Recombinant Yarrowia lipolytica Altered inheritance of mitochondria protein 34, mitochondrial (AIM34)

What is the recommended protocol for reconstitution and storage of recombinant AIM34 protein?

For optimal stability and activity of recombinant Y. lipolytica AIM34 protein, follow this established reconstitution and storage protocol:

Reconstitution Protocol:

• Briefly centrifuge the vial prior to opening to bring contents to the bottom

• Reconstitute the lyophilized protein in deionized sterile water to a concentration of 0.1-1.0 mg/mL

• Add glycerol to a final concentration of 50% (recommended, but can be adjusted between 5-50%)

• Aliquot for long-term storage to minimize freeze-thaw cycles

Storage Recommendations:

• Store reconstituted protein at -20°C/-80°C for long-term storage

• For working solutions, store aliquots at 4°C for up to one week

• Avoid repeated freeze-thaw cycles as this significantly reduces protein stability and activity

Stability Information:

• Liquid form: 6 months at -20°C/-80°C

• Lyophilized form: 12 months at -20°C/-80°C

The recommended buffer system is Tris/PBS-based buffer, pH 8.0, containing 6% trehalose . This formulation helps maintain protein stability during storage and subsequent experimental use.

How can I design experiments to study AIM34's role in mitochondrial inheritance in Y. lipolytica?

To investigate AIM34's role in mitochondrial inheritance in Y. lipolytica, a multifaceted experimental approach combining genetic, biochemical, and microscopic methods is recommended:

Genetic Approach:

• Generate a Δaim34 knockout strain using CRISPR/Cas9 technology

  • Recent advancements in Y. lipolytica gene editing have improved efficiency from 16-33% to 86-95% without outgrowth steps

  • Use the eSpCas9 protein integrated into the Y. lipolytica genome for higher fidelity gene editing

• Construct complementation vectors (e.g., using pUB4 vector framework) containing the wild-type AIM34 gene with its native promoter and terminator sequences

  • Include approximately 1,000 bp upstream and 400 bp downstream for proper expression control

Phenotypic Analysis:

• Compare mitochondrial morphology and distribution using fluorescent mitochondrial dyes or mitochondrially-targeted fluorescent proteins

• Assess respiratory function through:

  • Oxygen consumption rate measurements

  • Growth rate analysis on different carbon sources (glucose vs. glycerol)

  • Measurement of respiratory chain complex activities

• Analyze mtDNA stability and inheritance:

  • Quantify mtDNA copy number using qPCR

  • Assess mtDNA-derived transcript levels using RT-qPCR

  • Visualize mt-nucleoids using DNA-specific fluorescent dyes

Protein Interaction Studies:

• Perform co-immunoprecipitation with AIM34 to identify binding partners

• Use in vitro DNA binding assays to assess potential direct interactions with mtDNA

• Conduct yeast two-hybrid or proximity labeling experiments to map the interactome

For a more comprehensive understanding, integrate these approaches with metabolic analysis and growth under various stress conditions as mitochondrial defects often manifest differently under various physiological challenges.

What are the key differences between AIM34 in Y. lipolytica and homologous proteins in other yeast species?

Understanding the differences between AIM34 in Y. lipolytica and its homologs in other yeast species provides insights into both conserved mitochondrial functions and species-specific adaptations:

Sequence and Structural Comparisons:

*Estimated values based on typical conservation patterns between these species; exact values would require sequence alignment analysis

Functional Significance of Differences:

• Y. lipolytica is strictly aerobic and petite-negative, meaning its mitochondrial function is essential for viability , unlike S. cerevisiae which can survive with dysfunctional mitochondria through fermentative metabolism

• The mitochondrial proteome in Y. lipolytica shows adaptations related to its obligate aerobic lifestyle and capacity for lipid accumulation

• While S. cerevisiae can tolerate loss of various mitochondrial proteins, Y. lipolytica shows greater sensitivity to disruptions in mitochondrial function

Evolutionary Context:
Y. lipolytica belongs to basal lineages of hemiascomycetes , positioning it as valuable for comparative analyses of mitochondrial protein evolution. Its divergence from the Saccharomyces lineage preceded many of the adaptations that allowed facultative anaerobic growth, potentially preserving more ancestral features in its mitochondrial proteins.

For researchers studying AIM34 across species, these differences highlight the importance of considering the metabolic context when interpreting functional studies or attempting to extrapolate findings between yeast species.

What techniques are available for expressing and purifying functional AIM34 from Y. lipolytica?

Several expression and purification strategies have been successfully employed for recombinant Y. lipolytica mitochondrial proteins, including AIM34:

Expression Systems:

• E. coli Expression System:

  • Most commonly used for AIM34 production

  • Typically expressed with N-terminal His tag for affinity purification

  • Mature form (amino acids 29-240) without mitochondrial targeting sequence is expressed to improve solubility

• Yeast Expression Systems:

  • Homologous expression in Y. lipolytica

    • Advantages: Proper folding, potential post-translational modifications

    • Challenges: Lower yields than heterologous systems

  • Heterologous expression in S. cerevisiae

    • Suitable for proteins requiring eukaryotic processing

• Baculovirus Expression:

  • Alternative for proteins requiring eukaryotic folding machinery

  • Higher cost but can improve functionality for complex proteins

Purification Strategies:

Optimized Protocol for AIM34:

• Express mature AIM34 (aa 29-240) with N-terminal His tag in E. coli

• Lyse cells in Tris/PBS-based buffer (pH 8.0) containing protease inhibitors

• Purify using Ni-NTA affinity chromatography

• Perform buffer exchange to remove imidazole

• Concentrate and store with 6% trehalose and 50% glycerol for stability

• Verify purity by SDS-PAGE (expected purity >90%)

This approach typically yields functional protein suitable for biochemical and structural studies. Researchers should consider the intended experimental applications when selecting between these methods, as each offers distinct advantages for different downstream applications.

How does AIM34 contribute to Y. lipolytica's unique mitochondrial properties compared to non-oleaginous yeasts?

Y. lipolytica possesses distinctive mitochondrial properties that support its oleaginous nature and obligate aerobic metabolism, with AIM34 potentially playing a specialized role in these adaptations:

Mitochondrial Uniqueness in Y. lipolytica:

• Obligate Aerobic Metabolism:

  • Unlike S. cerevisiae, Y. lipolytica cannot survive without functional mitochondria

  • Mitochondrial proteins like AIM34 likely have evolved under stronger selective pressure for reliability

  • The strictly aerobic nature suggests more extensive mitochondrial networks requiring specialized inheritance mechanisms

• Integration with Lipid Metabolism:

  • Y. lipolytica can accumulate lipids up to 67.66% of dry cell weight when engineered

  • Mitochondrial acetyl-CoA production serves as a critical precursor for lipid biosynthesis

  • Citrate produced in mitochondria is exported and cleaved by ATP citrate lyase to generate cytosolic acetyl-CoA for fatty acid synthesis

• Elevated β-oxidation Capacity:

  • Enhanced ability to utilize hydrophobic substrates through peroxisomal and mitochondrial β-oxidation pathways

  • Specialized transporters for fatty acid uptake (UP1, UP4)

  • Upregulation of mitochondrial β-oxidation enzyme MFE2 significantly increases acetyl-CoA content

Potential AIM34 Contributions:

The specific contribution of AIM34 to these unique properties remains under investigation, but several hypotheses can be formulated based on available data:

• Adaptation to High Mitochondrial Activity:

  • AIM34 may support mitochondrial genome stability under the high respiratory flux conditions typical of oleaginous yeasts

  • Could play a role in mtDNA organization that accommodates the expanded mitochondrial networks needed for elevated respiratory capacity

• Coordination with Lipid Metabolism:

  • May participate in signaling networks that coordinate mitochondrial function with lipid accumulation and mobilization

  • Potentially interacts with mitochondrial membrane systems that must adapt to changing lipid environments

• Support for Specialized Metabolic Pathways:

  • Could facilitate organization of mitochondrial proteins involved in acetyl-CoA production

  • May contribute to the stability of mitochondrial structures during growth on hydrophobic substrates

Understanding these potential specialized functions requires further experimental investigation, including comparative studies between wild-type and Δaim34 strains under various growth conditions and carbon sources.

What methods are effective for analyzing AIM34 interaction with mitochondrial DNA and other nucleoid proteins?

To investigate AIM34 interactions with mitochondrial DNA (mtDNA) and other nucleoid proteins, researchers can employ these complementary methodological approaches:

In Vitro DNA Binding Assays:

• Electrophoretic Mobility Shift Assay (EMSA):

  • Incubate purified AIM34 with labeled mtDNA fragments

  • Analyze shifts in DNA migration on native gels

  • Include unlabeled competitor DNA to assess binding specificity

  • Similar approaches were used for YlMhb1p characterization

• DNA Footprinting:

  • Identify specific DNA sequences protected by AIM34 binding

  • Compare protection patterns with known mtDNA regulatory regions

  • Correlate binding sites with mtDNA maintenance functions

• Surface Plasmon Resonance (SPR):

  • Quantitatively measure AIM34-mtDNA binding kinetics and affinity

  • Compare affinity for different mtDNA sequences and structures

Protein-Protein Interaction Analysis:

• Co-Immunoprecipitation (Co-IP):

  • Use antibodies against AIM34 to pull down interacting proteins

  • Identify partners by mass spectrometry

  • Confirm interactions by reciprocal Co-IP

• Proximity Labeling:

  • Express AIM34 fused to BioID or APEX2 in Y. lipolytica

  • Identify proximal proteins through biotinylation and streptavidin pull-down

  • Map the spatial organization of nucleoid protein complexes

• Yeast Two-Hybrid Screening:

  • Screen for interactions with known nucleoid proteins

  • Identify novel interaction partners

  • Map interaction domains through deletion constructs

In Vivo Nucleoid Visualization:

• Fluorescence Microscopy:

  • Express fluorescently tagged AIM34 (e.g., GFP fusion)

  • Co-visualize with mtDNA using DNA-specific dyes

  • Perform time-lapse imaging to track dynamic interactions

• Chromatin Immunoprecipitation (ChIP):

  • Crosslink AIM34 to mtDNA in vivo

  • Immunoprecipitate AIM34-bound DNA fragments

  • Sequence precipitated fragments to map binding sites genome-wide

• Structured Illumination Microscopy (SIM) or STORM:

  • Achieve super-resolution imaging of nucleoid structures

  • Localize AIM34 within subdomains of mitochondrial nucleoids

  • Correlate with functional mtDNA regions

For a comprehensive analysis, researchers should combine multiple approaches from each category. This integrated strategy would provide complementary data on both the physical and functional interactions of AIM34 with mtDNA and other nucleoid proteins, revealing its role in mitochondrial genome maintenance.

How does the expression and function of AIM34 change under different carbon sources and growth conditions?

The expression and function of AIM34 in Y. lipolytica likely undergo significant regulation in response to different carbon sources and growth conditions, reflecting the metabolic adaptability of this oleaginous yeast:

Carbon Source Effects:

Growth Phase and Nutrient Availability:

• Nitrogen Limitation:

  • Under nitrogen-limited conditions, Y. lipolytica accumulates lipids (up to 14.3% of biomass)

  • AIM34 expression may be modulated to support mitochondrial function during this metabolic shift

  • Metabolic flux through ATP:citrate lyase increases significantly during nitrogen limitation

• Growth Phase Transitions:

  • Expression patterns of mitochondrial proteins often change between exponential and stationary phases

  • Late growth phase (OD max) shows increased expression of β-oxidation genes like MFE2

  • AIM34 may show similar regulation patterns to support changing mitochondrial requirements

Stress Conditions:

• Oxidative Stress:

  • Mitochondrial proteins often respond to ROS fluctuations

  • AIM34 may participate in protective mechanisms for mtDNA under oxidative stress

• Temperature Variation:

  • Y. lipolytica grows optimally at 28°C

  • Temperature shifts may alter mitochondrial protein expression patterns, including AIM34

Methodological Approaches to Study AIM34 Regulation:

• Transcriptional Analysis:

  • qRT-PCR to quantify AIM34 mRNA levels under different conditions

  • RNA-seq to place AIM34 regulation in context of global transcriptional changes

  • Promoter analysis to identify regulatory elements responsive to metabolic signals

• Protein Level Assessment:

  • Western blotting with anti-AIM34 antibodies

  • Proteomics to identify post-translational modifications

  • Protein stability assays to determine if regulation occurs at degradation level

• Functional Analysis:

  • Compare phenotypes of Δaim34 mutants across different carbon sources

  • Assess mitochondrial morphology and function changes using fluorescent reporters

  • Measure mtDNA stability under different growth conditions in presence/absence of AIM34

This comprehensive analysis would provide insights into how AIM34 contributes to the remarkable metabolic flexibility of Y. lipolytica across diverse environmental conditions.

What are the advanced techniques for studying AIM34's role in mtDNA maintenance and replication?

Investigating AIM34's specific role in mtDNA maintenance and replication requires sophisticated molecular and imaging techniques that can capture both static and dynamic aspects of mitochondrial genome stability:

Advanced Molecular Techniques:

• 2D Agarose Gel Electrophoresis:

  • Separate mtDNA based on both size and shape

  • Detect replication intermediates and recombination structures

  • Compare profiles between wild-type and Δaim34 strains to identify specific defects in mtDNA metabolism

• mtDNA Topology Analysis:

  • Use chloroquine gels to separate different topological forms of mtDNA

  • Assess the distribution of supercoiled, relaxed, and nicked mtDNA molecules

  • Determine if AIM34 affects the topological state of the mitochondrial genome

• In Organello mtDNA Synthesis:

  • Isolate intact mitochondria from wild-type and Δaim34 strains

  • Supply radioactive nucleotides to measure mtDNA synthesis rates

  • Identify specific steps in replication affected by AIM34 absence

Cutting-Edge Imaging Approaches:

• Super-Resolution Microscopy:

  • Visualize individual nucleoids at ~20nm resolution using PALM/STORM

  • Track AIM34 localization relative to mtDNA and replication machinery

  • Determine if AIM34 localizes to specific subdomains within nucleoids

• Live-Cell Imaging with Photoactivatable Fluorophores:

  • Monitor real-time dynamics of AIM34 during mtDNA replication

  • Use pulse-chase approaches to track newly synthesized mtDNA

  • Correlate AIM34 movements with mtDNA synthesis events

• Correlative Light and Electron Microscopy (CLEM):

  • Combine fluorescence imaging of AIM34 with ultrastructural analysis

  • Visualize AIM34 in relation to mitochondrial membrane structures

  • Provide nanoscale context for AIM34 function within mitochondria

Genetic and Biochemical Approaches:

• mtDNA Point Mutation and Deletion Analysis:

  • Measure mutation and deletion frequencies using next-generation sequencing

  • Compare mtDNA stability between wild-type and Δaim34 strains

  • Determine if specific mtDNA regions are differentially affected

• Protein-mtDNA Crosslinking:

  • Use formaldehyde or UV crosslinking to capture transient interactions

  • Identify precise mtDNA sequences bound by AIM34 in vivo

  • Map binding patterns across the mitochondrial genome

• Reconstituted In Vitro Systems:

  • Reconstitute minimal mtDNA maintenance systems with purified components

  • Test the effect of adding or removing AIM34 on replication efficiency

  • Identify direct biochemical activities of AIM34 in controlled settings

By combining these advanced approaches, researchers can develop a comprehensive model of AIM34's role in maintaining mtDNA integrity through replication, repair, and structural organization processes.

How can I design experiments to assess the impact of AIM34 mutations on Y. lipolytica metabolism and mitochondrial function?

To systematically assess the impact of AIM34 mutations on Y. lipolytica metabolism and mitochondrial function, a multi-tiered experimental approach is recommended:

Mutation Design and Strain Construction:

• Targeted Mutation Strategies:

  • Complete gene deletion using CRISPR/Cas9 with integrated eSpCas9 for high efficiency (>86%)

  • Point mutations in conserved residues identified through sequence alignment

  • Domain-specific deletions based on structural predictions

  • C-terminal or N-terminal tagging for functional studies

• Expression Control:

  • Replace native promoter with regulatable promoters like pPOX2 or pLIP2

  • These promoters show different induction levels in response to oleic acid

  • Enable controlled expression for dose-dependent studies

Comprehensive Phenotypic Analysis:

• Growth Profiling:

  • Measure growth rates on different carbon sources (glucose, glycerol, oleic acid)

  • Conduct stress response assays (oxidative, temperature, osmotic)

  • Perform competitive growth assays with wild-type strains

• Mitochondrial Morphology and Dynamics:

  • Visualize mitochondrial networks using fluorescent markers

  • Quantify network parameters (length, branching, fragmentation)

  • Track inheritance patterns during cell division

• Mitochondrial Genome Stability:

  • Quantify mtDNA copy number by qPCR

  • Assess mtDNA integrity through long-range PCR and sequencing

  • Measure mtDNA transcription levels via RT-qPCR

Metabolic Analysis:

• Respirometry:

  • Measure oxygen consumption rates (OCR) with a Seahorse analyzer or oxygen electrode

  • Assess specific activity of respiratory chain complexes

  • Determine respiratory capacity and reserve

• Metabolomics:

  • Perform targeted analysis of TCA cycle intermediates

  • Measure acetyl-CoA levels, which can increase up to 82% when β-oxidation is enhanced

  • Analyze lipid profiles and accumulation patterns

• 13C-Metabolic Flux Analysis:

  • Use 13C-labeled glucose to trace carbon flow through central metabolism

  • Compare flux distributions between wild-type and mutant strains

  • Identify specific metabolic pathways affected by AIM34 mutations

Experimental Design Table for Key Assays:

This systematic approach will provide comprehensive insights into AIM34's role in Y. lipolytica metabolism and mitochondrial function, with particular relevance to its unique status as an oleaginous, strictly aerobic yeast.

What are the key considerations for designing recombinant AIM34 for structure-function studies?

Designing recombinant AIM34 constructs for structure-function studies requires careful consideration of several factors to ensure proper protein folding, activity, and experimental utility:

Domain Architecture and Construct Design:

• Mitochondrial Targeting Sequence (MTS) Removal:

  • The N-terminal MTS (amino acids 1-28) should be excluded from expression constructs

  • Mature protein (aa 29-240) shows improved solubility and stability in recombinant systems

  • For Y. lipolytica proteins, proper MTS prediction is critical as they can differ from other yeasts

• Domain-Based Constructs:

  • Consider expressing individual functional domains separately

  • Similar to the approach used for YlMhb1p, where N-terminal (aa 15-156) and C-terminal (aa 157-238) regions were expressed separately

  • Test various domain boundaries based on bioinformatic predictions

Expression System Optimization:

• E. coli Expression:

  • Use BL21(DE3) or similar strains optimized for recombinant protein expression

  • Consider Rosetta strains if Y. lipolytica codon usage differs significantly from E. coli

  • Express at lower temperatures (16-25°C) to improve folding

• Yeast Expression Systems:

  • For complex folding requirements, consider expression in Y. lipolytica itself

  • Alternative: use S. cerevisiae with appropriate promoters and targeting signals

  • Expression in yeast may preserve critical post-translational modifications

Tag Selection and Placement:

Buffer Optimization for Stability:

• Storage Buffer Composition:

  • Tris/PBS-based buffer, pH 8.0, with 6% trehalose has shown good results

  • Add 50% glycerol for long-term storage at -20°C/-80°C

  • Avoid repeated freeze-thaw cycles to maintain activity

• Additives for Enhanced Stability:

  • Consider reducing agents (DTT, β-mercaptoethanol) if cysteine residues are present

  • Test different salt concentrations to optimize stability

  • Evaluate stabilizing agents like arginine or proline

Functional Validation Approaches:

• In Vitro Activity Assays:

  • Design assays for predicted biochemical activities (DNA binding, protein interaction)

  • Include positive controls with known activity

  • Validate that recombinant protein retains native activity

• Complementation Studies:

  • Test if recombinant constructs can complement Δaim34 phenotypes when expressed in vivo

  • Use this approach to validate functional importance of specific domains or residues

By integrating these considerations into recombinant protein design, researchers can maximize the likelihood of obtaining properly folded, functionally active AIM34 protein suitable for detailed structure-function analysis.

What are the challenges and solutions for expressing AIM34 in heterologous systems for functional studies?

Expressing Y. lipolytica AIM34 in heterologous systems presents several challenges, each requiring specific strategies to overcome:

Challenge 1: Codon Usage Bias

Y. lipolytica has a distinct codon usage pattern that may limit expression efficiency in heterologous hosts.

Solutions:

• Codon optimization for the target expression system

• Use of specialized E. coli strains (e.g., Rosetta) that supply rare tRNAs

• For high-yield production, synthesize a codon-optimized gene rather than using native sequence

Challenge 2: Protein Solubility and Folding

Mitochondrial proteins often have hydrophobic regions that can cause aggregation when expressed in prokaryotic systems.

Solutions:

• Expression at reduced temperatures (16-18°C) to slow folding and increase proper conformation

• Use of solubility tags such as GST, MBP, or SUMO

• Addition of chemical chaperones to growth media (e.g., sorbitol, arginine)

• Co-expression with molecular chaperones (GroEL/GroES, DnaK/DnaJ/GrpE)

Challenge 3: Post-Translational Modifications

Y. lipolytica may apply specific modifications to AIM34 that are absent in prokaryotic systems.

Solutions:

• Identify potential modification sites through bioinformatic analysis

• Express in eukaryotic systems (yeast, insect cells) when modifications are critical

• Consider site-directed mutagenesis to mimic constitutive modifications

Challenge 4: Mitochondrial Targeting Sequence Interference

The N-terminal mitochondrial targeting sequence can cause improper folding or aggregation.

Solutions:

• Remove the predicted mitochondrial targeting sequence (aa 1-28)

• Express only the mature protein (aa 29-240)

• Verify proper N-terminal processing through mass spectrometry

Challenge 5: Protein Purification Complications

Mitochondrial proteins may interact nonspecifically with cellular components, complicating purification.

Solutions:

• Optimize lysis conditions (detergents, salt concentration)

• Use multistep purification strategies to increase purity

• Consider on-column refolding for proteins recovered from inclusion bodies

Experimental Approach Comparison:

Case Study Example:
When expressing a similar Y. lipolytica mitochondrial protein (YlMhb1p), researchers successfully employed E. coli expression with GST-fusion and domain separation strategies . This approach allowed for both structural and functional studies of the protein. A similar strategy, with appropriate modifications for AIM34-specific characteristics, would likely yield functional protein for in vitro studies.

By systematically addressing these challenges, researchers can successfully express functional AIM34 in heterologous systems, enabling detailed biochemical and structural characterization.

How can I integrate AIM34 research with broader studies of Y. lipolytica as a biotechnology platform?

Integrating AIM34 research with broader applications of Y. lipolytica as a biotechnology platform creates valuable synergies for both fundamental understanding and applied research:

Connections to Y. lipolytica's Industrial Applications:

Integration Strategies:

• Metabolic Engineering Framework:

  • Include AIM34 and related mitochondrial factors in metabolic engineering designs

  • Consider mitochondrial impacts when overexpressing pathways that affect redox balance

  • Design experiments that monitor mitochondrial function alongside production metrics

• Strain Development Approach:

  • Create a matrix of AIM34 variants (wild-type, deletion, overexpression) in production strains

  • Test performance across different carbon sources and growth conditions

  • Identify optimal AIM34 status for specific production objectives

• Multi-Omics Integration:

  • Combine transcriptomics, proteomics, and metabolomics data

  • Map AIM34 function within networks affecting industrial phenotypes

  • Identify unexpected connections between mitochondrial function and production traits

Research Design Table:

Case Study Approach:
When engineering Y. lipolytica for β-carotene production, researchers achieved yields of 164 mg/L by enhancing the mevalonate pathway and acetyl-CoA production . Investigating how AIM34 status affects these same pathways could reveal additional opportunities for yield improvement. Similar approaches could be applied to other production systems, potentially leading to new engineering targets for industrial strain development.

By systematically connecting AIM34 research to industrial applications, researchers can contribute both to fundamental understanding of mitochondrial biology and to practical improvements in Y. lipolytica's capabilities as a biotechnology platform.

What bioinformatic approaches are useful for analyzing AIM34 structure, function, and evolutionary conservation?

A comprehensive bioinformatic analysis of AIM34 can provide valuable insights into its structure, function, and evolutionary context, guiding experimental approaches:

Sequence Analysis and Functional Prediction:

• Homology Detection and Multiple Sequence Alignment:

  • Identify homologs across fungal lineages using PSI-BLAST and HMM-based searches

  • Construct multiple sequence alignments to identify conserved residues

  • Pay special attention to conservation patterns between petite-positive and petite-negative yeasts

• Domain and Motif Identification:

  • Scan for known functional domains using InterPro, Pfam, and SMART

  • Identify short linear motifs using ELM that might mediate protein interactions

  • Search for mitochondrial targeting signals using MitoFates and TargetP

• Functional Site Prediction:

  • Identify potential DNA-binding regions based on charge distribution and conservation

  • Predict post-translational modification sites using NetPhos, GPS, etc.

  • Analyze surface properties to identify potential protein-protein interaction sites

Structural Analysis:

• Secondary Structure Prediction:

  • Use PSIPRED, JPred, or SPIDER3 to predict secondary structure elements

  • Identify potential transmembrane segments using TMHMM or Phobius

  • Analyze disorder propensity using IUPred or PONDR

• Tertiary Structure Prediction:

  • Generate 3D structural models using AlphaFold2 or RoseTTAFold

  • Validate models using PROCHECK, VERIFY3D, or MolProbity

  • Dock models with potential interaction partners (mtDNA, proteins)

• Integrative Structural Analysis:

  • Map conservation onto predicted structures to identify functional hotspots

  • Analyze electrostatic surface potential to identify nucleic acid binding regions

  • Perform molecular dynamics simulations to assess conformational flexibility

Evolutionary Analysis:

• Phylogenetic Profiling:

  • Construct phylogenetic trees to trace AIM34 evolution across fungal lineages

  • Correlate presence/absence patterns with metabolic capabilities

  • Identify potential co-evolution with other mitochondrial proteins

• Selection Pressure Analysis:

  • Calculate dN/dS ratios to identify sites under positive or purifying selection

  • Compare evolutionary rates between aerobic and facultatively anaerobic lineages

  • Identify potential functional shifts through evolutionary rate changes

• Comparative Genomics:

  • Analyze gene neighborhood conservation across species

  • Identify co-expression patterns with functionally related genes

  • Examine regulation motifs in promoter regions

Integrated Bioinformatic Workflow:

This comprehensive bioinformatic approach provides a strong foundation for experimental design, helping to prioritize specific residues for mutagenesis, predict functional interactions, and place AIM34 within the broader context of mitochondrial biology and evolution in Y. lipolytica.

How can I design CRISPR/Cas9 strategies for efficient modification of AIM34 in Y. lipolytica?

Recent advances in CRISPR/Cas9 technology for Y. lipolytica enable highly efficient modification of AIM34 with success rates exceeding 85% . Here's a comprehensive strategy for designing efficient gene editing approaches:

CRISPR/Cas9 System Selection:

• Integrated eSpCas9 System:

  • The recently developed eSpCas9 integrated into Y. lipolytica genome shows significantly enhanced editing efficiency

  • Achieves 86.09-95.19% efficiency without time-consuming outgrowth steps

  • Reduces off-target effects while maintaining high on-target activity

• Alternative Systems:

  • pCRISPRyl for expression of standard SpCas9

  • CRISPR-Cas12a (Cpf1) system for alternative PAM recognition

  • RNA polymerase III promoter-driven systems for sgRNA expression

sgRNA Design for AIM34 Targeting:

• Target Site Selection Criteria:

  • Identify 20 bp sequences followed by NGG PAM sites within AIM34 (YALI0B08118g)

  • Prioritize sites with high on-target scores and low off-target potential

  • Target early in the coding sequence to ensure loss of function in knockout experiments

  • For precise modifications, target close to the desired modification site

• Promoter Selection for sgRNA Expression:

  • tRNA-sgRNA fusion constructs improve efficiency

  • Synthetic RNA Polymerase III promoters enhance CRISPR-mediated editing

• Optimization Strategies:

  • Use RNA folding prediction to ensure sgRNA scaffold accessibility

  • Consider GC content (40-60% ideal) for efficient targeting

  • Avoid homeopolymeric sequences that may cause transcription termination

Repair Template Design:

• For Gene Knockout:

  • Design homology arms of 40-60 bp flanking the cut site

  • Include selection marker (URA3, LEU2) for efficient screening

  • Consider marker recycling strategies using Cre-lox or similar systems

• For Point Mutations or Tagged Versions:

  • Include at least 40 bp homology arms on each side

  • Introduce silent mutations in the PAM site to prevent re-cutting

  • For protein tagging, ensure flexible linkers between AIM34 and tags

Y. lipolytica Strain Considerations:

• Strain Selection:

  • Po1f strain is commonly used for gene manipulation

  • Consider strains with integrated eSpCas9 for highest efficiency

  • For multi-gene modifications, diploid strains can be created through mating

• Transformation Protocol:

  • Lithium acetate/PEG method optimized for Y. lipolytica

  • Electroporation for higher transformation efficiency

  • Allow sufficient recovery time in rich media before selection

Experimental Design Table for AIM34 Modifications:

Verification Strategies:

• PCR-based Screening:

  • Design primers spanning expected modification sites

  • Use size differences, restriction digestion, or sequencing to confirm edits

  • Consider colony PCR protocols optimized for Y. lipolytica

• Functional Verification:

  • For knockout: confirm absence of AIM34 expression by RT-PCR or Western blot

  • For tagged versions: verify localization and expression patterns

  • For point mutations: combine sequencing with functional assays