Recombinant Staphylococcus aureus UPF0060 membrane protein SaurJH9_2364 (SaurJH9_2364)

What is Staphylococcus aureus UPF0060 membrane protein SaurJH9_2364?

SaurJH9_2364 is a membrane protein from Staphylococcus aureus strain JH9 that belongs to the UPF0060 protein family. It consists of 108 amino acids with the UniProt accession number A5IVC1. The protein has multiple transmembrane regions and displays a characteristic hydrophobic profile typical of integral membrane proteins. The amino acid sequence (MLYPIFIFIL AGLCEIGGGY LIWLWLREGQ SSLVGLIGGA ILMLYGVIAT FQSFPSFGRV YAAYGGVFII MSLIFAMVVD KQMPDKYDVI GAIICIVGVL VMLLPSRA) reveals the presence of several hydrophobic stretches that likely form membrane-spanning helices .

How does the membrane topology of SaurJH9_2364 compare with other bacterial membrane proteins?

SaurJH9_2364 contains multiple membrane-spanning regions typical of multipass transmembrane proteins. While its exact topology hasn't been fully characterized, computational analysis suggests it contains 2-4 transmembrane segments. This places it in the category of multispan membrane proteins that have been successfully designed through computational approaches, as demonstrated by recent advances in transmembrane protein design . The protein likely adopts a helical bundle conformation within the membrane, similar to other bacterial transmembrane proteins that have been crystallized and structurally characterized.

What experimental evidence supports the predicted structure of SaurJH9_2364?

While direct structural evidence for SaurJH9_2364 remains limited, advances in membrane protein structural biology provide insights into its likely conformation. Recent work has shown that designed multispan membrane proteins with 2-4 transmembrane regions can form stable structures that match computational predictions with high accuracy . Magnetic tweezer unfolding experiments conducted on similar membrane proteins have demonstrated remarkable stability within lipid environments, suggesting that SaurJH9_2364 likely forms a stable transmembrane structure despite the challenges in directly visualizing it .

What are the optimal conditions for expression and purification of recombinant SaurJH9_2364?

For optimal expression of SaurJH9_2364, a bacterial expression system using E. coli strains specifically designed for membrane protein expression (such as C41/C43 or Lemo21) is recommended. The protein should be expressed with a purification tag (His-tag is commonly used) and extracted using mild detergents like n-dodecyl-β-D-maltoside (DDM) or lauryl maltose neopentyl glycol (LMNG) to maintain structural integrity. Purification typically involves immobilized metal affinity chromatography followed by size-exclusion chromatography to ensure homogeneity. Critical parameters to monitor include expression temperature (typically 18-25°C is preferred over 37°C) and induction conditions (lower IPTG concentrations of 0.1-0.5 mM are often more effective) .

How can researchers overcome the hydrophobicity challenges when working with SaurJH9_2364?

The hydrophobic nature of SaurJH9_2364 presents significant challenges for structural and functional studies. Recent advances provide several approaches to address this issue:

What analytical techniques are most suitable for studying the structure-function relationship of SaurJH9_2364?

Several complementary techniques are recommended for comprehensive analysis of SaurJH9_2364:

For SaurJH9_2364 specifically, starting with computational modeling followed by validation using site-directed mutagenesis and biophysical characterization would establish a foundational understanding before attempting crystallization trials .

How can computational approaches be utilized to predict ligand binding sites on SaurJH9_2364?

Modern computational approaches offer powerful methods to predict potential ligand binding sites on membrane proteins like SaurJH9_2364:

• Homology modeling: Using structurally characterized members of the UPF0060 family as templates to generate a three-dimensional model of SaurJH9_2364.

• Molecular docking: Virtual screening of compound libraries against predicted binding pockets to identify potential interaction partners.

• Molecular dynamics simulations: Investigating the dynamic behavior of the protein within a membrane environment to identify transient binding pockets not evident in static models.

• Machine learning approaches: Leveraging existing membrane protein-ligand interaction datasets to predict binding sites based on sequence and predicted structural features.

The accuracy of these computational predictions can be significantly enhanced when integrated with experimental data from mutagenesis studies or hydrogen-deuterium exchange mass spectrometry that can identify regions of conformational flexibility .

What role might SaurJH9_2364 play in Staphylococcus aureus pathogenicity and antibiotic resistance?

While the specific function of SaurJH9_2364 remains to be fully elucidated, membrane proteins in pathogenic bacteria often play crucial roles in virulence, antibiotic resistance, and host-pathogen interactions. The strain JH9 from which this protein originates is known to exhibit vancomycin resistance, raising the possibility that SaurJH9_2364 might contribute to this phenotype.

Research approaches to investigate this connection could include:

• Gene knockout studies to assess changes in antibiotic susceptibility

• Protein-protein interaction studies to identify binding partners within resistance pathways

• Comparative genomics across resistant and susceptible strains

• Structural analysis to identify potential antibiotic binding sites

The methodological framework would involve creating isogenic mutants, performing minimal inhibitory concentration (MIC) assays across various antibiotic classes, and correlating structural features with resistance phenotypes .

How can protein engineering approaches be applied to modify SaurJH9_2364 for enhanced stability in structural studies?

Several protein engineering strategies can be employed to enhance the stability of SaurJH9_2364 for structural studies:

• Directed evolution: Creating libraries of SaurJH9_2364 variants and selecting for enhanced stability in detergent environments.

• Computational design: Using algorithms to identify stabilizing mutations based on energy calculations and evolutionary conservation patterns.

• Disulfide engineering: Introducing strategic disulfide bonds to rigidify flexible regions without disrupting function.

• Thermostabilizing mutations: Introducing specific point mutations at positions known to enhance stability in other membrane proteins.

• Domain swapping: Replacing flexible loops with stable structures from homologous proteins.

Recent advances in transmembrane protein design have demonstrated the feasibility of creating highly stable membrane proteins with specific topologies. These approaches could be adapted to modify SaurJH9_2364 for improved expression, purification yield, and crystallization propensity .

What techniques can effectively measure the interaction of SaurJH9_2364 with potential binding partners?

Several biophysical and biochemical techniques can be employed to characterize interactions between SaurJH9_2364 and potential binding partners:

For membrane proteins like SaurJH9_2364, reconstituting the protein in nanodiscs or liposomes can provide a more native-like environment for interaction studies. Controls should include non-specific binding assessments and validation using multiple independent techniques .

How can researchers distinguish between specific and non-specific binding when studying SaurJH9_2364 interactions?

Distinguishing specific from non-specific interactions is crucial when working with membrane proteins like SaurJH9_2364. A comprehensive methodological approach should include:

• Negative controls: Using unrelated membrane proteins of similar size and hydrophobicity.

• Competition assays: Demonstrating that unlabeled ligand can compete with labeled ligand for binding.

• Concentration dependency: Showing saturable binding that fits expected binding models.

• Mutational analysis: Creating point mutations at predicted interaction sites and demonstrating reduced binding.

• Detergent controls: Testing binding in different detergent conditions to rule out detergent-mediated interactions.

• Isothermal titration calorimetry: Providing thermodynamic parameters consistent with specific binding.

• Surface plasmon resonance: Demonstrating concentration-dependent association and dissociation kinetics consistent with specific interactions.

These approaches should be used in combination, as no single method can definitively establish specificity .

What are the most effective approaches for analyzing the topology and membrane insertion of SaurJH9_2364?

Determining the membrane topology of SaurJH9_2364 requires multiple complementary approaches:

• Computational prediction: Using algorithms like TMHMM, Phobius, or TOPCONS to predict transmembrane regions.

• Cysteine accessibility methods: Introducing cysteine residues at various positions and assessing their accessibility to membrane-impermeable reagents.

• Fluorescence quenching: Using environment-sensitive fluorophores to determine which regions are exposed to aqueous or lipid environments.

• Protease protection assays: Determining which regions are protected from proteolytic digestion when reconstituted in liposomes.

• Epitope tagging: Introducing epitope tags at different positions and determining their accessibility by antibody binding.

• Glycosylation mapping: Engineering potential glycosylation sites and determining which become glycosylated when expressed in eukaryotic systems.

A comprehensive topological map would integrate data from multiple methods, as each has distinct strengths and limitations. Current methodologies for studying membrane protein topology have benefited from advances in computational design approaches that can predict stable conformations with high accuracy .

What strategies can overcome the challenges of crystallizing SaurJH9_2364 for X-ray diffraction studies?

Crystallizing membrane proteins like SaurJH9_2364 presents significant challenges. A systematic approach should include:

• Construct optimization: Creating multiple constructs with varying N- and C-terminal boundaries to identify stable, crystallizable fragments.

• Detergent screening: Testing diverse detergents, including novel amphiphilic agents like maltose-neopentyl glycol (MNG) compounds.

• Lipid cubic phase (LCP) crystallization: This method can provide a more native-like environment for membrane proteins.

• Surface engineering: Introducing mutations that reduce surface entropy or creating fusion proteins with crystallization chaperones like T4 lysozyme.

• Antibody fragment co-crystallization: Using Fab or nanobody fragments to provide additional crystal contacts.

• Loop engineering: Replacing flexible loops with stable, rigid structures to facilitate crystal packing.

• Heavy atom derivatives: Planning for phase determination by incorporating selenomethionine or designing constructs with engineered metal binding sites.

Recent advances in computational design have produced multi-span membrane proteins with high structural stability, suggesting that similar approaches could be applied to engineer crystallizable variants of SaurJH9_2364 .

How can researchers apply cryo-electron microscopy to study the structure of SaurJH9_2364?

Cryo-electron microscopy (cryo-EM) offers advantages for membrane proteins that are difficult to crystallize. For SaurJH9_2364, consider these methodological approaches:

• Sample preparation optimization:

  • Test multiple detergents and amphipols for protein stability

  • Evaluate protein purity and monodispersity by size-exclusion chromatography

  • Optimize vitrification conditions to minimize ice thickness

• Size enhancement strategies:

  • SaurJH9_2364 (12 kDa) is below the typical size limit for cryo-EM (~50 kDa)

  • Create fusion constructs with larger proteins or engineer oligomeric forms

  • Use antibody fragments to increase particle size and provide fiducial markers

• Data collection and processing:

  • Employ phase plates to enhance contrast

  • Use motion correction and particle sorting algorithms to improve resolution

  • Implement 3D classification to identify conformational heterogeneity

• Validation approaches:

  • Perform cross-linking mass spectrometry to validate structural models

  • Use molecular dynamics simulations to assess model stability in a membrane environment

  • Confirm key structural features through mutagenesis and functional assays

The recent success in determining high-resolution structures of designed multispan membrane proteins suggests that similar techniques could be applied to native proteins like SaurJH9_2364 .

What are the current limitations in computational prediction of SaurJH9_2364 structure and how can they be addressed?

Computational prediction of membrane protein structures faces several challenges that are particularly relevant to SaurJH9_2364:

• Limited template availability: There are few experimentally determined structures for the UPF0060 family, limiting template-based modeling accuracy.

  • Solution: Employ newer deep learning approaches like AlphaFold2 that are less dependent on template availability.

• Membrane environment complexity: Traditional modeling often inadequately represents the heterogeneous lipid environment.

  • Solution: Implement explicit membrane molecular dynamics simulations to refine initial models.

• Conformational flexibility: Membrane proteins often exist in multiple conformational states.

  • Solution: Use enhanced sampling methods like replica exchange molecular dynamics to explore conformational space.

• Validation challenges: Without experimental data, computational models remain hypothetical.

  • Solution: Design targeted experiments to validate key features of the predicted structure, such as crosslinking of predicted proximal residues.

Recent advances in computational design of multipass membrane proteins demonstrate that accurate structure prediction is possible even without close homologs. These approaches could be adapted to predict the structure of SaurJH9_2364 with increasing confidence .

How can researchers investigate the potential role of SaurJH9_2364 in antibiotic resistance mechanisms?

Investigating SaurJH9_2364's potential role in antibiotic resistance requires a multifaceted approach:

• Gene expression analysis: Determine if SaurJH9_2364 expression is altered in response to antibiotic exposure or in resistant strains.

  • Method: RT-qPCR or RNA-seq comparing expression levels under various antibiotic stresses

• Gene knockout/knockdown studies: Create SaurJH9_2364 deletion mutants and assess changes in antibiotic susceptibility.

  • Method: Minimal inhibitory concentration (MIC) assays across multiple antibiotic classes

• Protein-antibiotic interaction studies: Determine if antibiotics directly interact with SaurJH9_2364.

  • Method: Surface plasmon resonance or isothermal titration calorimetry with purified protein

• Membrane permeability assays: Assess if SaurJH9_2364 affects membrane properties that influence antibiotic penetration.

  • Method: Fluorescent dye uptake assays with wild-type and mutant strains

• Structural analysis: Identify potential antibiotic binding sites through computational docking and validate experimentally.

  • Method: Site-directed mutagenesis of predicted binding residues followed by functional assays

This methodological framework provides a comprehensive approach to understanding how this membrane protein might contribute to the antibiotic resistance phenotype observed in S. aureus strain JH9 .

What approaches can be used to identify potential interaction partners of SaurJH9_2364 in bacterial cells?

Identifying protein-protein interactions for membrane proteins like SaurJH9_2364 requires specialized techniques:

• Bacterial two-hybrid systems: Modified to accommodate membrane proteins, these systems can detect interactions in vivo.

  • BACTH (Bacterial Adenylate Cyclase Two-Hybrid) is particularly suitable for membrane protein interactions

• Proximity-dependent biotinylation: Express SaurJH9_2364 fused to an enzyme like BioID that biotinylates nearby proteins.

  • Method: Pull-down biotinylated proteins and identify by mass spectrometry

• Co-immunoprecipitation with crosslinking: Chemical crosslinking preserves transient interactions before cell lysis.

  • Method: Use membrane-permeable crosslinkers followed by affinity purification and mass spectrometry

• Split-GFP complementation: Engineer SaurJH9_2364 with one fragment of GFP and screen a library of proteins tagged with the complementary fragment.

  • Method: Fluorescence microscopy to detect successful complementation

• Genetic interaction screens: Synthetic genetic array analysis to identify genes that show synthetic lethality or suppression with SaurJH9_2364 mutations.

These approaches should be validated using multiple methods, as demonstrated in successful co-immunoprecipitation studies of other membrane proteins like CD40 and TSHR .

How can SaurJH9_2364 be exploited for biotechnological applications?

While SaurJH9_2364's natural function remains to be fully characterized, its properties as a membrane protein offer several biotechnological applications:

• Biosensor development: Engineer SaurJH9_2364 to respond to specific analytes with a detectable signal.

  • Method: Fusion with reporter proteins like fluorescent proteins or enzymes

• Drug screening platform: Utilize SaurJH9_2364 as a target for screening antimicrobial compounds.

  • Method: Develop binding or functional assays suitable for high-throughput screening

• Membrane protein expression system optimization: Use SaurJH9_2364 as a model to develop improved expression systems for challenging membrane proteins.

  • Method: Systematic testing of promoters, signal sequences, and host strains

• Protein engineering scaffold: Use the stable transmembrane fold as a scaffold for designing novel membrane proteins with desired functions.

  • Method: Computational design followed by directed evolution

• Vaccine development: Exploit conserved epitopes of SaurJH9_2364 for vaccine development against S. aureus.

  • Method: Epitope mapping and immunogenicity testing

The application of membrane proteins in biotechnology has been demonstrated in various contexts, including drug development and cell therapy applications, suggesting similar potential for SaurJH9_2364 .