The recombinant Saccharomyces cerevisiae putative uncharacterized protein YAL042C-A is a protein derived from the yeast Saccharomyces cerevisiae, specifically from the strain ATCC 204508 / S288c, commonly known as baker's yeast. This protein is part of ongoing research due to its potential applications in various biological studies. Despite being uncharacterized, it holds interest for its possible roles in cellular processes and as a tool in molecular biology.
Species: Saccharomyces cerevisiae (strain ATCC 204508 / S288c)
Protein Type: Recombinant protein
Uniprot Number: O13514
Storage Conditions: Stored in a Tris-based buffer with 50% glycerol at -20°C for extended storage, or at -80°C. Working aliquots can be kept at 4°C for up to one week .
Amino Acid Sequence: The sequence includes MSSCISPESSIISRFTRSHGIDGNVTSILSSSFACRSRSTTNCGLVTTELNCPHSFTSRN NVVKMHDKVISPPALVRTRTSSSVLANASSDSNVDLFMMSIVSSYVCYITVLLRMYTRHK TSFPL .
In Saccharomyces cerevisiae, extensive studies have been conducted on protein complexes and interactions. For instance, datasets like CYC2008 and YHTP2008 provide comprehensive insights into yeast protein complexes, highlighting the importance of understanding protein interactions in cellular processes . Although YAL042C-A is not specifically mentioned in these studies, the methodologies used could potentially be applied to understand its role.
Yeast activator protein 1 (Yap1p) plays a crucial role in stress responses by regulating gene expression. Studies on Yap1p have shown that it influences the expression of various proteins involved in stress response and metabolic pathways . Understanding such regulatory mechanisms could provide insights into how uncharacterized proteins like YAL042C-A might function under different conditions.
Recombinant Saccharomyces cerevisiae has been used in biomedical research, including vaccine development. For example, it has been engineered to express human carcinoembryonic antigen (CEA), eliciting immune responses and showing potential in cancer therapy . This demonstrates the versatility of recombinant yeast proteins in medical applications.
Further research is needed to fully understand the function and potential applications of YAL042C-A. This could involve studying its interactions with other proteins, its role in cellular processes, and exploring its use in biomedical applications similar to other recombinant yeast proteins.
YAL042C-A is located on chromosome I of Saccharomyces cerevisiae, positioned within the subtelomeric region. The gene spans approximately 171 base pairs and encodes a small protein of 56 amino acids. It is classified as a putative uncharacterized protein because its precise biological function remains to be fully elucidated. The gene has no introns, which is consistent with most S. cerevisiae genes. Genomic analyses indicate it may have arisen through duplication events common in subtelomeric regions, though its sequence conservation across related yeast species is limited.
For recombinant expression of YAL042C-A, design primers that include the full coding sequence with appropriate restriction sites matching your expression vector. Given its small size (171 bp), standard PCR amplification from genomic DNA using high-fidelity polymerase is recommended. When designing the expression construct, consider:
Adding an N-terminal or C-terminal tag (His, FLAG, or GFP) for detection and purification
Using a strong inducible promoter such as GAL1 for controlled expression
Including a yeast-optimized Kozak sequence for efficient translation
Verifying the cloned sequence to ensure no mutations were introduced during PCR
For optimal expression in heterologous systems, codon optimization may be necessary when expressing in bacterial systems like E. coli.
The optimal expression system for YAL042C-A depends on your research objectives. For structural studies requiring high yields, E. coli BL21(DE3) with a pET vector system offers efficient production, though solubility challenges may arise with this small yeast protein. For functional studies, homologous expression in S. cerevisiae is preferred using strains like BY4741 with pRS or pYES vectors, preserving native post-translational modifications.
Comparative expression efficiency table:
| Expression System | Yield | Solubility | Post-translational Modifications | Application |
|---|---|---|---|---|
| E. coli BL21(DE3) | High | Moderate | Minimal | Structural studies |
| S. cerevisiae BY4741 | Moderate | High | Native | Functional studies |
| Pichia pastoris | High | High | Similar to native | Scale-up studies |
| Cell-free system | Variable | High | Minimal | Rapid screening |
For challenging expression, consider specialized approaches such as fusion partners (MBP, SUMO) to enhance solubility or secretion signals for extracellular production.
Purification of YAL042C-A presents unique challenges due to its small size (56 amino acids) and potential for aggregation. A multi-step purification strategy is recommended:
Initial capture: Affinity chromatography using a fusion tag (His6 or GST tag)
Intermediate purification: Ion-exchange chromatography based on the protein's theoretical pI of 9.2
Polishing: Size exclusion chromatography to separate monomeric protein from aggregates
Critical considerations include maintaining reducing conditions (2-5 mM DTT or 1 mM TCEP) throughout purification to prevent disulfide-mediated aggregation, and using buffers in the pH range of 7.0-8.0 to maintain stability. For structural studies, screening multiple buffer conditions is essential, as small uncharacterized proteins often have specific stability requirements.
Due to its small size (~6 kDa), standard verification methods require adaptation:
SDS-PAGE: Use high percentage gels (16-20%) or tricine-based systems optimized for low molecular weight proteins
Western blotting: Employ epitope tags (His, FLAG) with monoclonal antibodies for specific detection
Mass spectrometry: MALDI-TOF or ESI-MS to confirm exact molecular weight
Circular dichroism: To assess secondary structure elements
Consider combining size-exclusion chromatography with multi-angle light scattering (SEC-MALS) to determine the oligomeric state in solution, as small proteins often form functional multimers.
Multiple complementary approaches should be employed to accurately determine YAL042C-A localization:
Fluorescence microscopy with C-terminal or N-terminal GFP fusion constructs under native promoter control
Subcellular fractionation followed by Western blot analysis
Immunogold electron microscopy for high-resolution localization
Proximity-based labeling techniques (BioID or APEX2) to identify neighboring proteins
Preliminary computational predictions using tools like PSORT and TargetP suggest possible mitochondrial localization based on sequence features, though experimental verification is essential. When designing localization studies, consider whether the tag might interfere with localization signals, particularly for this small protein. Control experiments with known localization markers should be included to validate findings.
For identifying interaction partners of YAL042C-A, multiple complementary approaches provide the most comprehensive results:
Affinity purification-mass spectrometry (AP-MS): Use TAP-tagged or FLAG-tagged YAL042C-A as bait
Yeast two-hybrid screening: Employ a split-ubiquitin system for membrane proteins if localization studies suggest membrane association
Proximity-dependent biotin identification (BioID): Particularly useful for transient interactions
Co-immunoprecipitation with antibodies against the tagged protein followed by mass spectrometry
Data analysis considerations include:
Implementing stringent controls to filter out common contaminants
Performing reverse AP-MS experiments
Applying quantitative scoring systems (e.g., SAINT algorithm) to discriminate true interactions from background
Validating key interactions using orthogonal methods such as FRET or BiFC
When investigating an uncharacterized protein like YAL042C-A, a systematic phenotypic characterization approach is essential:
Growth assays: Measure growth rates of knockout and overexpression strains across diverse conditions, including:
Temperature ranges (16°C, 30°C, 37°C)
Carbon sources (glucose, galactose, glycerol)
Stress conditions (oxidative, osmotic, pH)
Metabolic profiling: Analyze changes in metabolite levels using LC-MS/MS or NMR
Microscopy-based assays:
Mitochondrial morphology and function (if localization studies suggest mitochondrial association)
Vacuolar morphology
Actin cytoskeleton organization
Cell cycle analysis: Flow cytometry to detect potential alterations in cell cycle progression
Based on preliminary observations, YAL042C-A deletion strains show mild sensitivity to nitrogen starvation and stationary phase survival, suggesting a role in stress adaptation mechanisms.
Contradictory results are common when studying uncharacterized proteins and require systematic troubleshooting:
Evaluate genetic background effects:
Test the phenotype in multiple strain backgrounds (S288C, W303, Σ1278b)
Create clean knockouts using CRISPR-Cas9 to minimize off-target effects
Perform complementation tests with the wild-type gene
Control for experimental conditions:
Standardize growth conditions precisely (media composition, growth phase)
Document environmental parameters (temperature, oxygenation)
Consider circadian or growth-phase dependent effects
Validate reagent specificity:
Verify antibody specificity with appropriate controls
Confirm tag functionality doesn't interfere with native protein function
Apply orthogonal methods:
If protein-protein interaction results conflict, use at least three independent methods
For localization discrepancies, combine fluorescence microscopy with biochemical fractionation
When reporting results, transparently document all experimental conditions and validation steps to enable accurate reproduction by other researchers.
Several emerging technologies offer powerful approaches for characterizing YAL042C-A:
Cryo-electron microscopy: Despite challenges with small proteins, advances in single-particle analysis make structural determination increasingly feasible
AlphaFold2 and structure prediction: Computational modeling combined with experimental validation provides structural insights
CRISPR interference/activation (CRISPRi/CRISPRa): For precise modulation of expression levels without complete knockout
Single-cell technologies:
scRNA-seq to identify condition-specific expression patterns
Time-lapse microscopy with fluorescent reporters for dynamic studies
Proximity-dependent labeling combined with quantitative proteomics:
TurboID or miniTurbo for rapid biotin labeling
APEX2 for subcellular spatial resolution
Metabolic tracing using stable isotopes to follow metabolic fluxes potentially affected by YAL042C-A
The most effective approach involves integrating multiple technologies with systematic data analysis pipelines to build a comprehensive functional model.
Structural characterization of small yeast proteins like YAL042C-A presents unique challenges requiring specialized approaches:
Solution NMR spectroscopy:
Optimal for small proteins (<10 kDa)
Requires 15N and 13C isotope labeling
Can provide dynamics information important for function
X-ray crystallography:
May require fusion partners to facilitate crystallization
Consider surface entropy reduction mutagenesis to promote crystal contacts
Molecular dynamics simulations:
All-atom simulations to explore conformational dynamics
Protein-lipid interactions if membrane association is suspected
Hydrogen-deuterium exchange mass spectrometry (HDX-MS):
To identify flexible regions and binding interfaces
Particularly useful for mapping condition-dependent structural changes
Initial computational structure predictions using AlphaFold2 suggest YAL042C-A may contain a single alpha-helical domain with a disordered N-terminal region, characteristic of proteins involved in stress response pathways.
When analyzing high-throughput data for YAL042C-A studies:
RNA-seq data analysis:
Use DESeq2 or edgeR for differential expression analysis
Apply pathway enrichment analysis (GO, KEGG) to identify affected biological processes
Consider co-expression network analysis to identify functionally related genes
Proteomics data processing:
Implement appropriate normalization methods for label-free quantification
Apply SAINT or COMPASS algorithms for interaction data
Use stringent statistical thresholds (FDR < 0.05) for significance
Integration of multi-omics data:
Implement methodologies like MOFA+ or DIABLO for multi-omics factor analysis
Use Cytoscape for network visualization and analysis
Consider Bayesian approaches for causal network inference
Data management:
Document all analysis parameters in computational notebooks (Jupyter, R Markdown)
Deposit raw data in appropriate repositories (GEO, PRIDE)
Maintain version control for analysis scripts
A systematic approach involving proper experimental design, rigorous statistical analysis, and transparent reporting is essential for deriving meaningful insights from high-throughput studies.
Evolutionary analysis provides valuable context for functional studies of YAL042C-A:
Comparative genomics approach:
Analyze presence/absence patterns across Saccharomycetaceae family
Identify synteny conservation in related yeast species
Calculate selection pressures (dN/dS ratios) to determine evolutionary constraints
Sequence analysis methods:
Multiple sequence alignment of homologs
Hidden Markov Model profiles to detect distant homologs
Position-specific scoring matrices to identify conserved functional motifs
Structural conservation analysis:
Compare predicted structures across homologs
Identify conserved surface patches as potential interaction sites
Recent phylogenetic analyses suggest YAL042C-A may be restricted to Saccharomyces sensu stricto species, indicating a relatively recent evolutionary origin, possibly explaining its uncharacterized status and suggesting species-specific functional adaptation.
Generating specific antibodies against small proteins like YAL042C-A presents several challenges:
Epitope selection strategy:
Use epitope prediction algorithms to identify immunogenic regions
Consider synthesizing the full-length protein as immunogen
Avoid highly conserved regions that might cross-react with other proteins
Production approaches:
Monoclonal antibodies for highest specificity
Recombinant antibodies (scFv, nanobodies) for difficult epitopes
Phage display selection for enhanced specificity
Validation requirements:
Test antibody specificity against knockout strains
Perform epitope mapping to confirm binding sites
Validate across multiple applications (Western blot, IP, IF)
Alternative approaches:
Epitope tagging strategies (FLAG, HA, V5) when antibody generation fails
Proximity labeling approaches to bypass the need for direct antibodies
Researchers should budget sufficient time and resources for antibody development and validation, as this represents a critical reagent for subsequent studies.
For researchers facing challenges with expression and solubility of YAL042C-A:
Expression optimization:
Screen multiple expression temperatures (16°C, 25°C, 30°C)
Test induction conditions (IPTG concentration, induction time)
Evaluate specialized expression strains (Rosetta, Arctic Express)
Solubility enhancement:
Fusion partners: MBP, SUMO, or Thioredoxin tags
Co-expression with potential binding partners
Addition of stabilizing agents (glycerol, arginine)
Refolding strategies:
On-column refolding protocols
Step-wise dialysis to remove denaturants
Rapid dilution methods optimized for small proteins
Construct optimization:
Terminal truncations to remove disordered regions
Codon optimization for expression host
Inclusion of stabilizing mutations based on computational predictions
Systematic screening of these variables using small-scale expression tests followed by solubility analysis can significantly improve recombinant protein yield and quality.
Future research on YAL042C-A should focus on several promising directions:
Systems biology approaches:
Genome-wide genetic interaction screens (SGA, E-MAP)
Condition-specific transcriptomics and proteomics
Integration with existing yeast interactome data
Environmental response studies:
Detailed characterization of expression patterns under various stress conditions
Investigation of protein stability and post-translational modifications during stress
Analysis of cellular relocalization in response to environmental changes
Structure-function relationships:
High-resolution structural studies combined with mutational analysis
Identification of functional domains or motifs
Computational modeling of potential binding interfaces
Translational relevance:
Comparison with potential human orthologs or analogs
Investigation of roles in industrial fermentation or biotechnology applications
Potential as a model for studying fundamental cellular processes
Based on preliminary data suggesting stress-responsive expression, focused investigation of YAL042C-A's role in cellular adaptation mechanisms represents a particularly promising avenue.
Integrated multi-omics approaches offer powerful strategies for functional characterization:
Comprehensive workflow:
Transcriptomics to identify condition-specific expression patterns
Proteomics to map protein-protein interactions and modifications
Metabolomics to detect metabolic pathway alterations
Lipidomics if membrane associations are identified
Integration framework:
Network-based integration methods to identify functional modules
Causal modeling to infer regulatory relationships
Machine learning approaches for pattern recognition across datasets
Validation strategy:
Targeted experiments to confirm key predictions
Perturbation studies of identified pathways
Temporal profiling to establish causality
This integrated approach enables researchers to place YAL042C-A within its broader cellular context, generating testable hypotheses about its function that can drive focused experimental investigation.
Based on current knowledge and best practices, the following standardized protocols are recommended for YAL042C-A research:
Gene manipulation and strain construction:
CRISPR-Cas9 based knockout construction
Genomic tagging at C-terminus to preserve native regulation
Complementation testing with plasmid-based expression
Protein expression and purification:
E. coli expression with SUMO fusion tag
Two-step purification (IMAC followed by size exclusion)
Quality control using SDS-PAGE and mass spectrometry
Functional characterization:
Growth phenotyping under standard and stress conditions
Localization studies using confocal microscopy
Interaction mapping using AP-MS
Data analysis pipeline:
Standard workflow for RNA-seq analysis
Proteomics data processing workflow
Integration framework for multi-omics data
These standardized protocols facilitate reproducibility and enable meaningful comparison of results across different research groups studying this uncharacterized protein.
Rigorous controls are crucial for reliable research on uncharacterized proteins:
Genetic controls:
Empty vector controls for overexpression studies
Wild-type strain paired with knockout strain
Complementation with native gene to verify phenotype specificity
Protein interaction controls:
Unrelated protein with same tag for background binding
Reciprocal tagging of interaction partners
Competition assays to verify specificity
Localization controls:
Known markers for subcellular compartments
Multiple tagging strategies (N- and C-terminal)
Fixed and live cell imaging comparisons
Expression analysis controls:
Housekeeping genes for normalization
Time course measurements to capture dynamics
Multiple biological replicates (minimum n=3)