Recombinant Staphylococcus haemolyticus Probable CtpA-like serine protease (SH1486)

What is Staphylococcus haemolyticus and why is it significant in clinical microbiology?

Staphylococcus haemolyticus is a coagulase-negative staphylococcal (CoNS) species with substantial clinical importance. Recent studies have identified it as the most commonly isolated CoNS species in clinical settings, representing 52.9% of all isolates in some studies . S. haemolyticus has gained significant attention due to its concerning antibiotic resistance profile, as it demonstrates higher resistance rates than other staphylococcal species, including S. hominis and S. epidermidis . The clinical significance of S. haemolyticus is further underscored by its association with mortality rates of approximately 17.6% among infected patients, making it a priority pathogen for antimicrobial research .

Age distribution data reveals that S. haemolyticus infections are significantly more common in adults aged 18-60 years (71.1% of isolates), with fewer cases in pediatric populations and elderly patients over 60 years . This demographic pattern differs from other staphylococcal species, suggesting unique virulence or transmission characteristics that warrant further investigation.

What are CtpA-like serine proteases and what functions do they serve in bacterial physiology?

CtpA (carboxyl-terminal processing protease A) is a soluble periplasmic serine protease that plays crucial roles in bacterial physiology and pathogenesis . These proteases belong to a class of enzymes that cleave specific proteins at their carboxyl termini, often as part of post-translational modification processes. In Pseudomonas species, CtpA has been identified as functioning upstream of other proteases (such as Prc) in proteolytic cascades that regulate cell-surface signaling (CSS) systems .

The physiological significance of CtpA-like proteases extends beyond basic protein processing. Research demonstrates these enzymes modulate bacterial virulence, as mutants in ctpA genes show considerable attenuation in virulence models . Specifically, CtpA appears to prevent Prc-mediated proteolysis of anti-σ factors in cell-surface signaling pathways, thereby regulating bacterial responses to environmental stimuli . This regulatory function positions CtpA-like proteases as key mediators of bacterial adaptation to changing environments.

How can researchers effectively express and purify recombinant bacterial serine proteases like SH1486?

For effective expression and purification of recombinant bacterial serine proteases such as SH1486, researchers should implement a methodical approach that accounts for the unique characteristics of these enzymes.

Expression System Selection

When expressing SH1486 or similar proteases, the choice of expression system is critical. For bacterial serine proteases, E. coli-based expression systems often prove efficient, particularly BL21(DE3) strains that lack endogenous proteases. The methodology should include:

• Cloning the SH1486 gene into an expression vector containing an appropriate promoter (T7 is commonly used)

• Incorporating a fusion tag (His6, GST, or MBP) to facilitate purification

• Optimizing codon usage for efficient expression

• Testing multiple expression temperatures (16-37°C) to enhance solubility

Purification Protocol

A systematic purification protocol for SH1486 would typically involve:

• Initial capture through affinity chromatography (immobilized metal affinity chromatography for His-tagged proteins)

• Secondary purification via ion exchange chromatography

• Final polishing through size exclusion chromatography

• Buffer optimization to maintain stability (typically including 50-100 mM phosphate, pH 7.5-8.0)

Researchers should evaluate protease activity throughout the purification process, as loss of activity can occur during purification steps. Protease inhibitors should be excluded from buffers when purifying active enzymes for functional studies.

What standard assays can be used to measure serine protease activity of SH1486?

Several assays can be employed to accurately measure the enzymatic activity of SH1486 and other serine proteases:

Chromogenic Substrate Assays

These assays utilize peptide substrates linked to chromophores (commonly p-nitroanilide or p-nitrophenol) that release a colored product upon proteolytic cleavage. For CtpA-like proteases, substrates containing C-terminal recognition sequences provide specific activity measurements. Activity is typically measured spectrophotometrically at 405-410 nm.

Fluorogenic Substrate Assays

More sensitive than chromogenic assays, these utilize substrates coupled to fluorophores like AMC (7-amino-4-methylcoumarin) or AFC (7-amino-4-trifluoromethylcoumarin). After proteolytic cleavage, the released fluorophore is measured using a fluorometer, providing lower detection limits for enzyme activity.

Gel-Based Activity Assays

Zymography techniques incorporate protein substrates within polyacrylamide gels. After electrophoresis and incubation, proteolytic activity appears as clear zones against a stained background. For SH1486, casein or gelatin zymography would be appropriate, with modifications to detect C-terminal processing activity.

Activity Measurement Considerations

For reliable measurements of SH1486 activity, researchers should consider:

• Maintaining optimal buffer conditions (pH 7.0-8.5 for most serine proteases)

• Adding appropriate concentrations of divalent cations if required for activity

• Temperature control (typically 25-37°C)

• Inclusion of positive controls with known serine proteases

How might SH1486 contribute to antibiotic resistance mechanisms in S. haemolyticus?

The potential role of SH1486 in the exceptional antibiotic resistance observed in S. haemolyticus represents an important research direction. S. haemolyticus demonstrates the highest resistance rate among coagulase-negative staphylococci, with particularly concerning levels of methicillin resistance (68.8% of isolates) . While direct evidence linking SH1486 to these resistance mechanisms is not yet fully established, several research-backed hypotheses can be formulated:

CtpA-like proteases may contribute to antibiotic resistance through post-translational modification of proteins involved in cell envelope integrity. In Pseudomonas species, CtpA has been shown to function within proteolytic cascades that regulate cell-surface signaling systems . Similarly, SH1486 could process proteins involved in cell wall synthesis or membrane permeability, potentially affecting β-lactam antibiotic efficacy.

Another potential mechanism involves the processing of regulatory proteins that control expression of resistance genes. CtpA proteases are known to modulate anti-σ factor proteolysis in signaling pathways , and SH1486 might similarly influence regulatory pathways governing expression of resistance determinants in S. haemolyticus.

Methodologically, researchers investigating this question should consider:

• Generating SH1486 knockout mutants to assess changes in antibiotic susceptibility profiles

• Performing comparative proteomic analyses between wild-type and ΔSH1486 strains under antibiotic stress

• Identifying potential SH1486 substrates involved in cell envelope maintenance or stress responses

• Conducting transcriptomic analyses to determine if SH1486 affects expression of known resistance genes

What experimental approaches are most effective for characterizing the substrate specificity of SH1486?

Determining the substrate specificity of SH1486 requires a multi-faceted approach that combines biochemical, proteomic, and computational techniques:

Positional Scanning Synthetic Combinatorial Libraries (PS-SCL)

This technique utilizes peptide libraries where one position contains a defined amino acid while other positions contain mixtures. By systematically varying the fixed position, researchers can determine which amino acids are preferred at each position relative to the cleavage site. For C-terminal processing proteases like SH1486, libraries should be designed to assess preferences at positions adjacent to the C-terminus.

Proteomic Identification of Cleavage Sites (PICS)

PICS is a powerful technique for unbiased identification of protease substrates and their cleavage sites:

• Digest a proteome with a non-specific protease (e.g., trypsin)

• Chemically block newly generated N-termini

• Incubate peptides with SH1486

• Isolate and identify newly generated N-termini by mass spectrometry

• Bioinformatically map identified peptides to determine cleavage site preferences

In vivo Substrate Trapping

For identifying physiological substrates, researchers can employ substrate-trapping mutants of SH1486:

• Generate catalytically inactive SH1486 mutants that can still bind substrates

• Express these mutants in S. haemolyticus

• Purify the protease along with bound substrates

• Identify trapped proteins by mass spectrometry

Machine Learning Approaches

Machine learning algorithms can predict potential substrates based on known cleavage sites:

• Train algorithms using experimentally verified substrates

• Identify sequence and structural features that determine cleavage

• Scan the S. haemolyticus proteome for proteins with similar features

• Validate predictions experimentally

What role might SH1486 play in S. haemolyticus virulence and pathogenicity?

Based on research with similar proteases in other pathogens, SH1486 likely plays significant roles in S. haemolyticus virulence. Studies of CtpA in Pseudomonas aeruginosa have demonstrated that mutants in the ctpA gene show considerable attenuation in virulence in both zebrafish embryo and lung epithelial cell infection models . This suggests analogous functions may exist for SH1486 in S. haemolyticus pathogenesis.

Several mechanisms might explain the contribution of SH1486 to virulence:

• Regulation of membrane vesicle production: Research has shown that protease mutations can affect membrane vesicle production, which serves as a virulence mechanism in many bacteria. For instance, prc mutations in P. aeruginosa increase virulence through enhanced production of membrane vesicles . SH1486 might similarly regulate vesicle production in S. haemolyticus.

• Processing of virulence factors: As a C-terminal processing protease, SH1486 likely processes specific proteins to their mature, active forms. These could include adhesins, toxins, or immune evasion factors.

• Stress response modulation: CtpA-like proteases often function in stress response pathways, which are critical during host infection. SH1486 may help S. haemolyticus adapt to the hostile host environment by processing stress response regulators.

To investigate these potential roles, researchers should consider:

• Generating SH1486 deletion mutants and assessing virulence in appropriate infection models

• Comparing host immune responses to wild-type and mutant strains

• Examining the effect of SH1486 mutation on known virulence phenotypes

• Performing comparative proteomic analyses to identify virulence-associated proteins affected by SH1486 activity

How can advanced microscopy techniques be applied to study the cellular localization and dynamics of SH1486?

Understanding the subcellular localization and dynamics of SH1486 requires sophisticated microscopy approaches that can visualize proteins in living bacterial cells. Several methodologies are particularly suitable:

Super-Resolution Microscopy Approaches

Traditional fluorescence microscopy is limited by diffraction to approximately 200-300 nm resolution, insufficient for detailed bacterial protein localization. Super-resolution techniques overcome this limitation:

• Stimulated Emission Depletion (STED) Microscopy: Achieves ~30-80 nm resolution by using a second laser to suppress fluorescence emission from regions surrounding the focal point. For SH1486, researchers could:

  • Create fluorescent protein fusions (e.g., SH1486-mNeonGreen)

  • Optimize STED parameters for S. haemolyticus imaging

  • Track SH1486 localization during different growth phases and stress conditions

• Photoactivated Localization Microscopy (PALM): Achieves ~10-20 nm resolution by sequentially activating and imaging sparse subsets of photoactivatable fluorescent proteins. This approach allows for:

  • Precise quantification of SH1486 molecules per cell

  • Determination of protein clustering patterns

  • Mapping of membrane vs. periplasmic distribution

Correlative Light and Electron Microscopy (CLEM)

CLEM combines the protein-specific labeling of fluorescence microscopy with the ultrastructural detail of electron microscopy:

• Localize fluorescently-tagged SH1486 in fixed cells

• Process the same samples for electron microscopy

• Correlate SH1486 signals with specific cellular structures

• Achieve nanometer-scale resolution of protein localization relative to membranes and cell wall

Live-Cell Tracking and Single-Molecule Analysis

For understanding SH1486 dynamics in living cells:

• Use photoconvertible fluorescent proteins (e.g., mEos3.2) fused to SH1486

• Employ single-molecule tracking to follow individual SH1486 molecules

• Calculate diffusion coefficients under different conditions

• Determine if SH1486 forms stable complexes with other proteins

What bioinformatic approaches can predict potential substrates and interaction partners of SH1486?

Computational approaches offer powerful means to predict SH1486 substrates and interaction partners, guiding subsequent experimental validation. Several complementary bioinformatic strategies should be employed:

Sequence-Based Substrate Prediction

For CtpA-like proteases, C-terminal sequence features are often critical for substrate recognition:

• Position-Specific Scoring Matrices (PSSMs): Generate PSSMs from known CtpA substrates, focusing on C-terminal residues and adjacent regions. Apply these matrices to scan the S. haemolyticus proteome for similar motifs.

• Machine Learning Algorithms: Train support vector machines or neural networks using features of known substrates, including:

  • Amino acid composition of C-terminal regions

  • Secondary structure predictions

  • Surface accessibility

  • Charge distribution

Structural Bioinformatics

3D structural features can improve substrate prediction accuracy:

• Homology Modeling: Create a structural model of SH1486 based on known CtpA crystal structures, then use molecular docking to predict substrate binding.

• Structural Motif Recognition: Identify structural motifs in potential substrates that resemble known CtpA recognition elements.

Protein-Protein Interaction Predictions

SH1486 likely functions within protein interaction networks:

• Interolog Mapping: Identify proteins that interact with CtpA proteases in other bacteria, then find their orthologs in S. haemolyticus.

• Co-evolution Analysis: Perform statistical coupling analysis to identify proteins that show evolutionary correlation with SH1486, suggesting functional relationships.

Systems Biology Integration

Combine multiple data types for enhanced prediction accuracy:

• Network Analysis: Position SH1486 within predicted protein interaction networks, identifying hub proteins and functional modules.

• Co-expression Analysis: Analyze transcriptomic data to identify genes co-expressed with SH1486 under various conditions, suggesting functional relationships.

• Phenotypic Profiling: Use existing phenotypic data from protease mutants across bacterial species to infer SH1486 functions.

What are optimal experimental designs for studying SH1486 function in S. haemolyticus?

When investigating SH1486 function, researchers should consider implementing Single-Case Experimental Designs (SCEDs), which are particularly valuable for detailed analysis of specific interventions or conditions. These designs allow individual entities to serve as their own controls, making them well-suited for studying the effects of protease mutations or inhibitors .

Multiple Baseline and Phase Designs

This hybrid design, which accounted for 35.82% of studies in a recent analysis , would be particularly appropriate for SH1486 research. For investigating SH1486 function:

• Establish baseline measurements of multiple dependent variables (e.g., antibiotic resistance, growth rates, virulence factor expression)

• Introduce the intervention (e.g., SH1486 gene deletion, site-directed mutagenesis, or inhibitor treatment)

• Continue measurements across all variables to detect specific changes

This approach allows researchers to discriminate between direct and indirect effects of SH1486 manipulation. The median number of measurements in such designs is typically around 28, with approximately three experimental replicates .

Multiple Baseline and Alternation Designs

Another powerful approach (28.35% of studies ) involves alternating between conditions:

• Establish baseline measurements

• Alternate between control conditions and SH1486 manipulation

• Analyze the pattern of changes during alternation periods

This design is particularly effective for studying reversible effects of SH1486 inhibition or for comparing multiple SH1486 variants. Research indicates that randomization of condition sequences significantly strengthens the validity of these designs, with over half of such studies incorporating randomization .

The table below summarizes key experimental design characteristics based on published research:

How can researchers overcome challenges in generating knockout mutants of SH1486 in S. haemolyticus?

Creating targeted gene knockouts in S. haemolyticus presents several challenges due to its high natural antibiotic resistance and relatively low transformation efficiency. A methodical approach can overcome these obstacles:

Allelic Exchange Strategies

The most reliable method for SH1486 knockout involves allelic exchange:

• Vector Selection: Use temperature-sensitive plasmids (e.g., pIMAY or pBT2) that can be maintained at lower temperatures (28°C) but lost at higher temperatures (37-42°C).

• Homology Arm Design: Create ~1kb homology arms flanking the SH1486 gene. These should be amplified from S. haemolyticus genomic DNA and engineered to contain:

  • Restriction sites for cloning

  • No critical genetic elements beyond SH1486

  • Seamless fusion points to maintain proper reading frames

• Selection Marker Strategy: Given the high antibiotic resistance of S. haemolyticus , consider:

  • Using non-antibiotic selection markers (e.g., counterselectable markers like sacB)

  • Testing antibiotic susceptibility profiles before selecting markers

  • Implementing dual selection systems

Electroporation Optimization

Transformation efficiency can be enhanced through protocol optimization:

• Cell Wall Weakening: Treat cells with glycine (0.5-1.5%) during growth to weaken peptidoglycan

• Buffer Composition: Use electroporation buffers containing 0.5M sucrose and 10% glycerol

• Electric Field Parameters: Optimize voltage (1.5-2.5kV) and resistance (100-400Ω)

• Recovery Conditions: Allow extended recovery (3-5 hours) at suboptimal temperatures (30°C)

CRISPR-Cas9 Approaches

For S. haemolyticus strains recalcitrant to traditional methods:

• Introduce a plasmid expressing Cas9 and a guide RNA targeting SH1486

• Co-introduce a repair template containing homology arms

• Select for successful editing events

• Cure the CRISPR plasmid using temperature sensitivity

Verification Strategies

Confirming successful knockout requires multiple approaches:

• PCR verification with primers outside the homology regions

• Western blotting using anti-SH1486 antibodies

• RT-qPCR to confirm absence of SH1486 transcript

• Protease activity assays to confirm loss of function

How should researchers interpret conflicting data regarding SH1486 function in different experimental systems?

When faced with contradictory results regarding SH1486 function across different experimental platforms, researchers should implement a structured analytical approach:

Systematic Variation Analysis

First, conduct a detailed investigation of methodological differences that might explain discrepancies:

• Expression System Comparison: Recombinant SH1486 expressed in E. coli versus native expression in S. haemolyticus may exhibit different properties due to:

  • Post-translational modifications

  • Folding environment differences

  • Presence/absence of chaperones

  • Tag interference with function

• Assay Condition Variations: Small differences in assay conditions can significantly impact protease activity:

  • pH variations (optimal pH for CtpA-like proteases typically ranges 7.0-8.5)

  • Ionic strength differences

  • Presence of stabilizing agents

  • Temperature variations

• Substrate Differences: Discrepancies may arise from using:

  • Synthetic versus natural substrates

  • Different substrate concentrations

  • Variations in substrate preparation

Statistical Reanalysis

Apply robust statistical approaches to reconcile conflicting datasets:

Validation Through Orthogonal Methods

Confirm key findings using complementary techniques:

• In vitro vs. In vivo Correlation: Determine whether discrepancies reflect genuine differences between:

  • Biochemical activities in controlled environments

  • Physiological functions in cellular contexts

• Structural Biology Insights: Use structural approaches to resolve functional contradictions:

  • Crystallography to reveal conformational states

  • Hydrogen-deuterium exchange mass spectrometry for dynamics

  • NMR for solution behavior

What statistical approaches are most appropriate for analyzing SH1486 enzyme kinetic data?

Robust statistical analysis of SH1486 enzyme kinetics requires specialized approaches that account for the unique characteristics of enzymatic data:

Michaelis-Menten Kinetics Analysis

For basic enzyme kinetic studies of SH1486:

• Non-linear Regression: Direct fitting of the Michaelis-Menten equation:

  • $v = \frac{V_{max} \times [S]}{K_m + [S]}$

  • Provides more accurate parameter estimates than linearized plots

  • Allows proper weighting of data points

  • Enables direct estimation of standard errors

• Residual Analysis: Critical for validating model fit:

  • Residuals should show random distribution around zero

  • Systematic patterns indicate model inadequacy

  • Normality tests assess error distribution assumptions

• Bootstrapping Approaches: For more robust parameter confidence intervals:

  • Resample data with replacement

  • Perform many iterations of parameter estimation

  • Derive empirical confidence intervals without normality assumptions

Progress Curve Analysis

For analyzing continuous assays of SH1486 activity:

• Integrated Rate Equations: Fit entire progress curves to integrated forms of:

  • Michaelis-Menten equation for standard kinetics

  • Appropriate equations for more complex mechanisms

  • Include terms for potential product inhibition

• Global Fitting: Simultaneously analyze multiple progress curves:

  • Fit curves at different substrate/enzyme concentrations

  • Share common parameters across datasets

  • Increase statistical power and parameter reliability

Inhibition Studies Analysis

For analyzing SH1486 inhibition data:

• Competitive Inhibition:

  • $v = \frac{V_{max} \times [S]}{K_m(1 + \frac{[I]}{K_i}) + [S]}$

• Noncompetitive Inhibition:

  • $v = \frac{V_{max} \times [S]}{(K_m + [S])(1 + \frac{[I]}{K_i})}$

• IC50 Determination: For rapid inhibitor screening:

  • Fit dose-response curves to determine IC50 values

  • Convert IC50 to Ki using appropriate equations based on inhibition mechanism

  • Include Hill coefficients to account for potential cooperativity

Specialized Approaches for CtpA-like Proteases

Since CtpA proteases like SH1486 often show complex kinetics:

• Two-step Models: For proteases with significant acylation/deacylation steps:

  • Include terms for both substrate binding and acyl-enzyme intermediate formation

  • Account for potential rate-limiting steps

• Product Release Analysis: For proteases where product release may be rate-limiting:

  • Design experiments with varying product concentrations

  • Fit models including product inhibition terms

What emerging technologies could advance the study of SH1486 and related bacterial proteases?

Several cutting-edge technologies hold particular promise for advancing SH1486 research:

Cryo-Electron Microscopy (Cryo-EM)

Cryo-EM has revolutionized structural biology by enabling visualization of proteins in near-native states without crystallization:

• Single Particle Analysis: Determine SH1486 structure at near-atomic resolution:

  • Visualize enzyme-substrate complexes

  • Capture different conformational states

  • Resolve substrate binding mechanisms

• Tomography: Visualize SH1486 in its cellular context:

  • Determine membrane association patterns

  • Identify protein complexes containing SH1486

  • Map spatial distribution within S. haemolyticus cells

Proximity Labeling Proteomics

These methods identify proteins in close spatial proximity to SH1486:

• APEX2 Fusion Approach: Express SH1486-APEX2 fusions in S. haemolyticus:

  • APEX2 catalyzes biotinylation of nearby proteins upon H₂O₂ addition

  • Identify biotinylated proteins by streptavidin pulldown and mass spectrometry

  • Map the SH1486 proximity interactome

• BioID/TurboID Systems: Express SH1486 fused to promiscuous biotin ligases:

  • Spatially restricted biotinylation reveals proximal proteins

  • Temporal control allows tracking of dynamic interactions

  • Different labeling radii provide spatial relationship information

Time-Resolved Mass Spectrometry

For detecting transient enzyme-substrate interactions:

• Hydrogen-Deuterium Exchange Mass Spectrometry (HDX-MS):

  • Measure protection from deuterium exchange when substrates bind

  • Map binding interfaces with peptide-level resolution

  • Track conformational changes upon substrate binding

• Crosslinking Mass Spectrometry (XL-MS):

  • Capture transient interactions using chemical crosslinkers

  • Identify crosslinked peptides by MS/MS

  • Generate distance constraints for structural modeling

Nanobody-Based Technologies

Nanobodies (single-domain antibodies) can be developed against specific conformational states of SH1486:

• Conformation-Specific Inhibition: Generate nanobodies that:

  • Trap SH1486 in specific conformational states

  • Block substrate binding sites

  • Inhibit catalytic activity

• Intracellular Tracking: Express fluorescently tagged nanobodies to:

  • Track native SH1486 without fusion constructs

  • Visualize specific conformational states in vivo

  • Monitor dynamic changes during infection

How might insights from SH1486 research contribute to addressing antibiotic resistance in clinical settings?

Research on SH1486 has significant potential to inform novel approaches to combat antibiotic resistance in S. haemolyticus and related pathogens:

Protease Inhibitor Development

Given the potential role of CtpA-like proteases in bacterial virulence and antibiotic resistance, SH1486 represents a promising drug target:

• Structure-Based Drug Design: Using solved or modeled structures of SH1486:

  • Identify unique binding pockets

  • Design selective inhibitors

  • Develop allosteric modulators

• Natural Product Screening: Screen for SH1486 inhibitors from:

  • Microbial secondary metabolites

  • Plant extracts

  • Marine organism compounds

• Repurposing Existing Protease Inhibitors: Test known protease inhibitors against SH1486:

  • Modified serine protease inhibitors

  • Peptide mimetics

  • Covalent inhibitors with appropriate selectivity

Antibiotic Adjuvant Strategies

If SH1486 contributes to antibiotic resistance, its inhibition could potentiate existing antibiotics:

• Combination Therapy Testing: Evaluate SH1486 inhibitors in combination with:

  • β-lactam antibiotics

  • Glycopeptides

  • Other antibiotic classes

• Resistance Mechanism Disruption: Target specific resistance pathways:

  • If SH1486 processes proteins involved in cell wall modification

  • If SH1486 regulates efflux pump expression

  • If SH1486 controls stress responses that protect against antibiotics

Diagnostic Applications

Knowledge of SH1486 function could improve S. haemolyticus detection and characterization:

• Biomarker Development: Use SH1486 or its substrates as:

  • Diagnostic indicators of infection

  • Markers of antibiotic resistance potential

  • Targets for rapid identification tests

• Activity-Based Probes: Develop SH1486-specific activity probes:

  • For rapid detection of S. haemolyticus

  • To assess inhibitor efficacy in clinical samples

  • To monitor treatment response

The clinical importance of S. haemolyticus as a highly resistant pathogen (causing 17.6% mortality in some studies ) underscores the potential impact of such research directions. As the most resistant of all isolated coagulase-negative staphylococci , new approaches to combat S. haemolyticus infections are urgently needed, and SH1486 represents a promising target for such interventions.