Recombinant Bradyrhizobium japonicum Glycogen synthase 2 (glgA2)

What is Bradyrhizobium japonicum Glycogen synthase 2 (glgA2) and what is its functional role in bacterial metabolism?

Bradyrhizobium japonicum glycogen synthase 2 (glgA2) is an enzyme involved in glycogen synthesis, catalyzing the elongation of α-1,4-glucan chains using ADP-glucose as the glucosyl donor. B. japonicum USDA 110 has multiple polyhydroxyalkanoate synthases annotated in its genome, with glycogen synthases playing crucial roles in carbon storage . Similar to other rhizobia, glycogen metabolism in B. japonicum likely influences energy balance during symbiotic nitrogen fixation.

Methodology for functional characterization: To determine the precise role of glgA2, researchers should construct deletion mutants (ΔglgA2) and compare glycogen accumulation, growth characteristics, and symbiotic performance against wild-type strains. Complementation studies with the wild-type gene can confirm phenotypic observations. RNA-seq analysis during different growth phases can reveal expression patterns and metabolic network connections.

How does glgA2 differ structurally and functionally from other glycogen synthases in bacteria?

Based on comparative analysis with other bacterial glycogen synthases, B. japonicum glgA2 likely belongs to either GT4 or GT5 glycosyltransferase families. In Rhodococcus jostii, two glycogen synthases (RjoglgAb and RjoglgAc) show distinct functional characteristics despite catalyzing similar reactions :

Methodology for comparative analysis: Researchers should conduct sequence alignment and phylogenetic analysis with characterized bacterial glycogen synthases. Expression and purification of recombinant enzymes followed by detailed kinetic characterization will reveal functional differences.

What genomic context surrounds the glgA2 gene in Bradyrhizobium japonicum and how does this influence its expression?

Based on comparative genomics with Rhizobium tropici, the glgA2 gene in B. japonicum is likely part of an operon containing other glycogen metabolism genes. In R. tropici, glycogen metabolism genes are organized in a gene cluster including glycogen phosphorylase (glgP), glycogen branching enzyme (glgB), ADP glucose pyrophosphorylase (glgC), glycogen synthase (glgA), phosphoglucomutase (pgm), and glycogen debranching enzyme (glgX) .

Methodology for genomic context analysis: Researchers should perform genome walking and transcriptional analysis using RT-PCR to identify co-transcribed genes. Construction of promoter-reporter fusions can help identify regulatory elements controlling glgA2 expression under different environmental conditions.

What are the optimal expression systems and purification strategies for producing active recombinant B. japonicum glgA2?

Based on successful expression of other bacterial glycogen synthases, the following methodologies are recommended:

Expression system optimization:

• Vector selection: pET28a or similar vectors with T7 promoter systems

• Host strains: E. coli BL21(DE3) or Rosetta for rare codon optimization

• Induction conditions: 0.1-0.5 mM IPTG, 16-25°C overnight induction

Purification strategy:

• N-terminal His-tag fusion construction

• Immobilized metal affinity chromatography (IMAC) using Ni-NTA

• Size exclusion chromatography for further purification

• Buffer optimization (typically 50 mM Tris-HCl pH 8.0, 150 mM NaCl, 10% glycerol)

Researchers should monitor enzyme stability and activity throughout purification steps using activity assays described in FAQ 2.2.

What enzymatic assays are most appropriate for measuring glgA2 activity and determining kinetic parameters?

Two complementary methodologies are recommended for measuring glgA2 activity:

Coupled enzymatic assay:

• Reaction mix: ADP-glucose, glycogen, MgCl2, and coupling enzymes (pyruvate kinase, lactate dehydrogenase)

• Principle: ADP released during glycogen synthesis is used to regenerate ATP, coupled with NADH oxidation

• Detection: Decrease in NADH measured spectrophotometrically at 340 nm

• Advantage: Continuous real-time monitoring of activity

Radiometric assay:

• Reaction mix: [14C]ADP-glucose, glycogen, MgCl2

• Principle: Incorporation of radioactive glucose into glycogen

• Detection: Filter-binding followed by scintillation counting

• Advantage: Higher sensitivity and direct measurement of product formation

For kinetic parameter determination, researchers should vary substrate concentrations (ADP-glucose: 0.01-10 mM; glycogen: 0.01-10 mg/ml) and analyze data using Michaelis-Menten kinetics.

How can researchers design effective mutation studies to investigate structure-function relationships in glgA2?

Methodology for systematic structure-function analysis:

• Targeted mutagenesis approaches:

  • Alanine scanning of conserved residues identified through multiple sequence alignment

  • Site-directed mutagenesis of catalytic triad residues (typically Lys-X-Gly-Gly motif)

  • Domain swapping with other characterized glycogen synthases

• Validation of mutant effects:

  • Expression and purification using standardized protocols

  • Activity assays under standardized conditions

  • Thermal stability analysis using differential scanning fluorimetry

  • Structural analysis using circular dichroism spectroscopy

• In vivo functional analysis:

  • Complementation of glgA mutants with mutated versions of glgA2

  • Glycogen accumulation quantification using iodine staining and biochemical assays

  • Plant symbiosis assays to correlate structure-function relationships with symbiotic performance

How does glgA2 activity influence symbiotic nitrogen fixation efficiency in legume-Bradyrhizobium interactions?

Based on research with Rhizobium tropici, glycogen metabolism significantly impacts symbiotic performance. In R. tropici, a glgA mutant lacking glycogen synthase activity showed 20-38% increased plant dry weight compared to wild-type strains, indicating enhanced symbiotic nitrogen fixation . This suggests that redirecting carbon flux away from glycogen synthesis may increase energy availability for nitrogen fixation.

Methodology for symbiotic performance analysis:

• Generate glgA2 knockout and overexpression strains in B. japonicum

• Conduct plant inoculation experiments with soybean under controlled conditions

• Measure parameters including:

  • Nodule number, size, and leghemoglobin content

  • Nitrogenase activity using acetylene reduction assay

  • Plant biomass and nitrogen content

  • Bacteroid glycogen content using electron microscopy and biochemical assays

• Perform transcriptomic and metabolomic analyses of bacteroids to identify metabolic shifts

What is the regulatory relationship between glgA2 expression and environmental stress responses in B. japonicum?

Methodology for stress response analysis:

• Expose B. japonicum cultures to various stresses:

  • Carbon limitation and excess

  • Oxygen limitation and oxidative stress

  • Temperature stress (heat shock and cold shock)

  • pH stress (acidic and alkaline conditions)

  • Osmotic stress

• Quantify glgA2 expression using:

  • RT-qPCR for transcript levels

  • Western blotting for protein levels

  • Promoter-reporter fusions (gusA or gfp) for visual expression patterns

• Correlate expression patterns with:

  • Glycogen accumulation measured biochemically

  • Survival rates under prolonged stress

  • Metabolic flux analysis using 13C-labeled substrates

• Identify transcription factors and regulatory elements:

  • DNA-protein interaction studies (EMSA, ChIP-seq)

  • Promoter deletion analysis

How does the interplay between glgA2 and polyhydroxyalkanoate (PHA) metabolism affect carbon allocation in B. japonicum?

B. japonicum USDA 110 possesses multiple polyhydroxyalkanoate (PHA) synthases , suggesting complex carbon partitioning between glycogen and PHA storage pathways. In other bacteria, these storage polymers often show inverse relationships in accumulation patterns.

Methodology for carbon allocation analysis:

• Generate single and double mutants affecting both pathways:

  • ΔglgA2 (glycogen synthesis)

  • ΔphaC1 (PHA synthesis)

  • ΔglgA2ΔphaC1 (both pathways)

• Analyze carbon polymer accumulation under various growth conditions:

  • Quantify glycogen using enzymatic assays and iodine staining

  • Quantify PHA using Nile Red staining and gas chromatography

  • Correlate accumulation with growth phase and nutrient availability

• Perform 13C flux analysis to track carbon flow through:

  • Central carbon metabolism

  • Glycogen synthesis and degradation

  • PHA synthesis and degradation

• Assess symbiotic performance of mutants to determine the relative importance of each storage pathway for successful nodulation and nitrogen fixation

How should researchers address discrepancies in enzymatic activity data obtained from different expression systems?

Methodology for resolving experimental discrepancies:

• Standardize experimental conditions:

  • Use identical buffer compositions

  • Maintain consistent enzyme concentrations

  • Ensure substrate batch consistency

  • Control temperature precisely

• Validate protein quality:

  • Verify protein purity using SDS-PAGE

  • Confirm correct folding using circular dichroism

  • Assess oligomeric state using size exclusion chromatography

  • Quantify active site occupancy using substrate binding assays

• Statistical analysis approach:

  • Perform experiments in at least triplicate with independent protein preparations

  • Calculate means, standard deviations, and coefficients of variation

  • Use ANOVA to determine significance of differences between conditions

  • Report all experimental details to enable reproducibility

• Cross-validation strategies:

  • Compare results from multiple activity assays (coupled vs. radiometric)

  • Correlate in vitro activity with in vivo functionality

  • Compare with closely related enzymes under identical conditions

What bioinformatic approaches can predict substrate specificity differences between glgA2 and other glycogen synthases?

Methodology for computational substrate specificity analysis:

• Multiple sequence alignment:

  • Align B. japonicum glgA2 with characterized glycogen synthases

  • Identify conserved and variable regions in substrate binding sites

  • Map sequence conservation onto available crystal structures

• Homology modeling:

  • Generate 3D models using closest structural homologs as templates

  • Refine models using molecular dynamics simulations

  • Validate models using ProCheck and other validation tools

• Molecular docking:

  • Dock ADP-glucose and glycogen fragments into the active site

  • Calculate binding energies and identify key interaction residues

  • Compare binding modes with experimentally characterized enzymes

• Experimental validation:

  • Generate site-directed mutants of predicted specificity-determining residues

  • Measure kinetic parameters with various substrates

  • Determine substrate specificity profiles

What strategies can overcome poor solubility of recombinant B. japonicum glgA2 during heterologous expression?

Methodology for improving recombinant protein solubility:

• Expression condition optimization:

  • Reduce induction temperature to 16-20°C

  • Lower IPTG concentration to 0.1-0.2 mM

  • Use rich media (e.g., Terrific Broth) for expression

  • Harvest cells during log phase rather than stationary phase

• Vector and construct modifications:

  • Test different solubility-enhancing fusion tags (MBP, SUMO, TrxA)

  • Optimize codon usage for E. coli expression

  • Create truncated constructs removing flexible or hydrophobic regions

  • Use periplasmic targeting to promote proper folding

• Host strain selection:

  • Test BL21(DE3)pLysS to reduce leaky expression

  • Use Origami strains to enhance disulfide bond formation

  • Co-express with molecular chaperones (GroEL/ES, DnaK/J)

  • Use specialized strains for rare codon optimization

• Solubilization and refolding approaches:

  • Extract from inclusion bodies using 8M urea or 6M guanidine-HCl

  • Perform gradual dialysis to remove denaturants

  • Use artificial chaperones (cyclodextrin) during refolding

  • Screen additives (glycerol, arginine, polyols) to enhance stability

How can researchers distinguish between glycogen synthase 2 activity and other overlapping glycosyltransferase activities in B. japonicum extracts?

Methodology for specific activity discrimination:

• Substrate specificity profiling:

  • Test activity with various glucosyl donors (ADP-glucose, UDP-glucose, GDP-glucose)

  • Compare activity with different acceptors (glycogen, maltooligosaccharides, other polysaccharides)

  • Determine kinetic parameters for each substrate combination

• Inhibitor studies:

  • Use specific inhibitors targeting different glycosyltransferase families

  • Conduct competitive inhibition studies with substrate analogs

  • Perform thermal shift assays to verify inhibitor binding

• Immunological approaches:

  • Generate specific antibodies against B. japonicum glgA2

  • Deplete specific activities using immunoprecipitation

  • Perform western blot analysis on fractionated cell extracts

• Genetic approaches:

  • Create knockout strains lacking glgA2

  • Measure residual glycosyltransferase activities in mutant extracts

  • Complement with wild-type and mutant versions of glgA2