Recombinant Mannheimia succiniciproducens Glycerol-3-phosphate dehydrogenase [NAD (P)+] (gpsA)

What is the role of Glycerol-3-phosphate dehydrogenase (gpsA) in Mannheimia succiniciproducens metabolism?

Glycerol-3-phosphate dehydrogenase (gpsA) in M. succiniciproducens catalyzes the reversible conversion of dihydroxyacetone phosphate (DHAP) to glycerol-3-phosphate (G3P) using NADH or NADPH as a reducing agent. This enzyme represents a critical node connecting glycolysis to lipid metabolism, as G3P serves as a precursor for phospholipid biosynthesis .

To investigate gpsA's role in M. succiniciproducens metabolism, implement this methodological approach:

• Gene confirmation and characterization:

  • Identify the gpsA gene in the M. succiniciproducens genome through bioinformatics analysis

  • Clone and heterologously express in E. coli to confirm function (similar to complementation studies with B. burgdorferi gpsA)

  • Conduct growth complementation assays in a gpsA-deficient E. coli strain

• Enzyme characterization:

  • Express and purify recombinant gpsA using affinity chromatography

  • Determine kinetic parameters for substrates (DHAP, NADH, NADPH) and products

  • Measure enzymatic activity using spectrophotometric assays monitoring NADH oxidation at 340 nm

• Gene knockout studies:

  • Create gpsA deletion mutants using homologous recombination techniques

  • Analyze growth phenotypes under various nutrient conditions

  • Measure changes in survival under nutrient stress conditions

How does gpsA contribute to succinic acid production in Mannheimia succiniciproducens?

As a central metabolic enzyme, gpsA influences the redox balance and carbon flux in M. succiniciproducens, which directly impacts succinic acid production. By catalyzing the reduction of DHAP to G3P, gpsA consumes NADH, affecting the availability of reducing equivalents required for the reductive branch of the TCA cycle where succinic acid is produced .

To investigate this relationship, implement this experimental approach:

• Expression modulation studies:

  • Construct strains with varying levels of gpsA expression

  • Use inducible promoters to control expression during fermentation

  • Compare succinic acid production levels among strains

• Fermentation analysis:

  • Perform batch and fed-batch fermentations under anaerobic conditions with CO2 supplementation

  • Analyze fermentation products by HPLC, focusing on:

• Redox balance analysis:

  • Measure NADH/NAD+ ratios during fermentation

  • Correlate these measurements with succinic acid production rates

  • Investigate interactions with other dehydrogenases like GlpD

What are the optimal conditions for expressing recombinant Mannheimia succiniciproducens gpsA?

To express recombinant M. succiniciproducens gpsA with high yield and activity, a systematic optimization approach is required . Based on protocols for similar enzymes, the following methodology is recommended:

• Construct design:

  • Clone the gpsA gene into an expression vector like pET28a or pUC18

  • Include an affinity tag (His6 or SUMO) to facilitate purification

  • Consider codon optimization for expression host

• Expression conditions optimization:

  • Test multiple E. coli expression strains (BL21(DE), Rosetta, Arctic Express)

  • Optimize induction parameters:

• Solubility enhancement strategies:

  • Co-express with chaperones (GroEL/GroES, DnaK/DnaJ/GrpE)

  • Use fusion tags known to enhance solubility (MBP, GST, TrxA)

  • Add compatible solutes or osmolytes to the growth medium

• Protein purification:

  • Optimize cell lysis conditions (sonication, high-pressure homogenization)

  • Test different buffer systems for maximum stability

  • Implement multi-step purification for highest purity

  • Verify enzyme activity after each purification step

How is gpsA regulated in Mannheimia succiniciproducens?

To investigate the regulation of gpsA in M. succiniciproducens, a comprehensive approach is needed that examines regulation at multiple levels:

• Transcriptional regulation:

  • Identify the promoter region using 5' RACE and bioinformatics

  • Create transcriptional reporter fusions (gpsA promoter with GFP or lacZ)

  • Measure promoter activity under different conditions:

    • Various carbon sources (glucose, glycerol, sucrose)

    • Growth phases (exponential vs. stationary)

    • Stress conditions (nutrient limitation, pH changes)

  • Perform ChIP-seq to identify transcription factor binding sites

• Post-transcriptional regulation:

  • Analyze mRNA stability using rifampicin chase experiments

  • Investigate potential regulatory RNA elements in 5' and 3' UTRs

  • Assess if expression is inducible by specific substrates, similar to how the sucrose PTS in M. succiniciproducens is inducible by sucrose

• Metabolic regulation:

  • Determine allosteric regulators by enzyme assays with potential effectors

  • Measure product inhibition effects

  • Investigate feedback regulation from downstream metabolites

• Integrative approach:

  • Combine transcriptomic and metabolomic analyses to build a regulatory network model

  • Compare regulation patterns with those observed in other organisms like B. burgdorferi, where gpsA activity is influenced by nutrient availability

What cofactors does Mannheimia succiniciproducens gpsA use?

The naming of the enzyme as "Glycerol-3-phosphate dehydrogenase [NAD(P)+]" suggests it can utilize both NAD+ and NADP+ as cofactors. To experimentally determine and characterize its cofactor specificity:

• Enzyme assays with different cofactors:

  • Express and purify recombinant gpsA

  • Perform spectrophotometric assays using:

    • NADH alone

    • NADPH alone

    • Both cofactors in competition experiments

  • Determine kinetic parameters for each cofactor:

• Cofactor binding analysis:

  • Use isothermal titration calorimetry (ITC) to measure binding affinities

  • Employ fluorescence spectroscopy to assess cofactor binding

  • Perform circular dichroism to detect conformational changes upon cofactor binding

• Structure-function relationship:

  • Identify key residues involved in cofactor binding through structural prediction

  • Create site-directed mutants to alter cofactor specificity

  • Compare with related enzymes, like GlpD, which uses FAD or NAD+ as cofactors

How does the interaction between gpsA and other glycerol-3-phosphate dehydrogenases like GlpD affect metabolic flux in Mannheimia succiniciproducens?

The interaction between gpsA and GlpD creates a metabolic node that regulates the interconversion of DHAP and G3P, affecting carbon flow between glycolysis and lipid metabolism. In B. burgdorferi, a glpD deletion restored the wild-type phenotype to a gpsA mutant, suggesting a complex regulatory relationship .

To investigate this interaction in M. succiniciproducens:

• Generate and characterize mutant strains:

  • Create single mutants: ΔgpsA and ΔglpD

  • Create double mutant: ΔgpsA/ΔglpD

  • Develop complemented strains: ΔgpsA/gpsA+ and ΔglpD/glpD+

  • Compare growth characteristics under various conditions

• Enzyme activity measurements:

  • Measure activities of both enzymes in wild-type and mutant strains

  • Determine the effect of one enzyme's absence on the activity of the other

  • Assess enzyme activities under different growth conditions

• Metabolic profiling:

  • Quantify key metabolites in all strains:

• Flux analysis:

  • Perform 13C-metabolic flux analysis using labeled glucose

  • Map carbon flow through central metabolism in each strain

  • Identify compensatory pathways activated in mutant strains

• Stress response experiments:

  • Test survival under nutrient stress, similar to B. burgdorferi studies

  • Examine if glycerol becomes bactericidal to certain strains under stress conditions, as observed in B. burgdorferi

  • Investigate morphological changes in mutant strains under stress

What are the structural differences between Mannheimia succiniciproducens gpsA and similar enzymes in other organisms?

Understanding the structural uniqueness of M. succiniciproducens gpsA compared to homologs in other organisms can provide insights for protein engineering and metabolic optimization. A comprehensive structural biology approach includes:

• Sequence analysis and phylogeny:

  • Perform multiple sequence alignment of gpsA proteins from diverse bacteria

  • Generate phylogenetic trees to understand evolutionary relationships

  • Identify conserved domains and M. succiniciproducens-specific residues

• Structural prediction and modeling:

  • Generate homology models using crystal structures of related enzymes

  • Validate models using molecular dynamics simulations

  • Focus on active site, cofactor binding regions, and oligomerization interfaces

• Comparative structural analysis:

  • Compare predicted/determined structure with characterized gpsA enzymes:

• Experimental structure determination:

  • Express and purify M. succiniciproducens gpsA for structural studies

  • Attempt crystallization for X-ray crystallography

  • Use cryo-EM for larger assemblies or complexes

  • Employ NMR for dynamic regions or smaller domains

• Structure-guided functional analysis:

  • Create chimeric proteins exchanging domains between M. succiniciproducens gpsA and other homologs

  • Design site-directed mutants targeting predicted structural differences

  • Assess how structural features correlate with enzyme kinetics and metabolic function

How can we engineer Mannheimia succiniciproducens gpsA to enhance succinic acid production?

Metabolic engineering of gpsA can potentially optimize succinic acid production in M. succiniciproducens. Based on successful approaches with other enzymes like malate dehydrogenase , a comprehensive engineering strategy includes:

• Protein engineering approaches:

  • Rational design based on structural information:

    • Modify cofactor preference to optimize NADH utilization

    • Alter substrate binding site for improved catalytic efficiency

    • Engineer allosteric regulation sites to reduce feedback inhibition

  • Directed evolution:

    • Develop a high-throughput screening system for succinic acid production

    • Create mutant libraries using error-prone PCR or DNA shuffling

    • Screen for variants with improved properties under industrial conditions

• Expression optimization:

  • Manipulate promoter strength to achieve optimal expression levels

  • Design synthetic ribosome binding sites for translation efficiency

  • Implement inducible systems for controlled expression during different fermentation phases

• Pathway integration:

  • Coordinate gpsA engineering with other key enzymes in the pathway

  • Similar to the approach with malate dehydrogenase (MDH) where introducing Corynebacterium glutamicum MDH into M. succiniciproducens enhanced succinic acid production

  • Consider the following comparison from search results:

• Metabolic context optimization:

  • Combine gpsA engineering with deletion of competing pathways (ldhA, pflB, pta, ackA)

  • Balance gpsA activity with GlpD to optimize the glycerol-3-phosphate node

  • Implement fed-batch fermentation strategies with the engineered strain

What is the impact of gpsA knockout on the metabolome of Mannheimia succiniciproducens?

A comprehensive metabolomics approach is essential to understand how gpsA deletion affects the metabolic network of M. succiniciproducens. Based on effects observed in other organisms like B. burgdorferi , the following methodology is recommended:

• Strain development and verification:

  • Generate a clean gpsA deletion mutant using homologous recombination

  • Confirm deletion by PCR, sequencing, and enzyme activity assays

  • Create a complemented strain to verify phenotypes are due to gpsA deletion

• Metabolite extraction and analysis:

  • Grow wild-type and ΔgpsA strains under identical conditions

  • Extract metabolites using optimized protocols for bacterial samples

  • Analyze using multiple platforms:

    • Targeted LC-MS/MS for central carbon metabolites

    • Untargeted GC-MS for broader metabolome coverage

    • NMR for structural confirmation of key metabolites

• Comprehensive metabolic profiling:

  • Compare key metabolite levels between wild-type and ΔgpsA:

• Flux analysis:

  • Conduct 13C-metabolic flux analysis using labeled glucose

  • Compare flux distributions between wild-type and ΔgpsA

  • Identify compensatory pathways activated upon gpsA deletion

• Multi-omics integration:

  • Combine metabolomics with transcriptomics and proteomics

  • Identify regulatory responses triggered by metabolic imbalances

  • Develop a model describing how gpsA deletion affects the entire metabolic network

What role does gpsA play in the redox balance of Mannheimia succiniciproducens?

As a NAD(P)H-dependent enzyme, gpsA significantly impacts cellular redox balance. This question requires a methodological approach that directly measures redox parameters and their relationship to gpsA function :

• Physiological implications:

  • Examine morphological changes (like round body formation seen in B. burgdorferi)

  • Test sensitivity to oxidative and reductive stress

  • Assess growth under different carbon sources that may affect redox balance

• Connection to succinic acid production:

  • Analyze how altered redox balance in gpsA mutants affects succinic acid yield

  • Test if artificial manipulation of redox balance can restore production

  • Develop strategies to optimize redox balance for enhanced succinic acid production