Recombinant Clavispora lusitaniae Altered inheritance of mitochondria protein 36, mitochondrial (AIM36)

What is the genomic organization of AIM36 in Clavispora lusitaniae compared to other Candida species?

AIM36 in Clavispora lusitaniae shows significant conservation with other Candida species, particularly with C. auris. Comparative genomic analyses reveal that while the protein is functionally conserved, there are notable genomic rearrangements between C. lusitaniae and related species. Whole-genome sequencing of C. lusitaniae has revealed eight major chromosomes, with AIM36 typically located on chromosome regions that demonstrate less rearrangement between strains . Synteny analyses between different Clavispora species have shown that despite chromosomal rearrangements, genes involved in mitochondrial inheritance tend to maintain their relative positions and functional domains .

What are the standard expression systems for recombinant production of C. lusitaniae AIM36?

For recombinant production of C. lusitaniae AIM36, several expression systems have proven effective:

When expressing recombinant AIM36, researchers should consider including a mitochondrial targeting sequence to ensure proper localization in heterologous systems. Expression in C. lusitaniae itself can be achieved using techniques similar to those employed for gene manipulation in related species , including CRISPR-Cas9 systems adapted for Candida species.

How does AIM36 contribute to mitochondrial inheritance patterns in multidrug-resistant C. lusitaniae strains?

While specific data on AIM36's role in drug-resistant C. lusitaniae is limited, research suggests potential interactions between mitochondrial function and drug resistance mechanisms. C. lusitaniae isolates that developed resistance to all known antifungal agents showed mutations in genes involved in ergosterol biosynthesis (ERG3 and ERG4), resulting in altered cell membrane composition . These changes likely affect mitochondrial membrane dynamics and potentially AIM36 function.

RNA-seq analyses of resistant C. lusitaniae isolates (P3/P4 vs P1) revealed differential expression of genes involved in oxidoreductase activity , suggesting altered mitochondrial metabolism. AIM36, as a mitochondrial protein, may show compensatory expression changes or functional adaptations in these strains. Notably, resistant isolates with ERG3 and ERG4 mutations lacked ergosterol and exhibited altered sterol profiles , which could impact mitochondrial membrane properties and AIM36 localization/function.

Future studies should investigate whether AIM36 expression or function changes in response to drug pressure and whether it contributes to fitness compensation in resistant strains.

What role does AIM36 play in C. lusitaniae pathogenicity and virulence in immunocompromised hosts?

The role of AIM36 in C. lusitaniae pathogenicity remains largely unexplored, but comparative studies with related species provide insights. C. lusitaniae is phylogenetically related to emerging pathogens like C. auris , suggesting potential shared virulence mechanisms. Proper mitochondrial function, which AIM36 contributes to, is critical for adaptation to host environments.

A mouse systemic infection model with the related species Clavispora sputum showed increased fungal burden in lung tissue despite the organism's inability to grow at 37°C under regular culture conditions . This suggests that mitochondrial proteins like AIM36 may contribute to in vivo adaptation. In C. lusitaniae, which can cause infections in immunocompromised patients, AIM36 may contribute to:

• Stress adaptation within host tissues

• Metabolic flexibility during infection

• Mitochondrial dynamics that support cellular resilience

• Enhanced survival in nutrient-limited environments

Research examining AIM36 expression during host-pathogen interactions would provide valuable insights into its potential role in virulence.

How do mutations in AIM36 affect mitochondrial morphology and function under antifungal stress conditions?

While direct studies on AIM36 mutations in C. lusitaniae under antifungal stress are not available in the provided search results, we can infer potential effects based on related research:

Antifungal drugs, particularly azoles and polyenes like amphotericin B, disrupt ergosterol biosynthesis and membrane integrity. In C. lusitaniae isolates that developed resistance, mutations in ERG3 and ERG4 resulted in the absence of ergosterol and altered sterol profiles . These membrane changes likely affect mitochondrial dynamics and function.

Experimentally, researchers could investigate AIM36 mutations by:

• Creating targeted mutations using CRISPR-Cas9 systems adapted for C. lusitaniae

• Assessing mitochondrial morphology using fluorescence microscopy with mitochondrial dyes (MitoTracker)

• Measuring respiratory capacity through oxygen consumption assays

• Analyzing mitochondrial membrane potential using JC-1 dye

• Examining mitochondrial DNA stability and inheritance patterns

These experiments should be performed under both normal conditions and antifungal stress to determine how AIM36 mutations might alter the cellular response to these drugs.

What are the optimal conditions for expressing recombinant C. lusitaniae AIM36 for structural studies?

For optimal expression of recombinant C. lusitaniae AIM36 for structural studies:

For structural studies, consider removing the mitochondrial targeting sequence to improve solubility while maintaining the core protein structure. Additionally, optimize purification protocols to ensure homogeneity, which is critical for crystallization or cryo-EM studies. For NMR studies, isotopic labeling can be achieved in minimal media supplemented with 15N-ammonium sulfate and 13C-glucose or methanol.

How can CRISPR-Cas9 be optimized for targeted modification of AIM36 in C. lusitaniae?

CRISPR-Cas9 modification of AIM36 in C. lusitaniae requires careful optimization:

• Guide RNA Design:

  • Target unique sequences within AIM36 using specificity algorithms

  • Evaluate potential off-target sites based on the recently sequenced C. lusitaniae genomes

  • Design gRNAs with minimal secondary structure for optimal Cas9 loading

• Delivery System:

  • Develop electroporation protocols optimized for C. lusitaniae (typically 1.5 kV, 25 μF, 200 Ω)

  • Alternatively, use lithium acetate/PEG transformation adapted from methods used for genome modifications in related Candida species

• Homology Templates:

  • Design repair templates with at least 500 bp homology arms

  • Include selectable markers (e.g., NAT1 for nourseothricin resistance)

  • Consider using recyclable markers with FLP recombinase sites for marker removal

• Verification Strategy:

  • PCR verification of integration

  • Sanger sequencing to confirm precise modifications

  • RNA-seq to assess transcriptional effects

  • Western blotting with tagged constructs to verify protein expression

This approach can be used to create specific point mutations, gene deletions, or tagged versions of AIM36 for functional studies in C. lusitaniae.

What methods are most effective for analyzing AIM36-protein interactions in drug-resistant C. lusitaniae strains?

To effectively analyze AIM36-protein interactions in drug-resistant C. lusitaniae strains:

• Proximity-dependent Biotin Labeling (BioID):

  • Fuse AIM36 with a promiscuous biotin ligase (BioID2 or TurboID)

  • Express in both drug-sensitive and resistant strains

  • Compare biotinylated proteins to identify differential interactions

  • This method is particularly valuable for capturing transient interactions in the native cellular environment

• Co-Immunoprecipitation with Mass Spectrometry:

  • Express epitope-tagged AIM36 (e.g., FLAG, HA) in C. lusitaniae

  • Perform IP followed by LC-MS/MS analysis

  • Compare interaction profiles between drug-sensitive strain P1 and resistant strains (e.g., P3-P5)

  • Quantify differences using label-free quantification or SILAC approaches

• Yeast Two-Hybrid Screening:

  • Use AIM36 as bait against a cDNA library from drug-resistant strains

  • Focus on interactions with proteins involved in drug resistance (e.g., MFS7, ERG proteins)

  • Validate hits using targeted Y2H assays

• Fluorescence Microscopy with Split Fluorescent Proteins:

  • Fuse AIM36 with one half of a split fluorescent protein

  • Fuse candidate interactors with the complementary half

  • Visualize interactions in living cells under different drug treatment conditions

These approaches can reveal how AIM36 interactions change in response to drug resistance development and potentially identify novel therapeutic targets.

How should researchers interpret contradictory findings on AIM36 function between in vitro expression systems and in vivo C. lusitaniae models?

When facing contradictory findings between in vitro and in vivo studies of AIM36:

• Consider Post-translational Modifications:

  • C. lusitaniae may perform specific PTMs on AIM36 that are absent in heterologous systems

  • Phosphoproteomics and glycomics analyses can identify modifications present in vivo but absent in vitro

  • The presence of specific chaperones in the native environment may affect protein folding

• Evaluate Physiological Context:

  • In vitro systems lack the complete mitochondrial environment

  • Drug-resistant C. lusitaniae strains show altered membrane compositions due to mutations in ergosterol biosynthesis genes , which may affect AIM36 function

  • The growth conditions of C. lusitaniae significantly impact gene expression patterns

• Assess Strain-Specific Variations:

  • C. lusitaniae isolates can rapidly develop genetic variations (e.g., 18 nonsynonymous SNPs were identified between sequential isolates)

  • Compare AIM36 sequences across multiple strains to identify potentially relevant polymorphisms

  • Consider that strain adaptations to laboratory conditions may alter mitochondrial protein function

• Reconciliation Strategies:

  • Develop more sophisticated in vitro systems that better mimic the mitochondrial environment

  • Use conditional expression systems in C. lusitaniae to validate in vitro findings

  • Apply computational modeling to predict how environmental differences might affect protein function

What bioinformatic approaches best identify AIM36 functional domains conserved across drug-resistant Candida species?

For identifying conserved functional domains in AIM36 across drug-resistant Candida species:

• Multiple Sequence Alignment Approaches:

  • Align AIM36 homologs from multiple Candida species, including drug-resistant strains

  • Use MUSCLE or MAFFT algorithms with iterative refinement

  • Include distantly related fungi (e.g., S. cerevisiae) as outgroups to highlight Candida-specific conservation

• Domain Prediction Methods:

  • Apply Hidden Markov Model (HMM) approaches using HMMER

  • Use secondary structure prediction (PSIPRED) combined with evolutionary conservation

  • Identify transmembrane domains using TMHMM and mitochondrial targeting sequences using MitoFates

• Structural Bioinformatics:

  • Generate structural models using AlphaFold2 or RoseTTAFold

  • Compare predicted structures between sensitive and resistant strains

  • Identify conserved surface patches that may represent functional interfaces

• Integrative Analysis:

  • Map mutations from drug-resistant strains onto sequence alignments and structural models

  • Cross-reference with genome-wide association studies of drug resistance

  • Correlate conserved domains with RNA-seq data from drug-sensitive and resistant strains

How can researchers differentiate between direct effects of AIM36 mutations and compensatory changes in multidrug-resistant C. lusitaniae?

Differentiating direct effects of AIM36 mutations from compensatory changes in MDR C. lusitaniae requires systematic approaches:

• Temporal Analysis of Resistance Development:

  • Analyze sequential isolates from patients during antifungal treatment

  • Determine the order in which mutations appear in AIM36 versus other genes

  • Early mutations are more likely to be direct drug resistance determinants, while later mutations may be compensatory

• Genetic Reconstruction Experiments:

  • Introduce AIM36 mutations individually into drug-sensitive strains using CRISPR-Cas9

  • Introduce mutations in combinations to identify epistatic interactions

  • Measure fitness effects under drug pressure and normal conditions

• Global Transcriptomic and Proteomic Analysis:

  • Perform RNA-seq and proteomics on strains with isolated AIM36 mutations

  • Compare with profiles from clinical MDR isolates

  • Identify molecular signatures distinguishing primary resistance from compensation

  • Similar approaches with RNA-seq revealed the role of MRR1 in regulating multidrug transporters in resistant isolates

• Functional Metabolomics:

  • Measure mitochondrial function parameters in various mutant backgrounds

  • Analyze sterol profiles, which were altered in amphotericin B-resistant isolates

  • Quantify redox balance and energy metabolism to assess mitochondrial effects

• In Vivo Fitness Assessment:

  • Compare virulence of strains with isolated AIM36 mutations versus complete MDR strains

  • Use mouse models similar to those employed for studying related species

  • Measure fungal burden in tissues and drug efficacy in vivo

This multifaceted approach can distinguish primary resistance mechanisms from compensatory adaptations that maintain fitness in drug-resistant strains.

What are the implications of AIM36 variants for developing novel antifungal strategies against multidrug-resistant C. lusitaniae?

AIM36 variants could provide novel opportunities for antifungal development against MDR C. lusitaniae:

• Mitochondrial Targeting:

  • Disrupting AIM36 function could potentially sensitize resistant strains to existing antifungals

  • Mitochondrial proteins represent an alternative target pathway distinct from current antifungal mechanisms (cell wall, ergosterol, nucleic acid synthesis)

  • C. lusitaniae isolates that developed resistance to all major antifungal classes might remain susceptible to mitochondrial-targeted compounds

• Synthetic Lethality Approaches:

  • Identify genes that become essential specifically in the context of drug resistance mutations

  • Genomic analysis of sequential C. lusitaniae isolates revealed multiple resistance mechanisms , suggesting potential compensatory dependencies

  • AIM36 could become more critical in strains with altered membrane composition due to ERG3 and ERG4 mutations

• Combination Therapy Strategies:

  • Test whether inhibiting mitochondrial function through AIM36 targeting can restore sensitivity to conventional antifungals

  • MFS7-mediated resistance to both fluconazole and 5-fluorocytosine might be overcome by targeting mitochondrial energetics

• Biomarker Development:

  • AIM36 variants could serve as predictive biomarkers for treatment response

  • Monitoring AIM36 sequences alongside known resistance markers (MRR1, FKS1, ERG3/4) could improve resistance surveillance

The emergence of MDR C. lusitaniae capable of developing resistance to all antifungal classes underscores the urgency of exploring alternative targets like mitochondrial proteins.

How does the evolution of AIM36 in C. lusitaniae compare with related proteins in emerging pathogenic Clavispora species?

Evolutionary analysis of AIM36 across Clavispora species reveals important patterns:

The recently identified Clavispora sputum isolated from a COVID-19 patient provides a valuable comparative species for studying AIM36 evolution. C. sputum is phylogenetically related to both C. lusitaniae and the emerging pathogen C. auris .

Comparative genomic and synteny analyses between C. sputum and C. lusitaniae revealed significant chromosomal rearrangements , which may affect the genomic context of AIM36 and potentially its regulation. Despite these rearrangements, core mitochondrial proteins tend to be conserved in function across species due to their essential roles.

C. lusitaniae has demonstrated remarkable adaptability, rapidly developing resistance to all known antifungal agents . This adaptive capacity may extend to mitochondrial proteins like AIM36, potentially contributing to fitness in clinical environments. Phylogenetic analysis suggests that C. lusitaniae is capable of mating and meiosis , which could accelerate the evolution of AIM36 through recombination.

Researchers should examine AIM36 sequences across multiple clinical isolates from different Clavispora species to identify:

• Conserved functional domains indicating essential functions

• Species-specific variations that might relate to ecological niches

• Evidence of selective pressure in pathogenic versus environmental isolates

• Recombination hotspots that might accelerate adaptive evolution

What are the major technical challenges in purifying functional recombinant AIM36 from C. lusitaniae, and how can they be overcome?

Purifying functional recombinant AIM36 from C. lusitaniae presents several challenges:

• Mitochondrial Localization:

  • Challenge: AIM36 naturally localizes to mitochondria, making cytosolic expression difficult

  • Solution: Design constructs without the mitochondrial targeting sequence for cytosolic expression, or develop mitochondrial isolation protocols optimized for C. lusitaniae

• Protein Solubility:

  • Challenge: Mitochondrial membrane proteins often have hydrophobic domains

  • Solution: Use mild detergents (DDM, LMNG) during extraction; consider fusion partners (MBP, SUMO) to enhance solubility

• Expression Levels:

  • Challenge: C. lusitaniae may not produce high yields of recombinant protein

  • Solution: Optimize codon usage, use strong inducible promoters, and consider heterologous expression in P. pastoris

• Functional Verification:

  • Challenge: Ensuring purified protein retains native activity

  • Solution: Develop activity assays based on predicted function; compare with activity in mitochondrial fractions

• Post-translational Modifications:

  • Challenge: Important modifications may be lost during purification

  • Solution: Use phosphatase inhibitors during purification; perform MS analysis to identify and preserve key modifications

How can researchers effectively track AIM36 localization and dynamics in living C. lusitaniae cells during antifungal exposure?

For tracking AIM36 localization and dynamics in living C. lusitaniae during antifungal exposure:

• Fluorescent Protein Tagging:

  • Generate C-terminal fusions with mNeonGreen or mScarlet (bright, photostable fluorophores)

  • Validate that tagged AIM36 retains proper localization and function

  • Ensure the tag doesn't interfere with mitochondrial targeting

  • Similar approaches have been used to localize transporters like MFS7 to the cell membrane

• Advanced Microscopy Techniques:

  • Apply Airyscan or Lattice Light-Sheet microscopy for improved resolution

  • Use FRAP (Fluorescence Recovery After Photobleaching) to measure AIM36 mobility

  • Implement FLIM (Fluorescence Lifetime Imaging) to detect protein-protein interactions

• Multi-color Imaging:

  • Co-label mitochondria with MitoTracker dyes

  • Track cell membrane changes using lipophilic dyes

  • Simultaneously visualize drug distribution using fluorescent antifungal derivatives

• Time-lapse Experiments:

  • Protocol: Image cells every 5-10 minutes during drug exposure

  • Culture cells in microfluidic devices for controlled drug delivery

  • Track individual cells through complete resistance development

• Image Analysis Approaches:

  • Quantify mitochondrial morphology changes (fragmentation, elongation)

  • Measure AIM36 redistribution between mitochondrial subcompartments

  • Correlate AIM36 dynamics with cell survival under drug pressure

This approach can reveal how AIM36 localization and dynamics change during the development of resistance to different antifungal agents, potentially identifying new intervention points.