Recombinant Saccharomyces cerevisiae Uncharacterized protein YNL146W (YNL146W)

What is known about the basic properties of YNL146W protein?

YNL146W is classified as a hypothetical protein in Saccharomyces cerevisiae S288C with no definitively assigned function. Green fluorescent protein (GFP) fusion studies have localized it to the endoplasmic reticulum . The gene is not essential for yeast viability, as demonstrated by viability of deletion mutants . While it has no assigned GO Process or GO Function annotations, it does have a GO Component annotation relating to its localization in the endoplasmic reticulum . The protein is encoded by the genomic locus YNL146W on chromosome XIV of S. cerevisiae .

What expression patterns have been observed for YNL146W?

YNL146W shows variable expression patterns across different growth conditions, though specific expression data is limited. Standard proteomics approaches have confirmed its expression, with GFP-tagging experiments providing evidence of protein production and localization to the endoplasmic reticulum . The protein appears to be constitutively expressed at low to moderate levels under standard laboratory growth conditions, though comprehensive transcriptomic studies analyzing its expression across different environmental conditions would provide more detailed information about potential regulatory mechanisms.

What experimental approaches are recommended for investigating YNL146W function?

Multiple complementary approaches are recommended for investigating the function of this uncharacterized protein:

• Phenotypic analysis of deletion mutants: Create and characterize comprehensive phenotypic profiles of YNL146W deletion strains under various growth conditions, stressors, and chemical treatments.

• Protein localization and dynamics: Expand on existing GFP localization data with time-lapse microscopy and colocalization studies with known ER markers to understand dynamics and precise sub-compartmental localization.

• Protein-protein interaction studies: Implement techniques such as affinity purification coupled with mass spectrometry (AP-MS), yeast two-hybrid screens, or proximity-dependent biotin identification (BioID) to identify interaction partners.

• Transcriptomic and proteomic profiling: Compare wild-type and YNL146W deletion strains using RNA-seq and quantitative proteomics to identify affected pathways.

• CRISPR-based functional genomics: Apply CRISPR interference or activation approaches to modulate YNL146W expression levels and observe resulting phenotypes .

How can researchers effectively generate recombinant YNL146W for in vitro studies?

For recombinant production of YNL146W protein, researchers should consider the following optimized protocol:

• Expression system selection: For initial attempts, use E. coli BL21(DE3) with a pET vector system incorporating an N-terminal His-tag for purification. If membrane association causes solubility issues, consider yeast expression systems like Pichia pastoris.

• Codon optimization: Optimize codons for the expression host to enhance protein yield.

• Expression conditions: Test multiple induction conditions (temperature, IPTG concentration, induction time) to optimize soluble protein yield.

• Purification strategy: Implement a two-step purification using nickel affinity chromatography followed by size exclusion chromatography.

• Protein quality assessment: Verify protein integrity through circular dichroism, dynamic light scattering, and thermal shift assays before proceeding to functional studies.

If E. coli expression proves challenging due to the protein's ER localization, consider cell-free protein synthesis systems or expression in yeast with appropriate secretion signals and purification tags.

What phenotypic effects have been observed in YNL146W deletion or overexpression strains?

Limited phenotypic data is available for YNL146W mutants, but several key observations have emerged:

• Genetic interaction studies: High-throughput genetic interaction mapping has identified a negative genetic interaction between YNL146W and ASN1, indicating a potential functional relationship between these genes . The interaction score of -0.1205 (SGA Score) suggests a moderate negative genetic interaction.

• Stress response involvement: Research has implicated YNL146W in furfural tolerance mechanisms. When expression of YNL146W was modified in conjunction with other genes (particularly SIZ1i), enhanced furfural tolerance was observed .

• Growth characteristics: While deletion of YNL146W alone does not cause lethality, subtle growth effects have been observed under specific stress conditions, suggesting conditional functionality.

A more comprehensive phenotypic analysis across diverse environmental conditions and stressors would likely reveal additional functional insights.

How does YNL146W interact with the cellular stress response network?

Emerging evidence suggests YNL146W may play a role in stress response pathways, particularly relating to chemical stressors. In CRISPR-based studies, modification of YNL146W expression contributed to improved furfural tolerance when combined with modulation of other genes . This indicates a potential role in cellular detoxification or adaptation pathways.

To further investigate this connection, researchers should:

• Evaluate the expression profile of YNL146W under various stress conditions (oxidative, osmotic, heat shock, chemical toxins)

• Perform epistasis analysis with known stress response pathway components

• Assess the phosphorylation state of YNL146W during stress response activation

• Determine whether YNL146W is regulated by stress-responsive transcription factors

• Characterize the impact of YNL146W deletion on global transcriptional response to various stressors

The negative genetic interaction with ASN1 , which is involved in asparagine synthesis, may also provide clues about potential roles in amino acid metabolism or protein synthesis under stress conditions.

What is the evolutionary conservation of YNL146W across fungal species?

Evolutionary analysis of YNL146W would provide valuable insights into its functional importance. Researchers should conduct:

• Comparative genomic analysis: Identify orthologs across diverse fungal lineages using tools like BLAST, HMMER, and OrthoFinder

• Selection pressure analysis: Calculate dN/dS ratios to determine if the gene is under purifying, neutral, or positive selection

• Synteny analysis: Examine conservation of chromosomal context across related species

• Domain architecture analysis: Identify conserved structural features that might suggest function

A preliminary analysis suggests limited conservation outside closely related Saccharomyces species, which could indicate either a specialized function in budding yeast or rapid evolution. The lack of characterized domains further complicates evolutionary analysis.

What are the methodological challenges in studying membrane-associated uncharacterized proteins like YNL146W?

Studying ER-localized proteins like YNL146W presents several technical challenges that researchers should address:

• Solubility and purification issues: Membrane or membrane-associated proteins often require specialized solubilization methods using detergents or nanodiscs

• Maintaining native conformation: Ensuring the protein retains its functional fold outside its native membrane environment

• Functional assay development: Without known function, designing appropriate activity assays requires creative approaches:

  • Thermal shift assays with potential ligands

  • Lipid binding assays

  • Reconstitution in proteoliposomes for transport studies

  • Enzymatic activity screening against diverse substrates

• Structural determination challenges: Membrane proteins are notoriously difficult for structural biology; consider:

  • Cryo-EM for larger complexes

  • NMR for smaller domains

  • X-ray crystallography with fusion partners to aid crystallization

• In vivo relevance: Confirming that in vitro observations reflect physiological function requires careful validation

How can large-scale genetic interaction data help decipher YNL146W function?

Large-scale genetic interaction mapping provides a powerful approach to predict gene function through the principle of "guilt by association." For YNL146W, researchers should:

• Analyze comprehensive interaction profiles: The negative genetic interaction with ASN1 represents just one data point in what could be a complex interaction network. Systematic analysis of all genetic interactions can reveal functional neighborhoods.

• Construct interaction networks: Position YNL146W within the broader yeast genetic interaction network to identify functional modules.

• Leverage quantitative interaction scores: The SGA score of -0.1205 for the YNL146W-ASN1 interaction indicates moderate negative genetic interaction severity. Comparing this to other interactions provides context.

• Apply clustering algorithms: Group genes with similar genetic interaction profiles to identify potential pathway membership.

• Cross-reference with other -omics data: Integrate genetic interaction data with transcriptomic, proteomic, and metabolomic datasets for a systems-level view.

This limited interaction dataset suggests potential connections to amino acid metabolism, but more comprehensive interaction screening would likely reveal additional functional contexts.

What role does YNL146W play in furfural tolerance mechanisms?

Recent CRISPR-based studies have implicated YNL146W in furfural tolerance mechanisms . This finding is particularly significant as:

• YNL146W improved furfural tolerance when its expression was modified along with other genes, particularly SIZ1i

• The effect appears to be context-dependent, as YNL146W modification alone did not significantly improve tolerance, suggesting it functions within a broader detoxification or stress response network

• The synergistic interaction with other genes (SIZ1i, NAT1a) indicates potential involvement in protein modification pathways, as SIZ1 encodes a SUMO ligase and NAT1 is involved in N-terminal acetylation

To further investigate this role, researchers should:

• Determine the precise expression changes of YNL146W during furfural exposure

• Characterize protein-protein interactions that occur specifically under furfural stress

• Assess whether YNL146W undergoes post-translational modifications during stress response

• Determine subcellular localization changes during furfural exposure

• Measure metabolic changes in YNL146W mutants during furfural stress

This connection to industrial stress tolerance highlights potential biotechnological applications while providing clues about fundamental cellular stress response mechanisms.

How can advanced microscopy techniques provide insights into YNL146W function?

Given the known endoplasmic reticulum localization of YNL146W , advanced microscopy approaches offer valuable tools for functional characterization:

• Super-resolution microscopy: Techniques like STORM, PALM, or SIM can provide nanoscale resolution of YNL146W localization within ER subdomains, potentially revealing specific functional regions (sheet vs. tubular ER, ER-mitochondria contact sites, etc.)

• Live-cell dynamics: Time-lapse imaging with GFP-tagged YNL146W would reveal protein dynamics, redistribution during stress, cell cycle dependence, and potential movement between compartments

• Correlative light and electron microscopy (CLEM): Combining fluorescence localization with ultrastructural context can reveal associated subcellular structures

• Proximity labeling visualization: BioID or APEX2 fusion proteins could identify proximal proteins in situ

• FRAP (Fluorescence Recovery After Photobleaching): Measure protein mobility and potential membrane integration properties

• FRET-based interaction studies: Investigate protein-protein interactions with candidate partners using fluorescence resonance energy transfer

Sample preparation and imaging parameters should be optimized for ER visualization, potentially using markers like Sec61-mCherry for colocalization studies.

How can computational approaches advance our understanding of YNL146W?

Computational methods offer powerful complementary approaches for studying uncharacterized proteins like YNL146W:

• Sequence-based function prediction: Advanced algorithms like AlphaFold-Multimer or ESM-2 can predict structural features and potential interaction surfaces

• Network-based function prediction: Integrating multiple data types (genetic interactions, co-expression, protein-protein interactions) into functional networks

• Comparative genomics: Identifying patterns of co-evolution with functionally characterized genes

• Transcriptional regulation analysis: Examining promoter elements to identify regulatory mechanisms

• Metabolic modeling: Integrating YNL146W into genome-scale metabolic models to predict systemic effects

For YNL146W specifically, computational approaches should focus on:

• Predicting potential membrane interaction surfaces

• Identifying cryptic enzymatic active sites or binding pockets

• Analyzing co-expression patterns across comprehensive datasets

• Predicting post-translational modifications

What are the most promising research directions for determining the molecular function of YNL146W?

Based on current knowledge, several promising research avenues emerge:

• ER stress response investigation: Given its ER localization, examine the relationship between YNL146W and the unfolded protein response pathway

• Metabolic profiling: The genetic interaction with ASN1 suggests potential roles in metabolism; comprehensive metabolomic analysis of deletion strains could reveal affected pathways

• Industrial stress tolerance mechanisms: Further explore the role in furfural tolerance and test against other industrial stressors

• Post-translational modification analysis: Characterize modifications of YNL146W and its potential role in modifying other proteins

• Membrane organization: Investigate potential roles in ER membrane domain organization, lipid composition, or membrane contact sites

• Systematic mutagenesis: Identify essential regions through scanning mutagenesis coupled with functional complementation assays

The most efficient approach would likely combine multiple methodologies, starting with comprehensive phenotypic characterization followed by focused mechanistic studies in the most promising areas.

How does the research on uncharacterized proteins like YNL146W contribute to our understanding of eukaryotic cell biology?

Research on uncharacterized proteins like YNL146W contributes significantly to advancing our understanding of fundamental biology:

• Completing the functional annotation of model organisms: Despite decades of research, approximately 20% of S. cerevisiae genes remain functionally uncharacterized. Each newly characterized gene fills crucial gaps in our understanding of cellular systems.

• Discovering novel cellular mechanisms: Uncharacterized proteins often reveal unexpected cellular processes that expand our understanding of biology.

• Enhancing systems biology models: Complete functional annotation improves the accuracy of computational models predicting cellular behavior.

• Evolutionary insights: Understanding the function of species-specific genes helps explain unique adaptations and evolutionary processes.

• Biomedical and biotechnological applications: Many initially uncharacterized proteins have later proven crucial for applications in medicine and biotechnology.

YNL146W specifically, with its connections to stress tolerance and ER localization , may provide insights into cellular adaptation mechanisms relevant to both fundamental biology and industrial applications in bioprocessing and biofuel production.