Recombinant Burkholderia multivorans Glucose-6-phosphate isomerase (pgi), partial

What is the biochemical role of glucose-6-phosphate isomerase in bacterial metabolism?

Glucose-6-phosphate isomerase (EC 5.3.1.9), also known as phosphoglucose isomerase (PGI), catalyzes the reversible isomerization of D-glucose-6-phosphate (G-6-P) to D-fructose-6-phosphate (F-6-P). This enzyme plays a central role in sugar metabolism across all domains of life, including Archaea, Bacteria, and Eucarya . In bacteria, PGI functions in both glycolysis and gluconeogenesis, serving as a key enzyme in the Embden-Meyerhof-Parnas (EMP) pathway. Additionally, it connects glycolysis to the pentose phosphate pathway, which is essential for generating NADPH and pentoses for nucleic acid synthesis .

How conserved is the PGI enzyme across bacterial species?

While PGI is present in virtually all living cells, there is significant interspecies variation at the primary structure level, which can produce heterogeneity in structural and functional properties . For example, archaeal PGIs represent a novel type that shows no significant similarity to the conserved PGI superfamily found in eubacteria and eucarya . Research has shown that some organisms possess multiple PGI isoforms with distinct biochemical properties and cofactor specificity . This evolutionary divergence makes comparative studies of bacterial PGIs, including that from B. multivorans, particularly valuable for understanding structural-functional relationships.

What are typical kinetic parameters for bacterial PGIs?

Kinetic parameters vary across bacterial species. For recombinant PGI from Mycobacterium tuberculosis, the Km value was determined to be 0.318 mM for fructose-6-phosphate, and the Ki was 0.8 mM for 6-phosphogluconate . The enzyme exhibited a specific activity of approximately 600 U/mg protein. Most bacterial PGIs show optimal activity in the pH range of 7.0-9.0 and temperatures between 37-80°C, depending on the organism's natural habitat . For hyperthermophilic species like Pyrococcus furiosus, PGI can function optimally at much higher temperatures .

What are the most effective strategies for cloning the pgi gene from Burkholderia multivorans?

For cloning bacterial pgi genes, researchers typically:

• Design PCR primers based on the known pgi sequence from the bacterial genome database. For B. multivorans, primers should be designed to flank the coding region with appropriate restriction sites compatible with your expression vector.

• Amplify the target DNA using high-fidelity polymerase (such as Pwo polymerase as used for P. furiosus PGI cloning) .

• Clone the amplified fragment into an appropriate expression vector. Common vectors include pET-series vectors (like pET-22b(+) used for M. tuberculosis PGI) or pBAD vectors (used for P. furiosus PGI) .

• Verify the sequence to ensure no mutations were introduced during PCR amplification.

For B. multivorans specifically, consider the organism's high GC content when designing primers and optimizing PCR conditions to enhance amplification efficiency and specificity.

What expression system is most suitable for producing soluble recombinant B. multivorans PGI?

E. coli remains the most widely used expression system for bacterial enzymes. For recombinant PGI production:

• BL21(DE3) or similar strains are commonly used host cells for T7 promoter-based expression vectors .

• Expression conditions should be optimized to minimize inclusion body formation. Lower induction temperatures (16-25°C) and reduced IPTG concentrations often increase the proportion of soluble protein .

• For difficult-to-express proteins, consider fusion partners such as maltose-binding protein (MBP) or thioredoxin to enhance solubility.

• Alternative expression systems such as Pseudomonas species might be considered for Burkholderia proteins due to their closer phylogenetic relationship.

The recombinant M. tuberculosis PGI expressed in E. coli formed both soluble protein and inclusion bodies, with the soluble fraction being enzymatically active . Similar results might be expected for B. multivorans PGI.

What purification strategy yields the highest purity and activity for recombinant PGI?

A multi-step purification approach is typically required:

• Initial capture by affinity chromatography if a tag (His, GST) is incorporated in the construct.

• Ion-exchange chromatography has been successfully used for PGI purification, as demonstrated with M. tuberculosis PGI .

• Size-exclusion chromatography as a polishing step to remove aggregates and achieve high purity.

Throughout purification, it's essential to:

• Maintain appropriate buffer conditions (typically pH 7.0-8.0)

• Include protease inhibitors to prevent degradation

• Test fractions for enzyme activity using standard PGI assays

• Consider adding stabilizing agents (glycerol, reducing agents) if the enzyme shows instability

The purification protocol should be optimized to preserve the dimeric structure of PGI, which is essential for its catalytic activity .

What assays are recommended for measuring B. multivorans PGI activity?

Two primary approaches can be used for measuring PGI activity:

Discontinuous assays:

• For F-6-P formation: Incubate PGI with G-6-P at optimal temperature (likely 37°C for B. multivorans), stop the reaction at defined time points, and couple with auxiliary enzymes (F-1,6-BP aldolase, TIM, glycerol-phosphate-dehydrogenase) to measure NADH oxidation at 365 nm .

• For G-6-P formation: Incubate PGI with F-6-P, stop the reaction, and couple with glucose-6-phosphate dehydrogenase to measure NADP+ reduction at 365 nm .

Continuous assays:

• For F-6-P formation: Measure NADH oxidation in a coupled reaction system containing G-6-P, ATP, MgCl₂, NADH, PFK, FBP aldolase, TIM, and glycerol-3-phosphate dehydrogenase .

• For G-6-P formation: Monitor NADP+ reduction in a mixture containing F-6-P, NADP+, and glucose-6-phosphate dehydrogenase .

For accurate measurements, control reactions without PGI should be performed to account for background rates.

How can the cofactor specificity of B. multivorans PGI be determined?

While classic PGI does not require cofactors for its isomerase activity, interactions with other enzymes in metabolic pathways can involve cofactor preferences:

• Perform activity assays using both NAD+ and NADP+ as cofactors in coupled enzyme systems to determine if the PGI preferentially feeds into pathways with specific cofactor requirements .

• Compare enzyme kinetics with each cofactor to determine relative efficiency.

• Analyze structural features through homology modeling or crystal structure determination to identify putative cofactor binding sites.

Research on Pseudomonas putida has shown that different G6PDH isoforms (which work downstream of PGI) have different cofactor specificities for NAD+ versus NADP+, affecting the metabolic flux distribution . Understanding these preferences is crucial for metabolic engineering applications.

What approaches can reveal structure-function relationships in B. multivorans PGI?

Several complementary approaches can be employed:

• X-ray crystallography or cryo-EM: Determine the three-dimensional structure of the enzyme. PGI typically has an α/β structure with two domains per subunit, and the active site is located at both the domain interface and the subunit interface .

• Site-directed mutagenesis: Target conserved residues (particularly histidine and glutamate residues that may be at the active site) to assess their role in catalysis.

• Hydrogen-deuterium exchange mass spectrometry (HDX-MS): Examine protein dynamics and conformational changes during substrate binding.

• Molecular dynamics simulations: Model substrate binding and catalytic mechanisms based on the crystal structure.

• Circular dichroism spectroscopy: Analyze secondary structure elements and thermal stability.

The crystal structure of pig muscle PGI revealed that each subunit consists of two domains with the active site at both the domain interface and subunit interface . Similar structural features might be present in bacterial PGIs.

How does temperature affect the stability and activity of recombinant B. multivorans PGI?

To characterize thermal properties:

• Determine temperature optima by measuring activity across a temperature range (20-80°C).

• Assess thermal stability through:

  • Differential scanning calorimetry to determine melting temperature (Tm)

  • Activity retention after incubation at various temperatures

  • Circular dichroism to monitor structural changes with increasing temperature

• Compare with PGIs from other organisms - M. tuberculosis PGI showed optimal activity at 37°C , while hyperthermophilic archaeal PGIs like that from P. furiosus are active at much higher temperatures .

• Investigate structural features contributing to thermal stability or instability, particularly in the context of B. multivorans' natural habitat.

Understanding thermal properties is crucial when designing experimental protocols and considering potential biotechnological applications.

How can molecular evolution approaches be used to engineer B. multivorans PGI with enhanced properties?

Molecular evolution strategies include:

• Directed evolution: Generate libraries of pgi variants through error-prone PCR or DNA shuffling, followed by screening for desired properties (higher activity, stability, altered substrate specificity).

• Semi-rational design: Combine structural knowledge with targeted mutagenesis of specific regions (active site, subunit interface).

• Ancestral sequence reconstruction: Infer and synthesize ancestral PGI sequences to understand evolutionary trajectories.

• Computational design: Use algorithms to predict mutations that might enhance desired properties.

Success in enzyme engineering requires robust high-throughput screening methods to identify improved variants from large libraries.

What role does PGI play in B. multivorans metabolic adaptation to different carbon sources?

To investigate metabolic roles:

• Generate pgi knockout mutants and characterize growth phenotypes on different carbon sources.

• Perform metabolic flux analysis using 13C-labeled substrates to quantify changes in carbon flow.

• Analyze transcriptional responses of pgi and related genes under different growth conditions.

• Compare with findings from other organisms - research on P. putida showed that different G6PDH isoforms (enzymes related to PGI in central metabolism) act as metabolic "gatekeepers" for carbon sources entering at different nodes of the biochemical network .

• Investigate potential redundancy through alternative pathways or isozymes.

This research would provide insights into B. multivorans metabolic flexibility and potential adaptations to its natural environment.

How can researchers address inclusion body formation when expressing recombinant B. multivorans PGI?

Strategies to minimize inclusion bodies include:

• Optimize expression conditions:

  • Lower induction temperature (16-25°C)

  • Reduce inducer concentration

  • Use rich media formulations

  • Decrease expression rate with weaker promoters

• Modify the construct:

  • Add solubility-enhancing tags (MBP, SUMO, thioredoxin)

  • Express as a truncated protein if certain domains cause aggregation

  • Codon optimization for E. coli expression

• Refolding approaches if inclusion bodies persist:

  • Solubilize inclusion bodies with chaotropic agents (8M urea or 6M guanidinium hydrochloride)

  • Refold by gradual dialysis against decreasing concentrations of denaturant

  • Add folding additives (arginine, low concentrations of detergents)

Studies with M. tuberculosis PGI showed that it expressed partly as soluble protein and partly as inclusion bodies in E. coli , suggesting similar challenges might occur with B. multivorans PGI.

What strategies can resolve inconsistent kinetic data when characterizing recombinant PGI?

Inconsistent kinetic data can result from several factors:

• Enzyme quality issues:

  • Verify protein purity by SDS-PAGE and mass spectrometry

  • Check for proper folding using circular dichroism

  • Ensure the dimeric state is maintained using size exclusion chromatography

• Assay optimization:

  • Validate coupling enzyme activity and ensure it's not rate-limiting

  • Control temperature precisely throughout experiments

  • Optimize buffer components (pH, ionic strength)

  • Ensure linearity of the assay with respect to time and enzyme concentration

• Data analysis:

  • Use appropriate kinetic models (Michaelis-Menten, allosteric models)

  • Account for potential substrate/product inhibition

  • Apply statistical methods to evaluate data quality

• Batch-to-batch variation:

  • Standardize purification protocols

  • Prepare larger batches of stable enzyme preparations

  • Include appropriate controls with each experiment

Careful consideration of these factors will lead to more reliable and reproducible kinetic characterization.