Recombinant Mouse Neutral alpha-glucosidase C (Ganc), partial, refers to a genetically engineered version of the enzyme neutral alpha-glucosidase C, derived from mice. This enzyme is part of the glycoside hydrolase family 31, which plays a crucial role in carbohydrate metabolism by hydrolyzing glycosidic bonds. The "partial" designation indicates that the recombinant form might not include the full-length protein or might be a fragment of the enzyme.
Neutral alpha-glucosidase C (GANC) is known to hydrolyze terminal, non-reducing alpha-D-glucose residues from substrates like maltotriose and glycogen at neutral pH . This enzyme is involved in glycogen metabolism, which is essential for energy storage and release in cells. The human version of GANC is encoded by the GANC gene located on chromosome 15q15, a region associated with diabetes susceptibility .
Research on GANC is limited compared to other glucosidases, but it has been studied using in silico methods to understand its evolution and substrate specificity. GANC evolved from the alpha-subunit of glucosidase II (GANAB) in early vertebrates . The enzyme is expressed in the nucleoplasm and cytoplasm, where it colocalizes with actin filaments, suggesting a role beyond traditional carbohydrate metabolism .
While specific data on recombinant mouse GANC is scarce, recombinant enzymes are typically produced to study their function, structure, and potential therapeutic applications. Recombinant mouse lysosomal alpha-glucosidase (GAA), another glucosidase, has been extensively studied for its role in treating Pompe disease, a disorder caused by GAA deficiency . The techniques used to produce and analyze recombinant GAA could potentially be applied to GANC.
Neutral alpha-glucosidase C (Ganc) is a member of the glycosyl hydrolase gene family 31, which has activity at neutral pH, distinguishing it from acid alpha-glucosidases that function optimally at acidic pH. Ganc is involved in glycogen metabolism and has the ability to degrade glycogen. It differs from other alpha-glucosidases like lysosomal acid alpha-glucosidase (GAA) primarily in its pH optimum and subcellular localization. While GAA functions within lysosomes at acidic pH, Ganc operates at neutral pH in different cellular compartments. Ganc shows highest homology to the catalytic unit of glucosidase II among the alpha-glucosidase family members . The enzyme exhibits characteristic electrophoretic mobility relative to the lysosomal enzyme acid alpha-glucosidase and to glucosidase II, which can be used for identification purposes in experimental settings .
Mouse Ganc, similar to human GANC, has a molecular mass of approximately 104 kDa, consistent with a protein of around 914 amino acids . The enzyme contains the highly conserved catalytic site with the WXDMNE motif that is characteristic of family 31 glycosyl hydrolases . This catalytic site is critical for the hydrolysis of glycosidic bonds. Structurally, Ganc likely contains domains similar to other family 31 glycosyl hydrolases, which typically include an N-terminal trefoil-P domain, a beta-sheet domain, a catalytic barrel, and C-terminal beta-sheet domains, as observed in the related enzyme GAA . The hydrolysis mechanism involves cleavage of both alpha-1,4- and alpha-1,6-glucosidic linkages, allowing the enzyme to process complex glycogen structures.
For assessing Ganc enzymatic activity, researchers should adapt protocols similar to those used for other alpha-glucosidases, with particular attention to maintaining neutral pH conditions. A recommended approach is to use starch as a substrate, with the following protocol adapted from GAA assay methods :
Prepare assay buffer at neutral pH (approximately pH 7.0-7.4)
Dilute purified recombinant Ganc to 30-35 μg/mL in assay buffer
Prepare substrate by diluting 2% starch to 1.5% in assay buffer
Combine 20 μL of diluted Ganc with 380 μL of 1.5% starch
Include appropriate controls (buffer only with substrate)
Incubate reactions at 37°C for 60 minutes
Add 400 μL of stop solution (such as dinitrosalicylic acid-based reagent)
Heat at 95-100°C for 6 minutes, then cool on ice
Measure released glucose using colorimetric detection at approximately 540-550 nm
Calculate specific activity using the formula:
Specific Activity (pmol/min/μg) = | Adjusted glucose produced (nmol) × (1000 pmol/nmol) |
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Incubation time (min) × amount of enzyme (μg) |
This method allows quantitative assessment of Ganc activity while accounting for background activity and ensuring specificity .
Based on successful expression systems for related glycosidases, mammalian expression systems are most suitable for producing enzymatically active recombinant mouse Ganc. For optimal expression:
Utilize expression vectors such as pCDNA3 with a strong promoter (CMV) for mammalian cell expression
Consider expressing in multiple cell lines for comparison:
Mouse 3T3 cells for homologous expression
COS cells for high protein yield
Human cell lines lacking endogenous Ganc activity for functional studies
Successful expression was demonstrated for human GANC using CaPO₄-based transfection methods in multiple cell lines, including murine 3T3 cells and monkey kidney COS cells . For purification, include an affinity tag (such as 6-His) at the N-terminus of the construct, which allows for efficient purification while maintaining enzymatic activity . Complete sequencing of the expression construct is essential to confirm absence of cloning artifacts that could affect activity .
Differentiating between Ganc and other glucosidases in experimental samples requires a multi-parameter approach:
Electrophoretic mobility analysis: Starch gel electrophoresis at 4°C can separate Ganc from other glucosidases based on charge differences, which is particularly useful for distinguishing between allozymes .
pH optima profiling: Conduct activity assays across a pH range from 3.5 to 8.0. Ganc will show maximal activity at neutral pH (around 7.0), while lysosomal acid alpha-glucosidase exhibits peak activity at pH 4.0-4.5 .
Substrate specificity testing: Compare hydrolysis rates of different substrates:
4-methylumbelliferyl-α-D-glucoside for visualization of activity
Natural substrates like glycogen and starch
Specific oligosaccharides that may be preferentially cleaved by Ganc
Inhibitor sensitivity analysis: Test differential sensitivity to inhibitors:
Acarbose (α-glucosidase inhibitor)
Specific antibodies against Ganc
Molecular weight verification: Use Western blotting with specific antibodies to confirm the expected molecular weight of approximately 104 kDa for Ganc, compared to other glucosidases .
This comprehensive approach ensures reliable differentiation between Ganc and other related enzymes in complex biological samples.
Analyzing genetic variations in mouse Ganc and assessing their functional impact requires a systematic approach combining molecular genetics and enzymatic characterization:
Identification of genetic variants:
PCR amplification and sequencing of Ganc cDNA from different mouse strains
Analysis of genomic databases for known polymorphisms
RT-PCR from tissues of interest to identify potential splice variants
Functional characterization of variants:
Biochemical characterization of variant enzymes:
Determine pH optima profiles
Assess substrate preferences
Measure kinetic parameters (Km, Vmax)
Evaluate thermal stability and storage properties
Structural analysis:
Human GANC exhibits a biochemical genetic polymorphism with four alleles, including a null allele . Mouse Ganc likely shows similar diversity, making it an excellent model for studying enzyme polymorphisms and their physiological implications.
Maintaining recombinant mouse Ganc activity during storage requires careful attention to buffer conditions and handling procedures:
Short-term storage (1-2 weeks):
Store as filtered solution in Tris buffer with NaCl at 2-8°C
Include stabilizing agents such as glycerol (10-20%)
Consider adding protease inhibitors to prevent degradation
Long-term storage:
Buffer composition optimization:
For maximum stability, consider buffer systems containing:
20-50 mM Tris-HCl, pH 7.2-7.5
100-150 mM NaCl
Optional: 1-5 mM DTT to maintain reduced state of cysteines
Optional: 10% glycerol as cryoprotectant
Activity preservation during experiments:
These guidelines are adapted from established protocols for related enzymes and should maintain maximal activity of recombinant mouse Ganc during experimental timeframes .
Mouse Ganc functions within a complex network of glycogen metabolism enzymes, and understanding these interactions is crucial for comprehensive research:
Integration with glycogen synthesis and degradation pathways:
Ganc likely complements the action of other glycogen-degrading enzymes like phosphorylases
May interact with glycogen branching enzymes to modify glycogen structure
Could participate in specialized degradation pathways distinct from lysosomal degradation
Regulation within metabolic networks:
Potential coordination with glucose transporters for efficient substrate utilization
Possible co-regulation with glycogen synthase for balanced metabolism
May respond to cellular energy status signals
Protein-protein interactions:
Pathophysiological significance:
May have complementary functions to acid alpha-glucosidase (GAA) in different cellular compartments
Could provide alternative glycogen degradation pathways when other systems are compromised
Potentially involved in specialized aspects of glucose homeostasis
Although direct experimental evidence for these interactions is limited in the provided search results, the conservation of functional domains and the role of Ganc in glycogen metabolism suggest these interactions are likely significant and worthy of investigation in research settings.
When working with recombinant mouse Ganc, researchers may encounter several challenges that can be addressed with specific strategies:
Low expression levels:
Optimize codon usage for the host expression system
Test different promoters (CMV, EF1α, CAG) for higher expression
Use expression vectors with enhancer elements
Consider stable cell line development for consistent expression
Optimize transfection conditions (reagent:DNA ratio, cell density, incubation time)
Protein misfolding and inactivity:
Express at lower temperatures (30-34°C instead of 37°C) to slow folding
Include molecular chaperones as co-expression partners
Use mammalian expression systems rather than bacterial systems to ensure proper glycosylation
Validate construct sequence for accurate translation, especially at the catalytic site (WXDMNE motif)
Proteolytic degradation:
Add protease inhibitors during extraction and purification
Reduce extraction time and maintain cold temperatures
Avoid harsh elution conditions during purification
Consider adding stabilizing agents like glycerol or specific sugars
Inconsistent activity measurements:
Distinguishing from endogenous glucosidases:
These strategies address common challenges in recombinant enzyme work and should improve success rates in Ganc studies.
Designing experiments to investigate the physiological role of mouse Ganc requires a multi-faceted approach:
Expression pattern analysis:
Quantify Ganc mRNA and protein levels across mouse tissues
Compare expression patterns with other glycosidases
Analyze expression changes during development and under different physiological conditions
Use immunohistochemistry to determine cellular and subcellular localization
Loss-of-function studies:
Generate Ganc knockout or knockdown models
Use CRISPR-Cas9 for precise genome editing
Apply siRNA for transient knockdown in cell models
Analyze resulting changes in:
Glycogen metabolism and structure
Cellular response to metabolic stress
Gene expression profiles
Gain-of-function studies:
Overexpress wild-type and mutant Ganc in appropriate cell models
Compare with cells expressing related enzymes like acid alpha-glucosidase
Assess impact on glycogen content and metabolism
Evaluate cellular adaptation to altered Ganc levels
Substrate specificity and metabolic impact:
Analyze glycogen structure in Ganc-deficient and Ganc-overexpressing models
Trace labeled substrates to determine Ganc's contribution to glucose production
Investigate changes in downstream metabolic pathways
Disease model relevance:
Examine Ganc expression and activity in models of glycogen storage disorders
Investigate compensatory changes in Ganc in acid alpha-glucosidase deficiency (Pompe disease model)
Explore Ganc's role in metabolic disorders like diabetes, given its chromosomal location in a diabetes susceptibility region (human 15q15)
These experimental approaches would provide comprehensive insights into the physiological significance of Ganc in glycogen metabolism and potentially uncover novel therapeutic targets.
Understanding the similarities and differences between mouse Ganc and human GANC is essential for translational research:
Sequence homology and structural comparison:
Mouse and human GANC share significant sequence homology, with approximately 80-85% similarity at the amino acid level (comparable to the 80% homology between mouse and human GAA)
The catalytic WXDMNE motif is highly conserved between species
Both proteins have similar molecular weights: approximately 104 kDa for human GANC (914 amino acids)
Conservation is typically highest in functional domains and the catalytic core
Enzymatic properties:
Both enzymes function at neutral pH
Substrate specificity profiles are largely conserved, but mouse Ganc may show subtle differences in oligosaccharide preferences
Kinetic parameters (Km, Vmax) likely show species-specific variations
Inhibitor sensitivity profiles may differ slightly
Genetic variation:
Physiological context:
Tissue distribution patterns may differ between species
Regulatory mechanisms and expression patterns can show species-specific adaptations
Functional redundancy with other glucosidases may vary between mouse and human
Experimental considerations:
Mouse models may not perfectly recapitulate human GANC-related phenotypes
Species-specific antibodies may be required for accurate detection
Expression systems might need optimization when switching between species orthologs
These differences highlight the importance of species-specific validation when extrapolating findings between mouse models and human applications in Ganc research.
Evolutionary analysis of Ganc provides valuable insights into its functional significance:
Phylogenetic relationships:
Ganc belongs to glycosyl hydrolase family 31, which has ancient evolutionary origins
Within this family, Ganc shows highest homology to the catalytic unit of glucosidase II (67% similarity)
Lower but significant similarity to other family members: lysosomal acid alpha-glucosidase, maltase-glucoamylase, and sucrase-isomaltase (41-67%)
This pattern suggests an early gene duplication and functional divergence within the family
Conservation of functional domains:
The catalytic WXDMNE motif is highly conserved across species and family members
This conservation indicates strong evolutionary pressure to maintain glucosidase activity
Variable regions likely represent adaptations for specific substrates or regulatory mechanisms
Secondary substrate-binding domains may have evolved to enhance enzyme processivity
Functional implications:
The neutral pH optimum distinguishes Ganc from lysosomal glucosidases, suggesting adaptation to different cellular compartments
Conservation across mammals indicates essential metabolic functions
Persistence of multiple glucosidases with overlapping substrate specificity suggests non-redundant functions
The presence of allelic variants, including null alleles , suggests possible selective advantages under different conditions
Disease relevance:
This evolutionary perspective highlights Ganc's importance in fundamental metabolic processes and provides context for interpreting experimental findings in both basic and translational research settings.
Recombinant mouse Ganc represents a valuable tool for investigating various aspects of glycogen metabolism:
Structural studies of glycogen:
Use purified Ganc to analyze glycogen branching patterns
Compare Ganc-mediated degradation products with those of other glucosidases
Investigate the enzyme's action on glycogen from different tissues and pathological states
Determine the influence of secondary substrate-binding domains on processing complex glycogen structures
Enzyme replacement therapy models:
Test recombinant Ganc as a potential complementary approach to GAA replacement
Evaluate cellular uptake and distribution of recombinant enzyme
Assess impact on glycogen accumulation in models of glycogen storage disorders
Compare efficacy of different enzyme formulations and modifications
Reporter systems:
Develop Ganc-based biosensors for glycogen visualization
Create fusion proteins with fluorescent tags for tracking glycogen metabolism in real-time
Use enzyme-coupled assays to monitor glycogen levels in various physiological states
Comparative enzymology:
Systematically compare kinetic properties with other glucosidases
Define the unique substrate preferences of Ganc
Identify specific inhibitors that distinguish between glucosidase family members
Map structural features to functional differences between family members
Metabolic network analysis:
Use recombinant Ganc to probe the integration of glycogen metabolism with other pathways
Investigate how Ganc activity responds to metabolic signals
Examine potential roles in specialized tissues with unique energy requirements
These applications leverage the availability of recombinant Ganc to address fundamental questions in glycogen metabolism and potentially develop new therapeutic approaches for metabolic disorders.
Several promising research directions could significantly advance our understanding of Ganc function in metabolic disorders:
Diabetes connection investigation:
Given that human GANC localizes to chromosome 15q15, reported to confer susceptibility to diabetes , explore mouse Ganc's role in glucose homeostasis
Characterize Ganc expression and activity changes in diabetic mouse models
Investigate potential genetic associations between Ganc variants and metabolic phenotypes
Explore whether Ganc modulation could represent a novel therapeutic approach
Complementary roles with acid alpha-glucosidase:
Investigate whether Ganc provides compensatory activity in Pompe disease models (acid alpha-glucosidase deficiency)
Explore potential synergistic effects of combined enzyme replacement
Determine if Ganc upregulation could be therapeutically beneficial in glycogen storage disorders
Characterize the distinct cellular roles of neutral versus acid glucosidases
Regulatory network mapping:
Identify transcription factors and signaling pathways that regulate Ganc expression
Determine how Ganc activity is modulated by post-translational modifications
Map protein-protein interactions that influence Ganc function
Develop computational models of glycogen metabolism incorporating Ganc activity
Development of specific modulators:
Design and screen for specific Ganc inhibitors or activators
Evaluate their effects on glycogen metabolism in various tissues
Assess potential therapeutic applications in metabolic disorders
Develop targeted delivery approaches for enzyme or modulators
Cellular stress responses:
Investigate Ganc's role in cellular adaptation to nutrient limitation
Explore connections between Ganc activity and endoplasmic reticulum stress
Examine potential roles in autophagy and lysosomal function
Assess responses to oxidative stress and inflammation
These research directions would significantly advance our understanding of Ganc's physiological roles and potentially reveal new therapeutic targets for metabolic disorders.
A comprehensive protocol for purifying recombinant mouse Ganc would include:
Expression system preparation:
Cell harvest and initial processing:
Collect cells by centrifugation (adherent cells should be scraped or trypsinized)
Wash cell pellet with cold PBS
Resuspend in lysis buffer:
50 mM Tris-HCl, pH 7.5
150 mM NaCl
1% Triton X-100 or other suitable detergent
Protease inhibitor cocktail
Lyse cells by sonication or mechanical disruption
Clarify lysate by centrifugation at 15,000 × g for 30 minutes at 4°C
Affinity chromatography:
Equilibrate Ni-NTA or similar affinity resin with binding buffer:
50 mM Tris-HCl, pH 7.5
300 mM NaCl
10 mM imidazole
Apply clarified lysate to column
Wash extensively with binding buffer
Elute bound protein with elution buffer:
50 mM Tris-HCl, pH 7.5
300 mM NaCl
250 mM imidazole
Secondary purification:
Pool active fractions determined by activity assay
Perform size exclusion chromatography:
Use Superdex 200 or similar column
Buffer: 20 mM Tris-HCl, pH 7.5, 150 mM NaCl
Alternative: Ion exchange chromatography
Final processing:
Quality control:
This protocol incorporates elements from successful purification of related glycosidases and should yield active, highly purified recombinant mouse Ganc suitable for research applications .
Designing robust assays for measuring Ganc activity in tissue samples requires careful consideration of specificity, sensitivity, and reliability:
Sample preparation:
Homogenize tissue in neutral pH buffer (20 mM Tris-HCl, pH 7.2-7.4)
Include protease inhibitors to prevent enzyme degradation
Clarify homogenates by centrifugation (10,000-15,000 × g for 15 minutes)
Perform protein determination for normalization
Distinguishing Ganc from other glucosidases:
Conduct parallel assays at multiple pH values:
pH 7.0-7.5 for Ganc activity
pH 4.0-4.5 for lysosomal alpha-glucosidase activity
Use selective inhibitors:
Include maltose or specific inhibitors to distinguish from maltase activity
Use mannose-based inhibitors to distinguish from glucosidase II
Assay methodology:
Colorimetric starch hydrolysis assay:
Fluorogenic substrate assay:
Controls and validation:
Include tissue samples known to express high and low levels of Ganc
Run parallel samples with heat-inactivated enzyme
Perform assays with purified recombinant Ganc as positive control
Include assay buffer without enzyme as negative control
Data analysis and reporting:
Calculate specific activity using the formula:
Specific Activity (pmol/min/μg) = | Adjusted glucose produced (nmol) × (1000 pmol/nmol) |
---|---|
Incubation time (min) × amount of protein (μg) |
Normalize to protein concentration
Present data as mean ± standard deviation from multiple determinations