Recombinant Candida glabrata ATP synthase subunit 9, mitochondrial (ATP9)

What is ATP9 and what role does it play in C. glabrata mitochondrial function?

ATP9 (also known as subunit 9 or subunit c) is a critical component of the F0 sector of the mitochondrial ATP synthase complex in Candida glabrata. This small, hydrophobic protein forms the c-ring structure embedded in the inner mitochondrial membrane that facilitates proton translocation, driving ATP synthesis. In most yeast species including C. glabrata, ATP9 is encoded in the mitochondrial DNA (mtDNA) along with other key energy metabolism-related genes such as COX1, COX2, COX3, ATP6, and ATP8 . The mitochondrial location of this gene makes it particularly relevant for understanding mitochondrial inheritance, heteroplasmy dynamics, and respiratory function in this pathogenic yeast.

ATP9 functions as part of the rotary motor within ATP synthase, where the flow of protons through the c-ring causes rotation that drives conformational changes in the F1 sector, enabling ATP synthesis. Disruption of ATP9 function typically leads to respiratory deficiency, as the cell can no longer efficiently produce ATP through oxidative phosphorylation, resulting in petite colony phenotypes if the organism is petite-positive.

How does ATP9 expression change during infection and stress conditions?

Expression of mitochondrial genes, including ATP9, shows dynamic regulation during various stress conditions and infection scenarios. During macrophage infection, C. glabrata undergoes significant metabolic remodeling with temporal expression patterns of mitochondrial genes. Research using ChIP-seq against elongating RNA polymerase II has revealed that genes involved in ATP synthesis show distinct temporal patterns during macrophage infection .

For instance, the ATP synthesis gene CgCYC1 is dramatically upregulated immediately (0.5 hr) upon macrophage internalization, while other metabolic genes like CgCIT2 (TCA cycle) and CgICL1 (glyoxylate bypass) are induced at 2 hr post-infection . Since ATP9 is involved in ATP synthesis, it likely follows similar regulatory patterns to other energy metabolism genes, responding to the cell's need for energy production during infection.

During stress conditions, ATP9 expression may be affected by:

• Nutrient availability: C. glabrata experiences nutrient and energy deprivation upon entry into macrophages, potentially affecting ATP9 expression

• Oxidative stress: Reactive oxygen species (ROS) in macrophages can damage mtDNA and affect expression of mitochondrial genes

• Antifungal exposure: Azole antifungals may indirectly affect mitochondrial function and gene expression

Why is recombinant expression of ATP9 particularly challenging?

Recombinant expression of ATP9 presents several challenges stemming from its natural properties and location:

• Mitochondrial encoding: ATP9 is naturally encoded in the mitochondrial genome of C. glabrata, which uses a genetic code that differs slightly from the standard nuclear code

• Extreme hydrophobicity: ATP9 contains multiple transmembrane domains making it difficult to express in soluble form

• Proper folding requirements: Correct insertion into membranes and oligomerization into the c-ring structure requires specific chaperones and membrane environments

• Small size: At approximately 8 kDa, ATP9 is relatively small, making detection and purification challenging

Methodological approaches to overcome these challenges include:

• Using specialized expression systems designed for membrane proteins

• Fusion with solubility-enhancing tags

• Expression at reduced temperatures

• Extraction using mild, non-denaturing detergents

• In vitro translation systems supplemented with lipids or nanodiscs

How can I generate and verify C. glabrata strains with modified ATP9?

Creating C. glabrata strains with modified ATP9 requires specialized approaches due to its mitochondrial location. Based on successful strategies used for other mitochondrial genes in C. glabrata, the following methodology is recommended:

• Biolistic transformation approach:

  • Prepare a DNA construct containing a selectable marker (such as recoded ARG8) flanked by homologous sequences to the ATP9 gene

  • Use biolistic transformation to deliver the construct into mitochondria

  • Select transformants using appropriate selection media (e.g., arginine prototrophy)

• Managing heteroplasmy:

  • Initial transformants will likely be heteroplasmic (containing both wild-type and modified mtDNA)

  • Use selective growth conditions to drive toward homoplasmy

  • Monitor mtDNA composition using PCR, quantitative PCR, and Southern blotting

• Verification protocols:

  • Confirm mtDNA status using multiple methods (PCR, Southern blot)

  • Verify respiratory function using growth assays on fermentable vs. non-fermentable carbon sources

  • Measure ATP synthesis activity in isolated mitochondria

It is important to note that the dynamics of heteroplasmy in C. glabrata can be influenced by growth conditions. Research with ATP6 deletion has shown that aerobic conditions can facilitate the loss of original mtDNA, while anaerobic conditions may favor loss of transformed mtDNA . Additionally, increases in reactive oxygen species in mitochondria lacking essential components, along with cell division dynamics, play important roles in determining heteroplasmy stability .

Table 1: Recommended Verification Tests for ATP9-Modified C. glabrata Strains

What experimental approaches can reveal the role of ATP9 in C. glabrata virulence and stress response?

To investigate ATP9's role in virulence and stress response, researchers should employ a multi-faceted approach:

• Macrophage infection models:

  • Infect THP-1 macrophages with wild-type and ATP9-modified strains

  • Monitor fungal survival using colony forming unit (CFU) assays at different time points

  • Compare phagocytosis rates, intracellular proliferation, and macrophage escape

  • Use the protocol described in search results: PMA-differentiated THP-1 cells infected at MOI 5:1, followed by washing steps and CFU determination at relevant timepoints

• Transcriptional response analysis:

  • Apply ChIP-seq against elongating RNA polymerase II to map genome-wide transcription responses during infection

  • Compare transcriptional profiles between wild-type and ATP9-modified strains

  • Analyze temporal gene expression patterns at multiple timepoints (0.5, 2, 4, 6, and 8 hr) post-infection

  • Focus on metabolic remodeling genes known to be induced upon macrophage phagocytosis

• Stress tolerance assessment:

  • Evaluate growth under various stressors (oxidative, pH, nutrient limitation)

  • Test sensitivity to antifungal drugs, particularly azoles

  • Examine the response to mitochondrial inhibitors

• In vivo virulence models:

  • Use established animal models for C. glabrata infection

  • Compare tissue burden, dissemination, and survival rates

The importance of early metabolic adaptation in C. glabrata virulence is highlighted by research showing that upon macrophage entry, C. glabrata undergoes significant transcriptional changes in ATP synthesis genes (within 0.5 hr), followed by major metabolic remodeling at 2 hr post-phagocytosis . These adaptations appear critical for subsequent survival and proliferation within macrophages.

How does ATP9 function relate to azole resistance mechanisms in C. glabrata?

The relationship between ATP9 function and azole resistance in C. glabrata involves several interconnected mechanisms:

• Energy-dependent drug efflux:

  • ATP-binding cassette (ABC) transporters like CgCDR1 and CgCDR2 require ATP for azole efflux

  • ATP9 functionality directly impacts cellular ATP availability for these transporters

  • Alterations in ATP synthesis efficiency could affect drug efflux capacity

• Transcriptional regulation networks:

  • Transcription factors like CgPdr1 regulate multidrug resistance transporters in C. glabrata

  • Mitochondrial dysfunction can trigger compensatory responses affecting expression of these factors

  • Research has identified transcription factors (e.g., CgXbp1) that regulate both virulence-related genes and genes associated with drug resistance

• Membrane composition effects:

  • ATP synthase function affects mitochondrial membrane potential

  • Altered membrane potentials can influence cell membrane composition

  • Changes in ergosterol content (the target of azoles) may occur as adaptive responses

• Stress response pathways:

  • Mitochondrial dysfunction triggers stress responses that may cross-talk with azole resistance mechanisms

  • Common regulatory elements may control both mitochondrial function and drug resistance genes

The complex regulatory networks in C. glabrata include transcription factors that have undergone neofunctionalization, such as CgMar1, which appears to be involved in azole susceptibility regulation . This suggests that a comprehensive understanding of ATP9's role in azole resistance requires analysis of both direct energetic effects and indirect regulatory connections.

What are the optimal protocols for studying mitochondrial DNA heteroplasmy in ATP9 experiments?

Studying mtDNA heteroplasmy in ATP9 experiments requires careful methodological approaches:

• Quantitative assessment techniques:

  • Quantitative PCR (qPCR) with primers specific to wild-type and modified ATP9 sequences

  • Southern blotting with appropriate probes to distinguish between mtDNA variants

  • Next-generation sequencing for precise heteroplasmy quantification

• Controlling heteroplasmy dynamics:

  • Manipulation of growth conditions to influence heteroplasmy ratios

  • Research with ATP6 deletion in C. glabrata has shown that aerobic conditions facilitate loss of original mtDNA, while anaerobic conditions favor loss of transformed mtDNA

  • Monitor reactive oxygen species (ROS) levels, as they play important roles in determining heteroplasmy dynamics

• Single-cell analysis:

  • Isolate and analyze individual colonies to assess heteroplasmy at the single-cell level

  • Use fluorescent markers if possible to visualize different mtDNA populations

  • Track heteroplasmy changes through multiple generations

• Experimental timeline considerations:

  • Allow sufficient time for heteroplasmy resolution (typically 4-8 weeks)

  • Include regular sampling points to track heteroplasmy dynamics

  • Maintain consistent selection pressure throughout the experiment

Table 2: Protocols for Heteroplasmy Analysis in C. glabrata ATP9 Studies

The protocol should be adapted based on findings from ATP6 studies showing that increases in ROS in mitochondria lacking essential components, along with equal cell division dynamics, play important roles in determining heteroplasmy stability .

What are the most effective experimental controls for studying ATP9 function in C. glabrata?

Rigorous controls are essential for reliable ATP9 functional studies:

• Genetic controls:

  • Wild-type C. glabrata strain (ATCC 2001 or BG2) as positive control

  • ρ0 strain (completely lacking mtDNA) as negative control for respiratory function

  • Heteroplasmic strains with quantified mtDNA content to control for partial effects

  • Complemented ATP9 mutant strains to verify phenotype reversibility

• Expression verification controls:

  • Quantitative RT-PCR with appropriate reference genes

  • Western blotting with verified antibodies

  • Controls for mitochondrial mass and integrity

• Growth condition controls:

  • Parallel growth on fermentable (glucose) and non-fermentable (glycerol, ethanol) carbon sources

  • Aerobic versus anaerobic growth conditions

  • Growth with and without selection pressure

• Environmental stress controls:

  • Oxidative stress (H2O2, menadione)

  • pH stress

  • Nutrient limitation

  • Temperature variation

• Mitochondrial function controls:

  • Treatment with known inhibitors (oligomycin for ATP synthase)

  • Mitochondrial membrane potential measurements

  • ROS measurement controls

• Infection model controls:

  • Uninfected macrophage controls

  • Heat-killed C. glabrata controls

  • Phagocytosis inhibition controls

  • Macrophage activation status verification

When performing ATP9 studies in macrophage infection models, the protocol should include differentiation of THP-1 monocytes using PMA (16 nM), verification of macrophage differentiation, and appropriate MOI ratios (typically 5:1 yeast:macrophage) . For time-course experiments, sampling at multiple timepoints (0.5, 2, 4, 6, and 8 hr) post-infection allows capture of different phases of the host-pathogen interaction .

How can I optimize the expression and purification of recombinant C. glabrata ATP9 for structural studies?

Optimizing recombinant ATP9 expression and purification requires specialized approaches for this challenging membrane protein:

• Expression system selection:

  • E. coli strains engineered for membrane protein expression (C41/C43(DE3), Lemo21)

  • Yeast expression systems (S. cerevisiae, P. pastoris) for eukaryotic processing

  • Cell-free systems supplemented with lipids or detergents

• Construct design considerations:

  • Codon optimization for the host expression system

  • Fusion tags to enhance solubility (MBP, SUMO, TrxA)

  • Affinity tags for purification (His6, Strep-tag II)

  • Cleavable linkers between tag and ATP9

• Expression condition optimization:

  • Reduced temperature (16-20°C) to slow folding

  • Low inducer concentrations to prevent aggregation

  • Supplementation with membrane-stabilizing additives

  • Controlled aeration for optimal expression

• Membrane extraction strategies:

  • Mild detergents (DDM, LDAO, Fos-choline-12)

  • Detergent screening to identify optimal solubilization

  • Native membrane isolation before solubilization

  • Nanodiscs or amphipols for detergent-free purification

• Purification strategy:

  • Immobilized metal affinity chromatography (IMAC)

  • Size exclusion chromatography (SEC)

  • Ion exchange chromatography as needed

  • Affinity purification using ATP synthase inhibitors

• Structural integrity verification:

  • Circular dichroism spectroscopy

  • Limited proteolysis

  • Mass spectrometry

  • Functional reconstitution assays

Table 3: Optimization Parameters for Recombinant ATP9 Expression

For structural studies, consider the small size of ATP9 (~8 kDa) and its tendency to form oligomeric c-rings, which may require specialized approaches like cryo-electron microscopy rather than crystallography.

How should I analyze contradictory results in ATP9 expression studies under different stress conditions?

When facing contradictory results in ATP9 expression studies, apply this systematic analysis framework:

• Evaluate methodological differences:

  • Compare RNA/DNA extraction methods (particularly for mitochondrial genes)

  • Assess primer design and locations for qPCR studies

  • Review normalization strategies (reference genes used)

  • Examine RNA polymerase II ChIP-seq approaches versus direct RNA measurements

• Consider strain background effects:

  • Document complete strain genotypes and backgrounds

  • Assess mtDNA stability and heteroplasmy status

  • Verify petite-positive/negative status of strains

  • Check for inadvertent selection of suppressors

• Analyze growth condition variations:

  • Carbon source differences (fermentable vs. non-fermentable)

  • Growth phase at sampling (early log, mid-log, stationary)

  • Oxygenation levels during growth

  • Media composition differences

• Account for temporal dynamics:

  • Research shows transcriptional responses in C. glabrata are highly dynamic

  • ATP synthesis genes show specific temporal patterns, with some peaking early (0.5 hr) and others later during infection

  • Verify sampling timepoints are comparable between studies

• Consider biological context:

  • Host-pathogen interactions trigger complex time-dependent responses

  • The same gene may show opposite regulation at different infection stages

  • Genes involved in ATP synthesis may follow distinct expression patterns from each other

• Statistical approaches for reconciliation:

  • Meta-analysis techniques to integrate multiple datasets

  • Multivariate analysis to identify pattern dependencies

  • Time-series analysis for dynamic expression patterns

Research on C. glabrata infection models shows that ATP synthesis genes exhibit specific temporal patterns, with dramatic upregulation immediately upon macrophage internalization for some genes (e.g., CgCYC1), while other metabolic genes follow different patterns . These findings highlight the importance of considering temporal dynamics when interpreting seemingly contradictory expression data.

What data analysis approaches should I use to identify potential ATP9 interaction partners in C. glabrata?

To identify and validate ATP9 interaction partners, employ these complementary analytical approaches:

• Co-immunoprecipitation (Co-IP) data analysis:

  • Use label-free quantification (LFQ) for mass spectrometry data

  • Apply stringent statistical thresholds (p < 0.01, fold change > 2)

  • Implement SAINT (Significance Analysis of INTeractome) algorithm

  • Employ CRAPome filtering to remove common contaminants

  • Compare results against negative controls (tag-only, unrelated mitochondrial protein)

• Proximity labeling data analysis:

  • For BioID or APEX2 experiments, analyze enrichment over controls

  • Apply distance constraints based on labeling radius

  • Classify hits based on cellular compartment enrichment

  • Consider temporal dynamics of interactions

• Network analysis approaches:

  • Construct protein-protein interaction networks

  • Apply Markov clustering algorithms to identify functional modules

  • Calculate betweenness centrality to identify key connectors

  • Implement random walk with restart (RWR) algorithms

• Evolutionary analysis:

  • Perform sequence co-evolution analysis across fungal species

  • Identify correlated mutation patterns suggesting interaction

  • Apply statistical coupling analysis (SCA)

  • Compare with interaction data from model organisms

• Functional validation analysis:

  • Design targeted genetic interaction screens

  • Analyze synthetic lethality/sickness patterns

  • Implement CRISPR interference for validation studies

  • Quantify co-localization coefficients from microscopy

Table 4: Recommended Statistical Methods for ATP9 Interaction Analysis

Focus particularly on interactions within the ATP synthase complex (F1 and F0 sectors) and proteins involved in mitochondrial gene expression, as these are most likely to have functional relationships with ATP9.

How should I interpret changes in ATP9 expression during C. glabrata adaptation to macrophage environments?

Interpreting ATP9 expression changes during macrophage adaptation requires multifaceted analysis:

• Temporal context analysis:

  • C. glabrata undergoes distinct transcriptional waves during macrophage infection

  • ATP synthesis genes show dramatic upregulation immediately (0.5 hr) upon macrophage internalization

  • This is followed by expression of TCA cycle and metabolic remodeling genes at 2 hr post-phagocytosis

  • Compare ATP9 expression patterns to these established temporal patterns

• Metabolic adaptation framework:

  • C. glabrata experiences nutrient and energy deprivation upon macrophage entry

  • Initial upregulation of ATP synthesis genes may reflect energy demand for adaptation

  • Subsequent metabolic remodeling prepares for growth and energy generation

  • Interpret ATP9 changes within this metabolic adaptation context

• Stress response integration:

  • Analyze expression alongside oxidative stress response genes

  • Consider relationship to metal ion sequestration (e.g., CgMT-I) and iron uptake (CgFTR1) genes

  • Evaluate correlation with cell cycle arrest and DNA damage checkpoint genes

• Virulence mechanism correlation:

  • Research shows virulence-centric biological processes are among the most immediate C. glabrata responses to macrophage phagocytosis

  • Assess whether ATP9 regulation correlates with known virulence factors

  • Consider the role of ATP synthesis in supporting virulence traits

• Regulatory network analysis:

  • Examine potential co-regulation with genes controlled by known transcription factors

  • Consider the role of repressors like CgXbp1, which establish global transcriptional repression at early infection stages

  • Analyze promoter regions for transcription factor binding sites

The dynamic transcriptional response of C. glabrata during macrophage infection involves the interplay between transcriptional activators and repressors, shaping temporal gene expression patterns . ATP9 regulation should be interpreted within this complex regulatory context, considering both direct metabolic roles and potential contributions to virulence and stress adaptation.

How does C. glabrata ATP9 compare structurally and functionally to ATP9 in other fungal pathogens?

Comparative analysis of ATP9 across fungal pathogens reveals important evolutionary and functional insights:

• Sequence conservation analysis:

  • C. glabrata ATP9 shows high conservation in functional domains across Candida species

  • The critical proton-binding glutamate residue in transmembrane helix 2 is invariant

  • C. glabrata ATP9 typically displays greater sequence similarity to Saccharomyces cerevisiae than to Candida albicans

  • Terminal regions show higher variability between species, suggesting adaptation-specific functions

• Genomic location comparison:

  • In C. glabrata, ATP9 is encoded in the mitochondrial genome like most yeast species

  • Some fungal species have transferred ATP9 to the nuclear genome during evolution

  • Mitochondrial location in C. glabrata impacts heteroplasmy dynamics and genetic manipulation strategies

• Structural adaptations:

  • ATP9 forms the c-ring of ATP synthase with species-specific stoichiometry

  • Ring size variations between species affect the bioenergetic efficiency of ATP synthesis

  • Structural adaptations may reflect ecological niche specialization

• Functional differences:

  • Inhibitor sensitivity profiles vary between species

  • ATP synthase coupling efficiency differs between respiratory and fermentative specialists

  • Regulatory responses to stress show species-specific patterns

• Clinical relevance:

  • C. glabrata's intrinsic tolerance to azole antifungals may partially relate to mitochondrial function

  • Comparison with other pathogens can reveal unique adaptations in energy metabolism

  • Evolutionary analysis can identify potential C. glabrata-specific targets

Understanding these differences is crucial when designing cross-species studies or attempting to apply findings from model organisms to C. glabrata. Particular attention should be paid to the mitochondrial location of ATP9 in C. glabrata and the implications for genetic manipulation and heteroplasmy management.

What can heteroplasmy studies of ATP9 reveal about mitochondrial genome evolution in C. glabrata?

Studies of mtDNA heteroplasmy involving ATP9 can provide valuable insights into mitochondrial genome evolution in C. glabrata:

• Inheritance mechanisms:

  • Heteroplasmy dynamics reveal selection pressures on mitochondrial genomes

  • Research with ATP6 deletion in C. glabrata demonstrates that heteroplasmic mtDNA is not spontaneously lost under selection pressure

  • Aerobic conditions facilitate loss of original mtDNA in some transformants, while anaerobic conditions favor loss of transformed mtDNA

  • These patterns suggest complex inheritance mechanisms beyond simple replicative advantage

• Adaptive selection forces:

  • Heteroplasmy resolution patterns indicate functional constraints

  • Reactive oxygen species (ROS) levels in mitochondria influence heteroplasmy dynamics

  • Cell division plays important roles in determining heteroplasmy trajectory

  • These factors may drive evolutionary selection on mitochondrial genomes

• Genetic bottleneck effects:

  • Heteroplasmy studies can reveal genetic bottleneck sizes during transmission

  • Single-cell analysis of heteroplasmy can quantify mtDNA segregation dynamics

  • These parameters influence the rate of mitochondrial genome evolution

• Recombination events:

  • Heteroplasmic states may facilitate mtDNA recombination

  • Recombination can be detected through marker segregation patterns

  • Understanding recombination rates informs evolutionary models

• Compensatory adaptations:

  • Long-term heteroplasmy experiments can reveal nuclear genome adaptations

  • Compensatory mutations may arise to accommodate mitochondrial defects

  • These adaptation mechanisms provide insights into mito-nuclear co-evolution

Research with ATP6 deletion in C. glabrata has demonstrated methods to generate homoplasmic mtDNA strains , providing valuable technical approaches for similar studies with ATP9. The detailed investigation showing that increases in ROS in mitochondria lacking ATP6, along with cell division dynamics, determine heteroplasmy patterns provides a framework for understanding the evolutionary forces acting on mitochondrial genes in C. glabrata.

What are the most promising research directions for ATP9 studies in antifungal resistance?

The study of ATP9 in C. glabrata offers several promising avenues for antifungal resistance research:

• Energy metabolism and drug efflux:

  • Investigate how ATP9 function affects ATP availability for drug efflux pumps

  • Explore potential synergy between ATP synthase inhibitors and conventional antifungals

  • Examine correlation between ATP9 mutations and expression of efflux pumps CgCDR1 and CgCDR2

• Regulatory network exploration:

  • Analyze transcription factors that coordinate ATP9 expression with drug resistance genes

  • Research suggests transcription factors like CgXbp1 regulate both virulence-related genes and those associated with drug resistance

  • Investigate how mitochondrial dysfunction triggers compensatory responses affecting drug resistance

• Metabolic adaptation mechanisms:

  • Study how C. glabrata adapts its energy metabolism during azole exposure

  • Examine ATP9 expression during macrophage infection and azole treatment

  • Explore metabolic remodeling as a resistance mechanism

• Novel therapeutic targets:

  • Evaluate ATP9 as a potential antifungal target itself

  • Investigate species-specific features that could enable selective targeting

  • Explore combination approaches targeting both mitochondrial function and established resistance mechanisms

• Temporal dynamics of resistance:

  • Apply time-course experiments similar to macrophage infection studies to azole exposure

  • Characterize the temporal sequence of metabolic adaptations during resistance development

  • Identify critical early response genes that might be targeted to prevent resistance

Table 5: Priority Research Directions for ATP9 in Antifungal Resistance

Understanding the neofunctionalization of transcription factors like CgMar1, which appears to be involved in azole susceptibility regulation , alongside the temporal dynamics of C. glabrata's response to stressors, provides a framework for investigating ATP9's role in resistance mechanisms.

What technological advances would most benefit future research on C. glabrata ATP9?

Several technological advances would significantly enhance C. glabrata ATP9 research:

• Improved mitochondrial genome editing techniques:

  • CRISPR-based approaches adapted for mitochondrial targets

  • More efficient methods for achieving homoplasmy

  • Site-specific recombination systems for precise mtDNA modifications

  • These would overcome current limitations in generating ATP9 variants

• Advanced heteroplasmy tracking tools:

  • Single-cell sequencing methods optimized for mtDNA

  • Live-cell imaging of heteroplasmic populations

  • Fluorescent reporters for different mtDNA variants

  • These would improve understanding of heteroplasmy dynamics identified in C. glabrata studies

• Structural biology innovations:

  • Improved cryo-EM methods for membrane protein complexes

  • Novel approaches for stabilizing ATP synthase complexes

  • High-resolution structural techniques compatible with lipid environments

  • These would enable detailed structure-function analysis of ATP9 within ATP synthase

• Systems biology integration:

  • Multi-omics approaches to correlate ATP9 function with global cellular responses

  • Computational models of C. glabrata energy metabolism

  • Network analysis tools to map ATP9's position in regulatory networks

  • These would contextualize ATP9 within C. glabrata's adaptation to stressors and host environments

• Host-pathogen interaction technologies:

  • Improved ex vivo infection models

  • Real-time monitoring of pathogen metabolism during infection

  • Single-cell RNA-seq of host-pathogen interactions

  • These would build upon the temporal transcriptional response studies during macrophage infection

Advances in measuring RNA polymerase II occupancy to map genome-wide transcription responses, as demonstrated in C. glabrata macrophage infection studies , represent an example of how technological innovation can provide new insights into C. glabrata biology. Similar advances focused specifically on mitochondrial genes and functions would greatly benefit ATP9 research.

How can I resolve common issues in mitochondrial DNA manipulation experiments with C. glabrata?

When troubleshooting mtDNA manipulation experiments in C. glabrata, address these common challenges:

• Persistent heteroplasmy:

  • Challenge: Transformed mtDNA coexists with original mtDNA even under selection pressure

  • Solution: Implement extended selection under appropriate conditions (aerobic for loss of original mtDNA, anaerobic for loss of transformed mtDNA)

  • Monitor ROS levels, as they influence heteroplasmy dynamics

  • Use single-cell isolation followed by molecular screening to identify homoplasmic clones

• Failed transformation attempts:

  • Challenge: Low efficiency of mitochondrial transformation

  • Solution: Optimize biolistic parameters (pressure, distance, DNA coating)

  • Use mtDNA-specific selectable markers (e.g., recoded ARG8)

  • Implement recovery periods before applying selection

  • Consider alternative delivery methods like mitochondria-targeted nucleases

• Phenotypic instability:

  • Challenge: Variable phenotypes in apparently identical strains

  • Solution: Regularly monitor mtDNA status throughout experiments

  • Quantify heteroplasmy levels using qPCR

  • Maintain consistent growth conditions to prevent selection bias

  • Restart cultures from verified frozen stocks regularly

• Unexpected compensatory mechanisms:

  • Challenge: Cells develop unexpected adaptations masking expected phenotypes

  • Solution: Use acute induction systems where possible

  • Include early time points in analysis

  • Screen for suppressor mutations in nuclear genes

  • Compare multiple independent transformants

• Technical verification issues:

  • Challenge: Difficulty confirming mitochondrial modifications

  • Solution: Use multiple verification methods (PCR, Southern blot, sequencing)

  • Include controls for mtDNA quantity and quality

  • Optimize DNA extraction for mtDNA recovery

  • Consider long-range PCR for comprehensive analysis

Research with ATP6 deletion in C. glabrata demonstrates that generating homoplasmic mtDNA strains is possible but requires detailed understanding of heteroplasmy dynamics and appropriate selection strategies . Similar principles apply to ATP9 manipulation, though specific dynamics may differ based on the essential nature of this gene for respiratory function.