Recombinant Saccharomyces cerevisiae Putative uncharacterized protein YJR023C (YJR023C)

What are the recommended experimental approaches for initial characterization of YJR023C?

Initial characterization should follow a systematic approach:

• Gene deletion studies: Generate a YJR023C deletion strain to identify potential phenotypes under various growth conditions, including different carbon sources, temperature sensitivity, and stress responses as performed in systematic yeast gene deletion studies .

• Protein localization: Utilize the N-terminal HA-tagging approach described in recent proteome-wide yeast libraries coupled with fluorescent protein visualization to determine subcellular localization . This can be accomplished through:

  • Mating the HA-tagged YJR023C strain with a strain expressing a single-chain variable fragment that specifically binds the HA tag (scFvHA) fused to a fluorescent protein

  • Using the Z3 promoter system controlled by β-estradiol induction

• Protein interaction studies: Perform immunoprecipitation followed by mass spectrometry to identify protein interaction partners, which may provide clues about function.

• Transcriptomic analysis: Compare gene expression profiles between wild-type and YJR023C deletion strains under different conditions to identify potential regulatory relationships.

• Phenomics screening: Subject the deletion strain to comprehensive phenotypic analysis across hundreds of growth conditions to identify conditional phenotypes, similar to approaches used in other uncharacterized gene studies .

How can I reliably express and purify recombinant YJR023C for in vitro studies?

For effective expression and purification of YJR023C:

• Expression system selection:

  • Use E. coli BL21(DE3) for high-yield bacterial expression

  • Alternatively, express in S. cerevisiae itself using a strong constitutive promoter such as TEF2 (similar to the approach used for CEA expression in result )

• Optimization protocol:

  • Clone the YJR023C sequence into a suitable expression vector with an N-terminal affinity tag (His6 or GST)

  • For yeast expression, utilize the TEF2 promoter system similar to that described for other recombinant proteins

  • Test multiple induction conditions (temperature, inducer concentration, time) to optimize expression

• Purification strategy:

  • Apply a two-step purification using affinity chromatography followed by size exclusion

  • For membrane proteins, consider using detergents for solubilization

  • Store in Tris-based buffer with 50% glycerol at -20°C for stability as indicated in product specifications

• Validation methods:

  • Verify purified protein by SDS-PAGE, Western blot, and mass spectrometry

  • Assess protein folding using circular dichroism spectroscopy

How can I determine if YJR023C has a role in cellular stress response pathways?

To investigate YJR023C's potential role in stress response:

• Stress response assays:

  • Subject the YJR023C deletion strain to various stressors (oxidative, heat, osmotic, pH, nutrient limitation)

  • Measure growth rates compared to wild-type using methods similar to those employed to characterize the aging-associated gene AAG1 (YBR238C)

  • Quantify reactive oxygen species (ROS) levels using H2DCFDA fluorescence measurements

• Transcriptional regulation analysis:

  • Examine if YJR023C expression changes under stress conditions using qRT-PCR

  • Analyze whether YJR023C is regulated by known stress-responsive transcription factors such as MSN4

• Genetic interaction screening:

  • Perform synthetic genetic array (SGA) analysis with known stress response genes

  • Create double mutants with key stress pathway components to identify genetic interactions

• Protein modification detection:

  • Examine post-translational modifications under stress conditions

  • Determine if YJR023C undergoes phosphorylation, ubiquitination, or other modifications during stress

This approach mirrors successful stress response characterization of other previously uncharacterized genes like YBR238C (now named AAG1), which was found to affect mitochondrial function and cellular aging .

What methods can be used to identify potential membrane-related functions of YJR023C?

Based on its amino acid sequence suggesting multiple hydrophobic regions , YJR023C may have membrane-related functions. To investigate:

• Membrane localization studies:

  • Use GFP fusion proteins or immunofluorescence to visualize subcellular localization

  • Employ subcellular fractionation followed by Western blotting to confirm membrane association

  • Utilize the uracil-scavenging assay described in study to indirectly assess surface protein trafficking

• Membrane protein topology analysis:

  • Apply protease protection assays to determine protein orientation in the membrane

  • Use glycosylation site mapping to identify luminal domains

  • Implement the PNGase-F assay to detect glycosylation status as described in the proteome-wide library study

• Functional screening:

  • Test deletion strains for defects in membrane-related processes (transport, trafficking, integrity)

  • Screen for altered sensitivity to membrane-disrupting agents

  • Examine growth on different carbon sources requiring membrane transporters, similar to the YPD/YPG comparison approach

• Genetic interactions with known membrane proteins:

  • Create double deletion strains with characterized membrane protein genes

  • Test for synthetic lethality or rescue effects

A specialized experimental design for this purpose could adapt the Fur4-mediated uracil-scavenging screen described in , which successfully identified uncharacterized membrane trafficking factors.

How can I determine if YJR023C impacts cellular lifespan or aging processes?

To investigate potential roles in aging:

• Lifespan assays:

  • Measure chronological lifespan (CLS) using the outgrowth methods described in the AAG1 characterization study :

    • Aging cells in 96-well plates with measurement of outgrowth in YPD medium

    • Flask-based aging with serial dilution spot tests

    • OD600 measurement of outgrowth from serially diluted aged cultures

  • Measure replicative lifespan (RLS) by micromanipulation of daughter cells

• Genetic interaction tests:

  • Create double mutants with known aging genes like TOR pathway components

  • Test lifespan effects of YJR023C deletion in combination with rapamycin treatment, similar to the approaches used for YBR238C/AAG1

• Metabolic analysis:

  • Measure mitochondrial function parameters (oxygen consumption, membrane potential)

  • Assess ROS production using fluorescent probes

  • Analyze ATP production and metabolic flux

• Gene expression analysis:

  • Compare transcriptional profiles of wild-type and deletion strains during aging

  • Focus on known aging-related transcription factors like HAP4

This approach mirrors the comprehensive characterization performed on YBR238C (AAG1), which was identified as affecting both chronological and replicative lifespan through mitochondrial-dependent pathways .

How can I design experiments to resolve conflicting functional predictions for YJR023C?

When faced with conflicting functional predictions:

• Systematic validation approach:

  • Prioritize experiments based on confidence scores from different prediction methods

  • Design a factorial experimental plan testing multiple hypothesized functions simultaneously

  • Implement controls that can distinguish between alternative hypotheses

• Multi-modal evidence gathering:

  • Combine protein interaction data, localization studies, and phenotypic assays

  • Integrate computational predictions with experimental validation

  • Use the network-based approach described by Schwikowski et al. to analyze protein-protein interaction networks for functional insights

• Critical experiment design:

  • Identify the key distinguishing features between conflicting predictions

  • Design experiments specifically targeting these distinguishing features

  • Use CRISPR-based techniques for precise genetic manipulation

• Quantitative phenotyping:

  • Apply high-throughput phenotyping across diverse conditions

  • Implement fitness measurement approaches described in heterozygous screening studies

  • Use quantitative trait analysis to detect subtle phenotypic effects

This approach is particularly valuable for uncharacterized proteins where initial predictions may come from multiple, sometimes contradictory sources, similar to the situation described for YNR053C in the protein-protein interaction network study .

What specialized techniques can be applied to investigate potential RNA-binding properties of YJR023C?

If sequence analysis suggests potential RNA-binding properties (similar to the analysis of YBR238C ):

• RNA immunoprecipitation (RIP) assay:

  • Express tagged YJR023C and immunoprecipitate to isolate bound RNAs

  • Sequence captured RNAs to identify binding targets

  • Compare binding profiles under different cellular conditions

• Structural analysis approach:

  • Perform domain analysis using tools like ANNOTATOR to identify potential RNA-binding motifs

  • Use HHpred to detect structural homology with known RNA-binding proteins

  • Apply techniques like those used to identify the pentatricopeptide repeat region in YBR238C

• In vitro binding assays:

  • Express and purify recombinant YJR023C

  • Perform electrophoretic mobility shift assays (EMSAs) with candidate RNA molecules

  • Utilize surface plasmon resonance to measure binding kinetics

• Functional validation:

  • Create point mutations in predicted RNA-binding domains

  • Test mutants for RNA binding capacity and phenotypic consequences

  • Investigate whether YJR023C affects RNA processing, stability, or translation

This specialized approach integrates methods from the detailed characterization of YBR238C, which was found to have potential RNA-binding properties through sequence homology analysis .

How can I design a comprehensive study to identify genetic interactions between YJR023C and the TORC1 signaling pathway?

To investigate potential connections to TORC1 signaling:

• Rapamycin response profiling:

  • Compare growth of wild-type and YJR023C deletion strains with varying rapamycin concentrations

  • Analyze whether YJR023C expression is regulated by rapamycin treatment using qRT-PCR

  • Determine if YJR023C deletion alters cellular sensitivity to TORC1 inhibition

• Genetic interaction mapping:

  • Create double mutants with key TORC1 pathway components

  • Perform epistasis analysis to position YJR023C within or parallel to the TORC1 pathway

  • Use the approach described in the AAG1 study to identify the relationship between the gene and TORC1 signaling

• Phosphoproteome analysis:

  • Compare phosphorylation patterns between wild-type and YJR023C deletion strains

  • Focus on known TORC1 targets like S6K and 4E-BP

  • Identify whether YJR023C affects TORC1-dependent phosphorylation events

• Transcriptional response analysis:

  • Profile transcriptome changes in response to rapamycin in wild-type versus deletion strains

  • Identify if YJR023C deletion alters the normal transcriptional response to TORC1 inhibition

  • Compare with the transcriptional signatures of known TORC1 regulators

This comprehensive approach mirrors the successful methods used to characterize YBR238C/AAG1 as a TORC1-regulated gene involved in mitochondrial function and aging .

What are the most common technical challenges when working with uncharacterized yeast proteins and their solutions?

Common challenges and solutions include:

• Low expression levels:

  • Challenge: Native uncharacterized proteins often have low expression

  • Solution: Use strong inducible promoters (GAL1, CUP1) or constitutive promoters (TEF2)

  • Solution: Optimize codon usage for increased expression

  • Solution: Consider using a CRISPR/Cas9-mediated approach to boost endogenous expression

• Phenotype detection difficulties:

  • Challenge: Subtle or condition-specific phenotypes may be missed

  • Solution: Apply comprehensive phenotypic screening across multiple conditions

  • Solution: Use sensitive techniques such as competitive growth assays

  • Solution: Implement the heterozygous screening approach described in for detecting modest increases in genomic instability

• Functional redundancy issues:

  • Challenge: Redundant genes may mask phenotypes in single deletion strains

  • Solution: Create multiple gene deletions of functionally related genes

  • Solution: Use overexpression studies as a complementary approach

  • Solution: Consider the approach used to identify functionally redundant calcineurin targets in F. graminearum

• Protein localization challenges:

  • Challenge: Tags may interfere with protein function or localization

  • Solution: Use the smaller HA tag with scFvHA-fluorescent protein system described in

  • Solution: Try multiple tagging strategies (N-terminal, C-terminal, internal)

  • Solution: Validate localization using multiple methods (microscopy, fractionation)

These solutions integrate approaches from successful characterization studies of previously uncharacterized yeast proteins across multiple research programs.

How can I design effective controls for functional studies of YJR023C?

Designing robust controls is essential:

• Genetic controls:

  • Use isogenic wild-type strain (same background as deletion strain)

  • Include known deletion strains with expected phenotypes as positive controls

  • Create a complementation strain re-expressing YJR023C to confirm phenotype specificity

  • Include deletion strains of paralogous genes if identified

• Expression controls:

  • Implement vector-only controls for recombinant expression studies

  • Use inactive point mutants to distinguish between structural and functional roles

  • Include promoter-only reporters for transcriptional studies

  • Create control strains expressing unrelated proteins with similar tags

• Experimental validation controls:

  • Perform experiments with biological triplicates at minimum

  • Include multiple time points for temporal processes

  • Use multiple methodologies to confirm key findings

  • Implement the diverse CLS measurement approaches described in to ensure reproducibility

• Statistical approach:

  • Design experiments with sufficient statistical power

  • Use appropriate statistical tests for data analysis

  • Implement blinded scoring where applicable

  • Set clear thresholds for significance (e.g., p-value <0.05 for TF enrichment analysis)

This comprehensive control strategy integrates approaches from multiple successful yeast characterization studies including the AAG1 characterization and heterozygous screening approaches .

What experimental pipeline would you recommend for resolving contradictory phenotypic data when characterizing YJR023C?

When facing contradictory phenotypic data:

• Standardization protocol:

  • Verify strain identity through genotyping

  • Standardize growth conditions precisely (media composition, temperature, aeration)

  • Implement rigorous quality control for reagents

  • Establish quantitative phenotype metrics with clear scoring systems

• Multi-conditional testing framework:

  • Test phenotypes across a matrix of conditions (temperatures, carbon sources, stressors)

  • Create a heat map of phenotypic outcomes across conditions

  • Identify specific conditions where contradictions occur

  • Apply the factorial design principles from to systematically explore condition interactions

• Genetic background analysis:

  • Test in multiple strain backgrounds (BY4743, CEN.PK) as done in the AAG1 study

  • Create and test deletion in haploid and diploid contexts

  • Identify potential genetic modifiers through whole-genome sequencing

  • Consider heterozygous deletions in addition to homozygous knockouts

• Independent method validation:

  • Apply complementary methodologies for each phenotype

  • Use both high-throughput and focused detailed assays

  • Implement time-course studies to capture temporal aspects

  • Conduct epistasis testing with known pathway components

This systematic approach draws on strategies from successful yeast characterization studies and experimental design principles to resolve contradictory data through methodical investigation.

How might characterization of YJR023C contribute to understanding fundamental cellular processes in eukaryotes?

The characterization of YJR023C has potential to advance understanding in several areas:

• Evolutionary conservation analysis:

  • Identify homologs in other species through comparative genomics

  • Determine if YJR023C represents a conserved but uncharacterized eukaryotic function

  • Map conservation patterns to reveal evolutionary importance

• Systems biology integration:

  • Position YJR023C in the global yeast interactome

  • Identify its place in metabolic or signaling networks

  • Contribute to completing the functional map of the yeast genome, fulfilling the goal described by Oliver et al. of determining "how all yeast genes...interact to allow this simple eukaryotic cell to grow, divide, develop and respond to environmental changes"

• Translational implications:

  • Explore whether human homologs exist and their potential functions

  • Investigate if YJR023C plays roles in processes relevant to human disease

  • Consider applications similar to the recombinant yeast vaccine approaches

• Methodological advancement:

  • Develop new approaches for characterizing difficult proteins

  • Refine high-throughput functional genomics methods

  • Establish pipelines for systematic characterization of the remaining uncharacterized proteins

This perspective aligns with the overarching goal of functional genomics as described by Oliver et al. : to provide "an important 'navigational aid' to guide our studies of more complex genomes, such as those of humans, crop plants and farm animals."

What technological advances might facilitate better characterization of proteins like YJR023C in the future?

Emerging technologies with potential impact include:

• Advanced proteomics approaches:

  • Application of AlphaFold and other AI-based structure prediction tools to generate functional hypotheses

  • Integration of hydrogen-deuterium exchange mass spectrometry (HDX-MS) for dynamic structural analysis

  • Implementation of proximity labeling techniques (BioID, APEX) for identifying protein interactions in native contexts

  • Development of higher-throughput protein complex analysis methods

• Genome-wide genetic interaction mapping:

  • Application of CRISPR-based approaches for precise and efficient genome editing

  • Implementation of multiplexed genetic interaction screens for comprehensive epistasis mapping

  • Development of inducible degradation systems for temporal control of protein function

  • Integration of single-cell analysis with genetic perturbations

• Systems-level integration:

  • Application of multi-omics approaches integrating transcriptomics, proteomics, and metabolomics

  • Development of computational methods for integrating disparate data types

  • Implementation of machine learning approaches for functional prediction

  • Creation of comprehensive yeast cell models incorporating uncharacterized proteins

• Functional screens with increased sensitivity:

  • Development of reporters for subtle phenotypic changes

  • Implementation of high-content imaging for detailed phenotypic analysis

  • Application of microfluidics for single-cell analysis over time

  • Integration of biosensors for real-time monitoring of cellular processes

These technological advances align with the evolving landscape of functional genomics approaches and the need for increasingly sophisticated methods to characterize the remaining uncharacterized portions of the yeast proteome.