Recombinant Lactobacillus johnsonii N-acetylmuramic acid 6-phosphate etherase (murQ)

What is N-acetylmuramic acid 6-phosphate etherase (murQ) and what is its role in bacterial cell wall metabolism?

N-acetylmuramic acid 6-phosphate etherase (murQ) is an enzyme with systematic name (R)-lactate hydro-lyase that catalyzes the conversion of N-acetylmuramic acid 6-phosphate (MurNAc-6P) to N-acetylglucosamine 6-phosphate (GlcNAc-6P) and lactate. This enzyme plays a crucial role in peptidoglycan recycling, a process in which bacteria import cell wall degradation products and reincorporate them into either peptidoglycan biosynthesis or basic metabolic pathways .

The reaction catalyzed can be represented as:
MurNAc-6P → GlcNAc-6P + (R)-lactate

This enzyme functions through a mechanism involving the syn elimination of lactate to generate an alpha,beta-unsaturated aldehyde with (E)-stereochemistry, followed by the syn addition of water to yield the final product . Experimental evidence supporting this mechanism includes:

• Observation of kinetic isotope effects slowing the reaction of [2-(2)H] MurNAc 6-phosphate

• Incorporation of solvent-derived deuterium into C2 of the product

• Incorporation of solvent-derived (18)O isotope into the C3 position of the product, but not the C1 position

How is murQ gene expression regulated in bacteria?

The expression of murQ is primarily regulated by the transcription factor MurR, a member of the RpiR/AlsR family of transcriptional regulators. In Escherichia coli, MurR functions as a specific repressor of the murQP operon. The regulation mechanism follows these key steps:

• MurR binds to two neighboring opposite repeats within the murR-murQ intergenic region

• This binding represses transcription of both murQP and murR itself (auto-regulation)

• MurNAc-6P (the substrate of MurQ) acts as a specific inducer

• MurNAc-6P weakens the binding ability of MurR to the operator DNA, thereby derepressing the expression of murQP

Interestingly, another intermediate of amino sugar metabolism, GlcNAc-6P, can also interact with MurR but with lower binding affinity and weaker DNA-protein interference effects compared to MurNAc-6P .

Why is Lactobacillus johnsonii a suitable host for recombinant MurQ expression?

Lactobacillus johnsonii serves as a suitable host for recombinant MurQ expression for several biological and technical reasons:

• Natural habitat compatibility: L. johnsonii is a commensal bacterium isolated from vaginal and gastrointestinal tracts of vertebrate hosts, including humans, rodents, swine, and poultry . This natural association with mucous membranes makes it an excellent candidate for studying cell wall recycling processes relevant to host-microbe interactions.

• Probiotic potential: L. johnsonii strains have demonstrated various health-promoting properties, including pathogen antagonism, immune response modulation, and epithelial barrier enhancement . These characteristics make it valuable for studying how cell wall recycling enzymes like MurQ might contribute to probiotic effects.

• Strain diversity and adaptability: Various L. johnsonii strains (such as MT4, N6.2, BS15, and 456) have been extensively characterized , providing researchers with options to select strains with specific properties beneficial for MurQ expression.

• Acid resistance: Some L. johnsonii strains demonstrate superior acid resistance compared to other Lactobacillus species , which is advantageous for maintaining viability during experimental procedures.

• Genomic characterization: The genomes of multiple L. johnsonii strains have been sequenced, facilitating genetic manipulation for recombinant protein expression .

How can one optimize the expression and purification of recombinant L. johnsonii MurQ for structural studies?

Optimizing the expression and purification of recombinant L. johnsonii MurQ requires a systematic approach addressing multiple parameters:

Expression System Selection:

• E. coli-based expression: The pET28a expression vector encoding a human rhinovirus 3C (HRV3C) protease cleavage site and an N-terminal His6-tag has been successfully used for expressing similar proteins . This system provides efficient expression and facilitates purification.

• Native expression: Consider expressing MurQ in L. johnsonii itself using inducible promoter systems if maintaining native folding is critical.

Protein Solubility Enhancement:

• Truncation strategy: Design truncated versions of the MurQ gene (similar to T1 and T2 truncations described for MurR ) to improve crystallization properties.

• Fusion tags: Beyond His6-tags, evaluate solubility-enhancing tags such as MBP (maltose-binding protein) or SUMO.

• Co-expression with chaperones: Consider co-expressing with molecular chaperones to improve folding.

Purification Protocol:

• Initial capture: Immobilized metal affinity chromatography (IMAC) using Ni-NTA resin

• Tag removal: HRV3C protease cleavage of the His6-tag

• Secondary purification: Size exclusion chromatography to achieve >95% purity

• Buffer optimization: Screen buffers with varying pH (6.5-8.0), salt concentrations (100-500 mM NaCl), and additives (glycerol, reducing agents)

Quality Control Metrics:

• SDS-PAGE and Western blotting for purity assessment

• Circular dichroism for secondary structure verification

• Dynamic light scattering for monodispersity analysis

• Enzymatic activity assays using synthesized MurNAc-6P substrates

What experimental approaches can be used to analyze the catalytic mechanism of L. johnsonii MurQ compared to E. coli MurQ?

Analyzing the catalytic mechanism of L. johnsonii MurQ compared to E. coli MurQ requires a multi-faceted experimental approach:

1. Sequence and Structural Analysis:

• Perform multiple sequence alignments to identify conserved catalytic residues

• Generate homology models based on existing MurQ structures

• Conduct in silico docking with substrates and intermediates

2. Site-Directed Mutagenesis:

• Target putative catalytic residues identified through sequence comparison

• Create alanine scanning mutants across the active site

• Generate chimeric enzymes containing domains from both L. johnsonii and E. coli MurQ

3. Kinetic Analysis:

• Determine steady-state kinetic parameters (Km, kcat, kcat/Km) for both enzymes

• Perform pH-rate profiles to identify essential ionizable groups

• Measure kinetic isotope effects using deuterated substrates

• Compare temperature dependencies (activation energies)

4. Reaction Intermediate Characterization:

• Use rapid quench techniques to trap and identify reaction intermediates

• Implement NMR spectroscopy to monitor reaction progression in real time

• Employ mass spectrometry to detect transient species

5. Inhibition Studies:

• Test alternate substrates like 3-chloro-3-deoxy-GlcNAc 6-phosphate

• Screen transition state analogs and mechanism-based inhibitors

• Compare inhibition patterns between both enzymes

6. Spectroscopic Analysis:

• Monitor conformational changes during catalysis using fluorescence spectroscopy

• Utilize circular dichroism to detect secondary structure alterations upon substrate binding

• Implement infrared spectroscopy to observe bond formation/breakage

A systematic comparison table should be maintained to document differences:

How does the role of MurQ in L. johnsonii differ from its role in E. coli with respect to cell wall recycling and host interactions?

The role of MurQ in L. johnsonii likely differs from its E. coli counterpart due to distinct ecological niches and host interaction strategies:

Cell Wall Recycling Differences:

E. coli and L. johnsonii exhibit different peptidoglycan recycling strategies reflecting their distinct ecological niches:

• Regulatory mechanisms: While E. coli uses MurR as a repressor of murQP expression , L. johnsonii may employ different regulatory systems adapted to mucosal environments.

• Metabolic integration: E. coli can efficiently incorporate recycled cell wall components into basic metabolic pathways , whereas L. johnsonii may prioritize reincorporation into new peptidoglycan to maintain mucosal adherence.

• Environmental adaptation: L. johnsonii, as a commensal microbe of vertebrate mucosal surfaces, may have evolved its MurQ function to operate optimally at lower pH and in the presence of host mucins .

Host Interaction Implications:

The MurQ-mediated cell wall recycling in L. johnsonii may have evolved specialized functions related to:

• Immune modulation: Cell wall components processed by MurQ in L. johnsonii may generate immunomodulatory molecules that contribute to the anti-inflammatory effects observed with certain L. johnsonii strains .

• Antagonism against pathogens: Efficient recycling of peptidoglycan may provide L. johnsonii with competitive advantages against pathogens like Candida albicans in mucosal environments .

• Adhesion to host tissues: MurQ activity might indirectly affect the expression of surface molecules like elongation factor Tu (EF-Tu), which has been identified as an adhesin-like factor in L. johnsonii .

• Signaling through extracellular vesicles: L. johnsonii produces vesicles with immunomodulatory properties , and MurQ-processed cell wall components may be incorporated into these structures.

Functional Comparison Table:

What are the optimal methods for cloning and expressing the L. johnsonii murQ gene in heterologous systems?

Optimal cloning and expression of L. johnsonii murQ requires careful consideration of several methodological aspects:

Gene Acquisition and Optimization:

• Source DNA isolation:

  • Extract genomic DNA from L. johnsonii using specialized protocols for Gram-positive bacteria

  • Utilize lysozyme (10 mg/ml) and mutanolysin (100 U/ml) treatment prior to standard extraction procedures

  • Alternatively, synthesize the gene with codon optimization based on the target expression host

• Primer design for PCR amplification:

  • Include appropriate restriction sites for directional cloning

  • Add sequences for fusion tags if needed

  • Consider adding a ribosome binding site optimized for the expression host

  • Example forward primer with NdeI site: 5'-GGAATTCCATATGXXXXXXXXXXXXX-3'

  • Example reverse primer with XhoI site: 5'-CCGCTCGAGXXXXXXXXXXXXX-3'

Vector Selection and Cloning Strategy:

• Expression vector options:

  • pET28a with HRV3C protease cleavage site and N-terminal His6-tag (as used in similar studies )

  • pET-SUMO for enhancing solubility

  • pGEX for GST fusion to improve solubility

  • pMal-c2X for MBP fusion if solubility issues persist

• Cloning techniques:

  • Traditional restriction enzyme-based cloning

  • Gibson Assembly for seamless cloning without restriction sites

  • Gateway cloning for flexibility in moving between expression systems

  • Golden Gate assembly for multi-fragment assembly if needed

Expression Host Selection:

• E. coli strains:

  • BL21(DE3) for standard expression

  • Rosetta(DE3) if L. johnsonii codon bias is a concern

  • Origami(DE3) for enhanced disulfide bond formation

  • Arctic Express for expression at lower temperatures

• Alternative hosts:

  • L. lactis for expression in a Gram-positive background

  • B. subtilis for secreted expression

  • P. pastoris for high-yield expression of complex proteins

Expression Optimization Protocol:

• Induction conditions screening:

  • Test IPTG concentrations: 0.1, 0.5, and 1.0 mM

  • Evaluate induction temperatures: 15°C, 25°C, and 37°C

  • Vary induction times: 4, 8, and 16 hours

  • Consider auto-induction media for gradual protein expression

• Verification of expression:

  • SDS-PAGE analysis

  • Western blotting using anti-His antibodies

  • Activity assays to confirm functional expression

Complementation Assay for Functional Verification:

Implement a functional complementation approach similar to that used for murJ :

• Use E. coli strain with murQ deletion or under control of an inducible promoter

• Transform with the recombinant L. johnsonii murQ construct

• Test for growth in the absence of inducer (for repressible native gene)

• Verify complementation through growth curves and metabolite analysis

How can researchers assess the kinetic parameters of recombinant L. johnsonii MurQ and identify potential inhibitors?

Assessing kinetic parameters and identifying inhibitors of recombinant L. johnsonii MurQ requires specialized approaches:

Substrate Preparation and Handling:

• Synthesis of MurNAc-6P substrate:

  • Chemical synthesis from GlcNAc-6P and (R)-lactate

  • Enzymatic synthesis using MurNAc kinase

  • Analytical verification by HPLC, MS, and NMR

• Substrate stability considerations:

  • Prepare fresh substrate solutions daily

  • Store as lyophilized powder at -80°C

  • Verify substrate integrity before each assay run

Kinetic Assay Development:

• Primary assay options:

  • Spectrophotometric assay: Measure lactate release using lactate dehydrogenase coupled assay

  • HPLC-based assay: Direct quantification of substrate consumption and product formation

  • Mass spectrometry: Monitor reaction in real-time with high sensitivity

  • Isothermal titration calorimetry: Measure heat changes during catalysis

• Assay optimization parameters:

  • Buffer composition (pH 5.0-8.5)

  • Temperature range (25-45°C)

  • Ionic strength (0-500 mM NaCl)

  • Divalent cation requirements (Mg²⁺, Mn²⁺, Ca²⁺)

• Data collection for steady-state kinetics:

  • Initial velocity measurements at 8-10 substrate concentrations

  • Range from 0.2 × Km to 5 × Km

  • Minimum of three replicates per substrate concentration

  • Control reactions without enzyme

Kinetic Data Analysis:

• Model fitting approaches:

  • Michaelis-Menten equation for hyperbolic kinetics

  • Hill equation if cooperative behavior is observed

  • Non-linear regression for parameter determination

  • Global fitting for complex kinetic mechanisms

• Parameters to determine:

  • Km (substrate affinity)

  • kcat (catalytic rate constant)

  • kcat/Km (catalytic efficiency)

  • Hill coefficient (if cooperative)

Inhibitor Identification Strategies:

• Rational design approach:

  • Develop transition state analogs based on the syn elimination mechanism

  • Explore 3-substituted GlcNAc-6P derivatives (e.g., 3-chloro-3-deoxy-GlcNAc 6-phosphate)

  • Design lactyl-mimetic compounds

• High-throughput screening setup:

  • Miniaturize assay to 384-well format

  • Develop a fluorescent or colorimetric readout

  • Screen compound libraries at single concentration (10-20 μM)

  • Confirm hits with dose-response curves

• Fragment-based screening:

  • Use thermal shift assays to identify stabilizing fragments

  • Employ STD-NMR to detect weak binders

  • Link/grow fragments to develop higher-affinity inhibitors

Inhibition Mechanism Characterization:

• Inhibition type determination:

  • Competitive: Varies Km, no effect on Vmax

  • Noncompetitive: Affects Vmax, no effect on Km

  • Uncompetitive: Reduces both Km and Vmax proportionally

  • Mixed: Affects both Km and Vmax independently

• Inhibition constant (Ki) determination:

  • Dixon plots for competitive and noncompetitive inhibitors

  • Cornish-Bowden plots for uncompetitive inhibitors

  • Global fitting to appropriate inhibition equations

What approaches can be used to investigate the potential role of L. johnsonii MurQ in host-microbe interactions and probiotic effects?

Investigating L. johnsonii MurQ's role in host-microbe interactions requires a multidisciplinary approach:

Genetic Manipulation Strategies:

• Gene deletion/silencing in L. johnsonii:

  • CRISPR-Cas9 system with appropriate spacers inserted into pCRISPR plasmid

  • Lambda Red recombineering method for genetic manipulation

  • Construction of conditional expression strains using inducible promoters

• Complementation studies:

  • Reintroduction of wild-type and mutant murQ variants

  • Cross-species complementation with E. coli murQ

  • Controlled expression using titratable promoters

In Vitro Host-Microbe Interaction Models:

• Epithelial cell adhesion assays:

  • Compare adhesion of wild-type vs. murQ-deficient L. johnsonii to intestinal epithelial cell lines (Caco-2, HT-29)

  • Quantify using plate counting, flow cytometry, or confocal microscopy

  • Evaluate pH dependence of adhesion (particularly relevant for L. johnsonii)

• Immune cell modulation studies:

  • Co-culture dendritic cells with wild-type vs. murQ-deficient L. johnsonii

  • Measure cytokine production (IL-6, IL-10, TNF-α)

  • Assess dendritic cell maturation markers (CD86, CD40, ICAM-1)

  • Examine NF-κB pathway activation through reporter assays

• Pathogen inhibition experiments:

  • Test antagonism against Candida albicans in co-culture models

  • Measure inhibition zones, metabolic activity (XTT assay), and fungal cell wall integrity

  • Evaluate competition with enteric pathogens (Salmonella, pathogenic E. coli)

In Vivo Experimental Approaches:

• Colonization studies:

  • Oral administration of wild-type vs. murQ-deficient L. johnsonii to mice

  • Monitor colonization efficiency using strain-specific PCR primers

  • Assess persistence in the gastrointestinal tract over time

• Disease models:

  • Evaluate effectiveness in candidiasis models (oropharyngeal or vaginal)

  • Test in colitis models (DSS-induced, TNBS-induced)

  • Assess impact on metabolic disease models (high-fat diet)

• Immune response analysis:

  • Measure mucosal and systemic cytokine profiles

  • Quantify regulatory T cell populations in intestine, mesenteric lymph nodes, and spleen

  • Evaluate intestinal barrier integrity

Analytical Approaches for Mechanism Elucidation:

• Cell wall component analysis:

  • Compare peptidoglycan composition of wild-type vs. murQ-deficient L. johnsonii

  • Analyze released muropeptides during growth using HPLC-MS

  • Examine cell wall turnover rates using isotope labeling

• Metabolomic profiling:

  • Quantify changes in metabolic profiles of host and bacteria

  • Monitor inflammatory metabolites (e.g., 9,10-dihydroxyoctadecenoic acid)

  • Analyze short-chain fatty acid production

• Microbiome impact assessment:

  • Evaluate effects on gut microbiota composition using 16S rRNA sequencing

  • Monitor changes in specific bacterial populations (Bacteroidetes, Firmicutes, Enterobacteriaceae)

  • Assess functional changes through metagenomic/metatranscriptomic analysis

How can researchers address potential contradictions in data when studying L. johnsonii MurQ function across different experimental systems?

Addressing contradictions in L. johnsonii MurQ research requires systematic approaches to data inconsistency:

Identification of Contradiction Sources:

• Experimental system variations:

  • Different L. johnsonii strains may express MurQ variants with distinct properties

  • Expression systems (E. coli vs. native) can affect protein folding and function

  • Buffer conditions, particularly pH, can significantly impact enzyme activity

• Methodological inconsistencies:

  • Substrate preparation methods may introduce variability

  • Detection methods with different sensitivities can lead to apparently conflicting results

  • Temperature variations between labs can affect kinetic measurements

• Biological complexity factors:

  • Host-specific interactions may cause strain-dependent effects

  • Growth phase-dependent expression of MurQ may lead to varying results

  • Co-expression of other enzymes may impact apparent MurQ function

Contradiction Resolution Framework:

• Standardization approach:

  • Develop and share standard operating procedures (SOPs) for key assays

  • Establish reference strains and plasmids for community-wide use

  • Create calibrated substrate preparations to minimize batch-to-batch variation

• Cross-validation strategy:

  • Employ multiple, orthogonal techniques to measure the same parameter

  • Validate findings across different experimental models

  • Confirm key results in independent laboratories

• Systematic parameter variation:

  • Systematically test the effect of each experimental variable

  • Create multifactorial experimental designs to identify interaction effects

  • Develop comprehensive models incorporating context-dependent effects

Practical Tools for Managing Contradictory Data:

• Data integration tables:

What statistical approaches are most appropriate for analyzing the effects of recombinant L. johnsonii MurQ in complex biological systems?

Analyzing recombinant L. johnsonii MurQ effects in complex biological systems requires sophisticated statistical approaches:

Experimental Design Considerations:

• Power analysis for sample size determination:

  • Calculate required sample sizes based on expected effect sizes

  • Account for biological variability in host-microbe interaction studies

  • Consider nested designs to account for batch effects

• Control structure implementation:

  • Include multiple control groups (wild-type, inactive mutant, vector-only)

  • Implement proper randomization to minimize bias

  • Consider blocking designs to control for known sources of variation

Appropriate Statistical Methods:

• For enzyme kinetic data:

  • Non-linear regression for parameter estimation

  • Bootstrap resampling for confidence interval determination

  • Analysis of covariance (ANCOVA) for comparing kinetic parameters across conditions

• For in vitro cell culture experiments:

  • Two-way ANOVA with post-hoc tests for multiple treatment comparisons

  • Mixed-effects models for repeated measures designs

  • Multivariate analyses for correlated outcomes (e.g., multiple cytokines)

• For in vivo studies:

  • Longitudinal data analysis using generalized estimating equations (GEE)

  • Survival analysis for time-to-event data

  • Hierarchical linear models for nested data structures

• For microbiome and multi-omics data:

  • Zero-inflated models for microbiome abundance data

  • PERMANOVA for community composition comparisons

  • Network analysis for interaction patterns

  • Multivariate integration methods for multi-omics data

Advanced Statistical Approaches for Complex Systems:

• Causal inference methods:

  • Directed acyclic graphs (DAGs) to visualize hypothesized causal relationships

  • Propensity score methods to control for confounding

  • Mediation analysis to identify mechanistic pathways

• Machine learning integration:

  • Random forests for identifying important predictors

  • Partial least squares discriminant analysis (PLS-DA) for high-dimensional data

  • Support vector machines for classification tasks

• Meta-analytical approaches:

  • Individual participant data meta-analysis for combining experimental replicates

  • Bayesian hierarchical modeling for incorporating prior knowledge

  • Sensitivity analysis to assess robustness of findings

Data Visualization for Complex Results:

• Effective visualization strategies:

  • Use standardized effect sizes for comparisons across experiments

  • Implement forest plots for meta-analytical data

  • Create heat maps for high-dimensional data patterns

• Uncertainty visualization:

  • Always show confidence intervals or standard errors

  • Use violin plots to display full data distributions

  • Consider Bayesian credible intervals for complex models

Statistical Reporting Guidelines:

• Comprehensive reporting checklist:

  • Clear specification of hypothesis being tested

  • Detailed description of statistical models including assumptions

  • Complete reporting of test statistics, degrees of freedom, and p-values

  • Effect size estimates with confidence intervals

• Research integrity considerations:

  • Pre-registration of analysis plans when possible

  • Transparent reporting of all analyses performed (not just significant results)

  • Code and data sharing for reproducibility

What future research directions might advance our understanding of L. johnsonii MurQ and its applications?

Future research on L. johnsonii MurQ offers several promising directions:

Fundamental Enzyme Science:

• Structural biology:

  • Determine high-resolution crystal structures of L. johnsonii MurQ in apo, substrate-bound, and transition state analog-bound forms

  • Compare with E. coli MurQ to identify structural adaptations to different ecological niches

  • Implement molecular dynamics simulations to understand conformational changes during catalysis

• Evolution and adaptation:

  • Conduct comparative analysis of MurQ across Lactobacillus species to trace evolutionary adaptations

  • Investigate selective pressures that shaped MurQ function in mucosal-associated bacteria

  • Explore horizontal gene transfer events in the evolution of cell wall recycling pathways

• Enzyme engineering:

  • Design MurQ variants with enhanced catalytic efficiency

  • Develop MurQ variants with altered substrate specificity

  • Create thermostable variants for biotechnological applications

Host-Microbe Interaction Research:

• Cell wall recycling in colonization:

  • Investigate the role of MurQ in L. johnsonii persistence in mucosal environments

  • Study how cell wall recycling impacts competitive fitness against pathogens

  • Examine the dynamics of peptidoglycan turnover during host colonization

• Immunomodulatory effects:

  • Characterize how MurQ-processed cell wall components interact with host immune receptors

  • Investigate the role of MurQ in generating immunoactive muropeptides

  • Study the impact of MurQ activity on L. johnsonii phospholipid composition and subsequent dendritic cell responses

• Microbiome interactions:

  • Explore how L. johnsonii MurQ activity influences microbial community composition

  • Investigate cross-feeding of cell wall components within microbial consortia

  • Study the impact of MurQ function on enterococcal overgrowth during Candida infection

Translational Applications:

• Probiotic development:

  • Engineer L. johnsonii strains with optimized MurQ activity for enhanced probiotic properties

  • Develop synbiotic formulations that support MurQ-dependent metabolic activities

  • Investigate strain-specific differences in MurQ function for personalized probiotic applications

• Therapeutic targets:

  • Explore MurQ inhibitors as narrow-spectrum antimicrobials

  • Investigate MurQ-processed compounds as immune adjuvants

  • Develop MurQ-based diagnostic tools for microbial activities

• Biotechnological applications:

  • Utilize MurQ for enzymatic synthesis of modified amino sugars

  • Explore MurQ in bioremediation of glycopeptide antibiotics

  • Develop MurQ-based biosensors for cell wall recycling intermediates

Research Methodology Innovations:

• Advanced analytical techniques:

  • Develop single-molecule techniques to study MurQ catalysis in real-time

  • Implement CRISPR-based tracking of cell wall recycling in live bacteria

  • Create fluorescent sensors for monitoring MurQ activity in vivo

• Systems biology approaches:

  • Construct comprehensive models of cell wall recycling networks

  • Integrate multi-omics data to understand MurQ in the context of global metabolism

  • Develop predictive models for MurQ function across different environmental conditions

• Novel in vitro models:

  • Develop organoid-based systems to study L. johnsonii MurQ in physiologically relevant contexts

  • Create microfluidic systems to monitor real-time interactions between L. johnsonii and host cells

  • Implement organ-on-chip technologies to model complex host-microbe ecosystems