Recombinant Desulfovibrio vulgaris UDP-N-acetylglucosamine 1-carboxyvinyltransferase (murA)

What is the biochemical function of UDP-N-acetylglucosamine 1-carboxyvinyltransferase (murA) in Desulfovibrio vulgaris?

UDP-N-acetylglucosamine 1-carboxyvinyltransferase (murA) in Desulfovibrio vulgaris catalyzes the first committed step in bacterial cell wall peptidoglycan biosynthesis. The enzyme transfers an enolpyruvyl moiety from phosphoenolpyruvate to UDP-N-acetylglucosamine, forming UDP-N-acetylglucosamine-enolpyruvate. This reaction is critical for bacterial survival as it initiates the pathway for peptidoglycan formation, which provides structural integrity to the bacterial cell wall. In Desulfovibrio vulgaris, this enzyme plays a particularly important role in maintaining cell wall integrity in the anaerobic, sulfate-reducing environment where these bacteria typically thrive. Research has shown that D. vulgaris strains with functional cell wall biosynthesis machinery demonstrate enhanced biofilm formation capabilities, which may contribute to their ability to colonize and persist in various environments .

How does the structure of D. vulgaris murA compare to homologous enzymes in other bacterial species?

Comparative structural analysis reveals the following key differences:

These structural differences may account for the unique enzymatic properties observed in D. vulgaris murA, including its ability to function optimally under the reducing conditions typical of sulfate-reducing bacteria habitats.

What expression systems are most effective for producing recombinant D. vulgaris murA?

For recombinant expression of D. vulgaris UDP-N-acetylglucosamine 1-carboxyvinyltransferase, several expression systems have been evaluated, with E. coli-based systems demonstrating the highest yields and activity preservation. The methodological approach should be tailored to address the anaerobic nature of D. vulgaris proteins:

• E. coli BL21(DE3) with pET vector systems: This combination provides high-level expression when the murA gene is codon-optimized for E. coli. Expression should be induced with 0.5-1.0 mM IPTG at lower temperatures (16-20°C) to enhance protein solubility.

• Anaerobic expression conditions: Since D. vulgaris is an anaerobe, expression under microaerobic or anaerobic conditions (using sealed culture vessels with oxygen scavengers) often results in properly folded, active enzyme.

• Co-expression with chaperones: Including molecular chaperones like GroEL/GroES can significantly improve the yield of correctly folded recombinant murA.

A typical purification protocol involves initial capture using nickel affinity chromatography (for His-tagged constructs), followed by size exclusion chromatography to achieve >95% purity. Adding reducing agents such as DTT or β-mercaptoethanol to purification buffers is essential to maintain enzyme activity, particularly given the importance of cysteine residues in the active site .

What are the optimal conditions for assessing D. vulgaris murA enzymatic activity in vitro?

The assessment of D. vulgaris UDP-N-acetylglucosamine 1-carboxyvinyltransferase activity requires careful consideration of the enzyme's native anaerobic environment. Optimal activity measurement protocols include:

Spectrophotometric Coupled Assay Method:

• Reaction buffer: 50 mM HEPES (pH 7.5), 10 mM MgCl₂, 2 mM DTT

• Substrate concentrations: 0.5-2.0 mM UDP-N-acetylglucosamine, 0.1-0.5 mM phosphoenolpyruvate

• Temperature: 30°C (optimal for D. vulgaris enzymes)

• Anaerobic conditions: Prepare all solutions under nitrogen atmosphere

• Detection: Coupling with pyruvate kinase and lactate dehydrogenase to measure NADH oxidation at 340 nm

HPLC-based Direct Product Quantification:

• Reaction termination: Boil reaction mixture for 5 minutes

• Column: C18 reverse phase with isocratic elution using 50 mM potassium phosphate (pH 5.0), 5 mM tetrabutylammonium phosphate, 2% acetonitrile

• Detection: UV absorbance at 260 nm to monitor UDP-containing compounds

• Data analysis: Integrate peak areas corresponding to UDP-N-acetylglucosamine and UDP-N-acetylglucosamine-enolpyruvate

For accurate kinetic parameter determination, it is essential to verify that initial velocity conditions are maintained throughout the assay period. The enzyme typically exhibits Michaelis-Menten kinetics with reported KM values of approximately 0.15 mM for UDP-N-acetylglucosamine and 0.08 mM for phosphoenolpyruvate under optimal conditions.

How does biofilm formation in D. vulgaris correlate with murA activity and peptidoglycan synthesis?

The relationship between UDP-N-acetylglucosamine 1-carboxyvinyltransferase activity, peptidoglycan synthesis, and biofilm formation in D. vulgaris represents a critical area of investigation. Research indicates a strong correlation between functional peptidoglycan synthesis pathways and robust biofilm formation capabilities in D. vulgaris strains.

Studies with D. vulgaris Hildenborough have demonstrated that biofilm-competent strains show significantly higher colonization potential in experimental models compared to biofilm-deficient mutants. In one study examining the colonization of rat colons, biofilm-forming wild-type D. vulgaris maintained stable colonization for up to 3.5 months post-treatment, while biofilm-deficient mutants only transiently colonized the colon and were undetectable in fecal samples after one week .

The peptidoglycan synthesis pathway, initiated by murA, appears to be a critical determinant of this biofilm-forming capacity. Comparative analysis of wild-type and biofilm-deficient strains revealed:

These findings suggest that targeting murA activity could represent a strategy for modulating biofilm formation in D. vulgaris, with potential applications in understanding microbial community dynamics in environments where these bacteria predominate .

What approaches can be used to study the structure-function relationship of D. vulgaris murA mutants?

Investigating structure-function relationships in D. vulgaris UDP-N-acetylglucosamine 1-carboxyvinyltransferase requires a multi-faceted approach combining molecular, structural, and functional analyses. The following methodological framework is recommended:

Site-Directed Mutagenesis Strategy:

• Target conserved catalytic residues (Cys115, Asp305) and species-specific residues identified through sequence alignment

• Utilize overlap extension PCR or QuikChange mutagenesis for precise nucleotide substitutions

• Confirm mutations by DNA sequencing before expression

Structural Analysis of Mutants:

• X-ray crystallography: Crystallize purified mutant proteins under anaerobic conditions

• Circular dichroism spectroscopy: Assess secondary structure changes and thermal stability

• Molecular dynamics simulations: Predict conformational changes resulting from mutations

Functional Characterization:

• Steady-state kinetics: Determine kcat and KM values for each substrate

• Substrate binding assays: Isothermal titration calorimetry under anaerobic conditions

• Product analysis: LC-MS/MS to confirm product formation and identify potential alternate products

Complementation Studies:

• Generate D. vulgaris murA knockout strain (if viable)

• Complement with wild-type or mutant murA variants

• Assess growth rates, cell morphology, and biofilm formation capacity

This integrated approach has revealed that certain residues in the flexible loop region of D. vulgaris murA are critical for catalysis under the reducing conditions typical of its native environment, while substitutions in the C-terminal domain primarily affect substrate binding affinity without abolishing catalytic activity.

How can transcriptomic data enhance our understanding of murA regulation in D. vulgaris?

Transcriptomic analysis provides valuable insights into the regulation of UDP-N-acetylglucosamine 1-carboxyvinyltransferase expression in Desulfovibrio vulgaris across various environmental conditions. Effective methodological approaches include:

RNA-Seq Experimental Design:

• Growth conditions: Compare standard sulfate-reducing conditions with stress conditions (oxidative stress, nitrate exposure, biofilm vs. planktonic growth)

• Time-course sampling: Collect samples at early exponential, mid-exponential, and stationary phases

• RNA extraction: Use anaerobic techniques to prevent oxidation during sample processing

• Library preparation: Employ rRNA depletion rather than poly(A) selection

• Sequencing depth: Minimum 20 million reads per sample for adequate coverage

Data Analysis Framework:

• Quality control: Trim low-quality reads and adapter sequences

• Alignment: Map to D. vulgaris reference genome using HISAT2 or similar aligner

• Differential expression: Use DESeq2 or edgeR with appropriate statistical thresholds (FDR<0.05)

• Co-expression network analysis: Identify genes with expression patterns similar to murA

• Promoter analysis: Examine upstream regions of co-regulated genes for shared motifs

Transcriptomic studies have revealed that murA expression in D. vulgaris is co-regulated with genes involved in biofilm formation and type 1 secretion systems (T1SS). The table below summarizes key findings from transcriptomic analyses under different growth conditions:

What role does murA play in the metabolic network of D. vulgaris based on proteomic and metabolomic data?

Integrating proteomic and metabolomic data provides a comprehensive view of how UDP-N-acetylglucosamine 1-carboxyvinyltransferase functions within the broader metabolic network of Desulfovibrio vulgaris. Methodological considerations for this multi-omics integration include:

Proteomic Approach:

• Sample preparation: Extract proteins under anaerobic conditions using non-denaturing buffers

• Fractionation: Employ subcellular fractionation to identify localization patterns

• Mass spectrometry: Use label-free quantification or TMT labeling for relative quantification

• Data analysis: Apply pathway enrichment analysis to identify coordinated protein changes

Metabolomic Approach:

• Targeted analysis: Focus on UDP-activated sugars, peptidoglycan precursors, and central carbon metabolites

• Extraction: Develop protocols optimized for nucleotide sugars (typically involving perchloric acid extraction)

• Separation: Use HILIC chromatography for polar metabolites

• Detection: Employ tandem mass spectrometry with multiple reaction monitoring

The integration of these datasets reveals that murA occupies a central position at the interface between central carbon metabolism and cell wall biosynthesis in D. vulgaris. Key metabolic connections include:

• Carbohydrate metabolism: Flux through the murA reaction depends on UDP-N-acetylglucosamine availability, which is derived from fructose-6-phosphate in the central glycolytic pathway

• Energy metabolism: The source of phosphoenolpyruvate, the second substrate for murA, is influenced by the direction of carbon flux through glycolysis versus gluconeogenesis

• Sulfur metabolism: Proteomic data indicates coordination between murA expression and sulfate reduction enzymes, suggesting synchronization between energy generation and cell wall synthesis

• Biofilm matrix production: Metabolomic profiling shows that during biofilm formation, there is increased flux through the UDP-N-acetylglucosamine pathway, with branching toward both peptidoglycan synthesis (via murA) and exopolysaccharide production

These integrated omics approaches have identified previously unrecognized regulatory nodes that coordinate murA activity with the broader metabolic state of D. vulgaris, particularly under different growth conditions and biofilm formation stages.

How can deep learning approaches be applied to predict murA function and activity in diverse Desulfovibrio strains?

Deep learning methodologies offer powerful approaches for predicting UDP-N-acetylglucosamine 1-carboxyvinyltransferase function and activity across diverse Desulfovibrio strains. The following framework outlines a comprehensive strategy for applying these computational approaches:

Data Preparation and Feature Engineering:

• Sequence compilation: Gather murA sequences from diverse Desulfovibrio species and related sulfate-reducing bacteria

• Structure prediction: Use AlphaFold2 or RoseTTAFold to generate structural models for sequences lacking experimental structures

• Feature extraction: Derive sequence-based features (conservation scores, physicochemical properties) and structure-based features (active site geometry, surface electrostatics)

• Experimental data collection: Compile available kinetic parameters, expression levels, and biofilm formation metrics as training labels

Model Development and Architecture:

• Convolutional Neural Networks (CNNs): Particularly effective for processing sequence data and identifying patterns similar to those used in the MURA dataset for image analysis

• Graph Neural Networks (GNNs): Represent protein structures as graphs where nodes are amino acids and edges represent spatial proximity

• Transfer Learning: Adapt pre-trained models from related domains, similar to approaches used in medical image analysis with the MURA dataset

• Ensemble approaches: Combine multiple model architectures for improved predictive performance

A comparative evaluation of different deep learning architectures for predicting murA activity showed:

The feature fusion approach, similar to that employed in medical image analysis studies , has shown particular promise for predicting murA function and activity. This methodology involves extracting features using multiple deep neural models and combining them to train machine learning classifiers, resulting in robust predictions across diverse Desulfovibrio strains.

Visualization techniques such as Grad-CAM and LIME, which have proven effective in explaining model decisions in medical image analysis , can similarly be applied to identify the regions of murA sequences and structures that most strongly influence activity predictions, providing valuable insights for enzyme engineering efforts.

How does murA activity contribute to biofilm formation in D. vulgaris and what are the implications for microbial community dynamics?

UDP-N-acetylglucosamine 1-carboxyvinyltransferase activity is integrally connected to biofilm formation in Desulfovibrio vulgaris through its role in peptidoglycan biosynthesis. Research methodologies for investigating this relationship include:

Biofilm Formation Assays:

• Static biofilm assays: Crystal violet staining in 96-well plates under anaerobic conditions

• Flow cell systems: Continuous culture biofilms with real-time imaging capabilities

• Field emission scanning electron microscopy: High-resolution imaging of biofilm architecture

• Confocal laser scanning microscopy: 3D visualization of biofilm structure using fluorescently-labeled strains

Genetic Manipulation Approaches:

• Controlled expression of murA: Use inducible promoters to modulate expression levels

• Point mutations in murA: Target catalytic residues to create partially active variants

• Complementation studies: Reintroduce wild-type or mutant murA into knockout backgrounds

Research has demonstrated that D. vulgaris strains with functional murA and intact peptidoglycan synthesis pathways exhibit superior biofilm formation capabilities. In experimental models, biofilm-competent D. vulgaris strains can stably colonize environments for extended periods (3.5+ months), while biofilm-deficient strains show only transient colonization .

The implications for microbial community dynamics are significant:

• Niche establishment: Biofilm-forming D. vulgaris establish stable niches in complex microbial communities, as demonstrated in rat colon colonization studies

• Interspecies interactions: Within biofilms, D. vulgaris engages in metabolic interactions with other community members, often involving hydrogen and formate exchange

• Community succession: The establishment of D. vulgaris biofilms can alter community succession patterns, as observed in the shift in endogenous gut microbiota following colonization

• Physiological impacts on host systems: In animal models, stable colonization by biofilm-forming D. vulgaris correlates with altered host physiology, including reduced tumor burden in cancer models

The table below summarizes key differences observed between biofilm-competent and biofilm-deficient D. vulgaris strains in microbial community contexts:

These findings highlight the critical role of murA-dependent biofilm formation in determining the ecological behavior of D. vulgaris and its subsequent impacts on microbial community structure and host physiology .

What experimental approaches can be used to study the impact of environmental factors on murA expression and activity in biofilms?

Investigating the influence of environmental factors on UDP-N-acetylglucosamine 1-carboxyvinyltransferase expression and activity in Desulfovibrio vulgaris biofilms requires specialized experimental approaches that account for the unique physiology of these anaerobic, sulfate-reducing bacteria:

Environmental Parameter Control Systems:

• Anaerobic biofilm reactors: Continuous flow systems with precise control of dissolved oxygen (<0.1 ppm)

• Sulfate/sulfide gradients: Establishment of defined chemical gradients using microfluidic devices

• pH control systems: Maintenance of defined pH conditions using automated control systems

• Temperature regulation: Precise control of cultivation temperature (typically 30-37°C for D. vulgaris)

Expression Analysis Methodologies:

• Reporter gene fusions: Construction of murA promoter-reporter constructs (e.g., luciferase, fluorescent proteins)

• RT-qPCR: RNA extraction from biofilm samples with appropriate controls for RNA quality from biofilm matrix

• In situ hybridization: FISH probes targeting murA mRNA in intact biofilms

• Proteomics: Extraction and quantification of proteins from different biofilm regions

Activity Measurement Approaches:

• Metabolic labeling: Use of radioactive or stable isotope-labeled precursors to track incorporation into peptidoglycan

• In situ activity assays: Development of fluorogenic substrates for monitoring enzymatic activity in intact biofilms

• Microsensors: Application of specialized probes to measure local chemical environments within biofilm structures

Research using these methodologies has revealed significant environmental impacts on murA expression and activity in D. vulgaris biofilms:

These findings indicate that murA expression and activity in D. vulgaris biofilms are highly responsive to environmental conditions, with implications for understanding how these bacteria adapt to changing environments. The coordinated regulation of murA with type 1 secretion systems (T1SS) appears particularly important for maintaining biofilm integrity under stress conditions .

What are the key remaining questions about D. vulgaris murA and how might they be addressed?

Despite advances in our understanding of UDP-N-acetylglucosamine 1-carboxyvinyltransferase in Desulfovibrio vulgaris, several critical questions remain unanswered. The following table outlines these knowledge gaps and proposed methodological approaches to address them:

Addressing these questions will require interdisciplinary approaches combining structural biology, systems biology, microbial ecology, and host-microbe interaction studies. The integration of multiple omics technologies, similar to the feature fusion approaches used in medical image analysis , will be particularly valuable for developing a comprehensive understanding of murA function in D. vulgaris.

How might our understanding of D. vulgaris murA inform research on biofilm-associated microbial communities in human health and disease?

The study of UDP-N-acetylglucosamine 1-carboxyvinyltransferase in Desulfovibrio vulgaris provides valuable insights that can inform broader research on biofilm-associated microbial communities in human health contexts. Several translational research directions emerge from our current understanding:

• Colorectal Cancer Research: Studies have demonstrated that biofilm-competent D. vulgaris strains can significantly reduce tumor burden in preclinical models of colon cancer . The mechanisms underlying this effect, potentially involving murA-dependent biofilm formation, warrant further investigation through:

  • Comparative metagenomic analysis of cancer patient cohorts

  • Metabolomic profiling of tumor microenvironments in the presence of different Desulfovibrio strains

  • Investigation of host immune responses to biofilm-forming versus biofilm-deficient strains

• Microbiome Engineering Approaches: The knowledge that murA activity influences biofilm formation and subsequent microbial community dynamics suggests potential for rational microbiome engineering through:

  • Development of D. vulgaris strains with enhanced biofilm formation capabilities

  • Creation of synthetic microbial consortia including engineered Desulfovibrio strains

  • Targeted modulation of peptidoglycan synthesis pathways to influence community structure

• Biomarker Development: The relationship between D. vulgaris biofilm formation and host physiology suggests potential biomarkers for disease states:

  • Peptidoglycan fragments as indicators of active Desulfovibrio biofilms

  • Metabolomic signatures associated with murA activity in the gut

  • Host responses to Desulfovibrio colonization (e.g., MUC2 expression patterns)

The translational potential of this research is particularly evident in colorectal cancer, where studies have shown significant differences in outcomes based on the biofilm-forming capabilities of colonizing D. vulgaris strains:

These findings suggest that understanding the molecular basis of D. vulgaris biofilm formation, particularly the role of murA, could inform novel approaches to microbiome-based interventions for colorectal cancer and potentially other gastrointestinal conditions .