Recombinant Saccharomyces cerevisiae Uncharacterized protein YFR010W-A (YFR010W-A)

What is YFR010W-A and what do we currently know about its structure?

YFR010W-A is an uncharacterized protein from the budding yeast Saccharomyces cerevisiae, consisting of 62 amino acids with the sequence: MYTFSYSTHNELLEFFHLFVTIQWLALIGQKTLSQFCLYRNAAVVGFFIRFTFGTPIFLQLL . It is considered an evolutionarily young "emerging gene" that appears to exist only in S. cerevisiae . Recent studies suggest it may be one of 35 uncharacterized proteins potentially localized to mitochondria (UPMs), though it lacks a conventional N-terminal mitochondrial localization signal . The protein can be expressed recombinantly with an N-terminal His tag in E. coli expression systems for research purposes .

Why are researchers interested in studying uncharacterized yeast proteins like YFR010W-A?

Researchers study uncharacterized proteins like YFR010W-A for several compelling scientific reasons. Primarily, protein localization to specific organelles provides critical clues to infer a protein's function, making mitochondrial localization particularly interesting . YFR010W-A belongs to a group of "emerging genes" that represent an opportunity to study protein evolution and de novo gene birth processes. Additionally, some UPMs including YFR010W-A show upregulation during the postdiauxic shift phase when mitochondria are developing, suggesting functional relevance to mitochondrial processes . Understanding such proteins can provide insights into fundamental cellular processes and potentially reveal novel functional pathways specific to S. cerevisiae.

What experimental methods are commonly used to express and purify YFR010W-A for research?

For expression and purification of recombinant YFR010W-A, researchers typically employ the following methodological approach:

• Expression system: E. coli is the preferred host for recombinant production, with the full-length protein (1-62 amino acids) fused to an N-terminal His tag .

• Purification protocol:

  • Affinity chromatography using nickel resins to capture the His-tagged protein

  • SDS-PAGE analysis confirms purity (typically >85-90%)

  • Final preparation as a lyophilized powder

• Storage and handling:

  • Reconstitution in deionized sterile water to 0.1-1.0 mg/mL

  • Addition of 5-50% glycerol (typically 50%) as a cryoprotectant

  • Storage at -20°C/-80°C with minimal freeze-thaw cycles

  • Working aliquots can be maintained at 4°C for up to one week

• Buffer composition: Tris/PBS-based buffer containing 6% trehalose at pH 8.0, which enhances stability during lyophilization and storage .

How was YFR010W-A identified as a potential mitochondrial protein, and what evidence supports this localization?

YFR010W-A was identified as a potential mitochondrial protein through a systematic screening approach using computational prediction followed by experimental validation:

• Initial identification: The protein was first predicted to localize to mitochondria using the computational tool DeepLoc-1.0, which analyzes protein sequences for organelle-targeting features .

• Experimental validation methodology: Researchers employed a GFPdeg fusion protein system, where GFP is rapidly degraded in the cytoplasm but protected from degradation when localized to organelles like mitochondria . This allowed visualization of potential mitochondrial localization.

• Selection criteria: From the budding yeast proteome, proteins predicted to localize to mitochondria were filtered to remove those with already known mitochondrial localization or function, resulting in 95 candidates of unknown function for analysis .

• Experimental results: When expressed as GFPdeg fusion proteins, 35 uncharacterized proteins including YFR010W-A showed fluorescence patterns consistent with mitochondrial localization .

• Notable characteristics: Unlike many conventional mitochondrial proteins, YFR010W-A lacks an N-terminal mitochondrial localization signal, suggesting it may utilize an alternative import mechanism or function at the mitochondrial outer membrane .

The combined computational prediction and experimental validation provides strong evidence for YFR010W-A's mitochondrial localization, though further studies are needed to determine its precise submitochondrial localization and function.

What expression patterns does YFR010W-A exhibit during different yeast growth phases, and what might this indicate about its function?

Gene expression analysis reveals distinctive patterns for YFR010W-A across yeast growth phases:

• Postdiauxic shift upregulation: YFR010W-A shows increased expression during the postdiauxic shift phase, when yeast cells transition from fermentative to respiratory metabolism following glucose depletion .

• Correlation with mitochondrial development: This upregulation coincides with a period of mitochondrial development and increased mitochondrial activity, suggesting a potential role in respiratory metabolism or mitochondrial biogenesis .

• Metabolic context: During postdiauxic shift, yeast cells reprogram their metabolism to utilize non-fermentable carbon sources, requiring functional mitochondria for oxidative phosphorylation.

• Comparative analysis: The temporal expression pattern of YFR010W-A shares similarities with other mitochondrial proteins involved in respiratory chain function and mitochondrial organization.

This expression profile strongly suggests YFR010W-A may play a role in mitochondrial function specifically related to respiratory metabolism or adaptation to nutrient limitation. The correlation between its upregulation and mitochondrial development during metabolic transition provides valuable clues for experimental design focusing on respiratory growth conditions.

How can researchers study the potential interaction partners of YFR010W-A to elucidate its function?

To identify potential interaction partners of YFR010W-A, researchers should employ multiple complementary approaches:

• Affinity purification-mass spectrometry (AP-MS):

  • Express His-tagged YFR010W-A in yeast cells

  • Perform crosslinking to capture transient interactions

  • Purify using nickel affinity chromatography

  • Identify co-purifying proteins via mass spectrometry

• Proximity-based labeling:

  • Create fusion constructs with BioID or APEX2 enzymes

  • Express in yeast and allow proximity-dependent labeling

  • Purify biotinylated proteins and identify by mass spectrometry

  • This approach is particularly valuable for membrane-associated proteins

• Yeast two-hybrid screening:

  • Use YFR010W-A as bait against a yeast genomic library

  • Screen for positive interactions under stringent conditions

  • Validate interactions using orthogonal methods

• Co-immunoprecipitation with mitochondrial candidates:

  • Test interaction with proteins involved in mitochondrial processes

  • Focus on proteins co-expressed during postdiauxic shift

  • Use tagged versions of candidate partners

• Genetic interaction mapping:

  • Perform synthetic genetic array analysis with YFR010W-A deletion

  • Identify genes showing synthetic lethality or rescue effects

  • Construct interaction networks to place YFR010W-A in functional pathways

Each approach has specific strengths and limitations, so using multiple methods provides the most reliable results. Interactions should be validated across different experimental conditions, particularly those mimicking postdiauxic shift when YFR010W-A is upregulated.

What strategies can researchers use to investigate the functional consequences of YFR010W-A deletion or overexpression?

Researchers can employ several methodological approaches to investigate functional consequences of YFR010W-A manipulation:

Deletion analysis approaches:

• CRISPR-Cas9 gene deletion:

  • Design guide RNAs targeting the YFR010W-A locus

  • Replace with selection marker through homologous recombination

  • Verify deletion through PCR and sequencing

• Phenotypic characterization:

  • Growth curves in fermentative vs. respiratory media

  • Oxygen consumption rate measurements

  • Mitochondrial membrane potential assessment

  • Reactive oxygen species (ROS) detection

  • ATP production quantification

• Stress response testing:

  • Oxidative stress (H₂O₂, paraquat)

  • Respiratory inhibitors (antimycin A, oligomycin)

  • Carbon source shifts (glucose to glycerol/ethanol)

  • Temperature sensitivity

Overexpression analysis:

• Controlled expression systems:

  • GAL1 promoter for galactose-inducible expression

  • TET-on/off systems for tetracycline-regulated expression

  • Integration at specific loci for consistent expression levels

• Impact assessment:

  • Mitochondrial morphology (fluorescence microscopy)

  • Respiratory capacity (high-resolution respirometry)

  • Cell viability and growth rate determination

  • Protein aggregation analysis

• Complementation experiments:

  • Test variant forms (point mutations, truncations)

  • Cross-species complementation attempts

  • Structure-function relationship analysis

The experimental design should include appropriate controls, such as wild-type strains and strains with deletion/overexpression of known mitochondrial proteins. Time-course analyses are particularly important, focusing on the postdiauxic shift phase when YFR010W-A is naturally upregulated.

How can researchers determine the precise submitochondrial localization of YFR010W-A?

Determining the precise submitochondrial localization of YFR010W-A requires a multi-faceted experimental approach:

• Submitochondrial fractionation:

  • Isolate intact mitochondria from yeast expressing tagged YFR010W-A

  • Separate outer membrane, intermembrane space, inner membrane, and matrix

  • Analyze fractions by Western blotting alongside marker proteins for each compartment

  • Use controls such as Tom20 (outer membrane), cytochrome c (intermembrane space), ATP synthase (inner membrane), and Hsp60 (matrix)

• Protease protection assays:

  • Treat isolated mitochondria with increasing concentrations of proteases

  • Compare protease sensitivity of YFR010W-A with known proteins from different compartments

  • Perform with and without membrane permeabilization to distinguish surface-exposed from protected regions

• Super-resolution microscopy:

  • Co-localize fluorescently tagged YFR010W-A with submitochondrial markers

  • Use techniques like STED or PALM microscopy to resolve submitochondrial structures

  • Perform 3D reconstruction to visualize spatial organization

• Immunogold electron microscopy:

  • Label YFR010W-A with gold-conjugated antibodies

  • Visualize precise localization within mitochondrial ultrastructure

  • Quantify gold particle distribution across submitochondrial compartments

• Membrane association analysis:

  • Treat mitochondrial fractions with carbonate extraction or detergents

  • Determine if YFR010W-A behaves as integral membrane, peripheral membrane, or soluble protein

  • Analyze hydrophobicity profile and potential transmembrane domains

• Import assays with submitochondrial targeting signals:

  • Create chimeric constructs with known targeting signals for different compartments

  • Test whether specific submitochondrial targeting enhances localization efficiency

This comprehensive approach will establish the precise compartmental location of YFR010W-A, providing crucial insights into its potential functional role within mitochondria.

What approaches can researchers use to study the expression regulation of YFR010W-A during metabolic shifts?

To study YFR010W-A expression regulation during metabolic shifts, researchers should implement these methodological approaches:

• Promoter analysis and reporter systems:

  • Clone the YFR010W-A promoter region upstream of reporter genes (GFP, luciferase)

  • Create truncation series to identify minimal regulatory elements

  • Perform site-directed mutagenesis on predicted transcription factor binding sites

  • Monitor reporter expression during diauxic shift and other metabolic transitions

• Chromatin immunoprecipitation (ChIP):

  • Identify transcription factors binding to the YFR010W-A promoter

  • Focus on factors known to regulate mitochondrial genes (e.g., Hap2/3/4/5 complex)

  • Perform ChIP-seq to map binding sites genome-wide

  • Compare binding patterns before and after diauxic shift

• RNA analysis:

  • Quantify YFR010W-A mRNA levels using RT-qPCR across growth phases

  • Determine mRNA half-life during fermentative and respiratory growth

  • Perform 5' RACE to identify transcription start sites

  • Assess alternative splicing or RNA processing events

• Epigenetic regulation:

  • Analyze histone modifications at the YFR010W-A locus during metabolic transitions

  • Test the impact of histone deacetylase inhibitors on expression

  • Examine nucleosome positioning changes during metabolic shifts

• Metabolic sensor involvement:

  • Test YFR010W-A expression in strains lacking key metabolic sensors (Snf1, Tor1/2)

  • Examine response to rapamycin, 2-deoxyglucose, and other metabolic modulators

  • Create reporter strains in various genetic backgrounds lacking specific signaling components

• Translational regulation:

  • Perform polysome profiling to assess translation efficiency

  • Analyze 5' and 3' UTR contributions to translation control

  • Examine potential upstream open reading frames (uORFs)

This multi-layered approach will provide comprehensive insights into how YFR010W-A expression is regulated during metabolic transitions, particularly the postdiauxic shift when mitochondrial development occurs.

How should researchers interpret evolutionary analyses of YFR010W-A as an "emerging gene"?

When interpreting evolutionary analyses of YFR010W-A as an "emerging gene," researchers should consider these analytical frameworks:

• Phylogenetic distribution analysis:

  • Map YFR010W-A presence/absence across Saccharomyces species and related yeasts

  • Distinguish between true absence and sequence divergence beyond detection

  • Consider syntenic regions in related species lacking YFR010W-A orthologues

• Sequence evolution rate analysis:

  • Calculate dN/dS ratios to assess selective pressure

  • Compare evolutionary rates with established mitochondrial proteins

  • Identify conserved motifs that may indicate functional domains

  Evolutionary Feature	YFR010W-A	Established Mitochondrial Proteins	Other Emerging Genes
  Species distribution	S. cerevisiae only	Widely conserved	Variable, often lineage-specific
  Sequence conservation	Low across species	High across species	Generally low
  Selective pressure (dN/dS)	To be determined	Typically <1 (purifying)	Often near neutral
  Conserved motifs	Few identified	Multiple well-defined	Few identified

• Genomic context analysis:

  • Examine chromosomal location and neighboring genes

  • Investigate potential origin from non-coding sequences

  • Look for evidence of gene duplication or horizontal transfer

• Structural prediction approaches:

  • Focus on structural features rather than sequence conservation

  • Predict secondary/tertiary structure and compare with known proteins

  • Identify potential functional sites through structure-based methods

• Expression pattern evolution:

  • Compare expression profiles with orthologues if present in close relatives

  • Analyze promoter evolution and transcription factor binding site turnover

  • Evaluate whether expression regulation is conserved or recently evolved

• Functional constraint assessment:

  • Test functional interchangeability between related species

  • Evaluate tolerance to mutations compared to established genes

  • Consider roles in species-specific adaptive processes

When interpreting these analyses, researchers should recognize that emerging genes often follow different evolutionary patterns than established genes. The recent evolutionary origin of YFR010W-A suggests it may represent a lineage-specific innovation potentially involved in S. cerevisiae-specific mitochondrial functions or adaptations.

What statistical approaches are appropriate for analyzing phenotypic effects of YFR010W-A deletion?

When analyzing phenotypic effects of YFR010W-A deletion, researchers should employ these statistical approaches:

These statistical approaches ensure robust analysis of phenotypic data, accounting for biological variability while maximizing the ability to detect subtle but meaningful effects of YFR010W-A deletion.

How can researchers distinguish between direct and indirect effects when studying YFR010W-A function?

Distinguishing between direct and indirect effects in YFR010W-A functional studies requires rigorous methodological approaches:

• Temporal analysis:

  • Implement time-course experiments after YFR010W-A perturbation

  • Monitor cellular changes at multiple time points (minutes, hours, generations)

  • Establish temporal order of events to separate primary from secondary effects

  • Apply time-series statistical methods to identify immediate responses

• Acute vs. chronic depletion:

  • Compare phenotypes from immediate depletion systems (degron tags, inducible systems)

  • Contrast with long-term knockout effects where compensatory mechanisms may arise

  • Quantify differences in immediate vs. adapted responses

  • Design controlled depletion experiments with varying depletion rates

• Direct interaction identification:

  • Perform in vitro binding assays with purified components

  • Use proximity labeling with short labeling windows (minutes)

  • Apply crosslinking mass spectrometry to capture direct binding partners

  • Implement FRET/BRET approaches to detect direct interactions in living cells

• Genetic interaction mapping:

  • Construct double mutants with candidate pathway components

  • Perform epistasis analysis to establish pathway position

  • Use double perturbation to determine functional relationships

  • Apply quantitative interaction score metrics

• Reconstitution experiments:

  • Reintroduce wild-type YFR010W-A to knockout strains

  • Test mutated versions lacking specific domains or functions

  • Perform complementation with orthologues from related species

  • Create chimeric proteins to map functional regions

• Multi-omics integration:

  Data Type	Early Direct Effects	Later Indirect Effects	Integration Approach
  Transcriptomics	Limited gene changes	Widespread reprogramming	Time-series clustering
  Proteomics	Changes in direct interactors	Pathway-wide adaptations	Protein interaction networks
  Metabolomics	Specific metabolite alterations	Metabolic rewiring	Pathway flux analysis
  Phosphoproteomics	Immediate signaling changes	Compensatory pathways	Kinase-substrate networks

• Computational modeling:

  • Develop predictive models of direct YFR010W-A interactions

  • Simulate cascade effects following perturbation

  • Compare model predictions with experimental data

  • Refine models iteratively to distinguish direct from indirect effects

This systematic approach helps researchers distinguish the immediate, direct consequences of YFR010W-A function from the broader cellular adaptations and downstream effects that emerge over time.

What are the key technical challenges in working with small, uncharacterized proteins like YFR010W-A?

Researchers face several technical challenges when studying small, uncharacterized proteins like YFR010W-A:

• Antibody development difficulties:

  • Limited immunogenic epitopes in small proteins (YFR010W-A is only 62 amino acids)

  • Cross-reactivity concerns with related proteins

  • Validation challenges due to low endogenous expression levels

  • Recommended approach: Develop multiple antibodies against different epitopes and validate using knockout controls

• Protein purification challenges:

  • Potential insolubility or aggregation during recombinant expression

  • Tag interference with function of small proteins

  • Degradation during purification procedures

  • Optimization strategy: Test multiple expression systems, tags, and buffer conditions

• Functional assay development:

  • Lack of predictive information to guide assay design

  • Potential redundancy masking phenotypes

  • Subtlety of effects requiring sensitive detection methods

  • Solution approach: Employ high-sensitivity, high-throughput phenotypic screens

• Localization detection issues:

  • Fluorescent tags may be larger than the protein itself (YFR010W-A: ~7 kDa; GFP: ~27 kDa)

  • Tag position can disrupt localization signals

  • Low expression levels requiring signal amplification

  • Recommended technique: Use small epitope tags and validate with multiple tag positions

• Structural characterization difficulties:

  • Challenges in obtaining sufficient quantities for structural studies

  • Potential for disordered regions lacking stable structure

  • Membrane association complicating structure determination

  • Approach: Consider integrative structural biology combining multiple techniques

These challenges necessitate careful experimental design and multiple complementary approaches when studying YFR010W-A and similar small, uncharacterized proteins.

How can researchers effectively use computational tools to predict functions of YFR010W-A?

Researchers can leverage computational tools for YFR010W-A functional prediction using this strategic approach:

• Sequence-based prediction:

  • Apply multiple prediction algorithms rather than relying on a single tool

  • Use specialized tools for membrane proteins if YFR010W-A shows hydrophobic regions

  • Employ position-specific scoring matrices rather than simple BLAST searches

  • Search for short, conserved motifs that might be missed in whole-sequence analyses

• Structure prediction and analysis:

  • Utilize latest AI-based structure prediction tools (AlphaFold2, RoseTTAFold)

  • Perform molecular dynamics simulations to identify stable conformations

  • Analyze structural features for potential binding pockets or active sites

  • Compare predicted structures with known mitochondrial proteins

• Integrated functional prediction:

  Prediction Approach	Tools/Resources	Advantages	Limitations
  Subcellular localization	DeepLoc, TargetP, MitoFates	Good accuracy for known signals	Less effective for novel targeting mechanisms
  Protein-protein interactions	STRING, PrePPI, InterPreTS	Integrates multiple evidence types	High false positive rates
  Function prediction	DeepGOPlus, COFACTOR, ProFunc	Leverages structural information	Limited by training data diversity
  Pathway involvement	KEGG, BioCyc, FunCoup	Places protein in biological context	May miss novel or species-specific pathways

• Network-based approaches:

  • Integrate YFR010W-A into functional networks based on co-expression data

  • Apply guilt-by-association principles from related mitochondrial proteins

  • Use machine learning to predict functional relationships

  • Identify potential genetic interactions through computational means

• Evolutionary analysis tools:

  • Perform sensitive sequence searches for distant homologues

  • Use synteny analysis to identify positionally conserved genes

  • Apply phylogenetic profiling to identify co-evolving genes

  • Examine selective pressure patterns using evolutionary rate analysis

• Validation and refinement:

  • Benchmark computational predictions against known mitochondrial proteins

  • Assess prediction confidence using cross-validation approaches

  • Integrate predictions from multiple tools using consensus methods

  • Refine predictions iteratively as new experimental data becomes available

By systematically applying these computational approaches and critically evaluating their outputs, researchers can generate testable hypotheses about YFR010W-A function that guide experimental design and increase the efficiency of functional characterization efforts.

What are the broader implications of understanding uncharacterized mitochondrial proteins like YFR010W-A?

Understanding uncharacterized mitochondrial proteins like YFR010W-A has significant implications for multiple fields of biological research. These proteins represent an unexplored aspect of mitochondrial biology that may reveal novel functions and regulatory mechanisms beyond our current understanding. As "emerging genes" specific to S. cerevisiae, they provide valuable models for studying de novo gene birth and the evolution of organelle-specific functions . The postdiauxic shift upregulation of YFR010W-A suggests potential roles in metabolic adaptation and respiratory function development, which has implications for understanding cellular responses to changing nutrient conditions .

Methodologically, the approaches developed to study proteins like YFR010W-A establish roadmaps for characterizing other uncharacterized proteins across species. The integration of computational prediction, fluorescent protein fusion approaches, and functional genomics represents a powerful strategy for uncovering "dark matter" in proteomes . As research continues to illuminate the functions of these uncharacterized proteins, we gain a more complete understanding of mitochondrial biology, evolutionary processes, and the fundamental principles of protein function and localization in eukaryotic cells.

What future research directions should be prioritized for YFR010W-A characterization?

Based on current knowledge, several high-priority research directions emerge for YFR010W-A characterization:

• Precise submitochondrial localization determination using multiple complementary approaches to establish whether YFR010W-A associates with specific mitochondrial compartments or membranes.

• Comprehensive interaction partner identification using proximity labeling and affinity purification approaches to place YFR010W-A in a functional context.

• Phenotypic characterization focusing on mitochondrial functions during the postdiauxic shift when YFR010W-A is upregulated, examining parameters such as respiratory capacity, mitochondrial biogenesis, and metabolic adaptation.

• Structure-function analysis through systematic mutagenesis to identify critical residues and domains required for YFR010W-A function and localization.

• Integration of multi-omics data (transcriptomics, proteomics, metabolomics) from YFR010W-A knockout strains to understand its broader impact on cellular physiology.