KEGG: dvu:DVU1043
STRING: 882.DVU1043
GMP synthase (guaA) catalyzes the ATP-dependent conversion of xanthosine 5'-phosphate (XMP) to guanosine 5'-monophosphate (GMP) using glutamine as an amide donor. In D. vulgaris, as in other bacteria, guaA is a critical enzyme in the guanine nucleotide biosynthetic pathway. According to comparative genomic analyses, guaA works alongside guaB (IMP dehydrogenase) and gmk (guanylate kinase) to facilitate GTP synthesis, which is essential for various cellular processes including protein synthesis, signal transduction, and energy metabolism . The guaA gene appears to be one of the essential components in nucleotide metabolism, particularly relevant for an anaerobic organism like D. vulgaris that must carefully regulate energy utilization.
While specific information about guaA's genomic organization in D. vulgaris isn't explicitly detailed in the current literature, genomic analyses of D. vulgaris Hildenborough have mapped many metabolic genes. The guaA gene is likely part of a purine biosynthesis gene cluster, potentially organized in an operon structure with other nucleotide metabolism genes. Based on comparative genomics with other bacterial species, it may be co-localized with genes involved in purine metabolism, similar to the relationship seen in H. pylori where guaA (HP0409) functions alongside guaB (HP0829) and gmk (HP0321) . A comprehensive genetic characterization study of D. vulgaris has generated genome-wide resources that could help determine the precise genomic context of guaA .
The D. vulgaris GMP synthase likely follows the conserved two-domain architecture found in other bacterial homologs:
N-terminal glutamine amidotransferase (GAT) domain: Responsible for glutamine binding and hydrolysis to release ammonia
C-terminal synthetase domain: Catalyzes the ATP-dependent incorporation of the ammonia into XMP to form GMP
These domains work in a coordinated manner, with the ammonia generated in the GAT domain traveling through an intramolecular tunnel to the synthetase domain where it reacts with XMP. The protein requires ATP and Mg²⁺ as cofactors for activity. While D. vulgaris-specific structural adaptations haven't been fully characterized, as an anaerobe, its GMP synthase may contain unique features that optimize function in low-oxygen environments.
For expressing recombinant D. vulgaris guaA, researchers should consider several expression systems with their respective advantages:
| Expression System | Advantages | Considerations |
|---|---|---|
| E. coli BL21(DE3) | - High yield potential - Well-established protocols - Rapid growth | - Potential folding issues with anaerobic proteins - Codon bias differences |
| E. coli Rosetta | - Supplies rare codons - Better for GC-rich genes | - Slower growth than BL21 - Additional antibiotic selection needed |
| D. vulgaris host | - Native cellular environment - Proper protein folding | - More complex cultivation - Lower yields - Requires specialized anaerobic techniques |
Optimization parameters for E. coli expression include using lower induction temperatures (16-25°C), adding solubility-enhancing fusion tags (His, MBP, GST), and employing anaerobic expression conditions to improve folding. The 70-mer oligonucleotide design approach used for D. vulgaris microarrays provides insight into sequence optimization considerations .
A robust purification protocol for obtaining active recombinant D. vulgaris guaA should include:
Affinity chromatography: Using His-tag or other fusion partners (GST, MBP) as the primary capture step
Ion-exchange chromatography: For removing impurities based on charge differences
Size-exclusion chromatography: As a polishing step to achieve high purity
Key considerations for maintaining enzyme activity during purification:
Perform all steps at 4°C to minimize proteolysis
Include protease inhibitors in lysis buffers
Maintain reducing conditions (5-10 mM DTT or 2-3 mM β-mercaptoethanol) to prevent oxidation of cysteine residues
Consider including stabilizing agents specific for nucleotide-binding proteins (glycerol, low concentrations of substrates)
For D. vulgaris proteins, consider anaerobic purification to maintain native conformation
The purification approach should be validated by activity assays at each step to ensure the enzyme remains functional.
Multiple complementary methods can be employed to assess GMP synthase activity:
| Assay Method | Principle | Advantages | Limitations |
|---|---|---|---|
| Spectrophotometric | Measures absorbance change at 290 nm as XMP converts to GMP | - Direct measurement - Real-time monitoring | - Limited sensitivity - Potential interference |
| Coupled enzyme | Links GMP formation to NADH oxidation via auxiliary enzymes | - Higher sensitivity - Can measure in complex mixtures | - Dependent on coupling enzyme activity - More complex setup |
| HPLC-based | Directly quantifies XMP consumption and GMP production | - Most accurate quantification - Measures both substrate and product | - Endpoint measurement - Requires specialized equipment |
A standard kinetic characterization would determine:
Km values for substrates (XMP, glutamine, ATP)
kcat and catalytic efficiency (kcat/Km)
Effects of pH, temperature, and ionic strength
Potential allosteric regulators (GTP, other nucleotides)
For anaerobic D. vulgaris enzymes, comparing activity under aerobic vs. anaerobic conditions can provide insights into oxygen sensitivity and structural adaptations.
Based on established genetic manipulation techniques for D. vulgaris, researchers can employ several approaches:
Gene deletion via homologous recombination: The most effective method involves:
Construction of a knockout cassette by fusion PCR to delete guaA via double recombination
Electroporation of the cassette with lambda DNA to improve transformation efficiency
Selection with G418 (gentamicin) at 400 μg/ml in LS4D medium, which provides cleaner selection than chloramphenicol
Verification by PCR and Southern analysis
This approach has demonstrated transformation efficiency of 1.25 × 10⁻⁷ in D. vulgaris .
Conditional knockdown alternatives:
Inducible antisense RNA expression
CRISPR interference (CRISPRi) systems adapted for anaerobes
Riboswitch-controlled expression systems
If guaA proves essential (as might be expected for nucleotide metabolism genes), conditional approaches may be necessary. The large-scale genetic characterization of D. vulgaris has identified essential genes using transposon mutagenesis, which could inform the approach .
Multiple techniques can be employed to analyze guaA expression:
Microarray analysis using custom 70-mer oligonucleotide probes:
Design criteria include melting temperature within 5°C of target (82-92°C), absence of secondary binding, no hairpin/dimer formation exceeding 19 kcal/mol stability, and avoidance of high-G+C stretches
This approach was successfully used to analyze D. vulgaris gene expression under different growth conditions
RT-qPCR (Reverse Transcription Quantitative PCR):
More sensitive for specific gene quantification
Requires careful primer design and optimization
Needs stable reference genes for normalization
RNA-Seq:
Provides comprehensive transcriptome analysis
Allows identification of potential antisense transcripts or small RNAs affecting guaA
Enables co-expression network analysis
When analyzing expression data, researchers should account for D. vulgaris growth under anaerobic conditions and potential metal-dependent regulation systems like the Fur regulator described in the literature .
Several complementary approaches can be used to identify and characterize protein-protein interactions:
| Method | Application | Strengths | Limitations |
|---|---|---|---|
| Bacterial two-hybrid | In vivo detection of binary interactions | - Relatively simple setup - Works in bacterial environment | - High false positive/negative rates - Limited to binary interactions |
| Pull-down assays | In vitro verification of direct interactions | - Identifies direct binding partners - Can use purified components | - May not detect weak interactions - Requires recombinant protein |
| Co-immunoprecipitation | Isolation of native protein complexes | - Captures physiologically relevant interactions - Works with endogenous proteins | - Requires specific antibodies - Background binding issues |
| Crosslinking MS | Identification of interaction interfaces | - Maps contact regions - Detects transient interactions | - Complex data analysis - Technical expertise required |
For anaerobic organisms like D. vulgaris, interactions might be oxygen-sensitive, necessitating anaerobic conditions during experimentation. The genome-wide resources developed for D. vulgaris, including transposon mutant libraries, provide valuable tools for validating functional relevance of identified interactions .
GMP synthase (guaA) in D. vulgaris operates at a critical intersection of multiple metabolic pathways:
Purine nucleotide synthesis: Part of the pathway converting IMP → XMP → GMP → GDP → GTP, working with guaB (IMP dehydrogenase) and gmk (guanylate kinase)
Nitrogen metabolism: Utilizes glutamine as nitrogen donor, linking to amino acid metabolism and nitrogen assimilation pathways
Energy metabolism: Requires ATP, connecting purine synthesis to cellular energetics
Pentose phosphate pathway: Provides ribose-5-phosphate precursors for nucleotide synthesis through a series of enzymatic reactions involving rpe, devB, g6pD, tal, and tkt genes
The interconnection with these pathways makes guaA a potential metabolic regulation point. In bacteria, purine nucleotide synthesis is often coordinated with carbon and nitrogen metabolism, responding to nutrient availability and energy status.
While guaA's specific role in D. vulgaris stress response isn't directly addressed in the literature, its function in nucleotide metabolism suggests several potential roles:
Oxidative stress response: Maintenance of nucleotide pools is crucial for DNA repair mechanisms following oxidative damage, particularly relevant for an anaerobe like D. vulgaris
Nutrient limitation: During purine starvation, guaA activity becomes critical for maintaining essential GTP pools
Energy stress: As a GTP-producing pathway component, guaA may influence energy-sensing pathways during metabolic stress
Metal stress response: Given D. vulgaris' metal-dependent metabolism and the presence of metal-responsive regulators like Fur , guaA could be part of metal homeostasis networks
The large-scale genetic characterization study of D. vulgaris identified conditional phenotypes for 1,137 non-essential genes under various stress conditions , providing a framework for investigating guaA's stress-specific functions.
As a sulfate-reducing bacterium, D. vulgaris occupies anaerobic environmental niches with specific metabolic requirements:
Energy efficiency: In anaerobic environments with limited energy availability, efficient nucleotide synthesis through guaA activity is crucial for conserving ATP
Adaptation to microoxic fluctuations: D. vulgaris must maintain metabolic function during occasional oxygen exposure, potentially requiring regulation of nucleotide-dependent stress response mechanisms
Biofilm formation: Nucleotide signaling (involving GTP-derived second messengers) regulates biofilm formation in many bacteria, potentially linking guaA to community behaviors
Interspecies interactions: In microbial communities, D. vulgaris produces acetate and interacts metabolically with partner species, processes that may involve signaling pathways dependent on GTP availability
The genetic and metabolic adaptations of D. vulgaris for its ecological niche, including potential specializations in guaA function or regulation, represent an important area for further research.
Structural biology offers several approaches to gain insights into D. vulgaris guaA:
X-ray crystallography or cryo-EM studies to determine:
Three-dimensional structure of D. vulgaris guaA
Substrate binding sites and catalytic residues
Conformational changes during catalysis
Potential anaerobic adaptations in protein structure
Hydrogen-deuterium exchange mass spectrometry (HDX-MS) to:
Map protein dynamics and flexibility
Identify regions involved in substrate binding
Detect conformational changes upon ligand binding
Molecular dynamics simulations to investigate:
Substrate channeling between domains
Effects of mutations on protein stability and function
Influence of anaerobic conditions on protein dynamics
These approaches would be particularly valuable for understanding potential adaptations in D. vulgaris guaA that optimize function in anaerobic environments compared to aerobic bacterial homologs.
Systems biology approaches can integrate guaA function into a comprehensive understanding of D. vulgaris metabolism:
Genome-scale metabolic modeling:
Incorporation of guaA-catalyzed reactions into metabolic flux models
Simulation of metabolic outcomes under varying guaA activity
Integration with experimental data on growth and metabolite levels
Multi-omics data integration:
Correlation of guaA expression with global transcriptome, proteome, and metabolome data
Identification of co-regulated genes and proteins
Detection of metabolic bottlenecks and regulatory nodes
Flux analysis:
Measurement of metabolic fluxes through purine synthesis pathways using isotope tracers
Determination of how guaA activity influences downstream metabolic fluxes
The large-scale fitness dataset and RB-TnSeq mutant library developed for D. vulgaris provide valuable resources for systems biology approaches, as they can help identify condition-specific roles for guaA and its genetic interactions .
Comparative genomic analyses can reveal evolutionary insights about D. vulgaris guaA:
Sequence conservation analysis:
Identification of highly conserved catalytic residues versus variable regions
Detection of lineage-specific adaptations in sulfate-reducing bacteria
Correlation of sequence features with biochemical properties
Phylogenetic studies:
Reconstruction of evolutionary history of guaA across bacterial lineages
Identification of potential horizontal gene transfer events
Detection of co-evolutionary patterns with interacting proteins
Genomic context analysis:
Comparison of guaA genomic neighborhoods across species
Identification of conserved gene clusters or operons
Detection of regulatory elements that differ between aerobic and anaerobic bacteria