Recombinant Candida glabrata Probable cytosolic iron-sulfur protein assembly protein 1 (CIA1)

What is CIA1 and what is its primary function in C. glabrata?

CIA1 (Cytosolic Iron-sulfur protein Assembly protein 1) is a crucial component of the CIA machinery responsible for the maturation of cytosolic and nuclear iron-sulfur (Fe-S) proteins. In C. glabrata, this protein likely functions similarly to its homologs in related fungi, participating in the transfer of Fe-S clusters to target apoproteins. The CIA machinery typically works downstream of the mitochondrial Iron-Sulfur Cluster (ISC) assembly system, receiving a sulfur-containing precursor exported from mitochondria to build Fe-S clusters in the cytosol.

C. glabrata employs a unique hybrid iron regulation network that combines features from both Saccharomyces cerevisiae and pathogenic fungi like Candida albicans . Within this network, CIA1 plays an essential role in maintaining iron homeostasis by ensuring proper assembly of Fe-S clusters in proteins involved in various cellular processes including DNA metabolism, protein translation, and iron sensing. The proper functioning of CIA1 is critical for cell viability and potentially influences the pathogenicity of C. glabrata.

How does CIA1 relate to the iron metabolism in C. glabrata?

CIA1 is integrally connected to iron metabolism in C. glabrata as it participates in the assembly of Fe-S clusters, which are essential cofactors for numerous proteins. C. glabrata utilizes a hybrid iron regulation network where Aft1 functions as the main positive regulator under iron starvation conditions, while Cth2 degrades mRNAs encoding iron-requiring enzymes . Unlike S. cerevisiae but similar to other fungal pathogens, C. glabrata also employs Sef1 for optimal growth under iron limitation conditions .

The relationship between CIA1 and iron metabolism is bidirectional. On one hand, CIA1 requires iron availability to function properly in Fe-S cluster assembly. On the other hand, proper CIA1 function is essential for the activity of Fe-S proteins involved in iron sensing and regulation. For example, CIA1 likely contributes to the maturation of iron-responsive transcription factors and iron-dependent metabolic enzymes. In iron-limiting environments, such as those encountered during host infection, efficient CIA1 function becomes particularly important for prioritizing iron utilization among competing cellular processes.

How is CIA1 regulated in response to environmental changes?

CIA1 regulation in C. glabrata likely responds to several environmental factors, particularly iron availability. Based on C. glabrata's hybrid iron regulation network, CIA1 may be regulated through multiple mechanisms:

• Transcriptional regulation: Expression of CIA1 might be influenced by iron-responsive transcription factors like Aft1, which activates genes involved in iron uptake and recycling under iron deprivation . Additionally, Yap5 and Yap7, which have been shown to regulate iron sulfur cluster biogenesis in C. glabrata, may also influence CIA1 expression .

• Post-transcriptional regulation: The mRNA-degrading protein Cth2 targets transcripts encoding iron-utilizing proteins during iron limitation . If CIA1 mRNA contains appropriate binding sites, it could be subject to this regulation.

• Functional adaptation: CIA1 activity may be modulated by interaction with other components of the CIA machinery, which themselves respond to iron availability and oxidative stress.

Environmental stressors encountered during infection, such as oxidative stress from host immune cells, pH changes, and nutrient limitation, likely trigger adaptive responses in the iron-sulfur cluster assembly machinery, including CIA1. These adaptations help C. glabrata survive in the challenging host environment while maintaining essential Fe-S protein functions.

What are the recommended expression systems for recombinant C. glabrata CIA1?

Several expression systems can be employed for producing recombinant C. glabrata CIA1, each with distinct advantages for different research applications:

• Bacterial expression systems (E. coli):

  • BL21(DE3) strains offer high yield and simplicity

  • Rosetta strains address potential codon bias issues

  • SHuffle strains enhance disulfide bond formation if needed

  • Advantages include rapid growth, high yields, and economic efficiency

  • Limitations include potential improper folding and lack of eukaryotic post-translational modifications

• Yeast expression systems:

  • S. cerevisiae provides a closely related environment that may enhance proper folding

  • P. pastoris offers high yield with eukaryotic processing capabilities

  • C. glabrata itself could be used for homologous expression

  • These systems may better accommodate the specific folding requirements of CIA1

• Insect cell systems:

  • Sf9 or High Five cells provide advanced eukaryotic folding machinery

  • Baculovirus expression system allows for large-scale production

  • Suitable for complex proteins resistant to expression in simpler systems

For optimal results, the expression construct should include a purification tag (His, GST, or TAP) similar to the approach used for C. glabrata Pdr1 in previous studies . Codon optimization for the chosen expression system and inclusion of appropriate regulatory elements are also important considerations.

What purification strategies yield the highest purity and activity of recombinant CIA1?

Purifying recombinant CIA1 while maintaining its structural integrity and functional activity requires careful consideration of its biochemical properties as an Fe-S cluster-associated protein:

• Initial capture:

  • Affinity chromatography based on incorporated tags (IMAC for His-tagged protein, glutathione affinity for GST fusion)

  • Tandem affinity purification (TAP) approach may be particularly effective, as demonstrated for other C. glabrata proteins

  • All buffers should contain reducing agents (DTT or TCEP, 1-5 mM) to prevent oxidation of cysteine residues

• Intermediate purification:

  • Ion exchange chromatography based on CIA1's theoretical isoelectric point

  • Heparin affinity chromatography if CIA1 exhibits nucleic acid binding properties

  • Consider including 10-15% glycerol in all buffers to enhance protein stability

• Polishing step:

  • Size exclusion chromatography to remove aggregates and obtain homogeneous protein

  • Analysis of oligomeric state to confirm proper quaternary structure

When dealing with Fe-S proteins like CIA1, consider performing purification steps under anaerobic conditions or with minimal exposure to oxygen to prevent oxidation of Fe-S clusters. If the protein is purified without its Fe-S cluster, in vitro reconstitution may be necessary to obtain functional protein for downstream analyses.

How can I verify the proper folding and activity of recombinant CIA1?

Verifying proper folding and activity of recombinant CIA1 requires a multi-faceted approach combining structural assessment and functional assays:

• Structural integrity assessment:

  • Circular dichroism (CD) spectroscopy to analyze secondary structure elements

  • Thermal shift assays to evaluate protein stability and proper folding

  • Size exclusion chromatography to confirm monomeric state or appropriate oligomerization

  • Limited proteolysis to verify compact, folded structure

• Fe-S cluster incorporation:

  • UV-visible spectroscopy to detect characteristic Fe-S cluster absorbance patterns

  • Electron paramagnetic resonance (EPR) spectroscopy for detailed Fe-S cluster characterization

  • Iron quantification assays to determine iron:protein stoichiometry

  • Color assessment (Fe-S proteins often have brownish coloration)

• Functional assays:

  • In vitro Fe-S cluster transfer assays using known target apoproteins

  • Protein-protein interaction studies with other components of the CIA machinery

  • Complementation assays in CIA1-deficient yeast strains

  • Activity assays of recipient Fe-S proteins after interaction with CIA1

For meaningful results, it's essential to include proper controls in these assays, such as catalytically inactive CIA1 mutants, denatured protein samples, and known Fe-S proteins as positive controls. When analyzing experimental data, consider possible sources of variability and ensure appropriate statistical approaches are applied to distinguish significant differences from experimental noise.

How does CIA1 interact with the Aft1-regulated iron homeostasis network in C. glabrata?

The interaction between CIA1 and the Aft1-regulated iron homeostasis network in C. glabrata represents a fascinating research area that integrates Fe-S cluster assembly with iron regulation. In C. glabrata, Aft1 functions as the main regulator for iron uptake and recycling under iron deprivation conditions , while the CIA machinery facilitates Fe-S cluster assembly in cytosolic and nuclear proteins.

This interaction likely involves multiple mechanisms:

• Regulatory feedback: In related yeasts, Aft1 activity is regulated by Fe-S clusters, which signal iron sufficiency. Properly functioning CIA1 would contribute to this signaling pathway by ensuring Fe-S cluster incorporation into regulatory proteins that modulate Aft1 activity. This creates a feedback loop where effective Fe-S cluster assembly signals iron sufficiency, leading to Aft1 deactivation.

• Target gene regulation: Aft1 activates genes involved in iron acquisition and utilization. CIA1 or other components of the CIA machinery might be directly regulated by Aft1, especially under iron limitation conditions. Chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq), similar to the approach used for Pdr1 , could identify potential Aft1 binding sites in the CIA1 promoter.

• Post-transcriptional control: The search results indicate that Cth2 degrades mRNAs encoding iron-requiring enzymes in C. glabrata . If CIA1 mRNA contains Cth2 binding sites (typically AU-rich elements), its expression might be post-transcriptionally regulated during iron limitation.

• Functional coordination: Both the CIA machinery and the Aft1-regulated iron uptake system must be coordinated to maintain cellular iron homeostasis. This coordination may involve additional regulatory factors, such as Sef1, which has been shown to be required for full growth under iron limitation conditions in C. glabrata .

Investigating these interactions could provide valuable insights into how C. glabrata adapts to iron limitation during infection and potentially reveal novel targets for antifungal development.

What role might CIA1 play in antifungal resistance mechanisms?

The potential role of CIA1 in antifungal resistance in C. glabrata merits thorough investigation, especially considering C. glabrata's notorious resistance to azole antifungals. Several mechanisms could link CIA1 function to drug resistance:

• Connection to drug efflux systems: The search results indicate that Pdr1 is a transcriptional activator involved in azole resistance in C. glabrata . If CIA1 is required for the maturation of Fe-S proteins involved in drug efflux pump regulation or function, it could indirectly influence resistance. ChIP-seq analysis has identified promoters directly regulated by Pdr1, including those of ABC transporters like YBT1 , which might interact functionally with CIA1-dependent processes.

• Stress response connections: Antifungal drugs induce various cellular stresses, including oxidative stress. Fe-S proteins are particularly sensitive to oxidative damage, and CIA1's role in maintaining Fe-S protein function might be crucial for survival under drug-induced stress conditions. The search results mention that genes involved in DNA repair are directly regulated by Pdr1 , and many DNA repair enzymes require Fe-S clusters for function.

• Metabolic adaptations: Many antifungals target ergosterol biosynthesis, which is linked to iron metabolism through heme-containing enzymes. CIA1's role in iron utilization could influence cellular responses to ergosterol disruption. The search results mention that iron-sulfur cluster biogenesis and heme biosynthesis in C. glabrata are regulated by Yap5 and Yap7 , suggesting connections between these processes.

• Biofilm formation: C. glabrata can form biofilms that increase resistance to antifungals. If CIA1 function influences biofilm formation through Fe-S proteins involved in adhesion, matrix production, or stress responses, it could indirectly affect drug resistance.

Research approaches to investigate these connections could include comparative transcriptomics of CIA1 expression in resistant versus susceptible isolates, phenotypic analysis of CIA1 mutants under antifungal stress, and studies of genetic interactions between CIA1 and known resistance factors.

How does iron limitation affect CIA1 function during host infection?

During host infection, C. glabrata encounters severe iron limitation due to nutritional immunity, where the host restricts iron availability to limit pathogen growth. This iron restriction likely impacts CIA1 function in several ways:

• Expression adaptation: Under iron limitation, C. glabrata may adjust CIA1 expression to optimize Fe-S cluster assembly efficiency. The search results indicate that C. glabrata employs both Aft1-dependent regulation and Sef1-dependent mechanisms under iron limitation . Specifically, Sef1 is required for full growth under iron limitation conditions and influences the expression of iron-sulfur cluster-containing proteins like ACO1 and ISA1 .

• Functional prioritization: When iron is scarce, CIA1 activity may be redirected to prioritize Fe-S cluster delivery to essential proteins over non-essential ones. This triage system would ensure survival while economizing iron usage. The TCA cycle enzymes (ACO1, IDH1, IDH2) show expression changes in a sef1Δ mutant , suggesting potential regulation of iron-dependent metabolic pathways during adaptation to iron limitation.

• Interaction with host factors: During infection, CIA1 function might be influenced by host-derived molecules, such as reactive oxygen species produced by immune cells, which can damage Fe-S clusters. The ability to maintain CIA1 function despite these challenges could be a virulence determinant.

• Coordinate regulation with iron acquisition: C. glabrata must coordinate iron acquisition systems with iron utilization pathways, including CIA1-dependent processes. The search results describe C. glabrata's iron homeostasis system as "unique within the pathogenic fungi" , suggesting specialized adaptations for survival in the host environment.

Research approaches to investigate these adaptations could include in vivo expression analysis of CIA1 during infection, comparative proteomics of CIA1 interactors under iron-replete versus iron-limited conditions, and phenotypic analysis of CIA1 mutants in infection models.

How should inconsistent results in CIA1 functional assays be interpreted?

When faced with inconsistent results in CIA1 functional assays, researchers should systematically evaluate potential sources of variability and apply appropriate analytical frameworks:

• Protein-related factors:

  • Protein quality heterogeneity: Batch-to-batch variations in protein preparation can significantly impact results

  • Fe-S cluster occupancy: Partial or variable Fe-S cluster incorporation can lead to activity differences

  • Post-translational modifications: Variations in modification patterns may affect function

  • Degradation or oxidation: Fe-S proteins are particularly sensitive to oxidative damage

• Experimental conditions:

  • Oxidative environment: Even trace oxygen exposure can alter Fe-S protein activity

  • Buffer composition effects: pH, ionic strength, and specific ions can significantly impact activity

  • Temperature fluctuations: Can affect protein stability and reaction kinetics

  • Experimental design issues: As noted in the search results, experiments "need to be carried out without bias" and "the data must be shared with other experimenters" to ensure reproducibility3

• Analytical approach:

  • Establish proper controls: Include positive and negative controls in each experimental set

  • Blind analysis: "Data should be analyzed in a blind fashion by setting it up so that the experimenter is not aware of which conditions apply to the data being analyzed"3

  • Statistical considerations: "Sampling error describes the case when a sample is not an accurate representation of the total population"3, so ensure adequate replication

  • Distinguish between random and systematic errors: "Random errors are caused by unpredictable changes," while "systematic errors they are due to the difficulty of using a measuring tool or improperly calibrated instruments"3

What statistical approaches are most appropriate for analyzing CIA1 protein interaction data?

• For qualitative interaction screening:

  • Fisher's exact test or chi-square test for contingency table analysis

  • Multiple testing correction (FDR, Bonferroni) to control false positive rates

  • Enrichment analysis for functional categorization of interactors

  • Network analysis to identify interaction clusters and functional modules

• For quantitative interaction measurements:

  • Student's t-test or ANOVA for comparing interaction strengths across conditions

  • Non-parametric alternatives (Mann-Whitney, Kruskal-Wallis) if data don't meet normality assumptions

  • Regression analysis for dose-response relationships

  • ANCOVA when controlling for covariates that might influence interaction strength

• For high-throughput interaction data:

  • Specialized scoring systems (e.g., SAINT, CompPASS) to distinguish true interactions from background

  • Machine learning approaches to identify patterns in complex interaction datasets

  • Bayesian methods for integrating prior knowledge with experimental data

  • Data visualization techniques to reveal patterns and relationships

When designing experiments, remember that "qualitative data is prone to measurement error since it is subjective" and "quantitative or in other words numerical data derived from scientific instruments are preferable"3. Additionally, "bias may arise when a researcher is influenced by their desired or expected outcome"3, highlighting the importance of objective analysis approaches.

• Sufficient biological and technical replicates to account for variability

• Appropriate normalization methods to account for technical factors

• Sensitivity analysis to test the robustness of findings to different analytical approaches

• Clear reporting of statistical methods, test parameters, and significance thresholds

How can I distinguish between direct and indirect effects when studying CIA1 function?

Distinguishing between direct and indirect effects is crucial when studying CIA1 function, as Fe-S cluster assembly impacts numerous cellular processes. Consider these methodological approaches:

• Biochemical approaches:

  • In vitro reconstitution: Using purified components to demonstrate direct interactions

  • Protein-protein interaction assays: Co-immunoprecipitation, crosslinking, or FRET to detect direct binding

  • Structure-function analysis: Targeted mutations affecting specific interactions

  • Direct transfer assays: Monitoring Fe-S cluster transfer from CIA1 to recipient proteins in real-time

• Genetic approaches:

  • Epistasis analysis: Determine genetic relationships between CIA1 and potential interactors

  • Separation-of-function mutations: Target specific CIA1 activities to dissect multifunctional roles

  • Suppressor screening: Identify mutations that rescue CIA1 mutant phenotypes

  • Rapid depletion systems: Observe immediate versus delayed effects following CIA1 depletion

• Systems approaches:

  • Time-course experiments: Establish temporal order of events following CIA1 perturbation

  • Multi-omics integration: Correlate changes across different data types (transcriptomics, proteomics, metabolomics)

  • Network modeling: Infer causal relationships from complex datasets

  • Comparative analysis across conditions: Vary contexts to identify consistent versus context-dependent relationships

When interpreting results, consider the following framework:

Remember that "careful researchers always search for possible alternative explanations to their findings"3, and consider that C. glabrata has "evolved an iron homeostasis system which seems to be unique within the pathogenic fungi" , which may result in unique functional relationships for CIA1 compared to other model organisms.

What are common challenges in expressing recombinant CIA1 and how can they be overcome?

Expressing recombinant CIA1 from C. glabrata presents several challenges typical of Fe-S cluster-associated proteins:

• Expression challenges and solutions:

  • Low expression yield: Optimize codon usage for the expression host, use strong inducible promoters, and fine-tune induction conditions

  • Protein toxicity: Use tightly controlled expression systems, consider lower growth temperatures (16-20°C), and employ leaky expression strains

  • Improper folding: Co-express with molecular chaperones, use fusion partners known to enhance folding (MBP, SUMO), and optimize post-induction incubation time

  • Fe-S cluster incorporation: Supplement growth media with iron sources, consider expression under microaerobic conditions, and add sulfur sources

• Solubility issues and solutions:

  • Inclusion body formation: Reduce expression rate through lower inducer concentration and temperature, add solubility enhancers to media (sorbitol, betaine)

  • Aggregation during purification: Optimize buffer conditions (add glycerol, adjust ionic strength), maintain reducing environment, consider detergent additives

  • Limited stability: Include stabilizing agents (arginine, trehalose), minimize freeze-thaw cycles, and store with glycerol at -80°C

• Functional issues and solutions:

  • Loss of Fe-S clusters: Purify under anaerobic conditions, include reducing agents in all buffers, consider in vitro Fe-S cluster reconstitution

  • Heterogeneous protein population: Implement additional purification steps to separate holo- and apo-forms, characterize different fractions

  • Activity loss during storage: Optimize storage conditions, aliquot to avoid freeze-thaw cycles, validate activity before each experiment

Based on the search results mentioning tandem affinity purification (TAP)-tagged protein expression in C. glabrata , similar tagging approaches could be effective for CIA1 expression and purification. Specifically, integrating a tagged CIA1 construct at its native locus might provide more physiological expression levels and proper regulation.

What controls are essential for validating CIA1 functional studies?

Robust controls are critical for reliable CIA1 functional studies and should address multiple aspects of experimental design:

• Protein quality controls:

  • Catalytically inactive mutant: CIA1 with mutations in key functional residues

  • Thermally denatured protein: Heat-treated sample to confirm activity loss

  • Tag-only control: Express and purify tag alone to rule out tag-mediated effects

  • Protein from related species: CIA1 orthologs from S. cerevisiae or C. albicans to assess conservation of function

• Assay-specific controls:

  • No-substrate control: Reaction mixture lacking the specific substrate

  • Time zero control: Sample collected immediately after reaction initiation

  • Metal chelation control: Addition of iron chelators to confirm iron dependency

  • Oxidation control: Parallel reactions in presence/absence of oxidizing agents

• Biological validation controls:

  • Wild-type complement: Ensure that wild-type CIA1 rescues defects in CIA1-deficient cells

  • Known Fe-S proteins: Include established Fe-S proteins as positive controls

  • Non-Fe-S proteins: Include non-client proteins as negative controls

  • Physiological relevance: Test function under conditions mimicking host environment

As emphasized in the search results, "experimental error needs to be minimized" and "careful researchers always search for possible alternative explanations to their findings"3. Additionally, "data should be analyzed in a blind fashion by setting it up so that the experimenter is not aware of which conditions apply to the data being analyzed"3 to minimize bias.

When reporting results, clearly document all controls used, their rationale, and how they influenced data interpretation. This transparency is essential for reproducibility and building confidence in the findings, especially given that CIA1 research in C. glabrata represents a relatively specialized field.

How can I optimize experimental design to study CIA1 function under iron limitation?

Studying CIA1 function under iron limitation requires careful experimental design to mimic physiologically relevant conditions while maintaining experimental control:

• Iron limitation approaches:

  • Chemical chelation: Use iron-specific chelators (BPS, ferrozine) at calibrated concentrations

  • Defined media: Prepare media with precise iron concentrations using trace element mixes

  • Competitive limitation: Add iron-sequestering proteins (transferrin, lactoferrin) to mimic host conditions

  • Genetic approaches: Utilize iron transporter mutants to limit cellular iron uptake

• Experimental design considerations:

  • Gradual versus acute iron limitation: Assess both immediate responses and adaptive changes

  • Pre-adaptation: Pre-culture cells in iron-limited conditions before assays

  • Physiological relevance: Consider pH effects, as "alkaline pH (with its concomitant low iron solubility)" affects iron availability

  • Combined stresses: Include oxidative stress or antifungal exposure to mimic host conditions

• Analytical approaches:

  • Time-course sampling: Capture dynamic responses to iron limitation

  • Multi-parameter assessment: Monitor growth, morphology, gene expression, and protein function

  • Single-cell techniques: Account for population heterogeneity in stress responses

  • Comparative analysis: Include wild-type, CIA1 mutant, and iron regulatory mutant strains

• Validation strategies:

  • Intracellular iron measurement: Confirm actual iron status of cells

  • Marker gene expression: Monitor known iron-responsive genes as internal controls

  • Rescue experiments: Test whether iron supplementation reverses observed phenotypes

  • In vivo relevance: Correlate findings with infection models where appropriate

The search results highlight that C. glabrata has "evolved an iron homeostasis system which seems to be unique within the pathogenic fungi" and is "an evolutionary intermediate to SEF1-dependent fungal pathogens" . Therefore, experimental designs should account for this hybrid regulatory system, potentially incorporating comparisons with both S. cerevisiae (Aft1-dependent) and C. albicans (Sef1-dependent) to fully contextualize findings.

By implementing these considerations, researchers can generate more physiologically relevant data on CIA1 function under the iron-limited conditions that C. glabrata encounters during host infection.