Recombinant Staphylococcus aureus Uncharacterized protein SAS1160 (SAS1160), partial

What experimental approaches should be used for initial characterization of uncharacterized S. aureus proteins like SAS1160?

Initial characterization of uncharacterized S. aureus proteins requires a systematic multi-step approach. Begin with sequence analysis using bioinformatics tools to identify potential domains, motifs, and homology to known proteins. Following recombinant expression, employ a combination of biochemical assays including size exclusion chromatography, circular dichroism spectroscopy, and thermal shift assays to determine structural properties.

For functional characterization, implement:

• Protein-protein interaction studies using pull-down assays or bimolecular fluorescence complementation (BiFC) as demonstrated with THAL protein

• Subcellular localization determination using fluorescent tagging

• Expression analysis across different growth conditions using qPCR and western blotting

• Phenotypic analysis of knockout mutants in relevant infection models

A systematic approach similar to that used for SAS10/C1D family proteins investigation would be appropriate, where researchers identified both RNA processing and chromatin regulation functions through methodical experiments .

How do you design appropriate expression systems for recombinant S. aureus proteins that maintain native structure?

Designing expression systems for S. aureus proteins requires careful consideration of several factors to maintain native structure:

When designing constructs, consider:

• Codon optimization for expression host without altering critical structural elements

• Inclusion of appropriate signal peptides when necessary

• Strategic placement of purification tags to minimize interference with protein function

Research on S. aureus proteins like SSL1 demonstrates that proper signal peptide function is critical for secreted proteins . In cases requiring glycosylation, consider systems that properly process signal peptides, as demonstrated with SARS-CoV-2 S1 protein expression, where tag placement significantly affected glycosylation .

What are the recommended methods for analyzing potential virulence functions of uncharacterized S. aureus proteins?

To analyze potential virulence functions of uncharacterized S. aureus proteins like SAS1160, researchers should employ a comprehensive approach combining in vitro, ex vivo, and in vivo methodologies:

In vitro methods:

• Cytotoxicity assays with relevant human cell lines (e.g., epithelial, immune cells)

• Host-pathogen interaction assays (adhesion, invasion, persistence)

• Immune modulation assessment (cytokine responses, complement interaction)

Ex vivo methods:

• Human tissue explant models

• Extracellular vesicle isolation and characterization as demonstrated in studies showing that S. aureus EVs package cytosolic, surface, and secreted proteins including cytolysins

In vivo methods:

• Animal infection models comparing wild-type and knockout strains

• Superinfection models, particularly with influenza, as used for characterizing SasD

• Assessment of bacterial burden, inflammatory responses, and mortality

A systematic screening approach similar to that used for cell wall-anchored proteins (CWAs) can identify unique phenotypes in both pneumonia and influenza superinfection models. In studies of SasD, researchers found that mice infected with sasD mutants had decreased bacterial burden, inflammatory responses, and mortality compared to wild-type S. aureus, with significant reductions in IL-1β levels and altered macrophage viability .

How can researchers differentiate between SAS1160 and other S. aureus proteins with similar nomenclature like SSL1?

Differentiating between similarly named S. aureus proteins requires a structured analytical approach combining genomic, proteomic, and functional analyses:

Genomic differentiation:

• Compare gene sequences and genomic context using multiple S. aureus reference genomes

• Analyze gene presence across different strains (e.g., SSL1 is found in all S. aureus strains examined, with 12 known alleles)

• Identify strain variations through allele typing similar to the approach used for SSL1 protein

Proteomic differentiation:

• Use mass spectrometry for unambiguous protein identification

• Compare theoretical vs. observed molecular weights (e.g., SSL1 has a predicted molecular weight of 22.6 kDa after signal sequence cleavage)

• Analyze post-translational modifications

Functional differentiation:

• Assess enzymatic activities (e.g., SSL1 demonstrates protease activity)

• Perform substrate specificity assays

• Compare host protein interactions

When analyzing SSL1, researchers identified it as a protease and demonstrated its corneal virulence. They differentiated SSL1 from other proteins through N-terminal sequencing, confirming a 100% match with the SSL1 protein of strain Newman, and found that "the ssl1 gene, according to a BLAST search, is not present in other bacterial species, but is invariably found in all S. aureus strains examined" .

What protein stability and storage protocols are critical for maintaining activity of recombinant S. aureus proteins?

Maintaining stability and activity of recombinant S. aureus proteins requires careful consideration of storage conditions and buffer composition:

Recommended storage practices:

• For liquid formulations: Store at -20°C/-80°C with typical shelf life of 6 months

• For lyophilized formulations: Store at -20°C/-80°C with typical shelf life of 12 months

• Avoid repeated freeze-thaw cycles; store working aliquots at 4°C for up to one week

Reconstitution protocol:

• Briefly centrifuge vial prior to opening to bring contents to bottom

• Reconstitute in deionized sterile water to a concentration of 0.1-1.0 mg/mL

• Add glycerol to a final concentration of 5-50% for long-term storage

• Create single-use aliquots to avoid repeated freeze-thaw cycles

Buffer considerations:

• pH stability range determination using thermal shift assays

• Assessment of compatible stabilizing agents (glycerol, trehalose, sucrose)

• Evaluation of necessary cofactors or ions for maintaining structural integrity

Stability testing schedule:

• Initial time point (freshly prepared protein)

• 1-week stability

• 1-month stability

• 3-month stability

• 6-month stability

For each time point, assess activity retention, structural integrity, and aggregation state to establish optimal storage conditions.

What statistical design considerations should be incorporated when planning functional assays for uncharacterized proteins?

Planning robust functional assays for uncharacterized proteins requires careful statistical design considerations to ensure valid and reproducible results:

Sample size determination:

• Perform power analysis to determine appropriate sample size

• For comparing two proportions with expected response rates of 0.4% and 0.6% (2-tail test, 95% confidence interval, 50% power), approximately 10,444 samples per group would be required

• For smaller effect sizes, larger sample sizes are necessary to achieve statistical significance

Experimental design approaches:

• Implement factorial designs to evaluate multiple factors simultaneously

• Consider response surface methodology for optimization experiments

• Use D-Optimal designs to maximize the determinant of the information matrix (X'X)

Controls and validation:

• Include positive and negative controls in each experimental run

• Implement technical replicates (minimum triplicate) and biological replicates

• Use orthogonal assays to validate findings

Analysis considerations:

• Select appropriate statistical tests based on data distribution

• Consider whether parametric or non-parametric analyses are appropriate

• Account for multiple testing corrections when necessary

• Report effect sizes alongside p-values

As noted in experimental design literature, "Experiments in which one factor at a time was varied were shown to be wasteful and misleading" . Instead, researchers should implement multi-factor experimental designs that can efficiently evaluate complex relationships between variables.

How should researchers approach potential contradictions between in vitro and in vivo findings for S. aureus proteins?

When facing contradictions between in vitro and in vivo findings for S. aureus proteins, researchers should implement a structured reconciliation approach:

Systematic evaluation protocol:

• Scrutinize experimental conditions

  • Evaluate differences in protein concentrations between systems

  • Compare physiological relevance of in vitro conditions to in vivo microenvironments

  • Assess potential artifacts from recombinant vs. native protein forms

• Investigate host-pathogen context

  • Examine host factors present in vivo but absent in vitro

  • Consider immune system interactions that modify protein function

  • Evaluate the impact of microbial community interactions in vivo

• Design bridging experiments

  • Develop ex vivo models that better recapitulate in vivo conditions

  • Implement organoid or tissue explant systems as intermediate models

  • Use advanced imaging to track protein localization and interactions in vivo

• Examine strain-specific variations

  • Study multiple S. aureus isolates to account for strain variability

  • Consider allelic variations that might affect function, as seen with the SSL1 gene which has 12 known alleles with varying prevalence

• Reassess protein modifications

  • Examine potential post-translational modifications in vivo

  • Evaluate the impact of microenvironment pH, redox state, and ion concentrations

Research on S. aureus EVs demonstrates the importance of reconciling in vitro and in vivo findings - while EVs showed cytotoxicity in vitro, engineered EVs proved immunogenic and protective in a mouse sepsis model, highlighting the complex interplay between pathogenicity and immune response .

What techniques are most effective for investigating the role of uncharacterized proteins in S. aureus pathogenicity models?

Investigating uncharacterized proteins in S. aureus pathogenicity requires a multi-faceted approach combining genetic manipulation, infection models, and molecular analyses:

Genetic manipulation approaches:

• CRISPR-Cas9 targeted gene deletion to create clean knockouts

• Transposon mutagenesis libraries for high-throughput screening

• Complementation studies to confirm phenotypes

• Conditional expression systems for essential genes

Infection model selection:

• Acute infection models (skin, pneumonia, sepsis)

• Chronic/persistent infection models (osteomyelitis, endocarditis)

• Host-specific models relevant to natural infection sites

• Superinfection models with preceding viral infections to evaluate contextual roles

Molecular pathogenesis assessment:

• Transcriptomics to identify co-regulated virulence factors

• Proteomics to map interaction networks

• In vivo imaging to track bacterial dissemination

• Host response analysis (cytokines, immune cell recruitment)

Research on SasD effectively employed knockout mutants in both standard pneumonia and influenza superinfection models. This revealed that SasD influences inflammatory signaling within the lung, with mice infected with sasD mutants showing decreased bacterial burden, inflammatory responses, and mortality. Importantly, the requirements for cell wall-anchored proteins differed between single infection and superinfection scenarios, highlighting the importance of context-specific models .

How can researchers determine if SAS1160 is associated with extracellular vesicle formation in S. aureus?

To determine if SAS1160 is associated with S. aureus extracellular vesicle (EV) formation, researchers should implement a comprehensive analytical workflow:

EV isolation and characterization protocol:

• Culture S. aureus wild-type and SAS1160 mutant strains to late exponential phase

• Isolate EVs through differential ultracentrifugation followed by density gradient separation

• Characterize EVs using:

  • Nanoparticle tracking analysis (NTA) for size distribution and concentration

  • Dot immunoblot analysis for relative EV production

  • Protein assays for quantitative assessment

Compositional analysis:

• Perform proteomics analysis of EV content comparing wild-type and mutant EVs

• Use western blotting to confirm SAS1160 presence in EVs

• Analyze lipid composition to determine membrane characteristics

Functional characterization:

• Evaluate the impact of SAS1160 deletion on EV biogenesis rate and morphology

• Assess EV cytotoxicity against relevant host cell types

• Determine immunomodulatory properties of EVs from wild-type vs. mutant strains

Mechanistic investigation:

• Examine interactions with phenol-soluble modulins (PSMs), which promote EV biogenesis by disrupting the cytoplasmic membrane

• Investigate the role of peptidoglycan cross-linking and autolysin activity, which modulate EV production by altering cell wall permeability

• Assess potential interactions with other factors known to influence EV formation

Research on S. aureus EVs has shown that they package diverse proteins including cytosolic, surface, and secreted proteins, and specific genetic factors significantly impact EV production. For example, deletion of psmα genes reduced EV production, while the capsular phenotype had no obvious impact on EV formation .

What genomic analysis approaches can reveal the evolutionary conservation of uncharacterized proteins across S. aureus strains?

To investigate evolutionary conservation of uncharacterized proteins like SAS1160 across S. aureus strains, researchers should employ these genomic analysis approaches:

Comparative genomics workflow:

• Sequence alignment and homology detection

  • Perform BLAST searches against comprehensive S. aureus genome databases

  • Identify orthologous proteins across diverse clinical isolates

  • Quantify sequence conservation with tools like Clustal Omega or MUSCLE

• Allelic variation analysis

  • Identify polymorphic regions and conserved domains

  • Characterize allele types and their distribution, as done with SSL1 which has 12 known alleles

  • Correlate allelic variants with strain virulence phenotypes

• Genomic context evaluation

  • Analyze gene neighborhood conservation (synteny)

  • Identify associated mobile genetic elements

  • Determine if the gene resides within pathogenicity islands, as SSL1 resides within the SaPIn2 pathogenicity island

• Evolutionary pressure assessment

  • Calculate dN/dS ratios to detect selection signatures

  • Identify regions under positive or purifying selection

  • Compare evolutionary rates with known virulence factors

Implementation example:
For SSL1, researchers determined it is "invariably found in all S. aureus strains examined, e.g., 88/88 sequenced genomes," suggesting strong conservation. Analysis of clinical isolates revealed six different allele types with type 2 being most prevalent among ocular isolates (13/20). Amino acid sequence identity between different allele types ranged from 68.6% to 83.2%, indicating substantial conservation with strain-specific variations .

What bioinformatic tools are most appropriate for predicting potential functions of uncharacterized S. aureus proteins?

Predicting functions of uncharacterized S. aureus proteins requires a multi-faceted bioinformatic approach integrating various prediction tools and databases:

Sequence-based analysis tools:

• InterPro and Pfam for domain and family identification

• SMART for architecture analysis

• SignalP for signal peptide prediction

• TMHMM for transmembrane region identification

• ScanProsite for functional motif detection

Structure-based prediction:

• AlphaFold for protein structure prediction

• PyMOL for structural visualization and analysis

• COACH for ligand-binding site prediction

• ProFunc for structure-based function annotation

• ConSurf for functional region conservation mapping

Network-based approaches:

• STRING for protein-protein interaction prediction

• GeneMANIA for functional association networks

• KEGG Pathway for metabolic pathway integration

• BioCyc for genomic context analysis

Integrated predictive workflows:

• Initial sequence analysis for basic features (domains, motifs, localization signals)

• Structural prediction and comparison to characterized proteins

• Protein interaction network analysis to predict functional associations

• Integration of transcriptomic data to identify co-expressed genes

• Cross-species comparison to identify functional conservation

For SAS10/C1D family proteins, researchers initially identified structural similarities with superantigens, then through further analysis determined they do not bind MHC receptors or T cell receptors like superantigens do, but instead bind specific targeted host defense proteins, demonstrating how sequential bioinformatic analysis can refine functional predictions .

How should researchers approach experimental design when investigating potential immunomodulatory effects of S. aureus proteins?

Investigating immunomodulatory effects of S. aureus proteins requires carefully designed experiments addressing both innate and adaptive immune responses:

Experimental design framework:

• In vitro immune cell assays:

  • Use purified primary immune cells and relevant cell lines

  • Include multiple immune cell types (neutrophils, macrophages, dendritic cells, T cells)

  • Measure cytokine/chemokine responses, cell activation markers, and functional outcomes

  • Implement dose-response studies with physiologically relevant concentrations

• Ex vivo tissue models:

  • Employ human tissue explants for site-specific immune responses

  • Use perfusion systems to model dynamic immunological environments

  • Analyze spatial aspects of immune cell recruitment and activation

• In vivo immunological assessment:

  • Compare wild-type and knockout bacterial strains in infection models

  • Include both acute and chronic infection scenarios

  • Analyze tissue-specific immune responses and systemic effects

  • Consider models with pre-existing immune challenges (e.g., influenza infection models)

• Mechanistic investigation:

  • Utilize knockout mice lacking specific immune components

  • Implement neutralizing antibodies to block specific pathways

  • Use reporter systems to track immune signaling pathways

  • Apply systems biology approaches to map immune network perturbations

Statistical considerations:

• Implement multi-factor experimental designs to evaluate complex interactions

• Use repeated measures designs for time-course experiments

• Account for inter-individual variability in immune responses

• Report effect sizes alongside statistical significance

Research on S. aureus SSL proteins has revealed their ability to inhibit components of both adaptive and innate immune responses, with specific proteins binding targeted host defense molecules like IgA, IgG, and complement components .

What methods are recommended for investigating potential interactions between uncharacterized S. aureus proteins and host proteins?

Investigating interactions between uncharacterized S. aureus proteins and host proteins requires a systematic multi-technique approach:

Interaction screening methods:

• Yeast two-hybrid (Y2H) screening for binary interactions

• Affinity purification-mass spectrometry (AP-MS) for protein complexes

• Protein microarrays for high-throughput screening

• Bimolecular fluorescence complementation (BiFC) for in vivo interaction visualization

Validation and characterization techniques:

• Co-immunoprecipitation to confirm interactions in native contexts

• Surface plasmon resonance (SPR) for binding kinetics quantification

• Microscale thermophoresis (MST) for affinity determination

• Hydrogen-deuterium exchange mass spectrometry (HDX-MS) for interaction interface mapping

Functional consequence assessment:

• Mutagenesis of predicted interaction interfaces

• Competitive binding assays with known ligands

• Cell-based functional assays to assess biological outcomes

• Structural studies (X-ray crystallography or cryo-EM) of protein complexes

Implementation protocol:

• Initial screening to identify candidate interactors

• Biochemical validation with at least two orthogonal methods

• Affinity and kinetics determination

• Mapping of binding interfaces

• Functional studies to determine biological significance

Research on S. aureus SSL proteins demonstrated their binding to specific host defense proteins like IgA, IgG, and complement components . Similar approaches combining pull-down assays and functional studies could reveal SAS1160 binding partners. In studies of THAL protein, researchers used bimolecular fluorescence complementation assays to demonstrate interactions with histone chaperone Nucleolin 1, histone-binding NUC2, and histone demethylase JMJ14, providing insight into chromatin regulation functions .

How can researchers design knockout experiments to determine the essentiality of uncharacterized proteins in S. aureus?

Designing knockout experiments to determine protein essentiality in S. aureus requires strategic genetic manipulation approaches tailored to different experimental scenarios:

Knockout strategy selection:

Experimental validation protocol:

• Generate multiple independent mutants to control for secondary mutations

• Implement complementation studies to confirm phenotype specificity

• Perform growth curve analysis across multiple conditions

• Test competitive fitness in co-culture with wild-type strain

• Assess in vivo survival and virulence in relevant infection models

Essentiality determination criteria:

• Inability to recover viable deletion mutants despite multiple attempts

• Growth defects that can be rescued by complementation

• Depletion phenotypes in conditional expression systems

• Absence of transposon insertions in saturated mutagenesis libraries

Researchers studying S. aureus surface protein D (SasD) successfully generated knockouts and demonstrated its role in inflammatory signaling, providing an experimental framework applicable to other uncharacterized proteins . For suspected essential genes, the Nebraska Transposon Mutant Library approach offers a resource to identify potentially essential regions through mapping insertion sites .

What controls and validation steps are necessary when characterizing antibodies against novel S. aureus proteins?

Characterizing antibodies against novel S. aureus proteins requires comprehensive validation through multiple complementary approaches:

Essential validation steps:

• Specificity validation:

  • Western blot against recombinant protein, wild-type, and knockout bacterial lysates

  • ELISA with related proteins to assess cross-reactivity

  • Immunoprecipitation followed by mass spectrometry to confirm target identity

  • Pre-absorption with recombinant antigen to confirm specific binding

• Sensitivity assessment:

  • Limit of detection determination using serial dilutions

  • Comparison with alternative detection methods when available

  • Standard curve generation with purified recombinant protein

  • Assessment across multiple sample preparation methods

• Application-specific validation:

  • For immunohistochemistry: comparison with fluorescent protein tags

  • For flow cytometry: parallel staining with multiple antibody clones

  • For immunoprecipitation: validation of pull-down efficiency

  • For neutralization: functional inhibition assays

• Reproducibility testing:

  • Inter-lot consistency evaluation

  • Stability assessment under various storage conditions

  • Robustness across different buffer compositions

  • Performance across multiple biological replicates

Example validation scenario:
When characterizing antibodies against SARS-CoV-2 S1 protein expressed in a recombinant system, researchers found that an antibody (ABclonal A20136) recognized only the S1 product without an N-terminal tag, but not products with N-terminal FLAG tags. This demonstrated how protein modifications or tag placement can affect epitope recognition, highlighting the importance of comprehensive validation with multiple protein variants .

Research Data Tables

Table 1: Comparison of S. aureus Protein Expression Systems

Table 2: SSL1 Allele Distribution in Clinical Isolates

Data adapted from studies of SSL1 allele distribution