Recombinant Bartonella henselae Glycerol-3-phosphate dehydrogenase [NAD (P)+] (gpsA)

What is the functional significance of GpsA in Bartonella henselae metabolism?

Glycerol-3-phosphate dehydrogenase (GpsA) serves as a critical metabolic enzyme in bacteria including Bartonella species. Based on homology with other bacterial GpsA proteins, B. henselae GpsA likely catalyzes the reduction of dihydroxyacetone phosphate (DHAP) to glycerol-3-phosphate (G3P) using the reducing power of NADH or NADPH . This reaction represents a crucial connection between glycolysis and phospholipid biosynthesis, making GpsA a linchpin connecting central carbohydrate and lipid metabolism .

How does B. henselae GpsA differ structurally from other bacterial glycerol-3-phosphate dehydrogenases?

While specific structural data for B. henselae GpsA is limited in current literature, comparative analysis with other bacterial G3PDHs provides insights into likely structural features. Unlike mammalian G3PDHs, bacterial GpsA proteins typically function as homodimers or homotetramers and contain distinct NAD(P)H binding domains.

The functional properties of B. henselae GpsA can be inferred from complementation studies performed with other bacterial GpsA proteins. For example, research has demonstrated that Borrelia burgdorferi GpsA can functionally complement E. coli gpsA mutations, suggesting conservation of essential catalytic domains across bacterial species . Researchers working with B. henselae GpsA should consider these structural similarities when designing experiments or interpreting results.

What is the genomic context of the gpsA gene in B. henselae?

The gpsA gene in B. henselae is predicted to encode the glycerol-3-phosphate dehydrogenase enzyme based on sequence homology with other bacterial species. While the specific genomic neighborhood of B. henselae gpsA is not detailed in the provided literature, research in related bacteria shows that the genomic context of metabolic genes often provides insights into their regulation and functional relationships.

By comparison, in B. burgdorferi, the gpsA gene (bb0368) exists in a metabolic node with glpD, with their opposing enzymatic activities balancing glycolysis and lipid biosynthesis . Researchers investigating B. henselae gpsA should analyze its genomic context to identify potential co-regulated genes or operons that might contribute to understanding its physiological role and regulation mechanisms.

What expression systems are most effective for producing recombinant B. henselae GpsA?

For expression of recombinant B. henselae GpsA, E. coli-based systems offer practical advantages due to established protocols and high protein yields. Based on approaches used for similar bacterial enzymes, researchers should consider the following expression system options:

• pET vector systems with T7 promoter in E. coli BL21(DE3) or Rosetta strains

• IPTG-inducible systems with temperature optimization (typically 16-25°C post-induction)

• Fusion tags such as His6, MBP, or GST to facilitate purification and potentially enhance solubility

From experimental approaches with related proteins, expression can be validated through heterologous complementation studies. For example, B. burgdorferi gpsA was successfully cloned into the E. coli IPTG-inducible expression vector pUC18 and used to complement an E. coli gpsA mutant (BB20-14) that cannot grow on glucose as the sole carbon source . This approach not only confirms expression but also validates the functional activity of the recombinant protein.

What purification strategy yields the highest activity for recombinant B. henselae GpsA?

A multi-step purification strategy is recommended to obtain high-purity, active recombinant B. henselae GpsA:

• Initial capture: Immobilized metal affinity chromatography (IMAC) using Ni-NTA or Co-NTA resins for His-tagged constructs

• Intermediate purification: Ion exchange chromatography (typically Q-Sepharose)

• Polishing step: Size exclusion chromatography to obtain homogeneous protein preparation

Buffer optimization is critical for maintaining enzyme activity. A typical buffer system would include:

• 50 mM Tris-HCl or phosphate buffer (pH 7.5-8.0)

• 150-300 mM NaCl

• 10% glycerol as a stabilizing agent

• 1-5 mM DTT or 2-mercaptoethanol to maintain reduced cysteines

• Optional: 0.1 mM NADH/NADPH to stabilize the enzyme during purification

Throughout purification, activity should be monitored using the standard GpsA activity assay measuring NADH/NADPH oxidation spectrophotometrically at 340 nm in the presence of DHAP substrate.

How can researchers assess the purity and integrity of recombinant B. henselae GpsA preparations?

Multiple analytical techniques should be employed to comprehensively assess protein purity and integrity:

• SDS-PAGE: Evaluate protein purity and molecular weight (expected ~36-40 kDa based on homologous bacterial GpsA proteins)

• Western blotting: Using anti-His antibodies for tagged constructs or specific anti-GpsA antibodies if available

• Mass spectrometry: Confirm protein identity and detect any post-translational modifications

• Dynamic light scattering: Assess homogeneity and oligomeric state

• Circular dichroism: Verify proper secondary structure folding

• Thermal shift assay: Evaluate protein stability under different buffer conditions

For functional integrity, specific activity measurements using the standard GpsA assay (NADH oxidation in the presence of DHAP) should be compared to published values for related bacterial GpsA enzymes. While specific activity values for B. henselae GpsA are not reported in the provided literature, researchers should aim for consistent specific activity across preparations as a quality control measure.

What methods are most reliable for measuring B. henselae GpsA enzyme activity?

The standard spectrophotometric assay for measuring GpsA activity involves monitoring the oxidation of NADH or NADPH at 340 nm as it is consumed during the reduction of DHAP to G3P. A reliable protocol includes:

Spectrophotometric Assay Components:

• 50 mM Tris-HCl buffer (pH 7.5-8.0)

• 150 mM NaCl

• 0.2 mM NADH or NADPH

• 1 mM DHAP (substrate)

• 0.1-5 μg purified GpsA enzyme

• Total reaction volume: 200-1000 μL

The reaction is initiated by adding the substrate, and the decrease in absorbance at 340 nm is monitored over time. The specific activity is calculated using the extinction coefficient of NADH/NADPH (6,220 M⁻¹cm⁻¹).

Alternative approaches include:

• Coupled enzyme assays: Linking GpsA activity to a second reaction that produces a more easily detectable signal

• Radiometric assays: Using ¹⁴C or ³H-labeled substrates to track product formation

• HPLC or LC-MS methods: Directly quantifying substrate consumption and product formation

For in vivo activity assessment, complementation of E. coli gpsA mutant strains unable to grow on glucose as the sole carbon source can be used to confirm functional activity, as demonstrated with B. burgdorferi GpsA .

What are the optimal conditions for B. henselae GpsA activity in vitro?

Based on studies of bacterial GpsA enzymes, the following conditions likely represent the optimal parameters for B. henselae GpsA activity:

Optimal Conditions Table:

Researchers should perform enzyme characterization experiments to determine the specific Km values for DHAP and NADH/NADPH, as well as the pH and temperature optima for the B. henselae enzyme, as these parameters may differ from other bacterial GpsA enzymes.

How can researchers differentiate between GpsA and GlpD activities in bacterial extracts?

Differentiating between GpsA and GlpD activities is critical for understanding the metabolic flux through the G3P node in bacterial systems. These strategies can be employed:

• Direction-specific assays:

  • GpsA: Measure NADH/NADPH oxidation with DHAP as substrate

  • GlpD: Measure NAD+ reduction with G3P as substrate or use artificial electron acceptors

• Selective inhibition:

  • Using specific inhibitors that preferentially affect one enzyme over the other

  • Thermal inactivation if the enzymes have different stability profiles

• Genetic approaches:

  • Complementation with purified recombinant enzymes in knockout extracts

  • Analysis in single and double mutant backgrounds (ΔgpsA, ΔglpD, and ΔgpsA/ΔglpD)

Research in B. burgdorferi has demonstrated that deleting glpD in a gpsA mutant background can function as a suppressor mutation, restoring viability under nutrient stress and normalizing metabolic imbalances of NADH and G3P . This genetic approach clearly differentiates the opposing functions of these enzymes and reveals their metabolic interplay.

What is the role of GpsA in B. henselae virulence and pathogenesis?

While the specific role of GpsA in B. henselae virulence is not directly addressed in the provided literature, insights from studies in related bacteria suggest it may be crucial for pathogenesis. In B. burgdorferi, GpsA has been identified as an essential virulence factor - it is required for murine infection and crucial for persistence of the spirochete in the tick vector .

GpsA likely contributes to B. henselae pathogenesis through several mechanisms:

Given that B. henselae can cause persistent infections in both mammalian hosts and arthropod vectors, GpsA's role in managing metabolic adaptations during these transitions may be particularly important. Researchers investigating GpsA's role in B. henselae pathogenesis should consider both in vitro stress models and in vivo infection studies to comprehensively assess its contribution to virulence.

How does nutrient availability affect GpsA expression and activity in B. henselae?

Based on findings with related bacterial glycerol-3-phosphate dehydrogenases, GpsA expression and activity in B. henselae are likely modulated by nutrient availability. In B. burgdorferi, GpsA is required for survival under nutrient stress conditions, with mutants showing dramatically reduced viability when transferred to nutrient-limited medium .

The metabolic node comprising GpsA and GlpD appears to regulate carbon flow between lipid biosynthesis and glycolysis in response to the available carbon sources. Notably, in B. burgdorferi under nutrient stress:

• GpsA mutants show reduced reductase activity and undergo dramatic morphological changes from flat-wave to condensed spherical forms (round bodies)

• Addition of glycerol to nutrient stress medium is cytotoxic to wild-type bacteria but not to GlpD mutants, suggesting complex metabolic interactions

• N-acetylglucosamine (GlcNAc) affects survival in a GlpD-dependent manner, indicating connections between different carbohydrate utilization pathways

These findings suggest that GpsA in B. henselae may play a crucial role in metabolic adaptation to changing nutrient environments, particularly in the transition between host and vector or during different stages of infection. Researchers should examine GpsA expression and activity under various nutrient conditions relevant to the B. henselae life cycle.

What phenotypes are associated with gpsA mutations in Bartonella species?

While specific phenotypes of gpsA mutations in Bartonella species are not directly described in the provided literature, comparative analysis with other bacterial systems suggests several potential phenotypes:

Predicted phenotypes of B. henselae gpsA mutations:

In B. burgdorferi, gpsA deletion results in multiple phenotypes that can be suppressed by concurrent deletion of glpD, indicating a carefully balanced metabolic node . A similar relationship might exist in B. henselae, where the opposing activities of GpsA and GlpD must be balanced for optimal metabolic function.

To investigate gpsA mutation phenotypes in B. henselae, researchers should consider generating conditional mutants if direct deletion is lethal, and examine the resulting strains under various growth conditions and in infection models.

How can metabolomic approaches be used to study the impact of GpsA on B. henselae metabolism?

Metabolomic approaches offer powerful tools for investigating the global metabolic impact of GpsA in B. henselae:

Recommended metabolomic workflow:

• Sample preparation: Compare wild-type B. henselae, gpsA mutants, and complemented strains grown under defined conditions

• Untargeted metabolomics:

  • LC-MS/MS or GC-MS analysis to identify broad metabolic changes

  • Focus on central carbon metabolism, lipid precursors, and redox-related metabolites

• Targeted analysis: Quantify specific metabolites directly connected to GpsA function:

  • Glycerol-3-phosphate and dihydroxyacetone phosphate levels

  • NAD+/NADH and NADP+/NADPH ratios

  • Phospholipid precursors and end products

• Flux analysis: Use isotope-labeled substrates (13C-glucose, 13C-glycerol) to trace carbon flow

Research in B. burgdorferi has shown that GpsA serves as a dominant regulator of NADH and glycerol-3-phosphate levels in vitro, affecting both the cellular redox potential and precursor availability for lipid biosynthesis . Metabolomic analysis of B. henselae would likely reveal similar regulatory roles with potentially species-specific metabolic impacts.

What computational models exist for predicting GpsA interactions with inhibitors or regulators?

Computational models for studying B. henselae GpsA interactions include:

• Homology modeling:

  • Generate 3D structure models based on crystal structures of related bacterial G3PDHs

  • Refine models using molecular dynamics simulations to account for B. henselae-specific sequence variations

• Virtual screening approaches:

  • Structure-based virtual screening of compound libraries against active site models

  • Pharmacophore-based screening using known inhibitors of related enzymes

• Molecular docking studies:

  • Predict binding modes of substrates, cofactors, and potential inhibitors

  • Identify key residues involved in catalysis and ligand binding

• Metabolic network modeling:

  • Incorporate GpsA into genome-scale metabolic models of B. henselae

  • Perform flux balance analysis to predict metabolic impacts of GpsA inhibition

• Protein-protein interaction predictions:

  • Identify potential regulatory proteins that may interact with GpsA

  • Model complex formation between GpsA and potential partner proteins

These computational approaches should be validated experimentally through enzyme inhibition studies, mutagenesis of predicted key residues, and protein interaction assays.

How can researchers design specific inhibitors targeting B. henselae GpsA for research applications?

Rational design of B. henselae GpsA inhibitors for research applications should follow this methodological framework:

• Active site mapping:

  • Identify catalytic residues through sequence alignment with characterized G3PDHs

  • Locate cofactor binding sites (NADH/NADPH) and substrate binding regions (DHAP)

  • Identify species-specific variations that could be exploited for selective inhibition

• Inhibitor scaffolds:

  • Screen known dehydrogenase inhibitors as starting points

  • Design substrate analogs that compete with DHAP

  • Develop cofactor competitors that bind the NADH/NADPH site

  • Explore allosteric inhibitors that bind regulatory sites

• Selectivity considerations:

  • Compare with human G3PDH to avoid cross-reactivity

  • Design compounds that exploit bacterial-specific features

  • Consider permeability across bacterial membranes

• Validation methods:

  • In vitro enzyme inhibition assays with purified recombinant GpsA

  • Cellular assays measuring metabolite levels (G3P, DHAP) and bacterial viability

  • Testing in infection models to confirm target engagement in vivo

The fact that GpsA appears essential for infection in related bacteria makes it a valuable research target . Selective inhibitors would serve as chemical probes to study GpsA function in different aspects of B. henselae biology and pathogenesis.

What are common pitfalls in working with recombinant B. henselae GpsA and how can they be overcome?

Researchers working with recombinant B. henselae GpsA may encounter several challenges:

Common Pitfalls and Solutions:

An effective troubleshooting approach is to validate enzyme functionality through complementation of E. coli gpsA mutants, as demonstrated with B. burgdorferi GpsA . This provides a functional readout independent of direct enzymatic assays.

How can researchers differentiate the metabolic effects of GpsA from other dehydrogenases in complex bacterial systems?

Differentiating GpsA-specific metabolic effects from those of other dehydrogenases requires a multi-faceted approach:

• Genetic manipulations:

  • Generate clean deletion mutants (ΔgpsA)

  • Create conditional expression systems if gpsA is essential

  • Construct double mutants (e.g., ΔgpsA/ΔglpD) to understand compensatory mechanisms

• Biochemical approaches:

  • Utilize substrate specificity (DHAP vs other substrates)

  • Leverage cofactor preference (NADH/NADPH)

  • Develop GpsA-specific antibodies for immunoprecipitation of enzyme complexes

• Metabolomics with isotope labeling:

  • Trace 13C-labeled substrates through different metabolic pathways

  • Compare labeling patterns in wild-type vs gpsA mutant strains

  • Quantify flux through GpsA vs alternative pathways

• Systems biology integration:

  • Combine transcriptomics, proteomics, and metabolomics data

  • Construct metabolic models that predict pathway usage

  • Validate predictions with targeted enzyme assays

Research in B. burgdorferi has shown that deleting glpD can suppress the phenotypes of a gpsA mutation , highlighting the importance of considering metabolic networks rather than isolated enzymes when interpreting experimental results.

What specialized techniques are required to study GpsA function in the context of B. henselae infection models?

Investigating GpsA function in B. henselae infection contexts requires specialized techniques spanning multiple disciplines:

• Genetic tools for in vivo studies:

  • Inducible expression systems for controlled gpsA expression

  • Fluorescent protein fusions to track GpsA localization during infection

  • CRISPR interference for targeted knockdown if complete deletion is lethal

• Cell culture infection models:

  • Human endothelial cell infections to study vascular manifestations

  • Macrophage infection models to assess intracellular survival

  • Real-time imaging of GpsA activity using FRET-based sensors

• Animal infection models:

  • Specialized B. henselae infection models (cats as natural reservoir hosts)

  • Murine surrogate models for laboratory investigations

  • In vivo competition assays between wild-type and gpsA mutants

• Vector transition studies:

  • Cat flea (Ctenocephalides felis) infection models

  • Environmental stress transitions mimicking vector-host transfer

  • Metabolic profiling during host-vector transitions

• Clinical isolate comparisons:

  • Analysis of gpsA sequence and expression in diverse clinical isolates

  • Correlation of gpsA variants with virulence phenotypes

  • Functional complementation studies across isolates

Research in B. burgdorferi demonstrated that GpsA is essential for murine infection and crucial for persistence in the tick vector , suggesting similar specialized techniques would be valuable for understanding B. henselae GpsA function in relevant infection contexts.