Recombinant Salmonella gallinarum Monofunctional biosynthetic peptidoglycan transglycosylase (mtgA)

What is Monofunctional Biosynthetic Peptidoglycan Transglycosylase (mtgA) and how does it differ from bifunctional enzymes?

Monofunctional biosynthetic peptidoglycan transglycosylase (mtgA) is a specialized glycosyltransferase belonging to the glycosyltransferase family 51 (GT51) that catalyzes the polymerization of lipid II precursors to form glycan strands during bacterial cell wall synthesis. Unlike bifunctional PBPs (Penicillin-Binding Proteins) that possess both glycosyltransferase (GTase) and transpeptidase (TPase) activities, mtgA exclusively performs the glycosyltransferase function, hence the term "monofunctional."

The key differences between mtgA and bifunctional enzymes include:

• Monofunctional mtgA contains only the GTase domain, while bifunctional enzymes like PBP1A and PBP1B contain both GTase and TPase domains

• Bifunctional enzymes can both polymerize glycan strands and cross-link peptide stems, while mtgA only performs the polymerization function

• Bifunctional enzymes typically produce peptidoglycan with cross-links (18-26% for PBP1A and ~50% for PBP1B), whereas mtgA produces uncross-linked glycan strands

What is the significance of Salmonella gallinarum in avian pathology and how does mtgA contribute to its biology?

Salmonella gallinarum is an avian-specific pathogen that causes fowl typhoid, a severe systemic disease in poultry. Recent whole-genome sequencing studies have revealed important aspects of its evolution and adaptation:

• S. gallinarum has undergone a transition from international transmission to regional endemicity, as demonstrated by phylogenetic analysis using a spatiotemporal Bayesian framework

• The pathogen has independently acquired antimicrobial resistance genes through mobile genetic elements (mobilome), primarily plasmids and transposons, resulting in unique resistance profiles among different lineages

• These mobilome-resistome combinations exhibit geographical specificity, reflecting localized endemic processes likely influenced by regional farming practices

As a peptidoglycan synthesis enzyme, mtgA contributes to cell wall integrity and morphology, which are critical for bacterial survival, stress resistance, and host-pathogen interactions. The study of mtgA in S. gallinarum provides insights into bacterial adaptation mechanisms and potential targets for antimicrobial interventions.

What methods are commonly used to express and purify recombinant mtgA from Salmonella gallinarum?

Expression and purification of recombinant S. gallinarum mtgA typically follows these methodological steps:

• Gene cloning:

  • PCR amplification of the mtgA gene from S. gallinarum genomic DNA

  • Insertion into an expression vector with an appropriate affinity tag (His-tag, GST, etc.)

  • Confirmation of correct sequence and reading frame

• Expression optimization:

  • Testing multiple E. coli expression strains (BL21(DE3), Rosetta, C41/C43 for membrane proteins)

  • Optimizing induction conditions (temperature, IPTG concentration, induction time)

  • Small-scale expression tests before scaling up

• Protein extraction:

  • Cell lysis using sonication, French press, or enzymatic methods

  • For membrane-associated proteins like mtgA, inclusion of appropriate detergents (e.g., n-dodecyl-β-D-maltoside, CHAPS) is crucial

• Purification strategy:

  • Affinity chromatography (Ni-NTA for His-tagged proteins)

  • Ion-exchange chromatography to remove contaminants

  • Size-exclusion chromatography for final polishing and buffer exchange

  • On-column refolding may be necessary if the protein forms inclusion bodies

• Quality assessment:

  • SDS-PAGE and Western blotting to verify purity and identity

  • Enzymatic activity assays to confirm functionality

  • Thermal stability analysis to optimize storage conditions

How can the enzymatic activity of recombinant mtgA be assayed in vitro?

Several complementary approaches can be used to assess mtgA glycosyltransferase activity:

• SDS-PAGE-based assay:

  • Incubation of mtgA with radiolabeled lipid II substrate

  • Separation of lipid II and glycan products (up to ~20 disaccharide units) by SDS-PAGE

  • Detection by autoradiography and quantification by densitometric analysis

  • This method enables visualization of the polymerization process but cannot separate higher oligomers

• HPLC analysis of digested products:

  • Reaction of mtgA with radiolabeled lipid II

  • Stopping the reaction by boiling at mild acidic pH (which also hydrolyzes the pyrophosphate moiety)

  • Digestion with muramidase (cellosyl or mutanolysin) to release muropeptides

  • Reduction with sodium borohydride to convert MurNAc to N-acetylmuramitol

  • HPLC analysis using a radioactivity flow-through detector

  • This comprehensive approach allows calculation of average glycan strand length and other structural features

• Continuous fluorescence assays:

  • Using fluorescently labeled lipid II analogs

  • Real-time monitoring of polymerization kinetics

  • Determination of enzyme kinetic parameters (KM, Vmax, kcat)

• Mass spectrometry analysis:

  • Characterization of reaction products by MALDI-TOF or LC-MS/MS

  • Structural confirmation of glycan strands and identification of modifications

How does the structure and function of mtgA compare across different Salmonella serotypes and related bacterial species?

Comparative analysis of mtgA across bacterial species reveals important evolutionary patterns:

• Sequence conservation:

  • Core catalytic residues are typically highly conserved

  • Peripheral regions may show greater variability, reflecting adaptation to specific niches

  • Salmonella serotypes often show high conservation of mtgA sequence, with variations primarily in non-catalytic regions

• Structural variations:

  • Differences in transmembrane domains may affect membrane association

  • Variations in substrate-binding regions can influence specificity and activity

  • Some species have evolved additional regulatory domains

• Functional differences:

  • Variations in glycan strand length preference (e.g., PBP1A produces ~20 disaccharide units, while PBP1B produces >25 units)

  • Differences in activity regulation by protein partners

  • Variable responses to antibiotics and inhibitors

• Evolutionary implications:

  • Salmonella gallinarum shows an evolutionary rate of approximately 0.74 SNPs per year (95% HPD, 0.42-1.06), slower than the average across 22 Salmonella serotypes (1.97 SNPs per year)

  • This relatively slow evolution rate may influence the conservation pattern of essential genes like mtgA

What is the relationship between mtgA activity and antimicrobial resistance in Salmonella gallinarum?

The interaction between mtgA and antimicrobial resistance involves several mechanisms:

• Direct interactions:

  • While mtgA itself is not typically a target for common antibiotics, its function in cell wall synthesis makes it indirectly relevant to β-lactam resistance

  • Changes in mtgA expression or activity could compensate for inhibition of other peptidoglycan synthesis enzymes

• Mobilome-driven resistome adaptation:

  • Salmonella gallinarum has acquired antimicrobial resistance genes through plasmids and transposons, creating unique resistance profiles

  • This mobilome-resistome combination exhibits geographical specificity, supporting a localized endemic process

  • Antimicrobial therapy remains a priority choice against S. gallinarum infections, with increased risk of AMR development for sulfonamides, penicillin, and tetracyclines

• Cell wall alterations:

  • Changes in peptidoglycan structure due to modified mtgA activity could affect cell wall permeability

  • Altered peptidoglycan composition might influence susceptibility to cell wall-targeting antibiotics

• Stress response coordination:

  • mtgA expression may be coordinated with stress response systems activated during antibiotic exposure

  • Integration with broader cellular responses to antimicrobial pressure

How do protein-protein interactions regulate mtgA function in peptidoglycan synthesis?

The activity of peptidoglycan synthesis enzymes is modulated by complex protein-protein interactions:

• Coupling between GTase and TPase activities:

  • In bifunctional enzymes like PBP1B, the GTase activity produces glycan strands oriented to facilitate subsequent transpeptidation

  • This coupling enhances efficiency of peptidoglycan synthesis

• Dimerization effects:

  • PBP1B shows higher activity under conditions favoring dimerization, potentially allowing simultaneous synthesis of two glycan strands that can be cross-linked

  • In contrast, PBP1A functions as a monomer under standard conditions, with distinct GTase and TPase phases

• Interaction with existing peptidoglycan:

  • PBP1A requires pre-oligomerized or high-molecular weight PG as an acceptor for transpeptidase reactions

  • This explains the observation that significant TPase activity occurs only after an initial period of glycan strand production

• Attachment to cell wall:

  • PBP1A can attach approximately 25% of newly synthesized material to existing PG sacculi through transpeptidase reactions

  • This involves monomeric tri- and tetrapeptides in the sacculi acting as acceptors and pentapeptides in new glycan strands acting as donors

What techniques are used to analyze the thermal stability and degradation patterns of purified mtgA?

Thermal analysis techniques provide valuable information about protein stability and degradation mechanisms:

• Thermogravimetric Analysis (TGA):

  • Detects mass loss events during controlled heating

  • Identifies the onset of decomposition temperature

  • Documents critical thresholds such as temperature at 2% and 5% mass loss

  • For biomolecules like proteins, this typically reveals multiple distinct decomposition events

• Modulated TGA (MTGA):

  • Determines activation energy at different mass loss events

  • Provides deeper insights into decomposition mechanisms

  • Allows calculation of activation energy as a function of mass fraction converted

  • This advanced technique can reveal the fundamental thermodynamics of protein unfolding and degradation

• Evolved Gas Analysis (EGA):

  • Combines TGA with spectroscopic techniques (FTIR, MS) to analyze decomposition products

  • Identifies the chemical nature of volatiles released during thermal decomposition

  • Provides compositional information about protein degradation pathways

• Differential Scanning Calorimetry (DSC):

  • Measures heat flow associated with protein unfolding transitions

  • Determines melting temperature (Tm) and enthalpy of unfolding

  • Useful for comparing stability across different buffer conditions or mutant variants

Table 1: Typical Thermal Analysis Parameters for Protein Characterization

How are whole-genome sequencing data analyzed to understand the evolution of mtgA in Salmonella gallinarum?

Whole-genome sequencing analysis of S. gallinarum provides a comprehensive framework for understanding mtgA evolution:

• Population structure analysis:

  • Core genome SNP (cgSNP) distance calculation between strains using SNP-dists

  • Phylogenetic tree construction to visualize genetic relationships

  • Identification of distinct lineages and their geographical distribution

• Evolutionary rate estimation:

  • Bayesian evolutionary analysis using BEAST to estimate mutation rates

  • S. gallinarum shows an evolutionary rate of approximately 0.74 SNPs per year (95% HPD, 0.42-1.06)

  • This is slower than the average across 22 Salmonella serotypes (1.97 SNPs per year)

• Transmission event reconstruction:

  • Using SNP thresholds based on evolutionary rates (e.g., 2 SNPs representing approximately 2 years of evolution)

  • Incorporating geographical information to enhance precision of transmission route speculation

  • Tracking the international spread and subsequent regional endemicity of S. gallinarum

• Gene-specific analysis for mtgA:

  • Assessment of selection pressure (dN/dS ratio)

  • Identification of mutations in regulatory regions affecting expression

  • Structural modeling to predict functional impacts of amino acid substitutions

• Horizontal gene transfer (HGT) frequency calculation:

  • Evaluation of resistome transfer between lineages

  • Similar approaches can be applied to analyze potential transfer events involving mtgA

  • Code for HGT frequency calculation is available at specialized repositories

What statistical approaches are most appropriate for comparing mtgA activity across different experimental conditions?

Robust statistical analysis is essential for meaningful interpretation of experimental data:

• Parametric statistical tests:

  • ANOVA for comparing multiple experimental groups (e.g., different buffer conditions, temperature effects)

  • Student's t-test for pairwise comparisons (e.g., wild-type vs. mutant)

  • Linear regression for analyzing relationships between variables (e.g., substrate concentration vs. activity)

• Non-parametric alternatives:

  • Kruskal-Wallis test as an alternative to ANOVA when normality assumptions are not met

  • Mann-Whitney U test for pairwise comparisons with non-normal data

  • Spearman correlation for analyzing relationships between variables without assuming linearity

• Multiple testing correction:

  • Bonferroni correction for controlling family-wise error rate

  • Benjamini-Hochberg procedure for controlling false discovery rate

  • These corrections are particularly important when analyzing multiple mutants or conditions

• Experimental design considerations:

  • Power analysis to determine appropriate sample sizes

  • Randomization and blinding to minimize bias

  • Inclusion of appropriate positive and negative controls

• Specialized analyses for kinetic data:

  • Michaelis-Menten kinetics for determining KM and Vmax

  • Lineweaver-Burk plots for visualizing kinetic parameters

  • Global fitting approaches for complex kinetic models

Table 2: Comparison of Enzymatic Properties Between Monofunctional and Bifunctional Peptidoglycan Synthases

What are promising strategies for developing inhibitors targeting mtgA in Salmonella gallinarum?

Inhibitor development strategies for mtgA should consider:

• Structure-based approaches:

  • Homology modeling of S. gallinarum mtgA based on crystallized homologs

  • Virtual screening against the active site or allosteric pockets

  • Fragment-based drug design to identify novel chemical scaffolds

• Natural product exploration:

  • Screening of microbial extracts for mtgA inhibitors

  • Investigation of moenomycin derivatives, which are known GTase inhibitors that occupy the donor site of GTases

  • Structure-activity relationship studies to enhance potency and specificity

• Peptidoglycan mimetics:

  • Design of substrate analogs that compete with lipid II

  • Development of transition state mimics that bind with higher affinity

  • Creation of covalent inhibitors targeting conserved active site residues

• Combination approaches:

  • Dual-targeting inhibitors affecting both mtgA and other cell wall synthesis enzymes

  • Synergistic combinations with existing antibiotics

  • Formulations enhancing penetration through the outer membrane

• Species-specific features:

  • Targeting unique structural features of S. gallinarum mtgA

  • Exploiting differences in binding site architecture compared to human gut microbiota

  • Considering the regional adaptation patterns observed in S. gallinarum lineages

How might CRISPR-Cas9 technology enhance our understanding of mtgA function in Salmonella gallinarum?

CRISPR-Cas9 applications for mtgA research include:

• Precise genetic modifications:

  • Generation of clean gene deletions to study loss-of-function effects

  • Introduction of point mutations to analyze structure-function relationships

  • Creation of tagged versions for localization and interaction studies

  • Base editing for subtle modifications without double-strand breaks

• Regulatory studies:

  • Modification of promoter regions to alter expression levels

  • CRISPRi-based knockdown for partial inhibition studies

  • CRISPRa-based overexpression to assess effects of increased mtgA levels

• High-throughput screens:

  • Pooled CRISPR libraries targeting genomic regions affecting mtgA function

  • Identification of synthetic lethal interactions with mtgA mutations

  • Screening for compensatory mutations that restore fitness in mtgA-deficient strains

• In vivo applications:

  • Introduction of mutations directly in S. gallinarum clinical isolates

  • Creation of isogenic mutant series differing only in mtgA sequence

  • Tracking the effects of specific mutations on virulence and antimicrobial resistance

• Technical considerations for S. gallinarum:

  • Optimization of transformation protocols for clinical isolates

  • Development of appropriate selection markers compatible with existing resistance profiles

  • Validation of guide RNA efficacy in the Salmonella genomic context