100498\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChica RA, Doucet N, Pelletier JN (2005) Semi-rational approaches to engineering enzyme activity: combining the benefits of directed evolution and rational design[J]. Curr Opin Biotechnol 16(4):378\u0026ndash;384. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.copbio.2005.06.004\u003c/span\u003e\u003cspan address=\"10.1016/j.copbio.2005.06.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou L, Tao C, Shen X, Sun X, Wang J, Yuan Q (2024) Unlocking the potential of enzyme engineering via rational computational design strategies[J]. Biotechnol Adv 73:108376. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.biotechadv.2024.108376\u003c/span\u003e\u003cspan address=\"10.1016/j.biotechadv.2024.108376\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReetz MT, Carballeira JD (2007) Iterative saturation mutagenesis (ISM) for rapid directed evolution of functional enzymes[J]. Nat Protoc 2(4):891\u0026ndash;903. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nprot.2007.72\u003c/span\u003e\u003cspan address=\"10.1038/nprot.2007.72\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReetz MT, Carballeira JD, Vogel A (2006) Iterative saturation mutagenesis on the basis of B factors as a strategy for increasing protein thermostability[J]. Angew Chem Int Ed 45(45):7745\u0026ndash;7751. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/anie.200602795\u003c/span\u003e\u003cspan address=\"10.1002/anie.200602795\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRico-D\u0026iacute;az A, Ram\u0026iacute;rez-Escudero M, Vizoso-V\u0026aacute;zquez \u0026Aacute;, Cerd\u0026aacute;n ME, Becerra M, Sanz-Aparicio J (2017) Structural features of Aspergillus niger β-galactosidase define its activity against glycoside linkages[J]. FEBS J 284(12):1815\u0026ndash;1829. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/febs.14083\u003c/span\u003e\u003cspan address=\"10.1111/febs.14083\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi L, Li G, Cao LC et al (2015) Characterization of the cross-linked enzyme aggregates of a novel β-galactosidase, a potential catalyst for the synthesis of galacto-oligosaccharides[J]. J Agric Food Chem 63(3):894\u0026ndash;901. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/jf504473k\u003c/span\u003e\u003cspan address=\"10.1021/jf504473k\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrott O, Olson AJ (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading[J]. J Comput Chem 31(2):455\u0026ndash;461. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/jcc.21334\u003c/span\u003e\u003cspan address=\"10.1002/jcc.21334\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePancotti C, Benevenuta S, Birolo G et al (2022) Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset[J]. Brief Bioinform 23(1):bbab555. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bib/bbab555\u003c/span\u003e\u003cspan address=\"10.1093/bib/bbab555\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrott O, Olson AJ (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading[J]. J Comput Chem 31(2):455\u0026ndash;461. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/jcc.21334\u003c/span\u003e\u003cspan address=\"10.1002/jcc.21334\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreenberg NA, Mahoney RR (1982) Production and characterization of β-galactosidase from Streptococcus thermophilus[J]. J Food Sci 47(6):1824\u0026ndash;1835. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1365-2621.1982.tb12891.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-2621.1982.tb12891.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang J, MacKerell AD Jr (2013) CHARMM36 all-atom additive protein force field: validation based on comparison to NMR data[J]. J Comput Chem 34(25):2135\u0026ndash;2145. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/jcc.23354\u003c/span\u003e\u003cspan address=\"10.1002/jcc.23354\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVanommeslaeghe K, Hatcher E, Acharya C et al (2010) CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields[J]. J Comput Chem 31(4):671\u0026ndash;690. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/jcc.21367\u003c/span\u003e\u003cspan address=\"10.1002/jcc.21367\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDolezal R, Soukup O, Malinak D et al (2016) Towards understanding the mechanism of action of antibacterial N-alkyl-3-hydroxypyridinium salts: Biological activities, molecular modeling and QSAR studies[J]. Eur J Med Chem 121:699\u0026ndash;711. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ejmech.2016.05.058\u003c/span\u003e\u003cspan address=\"10.1016/j.ejmech.2016.05.058\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChilders MC, Daggett V (2018) Validating Molecular Dynamics Simulations against Experimental Observables in Light of Underlying Conformational Ensembles[J]. J Phys Chem B 122(26):6673\u0026ndash;6689. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/acs.jpcb.8b02144\u003c/span\u003e\u003cspan address=\"10.1021/acs.jpcb.8b02144\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNoriega MA, Rico-Rodr\u0026iacute;guez F, Rosales JD, Serrato-Berm\u0026uacute;dez JC (2024) Kinetics of galactooligosaccharides (GOS) production with two β-galactosidases: Metallic ion effect and mathematical model[J]. Chem Eng Res Des 212:341\u0026ndash;348. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.cherd.2024.11.001\u003c/span\u003e\u003cspan address=\"10.1016/j.cherd.2024.11.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuyghues-Despointes A, Pace CN, Englander SW, Scholtz JM (2001) Measuring the conformational stability of a protein by hydrogen exchange[M]. In: Murphy KP (ed) Protein Structure, Stability, and Folding, Methods in Molecular Biology, vol 168. Humana, Totowa, NJ, pp 69\u0026ndash;94. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1385/1-59259-193-0:069\u003c/span\u003e\u003cspan address=\"10.1385/1-59259-193-0:069\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eda Fonseca AM, Caluaco BJ, Madureira JMC et al (2024) Screening of potential inhibitors targeting the main protease structure of SARS-CoV-2 via molecular docking, and approach with molecular dynamics, RMSD, RMSF, H-bond, SASA and MMGBSA[J]. Mol Biotechnol 66(8):1919\u0026ndash;1933. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12033-023-00831-x\u003c/span\u003e\u003cspan address=\"10.1007/s12033-023-00831-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"archives-of-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aomi","sideBox":"Learn more about [Archives of Microbiology](https://www.springer.com/journal/203)","snPcode":"203","submissionUrl":"https://submission.nature.com/new-submission/203/3","title":"Archives of Microbiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Cold-active β-galactosidase, Semi-rational design, High-DP galacto-oligosaccharides, Transglycosylation efficiency","lastPublishedDoi":"10.21203/rs.3.rs-9561301/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9561301/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCold-active β-galactosidase has significant application value in the enzymatic synthesis of galacto-oligosaccharides (GOS), but its industrial application is limited by low transglycosylation efficiency and poor selectivity for high-degree-polymerization products. In this study, the cold-active β-galactosidase K3-β-gal was cloned and expressed from marine \u003cem\u003eBacillus\u003c/em\u003e sp. K-3. Four mutants (R252M, F261W, Y281R, F355K) were constructed via semi-rational design, among which mutant R252M showed substantially enhanced transglycosylation activity. This mutant fully retained the favorable temperature and pH adaptability of the wild-type enzyme (optimal temperature 20\u0026deg;C, optimal pH 6.0, and good stability under low-temperature and weakly acidic conditions). The total GOS conversion yield increased from 13.73% to 24.89% (an 81.29% increase), and the DP4/DP3 ratio rose from 0.95 to 1.53. Kinetic analysis revealed that the hydrolytic activity of R252M decreased by approximately 44%, suggesting that the catalytic equilibrium shifted from hydrolysis toward transglycosylation. Molecular dynamics simulations demonstrated that R252M remodeled the hydrogen bond network in the active pocket, enhanced overall protein rigidity, and reduced dynamic perturbations around the active site, thereby optimizing substrate binding and glycosyl transfer efficiency. This study provides a novel strategy for the efficient molecular engineering of cold-active β-galactosidases, and mutant R252M holds good promise for the green synthesis of high-DP GOS.\u003c/p\u003e","manuscriptTitle":"Improving high-degree-polymerization GOS synthesis of a marine cold-active β-galactosidase via semi-rational design","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-11 07:55:58","doi":"10.21203/rs.3.rs-9561301/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision 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