Recombinant Candida glabrata Ubiquitin-related modifier 1 (URM1)

What is Ubiquitin-related Modifier 1 (URM1) in Candida glabrata and how does it differ from other ubiquitin-like modifiers?

URM1 belongs to the ubiquitin-like modifier family but represents one of the most ancient members with distinct evolutionary characteristics. Unlike SUMO (Small Ubiquitin-like Modifier), which has been extensively studied in C. glabrata, URM1 has a more specialized role. URM1 functions through covalent attachment to target proteins via a cascade involving E1-like activating enzyme (Uba4) and lacks the requirement for E3 ligases that are essential in SUMO conjugation pathways. In C. glabrata, URM1 shares the common ubiquitin-like structural fold but plays distinct roles in cellular processes compared to other modifiers such as SUMO, which has been shown to be critical for protein homeostasis and stress responses as demonstrated in CgUlp2 deSUMOylase studies . To study these differences experimentally, researchers typically employ comparative proteomic approaches using affinity-tagged recombinant URM1 versus other modifiers to identify specific substrates and interaction partners.

How does URM1 contribute to C. glabrata pathogenesis and host interaction?

URM1 contributes to C. glabrata pathogenesis through multiple mechanisms. Research suggests that URM1 plays important roles in oxidative stress response pathways, which are crucial for C. glabrata to survive within host macrophages. Similar to other post-translational modification systems like SUMOylation, URM1ylation likely regulates key proteins involved in host-pathogen interactions. Studies have shown that protein modification systems are critical for C. glabrata's ability to adhere to epithelial cells and form biofilms, which are essential virulence factors . Additionally, protein homeostasis mechanisms are crucial for the proliferation of C. glabrata in macrophages, as demonstrated in studies of SUMO-targeted ubiquitin ligase pathways . To investigate URM1's specific role in pathogenesis, researchers should employ infection models using URM1 pathway mutants and analyze their ability to survive in macrophages, adhere to epithelial surfaces, and form biofilms.

What expression systems are most effective for producing recombinant C. glabrata URM1?

For producing recombinant C. glabrata URM1, several expression systems have been employed with varying efficacy. The most reliable approaches include:

• E. coli-based expression systems: Using BL21(DE3) strains with pET-based vectors incorporating His-tags or GST-tags for purification. Optimal expression is typically achieved at lower temperatures (16-20°C) after IPTG induction to enhance proper folding.

• Yeast expression systems: S. cerevisiae expression using CEN-based plasmids with moderate strength promoters has shown good yield of properly folded URM1. Based on methodologies used for related proteins, transformation of C. glabrata can be performed using PCR-amplified cassettes as described for other genetic manipulations .

• Mammalian cell expression: For studies requiring post-translational modifications similar to those in human cells, HEK293T cells transfected with vectors containing CMV promoters can be used.

Each system has advantages, with bacterial systems offering higher yields but potentially lacking certain modifications, while yeast-based systems may provide more authentic folding and modifications. The choice depends on the experimental needs, with most structural and biochemical studies favoring bacterial expression with optimization of solubility.

How can researchers effectively identify and validate URM1 substrates in C. glabrata?

Identifying and validating URM1 substrates in C. glabrata requires a multi-faceted approach. Based on methodologies applied to related modification pathways, the following protocol is recommended:

• Proteomics-based identification:

  • Express His-tagged URM1 in C. glabrata under native promoter or controlled inducible promoter

  • Perform nickel affinity purification under denaturing conditions to maintain conjugates

  • Analyze captured proteins by mass spectrometry with specific focus on branch peptides

• Candidate validation approaches:

  • Generate epitope-tagged versions of candidate proteins using homologous recombination techniques similar to those described for Mdm34-mCherry tagging

  • Perform immunoprecipitation followed by western blotting to confirm URM1 conjugation

  • Create lysine-to-arginine mutants at predicted conjugation sites to confirm specific attachment

• Functional validation:

  • Generate deletion mutants of identified substrates using established homologous recombination methods with appropriate markers such as HIS3 or nourseothricin resistance

  • Assess phenotypes related to known URM1 functions (oxidative stress resistance, mitochondrial function)

  • Perform complementation assays with wild-type and lysine mutant versions

This comprehensive workflow enables reliable identification and validation of URM1 substrates, which is critical for understanding its biological functions in C. glabrata pathophysiology.

What are the optimal conditions for studying URM1-dependent tRNA modifications in C. glabrata?

URM1 plays a critical role in tRNA thiolation, particularly of the wobble uridine (U34) in certain tRNAs. For optimal study of URM1-dependent tRNA modifications in C. glabrata, the following methodological approach is recommended:

• Extraction of tRNAs:

  • Culture C. glabrata cells in both regular and stress conditions (oxidative stress, nutrient limitation)

  • Extract total RNA using acidic phenol method at 4°C to preserve tRNA integrity

  • Enrich for tRNAs using size exclusion chromatography or commercial kits

• Detection and analysis of thiolated tRNAs:

  • Use APM (N-acryloylamino phenyl mercuric chloride) gel electrophoresis to separate thiolated from non-thiolated tRNAs

  • Employ northern blotting with specific probes for tRNALys(UUU), tRNAGlu(UUC), and tRNAGln(UUG)

  • Validate findings with liquid chromatography-mass spectrometry (LC-MS) analysis

• Genetic manipulation:

  • Generate URM1 pathway mutants (Δurm1, Δuba4) using homologous recombination strategies

  • Use quantitative RT-PCR methods similar to those described for analyzing gene expression in C. glabrata

  • Complement mutants with plasmid-expressed wild-type or mutant versions of URM1

• Functional readouts:

  • Assess translational fidelity using reporter constructs

  • Measure growth rates under various stress conditions

  • Analyze proteome changes in URM1 pathway mutants

The connection between tRNA modification and stress response is particularly relevant for C. glabrata pathogenesis, as proper protein synthesis under stress conditions is critical for survival in the host environment.

How do mitochondrial dynamics influence URM1 function in C. glabrata, and what methods best capture this relationship?

The relationship between mitochondrial dynamics and URM1 function in C. glabrata represents an emerging area of research. Based on studies of related pathways, mitochondrial dysfunction can significantly impact protein modification systems and vice versa. To investigate this relationship:

• Visualization techniques:

  • Employ fluorescence microscopy using GFP-tagged URM1 and mitochondrial markers (such as Tom70-GFP) to track co-localization

  • Use time-lapse microscopy to monitor dynamic associations during normal growth and stress conditions

  • Apply super-resolution microscopy for detailed spatial analysis

• Genetic approaches:

  • Generate double mutants of URM1 pathway components and ERMES complex genes (GEM1, MDM10, MDM12, MDM34, MMM1) using sequential gene deletion strategies

  • Analyze genetic interactions through growth assays under various conditions

  • Quantify mitochondrial morphology changes using established fluorescence parameters

• Biochemical analyses:

  • Measure reactive oxygen species (ROS) levels using fluorescent probes like DCFH-DA

  • Assess mitochondrial membrane potential using JC-1 or TMRM staining

  • Quantify respiratory capacity through oxygen consumption measurements

• Proteomic assessment:

  • Isolate mitochondria and analyze URM1-conjugated proteins specific to this organelle

  • Compare the mitochondrial proteome between wild-type and URM1 pathway mutants

  • Map changes in protein modification patterns during mitochondrial stress

Studies on the ERMES complex in C. glabrata have shown that mitochondrial dysfunction leads to increased ROS production and activation of stress response pathways, which likely intersect with URM1-mediated processes . This relationship may be particularly important for understanding how C. glabrata adapts to the host environment during infection.

How can researchers reconcile contradictory data on URM1's role in C. glabrata drug resistance?

Conflicting data regarding URM1's role in antifungal resistance can be approached methodically. To reconcile contradictory findings:

• Strain background assessment:

  • Systematically evaluate the genetic background of C. glabrata strains used across studies

  • Perform whole genome sequencing to identify potential compensatory mutations

  • Use the same reference strain (such as ATCC 2001/CBS138) for comparative studies

• Standardization of resistance testing:

  • Employ standardized protocols for minimum inhibitory concentration (MIC) determination

  • Use both microdilution methods and E-test strips to confirm results

  • Test resistance under various growth conditions (pH, temperature, media composition)

• Mechanistic investigation:

  • Analyze expression of drug efflux pumps (CDR1, CDR2) in URM1 pathway mutants using quantitative RT-PCR

  • Assess membrane ergosterol content and composition

  • Measure intracellular drug accumulation using fluorescent azole analogs

• Cross-pathway analysis:

  • Investigate the interaction between URM1 and other stress response pathways

  • Generate double mutants with known resistance determinants

  • Analyze transcriptome changes in response to drug exposure in wild-type versus URM1 mutants

A methodical approach to these contradictions may reveal that URM1's role in drug resistance is context-dependent, possibly influenced by mitochondrial function, as observed with the ERMES complex where deletion of GEM1 increased azole resistance through mechanisms involving ROS production and drug efflux pump expression .

What statistical approaches are most appropriate for analyzing URM1 substrate proteomic data in C. glabrata?

Analysis of proteomic data for URM1 substrates requires robust statistical approaches to differentiate true substrates from background. The recommended statistical workflow includes:

• Data preprocessing:

  • Apply normalization methods appropriate for the specific mass spectrometry platform used

  • Perform log transformation of intensity values to approximate normal distribution

  • Implement missing value imputation using K-nearest neighbor or QRILC methods

• Statistical testing:

  • Apply moderated t-tests with multiple testing correction (Benjamini-Hochberg)

  • Implement SAINT (Significance Analysis of INTeractome) algorithm for spectral count data

  • Use volcano plots displaying both fold change and statistical significance

• Machine learning approaches:

  • Apply supervised learning algorithms to identify features of URM1 substrates

  • Use motif enrichment analysis to identify potential URM1 conjugation sites

  • Implement cluster analysis to group functionally related substrates

• Validation metrics:

  • Calculate false discovery rates using appropriate controls

  • Perform power analysis to determine sample size requirements

  • Implement bootstrapping to assess result stability

The following data table illustrates a typical analysis output for URM1 substrate identification:

This statistical approach ensures reliable identification of URM1 substrates while minimizing false positives, which is crucial for downstream functional studies.

How should researchers interpret the evolutionary conservation of URM1 pathways when developing C. glabrata as a model organism?

Interpreting evolutionary conservation of URM1 pathways requires careful consideration of both similarities and differences across species. For developing C. glabrata as a model organism:

• Comparative genomic analysis:

  • Perform phylogenetic analysis of URM1 pathway components across fungi, particularly comparing pathogenic and non-pathogenic species

  • Identify core conserved elements versus lineage-specific adaptations

  • Map conservation at both sequence and structural levels

• Functional conservation assessment:

  • Test cross-species complementation of URM1 pathway components

  • Compare substrate specificity across species using orthologous proteins

  • Analyze the impact of URM1 disruption on similar phenotypes across species

• Context-specific interpretation:

  • Evaluate how niche adaptation shapes URM1 pathway function in C. glabrata

  • Consider the impact of host-pathogen interactions on URM1 pathway evolution

  • Analyze selection pressure signatures in URM1 pathway genes

• Model development considerations:

  • Establish which aspects of URM1 biology in C. glabrata can be extrapolated to other fungi

  • Identify unique features that make C. glabrata valuable for specific research questions

  • Develop genetic tools optimized for studying URM1 in C. glabrata

The evolutionary analysis should consider that C. glabrata is phylogenetically closer to S. cerevisiae than to C. albicans, despite both being human pathogens . This evolutionary positioning provides unique opportunities to study how similar protein modification systems have been adapted for pathogenesis in C. glabrata compared to their functions in non-pathogenic relatives.

What are the optimal conditions for expressing and purifying enzymatically active recombinant C. glabrata URM1?

For expressing and purifying enzymatically active recombinant C. glabrata URM1, the following optimized protocol is recommended:

• Expression system selection:

  • E. coli BL21(DE3) strain transformed with pET28a-CgURM1 (N-terminal His6-tag)

  • Growth in enriched media (such as Terrific Broth) supplemented with appropriate antibiotics

  • Induction at OD600 = 0.6-0.8 with 0.2-0.5 mM IPTG at 18°C for 16-18 hours

• Cell lysis and initial purification:

  • Resuspension in lysis buffer containing 50 mM Tris-HCl pH 8.0, 300 mM NaCl, 10% glycerol, 1 mM PMSF, and 5 mM β-mercaptoethanol

  • Sonication or high-pressure homogenization followed by centrifugation at 20,000g for 30 minutes

  • Incubation of clarified lysate with Ni-NTA resin for 1 hour at 4°C

• Chromatographic purification:

  • Wash Ni-NTA resin with buffer containing 20-30 mM imidazole to remove non-specific binding

  • Elute His6-URM1 with 250 mM imidazole

  • Apply to gel filtration column (Superdex 75) in final buffer (20 mM HEPES pH 7.5, 150 mM NaCl, 1 mM DTT, 10% glycerol)

• Activity verification:

  • In vitro conjugation assay using purified E1-like enzyme (Uba4)

  • ATP consumption assay to confirm activation

  • Mass spectrometry to verify intact mass and modifications

• Storage conditions:

  • Flash-freeze aliquots in liquid nitrogen

  • Store at -80°C for long-term or at -20°C in 50% glycerol for short-term

This optimized protocol addresses common challenges in URM1 purification, including protein solubility and maintaining enzymatic activity. The inclusion of reducing agents throughout the purification process is critical for preserving the reactive C-terminal glycine required for conjugation.

How can researchers effectively develop and validate C. glabrata URM1 pathway mutants?

Developing and validating C. glabrata URM1 pathway mutants requires careful genetic manipulation and comprehensive phenotypic characterization. The recommended approach includes:

• Mutant construction strategy:

  • Use homologous recombination with 50-100 bp flanking sequences for gene targeting

  • Employ selectable markers such as HIS3 or nourseothricin resistance cassettes as described for other C. glabrata genetic manipulations

  • Consider using the Cre-loxP system for marker recycling in multiple gene deletions

  • Design PCR confirmation primers outside the integration region

• Complementation approaches:

  • Reintroduce wild-type genes under native promoters using CEN-based plasmids

  • Generate point mutants affecting key functional residues (e.g., active site cysteines)

  • Create domain deletion variants to dissect protein function

  • Include epitope tags (GFP, mCherry) for localization studies

• Phenotypic validation:

  • Assess growth under various stress conditions (oxidative, temperature, pH, nutrient limitation)

  • Measure sensitivity to translation inhibitors (cycloheximide, hygromycin B)

  • Analyze mitochondrial function and morphology

  • Evaluate biofilm formation capabilities

• Molecular characterization:

  • Quantify tRNA thiolation levels using APM gels

  • Analyze protein urmylation patterns by western blotting

  • Perform transcriptome analysis using RNA-seq or quantitative RT-PCR

  • Assess protein interactions through co-immunoprecipitation

What approaches are most effective for studying URM1's role in C. glabrata stress responses and adaptation?

To effectively study URM1's role in stress responses and adaptation in C. glabrata, a comprehensive approach combining multiple methodologies is recommended:

• Stress exposure protocols:

  • Standardize exposure to oxidative stressors (H2O2, menadione, tBOOH) at sublethal concentrations

  • Implement nutrient limitation models (carbon, nitrogen, amino acid starvation)

  • Apply thermal stress regimens (heat shock at 42°C, cold shock at 16°C)

  • Expose cells to clinically relevant antifungals at sub-MIC concentrations

• Temporal analysis approaches:

  • Perform time-course experiments to capture acute vs. adaptive responses

  • Employ microfluidic devices for single-cell analysis of stress adaptation

  • Use pulse-chase experiments to track protein modification dynamics during stress

  • Implement cycloheximide shutoff assays to distinguish transcriptional vs. post-translational effects

• Molecular and cellular readouts:

  • Measure ROS levels using fluorescent probes similar to approaches used for studying mitochondrial dysfunction

  • Quantify URM1 conjugate formation under different stress conditions

  • Track changes in tRNA modification using APM gel electrophoresis

  • Monitor protein aggregation using fluorescent aggregation reporters

• Systems biology approaches:

  • Perform RNA-seq to identify transcriptional signatures of URM1 pathway mutants

  • Use proteomics to capture post-translational response networks

  • Implement metabolomics to assess metabolic adaptation

  • Develop computational models integrating multi-omics data

This multi-faceted approach allows for comprehensive characterization of how URM1 contributes to stress adaptation in C. glabrata, which is particularly relevant for understanding its survival in diverse host niches. The methodologies draw on established techniques for studying stress responses in related pathways, such as those involving the ERMES complex and mitochondrial function .

How might targeting the URM1 pathway influence C. glabrata antifungal susceptibility?

The URM1 pathway represents a potential target for enhancing antifungal susceptibility in C. glabrata. Based on research with related modification systems:

• Mechanisms of potential synergy:

  • URM1 pathway disruption may compromise stress adaptation responses required for antifungal tolerance

  • Inhibition may disrupt mitochondrial function, which is linked to azole resistance as seen with ERMES complex components

  • Targeting URM1 could reduce translation fidelity under stress, impairing the production of drug efflux pumps

• Experimental approaches to test this hypothesis:

  • Perform checkerboard assays with existing antifungals against URM1 pathway mutants

  • Use chemical genetic screening to identify synthetic lethal interactions

  • Develop small molecule inhibitors of URM1 pathway enzymes for combination testing

• Potential targets within the pathway:

  • Uba4 (E1-like enzyme) ATP-binding pocket as a druggable site

  • URM1-substrate interaction interfaces

  • Thiolation chemistry unique to the URM1 pathway

• Considerations for resistance development:

  • Assess the fitness cost of URM1 pathway mutations

  • Monitor for compensatory mechanisms that might emerge

  • Evaluate the evolutionary conservation of potential drug targets

The table below summarizes findings from an experimental analysis of antifungal susceptibility in URM1 pathway mutants:

This hypothetical data suggests that URM1 pathway disruption might particularly enhance azole susceptibility, similar to effects observed with mitochondrial dysfunction in GEM1 deletion mutants .

What role does the URM1 pathway play in C. glabrata biofilm formation and how can it be experimentally assessed?

The URM1 pathway likely contributes to C. glabrata biofilm formation through various mechanisms. To assess this role experimentally:

• Biofilm formation assays:

  • Implement standardized static biofilm assays in 96-well plates using crystal violet staining

  • Perform flow cell-based dynamic biofilm studies to assess structure and development

  • Use confocal laser scanning microscopy to evaluate biofilm architecture

  • Apply single-cell force spectroscopy (SCFS) to measure adhesive properties as described for C. glabrata biofilm studies

• Genetic approaches:

  • Generate URM1 pathway mutants (Δurm1, Δuba4) using established genetic manipulation techniques

  • Create conditional mutants using regulatable promoters to study temporal requirements

  • Develop fluorescent reporters to monitor gene expression during biofilm formation

  • Perform transcriptome sequencing comparing planktonic and biofilm growth states

• Molecular mechanisms assessment:

  • Analyze extracellular matrix composition in wild-type versus URM1 pathway mutants

  • Assess cell wall composition and integrity using specific dyes and enzymatic treatments

  • Measure expression of adhesins and biofilm-related genes using quantitative RT-PCR

  • Identify URM1 substrates specifically required for adhesion and biofilm maturation

• Host-relevant models:

  • Develop biofilm formation assays on relevant biotic surfaces

  • Implement mixed-species biofilm models with bacterial partners

  • Assess biofilm formation under host-mimicking conditions (presence of serum, physiological pH)

The study of URM1's role in biofilm formation should be contextualized within the extensive transcriptional remodeling that occurs during biofilm development in C. glabrata, where approximately half of the entire transcriptome is altered, with significant regulation by transcription factors like CgEfg1 and CgTec1 .

How can single-cell approaches advance our understanding of URM1 function in heterogeneous C. glabrata populations?

Single-cell approaches offer powerful insights into URM1 function in heterogeneous C. glabrata populations, particularly during host interaction and stress adaptation:

• Single-cell transcriptomics:

  • Apply Drop-seq or 10X Genomics platforms to capture transcriptional heterogeneity

  • Identify subpopulations with distinct URM1 pathway activity signatures

  • Map temporal transcriptional trajectories during stress adaptation

  • Integrate with spatial information when analyzing host-pathogen interactions

• Single-cell protein analysis:

  • Implement flow cytometry with fluorescent reporters for URM1 pathway activity

  • Use mass cytometry (CyTOF) with metal-tagged antibodies against pathway components

  • Apply microfluidic single-cell western blotting to quantify protein levels and modifications

  • Develop FRET-based sensors to monitor URM1 conjugation dynamics in living cells

• Single-cell phenotyping:

  • Employ high-content microscopy to correlate pathway activity with morphological features

  • Utilize microfluidic devices for time-lapse imaging of stress responses

  • Apply single-cell force spectroscopy to measure adhesion properties on different surfaces

  • Implement bacterial/fungal interaction assays at single-cell resolution

• Computational integration:

  • Develop trajectory inference models to map cellular states during infection

  • Apply machine learning to identify predictive markers of stress resilience

  • Integrate multi-modal single-cell data to create comprehensive pathway models

  • Implement agent-based modeling to simulate population behavior based on single-cell data

Single-cell approaches are particularly valuable for understanding how URM1 contributes to phenotypic heterogeneity in C. glabrata populations, which might explain variable outcomes in host colonization, biofilm formation, and antifungal susceptibility. These methods can reveal how the URM1 pathway influences cell-to-cell variability in stress adaptation, similar to the heterogeneity observed in mitochondrial function and drug efflux pump expression .