Recombinant UPF0337 protein SAV_738 (SAV_738)

What is UPF0337 protein SAV_738 and what organism does it originate from?

UPF0337 protein SAV_738 is a protein of unknown function (UPF) from Staphylococcus aureus. The "SAV_" prefix in the identifier indicates its origin from the S. aureus genome. As a UPF-classified protein, its precise biological function remains to be fully characterized, presenting significant research opportunities for structural and functional studies. The protein is part of the growing field of research focused on understanding the complete proteome of S. aureus, a pathogen of considerable clinical significance due to its association with antibiotic resistance, particularly methicillin-resistant strains (MRSA) .

How should researchers approach the initial characterization of UPF0337 protein SAV_738?

Initial characterization should follow a systematic approach:

• Bioinformatic analysis: Begin with sequence homology searches, motif identification, and structural prediction algorithms to generate hypotheses about potential functions.

• Expression optimization: Test multiple expression systems to establish which provides properly folded, active protein (see FAQ 2.1).

• Basic biochemical characterization: Determine molecular weight, isoelectric point, and stability under various conditions.

• Structural studies: Consider circular dichroism (CD) spectroscopy for secondary structure assessment, followed by more advanced techniques like X-ray crystallography or NMR.

• Functional screening: Design assays based on bioinformatic predictions to test potential enzymatic activities or binding partners.

This systematic approach helps establish foundational knowledge about the protein while guiding more specialized investigations.

What analytical methods are most appropriate for verifying recombinant SAV_738 identity and purity?

For thorough characterization of recombinant SAV_738:

Identity verification methods:

• Mass spectrometry (MS) for accurate molecular weight determination

• Peptide mass fingerprinting following enzymatic digestion

• N-terminal sequencing to confirm the correct start site

• Western blotting if antibodies are available

Purity assessment methods:

• SDS-PAGE with densitometry analysis (aim for >95% purity)

• Size exclusion chromatography to detect aggregates or degradation products

• Isoelectric focusing to detect charge variants

For advanced MS-based identification, high-resolution tandem MS techniques similar to those used for other staphylococcal proteins can be employed, involving intact protein liquid chromatographic separation and high-resolution MS detection . The observation of characteristic charge state patterns and fragmentation spectra can provide definitive identification of recombinant proteins.

Which expression systems are most suitable for recombinant SAV_738 production and what are their comparative advantages?

Multiple expression systems can be used for SAV_738 with distinct advantages:

The choice should be guided by research requirements: use E. coli for structural studies requiring large quantities, and mammalian systems when native-like activity is crucial for functional analyses.

How can researchers optimize experimental conditions for maximum soluble expression of SAV_738 in E. coli?

Optimization of SAV_738 expression in E. coli should follow a systematic experimental design approach similar to that described for other recombinant proteins . Key variables to consider include:

• Expression vectors: Test different promoter strengths and fusion tags (His, GST, MBP, SUMO) that can enhance solubility.

• Host strains: Compare BL21(DE3), Rosetta, Origami, or SHuffle strains which vary in their ability to form disulfide bonds and accommodate rare codons.

• Growth media: Evaluate rich media (LB, TB, 2YT) versus defined media, supplemented with glucose or glycerol as carbon sources.

• Induction conditions: Optimize:

  • Temperature (lower temperatures of 16-25°C often increase solubility)

  • IPTG concentration (0.1-1.0 mM range)

  • Induction timing (mid-log vs late-log phase)

  • Duration (4h vs overnight)

• Co-expression with chaperones: GroEL/GroES, DnaK/DnaJ/GrpE systems can assist proper folding.

A factorial design experiment examining these variables simultaneously, rather than one-at-a-time optimization, will more efficiently identify optimal conditions and reveal interaction effects between variables.

How do post-translational modifications affect SAV_738 structure and function?

Post-translational modifications (PTMs) can critically influence SAV_738 structure and function, as observed with other staphylococcal proteins:

• Potential modifications: While specific PTMs for SAV_738 are not well-characterized in the provided search results, staphylococcal proteins may undergo various modifications including glycosylation, as observed with PBP2a .

• Functional implications: PTMs can affect:

  • Protein folding and stability

  • Enzymatic activity

  • Protein-protein interactions

  • Cellular localization

  • Resistance to degradation

• Detection methods: To identify PTMs on SAV_738:

  • Mass spectrometry analysis (particularly LC-MS/MS)

  • Specific staining methods (e.g., ProQ Emerald for glycoproteins)

  • Western blotting with modification-specific antibodies

• Expression system selection: The choice between prokaryotic and eukaryotic expression systems should be guided by the required PTMs for proper folding and function, with mammalian and insect cell systems providing more complex modifications than bacterial systems .

Characterizing PTMs on native SAV_738 and comparing with recombinant versions from different expression systems is essential for ensuring biological relevance of functional studies.

What purification strategies are most effective for obtaining high-purity SAV_738?

A multi-step purification strategy is recommended for SAV_738:

Initial capture:

• Affinity chromatography if tagged (e.g., Ni-NTA for His-tagged protein)

• Ion exchange chromatography based on theoretical pI

Intermediate purification:

• Higher resolution ion exchange chromatography

• Hydrophobic interaction chromatography

Polishing steps:

• Size exclusion chromatography to remove aggregates and achieve >95% purity

• Removal of affinity tags if present (using specific proteases like TEV or thrombin)

Optimization considerations:

• Buffer composition (pH, salt concentration, additives)

• Temperature stability during purification

• Addition of protease inhibitors if degradation is observed

Each step should be optimized with small-scale tests before scaling up, with purity assessed by SDS-PAGE and activity by appropriate functional assays.

How can researchers assess and improve the stability of purified SAV_738?

Systematic assessment of SAV_738 stability should include:

• Thermal stability analysis:

  • Differential scanning fluorimetry (DSF)

  • Circular dichroism (CD) with temperature ramping

  • Activity assays after thermal challenge

• pH stability profiling:

  • Testing protein stability across pH range 4-9

  • Monitoring by activity assays and aggregation measurements

• Storage condition optimization:

  • Testing various buffers (phosphate, Tris, HEPES)

  • Evaluating stabilizing additives (glycerol, sucrose, specific ions)

  • Comparing storage temperatures (-80°C, -20°C, 4°C)

  • Assessing freeze-thaw stability

• Stability enhancement strategies:

  • Site-directed mutagenesis of unstable regions identified by hydrogen-deuterium exchange

  • Addition of ligands or binding partners

  • Formulation with stabilizing excipients

Similar approaches have proven successful for other staphylococcal proteins like LasA, which demonstrated significant thermal stability that supported its potential for industrial-scale manufacturing and clinical applications .

What structural analysis techniques are most informative for understanding SAV_738 function?

Multiple complementary structural approaches should be employed:

High-resolution structural determination:

• X-ray crystallography for atomic-level structure

• NMR spectroscopy for solution structure and dynamics

• Cryo-electron microscopy for larger assemblies

Dynamics and interaction studies:

• Hydrogen-deuterium exchange mass spectrometry to identify flexible regions

• Small-angle X-ray scattering (SAXS) for shape and conformational changes

• Förster resonance energy transfer (FRET) for monitoring conformational changes

Computational approaches:

• Molecular dynamics simulations to predict flexibility and potential binding sites

• Structural comparison with homologous proteins of known function

• Molecular docking to predict potential ligand interactions

The integration of these methods can provide insights into functional domains, potential active sites, and interaction interfaces that inform hypothesis-driven functional studies.

What approaches can researchers use to identify potential binding partners of SAV_738?

Several complementary methods should be employed to identify SAV_738 interaction partners:

In vitro methods:

• Pull-down assays with tagged SAV_738

• Surface plasmon resonance (SPR) screening

• Protein microarray analysis

• Isothermal titration calorimetry (ITC) for quantitative binding parameters

Cell-based methods:

• Yeast two-hybrid screening

• Proximity labeling approaches (BioID, APEX)

• Co-immunoprecipitation followed by mass spectrometry

• FRET-based interaction screening

Computational approaches:

• Prediction of interaction interfaces based on structural features

• Text mining of scientific literature for potential interactions

• Network analysis based on genomic context and co-expression data

Results from these multiple approaches should be integrated and validated using orthogonal methods to establish high-confidence interaction networks.

How can functional genomics approaches be applied to understand SAV_738's role in Staphylococcus aureus?

A comprehensive functional genomics strategy would include:

• Comparative genomics analysis:

  • Examine conservation of SAV_738 across staphylococcal strains

  • Identify genomic context and potential operonic organization

  • Search for co-occurrence patterns with genes of known function

• Transcriptomic profiling:

  • RNA-seq under various growth conditions to identify co-regulated genes

  • Analysis of expression patterns during infection models

  • Response to antibiotic exposure and stress conditions

• Proteomic approaches:

  • Quantitative proteomics to measure abundance changes

  • Interaction proteomics to identify protein complexes

  • Post-translational modification mapping

• Genetic manipulation:

  • Gene knockout or knockdown studies to assess phenotypic effects

  • Complementation studies to confirm gene-phenotype relationships

  • CRISPR interference for targeted repression

• Phenotypic screening:

  • Growth studies under various conditions

  • Antibiotic susceptibility testing

  • Biofilm formation assays

  • Virulence assessment in infection models

Integration of these approaches can provide a comprehensive understanding of SAV_738's biological role, particularly in the context of staphylococcal pathogenesis.

What methodologies are appropriate for investigating if SAV_738 possesses enzymatic activity?

A systematic approach to enzymatic characterization includes:

• Bioinformatic prediction:

  • Sequence analysis for conserved catalytic motifs

  • Structural comparison with known enzyme families

  • Active site prediction based on conserved residues

• General activity screening:

  • Substrate panels for common enzymatic activities (hydrolase, transferase, isomerase)

  • Colorimetric assays for detecting reaction products

  • Coupled enzyme assays for detecting specific activities

• Specific activity characterization:

  • Determination of enzyme kinetics (Km, Vmax, kcat)

  • Cofactor requirements and ion dependencies

  • pH and temperature optima

  • Substrate specificity profiling

• Mechanism investigation:

  • Site-directed mutagenesis of predicted catalytic residues

  • Inhibitor studies to confirm mechanism class

  • Structural studies with substrate analogs or transition state mimics

• Validation in biological context:

  • Complementation of knockout phenotypes

  • Metabolic profiling to detect changes in potential substrates

This methodical approach has proven successful for characterizing staphylococcal enzymes like LasA protease, which was shown to have significant staphylolytic activity against methicillin-resistant strains .

How can mass spectrometry be optimized for detailed characterization of SAV_738 and its variants?

Advanced mass spectrometry approaches for SAV_738 characterization should include:

• Intact protein analysis:

  • High-resolution MS for accurate molecular weight determination

  • Charge-state distribution analysis for conformation assessment

  • Native MS for quaternary structure evaluation

• Top-down proteomics:

  • Direct fragmentation of intact SAV_738 for sequence confirmation

  • Identification of post-translational modifications

  • Development of targeted MS/MS methods for specific fragments

• Bottom-up proteomics:

  • Enzymatic digestion followed by LC-MS/MS for sequence coverage

  • Modification mapping through specialized enrichment strategies

  • Quantitative approaches for comparative studies

• Advanced MS techniques:

  • Ion-ion proton-transfer charge reduction (PTCR) for improved detection

  • In-source fragmentation for generating specific peptide-like fragments

  • Hydrogen-deuterium exchange MS for conformational studies

• Method development considerations:

  • Optimization of chromatographic separation

  • Development of 5-minute LC-MS/MS methods for rapid analysis

  • Implementation of targeted detection strategies

These approaches are similar to those successfully employed for PBP2a characterization, where tandem MS enabled detection of protein variants and post-translational modifications like N-terminal methionine formylation and glycosylation .

What experimental design strategies are most effective for optimizing multiple parameters in SAV_738 expression studies?

Rather than optimizing one parameter at a time, researchers should implement:

• Factorial experimental design:

  • Screening multiple factors simultaneously (media, temperature, inducer concentration)

  • Identifying interaction effects between variables

  • Reducing total experiment numbers while increasing information output

• Response surface methodology (RSM):

  • Creating mathematical models of how variables affect protein expression

  • Predicting optimal conditions beyond tested points

  • Visualizing response surfaces to understand parameter relationships

• Statistical analysis approaches:

  • Analysis of variance (ANOVA) to determine significant factors

  • Regression modeling to quantify effects

  • Principal component analysis to reduce dimensionality in complex datasets

• Design implementation:

  • Use of microtiter plate formats for parallel condition testing

  • Automated liquid handling for increased throughput

  • Standardized analytics for consistent response measurement

• Optimization metrics:

  • Total protein yield

  • Soluble fraction percentage

  • Specific activity of purified protein

  • Cost-effectiveness of production conditions

Such systematic approaches have been successfully applied to recombinant protein expression, significantly improving yields and quality while reducing development time .

How can researchers investigate structure-function relationships in SAV_738 through protein engineering?

Systematic protein engineering approaches include:

• Alanine scanning mutagenesis:

  • Systematic replacement of residues with alanine

  • Identification of critical functional residues

  • Mapping of interaction interfaces

• Domain swapping and truncation analysis:

  • Creation of chimeric proteins with homologs

  • Systematic domain deletion constructs

  • Minimal functional domain determination

• Directed evolution:

  • Random mutagenesis through error-prone PCR

  • Creation of variant libraries

  • High-throughput screening for enhanced properties

• Rational design approaches:

  • Structure-guided mutagenesis of specific residues

  • Introduction of disulfide bonds for stability

  • Modification of surface properties for solubility enhancement

• Functional validation:

  • Comparative enzymatic assays of variants

  • Structural analysis of successful variants

  • In vivo complementation studies

These approaches can reveal critical insights into SAV_738 function, similar to studies of other staphylococcal proteins like LasA, where functional analysis demonstrated its potential as an enzybiotic agent against antibiotic-resistant staphylococci .

What considerations are important when designing experiments to study SAV_738 interactions with other biomolecules?

When investigating SAV_738 interactions, researchers should consider:

• Protein preparation quality control:

  • Ensure high purity (>95%) to avoid contaminant interactions

  • Verify proper folding through circular dichroism or activity assays

  • Assess aggregation state through dynamic light scattering

• Interaction detection method selection:

  • For kinetic studies: surface plasmon resonance or biolayer interferometry

  • For thermodynamic parameters: isothermal titration calorimetry

  • For structural details: X-ray crystallography of complexes, cryo-EM, or NMR

• Experimental design considerations:

  • Appropriate buffer conditions mimicking physiological environment

  • Concentration ranges spanning predicted Kd values

  • Proper controls including non-binding mutants

• Validation strategies:

  • Confirmation with multiple orthogonal techniques

  • Mutagenesis of predicted interaction interfaces

  • Functional assays to confirm biological relevance

• Data analysis approaches:

  • Fitting to appropriate binding models (1:1, cooperative, etc.)

  • Global analysis of datasets from multiple techniques

  • Statistical assessment of reproducibility

These methodological considerations ensure reliable characterization of SAV_738 interactions, providing insights into its biological function within the complex network of staphylococcal proteins.