Recombinant Saccharomyces cerevisiae Uncharacterized protein YIL092W (YIL092W)

What is known about the uncharacterized protein YIL092W in Saccharomyces cerevisiae?

YIL092W is an uncharacterized protein encoded in the Saccharomyces cerevisiae genome. Similar to many uncharacterized proteins, its biological function, interacting partners, and role in cellular processes remain largely unknown. The protein is classified as "uncharacterized" because researchers have not yet determined its specific function through experimental validation. Saccharomyces cerevisiae, as a model organism, has been instrumental in various biological studies, including understanding protein function and interactions, making it an excellent system for characterizing unknown proteins like YIL092W . To begin characterizing this protein, researchers typically start with bioinformatic approaches to predict possible functions based on sequence homology, domain identification, and phylogenetic analysis before moving to wet-lab experimental validation.

How can I design an initial experimental approach to begin characterizing YIL092W?

When designing initial experiments to characterize an unknown protein like YIL092W, a systematic approach is essential. Begin by clearly defining your variables - with the expression or manipulation of YIL092W as your independent variable and a measurable cellular response (growth rate, stress response, metabolite production) as your dependent variable . Start with gene deletion or overexpression studies to observe phenotypic changes. For gene deletion, create knockout strains using homologous recombination techniques specific to yeast. For overexpression, clone the YIL092W coding sequence into an appropriate yeast expression vector with an inducible promoter. Compare the growth, morphology, and cellular responses of these modified strains with wild-type yeast under various conditions (different carbon sources, temperature stress, osmotic stress, etc.) to identify conditions where YIL092W may play a functional role. Document both positive and significant findings as well as negative or statistically insignificant results, as both are valuable for understanding protein function .

What are the recommended methods for expressing and purifying recombinant YIL092W for in vitro studies?

For expressing and purifying recombinant YIL092W, several methodological considerations are important. Begin by designing an expression construct containing the YIL092W coding sequence with an appropriate affinity tag (6xHis, GST, or FLAG) to facilitate purification. For homologous expression within S. cerevisiae, use a strong inducible promoter like GAL1 or constitutive promoter like TDH3 (GPD). When expressing in yeast cells, optimal growth conditions must be established through experimental testing of different media compositions, induction times, and temperatures.

For purification, develop a protocol that typically includes:

• Cell lysis using glass beads or enzymatic methods optimized for yeast cells

• Initial purification using affinity chromatography based on your chosen tag

• Secondary purification via ion exchange or size exclusion chromatography

• Quality assessment using SDS-PAGE and Western blotting

Track protein yield and purity at each step using spectrophotometric measurements and gel analysis. For difficult-to-express proteins, test multiple expression systems, including E. coli or insect cells, adjusting codon usage as needed. Document purification efficiency at each step with quantitative measurements of protein concentration, purity percentage, and specific activity if an assay is available.

What computational approaches can predict potential functions of YIL092W prior to experimental validation?

Advanced computational approaches provide valuable insights before committing to time-intensive experimental validations. Begin with comprehensive sequence analysis using multiple tools: BLAST for identifying homologous proteins across species, PFAM and InterPro for domain prediction, and PSIPRED for secondary structure modeling. For YIL092W, apply specialized prediction algorithms that analyze conserved motifs, subcellular localization signals, and post-translational modification sites.

Leverage systems biology approaches by examining:

• Co-expression networks to identify genes with similar expression patterns

• Protein-protein interaction predictions based on structural homology

• Metabolic pathway analysis to position the protein in known cellular processes

• Phylogenetic profiling to trace evolutionary conservation patterns

When applying these methods, maintain rigor by using multiple independent tools and cross-validating predictions. Document confidence scores and p-values associated with each prediction . For instance, if sequence analysis suggests membrane localization, verify this through different predictors (SignalP, TMHMM, Phobius) and assess the statistical confidence of each prediction. This comprehensive computational analysis will guide the design of focused experimental approaches, saving valuable research time and resources.

How can I design comprehensive experiments to determine YIL092W's role in cellular stress response?

To investigate YIL092W's potential role in cellular stress responses, design a systematic experimental approach with multiple stress conditions. Begin by creating both deletion (ΔyiL092W) and overexpression strains alongside appropriate controls, including complemented strains where the deletion is rescued by expressing YIL092W on a plasmid to confirm phenotype specificity .

Expose these strains to a matrix of stress conditions including:

• Oxidative stress (H₂O₂, menadione)

• Temperature stress (heat shock, cold shock)

• Osmotic stress (high salt, sorbitol)

• Nutrient limitation (carbon, nitrogen, phosphate)

• DNA damage agents (UV, MMS)

• ER stress inducers (tunicamycin, DTT)

For each condition, measure multiple outputs to generate comprehensive phenotypic profiles:

Use statistical analysis to identify significant differences between wild-type and modified strains, reporting exact p-values rather than simply p<0.05 . This comprehensive approach will reveal specific stress conditions where YIL092W plays a functional role, providing direction for more focused mechanistic studies.

What advanced proteomics approaches would be most effective for identifying interaction partners of YIL092W?

For identifying interaction partners of YIL092W, implement a multi-faceted proteomics strategy combining complementary techniques. Begin with affinity purification coupled to mass spectrometry (AP-MS) using tagged YIL092W as bait. Express YIL092W with different epitope tags (FLAG, HA, or TAP tag) to minimize tag-specific artifacts and perform pulldowns under varying buffer conditions to capture both stable and transient interactions.

For detecting transient or weak interactions, implement proximity-dependent labeling techniques:

• BioID: Fuse YIL092W with a biotin ligase to biotinylate proteins in close proximity

• APEX2: Fuse with an engineered peroxidase for spatially-restricted protein labeling

• Split-TurboID: Use for detecting specific protein-protein interactions in living cells

Complement these approaches with crosslinking mass spectrometry (XL-MS) to capture direct interaction interfaces. For all techniques, include appropriate controls:

• Tag-only expressing strains

• Unrelated tagged proteins with similar expression levels/localization

• Multiple biological replicates

Analyze the resulting proteomics data using specialized software to filter out common contaminants and calculate enrichment scores and statistical significance for each potential interactor. Visualize the interaction network and classify partners based on cellular function to identify biological processes involving YIL092W. Validate key interactions using orthogonal methods such as yeast two-hybrid, co-immunoprecipitation, or fluorescence microscopy co-localization studies.

How can I determine if YIL092W is involved in specific metabolic pathways in S. cerevisiae?

To investigate YIL092W's potential role in metabolic pathways, implement a comprehensive metabolic profiling approach. Begin by growing YIL092W deletion and overexpression strains alongside wild-type controls in media with different carbon sources (glucose, galactose, glycerol, ethanol) to reveal carbon metabolism involvement . For each condition, collect samples at multiple growth phases (lag, exponential, diauxic shift, stationary) to capture dynamic metabolic changes.

Perform targeted metabolomics focusing on key pathway intermediates:

• Glycolysis/gluconeogenesis metabolites

• TCA cycle intermediates

• Amino acid biosynthesis precursors

• Nucleotide metabolism components

• Lipid metabolism precursors

Analyze changes in metabolite levels using liquid chromatography-mass spectrometry (LC-MS) or gas chromatography-mass spectrometry (GC-MS). Quantify at least 30-50 key metabolites and calculate fold changes relative to wild-type controls. Present results in a comprehensive metabolic profile table:

Complement metabolomics with enzyme activity assays for key metabolic enzymes and 13C-flux analysis to trace carbon flow through central metabolic pathways. This multi-layered approach will reveal whether YIL092W impacts specific metabolic processes, either directly as a metabolic enzyme or indirectly as a regulator of metabolic pathways.

What are the recommended approaches for determining YIL092W subcellular localization?

Determining the subcellular localization of YIL092W requires multiple complementary approaches to ensure reliable results. Begin with fluorescent protein tagging by creating C-terminal and N-terminal fusions with fluorescent proteins (GFP, mCherry, or mScarlet). Express these constructs from the native YIL092W promoter to maintain physiological expression levels, and examine cells using confocal microscopy during different growth phases and environmental conditions, as localization may be dynamic .

For more precise localization, perform co-localization studies with established organelle markers:

• Nucleus: Histone H2B-BFP

• Mitochondria: MitoTracker dyes

• ER: Sec63-mCherry

• Golgi: Anp1-mCherry

• Vacuole: FM4-64 staining

• Peroxisomes: Pex3-BFP

Complement fluorescence microscopy with biochemical fractionation:

• Isolate subcellular fractions using differential centrifugation

• Perform Western blot analysis to detect YIL092W using specific antibodies or tag detection

• Use established marker proteins to confirm the purity of each fraction

Quantify the relative abundance of YIL092W across fractions as shown in this example table:

For proteins with multiple localizations, perform time-lapse imaging to track dynamic localization changes in response to environmental stimuli or throughout the cell cycle. This comprehensive approach will definitively establish the subcellular residence of YIL092W and provide crucial insights into its potential function.

How can I investigate if YIL092W undergoes post-translational modifications that affect its function?

Investigating post-translational modifications (PTMs) of YIL092W requires a systematic approach combining computational prediction and experimental validation. Begin with in silico analysis using specialized PTM prediction tools to identify potential modification sites:

• Phosphorylation: NetPhos, GPS

• Ubiquitination: UbPred, UbiSite

• Glycosylation: NetNGlyc, NetOGlyc

• Acetylation: PAIL, GPS-PAIL

• SUMOylation: GPS-SUMO

For experimental validation, purify YIL092W using tandem affinity purification (TAP) tagging under native conditions to preserve modifications. Subject the purified protein to mass spectrometry analysis using:

• Bottom-up proteomics with enrichment for specific PTMs

• Top-down proteomics to analyze intact proteoforms

• Middle-down approach for larger peptide fragments

To determine the functional impact of identified PTMs, create point mutations at modification sites (e.g., serine to alanine for phosphorylation sites) and assess protein function, localization, and interaction capabilities compared to wild-type YIL092W. For phosphorylation studies, analyze YIL092W modification patterns under different growth conditions and stresses to identify regulatory mechanisms. Present PTM findings in a comprehensive format:

For each identified modification, determine conservation across related species, as functionally important PTMs tend to be evolutionarily conserved. This comprehensive PTM analysis will provide crucial insights into the regulation and function of YIL092W.

What are the common challenges in expressing recombinant YIL092W and how can they be overcome?

When expressing recombinant YIL092W, researchers frequently encounter several challenges that require methodical troubleshooting. Protein misfolding and aggregation often occur when expressing uncharacterized proteins. To address this, systematically optimize expression conditions by testing different temperatures (15°C, 20°C, 25°C, 30°C), induction times (2h, 4h, 8h, overnight), and inducer concentrations. For S. cerevisiae expression, consider using specialized strains with enhanced folding capacity or deleted protease genes .

For proteins with poor expression levels, implement these methodological approaches:

• Codon optimization based on S. cerevisiae preferred codons

• Testing different fusion tags (MBP, SUMO, or Thioredoxin) known to enhance solubility

• Co-expression with molecular chaperones like Hsp70 or Hsp90

• Addition of stabilizing compounds to growth media (glycerol, sorbitol, arginine)

If the protein is toxic to the expression host, use tightly controlled inducible promoters with minimal basal expression. For membrane-associated proteins, include appropriate detergents during purification:

Document all optimization steps systematically, including quantitative measurements of protein yield and solubility under each condition. This methodical approach will help identify the optimal expression conditions for obtaining functional YIL092W protein in sufficient quantities for downstream analyses .

How can I resolve contradictory results in YIL092W functional studies?

When confronted with contradictory results in YIL092W functional studies, implement a systematic approach to identify the source of discrepancies. Begin by critically evaluating experimental design differences that might explain contradictory outcomes, including strain backgrounds, growth conditions, and methodological variations . Create a comprehensive comparison table of experimental parameters across studies:

Consider these methodological approaches to resolve contradictions:

• Validate gene deletion strains by PCR and sequencing to confirm proper targeting

• Perform complementation experiments to verify phenotypes are directly caused by YIL092W deletion

• Use multiple methodologies to assess the same outcome (e.g., measuring growth by OD600, colony counting, and biomass determination)

• Collaborate with labs reporting different results to standardize protocols

Document all variables and their systematic testing, presenting comprehensive data including any statistically insignificant results. This thorough approach will help identify the specific conditions under which YIL092W exhibits particular functions, resolving apparent contradictions through context-specific understanding.

What controls are essential when studying YIL092W to ensure reliable and reproducible results?

Implementing rigorous controls is critical for generating reliable and reproducible results when studying an uncharacterized protein like YIL092W. For genetic manipulation studies, essential controls include:

• Empty vector controls for overexpression studies

• Wild-type parental strain grown under identical conditions

• Complementation strains where the deletion is rescued by wild-type YIL092W

• Strains expressing catalytically inactive mutants (if potential enzymatic activity is studied)

• Multiple independent transformants/clones to account for clonal variation

When performing localization or interaction studies, implement these critical controls:

• Free fluorescent protein expression for localization studies

• Tag-only constructs for pull-down experiments

• Unrelated proteins with similar expression levels as interaction specificity controls

• Multiple tag types and positions (N-terminal, C-terminal) to rule out tag artifacts

For functional assays, incorporate condition controls:

• Time-course measurements to capture dynamic responses

• Concentration gradients for any treatment or stress

• Positive controls using genes with established functions in the pathway of interest

Document all control experiments with quantitative data and statistical analysis:

By systematically implementing and documenting these controls, you establish the specificity and reliability of your findings regarding YIL092W function. This approach ensures that observed phenotypes are directly attributable to YIL092W rather than experimental artifacts or secondary effects .

What bioinformatic approaches can help integrate YIL092W experimental data with existing knowledge?

Integrating experimental data on YIL092W with existing knowledge requires sophisticated bioinformatic approaches to contextualize your findings within the broader cellular landscape. Begin by performing comprehensive ortholog analysis across species to identify evolutionary conservation patterns, focusing on both sequence and structural similarities . Use this evolutionary context to transfer functional annotations from better-characterized orthologs in other species.

For network-based integration, implement these approaches:

• Construct protein-protein interaction networks incorporating your experimentally identified YIL092W interactors

• Perform gene ontology (GO) enrichment analysis on these networks to identify overrepresented biological processes

• Map genetic interaction data onto these networks to identify functional relationships

• Integrate transcriptomic and proteomic datasets to identify co-regulated genes

Visualize these integrated networks using specialized tools like Cytoscape, and perform community detection algorithms to identify functional modules containing YIL092W. Incorporate data from published high-throughput studies specific to S. cerevisiae:

Apply machine learning approaches such as random forest or support vector machines to integrate these heterogeneous data types and predict potential functions of YIL092W. Validate these predictions through targeted experiments, creating an iterative cycle of prediction and validation to progressively refine understanding of YIL092W function .

For time-series data analysis, apply these specialized approaches:

• Functional data analysis to capture temporal patterns

• Mixed-effects models to account for repeated measurements

• Dynamic Bayesian networks to infer causal relationships over time

• ANOVA with time as a factor for identifying significant temporal changes

When integrating multiple data types, implement dimension reduction techniques:

For assessing protein-protein interactions, implement statistical frameworks that account for common contaminants in AP-MS data, such as SAINT or CompPASS. When reporting results, provide exact p-values rather than significance thresholds, and include effect sizes and confidence intervals alongside p-values .

For complex phenotypic data, use multivariate statistics like MANOVA or PERMANOVA when multiple related outcomes are measured simultaneously. Document all statistical methods, including software versions, parameters, and data normalization procedures to ensure reproducibility. This comprehensive statistical approach will extract meaningful biological insights from complex experimental data while controlling for false discoveries.

How can findings about YIL092W contribute to understanding fundamental biological processes?

Characterizing the function of YIL092W has potential to illuminate fundamental biological processes through several mechanisms. As an uncharacterized protein in one of the most thoroughly studied model organisms, YIL092W represents one of the remaining knowledge gaps in our understanding of eukaryotic cell biology. By determining its function, we contribute to completing the functional annotation of the yeast genome, which serves as a reference point for understanding more complex eukaryotic systems .

The systematic characterization of YIL092W may reveal novel cellular mechanisms, particularly if it belongs to a previously uncharacterized protein family or represents a unique functional adapter between known cellular processes. If YIL092W has orthologs in other species, your findings will contribute to the annotation of these related proteins through evolutionary inference, potentially revealing conserved cellular machinery across eukaryotes.

To maximize the broader impact of YIL092W research, focus on these approaches:

• Map the protein into existing cellular frameworks using network analysis

• Investigate conservation patterns across species to understand evolutionary importance

• Examine its potential role in fundamental processes like stress response, which have broad relevance

• Look for connections to disease-associated pathways that might have translational implications

Document both positive and negative findings comprehensively, as even the absence of phenotypes under certain conditions provides valuable information about cellular redundancy and robustness. This approach ensures that characterization of YIL092W contributes to our fundamental understanding of eukaryotic cell biology regardless of the specific function discovered .

What are the most promising future research directions for further characterizing YIL092W?

Based on current understanding of uncharacterized yeast proteins, several promising research directions can advance our knowledge of YIL092W. High-throughput CRISPR screening approaches offer opportunities to identify genetic interactions by creating double mutants of YIL092W with other genes and screening for synthetic phenotypes. This approach could place YIL092W in specific biological pathways through genetic interaction mapping .

Advanced structural biology approaches represent another frontier:

• Cryo-electron microscopy to determine protein structure at near-atomic resolution

• Hydrogen-deuterium exchange mass spectrometry to identify dynamic regions

• Integrative structural biology combining multiple data types

• In-cell NMR to observe protein behavior in native environments

Emerging single-cell technologies offer unprecedented insights:

The integration of multi-omics approaches—combining transcriptomics, proteomics, metabolomics, and lipidomics data—will provide a systems-level understanding of YIL092W function. Development of small-molecule modulators (activators or inhibitors) of YIL092W would create valuable chemical biology tools for acute perturbation studies, complementing genetic approaches.

These future directions should be prioritized based on preliminary data from initial characterization studies, focusing resources on the most promising avenues while maintaining an open and adaptable research strategy .

How can I validate that my experimental findings about YIL092W are physiologically relevant?

Implement these methodological approaches for physiological validation:

• Use genomic integration of tagged constructs rather than plasmid-based expression

• Create point mutations rather than complete deletions when possible

• Employ inducible/repressible systems to create partial loss-of-function

• Validate findings across multiple strain backgrounds to ensure generalizability

To connect molecular findings with cellular physiology, examine phenotypes across multiple scales: