Recombinant Candida glabrata Protein OS-9 homolog (YOS9), partial

Basic Research Questions

• What is the function of Candida glabrata Protein OS-9 homolog (YOS9) in endoplasmic reticulum quality control?

  YOS9 in C. glabrata (CAGL0E04686g) functions as a critical component of the endoplasmic reticulum-associated degradation (ERAD) pathway, similar to its homolog in Saccharomyces cerevisiae. Based on studies of the S. cerevisiae ortholog, YOS9 acts as a "degradation lectin" that recognizes specific N-glycan structures on misfolded glycoproteins . The protein contains a mannose-6-phosphate receptor homology (MRH) domain that binds to Man8GlcNAc2 or Man5GlcNAc2 N-glycans on misfolded proteins, targeting them for degradation . In experimental systems, researchers can assess YOS9 function by monitoring the degradation rates of model misfolded glycoproteins such as CPY* (mutant carboxypeptidase Y) in wild-type versus YOS9-deleted strains.

  Methodological approach: To study YOS9 function in C. glabrata, employ pulse-chase experiments with radiolabeled amino acids to track degradation of model substrates. Compare degradation kinetics between wild-type and Δyos9 mutant strains to quantify the contribution of YOS9 to ERAD efficiency.

• How should researchers optimize expression and purification of recombinant C. glabrata YOS9 for functional studies?

  Successful expression and purification of functional YOS9 requires careful consideration of expression systems and purification conditions to maintain protein integrity. The following methodology has proven effective:

  Expression systems comparison:

  Expression System	Advantages	Disadvantages	Yield (mg/L culture)
  E. coli	Rapid growth, high yield	Potential improper folding	5-10
  Yeast (S. cerevisiae)	Native-like post-translational modifications	Longer growth time	2-4
  Baculovirus	Good for membrane-associated proteins	Complex system	1-3
  Mammalian cell	Most authentic modifications	Lowest yield, highest cost	0.5-2

  For functional studies of YOS9, a yeast expression system is often preferable due to proper glycosylation and folding of this ER-resident protein. After expression, purification should employ gentle conditions to preserve the MRH domain structure. Avoid repeated freeze-thaw cycles as they significantly impact protein activity, and store working aliquots at 4°C for no more than one week.

• What experimental models are available for studying YOS9 function in Candida pathogenesis?

  Several experimental models can be employed to study YOS9's role in C. glabrata pathogenesis:

  In vitro models:

  • Macrophage infection assays using RAW264.7 or primary macrophages to assess intracellular survival

  • Epithelial cell adhesion assays to evaluate host-pathogen interactions

  Animal models:

  • Systemic candidiasis model in mice

  • Galleria mellonella larval infection model

  The Galleria mellonella model has emerged as a particularly useful tool for studying virulence genes in C. glabrata. As demonstrated with CgXbp1 transcription factor studies, larval survival rates can be compared between wild-type and gene deletion strains to assess virulence contributions . This model allows for high-throughput screening and has good correlation with murine models while avoiding many ethical considerations.

Advanced Research Questions

• How does YOS9 expression in C. glabrata change during macrophage infection and stress response?

  YOS9 expression in C. glabrata undergoes dynamic regulation during macrophage infection. Based on genome-wide RNA polymerase II occupancy studies similar to those performed for other C. glabrata genes, YOS9 likely shows temporal expression patterns correlated with specific phases of infection .

  Research has shown that C. glabrata mounts chronological transcriptional responses during macrophage infection, with distinct gene sets activated at different timepoints:

  • Early phase (0-1 hour): Immediate stress response genes

  • Intermediate phase (1-2 hours): Metabolic adaptation genes

  • Late phase (2-4 hours): Carbon metabolism and DNA repair genes

  YOS9, as part of the ER stress response, would be expected to show increased expression during the intermediate to late phase as the pathogen adapts to the intracellular environment. To confirm this, researchers should perform chromatin immunoprecipitation followed by next-generation sequencing (ChIP-seq) against elongating RNA Polymerase II to track dynamic YOS9 transcription during infection .

• What is the relationship between YOS9 and antifungal drug resistance in clinical C. glabrata isolates?

  The relationship between YOS9 and antifungal resistance is complex and warrants investigation, especially given C. glabrata's intrinsic resistance to azole antifungals. Recent studies of clinical isolates have revealed genotypic diversity within individual patient blood cultures, with mixed fluconazole-susceptible and -resistant populations .

  YOS9's role in protein quality control may indirectly contribute to drug resistance through several potential mechanisms:

  1. Enhanced degradation of damaged proteins resulting from drug-induced stress

  2. Possible interactions with drug efflux pumps from the ABC transporter family

  3. Potential role in maintaining cell wall integrity under drug stress

  Research methodology: To investigate these connections, researchers should:

  1. Compare YOS9 expression levels between azole-susceptible and resistant clinical isolates

  2. Generate YOS9 deletion mutants in both backgrounds and assess changes in minimum inhibitory concentrations (MICs)

  3. Perform transcriptomic analysis to identify differentially expressed genes in Δyos9 mutants under drug stress

  4. Investigate potential physical interactions between YOS9 and known resistance factors

  These approaches would help elucidate whether YOS9 contributes to the notable drug resistance observed in C. glabrata infections .

• How can CRISPR-Cas9 be optimized for studying YOS9 function in Candida glabrata?

  CRISPR-Cas9 systems can be effectively optimized for studying YOS9 in C. glabrata through several critical modifications to standard protocols:

  Optimized CRISPR-Cas9 system for C. glabrata:

  1. Promoter selection: Use the C. glabrata RNA polymerase III promoter (SNR52) for sgRNA expression instead of commonly used S. cerevisiae promoters

  2. Codon optimization: Humanized Cas9 should be codon-optimized for C. glabrata

  3. sgRNA design considerations:

     • Target unique regions within YOS9 to prevent off-target effects

     • Design multiple sgRNAs targeting different regions of YOS9

     • Validate sgRNA efficiency using in silico tools specific for fungi

  4. Transformation method: Electroporation yields higher efficiency than lithium acetate methods

  5. Repair template design: Include at least 50bp homology arms flanking the cut site

  Verification strategy:

  • PCR verification of editing

  • Western blot confirmation of protein loss

  • Functional assays to confirm phenotype

  • Whole genome sequencing to detect potential off-target effects

  This approach has been successfully implemented in studies of other C. glabrata genes and can be applied to YOS9 functional analysis .

• What is the role of YOS9 in C. glabrata's adaptation to different host niches?

  C. glabrata colonizes diverse host niches including the oral cavity, gastrointestinal tract, and genitourinary tract, each presenting unique microenvironmental stresses . YOS9 likely plays a critical role in adapting to these different environments through its function in ER quality control.

  In different host niches, C. glabrata encounters varying:

  • pH levels

  • Nutrient availability

  • Host immune defenses

  • Competing microbiota

  YOS9's contribution to adaptation includes:

  1. pH adaptation: Maintaining proper folding of cell surface proteins required for acid/alkaline stress responses

  2. Nutrient acquisition: Supporting the quality control of nutrient transporters and adhesins like the EPA (epithelial adhesin) family proteins

  3. Immune evasion: Contributing to proper folding of proteins involved in masking pathogen-associated molecular patterns (PAMPs)

  Experimental approach: To study YOS9's role in niche adaptation, researchers should:

  1. Generate YOS9 conditional expression strains

  2. Compare colonization efficiency in different mucosal tissue models

  3. Analyze protein secretion profiles using proteomics

  4. Evaluate the strain's competitive fitness against wild-type in mixed infection models

  This would provide insights into how YOS9-mediated quality control contributes to C. glabrata's remarkable adaptability to different host environments .

• How does YOS9 interact with other components of the ERAD pathway in Candida glabrata?

  YOS9 in C. glabrata functions as part of a larger ERAD network, interacting with several key proteins to facilitate misfolded protein degradation. Based on homology to the well-characterized S. cerevisiae system, YOS9 likely forms complexes with:

  1. Hrd1 complex components: Including Hrd1 (E3 ubiquitin ligase), Hrd3, and Der1

  2. Htm1/EDEM: Works in the same pathway as YOS9, potentially modifying N-glycans to create the recognition signal

  3. Kar2/BiP: ER-resident chaperone that may help recruit misfolded substrates

  Protein-protein interaction network:

  Interaction Partner	Interaction Type	Function in Complex	Detection Method
  Hrd3	Direct binding	Substrate recruitment	Co-IP, Y2H
  Htm1/EDEM	Functional	Glycan processing	Genetic epistasis
  Kar2/BiP	Indirect	Substrate delivery	Mass spectrometry
  Cdc48	Downstream	Extraction of substrates	Sequential co-IP

  Experimental approach for studying these interactions:

  1. Epitope tag YOS9 and perform co-immunoprecipitation followed by mass spectrometry to identify interacting partners

  2. Conduct bimolecular fluorescence complementation (BiFC) assays to visualize interactions in living cells

  3. Perform genetic epistasis analysis by creating double mutants of YOS9 and other ERAD components

  4. Use proximity-dependent biotin identification (BioID) to capture transient interactions

  Understanding these interactions is crucial for elucidating how C. glabrata maintains proteostasis during infection and stress conditions .

• What methodologies are most effective for studying the glycan-binding specificity of C. glabrata YOS9?

  Studying the glycan-binding specificity of YOS9 requires specialized techniques that can detect subtle differences in binding preferences. Based on research with the S. cerevisiae homolog, YOS9 specifically recognizes Man8GlcNAc2 or Man5GlcNAc2 N-glycans on misfolded proteins .

  Recommended methodological approaches:

  1. Glycan microarray analysis:

     • Immobilize a library of defined glycan structures on a chip

     • Probe with purified recombinant YOS9

     • Detect binding using fluorescently labeled antibodies

     • Quantify binding affinity to different glycan structures

  2. Surface plasmon resonance (SPR):

     • Immobilize purified YOS9 on a sensor chip

     • Flow solutions containing different glycan structures

     • Measure real-time binding and dissociation kinetics

     • Calculate binding constants (Ka, Kd) for different glycans

  3. Isothermal titration calorimetry (ITC):

     • Directly measure thermodynamic parameters of YOS9-glycan interactions

     • Determine binding stoichiometry, enthalpy, and entropy

     • Generate complete thermodynamic profiles for different glycan ligands

  4. Site-directed mutagenesis of the MRH domain:

     • Identify conserved residues in the mannose-binding pocket

     • Create point mutations in these residues

     • Test mutant proteins for altered glycan binding profiles

     • Correlate binding changes with functional outcomes in vivo

  These approaches would help define the precise glycan structures recognized by C. glabrata YOS9 and how this specificity contributes to its function in ERAD and potentially in pathogenesis .

• How does the temporal expression of YOS9 correlate with virulence factor production during C. glabrata infection?

  Understanding the temporal relationship between YOS9 expression and virulence factor production requires comprehensive time-course studies during infection. Based on research with other C. glabrata genes, a chronological program of gene expression occurs during host-pathogen interaction .

  Key methodology for temporal studies:

  1. In vitro macrophage infection model:

     • Infect macrophages with C. glabrata

     • Collect samples at multiple timepoints (0.5, 1, 2, 4, 6, 8 hours)

     • Perform RNA-seq and ChIP-seq to track gene expression changes

     • Compare YOS9 expression patterns with known virulence genes

  2. Correlation analysis with virulence factors:

     • Track expression of adhesins (EPA genes)

     • Monitor stress response genes

     • Analyze expression of metabolic adaptation genes

     • Compare with YOS9 expression trajectory

  Based on studies of other C. glabrata genes during macrophage infection, genes tend to cluster into distinct temporal groups :

  Infection Phase	Time (hours)	Predominant Gene Functions	YOS9 Expression
  Early	0-1	Stress response, adhesion	Potentially elevated
  Intermediate	1-2	Metabolic remodeling	Likely peaked
  Late	2-4	Carbon metabolism, DNA repair	Returning to baseline
  Persistent	>4	Growth and division	Maintained at moderate levels

  This temporal correlation would help elucidate how YOS9-mediated quality control contributes to the proper timing of virulence factor deployment during the infection process .