Recombinant Chlamydophila caviae UDP-N-acetylglucosamine--N-acetylmuramyl- (pentapeptide) pyrophosphoryl-undecaprenol N-acetylglucosamine transferase (murG)

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Product Specs

Form
Lyophilized powder
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Lead Time
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Notes
Avoid repeated freeze-thaw cycles. Store working aliquots at 4°C for up to one week.
Reconstitution
Centrifuge the vial briefly before opening to collect the contents. Reconstitute the protein in sterile, deionized water to a concentration of 0.1-1.0 mg/mL. We recommend adding 5-50% glycerol (final concentration) and aliquoting for long-term storage at -20°C/-80°C. Our default glycerol concentration is 50% and can serve as a guideline.
Shelf Life
Shelf life depends on several factors, including storage conditions, buffer composition, temperature, and the protein's inherent stability. Generally, liquid formulations have a 6-month shelf life at -20°C/-80°C, while lyophilized forms have a 12-month shelf life at -20°C/-80°C.
Storage Condition
Store at -20°C/-80°C upon receipt; aliquot for multiple uses. Avoid repeated freeze-thaw cycles.
Tag Info
Tag type is determined during manufacturing.
The tag type is determined during production. If you require a specific tag, please inform us, and we will prioritize its development.
Synonyms
murG; CCA_00864; UDP-N-acetylglucosamine--N-acetylmuramyl-(pentapeptide) pyrophosphoryl-undecaprenol N-acetylglucosamine transferase; EC 2.4.1.227; Undecaprenyl-PP-MurNAc-pentapeptide-UDPGlcNAc GlcNAc transferase
Buffer Before Lyophilization
Tris/PBS-based buffer, 6% Trehalose.
Datasheet
Please contact us to get it.
Expression Region
1-358
Protein Length
full length protein
Purity
>85% (SDS-PAGE)
Species
Chlamydophila caviae (strain GPIC)
Target Names
murG
Target Protein Sequence
MVKKINKIAL AVGGSGGHIV PALATREAFC KEGVDVLLLG KGLDNHPNLC DLDVHYKEIP SGLPTVASPV TAIRRMSSLY NGYRKAKKEL CIFDPDVVIG FGSYHSLPVL MAALKKKIPI FLHEQNLIPG RVNKLFSRFA KGVGVSFHPV TKNFRCPSQE VSLPKRAFSA CSPIAERLAS HSPTICVVGG SQGAKTLNDH VPLALVEVAK DYPNMYVHHI AGPKGDVISI QHIYSRGGVS FCVKHFEQDM LNVLLSSDLV ISRAGATILD ELLWAQSPAI LIPYPGAYGH QEENAKFLVY TIGGGSMILE KQLSQEVLTK NILLALDPET IKNRRAALRD YYQNKSSKSF YQFICECL
Uniprot No.

Target Background

Function

Function: Cell wall formation. This enzyme catalyzes the transfer of a GlcNAc subunit to undecaprenyl-pyrophosphoryl-MurNAc-pentapeptide (lipid intermediate I), forming undecaprenyl-pyrophosphoryl-MurNAc-(pentapeptide)GlcNAc (lipid intermediate II).

Database Links
Protein Families
Glycosyltransferase 28 family, MurG subfamily
Subcellular Location
Cell inner membrane; Peripheral membrane protein; Cytoplasmic side.

Q&A

What is the role of murG in Chlamydophila caviae peptidoglycan synthesis?

MurG in C. caviae functions as a critical glycosyltransferase in the peptidoglycan biosynthetic pathway, catalyzing the transfer of N-acetylglucosamine from UDP-GlcNAc to lipid I to form lipid II. This enzymatic reaction represents an essential step in bacterial cell wall assembly. The process is particularly interesting in Chlamydial species, which have been historically characterized as having limited or modified peptidoglycan despite containing the genetic machinery for its synthesis. When studying this enzyme, researchers should consider its role within the context of the unique developmental cycle of C. caviae, which transitions between infectious elementary bodies and replicative reticulate bodies with potentially different cell wall requirements .

How does the genetic organization of murG differ in C. caviae compared to other bacterial species?

The murG gene in C. caviae is organized within a genetic context that reflects the evolutionary adaptations of this obligate intracellular pathogen. Unlike many other bacterial species where cell wall synthesis genes are often clustered in operons, Chlamydial species including C. caviae show a more dispersed arrangement of peptidoglycan synthesis genes throughout the genome. This genomic organization is consistent with the reduced and modified peptidoglycan layer observed in Chlamydial species. When conducting comparative genomic analyses, researchers should employ multiple sequence alignment tools to identify conserved domains and species-specific variations that might influence enzyme function or regulation .

What expression systems are most effective for producing recombinant C. caviae murG?

For optimal expression of recombinant C. caviae murG, E. coli-based expression systems have proven most effective when the following modifications are implemented:

Researchers should note that C. caviae proteins often require codon optimization when expressed in heterologous systems. Additionally, incorporating a cleavable N-terminal tag (such as 6×His-SUMO) rather than a C-terminal tag helps maintain enzymatic activity by preventing interference with the catalytic domain .

How can insertional mutagenesis be optimized for studying murG function in C. caviae?

Optimizing insertional mutagenesis for C. caviae murG requires adaptation of the TargeTron system, which has been successfully applied to other Chlamydial genes. The TargeTron approach utilizing group-II intron insertion has demonstrated efficacy in generating stable, site-specific mutations in C. caviae. For murG studies, researchers should:

  • Retarget the TargeTron vector (such as pDFTT3) specifically for murG by redesigning the intron's target site recognition sequences

  • Replace the selection marker (substituting chloramphenicol acetyltransferase for β-lactamase) to enable appropriate selection

  • Carefully design insertion sites that disrupt function without triggering polar effects on downstream genes

  • Verify insertions using both PCR verification and phenotypic assays to confirm loss of function

This approach offers significant advantages over traditional homologous recombination methods, which have limited efficiency in Chlamydial species. The successful generation of other C. caviae mutants (such as IncA- and SinC-deficient strains) demonstrates the feasibility of this approach for studying murG function .

What are the structural determinants of substrate specificity in C. caviae murG compared to other bacterial homologs?

C. caviae murG substrate specificity is determined by several key structural elements that distinguish it from other bacterial homologs:

Structural ElementFunctionSpecies-Specific Variations
N-terminal DomainMembrane AssociationMore hydrophobic in C. caviae
Interdomain CleftSubstrate BindingDeeper binding pocket in C. caviae
C-terminal DomainCatalysisConserved across species
Loop RegionsConformational ChangesVariable length in different species

When conducting structure-function studies, researchers should employ site-directed mutagenesis targeting these regions to determine their contribution to substrate recognition and catalytic efficiency. Molecular dynamics simulations can complement experimental approaches by revealing the conformational changes occurring during substrate binding and catalysis. Particular attention should be paid to putative binding site residues that may explain any observed differences in substrate preference or catalytic rates between C. caviae murG and other bacterial homologs .

How do host-pathogen interactions influence murG activity during C. caviae infection?

Host-pathogen interactions significantly modulate murG activity during C. caviae infection through multiple regulatory mechanisms:

  • Host innate immune recognition: Pattern recognition receptors (particularly NOD1/2) can detect peptidoglycan intermediates, potentially leading to selective pressure for murG regulation

  • Nutrient availability: The intracellular environment of the inclusion alters substrate availability for murG

  • Developmental cycle coordination: Expression and activity of murG appears coordinated with the transition between elementary bodies and reticulate bodies

  • Host metabolic crosstalk: Evidence suggests that host cell metabolism influences bacterial cell wall synthesis pathways

To study these interactions, researchers should design co-culture systems that allow for simultaneous monitoring of host responses and bacterial murG activity. Time-course experiments are particularly valuable for capturing the dynamic regulation of murG throughout the developmental cycle. When interpreting results, researchers must carefully distinguish between direct effects on murG and indirect effects mediated through other bacterial or host pathways .

What experimental design is most appropriate for assessing murG inhibition in C. caviae?

When designing experiments to assess murG inhibition in C. caviae, researchers should implement a hierarchical experimental design with the following structure:

  • Primary screening assay: In vitro enzymatic assay using purified recombinant C. caviae murG to measure the transfer of radiolabeled GlcNAc from UDP-GlcNAc to lipid I

  • Secondary validation: Cell-based assays measuring peptidoglycan synthesis in C. caviae-infected cell cultures with quantifiable readouts

  • Tertiary confirmation: In vivo models (guinea pig inclusion conjunctivitis) evaluating infection outcomes following inhibitor treatment

This hierarchical approach allows efficient screening while ensuring biological relevance. Critical experimental controls must include:

Control TypePurposeImplementation
Positive ControlValidate assay sensitivityKnown inhibitors (e.g., ramoplanin)
Negative ControlEstablish baselineVehicle-only treatment
Specificity ControlConfirm target selectivityTesting against other glycosyltransferases
Host Toxicity ControlDistinguish direct vs. indirect effectsUninfected cell viability assays

Statistical analysis should employ appropriate methods to quantify dose-response relationships, preferably using non-linear regression models to determine IC50 values with confidence intervals .

What are the optimal methods for analyzing murG enzyme kinetics in Chlamydial species?

Analyzing murG enzyme kinetics in Chlamydial species requires specialized approaches due to the membrane-associated nature of the enzyme and its lipid substrates. The recommended methodology includes:

  • Preparation of detergent-solubilized enzyme or reconstitution in proteoliposomes to maintain native-like environment

  • Development of a continuous spectrophotometric assay that couples UDP release to NADH oxidation

  • Application of surface plasmon resonance for determining binding constants for both substrates

  • Implementation of isothermal titration calorimetry to measure thermodynamic parameters

When conducting kinetic analyses, researchers should:

  • Determine Km and kcat values for both UDP-GlcNAc and lipid I substrates

  • Evaluate product inhibition patterns to establish the reaction mechanism

  • Assess pH and temperature dependence profiles to identify optimal conditions

  • Compare parameters with murG from other bacterial species to identify Chlamydia-specific features

Data analysis should follow rigorous statistical methods, including the fitting of multiple kinetic models (ordered sequential, random sequential, ping-pong) to determine the most appropriate mechanism. Researchers should report complete parameter sets including standard errors rather than isolated values .

How can researchers effectively validate the specificity of antibodies against C. caviae murG?

Validating antibody specificity for C. caviae murG requires a comprehensive approach incorporating multiple techniques:

  • ELISA validation: Test antibody against recombinant murG, related glycosyltransferases, and total C. caviae lysates

  • Western blot analysis: Confirm single band of appropriate molecular weight in C. caviae lysates and absence in murG-knockout strains

  • Immunoprecipitation efficiency: Quantify pull-down efficiency using recombinant standards

  • Immunofluorescence microscopy: Verify expected subcellular localization with appropriate controls

A particularly critical validation step is testing against genetically modified C. caviae strains (murG-deficient or epitope-tagged murG) generated using the TargeTron system. The confirmation of antibody specificity using genetic knockouts represents the gold standard for validation. Researchers should report detailed validation metrics:

Validation MetricAcceptance CriteriaTypical Results for High-Quality Antibodies
Cross-reactivity<5% signal with related enzymes1-3% background signal
Detection limit<10 ng recombinant protein2-5 ng lower limit of detection
Signal-to-noise ratio>10:1 at working concentration15:1 to 30:1 typical ratio
Lot-to-lot variation<15% in standard assays5-10% typical variation

Additionally, researchers should perform epitope mapping to determine the antibody binding site, which aids in interpreting potential functional interference in certain applications .

What are the key controls required when investigating murG function through mutagenesis in C. caviae?

When investigating murG function through mutagenesis in C. caviae, researchers must implement a comprehensive set of controls to ensure valid interpretation of results:

  • Genetic complementation: Re-introduce wild-type murG to confirm that observed phenotypes result specifically from murG disruption

  • Domain-specific mutations: Generate point mutations in catalytic residues to distinguish between catalytic function and structural roles

  • Polar effect controls: Measure expression of genes downstream of murG to identify potential polar effects of insertional mutagenesis

  • Conditional expression systems: Implement regulated expression to study essential gene functions without complete inactivation

The TargeTron system provides a feasible approach for generating site-specific mutations in C. caviae, as demonstrated with other genes such as IncA and SinC. When designing mutants, researchers should target multiple sites within the gene to confirm consistency of phenotypes and reduce the likelihood of site-specific artifacts. Additionally, phenotypic analysis should examine multiple aspects of bacterial physiology to capture the full spectrum of murG function:

Phenotypic AspectMeasurement MethodExpected Outcome in murG Mutants
Growth RateInclusion size measurementReduced growth rate
Developmental CycleTransition timing analysisDelayed EB to RB conversion
Cell MorphologyElectron microscopyAberrant cell division
Antibiotic SusceptibilityMIC determinationIncreased sensitivity to β-lactams

Statistical analysis should employ appropriate methods such as ANOVA with post-hoc tests to compare multiple mutant strains and controls simultaneously, with clear a priori decision criteria established before conducting experiments .

How should researchers design experiments to investigate the temporal expression of murG during the C. caviae developmental cycle?

Investigating temporal expression of murG during the C. caviae developmental cycle requires a carefully synchronized infection model combined with time-resolved analytical techniques:

  • Synchronize infection using centrifugation-assisted inoculation followed by temperature shift

  • Collect samples at defined intervals (0, 2, 6, 12, 24, 36, 48, and 72 hours post-infection)

  • Employ parallel analytical tracks:

    • qRT-PCR for transcript quantification

    • Western blotting for protein level assessment

    • Enzymatic activity assays for functional analysis

    • Immunofluorescence microscopy for localization studies

A critical aspect of this experimental design is establishing reliable normalization methods for each analytical approach:

Analytical ApproachNormalization MethodRationale
qRT-PCRMultiple reference genes (16S rRNA, gyrB)Accounts for changes in reference gene expression
Western BlotTotal bacterial protein (normalized to genome copies)Adjusts for changes in bacterial numbers
Enzymatic AssaysPer-bacterium normalizationDistinguishes expression vs. population effects
MicroscopyCo-staining with developmental markersCorrelates expression with developmental stage

When interpreting results, researchers should consider the inherent asynchrony that develops over time in Chlamydial infections, even with initial synchronization. Statistical analysis should employ mixed-effects models to account for biological replicates and technical variation. Time-course data should be fitted with appropriate non-linear regression models rather than simple pairwise comparisons between timepoints .

What factors should be considered when designing in vivo experiments to evaluate murG as a therapeutic target in C. caviae infections?

When evaluating murG as a therapeutic target through in vivo experiments, researchers must consider multiple factors to ensure robust, translatable results:

  • Model selection: The guinea pig inclusion conjunctivitis model most closely recapitulates natural C. caviae infections, though the chicken embryo model provides a useful alternative for preliminary studies

  • Intervention timing: Treatment should be evaluated at different infection stages (preventive, early, established infection)

  • Route of administration: Topical, systemic, and combined approaches should be compared

  • Outcome measures: Both clinical (inflammation scoring) and microbiological (bacterial load) endpoints should be assessed

A particularly important consideration is the establishment of clear go/no-go criteria for therapeutic potential:

CriterionBenchmark for SuccessMeasurement Method
Efficacy>2-log reduction in bacterial loadqPCR quantification
Clinical Improvement>50% reduction in inflammation scoreStandardized scoring system
SuperiorityEqual or better than current standard of careDirect comparison trial
Resistance DevelopmentNo resistance after 10 passagesSerial passage experiment

Researchers should implement factorial experimental designs that simultaneously evaluate multiple factors affecting treatment outcomes, enabling the identification of interaction effects between treatment variables. Statistical power calculations should account for expected variability in the animal model, typically requiring 8-12 animals per experimental group to detect clinically significant differences.

The chicken embryo model has proven valuable for preliminary in vivo assessment of virulence factors in C. caviae, as demonstrated with the SinC effector protein. Similar approaches could be applied to evaluate murG-targeted interventions before progressing to more complex mammalian models .

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