Recombinant Lactobacillus johnsonii UDP-N-acetylglucosamine 1-carboxyvinyltransferase (murA)

Basic Research Questions

• What is the biological significance of UDP-N-acetylglucosamine 1-carboxyvinyltransferase (MurA) in Lactobacillus johnsonii?

UDP-N-acetylglucosamine 1-carboxyvinyltransferase (MurA) is a critical enzyme in the bacterial cell wall biosynthesis pathway. In L. johnsonii, as in other bacteria, MurA catalyzes the first committed step in peptidoglycan synthesis by transferring an enolpyruvyl group from phosphoenolpyruvate (PEP) to UDP-N-acetylglucosamine (UDPAG) to form UDP-N-acetylglucosamine enolpyruvate . This reaction is essential for the production of UDP-N-acetylmuramate, a key building block of the bacterial cell wall.

The role of MurA in L. johnsonii is particularly interesting because L. johnsonii is a common probiotic bacterium found in the gastrointestinal tracts of various hosts, including humans, mice, dogs, poultry, and pigs . Understanding the function of MurA in L. johnsonii provides insights into the cell wall biosynthesis of this beneficial bacterium, which may relate to its ability to colonize the intestinal tract and interact with host systems.

• How should recombinant L. johnsonii MurA be expressed and purified for research purposes?

Recombinant L. johnsonii MurA can be expressed and purified using established molecular biology techniques. Based on protocols used for similar bacterial proteins, the following methodology is recommended:

Expression System and Conditions:

• Clone the L. johnsonii murA gene into an expression vector such as pET28a, which adds a His-tag for purification

• Transform the recombinant construct into E. coli expression strains (e.g., BL21(DE3) or Rosetta(DE3)pLysS)

• Grow transformed cells in LB medium with appropriate antibiotics to an OD600 of ~0.5-0.6

• Induce protein expression with IPTG at lower temperatures (24°C) to enhance solubility

• For optimal soluble protein expression, use the following conditions:

  • IPTG concentration: 0.2-0.5 mM

  • Induction temperature: 24°C

  • Induction time: 16-22 hours

  • Shaking speed: 130-150 rpm

Purification Protocol:

• Harvest cells by centrifugation (20,000 × g, 20 min, 4°C)

• Resuspend cell pellet in binding buffer (500 mM NaCl, 5% glycerol, 50 mM Tris, 5 mM imidazole, pH 8.0)

• Lyse cells using French press or sonication

• Clarify lysate by centrifugation (35,000 × g, 45 min)

• Purify using Ni²⁺ affinity chromatography:

  • Wash with buffer containing 25 mM imidazole

  • Elute with buffer containing 250 mM imidazole

• Dialyze against storage buffer (10 mM Tris pH 8.0, 2.5% glycerol, 500 mM NaCl, 0.5 mM TCEP)

• Store at -80°C

Protein concentration can be determined using Bradford assay with BSA as a standard.

• What experimental designs are most suitable for studying recombinant L. johnsonii MurA enzyme kinetics?

When studying recombinant L. johnsonii MurA enzyme kinetics, researchers should employ rigorous experimental design principles to ensure valid and reliable results:

Recommended Experimental Design Approach:

• Variable Control:

  • Independent variables: Substrate concentrations (UDP-N-acetylglucosamine and phosphoenolpyruvate), temperature, pH, inhibitor concentrations

  • Dependent variable: Enzyme activity (rate of product formation)

  • Control variables: Buffer composition, ionic strength, enzyme concentration, incubation time

• Systematic Testing Schema:

  • For Km determination: Use at least 7-8 different substrate concentrations (ranging from 0.2×Km to 5×Km)

  • For inhibitor studies: Use multiple inhibitor concentrations with at least three substrate concentrations

  • Include technical replicates (n=3 minimum) for each condition

  • Include appropriate negative controls (no enzyme, no substrate)

• Enzyme Assay Methodology:

  • Monitor reaction progress using spectrophotometric methods (measuring PEP consumption at 232 nm)

  • Alternative: Couple the reaction to subsequent steps and measure NADPH oxidation

  • Measure initial velocities within the linear range of the reaction

• Data Analysis:

  • Use non-linear regression to fit data to Michaelis-Menten equation

  • For inhibitor studies, determine inhibition type using Lineweaver-Burk plots or direct non-linear regression fitting

  • Apply appropriate statistical tests to determine significance of differences between conditions

By following these experimental design principles, researchers can obtain reliable kinetic parameters for L. johnsonii MurA, comparable to those determined for MurA from other bacterial species. This approach minimizes experimental bias and ensures reproducibility of results.

Advanced Research Questions

• How do the kinetic parameters of L. johnsonii MurA compare with those from other bacterial species, and what are the implications for inhibitor development?

The kinetic parameters of MurA enzymes vary across bacterial species, which has important implications for inhibitor development. While specific kinetic data for L. johnsonii MurA is not comprehensively documented in the provided search results, we can draw comparisons with well-characterized MurA enzymes from other bacteria.

Comparative Kinetic Parameters of MurA Enzymes:

*Values for L. johnsonii MurA are inferred based on sequence homology with other bacterial MurA enzymes.

The conservation of key amino acid residues in the active site across different bacterial MurA enzymes suggests that L. johnsonii MurA likely has similar substrate binding properties. Five important amino acid residues are consistently conserved in bacterial MurA enzymes:

• Lys22: Participates in covalent adduct formation with PEP and fosfomycin

• Cys115: Involved in product release and final deprotonation

• Asp305: Involved in product release and final deprotonation

• Asp369 and Leu370: Facilitate interaction with fosfomycin

The presence of a conserved active site cysteine residue in L. johnsonii MurA (analogous to Cys115 in E. coli) suggests that the enzyme would be sensitive to fosfomycin, unlike MurA from species such as Mycobacterium tuberculosis, where a cysteine-to-aspartate substitution confers resistance.

These structural and functional similarities make L. johnsonii MurA a good model for studying bacterial cell wall biosynthesis inhibitors, with implications for developing novel antimicrobials that could potentially target pathogenic bacteria while sparing beneficial probiotic strains like L. johnsonii.

• What methods should be employed to investigate fosfomycin binding and inhibition mechanisms in recombinant L. johnsonii MurA?

Investigating fosfomycin binding and inhibition mechanisms in recombinant L. johnsonii MurA requires a multidisciplinary approach combining enzymatic, structural, and computational methods:

Enzyme Inhibition Assays:

• Dose-Response Analysis:

  • Measure MurA activity with varying fosfomycin concentrations (0.001-10 mM)

  • Determine IC50 values using non-linear regression

  • Compare inhibition under different enzyme:substrate:inhibitor incubation conditions to establish the order of binding

• Time-Dependent Inhibition Studies:

  • Pre-incubate enzyme with fosfomycin before adding substrates

  • Plot residual activity versus pre-incubation time at different inhibitor concentrations

  • Calculate kinact and Ki values to quantify the inactivation process

• Substrate Protection Experiments:

  • Pre-incubate enzyme with varying concentrations of UDP-N-acetylglucosamine before adding fosfomycin

  • Determine if substrate binding prevents inhibitor binding, indicating competitive inhibition

Structural Studies:

• X-ray Crystallography:

  • Crystallize L. johnsonii MurA alone and in complex with fosfomycin

  • Determine structures at resolutions better than 2.5 Å

  • Analyze the binding site and conformational changes upon inhibitor binding

• Homology Modeling and Molecular Docking:

  • Generate a homology model of L. johnsonii MurA based on available MurA structures

  • Perform molecular docking to predict fosfomycin binding mode

  • Superimpose the model with experimentally determined structures of MurA-fosfomycin complexes (e.g., from H. influenzae)

• Site-Directed Mutagenesis:

  • Create mutants of key active site residues (Cys115, Lys22, Asp305, etc.)

  • Evaluate the effect of mutations on fosfomycin binding and inhibition

  • Confirm the role of specific residues in the inhibition mechanism

Computational Methods:

• Molecular Dynamics Simulations:

  • Simulate the interaction between L. johnsonii MurA and fosfomycin in a solvated system

  • Analyze binding stability and dynamic conformational changes

  • Calculate binding free energies using methods like MM-PBSA or FEP

The integration of these methods would provide a comprehensive understanding of fosfomycin binding and inhibition mechanisms in L. johnsonii MurA, potentially revealing species-specific features that could be exploited for selective inhibitor design.

• How can recombinant L. johnsonii MurA be employed as a mucosal vaccine delivery vehicle, and what are the methodological considerations?

Utilizing recombinant L. johnsonii as a mucosal vaccine delivery vehicle represents an innovative approach in vaccine development, with MurA potentially serving as a target antigen or fusion partner for heterologous antigens. Based on the search results, particularly information about L. johnsonii's probiotic properties and use as a vaccine vehicle , the following methodological framework is recommended:

System Design Considerations:

• Antigen Selection and Fusion Strategy:

  • Express MurA as a surface-displayed protein using cell wall anchoring domains

  • Alternatively, integrate epitopes of interest into the MurA sequence at surface-exposed loops

  • Ensure that modifications do not disrupt the enzymatic activity if maintaining active MurA is desired

• Expression Vector Design:

  • Utilize food-grade selection markers instead of antibiotic resistance genes

  • Include strong constitutive promoters or inducible systems compatible with L. johnsonii

  • Incorporate signal sequences for efficient secretion or surface display

Experimental Protocol:

• Recombinant Strain Construction:

  • Transform L. johnsonii with the expression vector using electroporation

  • Select transformants using appropriate selection markers

  • Verify surface expression using immunofluorescence or flow cytometry

• In Vitro Validation:

  • Test survival under simulated gastric conditions (pH 2.0-3.0, pepsin)

  • Assess bile tolerance (0.3% bile salts)

  • Confirm antigen expression stability under stress conditions

  • Evaluate interaction with immune cells (dendritic cells, macrophages)

• In Vivo Immunization Protocol:

  • Animal model: Mice (C57BL/6 recommended based on L. johnsonii prevalence in this strain)

  • Dosage: 10⁹-10¹⁰ CFU per oral dose

  • Schedule: Prime-boost regimen (e.g., days 0, 14, 28)

  • Controls: Wild-type L. johnsonii, phosphate-buffered saline

• Immune Response Assessment:

  • Systemic immunity: Serum IgG (ELISA)

  • Mucosal immunity: Fecal IgA, broncho-alveolar lavage IgA

  • Cellular immunity: T-cell proliferation, cytokine profiling (IL-4, IL-5, IL-13, IFN-γ)

Potential Applications:

The L. johnsonii MurA delivery system could be particularly valuable for:

• Respiratory pathogens (given L. johnsonii's demonstrated protection against respiratory syncytial virus)

• Enteric pathogens (leveraging L. johnsonii's natural gut colonization abilities)

• Oral tolerance induction for autoimmune conditions

Previous studies have demonstrated that oral immunization with recombinant L. johnsonii expressing cell wall-anchored proteins can induce both systemic IgG and local mucosal IgA responses , suggesting this approach could be effective for MurA-based vaccine delivery.

• What genomic analysis approaches are most effective for identifying and comparing MurA genes across Lactobacillus johnsonii strains?

Comprehensive genomic analysis of MurA genes across L. johnsonii strains requires sophisticated bioinformatic approaches to ensure accurate identification, annotation, and comparative analysis. Based on strategies employed in recent genomic studies of L. johnsonii , the following methodological framework is recommended:

Genome Sequencing and Assembly:

• Sequencing Strategy:

  • Employ a hybrid sequencing approach combining:

    • Short-read technology (Illumina) for high accuracy

    • Long-read technology (Oxford Nanopore or PacBio) for resolving repetitive regions

  • Aim for >100× coverage for short reads and >50× for long reads

• Assembly Pipeline:

  • Use hybrid assembly tools (e.g., Unicycler, SPAdes hybrid mode)

  • Perform quality assessment using QUAST and BUSCO

  • Conduct genome circularization and finishing using tools like Circlator

MurA Gene Identification and Annotation:

• Primary Annotation:

  • Use prokaryotic genome annotation pipelines (Prokka, PGAP)

  • Apply specific bacterial gene finding algorithms (Prodigal, GeneMarkS)

  • Search for MurA using specific profile HMMs from TIGRFAM (TIGR00179) or Pfam (PF00275)

• Manual Curation:

  • Verify gene starts using ribosome binding site prediction

  • Examine promoter regions for regulatory elements

  • Check for potential pseudogenes or gene fusions

Comparative Genomic Analysis:

• Structural Analysis:

  • Generate homology models of MurA variants using Swiss-Model or I-TASSER

  • Compare active site architecture and substrate binding pockets

  • Identify strain-specific substitutions that might affect function or inhibitor binding

• Genomic Context Analysis:

  • Examine conservation of gene neighborhoods around murA

  • Identify potential operonic structures and co-regulated genes

  • Compare with other Lactobacillus species to identify horizontal gene transfer events

Example Data Visualization Table:

This comprehensive genomic analysis approach allows researchers to identify strain-specific variations in MurA genes that might correlate with differences in enzyme function, host adaptation, or antibiotic sensitivity across L. johnsonii strains.

• How does the expression of recombinant L. johnsonii MurA in different host systems affect protein yield, activity, and structural integrity?

The choice of expression system for recombinant L. johnsonii MurA significantly impacts protein yield, activity, and structural integrity. This is a critical consideration for researchers studying this enzyme. Based on established protocols for bacterial enzyme expression and the specific information in the search results, the following comprehensive analysis is provided:

Comparative Analysis of Expression Systems for L. johnsonii MurA:

Methodological Considerations for Expression Optimization:

• Codon Optimization:

  • Analyze the codon usage bias of L. johnsonii murA gene

  • Optimize codons for the expression host while maintaining key regulatory elements

  • Consider the impact on mRNA secondary structure and stability

• Fusion Tags and Their Effects:

  • N-terminal His6-tag: Minimal impact on activity, efficient purification

  • C-terminal tags: May interfere with dimerization and activity

  • Cleavable tags: Consider PreScission or TEV protease sites for tag removal

• Solubility Enhancement Strategies:

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

  • Fusion with solubility enhancers (MBP, SUMO, Thioredoxin)

  • Addition of compatible solutes in expression media (glycine betaine, proline)

• Activity Assessment Across Expression Systems:

  • Standard activity assay: Monitor PEP consumption spectrophotometrically

  • Thermal stability comparison using differential scanning fluorimetry

  • Determine specific activity (μmol product formed/min/mg protein)

Structural Integrity Evaluation Protocol:

• Circular Dichroism (CD) Spectroscopy:

  • Far-UV CD (190-250 nm) to assess secondary structure content

  • Thermal denaturation curves to determine stability differences

  • Compare with predicted secondary structure based on homology models

• Size Exclusion Chromatography with Multi-Angle Light Scattering (SEC-MALS):

  • Determine oligomeric state in solution

  • Assess homogeneity of protein preparation

  • Compare apparent molecular weight with theoretical values

• Limited Proteolysis:

  • Digest protein with controlled amounts of trypsin, chymotrypsin, or subtilisin

  • Analyze fragmentation patterns by SDS-PAGE

  • Identify flexible or misfolded regions by mass spectrometry

By systematically evaluating these factors, researchers can optimize the expression of recombinant L. johnsonii MurA to obtain protein preparations with high yield, activity, and structural integrity suitable for detailed enzymatic, structural, and inhibition studies.