Recombinant Candida glabrata Sorting nexin-4 (SNX4)

What is the structural organization of Sorting nexin-4 in Candida glabrata?

Sorting nexin-4 in C. glabrata likely contains the characteristic domains found in other SNX family proteins, including a phosphatidylinositol 3-phosphate binding domain (phox homology or PX domain) necessary for peripheral membrane localization, and a C-terminal Bin/Amphiphysin/Rvs (BAR) domain that recognizes and binds to curved membranes upon dimerization . The PX domain specifically binds to phosphatidylinositol 3-phosphate, recruiting SNX4 to endosomal membranes . Like other SNX-BAR proteins, C. glabrata SNX4 likely forms homodimers or heterodimers with other sorting nexins to create membrane tubules that facilitate protein trafficking between endosomal compartments and the plasma membrane . Based on conservation with other fungal species, C. glabrata SNX4 would be expected to participate in recycling pathways that prevent cargo degradation in the vacuole (the fungal equivalent of lysosomes) .

How should I design a recombinant expression system for C. glabrata SNX4?

When designing a recombinant expression system for C. glabrata SNX4, several factors should be considered:

• Expression host selection: While E. coli provides high yield and rapid growth, yeast expression systems like Saccharomyces cerevisiae may offer better protein folding due to their closer evolutionary relationship to C. glabrata. Since proper folding of both the PX and BAR domains is critical for SNX4 function, a eukaryotic expression system may be preferable for functional studies.

• Affinity tags: Include an N- or C-terminal tag (His6, GST, MBP) to facilitate purification while ensuring that the tag doesn't interfere with membrane binding or protein interactions. C-terminal tags may be preferable if the N-terminus contains functional motifs.

• Solubility considerations: SNX4 is a membrane-associated protein, so expression conditions should be optimized to prevent aggregation. Consider fusion partners that enhance solubility (MBP, SUMO) and include appropriate detergents in purification buffers.

• Domain-based constructs: For structural studies, express individual domains (PX domain, BAR domain) separately, as full-length protein may exhibit conformational flexibility that complicates crystallization.

What are the optimal conditions for purifying recombinant C. glabrata SNX4?

For optimal purification of recombinant C. glabrata SNX4:

• Lysis buffer composition:

  • 50 mM Tris or HEPES pH 7.5-8.0

  • 300 mM NaCl (adjust based on solubility)

  • 5-10% glycerol for stability

  • 1-5 mM DTT or TCEP as reducing agent

  • Protease inhibitor cocktail

  • Consider mild detergents (0.1% Triton X-100 or 1% CHAPS) if solubility is an issue

• Multi-step purification strategy:

  • Initial capture: Affinity chromatography using tag (Ni-NTA for His-tagged protein)

  • Intermediate: Ion exchange chromatography to remove contaminants

  • Final polishing: Size exclusion chromatography to ensure homogeneity and proper oligomeric state

• Quality control assessments:

  • SDS-PAGE and Western blotting to confirm identity and purity

  • Dynamic light scattering to check for aggregation

  • Circular dichroism to verify proper folding

  • Functional assays (lipid binding) to confirm activity

For membrane binding studies, incorporate liposomes containing phosphatidylinositol 3-phosphate during purification to stabilize the protein in its membrane-bound state.

What expression yields can I expect when producing recombinant C. glabrata SNX4?

Expression yields for recombinant C. glabrata SNX4 vary significantly depending on the expression system used:

Yields can be improved by optimizing:

• Growth temperature (often lower temperatures improve folding)

• Induction conditions (concentration of inducer, timing)

• Media composition (rich vs. defined media)

• Cell lysis methods (gentle extraction preserves structure)

For membrane-associated proteins like SNX4, final yields of active protein are typically lower than cytosolic proteins due to challenges with proper folding and maintaining solubility.

How can I evaluate the membrane tubulation activity of recombinant C. glabrata SNX4?

To evaluate the membrane tubulation activity of recombinant C. glabrata SNX4:

• In vitro liposome tubulation assay:

  • Prepare liposomes with composition mimicking endosomal membranes (including PI3P)

  • Incubate purified SNX4 with liposomes at varying concentrations

  • Visualize using negative-stain electron microscopy or cryo-EM

  • Quantify tubule formation by measuring tubule length, diameter, and frequency

• GUV-based assays (Giant Unilamellar Vesicles):

  • Generate GUVs containing fluorescent lipids and PI3P

  • Add fluorescently labeled SNX4

  • Observe membrane deformation using confocal microscopy

  • Quantify curvature generation in real-time

• Cellular assays:

  • Express fluorescently tagged SNX4 in cultured cells

  • Visualize endosomal tubule formation using live-cell imaging

  • Quantify tubule dynamics (extension rate, lifetime, frequency)

  • Compare with known tubulation-defective mutants

• Structure-function analysis:

  • Generate mutations in the BAR domain that disrupt dimerization

  • Test tubulation activity of mutants vs. wild-type protein

  • Create chimeric proteins with BAR domains from other sorting nexins

When analyzing results, consider that SNX4 may require additional factors for optimal tubulation activity in vivo, such as interaction partners that are absent in reconstituted systems .

What methods can determine the cargo specificity of C. glabrata SNX4?

To determine the cargo specificity of C. glabrata SNX4:

• Proteomic approaches:

  • Compare plasma membrane proteomes of wild-type vs. SNX4 knockout strains

  • Perform SILAC labeling for quantitative comparison

  • Focus on proteins showing decreased surface expression in knockout

  • Validate top candidates with targeted approaches

• Proximity labeling techniques:

  • Express SNX4 fused to BioID or APEX2 in C. glabrata

  • Allow in vivo biotinylation of proteins in proximity to SNX4

  • Purify biotinylated proteins and identify by mass spectrometry

  • Compare to control strains expressing only the labeling enzyme

• Direct binding assays:

  • Express cytoplasmic domains of potential cargo proteins

  • Perform pull-down assays with purified SNX4

  • Use surface plasmon resonance to measure binding affinities

  • Map binding interfaces using truncation mutants

• Cargo trafficking assays:

  • Generate fluorescent protein fusions with candidate cargoes

  • Compare trafficking dynamics in wild-type vs. SNX4 knockout cells

  • Quantify surface/internal distribution using flow cytometry

  • Measure protein half-life with cycloheximide chase experiments

When interpreting results, remember that in neurons, SNX4 depletion affects a variety of synaptic membrane proteins rather than just the canonical transferrin receptor cargo seen in other cell types, suggesting context-dependent cargo specificity .

How does C. glabrata SNX4 compare functionally to homologs in other fungal species?

Comparative analysis of C. glabrata SNX4 with homologs in other fungi reveals insights into functional conservation and specialization:

• Evolutionary conservation patterns:

  • The core PX and BAR domains show high sequence conservation across fungal species

  • Species-specific variations are often found in linker regions and terminal segments

  • C. glabrata SNX4 likely maintains the fundamental endosomal recycling function

• Complementation studies:

  • In S. cerevisiae, SNX4 (Snx4p) prevents degradation of proteins like the exocytic v-SNARE Snc1p by recycling them from endosomes to the plasma membrane

  • Cross-species complementation experiments can test if C. glabrata SNX4 rescues phenotypes in S. cerevisiae snx4Δ strains

  • Failure to complement would suggest species-specific adaptations

• Interactome differences:

  • S. cerevisiae Snx4p interacts with Snx41p and Snx42p to form distinct sorting complexes

  • C. glabrata may have evolved different interaction partners reflecting its pathogenic lifestyle

  • Mammalian SNX4 forms complexes with SNX7, SNX30, SNX5, or SNX32

• Cargo specificity variations:

  • Pathogenic fungi may utilize SNX4 to traffic virulence factors or stress response proteins

  • Differences in cargo recognition could reflect adaptation to host environments

  • Comparison with C. albicans SNX4 could reveal pathogen-specific functions

Studies in neurons have shown that SNX4's role may extend beyond the canonical trafficking of transferrin receptor seen in non-neuronal cells, suggesting context-dependent functions that may also exist in different fungal species .

What role might SNX4 play in C. glabrata pathogenicity and antifungal resistance?

SNX4's potential contributions to C. glabrata pathogenicity and antifungal resistance include:

• Regulation of virulence factor trafficking:

  • C. glabrata SNX4 could control the surface exposure of adhesins needed for host cell attachment

  • Secretion of hydrolytic enzymes might depend on SNX4-mediated sorting

  • Immune evasion factors may require SNX4 for proper localization

• Stress response adaptation:

  • C. glabrata thrives in diverse host niches with varying pH, nutrient availability, and immune pressures

  • SNX4 could regulate the trafficking of stress sensors and response proteins

  • Rapid membrane composition remodeling during stress might involve SNX4 pathways

• Antifungal drug resistance mechanisms:

  • C. glabrata is known for resistance to azole antifungals

  • SNX4 could regulate the surface expression of drug efflux pumps (e.g., Cdr1, Cdr2)

  • Membrane ergosterol content, the target of many antifungals, might be influenced by SNX4-dependent trafficking

• Adaptation to nutrient limitation:

  • Host environments often restrict essential nutrients as a defense mechanism

  • SNX4 might regulate the recycling of nutrient transporters to maximize acquisition efficiency

  • Iron acquisition systems particularly may depend on SNX4, similar to transferrin receptor recycling in mammalian cells

Experimental approaches to test these hypotheses would include generating C. glabrata SNX4 knockout strains and assessing their virulence in infection models, antifungal susceptibility, and ability to adapt to various stressors.

What controls are essential when analyzing protein trafficking in C. glabrata SNX4 mutants?

When analyzing protein trafficking in C. glabrata SNX4 mutants, the following controls are essential:

• Genetic validation controls:

  • Complementation with wild-type SNX4 to confirm phenotype reversal

  • Multiple independent SNX4 mutant clones to rule out off-target effects

  • Domain-specific mutants (PX domain, BAR domain) to dissect functions

  • Empty vector controls for complementation experiments

• Cargo protein controls:

  • Known SNX4-independent cargo proteins as negative controls

  • Known SNX4-dependent cargo (if identified) as positive controls

  • Total protein level measurements to distinguish trafficking from expression changes

  • Cellular localization markers to verify compartment identity

• Technical controls:

  • Microscopy: Proper channel alignment, bleed-through controls, threshold consistency

  • Biochemical fractionation: Marker proteins for each compartment, loading controls

  • Flow cytometry: Unstained controls, single-color controls, isotype controls

  • Image analysis: Randomized blind analysis, consistent ROI selection

• Physiological state controls:

  • Growth phase standardization (log phase cultures)

  • Media composition consistency

  • Temperature and pH maintenance

  • Stress exposure timing for stress response studies

Studies in neurons have shown that SNX4 knockdown effects can vary between specific short hairpin RNAs, suggesting possible off-target effects that must be controlled for by using multiple independent approaches to disrupt SNX4 function .

How can I troubleshoot protein aggregation issues with recombinant C. glabrata SNX4?

To troubleshoot protein aggregation issues with recombinant C. glabrata SNX4:

• Expression optimization:

  • Lower induction temperature (16-20°C) to slow folding and prevent aggregation

  • Reduce inducer concentration for more gradual expression

  • Shorten induction time to prevent accumulation of misfolded protein

  • Co-express with molecular chaperones (GroEL/ES, DnaK/DnaJ/GrpE)

• Buffer optimization:

  • Screen buffer compositions systematically (pH 6.0-8.5, NaCl 100-500 mM)

  • Test different buffering agents (Tris, HEPES, phosphate)

  • Add stabilizing agents (10% glycerol, 100-500 mM arginine, 1 M urea)

  • Include reducing agents (5 mM DTT or TCEP) to prevent disulfide-mediated aggregation

• Solubility enhancement strategies:

  • Express as fusion with highly soluble partners (MBP, SUMO, Trx)

  • Include mild detergents during purification (0.03% DDM, 0.1% CHAPS)

  • Add PIP3 headgroups or liposomes to stabilize the PX domain

  • Try extraction with increased salt concentration (500 mM NaCl)

• Protein engineering approaches:

  • Express individual domains separately

  • Remove flexible regions identified by disorder prediction

  • Introduce surface mutations to increase solubility

  • Create truncated constructs based on limited proteolysis results

Systematic screening can be documented in a table format:

This methodical approach helps identify optimal conditions for obtaining soluble, functional protein.

What approaches can resolve contradictory results between in vitro and in vivo studies of C. glabrata SNX4?

To resolve contradictory results between in vitro and in vivo studies of C. glabrata SNX4:

• Bridging experimental systems:

  • Semi-permeabilized cell assays that maintain cytosolic factors while allowing controlled addition of recombinant proteins

  • Cell extract supplementation experiments to identify missing cofactors

  • Liposome recruitment assays using native membranes isolated from C. glabrata

  • Reconstitution of purified components in increasing complexity

• Protein state verification:

  • Confirm post-translational modification status of native vs. recombinant SNX4

  • Validate protein folding using spectroscopic methods (CD, fluorescence)

  • Check oligomerization state using size exclusion chromatography

  • Verify membrane binding capacity with liposome flotation assays

• Controlled variable testing:

  • Systematically vary buffer conditions to mimic intracellular environment

  • Test pH dependence across physiological range (pH 5.5-7.5)

  • Examine temperature sensitivity of interactions

  • Assess effects of molecular crowding agents

• Interaction partner identification:

  • Perform pull-downs from C. glabrata lysates using recombinant SNX4

  • Test if adding specific binding partners restores activity in vitro

  • Use proximity labeling in vivo to identify the complete SNX4 interactome

  • Create minimal reconstituted systems with key identified partners

In neurons, SNX4 depletion affects numerous synaptic proteins rather than just the canonical transferrin receptor affected in non-neuronal cells, suggesting context-dependent functions that might explain discrepancies between different experimental systems .

How do I design a CRISPR-Cas9 system for modifying SNX4 in C. glabrata?

Designing a CRISPR-Cas9 system for modifying SNX4 in C. glabrata requires specific considerations for this pathogenic yeast:

• Guide RNA design:

  • Select target sequences with minimal off-target potential using C. glabrata genome database

  • Design gRNAs targeting early exons to ensure complete loss of function

  • Verify PAM sites (NGG for SpCas9) accessibility in the genomic region

  • Create multiple gRNAs targeting different regions to improve success rates

• Repair template construction:

  • For gene deletion: Design homology arms 500-1000 bp flanking the SNX4 coding region

  • For epitope tagging: Insert tag sequence in-frame at N- or C-terminus with ~50 bp homology arms

  • For point mutations: Include the desired mutation with ~50 bp homology on each side

  • Include selectable markers appropriate for C. glabrata (NAT1, HygB)

• Delivery system optimization:

  • Use lithium acetate/PEG transformation protocol optimized for C. glabrata

  • Consider electroporation for higher transformation efficiency

  • Deliver Cas9 and gRNA as ribonucleoprotein complex for transient expression

  • Use a C. glabrata-optimized Cas9 expression cassette for stable expression

• Screening and validation:

  • Design PCR primers spanning the modification site

  • Sequence verify all modifications

  • Confirm protein expression changes by Western blot

  • Assess potential off-target effects at predicted sites

Example gRNA design parameters:

• Target sequence: 20 nucleotides upstream of PAM (NGG)

• GC content: 40-60% for optimal binding

• Avoid sequences with homology elsewhere in the genome

• Target conserved domains for functional disruption

How should I analyze colocalization of C. glabrata SNX4 with endosomal markers?

To analyze colocalization of C. glabrata SNX4 with endosomal markers:

• Image acquisition considerations:

  • Use confocal microscopy with appropriate filter sets to minimize bleed-through

  • Acquire images at Nyquist sampling rate for optimal resolution

  • Collect Z-stacks to capture the full 3D volume of cells

  • Include single-labeled controls to correct for spectral overlap

• Quantitative colocalization metrics:

  • Pearson's correlation coefficient (PCC): Measures linear correlation between intensities (-1 to +1)

  • Manders' overlap coefficients (MOC): Proportion of each signal overlapping with the other (0 to 1)

  • Object-based methods: Count discrete structures that contain both markers

• Analysis workflow:

  • Apply appropriate background subtraction

  • Set consistent thresholds across samples

  • Apply deconvolution if necessary to improve signal-to-noise

  • Generate scatterplots of pixel intensities from both channels

  • Calculate coefficients and statistical significance

• Interpretation guidelines:

  • PCC > 0.5 suggests meaningful colocalization

  • Compare experimental values to randomized controls

  • Analyze multiple cells (>20) across independent experiments

  • Consider partial colocalization biologically significant

Studies in neurons have shown that endogenous SNX4 colocalizes with both early endosome marker RAB5 (Pearson's coefficient 0.58) and recycling endosome marker RAB11 (Pearson's coefficient 0.45) . Similar approaches can be applied to C. glabrata studies, with appropriate controls to account for the smaller cell size.

What statistical approaches should be used when analyzing SNX4-dependent protein trafficking changes?

For analyzing SNX4-dependent protein trafficking changes:

• Experimental design considerations:

  • Include biological replicates (minimum n=3) with multiple technical replicates

  • Use time-course measurements for trafficking kinetics

  • Include appropriate wild-type and negative controls

  • Power analysis to determine sample size needed for statistical significance

• Statistical tests for different data types:

  • Normally distributed continuous data: t-test (two conditions) or ANOVA (multiple conditions)

  • Non-normally distributed data: Mann-Whitney U or Kruskal-Wallis tests

  • Time-course data: Repeated measures ANOVA or mixed-effects models

  • Colocalization coefficients: Fisher's z-transformation before parametric testing

• Multiple hypothesis testing correction:

  • Bonferroni correction for stringent control of false positives

  • Benjamini-Hochberg procedure for false discovery rate control

  • q-value calculation for large-scale proteomics data

• Data visualization approaches:

  • Box plots showing distribution, median, and outliers

  • Bar graphs with individual data points visible

  • Time-course plots with error bars

  • Heat maps for multiple protein/condition comparisons

Example statistical reporting for trafficking data:

In neurons, quantitative mass spectrometry revealed that upon SNX4 knockdown, proteins involved in neurotransmission were the most dysregulated class . Similar approaches could be applied to C. glabrata to identify trafficking changes systematically.

How do I interpret proteomic data from C. glabrata SNX4 mutants?

To interpret proteomic data from C. glabrata SNX4 mutants:

• Data processing and normalization:

  • Apply appropriate normalization methods (global median, spike-in controls)

  • Log-transform data to approximate normal distribution

  • Filter low-confidence identifications

  • Consider batch effects and technical variations

• Differential expression analysis:

  • Calculate fold changes between SNX4 mutant and wild-type

  • Apply statistical tests with multiple hypothesis correction

  • Set significance thresholds (typically fold change ≥1.5, p-value <0.05)

  • Generate volcano plots to visualize significance vs. magnitude

• Functional categorization:

  • Perform Gene Ontology enrichment analysis

  • Apply pathway analysis (KEGG, Reactome)

  • Identify protein domains enriched in affected proteins

  • Analyze cellular compartment enrichment

• Biological interpretation:

  • Focus on membrane proteins that may be direct SNX4 cargoes

  • Look for changes in known trafficking machinery components

  • Consider secondary effects due to altered cell physiology

  • Compare with SNX4 studies in other organisms

In neurons, SNX4 knockdown affected membrane proteins at both presynaptic and postsynaptic terminals involved in processes such as synapse assembly, neurotransmission, and synaptic vesicle cycling . For C. glabrata, focus on membrane proteins involved in stress response, nutrient acquisition, and cell wall maintenance that might be directly affected by SNX4-mediated trafficking.

How might C. glabrata SNX4 research inform antifungal development strategies?

Research on C. glabrata SNX4 could inform novel antifungal development strategies through several mechanisms:

• Targeting SNX4-dependent trafficking pathways:

  • If SNX4 is essential for C. glabrata virulence or stress response

  • If SNX4 regulates drug efflux pump localization

  • If SNX4 mediates cell wall integrity maintenance

• Potential drug development approaches:

  • Small molecule inhibitors targeting the PX domain-phosphoinositide interaction

  • Peptide-based disruptors of SNX4 protein-protein interactions

  • Compounds affecting SNX4 dimerization or membrane tubulation

• Combinatorial therapy strategies:

  • SNX4 inhibition to sensitize C. glabrata to existing antifungals

  • Dual targeting of complementary trafficking pathways

  • Disruption of SNX4-dependent stress responses combined with stress-inducing antifungals

• Structure-based drug design opportunities:

  • Exploit structural differences between fungal and human SNX4

  • Target species-specific interaction interfaces

  • Develop allosteric inhibitors affecting conformational dynamics

C. glabrata is known for its resistance to azole antifungals, often through upregulation of drug efflux pumps . If SNX4 regulates the trafficking of these pumps, inhibiting SNX4 function could potentially restore sensitivity to existing antifungals, providing a novel therapeutic approach to combat resistance.

What are the challenges in translating in vitro findings on C. glabrata SNX4 to in vivo infection models?

Translating in vitro findings on C. glabrata SNX4 to in vivo infection models presents several challenges:

• Physiological differences between laboratory and host conditions:

  • In vitro media vs. complex host environments (pH, nutrients, oxygen)

  • Static cultures vs. dynamic host interactions

  • Absence of host immune factors in vitro

  • Temperature and stress conditions that differ from standard laboratory settings

• Technical challenges for in vivo assessment:

  • Limited real-time imaging capabilities in host tissues

  • Difficulty isolating fungal material from host tissues for molecular analysis

  • Low fungal burden in some infection models limiting detection sensitivity

  • Host variability introducing confounding factors

• Genetic manipulation considerations:

  • Stability of genetic modifications in vivo without selection pressure

  • Potential fitness costs of mutations becoming apparent only in vivo

  • Different phenotypes in laboratory vs. clinical isolates

  • Compensatory mechanisms activated specifically in vivo

• Experimental design complexities:

  • Selection of appropriate animal models mimicking human infection

  • Relevant endpoints for virulence assessment

  • Controlling for host factors (immune status, microbiome)

  • Ethical considerations limiting sample sizes and experiment duration

To address these challenges, researchers should consider:

• Using ex vivo models as intermediates between in vitro and in vivo

• Developing tissue-mimicking culture systems

• Employing conditional gene expression systems

• Conducting parallel studies in multiple C. glabrata clinical isolates

What novel technologies could advance our understanding of C. glabrata SNX4 function?

Novel technologies that could advance our understanding of C. glabrata SNX4 function include:

• Advanced imaging approaches:

  • Super-resolution microscopy to visualize endosomal structures below the diffraction limit

  • Lattice light-sheet microscopy for 3D imaging with minimal phototoxicity

  • Single-molecule tracking to follow SNX4 dynamics in living cells

  • Correlative light and electron microscopy to link function with ultrastructure

• Genome editing and screening technologies:

  • CRISPR interference for tunable gene repression

  • CRISPR activation for controlled overexpression

  • Genome-wide CRISPR screens to identify genetic interactions

  • Inducible degradation systems for acute protein depletion

• Protein interaction mapping approaches:

  • BioID or TurboID proximity labeling in living C. glabrata cells

  • Thermal proteome profiling to detect drug-target engagement

  • Cross-linking mass spectrometry to capture transient interactions

  • Microfluidic techniques for measuring weak interactions

• Systems biology approaches:

  • Multi-omics integration (proteomics, lipidomics, transcriptomics)

  • Machine learning for pattern recognition in complex datasets

  • Flux analysis to track membrane protein movement

  • Computational modeling of trafficking networks

In neurons, a combination of imaging, functional studies, and quantitative proteomics revealed SNX4's unexpected role in synaptic function beyond traditional cargo trafficking . Similar multidisciplinary approaches could uncover the unique aspects of SNX4 function in C. glabrata pathobiology.

How can comparative studies across fungal species inform C. glabrata SNX4 research?

Comparative studies across fungal species can significantly inform C. glabrata SNX4 research:

• Evolutionary insights:

  • Sequence conservation analysis to identify functional hotspots

  • Lineage-specific adaptations in pathogenic vs. non-pathogenic fungi

  • Rates of evolution in different protein domains suggesting selective pressures

  • Comparative genomics to identify species-specific interaction partners

• Functional conservation testing:

  • Cross-species complementation studies (e.g., C. glabrata SNX4 in S. cerevisiae snx4Δ)

  • Chimeric protein construction to map species-specific functional regions

  • Heterologous expression studies to identify differential localization patterns

  • Cargo specificity comparison across fungal species

• Pathogenesis-specific adaptations:

  • Comparison between multiple Candida species (C. glabrata, C. albicans, C. krusei)

  • Analysis of SNX4 function in other pathogenic fungi (Cryptococcus, Aspergillus)

  • Correlation of SNX4 sequence variations with pathogenicity traits

  • Host adaptation signatures in SNX4 sequences

• Methodological advantages:

  • Leveraging genetic tools available in model fungi (S. cerevisiae)

  • Applying insights from well-studied systems to C. glabrata

  • Identifying conserved cargoes across species

  • Using phylogenetic relationships to predict function

In S. cerevisiae, SNX4 (Snx4p) prevents degradation of the exocytic v-SNARE Snc1p by recycling it from endosomes to the plasma membrane . Investigating whether C. glabrata SNX4 performs similar functions, and whether additional pathogen-specific cargoes exist, could provide important insights into its role in virulence and stress adaptation.

What are the critical knowledge gaps in our understanding of C. glabrata SNX4?

Critical knowledge gaps in our understanding of C. glabrata SNX4 include:

• Basic characterization:

  • Complete protein structure and domain organization

  • Subcellular localization pattern in C. glabrata

  • Expression changes during different growth phases and stress conditions

  • Post-translational modifications regulating activity

• Functional aspects:

  • Identity of specific cargo proteins in C. glabrata

  • Composition of SNX4-containing protein complexes

  • Membrane tubulation and trafficking capabilities

  • Redundancy with other sorting nexins in C. glabrata

• Pathobiology relevance:

  • Role in virulence and host-pathogen interactions

  • Contribution to antifungal drug resistance mechanisms

  • Function during different stages of infection

  • Impact on stress response and adaptation to host environments

• Therapeutic potential:

  • Essentiality for C. glabrata survival or virulence

  • Druggability of SNX4 domains or interactions

  • Potential for combination therapy approaches

  • Selectivity potential between fungal and human homologs