Recombinant Desulfovibrio vulgaris Histidinol-phosphate aminotransferase (hisC)

What is the biochemical function of histidinol-phosphate aminotransferase in D. vulgaris?

Histidinol-phosphate aminotransferase (HisC) is a pyridoxal 5'-phosphate (PLP)-dependent enzyme that catalyzes a critical reversible transamination reaction in the histidine biosynthesis pathway. Specifically, HisC transfers an amino group from histidinol phosphate (His-P) to 2-oxoglutarate (O-Glu) . This reaction represents a key step in amino acid metabolism within D. vulgaris, which is a sulfate-reducing bacterium belonging to the class of anaerobic microorganisms. The enzyme's activity depends on its PLP cofactor, which serves as an electron sink during the transamination process. The reaction produces an imidazole acetol phosphate intermediate in the histidine biosynthesis pathway.

How does D. vulgaris HisC differ structurally from other bacterial aminotransferases?

While specific structural data for D. vulgaris HisC is limited in the provided search results, structural studies of histidinol-phosphate aminotransferases from other bacterial species provide valuable insights that can inform research on the D. vulgaris enzyme. Crystal structures of HisC from Corynebacterium glutamicum have been determined at resolutions of 2.2, 2.1, and 1.8 Å for the apo enzyme, internal PLP aldimine adduct, and pyridoxamine 5-phosphate-enzyme complex, respectively .

Comparative structural analysis with HisC from Thermotoga maritima and Escherichia coli has identified key residues involved in substrate specificity. Particularly important is Tyr21, which forms a hydrogen bond with the phosphate group of His-P, contributing significantly to substrate recognition and discrimination against other potential amino donors like phenylalanine and leucine . Other conserved residues, including Tyr123 and Tyr257, interact with the substrate primarily through van der Waals interactions rather than hydrogen bonding, as evidenced by mutagenesis studies showing only moderate effects on catalytic efficiency when these residues are replaced with phenylalanine .

What genomic context surrounds the hisC gene in D. vulgaris Hildenborough?

The D. vulgaris Hildenborough genome has been well-characterized through multiple genetic studies. While the search results don't explicitly detail the genomic context of hisC, they do provide insights into the genomic organization and manipulation techniques for this organism. D. vulgaris possesses a native plasmid pDV1 that contains a type II restriction modification system, which affects transformation efficiency .

The complete genome sequence of D. vulgaris Hildenborough has revealed numerous genes involved in metabolic pathways, including those for amino acid biosynthesis. The hisC gene would typically be part of the histidine biosynthesis operon, potentially clustered with other his genes. Understanding this genomic context is crucial when designing primers for amplification, expression, or deletion of the hisC gene within recombinant systems.

What are the most effective methods for expressing recombinant D. vulgaris HisC?

Expressing recombinant D. vulgaris HisC requires consideration of several factors specific to this sulfate-reducing bacterium. Based on genetic manipulation techniques developed for D. vulgaris, researchers should consider the following methodological approach:

• Vector Selection: For heterologous expression, vectors containing the origin of replication from the cryptic plasmid pBG1 have shown effectiveness in D. vulgaris . For homologous expression, the development of markerless deletion systems has provided important tools for genetic manipulation.

• Host Strain Optimization: Researchers should consider using host strains with improved transformation efficiency, such as those with deletions in restriction-modification systems. The JW7035 strain (Δupp Δ(hsdR-CHP)) has demonstrated 100-1,000 times greater transformation efficiency compared to wild-type when introducing stable plasmids .

• Promoter Selection: The aph(3′)-II promoter (promoter for the kanamycin resistance gene in Tn5) has been successfully used for constitutive expression in D. vulgaris, as demonstrated in the case of upp gene expression .

• Transformation Protocol: Electroporation has proven effective for introducing DNA into D. vulgaris, though transformation efficiencies vary based on the genetic background of the host strain. The deletion of restriction-modification systems significantly improves transformation efficiency .

How can I develop a markerless genetic system to study hisC function in D. vulgaris?

A markerless genetic system for D. vulgaris has been developed using uracil phosphoribosyltransferase (encoded by upp) as a counterselectable marker. This system can be adapted to study hisC function through the following steps:

• Construction of a Δupp Host Strain: First, create a host strain with the upp gene deleted, which confers resistance to the toxic pyrimidine analog 5-fluorouracil (5-FU). This can be achieved using a suicide plasmid vector containing regions upstream and downstream of upp fused together .

• Creation of a hisC Deletion/Modification Vector: Develop a suicide plasmid containing:

  • Regions flanking the hisC gene

  • The wild-type upp gene expressed constitutively from the aph(3′)-II promoter

  • An antibiotic resistance marker (e.g., spectinomycin)

• Two-Step Integration and Excision Strategy:

  • First recombination: Introduce the plasmid into the Δupp host strain and select for antibiotic resistance to identify strains with integrated plasmid

  • Second recombination: Allow growth without antibiotic selection to permit excision of the plasmid through a second recombination event

  • Selection: Plate on medium containing 5-FU to select for 5-FU resistant colonies that have lost the upp gene through the second recombination

• Verification of Modification: Verify the desired modification using PCR and Southern blot analysis to confirm the genetic changes have occurred as intended .

This approach allows for the creation of in-frame deletions or precise modifications of hisC without leaving antibiotic resistance markers, facilitating multiple sequential genetic manipulations.

What strategies can optimize transformation efficiency when working with recombinant D. vulgaris constructs?

Improving transformation efficiency is critical when working with recombinant D. vulgaris constructs. Based on the research findings, several strategies can significantly enhance transformation outcomes:

• Deletion of Restriction-Modification Systems: Removing the endonuclease (hsdR, DVU1703) of the type I restriction-modification system increases transformation efficiency by 100-1,000 fold compared to wild-type D. vulgaris . This approach addresses a major barrier to introducing foreign DNA into D. vulgaris.

• Plasmid Size Consideration: Smaller plasmids tend to transform more efficiently. For example, pMO719 (5.1 kb) showed improved transformation efficiency compared to larger constructs in some strain backgrounds .

• Host Strain Selection: The host strain JW7035 [Δupp Δ(hsdR-CHP)] demonstrated significantly improved transformation efficiency. Similarly, strain JW801, which has lost the native plasmid pDV1 (containing a type II restriction-modification system), also showed enhanced transformation capabilities .

• Plasmid Origin: Using plasmids containing the origin of replication from the endogenous SRB cryptic plasmid pBG1 improves stability and maintenance in D. vulgaris .

• Optimized Electroporation Protocol: The method of preparing competent cells and electroporation conditions should be optimized specifically for D. vulgaris to maximize DNA uptake.

The following table summarizes comparative transformation efficiencies observed in different D. vulgaris strains:

What residues are critical for substrate specificity in D. vulgaris HisC, and how can they be investigated?

Based on structural studies of histidinol-phosphate aminotransferases, several residues are likely critical for substrate specificity in D. vulgaris HisC. While specific data for D. vulgaris HisC is not directly provided in the search results, comparative analysis with homologous enzymes from other bacteria offers valuable insights:

• Key Residues:

  • Tyrosine residues equivalent to Tyr21 in C. glutamicum HisC likely form hydrogen bonds with the phosphate group of histidinol phosphate (His-P), contributing significantly to substrate recognition and discrimination against other potential amino donors .

  • Residues equivalent to Asn99 in C. glutamicum HisC may be involved in binding the phosphate group of the pyridoxal 5'-phosphate cofactor rather than directly contributing to substrate specificity .

  • Conserved tyrosine residues similar to Tyr123 and Tyr257 in C. glutamicum HisC likely interact with the substrate through van der Waals interactions .

• Investigation Methods:

  • Site-Directed Mutagenesis: Generate point mutations at these conserved residues (e.g., Tyr to Phe substitutions) to assess their contribution to substrate binding and catalysis

  • Kinetic Analysis: Measure enzyme kinetics (kcat, Km, kcat/Km) of wild-type and mutant enzymes with various substrates to quantify the impact of mutations on catalytic efficiency

  • Structural Analysis: Determine crystal structures of D. vulgaris HisC in complex with substrates or substrate analogs to visualize binding interactions

  • Substrate Specificity Profiling: Assess enzyme activity with structurally related compounds to map the substrate recognition landscape

• Expected Outcomes:

  • Mutations in residues forming hydrogen bonds with the phosphate group of His-P would likely show significant decreases in substrate specificity and catalytic efficiency

  • Mutations in residues involved in van der Waals interactions might show more moderate effects on catalytic efficiency

Determining the crystal structure of D. vulgaris HisC in different ligand-bound states requires a systematic approach:

• Protein Production and Purification:

  • Express recombinant HisC with minimal tags to avoid interference with crystallization

  • Implement rigorous purification to achieve >95% purity and monodispersity

  • Use size-exclusion chromatography as a final purification step

  • Concentrate to 5-15 mg/ml for crystallization trials

• Crystallization Strategies:

  • Apo Enzyme: Screen a wide range of crystallization conditions using commercial screens

  • PLP Aldimine Adduct: Ensure sufficient PLP is present during purification or add PLP before crystallization

  • Enzyme-Substrate Complex: Either co-crystallize with substrates/analogs or soak apo crystals with ligands

  • Implement Techniques to Improve Crystal Quality:

    • Seeding from initial crystals

    • Surface entropy reduction mutations

    • Crystallization at different temperatures (4°C, 18°C)

    • Micro-batch, vapor diffusion, and lipidic cubic phase methods

• Data Collection and Processing:

  • Collect high-resolution diffraction data at synchrotron facilities

  • Process data using appropriate software packages (XDS, DIALS, HKL2000)

  • Implement strategies for phase determination:

    • Molecular replacement using structures of HisC from C. glutamicum, E. coli, or T. maritima as search models

    • Experimental phasing using selenomethionine-labeled protein or heavy atom derivatives if molecular replacement fails

• Structure Refinement and Analysis:

  • Refine structures using programs like PHENIX, REFMAC, or BUSTER

  • Validate structures using tools like MolProbity

  • Analyze ligand binding interactions with a focus on:

    • Hydrogen bonding networks

    • van der Waals interactions

    • Conformational changes upon ligand binding

    • Comparison with homologous structures

• Target Resolution and Expected Insights:

  • Aim for resolutions of 2.0 Å or better to clearly resolve side chain conformations and water molecules

  • Resolution of 1.8 Å or better would enable detailed analysis of hydrogen bonding networks

  • Structures in different states can reveal conformational changes during catalysis

The crystal structures of HisC from C. glutamicum at resolutions of 2.2, 2.1, and 1.8 Å for different states provide precedent for successful crystallization of this enzyme family .

How can D. vulgaris HisC be engineered to accept non-native substrates for biocatalytic applications?

Engineering D. vulgaris HisC for expanded substrate specificity requires a rational design approach informed by structural and functional data:

• Substrate Specificity Analysis:

  • Determine baseline activity of wild-type enzyme with various amino donors and acceptors

  • Identify key residues that interact with the phosphate group of His-P and the imidazole moiety

  • The Tyr21Phe mutation in C. glutamicum HisC affected discrimination against other amino donors like phenylalanine and leucine, suggesting analogous residues in D. vulgaris HisC could be targets for engineering expanded specificity

• Rational Design Strategies:

  • Active Site Redesign: Modify residues that form hydrogen bonds with the phosphate group to accommodate different functional groups

  • Substrate Binding Pocket Expansion: Introduce mutations that increase the size of the binding pocket to accommodate bulkier substrates

  • Second-Shell Mutations: Modify residues that influence the orientation and dynamics of direct substrate-binding residues

• Directed Evolution Approaches:

  • Develop high-throughput screening assays for aminotransferase activity

  • Create libraries through error-prone PCR, DNA shuffling, or focused mutagenesis

  • Implement iterative rounds of selection with gradually increasing selective pressure

• Computational Design Methods:

  • Use computational tools like Rosetta or YASARA to predict the effect of mutations

  • Implement molecular dynamics simulations to assess protein dynamics and substrate interactions

  • Apply machine learning approaches trained on aminotransferase datasets to guide rational design

• Validation and Characterization:

  • Determine kinetic parameters for engineered variants with target non-native substrates

  • Solve crystal structures of successful variants to understand the structural basis of expanded specificity

  • Assess stability and expression levels of engineered variants

Expected changes in substrate preference can be presented in a comparison table:

What role might D. vulgaris HisC play in the pathogenesis of ulcerative colitis, and how can this be investigated?

Recent research has implicated Desulfovibrio species in inflammatory conditions like ulcerative colitis (UC), suggesting potential roles for D. vulgaris enzymes, including HisC, in this context:

• Current Evidence of D. vulgaris in UC:

  • Desulfovibrio, an inflammation-promoting flagellated bacteria, has been found to be increased in UC patients

  • The overgrowth of Desulfovibrio genus has been observed in the crypt mucous gel of UC patients

  • Desulfovibrio vulgaris flagellin (DVF) has been shown to interact with leucine-rich repeat containing 19 (LRRC19) and exacerbate colitis

  • High-fat diet (HFD) feeding has been associated with increased Desulfovibrio levels, suggesting a potential link to diet-induced colitis

• Hypothesized Roles of HisC:

  • HisC may contribute to bacterial fitness in the gut environment by enabling histidine biosynthesis

  • Histidine metabolism could potentially influence production of inflammatory mediators

  • HisC might be involved in adaptation to the nutrient-limited environment of the inflamed gut

• Methodological Approaches to Investigation:

  • Gene Deletion Studies: Create D. vulgaris ΔhisC mutants using the markerless deletion system and assess colonization capacity and inflammatory potential in animal models

  • Transcriptomic Analysis: Evaluate hisC expression levels in D. vulgaris isolated from UC patients versus healthy controls

  • Metabolomic Studies: Analyze histidine and related metabolites in gut samples from UC patients with high versus low D. vulgaris abundance

  • Animal Models: Administer recombinant HisC or specific inhibitors in DSS-induced colitis models to evaluate effects on disease progression

• Experimental Design for In Vivo Studies:

  • Mouse Model: Treat mice with dextran sulfate sodium (DSS) to induce colitis with or without administration of D. vulgaris wild-type or ΔhisC strains

  • Parameters to Assess:

    • Clinical scores (weight loss, stool consistency, bleeding)

    • Histological assessment of colonic inflammation

    • Immune cell infiltration and cytokine profiles

    • Microbial community composition

    • D. vulgaris colonization levels

• Potential Therapeutic Implications:

  • If HisC is found to play a significant role in pathogenesis, it could serve as a target for novel therapeutic approaches

  • HisC inhibitors might be developed as selective agents against D. vulgaris in the gut microbiome

How can systems biology approaches be used to understand the role of HisC in D. vulgaris metabolism during environmental stress?

Systems biology offers powerful approaches to elucidate the role of HisC in D. vulgaris metabolism under various stress conditions:

• Multi-omics Integration Strategy:

  • Transcriptomics: Analyze hisC expression patterns under different environmental stressors (oxygen exposure, nutrient limitation, heavy metals, etc.)

  • Proteomics: Quantify HisC protein levels and post-translational modifications under stress conditions

  • Metabolomics: Track histidine and related metabolite fluctuations in response to environmental perturbations

  • Fluxomics: Use isotope labeling to determine carbon and nitrogen flux through the histidine biosynthesis pathway

• Network Analysis Approaches:

  • Construct gene regulatory networks to identify factors controlling hisC expression

  • Develop protein-protein interaction networks to discover functional associations of HisC

  • Create metabolic models to predict the system-wide effects of HisC activity changes

  • Use statistical approaches to identify correlations between hisC expression and other cellular processes

• Genome-Scale Metabolic Modeling:

  • Incorporate HisC reactions into genome-scale metabolic models of D. vulgaris

  • Perform flux balance analysis to predict the importance of HisC under different conditions

  • Simulate gene deletion effects (in silico knockout) to predict the systemic impact of hisC loss

  • Integrate experimental data to refine and validate models

• Experimental Validation Approaches:

  • Generate D. vulgaris strains with controlled hisC expression levels (e.g., using inducible promoters)

  • Perform competition experiments between wild-type and hisC mutants under stress conditions

  • Use ChIP-seq to identify transcription factors regulating hisC expression

  • Implement CRISPR interference (CRISPRi) for dynamic modulation of hisC expression

• Data Visualization and Integration:

  • Develop interactive visualizations of metabolic pathways highlighting HisC's position and connections

  • Create stress-response maps showing the temporal dynamics of HisC activity

  • Design predictive models of D. vulgaris adaptation to environmental changes based on HisC function

This systems approach can reveal whether HisC serves as a metabolic hub or stress response element in D. vulgaris, potentially identifying unexpected roles beyond its canonical function in histidine biosynthesis.

What are the common challenges in purifying active recombinant D. vulgaris HisC and how can they be addressed?

Purifying active recombinant D. vulgaris HisC presents several challenges that require systematic troubleshooting:

• Protein Solubility Issues:

  • Challenge: Expression in E. coli often leads to inclusion body formation for proteins from anaerobic organisms

  • Solutions:

    • Lower induction temperature (16-20°C)

    • Use solubility-enhancing fusion tags (SUMO, MBP, Thioredoxin)

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

    • Attempt expression in anaerobic conditions to mimic native environment

    • Optimize induction conditions (lower IPTG concentration, slower induction)

• Cofactor Retention:

  • Challenge: PLP cofactor may dissociate during purification

  • Solutions:

    • Add PLP (50-100 μM) to all purification buffers

    • Monitor PLP binding spectroscopically (characteristic absorption at ~420 nm)

    • Dialyze protein with excess PLP followed by removal of unbound cofactor

    • Reconstitute with PLP if necessary before activity assays

• Oxidative Sensitivity:

  • Challenge: Proteins from anaerobic organisms like D. vulgaris may be sensitive to oxidation

  • Solutions:

    • Include reducing agents (DTT, β-mercaptoethanol, or TCEP) in all buffers

    • Perform purification under anaerobic conditions when possible

    • Add oxygen scavengers to buffer systems

    • Avoid freeze-thaw cycles that can introduce oxygen

• Protein Stability Issues:

  • Challenge: Recombinant HisC may show limited stability in standard buffer conditions

  • Solutions:

    • Optimize buffer composition through thermal shift assays

    • Test stabilizing additives (glycerol, arginine, trehalose)

    • Determine and maintain optimal pH range

    • Consider buffer components that mimic the natural environment of D. vulgaris

• Low Expression Yield:

  • Challenge: Expression levels may be insufficient for structural or biochemical studies

  • Solutions:

    • Optimize codon usage for expression host

    • Test different expression vectors and promoter systems

    • Consider homologous expression in D. vulgaris using the genetic tools described in the literature

    • Scale up culture volume for batch purification

• Practical Troubleshooting Protocol:

  • Implement systematic variant screening (expression temperature, induction time, host strain)

  • Monitor protein at each purification step by activity assays and SDS-PAGE

  • Validate proper folding using circular dichroism or thermal shift assays

  • Confirm identity and integrity by mass spectrometry

How can I develop specific and sensitive assays to measure D. vulgaris HisC activity in complex biological samples?

Developing assays for D. vulgaris HisC activity in complex samples requires addressing specificity, sensitivity, and matrix effects:

• Spectrophotometric Coupled Enzyme Assays:

  • Principle: Couple the transamination reaction to a secondary enzyme reaction that produces a spectrophotometric signal

  • Implementation:

    • Link to glutamate dehydrogenase activity which reduces NAD+ to NADH (monitored at 340 nm)

    • Design controls to account for background aminotransferase activities in complex samples

    • Optimize enzyme concentrations and reaction conditions for linearity

  • Sensitivity Enhancement: Implement fluorescent NAD(P)H detection methods for increased sensitivity

• High-Performance Liquid Chromatography (HPLC) Assays:

  • Principle: Direct quantification of substrate consumption and product formation

  • Implementation:

    • Develop HPLC methods to separate and quantify histidinol phosphate, imidazole acetol phosphate, and amino acid partners

    • Implement pre-column derivatization (e.g., OPA, PITC, AQC) for improved detection

    • Use internal standards to account for sample matrix effects

  • Application to Complex Samples: Sample clean-up procedures (protein precipitation, solid-phase extraction) before analysis

• Mass Spectrometry-Based Assays:

  • Principle: Direct and highly specific detection of substrates and products

  • Implementation:

    • Develop multiple reaction monitoring (MRM) methods for target metabolites

    • Use isotopically labeled standards for accurate quantification

    • Implement nanoLC-MS for enhanced sensitivity

  • Advantages: High specificity, ability to distinguish isomers, lower detection limits

• Activity-Based Protein Profiling:

  • Principle: Use of substrate analogs that covalently label active HisC

  • Implementation:

    • Design PLP-reactive probes that specifically target aminotransferases

    • Visualize labeled enzymes by fluorescence or detect by Western blotting

    • Extract labeled proteins for mass spectrometry identification

  • Application: Enables activity measurements in situ without protein purification

• Immunological Methods for HisC Quantification:

  • Principle: Use of specific antibodies to quantify HisC protein

  • Implementation:

    • Develop and validate antibodies against D. vulgaris HisC

    • Establish ELISA or Western blot protocols optimized for complex samples

    • Correlate protein levels with activity measurements

  • Limitations: Measures protein abundance rather than activity

• Data Analysis Framework:

  • Implement standard curves with appropriate ranges for expected activity levels

  • Develop normalization strategies for different sample types

  • Establish statistical approaches to account for matrix effects and variability

These methods can be combined to provide comprehensive assessment of HisC activity in diverse samples ranging from purified enzyme preparations to complex biological matrices like bacterial cultures or environmental samples.

What are the key considerations when interpreting conflicting experimental data about D. vulgaris HisC function?

When faced with conflicting experimental data regarding D. vulgaris HisC function, researchers should implement a systematic approach to interpretation:

• Methodological Differences Evaluation:

  • Enzyme Preparation Variations:

    • Expression systems (E. coli vs. homologous expression in D. vulgaris)

    • Purification methods and protein purity

    • Presence/absence of affinity tags and their potential effects

    • Cofactor saturation levels

  • Assay Condition Discrepancies:

    • Buffer composition, pH, and ionic strength

    • Presence of reducing agents

    • Temperature and incubation times

    • Substrate concentrations and potential inhibitory effects at high concentrations

• Statistical Robustness Assessment:

  • Evaluate sample sizes and replication levels

  • Analyze statistical methods used and their appropriateness

  • Consider significance thresholds and potential p-hacking

  • Implement meta-analysis techniques when multiple datasets are available

• Biological Context Considerations:

  • Environmental Factors:

    • Aerobic versus anaerobic conditions (critical for D. vulgaris proteins)

    • Growth phase of source organisms

    • Nutrient availability effects on enzyme expression and activity

  • Genetic Background:

    • Different strains of D. vulgaris might have variations in HisC

    • Presence of mutations in regulatory genes affecting HisC expression

    • Post-translational modifications influenced by growth conditions

• Technical Validation Framework:

  • Independent Verification Approaches:

    • Confirm key findings using orthogonal methods

    • Engage multiple laboratories for collaborative validation

    • Implement blind testing protocols to minimize bias

  • Controls Evaluation:

    • Assess positive and negative controls used

    • Evaluate the suitability of comparative enzymes used as benchmarks

    • Check for appropriate blanks and background corrections

• Reconciliation Strategies:

  • Develop testable hypotheses that could explain observed discrepancies

  • Design critical experiments specifically addressing contradictions

  • Consider conditional regulatory mechanisms that might explain context-dependent results

  • Build quantitative models incorporating all variables to identify conditions causing divergent results

• Decision-Making Framework for Conflicting Data:

By systematically evaluating conflicting data through these approaches, researchers can identify the most likely explanations for discrepancies and design definitive experiments to resolve uncertainties.