Recombinant Saccharomyces cerevisiae Putative uncharacterized protein YKR075W-A (YKR075W-A)

What is YKR075W-A protein and what are its basic characteristics?

YKR075W-A is a putative uncharacterized protein from Saccharomyces cerevisiae (baker's yeast) consisting of 89 amino acids. The full amino acid sequence is: MSSNFTKALSLLSIEALISSTSSVTQHSVFFFKADFRFFVCFWSIWFWTGDISFSLLSML VKSGPYNTVTSVSLFQLMDSGLDLEFCKP . This protein has been classified as "putative uncharacterized" because its precise function in vivo has not been fully elucidated. The protein is often produced recombinantly with a histidine tag to facilitate purification and subsequent experimental analysis. Its UniProt ID is Q8TGM9, which can be used to access additional structural and functional information from protein databases .

How is recombinant YKR075W-A protein typically expressed and purified?

Recombinant YKR075W-A protein is typically expressed in Escherichia coli expression systems rather than in its native Saccharomyces cerevisiae. The process involves:

• Cloning the YKR075W-A gene into an appropriate expression vector

• Transforming the construct into E. coli cells

• Inducing protein expression under optimized conditions

• Cell lysis to release the recombinant protein

• Purification using affinity chromatography, typically with Ni-NTA resin that binds to the histidine tag

The purified protein is often obtained as a lyophilized powder with purity greater than 90% as determined by SDS-PAGE . For research applications, the protein can be reconstituted in deionized sterile water to a concentration of 0.1-1.0 mg/mL, with the addition of 5-50% glycerol for long-term storage at -20°C/-80°C .

What are the optimal storage conditions for YKR075W-A protein?

The optimal storage conditions for YKR075W-A protein are:

It is important to note that repeated freeze-thaw cycles should be avoided as they can lead to protein degradation and loss of activity. The manufacturer's default final concentration of glycerol is typically 50%, which researchers can use as a reference . The storage buffer generally consists of Tris/PBS-based buffer with 6% Trehalose at pH 8.0 .

What experimental approaches are most effective for characterizing the function of YKR075W-A?

Characterizing an uncharacterized protein like YKR075W-A requires a multi-faceted approach:

• Structural Analysis: X-ray crystallography, NMR spectroscopy, or cryo-electron microscopy to determine the three-dimensional structure.

• Sequence Analysis: Bioinformatic approaches comparing the sequence with characterized proteins to identify potential functional domains or motifs.

• Interactome Mapping: Yeast two-hybrid screening, co-immunoprecipitation followed by mass spectrometry, or proximity labeling to identify protein interaction partners.

• Gene Expression Analysis: RT-qPCR, RNA-seq, or microarray analysis to determine when and where the gene is expressed.

• Phenotypic Analysis: CRISPR-mediated knockout or knockdown experiments followed by comprehensive phenotypic screening.

The integration of these approaches provides a more robust characterization than any single method. For example, structural information combined with interaction data can suggest potential biochemical functions, while expression patterns can indicate physiological contexts in which the protein functions.

How can researchers design experiments to elucidate the potential membrane association of YKR075W-A based on its sequence?

The amino acid sequence of YKR075W-A contains hydrophobic regions that suggest potential membrane association. To investigate this property, researchers should design experiments that address both structural predictions and functional validation:

Experimental Design Approach:

• In silico analysis:

  • Hydropathy plotting to identify potential transmembrane domains

  • Secondary structure prediction to identify alpha-helical regions that might insert into membranes

  • Comparison with known membrane protein motifs

• Biochemical validation:

  • Membrane fractionation studies to determine if the native protein localizes to membrane fractions

  • Protease protection assays to determine topology

  • Fluorescence microscopy with GFP-tagged constructs to visualize cellular localization

• Biophysical characterization:

  • Circular dichroism spectroscopy in the presence of membrane mimetics

  • FRET-based assays to measure insertion into lipid bilayers

  • Atomic force microscopy to visualize protein-membrane interactions

This experimental design follows the principle of triangulation, using multiple independent approaches to confirm membrane association and characterize the nature of this association.

What are the best methods for studying potential post-translational modifications of YKR075W-A?

Post-translational modifications (PTMs) can significantly impact protein function. For YKR075W-A, a comprehensive PTM analysis should include:

Methodological Framework:

• Mass Spectrometry-Based Approaches:

  • Bottom-up proteomics: Digestion of the protein followed by LC-MS/MS analysis

  • Top-down proteomics: Analysis of the intact protein to preserve PTM combinations

  • Targeted MS approaches: Multiple reaction monitoring (MRM) for quantification of specific modifications

• Site-Specific Mutagenesis:

  • Mutation of potential modification sites (e.g., Ser, Thr, Tyr for phosphorylation)

  • Functional assays comparing wild-type and mutant proteins

• PTM-Specific Detection Methods:

  • Phosphorylation: 32P labeling, phospho-specific antibodies, Phos-tag gels

  • Glycosylation: Lectin blotting, PNGase F treatment

  • Ubiquitination: Immunoprecipitation with ubiquitin antibodies

• Temporal Dynamics:

  • Pulse-chase experiments to monitor modification kinetics

  • Cell cycle synchronization to detect cell cycle-dependent modifications

By combining these approaches, researchers can build a comprehensive map of YKR075W-A modifications and their functional implications.

How should researchers design controls for YKR075W-A functional studies?

Robust experimental design for YKR075W-A functional studies requires carefully selected controls:

Control Framework:

• Positive Controls:

  • Well-characterized proteins with similar structural features

  • Synthetic peptides corresponding to functional domains

• Negative Controls:

  • Heat-denatured YKR075W-A protein

  • Unrelated proteins with similar size/tag system

  • Buffer-only conditions

• Internal Controls:

  • Wild-type YKR075W-A alongside mutant variants

  • Dose-response curves to establish concentration dependence

• System Controls:

  • Yeast strains with YKR075W-A deletion

  • Complementation assays with the recombinant protein

• Technical Controls:

  • Multiple biological replicates (minimum n=3)

  • Different protein batches to account for preparation variability

This control framework adheres to the principles of good experimental design by incorporating specificity controls, activity controls, and technical validation elements.

What experimental approaches can resolve contradictory data about YKR075W-A function?

When faced with contradictory data regarding YKR075W-A function, researchers should implement a systematic troubleshooting and validation strategy:

Resolution Framework:

• Methodological Validation:

  • Cross-validate findings using orthogonal techniques

  • Vary experimental conditions systematically to identify parameter-dependent effects

  • Conduct inter-laboratory validation studies

• Sample Authentication:

  • Verify protein identity using mass spectrometry

  • Assess protein quality through thermal shift assays

  • Confirm activity using biochemical assays

• Context Dependency Analysis:

  • Test in different cellular backgrounds (e.g., different yeast strains)

  • Vary environmental conditions (pH, temperature, ionic strength)

  • Examine effects of potential binding partners

• Integrative Data Analysis:

  • Use Bayesian approaches to integrate multiple data types

  • Perform meta-analysis of similar studies

  • Develop computational models to explain contextual differences

This approach emphasizes the importance of reproducibility while acknowledging that biological systems are complex and context-dependent. The goal is not simply to resolve contradictions but to understand the underlying complexity that explains apparent contradictions.

How can researchers design time-course experiments to study YKR075W-A dynamics?

Time-course experiments are crucial for understanding the dynamic behavior of proteins like YKR075W-A:

Time-Course Design Principles:

• Temporal Resolution Selection:

  • Match sampling frequency to expected kinetics

  • Logarithmic sampling for processes with decreasing rates

  • Include both early (seconds/minutes) and late (hours/days) timepoints

• Synchronization Methods:

  • Cell cycle synchronization for cell cycle-dependent processes

  • Inducible expression systems for controlled initiation

  • Temperature-sensitive mutants for conditional activation

• Multiplexed Data Collection:

  • Parallel measurement of multiple parameters

  • Single-cell approaches to capture population heterogeneity

  • Live-cell imaging for continuous monitoring

• Data Analysis Strategies:

  • Differential equation modeling for kinetic parameters

  • Principal component analysis for dimensionality reduction

  • Clustering methods for trajectory classification

This framework ensures that time-course experiments are designed with appropriate temporal resolution and analytical approaches to capture the relevant dynamics of YKR075W-A.

What is the optimal protocol for reconstituting lyophilized YKR075W-A for functional studies?

The reconstitution of lyophilized YKR075W-A is a critical step that can significantly impact subsequent functional studies. The optimal protocol includes:

Step-by-Step Reconstitution Protocol:

• Pre-Reconstitution Preparation:

  • Briefly centrifuge the vial containing lyophilized protein to bring contents to the bottom

  • Allow the vial to equilibrate to room temperature (15-20 minutes)

• Primary Reconstitution:

  • Add deionized sterile water to achieve a concentration of 0.1-1.0 mg/mL

  • Gently rotate or invert the vial until complete dissolution (avoid vortexing)

  • Allow to stand for 5-10 minutes at room temperature

• Stabilization:

  • Add glycerol to a final concentration of 5-50% (manufacturer's default is 50%)

  • Mix gently by pipetting up and down

• Aliquoting:

  • Divide into small single-use aliquots (typically 10-20 μL)

  • Flash-freeze in liquid nitrogen

• Storage:

  • Store aliquots at -20°C for short-term or -80°C for long-term storage

  • Avoid repeated freeze-thaw cycles by using fresh aliquots for each experiment

Quality control testing post-reconstitution should include verification of protein concentration, assessment of aggregation state by dynamic light scattering, and validation of functional activity through appropriate biochemical assays.

How can researchers effectively use structural prediction tools to gain insights into YKR075W-A function?

Structural prediction tools offer valuable insights into protein function when experimental structures are unavailable. For YKR075W-A, the following approach is recommended:

Structural Prediction Workflow:

• Primary Sequence Analysis:

  • Identification of conserved domains using PFAM, SMART, or InterPro

  • Secondary structure prediction using PSIPRED or JPred

  • Disorder prediction using IUPred or PONDR

• 3D Structure Prediction:

  • Template-based modeling using SWISS-MODEL or I-TASSER if homologs exist

  • Ab initio modeling using Rosetta or AlphaFold for novel folds

  • Refinement of models using molecular dynamics simulations

• Functional Site Prediction:

  • Active site prediction using CASTp or COACH

  • Ligand binding site prediction using 3DLigandSite

  • Protein-protein interaction interface prediction using SPPIDER

• Validation and Refinement:

  • Model quality assessment using ProQ, QMEAN, or MolProbity

  • Experimental validation of key predictions

  • Iterative refinement based on experimental feedback

This hierarchical approach combines multiple computational methods to build a comprehensive structural model, which can then guide hypothesis generation and experimental design for functional studies.

What are the best approaches for studying YKR075W-A protein-protein interactions?

Identifying and characterizing protein-protein interactions is essential for understanding YKR075W-A function. A comprehensive approach includes:

Protein Interaction Analysis Strategy:

• Discovery Phase Methods:

  • Yeast two-hybrid screening using YKR075W-A as bait

  • Affinity purification followed by mass spectrometry (AP-MS)

  • Proximity-dependent biotin labeling (BioID or APEX)

  • Protein complementation assays (e.g., split-GFP)

• Validation Phase Methods:

  • Co-immunoprecipitation with candidate interactors

  • FRET or BRET assays to confirm direct interactions

  • Surface plasmon resonance or isothermal titration calorimetry for binding kinetics

  • Mammalian two-hybrid assays as orthogonal validation

• Characterization Phase Methods:

  • Deletion/mutation mapping to identify interaction domains

  • Competition assays to determine interaction exclusivity

  • Structural studies of complexes (X-ray, NMR, or cryo-EM)

  • Functional assays to determine biological significance

• Network Analysis:

  • Integration of interaction data into protein networks

  • GO term enrichment analysis of interactors

  • Pathway analysis to identify biological processes

This multi-phase approach ensures that identified interactions are specific, reproducible, and biologically relevant, providing a foundation for understanding YKR075W-A function within the cellular context.

How should researchers analyze data from YKR075W-A knockout or knockdown experiments?

Analysis of YKR075W-A knockout or knockdown experiments requires careful consideration of both experimental design and data interpretation:

Data Analysis Framework:

• Validation of Knockout/Knockdown Efficiency:

  • RT-qPCR to confirm mRNA reduction

  • Western blot to confirm protein reduction

  • Genomic sequencing to confirm CRISPR-mediated modifications

• Phenotypic Analysis:

  • Growth curve analysis to detect proliferation defects

  • Microscopy for morphological changes

  • Metabolic profiling for biochemical alterations

• Statistical Approaches:

  • Power analysis to determine appropriate sample size

  • Selection of appropriate statistical tests based on data distribution

  • Multiple hypothesis testing correction (e.g., Benjamini-Hochberg)

• Controls and Normalization:

  • Wild-type controls processed in parallel

  • Rescue experiments to confirm specificity

  • Internal normalization controls for qPCR and protein quantification

• Integrative Analysis:

  • Correlation of phenotypic changes with molecular alterations

  • Pathway analysis to identify affected biological processes

  • Network analysis to identify compensatory mechanisms

This comprehensive framework ensures robust interpretation of knockout/knockdown experiments, enabling researchers to distinguish direct effects of YKR075W-A loss from secondary or compensatory responses.

What approaches should be used to analyze complex datasets from YKR075W-A interactome studies?

Interactome studies generate complex datasets that require sophisticated analytical approaches:

Interactome Analysis Strategy:

• Data Preprocessing:

  • Filtering of non-specific interactions using control datasets

  • Normalization to account for protein abundance differences

  • Transformation to meet statistical assumptions

• Confidence Scoring:

  • Implementation of probabilistic scoring (e.g., SAINT algorithm)

  • Integration of multiple replicate experiments

  • Incorporation of prior knowledge from databases

• Network Construction and Analysis:

  • Visualization using platforms like Cytoscape

  • Calculation of network parameters (degree, betweenness, clustering)

  • Module detection to identify functional complexes

• Functional Interpretation:

  • Gene Ontology enrichment analysis

  • Pathway mapping using KEGG or Reactome

  • Domain-based analysis of interaction interfaces

• Integration with Other Data Types:

  • Correlation with expression data

  • Integration with structural information

  • Mapping to genetic interaction networks

This multi-layered analytical approach transforms raw interaction data into biologically meaningful insights about YKR075W-A function.

How can researchers combine multiple experimental approaches to build a comprehensive model of YKR075W-A function?

Building a comprehensive model of YKR075W-A function requires integration of diverse experimental data:

Integrative Modeling Framework:

• Data Collection and Harmonization:

  • Standardize experimental conditions across studies

  • Convert different data types to comparable formats

  • Assess and account for data quality and reliability

• Multi-Scale Integration:

  • Molecular scale: Structural and interaction data

  • Cellular scale: Localization and expression data

  • System scale: Phenotypic and network-level data

• Computational Modeling Approaches:

  • Boolean networks for qualitative relationships

  • Ordinary differential equations for kinetic behavior

  • Agent-based models for spatial dynamics

• Model Validation:

  • Experimental testing of model predictions

  • Cross-validation using data partitioning

  • Sensitivity analysis to identify key parameters

• Iterative Refinement:

  • Update models as new data becomes available

  • Resolve contradictions through additional experiments

  • Expand model scope to include new components

This integrative approach synthesizes diverse data types into a coherent model that can explain existing observations and generate testable predictions about YKR075W-A function.

What are common challenges in working with YKR075W-A and how can they be addressed?

Researchers working with YKR075W-A may encounter several challenges:

Troubleshooting Guide:

• Protein Solubility Issues:

  • Challenge: YKR075W-A may form aggregates after reconstitution

  • Solution: Optimize buffer conditions (pH, salt concentration, additives)

  • Alternative: Consider fusion tags that enhance solubility (MBP, SUMO)

• Low Expression Yield:

  • Challenge: Poor expression in E. coli systems

  • Solution: Optimize codon usage for E. coli

  • Alternative: Try different expression systems (yeast, insect cells)

• Functional Assay Development:

  • Challenge: Lack of known function makes assay design difficult

  • Solution: Start with binding assays to identified interactors

  • Alternative: Use phenotypic assays in knockout/complementation systems

• Antibody Availability:

  • Challenge: Limited availability of specific antibodies

  • Solution: Use the His-tag for detection and purification

  • Alternative: Develop custom antibodies against unique peptide regions

• Structural Analysis Difficulties:

  • Challenge: Challenges in obtaining crystal structures

  • Solution: Try NMR for solution structure

  • Alternative: Use crosslinking mass spectrometry for structural constraints

This troubleshooting guide provides practical solutions to common challenges, facilitating successful experimental work with YKR075W-A.

How can researchers design experiments to distinguish between direct and indirect effects of YKR075W-A?

Distinguishing direct from indirect effects is crucial for accurate functional characterization:

Experimental Design for Causality:

• Rapid Induction/Depletion Systems:

  • Auxin-inducible degron for rapid protein depletion

  • Tetracycline-inducible expression for controlled induction

  • Analysis of immediate vs. delayed responses

• Structure-Function Analysis:

  • Targeted mutagenesis of specific domains

  • Creation of separation-of-function mutants

  • Correlation of structural features with specific functions

• In Vitro Reconstitution:

  • Purified component systems to test direct biochemical activities

  • Stepwise addition of components to identify minimal requirements

  • Comparison of in vitro and in vivo phenotypes

• Proximity-Based Methods:

  • FRET-based sensors to detect direct interactions in real-time

  • Crosslinking approaches to capture transient interactions

  • Single-molecule methods to observe direct molecular events

This methodological framework enables researchers to establish causal relationships and distinguish direct molecular functions from downstream consequences.

What considerations are important when designing experiments to study YKR075W-A in different genetic backgrounds?

Genetic background can significantly influence experimental outcomes:

Genetic Background Considerations:

• Strain Selection Criteria:

  • Use isogenic strains differing only in YKR075W-A status

  • Consider well-characterized laboratory strains vs. wild isolates

  • Include multiple distinct genetic backgrounds for robustness

• Genetic Interaction Analysis:

  • Synthetic genetic array (SGA) screening to identify genetic interactors

  • Double-mutant analysis to detect epistatic relationships

  • Suppressor screening to identify functional relationships

• Background Effect Control:

  • Back-crossing to standardize genetic background

  • Complementation tests to confirm phenotype specificity

  • Creation of congenic strains for critical comparisons

• Evolutionary Considerations:

  • Compare YKR075W-A function across Saccharomyces species

  • Assess conservation of interacting partners

  • Test for functional complementation across species

These considerations ensure that observed phenotypes are reliably attributed to YKR075W-A rather than background-specific effects, enhancing the generalizability and robustness of findings.

What are the most promising future research directions for YKR075W-A?

Based on current knowledge, several research directions show particular promise:

• Systematic Functional Screening: Comprehensive phenotypic analysis across diverse conditions to identify specific functional contexts.

• Evolutionary Analysis: Comparative studies across fungal species to identify conserved functions and species-specific adaptations.

• High-Resolution Structural Studies: Determination of crystal or cryo-EM structures to provide atomic-level insights into function.

• Systems Biology Integration: Incorporation of YKR075W-A into comprehensive cellular models to understand its role in broader biological networks.

• Translational Applications: Exploration of potential biotechnological applications based on the unique properties of YKR075W-A.

These directions represent complementary approaches that together will provide a comprehensive understanding of YKR075W-A function, potentially revealing novel biological principles and applications.

How can researchers contribute to the community knowledge base about YKR075W-A?

Advancing collective knowledge about YKR075W-A requires coordinated community efforts:

• Data Sharing: Deposition of experimental data in public repositories such as UniProt, PDB, and BioGRID.

• Method Standardization: Development and sharing of optimized protocols for working with YKR075W-A.

• Resource Development: Creation of strain collections, plasmids, and antibodies accessible to the research community.

• Collaborative Networks: Establishment of research consortia focused on comprehensive characterization of uncharacterized yeast proteins.

• Integration with Systems Biology: Contribution of YKR075W-A data to systems-level models of cellular function.