Recombinant Candida glabrata Protein TIF31 homolog (TIF31), partial

What is the biological significance of the TIF31 homolog in Candida glabrata?

The TIF31 homolog in Candida glabrata likely plays a significant role in protein synthesis pathways, similar to homologous proteins in related fungal species. C. glabrata is the second most common cause of candidiasis after C. albicans, accounting for 15-25% of invasive Candida infections . Understanding TIF31's function is particularly important as C. glabrata infections are often difficult to treat due to antifungal resistance, especially to azole drugs like fluconazole . As with other C. glabrata proteins, TIF31 may contribute to pathogenicity, particularly in immunocompromised patients, older adults, and those with critical illnesses such as AIDS, cancer, or diabetes .

How do TIF31 homologs compare between Candida glabrata and other Candida species?

Comparing TIF31 homologs between C. glabrata and other Candida species requires careful sequence alignment and structural analysis. Unlike some proteins that are species-specific, such as the recently characterized Yhi1 protein in C. glabrata , TIF31 homologs may show varying degrees of conservation across Candida species. Research methodologies for such comparative analysis typically involve:

• Multiple sequence alignment of TIF31 homologs across species

• Phylogenetic analysis to determine evolutionary relationships

• Structural predictions to identify conserved domains

• Functional assays to determine if biological activity is conserved

As demonstrated with other C. glabrata proteins, species-specific variations can significantly impact protein function and may contribute to the unique pathogenic properties of C. glabrata .

What expression systems are most suitable for producing recombinant C. glabrata TIF31?

Based on successful approaches with other C. glabrata proteins, several expression systems can be considered for recombinant TIF31 production:

For expression in E. coli, fusion constructs similar to those used for other C. glabrata proteins can be employed. For example, a TrxA-6xHis-TCS (Thrombin Cleavage Site) fusion strategy has been successful with other fungal proteins . Specifically, cloning the TIF31 ORF into pET32b(+) between appropriate restriction sites (such as XbaI and BamHI) and transforming into E. coli BL21(DE3) pLysS provides a solid starting point .

What are the optimal conditions for purifying recombinant C. glabrata TIF31 protein?

Purification of recombinant C. glabrata TIF31 protein typically requires a multi-step approach:

• Initial Extraction and Clarification:

  • For intracellular proteins from E. coli, cell lysis using sonication or mechanical disruption in appropriate buffer systems (typically Tris or phosphate-based buffers at pH 7.4-8.0)

  • Centrifugation at high speed (15,000-20,000 × g) to remove cell debris

• Affinity Chromatography:

  • If expressed with a His-tag (as with the TrxA-6xHis approach used for other C. glabrata proteins ), use nickel or cobalt affinity resins

  • Typical binding buffer: 50 mM Tris pH 8.0, 300 mM NaCl, 10 mM imidazole

  • Elution buffer: Same with 250-500 mM imidazole

• Tag Removal (if necessary):

  • If using a thrombin cleavage site similar to other C. glabrata proteins , incubate with thrombin (1-5 units per mg of fusion protein) at room temperature for 16-20 hours

  • Remove the cleaved tag by a second affinity chromatography step

• Further Purification:

  • Size exclusion chromatography to remove aggregates and ensure homogeneity

  • Ion exchange chromatography if charge-based separation is needed

• Quality Control:

  • SDS-PAGE analysis for purity

  • Western blot for identity confirmation

  • Activity assays specific to TIF31 function

Each step should be optimized based on the specific properties of TIF31, with particular attention to protein stability conditions.

How can I design effective functional assays for recombinant TIF31 from C. glabrata?

Designing effective functional assays for TIF31 requires understanding its potential biological roles. Based on approaches used for other C. glabrata proteins, consider:

• Protein Interaction Assays:

  • Pull-down assays using tagged TIF31 to identify binding partners

  • Yeast two-hybrid screening to detect protein-protein interactions

  • Co-immunoprecipitation with suspected interaction partners

• In vitro Activity Assays:

  • If TIF31 has predicted enzymatic activity, design substrate conversion assays

  • For potential nucleic acid binding, use electrophoretic mobility shift assays (EMSA)

• Cellular Assays:

  • Complement TIF31-deficient strains with recombinant protein to assess functional recovery

  • Overexpression studies to observe phenotypic effects

  • Localization studies using fluorescently tagged TIF31

• Infection Models:

  • Galleria mellonella larvae model, which has been effectively used to study C. glabrata virulence factors

  • Cell culture infection models with human epithelial or immune cells

  • Assess differences in virulence between wild-type and TIF31-modified strains

When designing these assays, include appropriate controls such as heat-inactivated protein, unrelated proteins of similar size, and empty vector controls for expression studies.

What gene deletion strategies are most effective for studying TIF31 function in C. glabrata?

Based on established methods for C. glabrata gene deletion described in the research literature, an effective approach includes:

• Design of Deletion Cassette:

  • Amplify approximately 500 bp homologous flanking regions of the TIF31 gene

  • Clone these regions into an appropriate vector (e.g., pBEVY-L)

  • Include a selectable marker between the flanking regions

• Transformation Protocol:

  • Use the lithium acetate method adapted for C. glabrata

  • Prepare the deletion cassette by digesting the recombinant plasmid with appropriate restriction enzymes

  • Transform C. glabrata cells and select on appropriate media

• Confirmation of Deletion:

  • PCR verification using primers binding outside the integration region

  • Quantitative RT-PCR to confirm absence of transcript

  • Western blotting to confirm absence of protein (if antibodies are available)

• Phenotypic Analysis:

  • Growth assays under various conditions

  • Stress response tests (oxidative, osmotic, temperature)

  • Virulence assessment in infection models such as G. mellonella

• Complementation Studies:

  • Reintroduce the TIF31 gene to confirm that phenotypic changes are due to the deletion

  • Consider expressing TIF31 under both native and constitutive promoters

For maximum reliability, generate and analyze at least two independent transformants for each genetic modification .

How does TIF31 contribute to the pathogenicity of Candida glabrata infections?

Investigating TIF31's role in C. glabrata pathogenicity requires a multi-faceted approach similar to studies of other virulence determinants:

• Virulence Assessment in Model Systems:

  • Compare wild-type and TIF31-deficient strains in the G. mellonella model, which has successfully identified other C. glabrata virulence factors

  • Measure larval survival rates, fungal burden, and host immune responses

  • Consider murine models for more complex host-pathogen interaction studies

• Host Cell Interaction Studies:

  • Adherence assays to epithelial and endothelial cells

  • Invasion and internalization quantification

  • Host cell damage assessment using cytotoxicity assays

• Immune Evasion Capabilities:

  • Resistance to phagocytosis by macrophages and neutrophils

  • Survival within phagocytic cells

  • Modulation of host cytokine responses

• Contribution to Biofilm Formation:

  • Quantitative biofilm formation assays comparing wild-type and TIF31-deficient strains

  • Analysis of extracellular matrix composition

  • Antifungal resistance testing of biofilms

• Interspecies Interactions:

  • As C. glabrata often co-infects with C. albicans, examine whether TIF31 affects interactions between these species

  • Determine if TIF31 influences mixed-species biofilms or signaling similar to the Yhi1 protein, which mediates interactions between C. glabrata and C. albicans

The invasive candidiasis model presents a particularly relevant context, as C. glabrata accounts for 15-25% of such cases and often exhibits high mortality when reaching the bloodstream .

What structural features of TIF31 are critical for its function, and how can they be characterized?

Characterizing the critical structural features of TIF31 requires a combination of computational prediction and experimental validation:

• Computational Structure Analysis:

  • Homology modeling based on related proteins with known structures

  • Prediction of functional domains and motifs

  • Molecular dynamics simulations to identify flexible regions

  • Docking studies with potential interaction partners

• Experimental Structure Determination:

  • X-ray crystallography of the purified protein (may require optimization of crystallization conditions)

  • NMR spectroscopy for solution structure (particularly useful for flexible regions)

  • Cryo-electron microscopy for larger complexes

• Structure-Function Relationships:

  • Site-directed mutagenesis of predicted key residues

  • Expression of truncated variants to identify minimal functional domains

  • Look for motifs similar to the novel AXVXH pentapeptide motif identified in other C. glabrata proteins

• Functional Validation of Structural Elements:

  • Complementation studies with mutant variants in TIF31-deficient strains

  • In vitro activity assays with purified mutant proteins

  • Binding studies to quantify effects on protein-protein interactions

A systematic approach similar to that used for identifying functional motifs in the Yhi1 protein could be particularly effective. This would involve generating truncated versions of TIF31 and testing their functionality, then refining the analysis to identify specific motifs or residues critical for function.

How does antifungal resistance correlate with TIF31 expression in clinical isolates of C. glabrata?

Investigating the relationship between TIF31 expression and antifungal resistance in clinical isolates requires:

• Clinical Isolate Collection and Characterization:

  • Obtain diverse C. glabrata clinical isolates from different geographical regions and patient populations

  • Determine minimum inhibitory concentrations (MICs) for various antifungals, particularly azoles like fluconazole that C. glabrata is often resistant to

  • Generate a resistance profile for each isolate

• TIF31 Expression Analysis:

  • Quantitative RT-PCR to measure TIF31 transcript levels under standard conditions and antifungal stress

  • Western blotting to quantify protein levels if antibodies are available

  • Promoter analysis to identify potential regulatory elements responsive to drug stress

• Correlation Analysis:

  • Statistical analysis correlating TIF31 expression with MIC values

  • Multivariate analysis accounting for other known resistance factors

  • Time-course studies to determine if expression changes precede or follow resistance development

• Functional Validation:

  • Overexpression of TIF31 in susceptible strains to test for increased resistance

  • Deletion or downregulation in resistant strains to test for restored susceptibility

  • Heterologous expression in model organisms like S. cerevisiae to isolate TIF31's effect

• Mechanistic Studies:

  • Investigation of TIF31's potential interaction with known resistance mechanisms (e.g., efflux pumps, drug target modifications)

  • Analysis of TIF31's effect on cell wall integrity, which can influence drug penetration

  • Examination of TIF31's role in stress response pathways activated by antifungal exposure

This approach would help determine whether TIF31 could serve as a biomarker for resistance or a potential target for combination therapies to overcome resistance.

What are common pitfalls in recombinant expression of C. glabrata proteins and how can they be addressed?

Common challenges in recombinant expression of C. glabrata proteins include:

When troubleshooting, systematically vary one parameter at a time and maintain detailed records of conditions and outcomes. For particularly challenging proteins, consider screening multiple constructs in parallel with varying truncations or fusion partners.

How can I develop specific antibodies against C. glabrata TIF31 protein for research applications?

Developing specific antibodies against C. glabrata TIF31 involves several key steps:

• Antigen Design and Preparation:

  • Full-length recombinant TIF31 protein purified as described previously

  • Synthetic peptides corresponding to predicted immunogenic regions (typically 10-20 amino acids)

  • Consider multiple antigens targeting different regions for increased specificity

• Immunization Strategy:

  • For polyclonal antibodies: immunize rabbits with purified antigen in suitable adjuvant

  • For monoclonal antibodies: immunize mice followed by hybridoma technology

  • Typical immunization protocol includes primary immunization and 3-4 booster shots

• Antibody Screening and Validation:

  • ELISA screening against the immunizing antigen

  • Western blotting against recombinant TIF31 and C. glabrata lysates

  • Immunoprecipitation to confirm native protein recognition

  • Additional validation in TIF31-deleted strains as negative controls

• Cross-Reactivity Testing:

  • Test against lysates from related Candida species

  • Evaluate reactivity with human proteins to ensure specificity

  • Perform epitope mapping to understand the molecular basis of recognition

• Application-Specific Optimization:

  • For Western blotting: determine optimal antibody concentration and blocking conditions

  • For immunofluorescence: test fixation methods and antibody penetration

  • For immunoprecipitation: optimize buffer conditions and bead types

Alternatively, epitope tagging of TIF31 (e.g., with FLAG, HA, or c-Myc) can provide a reliable detection method using commercially available antibodies, particularly useful for initial studies while specific antibodies are being developed.

What are the most reliable methods for quantifying TIF31 expression levels in different C. glabrata growth conditions?

For reliable quantification of TIF31 expression under different growth conditions, consider these complementary approaches:

• Transcriptional Analysis:

  • Quantitative RT-PCR (RT-qPCR) with carefully validated primers

  • RNA-Seq for genome-wide expression context

  • Controls: multiple reference genes stable under your experimental conditions

• Protein-Level Analysis:

  • Western blotting with specific antibodies or epitope tags

  • ELISA for quantitative measurements

  • Mass spectrometry-based proteomics for unbiased quantification

  • Controls: loading controls stable under your experimental conditions

• Reporter Systems:

  • TIF31 promoter fusion to reporters like GFP or luciferase

  • Construction similar to that used for other C. glabrata proteins

  • Controls: constitutive promoter reporters in parallel

• Single-Cell Analysis:

  • Flow cytometry with fluorescent reporters or antibodies

  • Fluorescence microscopy for localization and heterogeneity assessment

  • Controls: analyze multiple time points to capture dynamic changes

• Standardization Practices:

  • Normalize to cell number, total RNA, or total protein as appropriate

  • Include biological replicates (n≥3) and technical replicates

  • Include positive controls (conditions expected to change expression)

  • Use consistent harvesting methods to avoid introducing variability

For growth conditions, systematically test variables relevant to C. glabrata pathophysiology, including:

• Growth phase (lag, log, stationary)

• Nutrient limitation (carbon, nitrogen, phosphate)

• Environmental stressors (oxidative, pH, temperature)

• Antifungal exposure (sub-inhibitory concentrations)

• Host-relevant conditions (serum, macrophage co-culture)

A combination of these approaches provides the most comprehensive and reliable assessment of TIF31 expression patterns.

How might TIF31 serve as a potential target for novel antifungal strategies?

Evaluating TIF31 as a potential antifungal target requires systematic investigation:

• Target Validation:

  • Determine if TIF31 is essential for C. glabrata viability or virulence

  • Compare phenotypes of TIF31-deficient strains in vitro and in infection models

  • Assess conservation across pathogenic fungi versus humans to identify selectivity potential

• Druggability Assessment:

  • Structural analysis to identify potential binding pockets

  • In silico screening of compound libraries against TIF31 structure

  • Fragment-based screening approaches

• Inhibitor Development Strategy:

  • High-throughput screening of compound libraries against TIF31 function

  • Structure-based design of inhibitors targeting critical domains

  • Peptide-based inhibitors targeting protein-protein interactions

  • Consider approaches similar to those used for developing inhibitors against the AXVXH pentapeptide motif found in other C. glabrata proteins

• Inhibitor Evaluation Pipeline:

  • In vitro activity against purified TIF31

  • Cell-based assays in C. glabrata cultures

  • Specificity testing against human homologs

  • Efficacy in infection models (e.g., G. mellonella )

  • Pharmacokinetic and toxicity studies

• Combination Therapy Potential:

  • Test TIF31 inhibitors in combination with existing antifungals

  • Evaluate synergistic effects, particularly against resistant strains

  • Investigate potential for resistance development

This approach could be particularly valuable given the increasing prevalence of antifungal resistance in C. glabrata, especially to commonly used azole drugs .

Can TIF31 expression or mutations serve as biomarkers for C. glabrata virulence or drug resistance?

Exploring TIF31's potential as a biomarker requires:

• Clinical Sample Analysis:

  • Collect C. glabrata isolates from diverse clinical scenarios (superficial vs. invasive infections)

  • Sequence TIF31 to identify polymorphisms or mutations

  • Quantify expression levels in clinical isolates

• Correlation with Clinical Outcomes:

  • Track patient outcomes (treatment success, mortality)

  • Analyze TIF31 variations in relation to disease severity and treatment response

  • Develop multivariate models incorporating TIF31 and other factors

• Predictive Biomarker Development:

  • Identify specific TIF31 patterns associated with virulence or resistance

  • Develop rapid detection methods (PCR, LAMP, antibody-based)

  • Validate in prospective clinical studies

• Integration with Other Biomarkers:

  • Combine TIF31 analysis with other known virulence or resistance markers

  • Develop scoring systems for risk stratification

  • Create decision algorithms for treatment selection

The potential for TIF31 as a biomarker is supported by precedents with other C. glabrata proteins. For example, researchers have identified the potential of the Yhi1 protein as a biomarker for mixed-species infections involving C. glabrata and C. albicans . Similar approaches could be applied to TIF31, particularly if it shows consistent patterns of expression or mutation in specific clinical scenarios.

What are the ethical considerations in developing research tools targeting C. glabrata proteins like TIF31?

Ethical considerations in developing research tools for C. glabrata proteins include:

• Biosafety and Biosecurity:

  • Appropriate containment measures for working with pathogenic fungi

  • Risk assessment for genetic modifications

  • Protocols for preventing laboratory-acquired infections

  • Consideration of dual-use research potential

• Research Integrity:

  • Transparent reporting of methods and results

  • Validation using multiple approaches and controls

  • Addressing conflicts of interest

  • Responsible sharing of materials and data

• Clinical Sample Ethics:

  • Proper informed consent for patient-derived isolates

  • Protection of patient privacy and data

  • Equitable sampling across diverse populations

  • Consideration of return of results when relevant

• Animal Research Ethics:

  • Implementation of the 3Rs (Replacement, Reduction, Refinement)

  • Justification for animal models when alternatives are insufficient

  • Humane endpoints in infection models

  • Appropriate statistical design to minimize animal use

• Responsible Innovation:

  • Consideration of downstream applications and implications

  • Engagement with diverse stakeholders, including patient groups

  • Attention to global health equity in tool development

  • Sustainable and accessible development pathways

Researchers should engage with institutional review boards, ethics committees, and biosafety committees early in the research planning process to ensure compliance with institutional, national, and international guidelines.

What emerging technologies might enhance our understanding of TIF31 function in C. glabrata?

Several cutting-edge technologies hold promise for advancing TIF31 research:

• CRISPR-Cas9 Applications:

  • Precise genome editing for functional domain analysis

  • CRISPRi for tunable gene repression

  • CRISPRa for controlled overexpression

  • Base editing for introducing specific mutations

• Single-Cell Technologies:

  • Single-cell RNA-seq to explore expression heterogeneity

  • Single-cell proteomics for protein-level analysis

  • Spatial transcriptomics to understand expression in biofilms or tissues

  • Live cell imaging with advanced fluorescent reporters

• Structural Biology Advances:

  • Cryo-EM for high-resolution structure determination

  • Integrative structural biology combining multiple data types

  • Hydrogen-deuterium exchange mass spectrometry for dynamics

  • AlphaFold2 and other AI-based structure prediction tools

• Interactomics Approaches:

  • Proximity labeling (BioID, APEX) to identify interaction partners

  • Protein microarrays for systematic interaction screening

  • Cross-linking mass spectrometry for structural interactomics

  • Thermal proteome profiling for drug-target engagement

• Advanced In Vivo Imaging:

  • Intravital microscopy to observe fungal-host interactions

  • Whole-body imaging with fungal-specific probes

  • Host-pathogen dual reporters for simultaneous visualization

  • Correlative light and electron microscopy for ultrastructural context

These technologies could be particularly valuable for understanding TIF31's role in C. glabrata pathogenicity and its potential interactions with other virulence factors, similar to the approaches that revealed the role of Yhi1 in mediating interactions between C. glabrata and C. albicans .

How might systems biology approaches enhance our understanding of TIF31 in the context of C. glabrata pathogenicity?

Systems biology approaches offer powerful frameworks for understanding TIF31 within the broader context of C. glabrata biology:

• Multi-omics Integration:

  • Combine transcriptomics, proteomics, and metabolomics data

  • Map TIF31 onto known biological networks

  • Identify condition-specific regulatory modules

  • Develop predictive models of TIF31 regulation and function

• Network Analysis:

  • Construct protein-protein interaction networks including TIF31

  • Perform gene co-expression analysis across multiple conditions

  • Identify network motifs and regulatory circuits

  • Compare networks between drug-sensitive and resistant strains

• Evolutionary Systems Biology:

  • Comparative analysis across Candida species

  • Identification of selective pressures on TIF31

  • Analysis of co-evolving gene clusters

  • Reconstruction of ancestral states and evolutionary trajectories

• Host-Pathogen Systems Biology:

  • Dual RNA-seq of host and pathogen during infection

  • Modeling of host-pathogen protein interactions

  • Identification of infection-induced network perturbations

  • Prediction of critical nodes for intervention

• Computational Modeling:

  • Flux balance analysis incorporating TIF31 function

  • Agent-based modeling of infection dynamics

  • Machine learning approaches to identify patterns in complex datasets

  • In silico prediction of genetic interaction networks

These approaches can place TIF31 in its biological context, potentially revealing unexpected connections to virulence mechanisms and drug resistance pathways, similar to how systems approaches have illuminated the roles of other C. glabrata proteins in pathogenicity .

What interdisciplinary collaborations might accelerate research on C. glabrata TIF31 and similar fungal proteins?

Productive interdisciplinary collaborations for advancing TIF31 research include:

• Clinical Microbiology and Infectious Disease:

  • Access to diverse clinical isolates

  • Correlation of laboratory findings with clinical outcomes

  • Translation of research findings into diagnostic tools

  • Identification of clinically relevant research questions

• Structural Biology and Biophysics:

  • High-resolution structure determination

  • Protein dynamics and conformational studies

  • Interaction interface mapping

  • Structure-based drug design

• Immunology:

  • Host immune response to C. glabrata infection

  • Innate immune evasion mechanisms

  • Adaptive immunity to fungal antigens

  • Immunomodulatory effects of fungal proteins

• Bioinformatics and Computational Biology:

  • Genome mining for novel antifungal targets

  • Evolutionary analysis across fungal species

  • Network modeling and systems biology

  • AI-assisted protein function prediction

• Pharmaceutical Sciences and Medicinal Chemistry:

  • Small molecule screening and optimization

  • Drug delivery to intracellular fungi

  • Formulation development for antifungal compounds

  • Pharmacokinetic and pharmacodynamic modeling

Collaborative approaches have proven valuable in other fungal protein research, as exemplified by the multidisciplinary techniques used to characterize the novel AXVXH pentapeptide motif in the Yhi1 protein . Similar interdisciplinary efforts could significantly accelerate understanding of TIF31 function and its potential applications in diagnosing and treating C. glabrata infections.