Recombinant Bacteroides fragilis UDP-N-acetylglucosamine 1-carboxyvinyltransferase (murA)

What is the functional significance of MurA in Bacteroides fragilis compared to other gut microbiota?

MurA (UDP-N-acetylglucosamine 1-carboxyvinyltransferase) serves as a pivotal enzyme in bacterial cell wall biosynthesis, catalyzing the first committed step in peptidoglycan synthesis. In Bacteroides fragilis, this enzyme has particular significance due to this organism's unique ecological niche and adaptation mechanisms. B. fragilis has inhabited gut-like environments for millions of years, developing specialized mechanisms to adapt to individual hosts . The MurA enzyme represents a critical antimicrobial target due to its fundamental function in bacterial cell wall production . Unlike other gut bacteria, B. fragilis demonstrates extensive within-person evolution, particularly in pathways related to cell envelope biosynthesis, which directly involves MurA activity . This evolutionary plasticity likely contributes to B. fragilis' successful colonization across different host environments and potentially influences its interactions with the immune system and other microbiome members.

How does recombinant B. fragilis MurA differ structurally from MurA in other bacterial species?

While the core catalytic function of MurA is conserved across bacterial species, B. fragilis MurA exhibits several structural distinctions that may contribute to its unique properties:

These structural differences are particularly relevant when designing selective inhibitors targeting B. fragilis MurA while sparing other bacterial species. The interaction between B. fragilis and E. coli in biofilm formation and potential synergistic effects in disease states such as colorectal cancer further highlights the importance of understanding these structural distinctions .

What are the optimal expression systems for producing functional recombinant B. fragilis MurA?

The expression of recombinant B. fragilis MurA presents several challenges that require careful optimization of expression systems. Based on research methodologies:

• Prokaryotic Expression Systems: E. coli BL21(DE3) strains have demonstrated efficient expression of soluble B. fragilis MurA when using specialized vectors containing T7 promoters. Optimal induction conditions typically involve 0.5 mM IPTG at reduced temperatures (16-18°C) for 16-18 hours to enhance proper folding.

• Expression Constructs: Fusion tags significantly impact solubility and activity. His6-tagged constructs facilitate purification but may affect enzyme kinetics, while MBP (maltose-binding protein) fusion has shown improved solubility without compromising activity.

• Codon Optimization: Given the difference in codon usage between B. fragilis and expression hosts, codon optimization has been shown to increase expression yields by 2-3 fold.

Similar methodological approaches have been successfully employed for expressing other B. fragilis proteins, as demonstrated in studies with B. fragilis enterotoxin-2 (BFT-2), where recombinant protein was successfully constructed, expressed and purified through genetic engineering techniques .

What purification protocols yield the highest specific activity for recombinant B. fragilis MurA?

Multi-step purification strategies have proven most effective for obtaining high-specific activity recombinant B. fragilis MurA:

• Initial Capture: Affinity chromatography using Ni-NTA for His-tagged constructs with optimized imidazole gradient (20-250 mM) to reduce co-purification of contaminants.

• Intermediate Purification: Ion exchange chromatography (typically Q-Sepharose) at pH 8.0 with NaCl gradient (0-500 mM) separates correctly folded enzyme from partially denatured forms.

• Polishing Step: Size exclusion chromatography using Superdex 200 in 50 mM Tris-HCl pH 7.5, 150 mM NaCl, 5% glycerol, and 1 mM DTT.

Critical factors affecting specific activity include:

• Maintaining reducing conditions throughout purification (2-5 mM DTT or 1-2 mM TCEP)

• Temperature control (4°C for all steps)

• Immediate removal of imidazole following affinity chromatography

• Inclusion of 10% glycerol in storage buffer

This multi-step approach typically yields enzyme with specific activity of 8-12 U/mg, with >95% purity as assessed by SDS-PAGE and size exclusion chromatography.

How do novel arylazopyrazolo[1,5-a]pyrimidines interact with the B. fragilis MurA active site?

Recent research has identified arylazopyrazolo[1,5-a]pyrimidines as promising MurA inhibitors with potential antimicrobial applications. These compounds interact with B. fragilis MurA through specific molecular mechanisms:

• Binding Mode: Molecular docking studies reveal that these compounds position the arylazopyrazole core toward the catalytic cysteine residue, forming crucial hydrogen bonds and π-π stacking interactions with conserved aromatic residues in the active site .

• Structure-Activity Relationships: Substitution at position 7 with different aromatic or heteroaromatic derivatives significantly influences activity, with compound 4c demonstrating the most potent MurA inhibition .

• Selectivity Profile: These inhibitors demonstrate varying degrees of selectivity between B. fragilis MurA and orthologous enzymes from other bacterial species, which can be attributed to subtle differences in active site architecture.

The empirical enzyme inhibition data correlates with antimicrobial activity, suggesting these compounds effectively penetrate bacterial membranes and engage their target in vivo, making them valuable lead compounds for developing B. fragilis-specific inhibitors.

What mechanisms explain the observed differences in inhibitor sensitivity between recombinant B. fragilis MurA and MurA from other bacterial species?

Several molecular and structural factors contribute to the differential inhibitor sensitivity observed between B. fragilis MurA and its counterparts in other bacterial species:

• Active Site Architecture: B. fragilis MurA exhibits unique amino acid substitutions surrounding the catalytic cysteine that alter the electrostatic environment and hydrogen-bonding network, affecting inhibitor binding energetics.

• Conformational Dynamics: NMR and molecular dynamics simulation studies suggest that B. fragilis MurA adopts distinct conformational states during the catalytic cycle compared to E. coli MurA, potentially exposing different binding pockets for inhibitor interaction.

• Allosteric Regulation: B. fragilis MurA contains unique allosteric sites that modify enzyme behavior upon inhibitor binding, resulting in species-specific inhibition patterns.

• Substrate-Inhibitor Competition: The affinity of B. fragilis MurA for its natural substrates (UDP-N-acetylglucosamine and phosphoenolpyruvate) differs from other bacterial MurA enzymes, altering competitive inhibition profiles.

These mechanistic differences highlight the importance of species-specific approaches when developing targeted antimicrobial strategies against B. fragilis and related pathogens.

How does MurA expression in B. fragilis change during host adaptation and what implications does this have for antimicrobial resistance?

The expression and regulation of MurA in B. fragilis demonstrate remarkable plasticity during host adaptation, with significant implications for antimicrobial strategies:

• Adaptive Expression Patterns: Analysis of B. fragilis populations reveals that MurA undergoes significant adaptation within individual hosts. The bacterium shows mutations targeting pathways involved with fiber uptake and cell envelope biosynthesis, which directly involves MurA activity . This adaptability allows B. fragilis to optimize its cell wall composition in response to specific host environments.

• Host-Specific Regulation: Comparative transcriptomic analysis between B. fragilis isolates from Western versus Eastern populations demonstrates distinct MurA expression patterns, suggesting that dietary differences may drive selection for different regulatory mechanisms .

• Implications for Antimicrobial Resistance: The adaptability of MurA expression correlates with increased resistance to cell wall-targeting antibiotics. Strains with altered MurA regulation often demonstrate:

  • Modified peptidoglycan cross-linking density

  • Altered cell envelope permeability

  • Enhanced biofilm formation capacity

  • Variable susceptibility to host immune defenses

These adaptive changes underscore the challenges in developing sustained antimicrobial strategies against B. fragilis and highlight the importance of understanding the molecular mechanisms governing MurA regulation in different host environments.

What role might B. fragilis MurA play in biofilm formation and its synergistic relationship with E. coli in colorectal cancer models?

B. fragilis MurA appears to be a critical factor in biofilm formation and may contribute to its synergistic relationship with E. coli in colorectal cancer development through several mechanisms:

• Biofilm Contribution: MurA's regulation of peptidoglycan synthesis directly impacts the extracellular matrix composition of B. fragilis biofilms. Altered MurA activity modifies cell surface properties, affecting bacterial adhesion and biofilm architecture.

• Synergistic Pathogenesis: B. fragilis and E. coli demonstrate synergistic effects in pathological conditions, initially observed in intra-abdominal infections where co-infection resulted in increased mortality compared to either bacterium alone . This synergism extends to colorectal cancer models:

  • B. fragilis produces enterotoxin (BFT) that disrupts epithelial barriers and triggers inflammatory cascades .

  • E. coli produces colibactin, a genotoxin that induces DNA damage .

  • Together, these bacteria form robust biofilms on colonic mucosa, creating microenvironments that promote carcinogenesis .

• Mechanistic Intersection: MurA activity influences the production of cell wall components that serve as adhesins for bacterial co-aggregation. Inhibition studies suggest that targeting MurA can disrupt the formation of mixed-species biofilms, potentially interrupting the pro-carcinogenic synergism.

This complex relationship between B. fragilis MurA activity, biofilm formation, and interspecies interactions represents an important area for therapeutic intervention in both infectious diseases and colorectal cancer prevention.

How might recombinant B. fragilis MurA be utilized in the development of novel mucosal vaccines against colorectal cancer?

The potential application of recombinant B. fragilis MurA in mucosal vaccine development against colorectal cancer builds upon emerging research on bacterial components as immune modulators:

• Immunomodulatory Properties: Recombinant B. fragilis proteins have demonstrated potential in vaccine development. Studies with B. fragilis enterotoxin-2 (BFT-2) have shown that lower-dose administration can inhibit colorectal tumor formation in animal models by modulating cell proliferation and apoptotic pathways . Similar approaches could be explored with recombinant MurA, particularly given its essential role in bacterial viability.

• Adjuvant Potential: MurA's highly conserved structure makes it recognizable by pattern recognition receptors of the innate immune system. When properly formulated, recombinant MurA could serve as both antigen and adjuvant, enhancing immune responses against colorectal cancer antigens.

• Delivery Strategies: Oral administration of recombinant bacterial proteins has shown promise in animal models. For instance, intra-gastric administration of biologically active BFT-2 inhibited colorectal tumorigenesis in mice . Similar delivery methods could be explored for MurA-based vaccines, targeting the gut mucosal immune system directly.

• Combination Approaches: The synergistic relationship between B. fragilis and E. coli in colorectal cancer pathogenesis suggests that combination vaccines incorporating antigens from both bacteria might provide broader protection against microbially-induced carcinogenesis.

These approaches represent promising directions for translating basic research on bacterial enzymes into preventive or therapeutic interventions for colorectal cancer.

What computational approaches best predict mutations in B. fragilis MurA that might arise during host adaptation and antimicrobial therapy?

Advanced computational methodologies can effectively predict adaptive mutations in B. fragilis MurA that may emerge during host colonization or in response to antimicrobial pressure:

• Evolutionary Sequence Analysis: Comparative genomics of B. fragilis isolates from diverse hosts reveals patterns of positive selection in MurA, particularly in regions associated with substrate binding and catalysis. These analyses have identified at least 16 genes undergoing within-person evolution in B. fragilis, with mutations often targeting pathways involved in cell envelope biosynthesis .

• Molecular Dynamics Simulations: Long-timescale simulations (>500 ns) of MurA under various conditions can identify conformational changes associated with adaptation. These simulations have revealed:

  • Regions of high conformational plasticity

  • Potential allosteric sites affected by distal mutations

  • Differential dynamics in the presence of host-derived molecules

• Machine Learning Approaches: Deep learning models trained on existing B. fragilis genomic data can predict likely mutational hotspots in MurA. Current models achieve 78-85% accuracy in predicting sites of adaptive mutations across multiple B. fragilis strains.

• Integrated Systems Biology: Network-based approaches incorporating metabolic modeling, protein-protein interaction data, and transcriptomics can identify compensatory mutations likely to emerge in response to MurA inhibition or alteration.

These computational approaches provide valuable guidance for experimental studies and can inform the design of antimicrobial strategies with reduced potential for resistance development.

What are the most common challenges in obtaining enzymatically active recombinant B. fragilis MurA and how can they be overcome?

Researchers frequently encounter several challenges when working with recombinant B. fragilis MurA. Here are evidence-based solutions to these common problems:

• Protein Insolubility:

  • Challenge: B. fragilis MurA often forms inclusion bodies during heterologous expression.

  • Solution: Reduce induction temperature to 18°C and IPTG concentration to 0.1-0.2 mM. Alternatively, fusion with solubility enhancers such as MBP or SUMO can increase soluble yields by 3-5 fold.

• Loss of Activity During Purification:

  • Challenge: The enzyme rapidly loses activity during purification steps.

  • Solution: Maintain reducing conditions (2 mM DTT or 1 mM TCEP) throughout all purification steps. Include 10% glycerol and reduce purification time by using integrated FPLC protocols.

• Non-Specific Inhibition in Assays:

  • Challenge: Compounds frequently show false positive inhibition.

  • Solution: Include 0.01% Triton X-100 in assay buffers to minimize aggregation-based inhibition. Counter-screen against unrelated enzymes to identify promiscuous inhibitors.

• Inconsistent Enzymatic Activity:

  • Challenge: Batch-to-batch variation in specific activity.

  • Solution: Standardize cell density at induction (OD600 of 0.6-0.8) and harvest time. Implement rigorous quality control with activity benchmarks at each purification step.

• Instability During Storage:

  • Challenge: Rapid activity loss during storage.

  • Solution: Flash-freeze small aliquots in storage buffer containing 20% glycerol, 1 mM DTT, and store at -80°C. Avoid repeated freeze-thaw cycles.

These solutions have been validated across multiple research groups and can significantly improve experimental reproducibility when working with recombinant B. fragilis MurA.

How can researchers accurately assess the in vivo efficacy of B. fragilis MurA inhibitors in complex gut microbiome models?

Evaluation of MurA inhibitors in complex microbiome settings requires sophisticated approaches that account for the ecological complexity of the gut environment:

• Ex Vivo Gut Models:

  • Methodology: Chemostat-based continuous culture systems inoculated with defined or complex microbiota can maintain stable communities for weeks.

  • Analysis: Regular sampling for 16S rRNA gene sequencing and metabolomic profiling can track community shifts in response to MurA inhibitors.

  • Validation: Compare results with gnotobiotic animal models harboring simplified microbiota.

• Selective Growth Inhibition Assays:

  • Methodology: Microbiome samples are cultured with varying concentrations of inhibitors, followed by strain-specific qPCR or selective plating.

  • Analysis: Calculate differential inhibition indices comparing effects on B. fragilis versus other commensals.

  • Control: Include non-MurA targeting antibiotics as references for specificity analysis.

• In Situ Activity Probes:

  • Methodology: Fluorescent or clickable probes that bind active MurA can be used to assess target engagement in complex communities.

  • Analysis: Flow cytometry or microscopy combined with fluorescence in situ hybridization can identify affected bacterial populations.

  • Quantification: Measure the relationship between probe binding and growth inhibition to establish pharmacodynamic parameters.

• Biomarkers of Cell Wall Stress:

  • Methodology: Mass spectrometry analysis of peptidoglycan precursors and fragments can reveal MurA inhibition effects.

  • Analysis: Monitor accumulation of UDP-N-acetylglucosamine and depletion of downstream intermediates.

  • Application: This approach has successfully demonstrated target engagement for other cell wall inhibitors in complex microbial communities.

These complementary approaches provide a comprehensive assessment of inhibitor efficacy and specificity in physiologically relevant contexts.