Recombinant Candida glabrata Translation factor GUF1, mitochondrial (GUF1), partial

How does GUF1 expression change during different growth phases and stress conditions in C. glabrata?

Expression analysis of mitochondrial factors in C. glabrata reveals dynamic regulation patterns across growth phases and stress conditions. While specific GUF1 expression data is not extensively documented, similar mitochondrial factors show significant temporal regulation during macrophage infection.

To effectively study GUF1 expression changes:

• Use RNA polymerase II ChIP-seq time course analysis to track transcriptional changes over time (similar to approaches used for other C. glabrata factors)

• Implement qRT-PCR to quantify expression levels under various conditions

• Employ reporter constructs (GFP/luciferase fusions) to monitor expression in real-time

For example, when studying transcriptional responses in C. glabrata during macrophage infection, researchers identified distinct temporal expression patterns across different timepoints (0.5, 2, 4, and 6 hr post-infection), with approximately 1,500 genes showing significant expression changes . Similar approaches could reveal how GUF1 responds to phagocytosis, oxidative stress, nutrient limitation, and antifungal exposure.

What experimental systems are optimal for expressing recombinant C. glabrata GUF1?

For optimal expression of recombinant C. glabrata GUF1:

Expression Systems Comparison:

For initial characterization, the C. glabrata BG2 strain (commonly used as wild-type and parental strain for genetic modifications) provides an authentic context for GUF1 expression . Culture this strain overnight (14-16 hr) in YPD medium at 30°C with shaking at 200 rpm to establish optimal growth conditions before protein extraction or gene manipulation .

For heterologous expression, codon-optimization is essential due to C. glabrata's distinct codon usage patterns, which differ from both S. cerevisiae and E. coli.

What are the most effective methods for creating GUF1 knockout or modified strains in C. glabrata?

Creating genetically modified C. glabrata strains requires specialized approaches due to this organism's inherent resistance mechanisms and unique genetic properties:

Recommended Protocol:

• Design targeting constructs with long homology arms (>500 bp) flanking the GUF1 locus

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

• Implement the lithium acetate transformation protocol optimized for C. glabrata

• Confirm genetic modifications through both PCR verification and sequencing

• Validate phenotypic consequences through complementation studies

When creating knockouts, it's critical to maintain isogenic backgrounds to ensure accurate phenotypic comparisons. Based on approaches used for other C. glabrata genes, transforming the modified construct into the BG2 strain is recommended as this strain serves as the standard wild-type for most C. glabrata studies .

For complementation studies, reintroduce the wild-type GUF1 gene on a low-copy plasmid to confirm that observed phenotypes result specifically from GUF1 disruption rather than unintended secondary mutations, following the validation approach used for other C. glabrata genes such as FEN1 .

How can researchers effectively analyze GUF1's role in mitochondrial translation and C. glabrata virulence?

To systematically investigate GUF1's role in mitochondrial translation and virulence:

Experimental Framework:

• Transcriptome Analysis: Use RNA-seq or RNAPII ChIP-seq to compare wild-type and Δguf1 strains, particularly during macrophage infection or stress conditions. This approach can identify genes whose expression depends on GUF1 function, similar to methods used for analyzing CgXbp1-dependent transcriptional responses .

• Mitochondrial Function Assays:

  • Oxygen consumption rate measurements

  • Mitochondrial membrane potential assessment using fluorescent dyes

  • ATP production quantification under various growth conditions

• Virulence Assessment:

  • Macrophage survival assays: Compare colony-forming unit (CFU) counts between wild-type and Δguf1 mutants at 2, 8, and 24 hours post-infection to quantify survival and proliferation within phagocytes

  • Mouse models of colonization and infection: Assess fungal burden in tissues over time

  • Competitive fitness assays: Co-infect with wild-type and mutant strains to directly compare fitness in vivo

For macrophage infection models, THP-1 cells cultured in RPMI medium supplemented with glutamine, antibiotics, and heat-denatured serum provide a standardized system for assessing C. glabrata survival and proliferation . When analyzing fungal survival in macrophages, normalize CFU counts at later timepoints (8hr, 24hr) to the 2hr timepoint to account for potential differences in initial phagocytosis rates .

What approaches should be used to study GUF1 protein interactions within the mitochondrial translation machinery?

For comprehensive characterization of GUF1 protein interactions:

Multi-faceted Interaction Analysis:

• Co-immunoprecipitation (Co-IP): Using epitope-tagged GUF1 to pull down interacting partners, followed by mass spectrometry identification

• Proximity-based labeling: BioID or APEX2 fusion proteins to identify proximal proteins in intact mitochondria

• Yeast two-hybrid screening: Modified for mitochondrial proteins using appropriate bait and prey constructs

• Cryo-EM structural studies: For visualizing GUF1 within the mitochondrial ribosome complex

When designing interaction studies, consider the potential role of GUF1 within broader transcriptional regulatory networks. In C. glabrata, mitochondrial factors often interact with nuclear-encoded regulators controlling diverse physiological pathways important for virulence, including carbon metabolism, amino acid biosynthesis, and stress responses .

For protein complex analysis, density gradient centrifugation can effectively separate mitochondrial ribosomal complexes with and without associated GUF1, revealing its dynamic association with the translation machinery under different conditions.

How does GUF1 function intersect with antifungal resistance mechanisms in C. glabrata?

The relationship between mitochondrial function and antifungal resistance in C. glabrata represents a complex and clinically significant research area:

Potential Mechanisms and Experimental Approaches:

• Echinocandin Resistance: While direct evidence linking GUF1 to echinocandin resistance is limited, mitochondrial factors may influence cell wall integrity and sphingolipid composition, which affect echinocandin susceptibility. Test MIC values for echinocandins in Δguf1 strains compared to wild-type, particularly focusing on caspofungin sensitivity changes .

• Azole Resistance: Investigate whether GUF1 influences expression of azole resistance genes regulated by transcription factors like CgPdr1. CgPdr1 governs multiple ATP-binding cassette transporters (including CgCDR1, CgCDR2, and CgSNQ2) that mediate azole resistance . Compare transcriptional profiles of azole resistance genes between wild-type and Δguf1 strains using qRT-PCR or RNA-seq.

• Metabolic Adaptation: Assess whether GUF1 disruption alters metabolic flexibility and cellular energetics, potentially affecting the fitness cost of resistance mutations. Design experiments measuring growth rates and competitive fitness of Δguf1 strains with and without resistance mutations in different carbon sources.

For comprehensive analysis, implement time-course experiments during antifungal exposure, as temporal dynamics of gene expression are critical in C. glabrata's adaptive responses. The rapid emergence and diversification of drug-adapted strains observed during caspofungin treatment suggests similar dynamic processes may occur with other mitochondrially-influenced resistance mechanisms .

How can researchers resolve contradictory findings related to mitochondrial translation factors in different Candida species?

Resolving contradictory findings across Candida species requires systematic comparative approaches:

Methodological Framework:

• Standardized Experimental Conditions: Implement identical growth conditions, genetic backgrounds, and phenotypic assays when comparing homologous factors across species. Culture all species using the same media formulations, temperature, and growth phase to minimize experimental variables.

• Cross-Species Complementation: Create chimeric constructs or perform heterologous expression to determine if functional differences are intrinsic to the protein or dependent on cellular context. For example, express C. glabrata GUF1 in C. albicans Δguf1 strains and vice versa.

• Evolutionary Analysis: Examine sequence conservation, selection pressure, and evolutionary history of GUF1 across Candida species to identify potential species-specific adaptations. Calculate Ka/Ks ratios to identify regions under positive selection.

• Multi-omics Integration: Combine transcriptomics, proteomics, and metabolomics data to place contradictory findings within broader cellular contexts. This approach can reveal species-specific regulatory networks that might explain functional differences.

When interpreting contradictory results, consider that C. glabrata is phylogenetically closer to Saccharomyces cerevisiae than to C. albicans, despite its pathogenic lifestyle . This evolutionary distance often results in significant functional differences between seemingly homologous proteins across Candida species.

What are the critical considerations for designing in vivo experiments to assess GUF1's role in C. glabrata pathogenesis?

Designing robust in vivo experiments requires careful consideration of multiple factors:

Experimental Design Considerations:

• Animal Model Selection:

  • For gastrointestinal colonization: Use immunocompetent mice with antibiotic pretreatment to establish stable colonization, similar to models used for studying evolutionary dynamics during antifungal treatment

  • For disseminated infection: Consider neutropenic mouse models that better replicate human invasive candidiasis

  • For organ-specific colonization: Develop targeted models for kidney, liver, or brain infection

• Infection Parameters:

  • Inoculum preparation: Standardize growth phase and cell counts

  • Administration route: Select appropriate for target tissue (intravenous for systemic, oral gavage for GI)

  • Infection duration: Design time-course studies capturing both early (24-48h) and late (7-14 day) infection stages

• Readout Methods:

  • Fungal burden quantification: CFU counts from homogenized tissues

  • Competitive fitness assays: Co-infection with differentially marked strains

  • Host response analysis: Cytokine profiling, immune cell recruitment, histopathology

• Experimental Controls:

  • Include complemented strains (Δguf1+GUF1) to confirm phenotype specificity

  • Compare multiple independently generated mutants to rule out secondary mutations

  • Include relevant control strains with known virulence phenotypes

When monitoring fungal colonization dynamics, implement amplicon sequencing approaches to track the emergence and abundance of both wild-type and mutant populations over time, similar to methods used to study evolutionary dynamics of C. glabrata during caspofungin treatment .

What emerging technologies offer new insights into GUF1 function and regulation in C. glabrata?

Several cutting-edge technologies are poised to revolutionize our understanding of mitochondrial translation factors:

Transformative Methodologies:

• CRISPRi/CRISPRa Systems: These allow for tunable repression or activation of GUF1 expression without permanent genetic modification, enabling precise temporal control for studying essential genes. Implement dCas9-based systems optimized for C. glabrata's genetic background.

• Single-Cell Transcriptomics: This technology can reveal population heterogeneity in GUF1 expression and identify distinct subpopulations with altered expression patterns during infection or stress. Compare expression profiles at single-cell resolution between in vitro cultures and cells recovered from infection models.

• Ribosome Profiling: This technique provides nucleotide-resolution insights into translational dynamics, revealing how GUF1 affects mitochondrial translation efficiency and accuracy under different conditions. Implement mitochondria-specific ribosome profiling protocols to capture organelle-specific translation dynamics.

• Advanced Imaging Technologies:

  • Super-resolution microscopy for visualizing GUF1 distribution within mitochondria

  • Live-cell imaging with genetically encoded biosensors to track GUF1 activity in real-time

  • Correlative light and electron microscopy (CLEM) to link GUF1 function to mitochondrial ultrastructure

• Mitochondrial Metabolomics: Comprehensive profiling of mitochondrial metabolites can link GUF1 function to specific metabolic pathways and energy production processes. Implement stable isotope labeling to track carbon flux through mitochondrial pathways in wild-type versus Δguf1 strains.

Similar high-resolution temporal analyses to those used for studying C. glabrata transcriptional responses during macrophage infection could be adapted to study GUF1's dynamic function under changing environmental conditions .

How might understanding GUF1 function contribute to novel therapeutic approaches for Candida glabrata infections?

Understanding GUF1's role could lead to several therapeutic innovations:

Therapeutic Implications:

• Target Validation: Determine if GUF1 represents a viable drug target by assessing:

  • Essentiality under infection-relevant conditions

  • Conservation and structural differences from human homologs

  • Accessibility to small molecule inhibitors

  • Phenotypic consequences of inhibition in vitro and in vivo

• Combination Therapy Strategies: Investigate whether GUF1 inhibition could synergize with existing antifungals by:

  • Testing combinations with echinocandins, azoles, and polyenes

  • Measuring fractional inhibitory concentration indices (FICI)

  • Assessing resistance development rates in combination versus monotherapy

• Biomarker Development: Explore GUF1 as a potential biomarker for:

  • Predicting antifungal susceptibility profiles

  • Monitoring treatment efficacy through detection of GUF1-related metabolites

  • Identifying virulent versus commensal C. glabrata strains

• Host-Directed Therapeutics: Examine how host cells interact with GUF1-dependent processes by:

  • Characterizing mitochondrial dynamics during host-pathogen interactions

  • Identifying host factors that modulate GUF1 function

  • Developing strategies to enhance host recognition of GUF1-deficient strains

The high mortality rate (30-60%) associated with Candida infections in immunocompromised populations underscores the urgent need for novel therapeutic approaches . GUF1's potential role in both virulence and drug resistance makes it particularly relevant for therapeutic development.

What are the most significant gaps in our current understanding of mitochondrial translation factors in fungal pathogens?

Critical knowledge gaps include:

Research Priorities:

• Tissue-Specific Expression Patterns: Little is known about how GUF1 expression varies across different infection sites. Design studies comparing GUF1 expression in C. glabrata isolated from blood, kidney, gastrointestinal tract, and urinary tract infections.

• Post-Translational Modifications: The regulatory mechanisms controlling GUF1 activity through PTMs remain largely unexplored. Implement phosphoproteomics, acetylomics, and other PTM-specific analyses to characterize GUF1 modifications under different conditions.

• Strain Variation: Natural variation in GUF1 sequence and expression across clinical isolates is poorly characterized. Sequence GUF1 from diverse clinical isolates and correlate variations with phenotypic differences in virulence and drug resistance.

• Integration with Nuclear Genome: How mitochondrial translation coordinates with nuclear gene expression during infection remains unclear. Investigate communication between mitochondrial and nuclear compartments during host-pathogen interactions.

• Evolutionary Adaptations: The selective pressures driving mitochondrial translation factor evolution in fungal pathogens are not well understood. Compare selection signatures on GUF1 between commensal and pathogenic fungi to identify pathogenesis-related adaptations.

These research gaps align with broader challenges in understanding C. glabrata pathogenesis, including how this organism survives, adapts, and proliferates in phagocytes, and the molecular basis for its intrinsically high azole resistance .

What are the optimal storage and handling conditions for recombinant C. glabrata GUF1 protein?

Proper storage and handling are critical for maintaining GUF1 activity:

Stability and Storage Protocol:

For activity assays, always include positive controls with fresh protein preparations to normalize for activity loss during storage. When using tagged recombinant GUF1, verify that the tag doesn't interfere with protein function through comparative activity assays with untagged versions.

Activity should be monitored using GTPase assays under standardized conditions (37°C, pH 7.4) that reflect the physiological environment encountered during infection.

How can researchers effectively troubleshoot expression and purification challenges specific to C. glabrata GUF1?

Common challenges and solutions include:

Troubleshooting Guide:

• Low Expression Yield:

  • Problem: GUF1 expression levels are below detection threshold

  • Solutions:

    • Optimize codon usage for expression host

    • Test different promoters (constitutive vs. inducible)

    • Adjust induction parameters (temperature, inducer concentration, duration)

    • Screen multiple expression strains

• Inclusion Body Formation:

  • Problem: GUF1 forms insoluble aggregates

  • Solutions:

    • Express at lower temperatures (16-20°C)

    • Co-express with molecular chaperones

    • Use solubility-enhancing fusion tags (MBP, SUMO)

    • Develop refolding protocols if necessary

• Proteolytic Degradation:

  • Problem: GUF1 shows degradation bands on SDS-PAGE

  • Solutions:

    • Include protease inhibitor cocktail during purification

    • Use protease-deficient expression strains

    • Optimize buffer conditions to reduce protease activity

    • Perform purification at 4°C with minimal handling time

• Poor Binding to Affinity Resins:

  • Problem: Tagged GUF1 shows low affinity for purification resins

  • Solutions:

    • Test alternate tag positions (N vs. C-terminal)

    • Optimize binding conditions (salt concentration, pH, detergents)

    • Use longer linkers between GUF1 and affinity tag

    • Consider alternative purification strategies

When developing a purification strategy, implement a similar approach to that used for other C. glabrata proteins, with initial cultures grown overnight in YPD medium at 30°C and 200 rpm prior to induction and protein extraction .