Recombinant Saccharomyces cerevisiae Putative UPF0479 protein YHL050W-A (YHL050W-A)

What is the YHL050W-A gene and what do we currently know about its expression patterns?

YHL050W-A is a gene in Saccharomyces cerevisiae that encodes a putative UPF0479 protein with largely uncharacterized function. Expression data indicates that YHL050W-A shows differential expression under certain experimental conditions, with studies showing downregulation values of -1.840 and -1.142 in specific contexts . The gene appears to be potentially involved in stress response pathways, as it is mentioned in the context of analysis comparing programmed cell death and cellular stress response. To properly characterize its expression patterns, researchers should implement RNA-seq analysis across multiple experimental conditions, including nutrient limitation, oxidative stress, heat shock, and normal growth conditions. The comparative analysis of expression patterns should incorporate appropriate normalization methods to account for technical and biological variability.

Time-course experiments are particularly valuable for characterizing expression dynamics of putative proteins like YHL050W-A, as they can reveal transient expression changes that might be missed in endpoint analyses. When designing such experiments, researchers should consider collection points at 15 minutes, 30 minutes, 1 hour, 2 hours, 4 hours, and 8 hours post-stimulus to capture both immediate and delayed transcriptional responses. Additionally, integration of expression data with other omics approaches, such as proteomics and metabolomics, can provide a more comprehensive understanding of the functional importance of YHL050W-A in cell physiology.

How can I clone and express recombinant YHL050W-A protein for structural and functional studies?

Successful cloning and expression of recombinant YHL050W-A requires careful consideration of several methodological factors. Begin by designing primers that include appropriate restriction sites compatible with your expression vector of choice, ensuring the reading frame is maintained. For initial expression studies, consider using the pVSec vector system, which has been successfully employed for expression of various proteins in S. cerevisiae . To optimize expression, test multiple promoter systems including constitutive (GPD, TEF) and inducible (GAL1, CUP1) promoters to identify the optimal expression conditions for YHL050W-A.

For purification purposes, incorporate a fusion tag (6xHis, GST, or MBP) that can later be removed using a specific protease recognition site if necessary for downstream applications. Expression can be conducted in S. cerevisiae itself or in heterologous systems such as E. coli or P. pastoris, with each system offering different advantages in terms of yield, post-translational modifications, and protein folding. When expressing in S. cerevisiae, consider using strains with enhanced secretion capabilities, potentially including strains with YGP1 disruption which has been shown to enhance heterologous protein secretion . Optimization of culture conditions including temperature (20-30°C), media composition, and induction parameters will significantly impact protein yield and quality. After expression, purify the protein using affinity chromatography followed by size exclusion chromatography to ensure high purity for subsequent structural and functional analyses.

What are the most effective methods for determining the subcellular localization of YHL050W-A in S. cerevisiae?

Determining the subcellular localization of YHL050W-A is crucial for understanding its potential function. A comprehensive approach would combine multiple complementary techniques to provide robust evidence for protein localization. Begin with fluorescence microscopy using YHL050W-A fused to fluorescent proteins such as GFP or mCherry. When designing these fusion constructs, it's important to test both N- and C-terminal fusions, as tag position can affect protein localization and function. Express these constructs under the native promoter to maintain physiological expression levels and avoid artifacts associated with overexpression.

Complement the microscopy approach with subcellular fractionation followed by western blotting using either antibodies against the fusion tag or custom antibodies against YHL050W-A if available. This biochemical approach provides quantitative information about the distribution of the protein across different cellular compartments. For more precise localization, implement co-localization studies with established organelle markers for the eight major cellular compartments in yeast: cytosol, mitochondrion, peroxisome, nucleus, endoplasmic reticulum, Golgi apparatus, vacuole, and extracellular space . Additionally, consider using proximity labeling approaches such as BioID or APEX to identify neighboring proteins, which can provide further evidence for functional localization. Finally, computational prediction tools based on protein sequence can provide initial hypotheses about localization, but these should always be experimentally validated.

How does YHL050W-A gene expression change during different growth phases and stress conditions?

Analyzing YHL050W-A expression across different growth phases and stress conditions requires a well-designed experimental approach. Implement continuous culture methods such as chemostat cultivation to maintain cells at specific growth rates and nutrient limitations, allowing for precise control of experimental conditions. Measure gene expression using both RT-qPCR for targeted analysis and RNA-seq for genome-wide context, ensuring proper normalization with multiple reference genes that remain stable under your experimental conditions. From existing data, YHL050W-A shows differential expression patterns that may indicate involvement in stress response pathways .

When exposing cells to stress conditions, include oxidative stress (H₂O₂, menadione), osmotic stress (NaCl, sorbitol), heat shock, nutrient limitation, and chemical stressors relevant to your research question. Collect samples at multiple time points to capture both immediate (0-60 minutes) and adaptive (2-24 hours) responses. Integration of transcriptomic data with phenotypic assays, such as growth rate measurements, viability assays, and specific stress response indicators, will provide functional context for expression changes. Additionally, compare expression patterns of YHL050W-A with known stress response genes to place it within established regulatory networks. This approach aligns with comprehensive functional genomics studies that have been applied to characterize gene function in S. cerevisiae .

What are the most effective CRISPR-Cas9 strategies for generating YHL050W-A knockout and conditional mutants in S. cerevisiae?

Developing effective CRISPR-Cas9 strategies for YHL050W-A manipulation requires careful consideration of several technical aspects. For knockout generation, design at least three guide RNAs targeting different regions of the gene using tools like CHOPCHOP or E-CRISP that account for S. cerevisiae codon usage and minimize off-target effects. The repair template should contain 40-60 bp homology arms flanking either a selection marker or preferably a stop codon insertion that maintains the reading frame of downstream genes if present . This approach is particularly important for compact genomes like S. cerevisiae where genes may overlap or have regulatory elements within coding regions of adjacent genes.

For conditional mutants, consider implementing either an auxin-inducible degron (AID) system or a temperature-sensitive allele approach. The AID system requires fusion of an auxin-responsive IAA domain to YHL050W-A and expression of the TIR1 F-box protein, allowing for rapid, reversible protein depletion upon auxin addition. Alternatively, develop promoter-replacement strategies using the tetO-repressible or GAL1 promoter systems for conditional expression. When introducing these modifications, use a single plasmid system containing both Cas9 and the guide RNA to maximize transformation efficiency. After transformation, confirm genomic modifications through PCR, sequencing, and expression analysis. For functional validation, perform comprehensive phenotypic analyses under different growth conditions and stresses to identify conditions where YHL050W-A function becomes essential or contributes to cellular fitness. This approach has been successfully used to study cell wall-related proteins and secretion pathways in S. cerevisiae .

How can integrated multi-omics approaches be used to elucidate the function of YHL050W-A in S. cerevisiae?

Implementing an integrated multi-omics approach for YHL050W-A functional characterization requires coordinated analysis across several molecular levels. Begin with comparative transcriptomics between wild-type and YHL050W-A deletion strains under multiple conditions to identify genes with correlated expression patterns. RNA-seq should be performed with sufficient biological replicates (minimum n=3) and appropriate sequencing depth (>20 million reads per sample) to detect subtle expression changes. Follow this with proteomics analysis using both shotgun MS/MS approaches for global protein changes and targeted proteomics (PRM or SRM) for quantifying specific interaction partners or post-translational modifications that may regulate YHL050W-A function.

Metabolomics analysis using both targeted and untargeted approaches can reveal metabolic pathways affected by YHL050W-A deletion, providing functional insights even when direct phenotypes are subtle. Integrate these datasets using computational tools designed for multi-omics integration, such as weighted gene co-expression network analysis (WGCNA) or multivariate statistical approaches like O2PLS. Physical interaction studies using BioID, IP-MS, or yeast two-hybrid screening can identify direct protein partners. For genome-scale perspectives, leverage existing metabolic models of S. cerevisiae, such as iND750 , to predict systems-level impacts of YHL050W-A perturbation. These approaches have successfully identified novel functions for previously uncharacterized genes in S. cerevisiae and can be particularly powerful for putative proteins like YHL050W-A where direct functional assays may not be immediately obvious.

What computational approaches can predict potential functions of YHL050W-A based on structural homology and evolutionary conservation?

Computational prediction of YHL050W-A function requires a multi-level bioinformatic analysis pipeline. Begin with sequence-based analyses including hidden Markov model searches against protein family databases (Pfam, InterPro) to identify conserved domains characteristic of the UPF0479 family. Perform position-specific iterative BLAST (PSI-BLAST) searches to identify remote homologs that may have characterized functions. For evolutionary analyses, construct maximum likelihood phylogenetic trees using UPF0479 proteins from diverse fungal species to identify patterns of conservation that may indicate functional constraints. Calculate selection pressures (dN/dS ratios) across the protein sequence to identify residues under purifying selection, which often correlate with functional importance.

For structural predictions, utilize protein structure prediction tools like AlphaFold2 or RoseTTAFold to generate reliable 3D models of YHL050W-A. Analyze these models using structure comparison tools (DALI, TM-align) to identify structural similarity with proteins of known function, even in the absence of sequence conservation. Perform in silico docking with potential metabolites or proteins to predict binding partners. Additionally, implement co-evolution analysis methods like direct coupling analysis (DCA) to identify residue pairs that have co-evolved, potentially indicating functional interactions or structural constraints. For systems-level predictions, analyze co-expression networks from large-scale transcriptomic datasets to identify genes with similar expression patterns across multiple conditions, suggesting functional relationships. This integrated computational approach has successfully identified functions for previously uncharacterized proteins in S. cerevisiae and can provide testable hypotheses for experimental validation of YHL050W-A function.

How can synthetic genetic array (SGA) analysis be optimized to identify genetic interactions of YHL050W-A?

Optimizing SGA analysis for YHL050W-A requires careful experimental design and methodological considerations to maximize data quality and biological insights. Begin by creating both deletion and hypomorphic alleles of YHL050W-A as query strains, as complete deletion may mask certain genetic interactions if the gene is not essential. Use the latest SGA methodology incorporating robotics for high-throughput manipulation and imaging-based scoring systems for quantitative assessment of genetic interactions. When designing the experiment, include condition-specific SGA screens under relevant stresses (oxidative, osmotic, temperature) to uncover condition-dependent genetic interactions that may not be apparent under standard laboratory conditions.

For data analysis, implement advanced computational approaches that account for both additive and multiplicative models of genetic interaction to accurately classify interactions as negative (synthetic sick/lethal) or positive (suppressive). Calculate precise genetic interaction scores that account for both the strength and statistical significance of interactions. After identifying primary interactions, perform secondary validation using targeted growth assays with increased replication. Extend the analysis by integrating genetic interaction data with existing functional information using tools like spatial analysis of functional enrichment (SAFE) or network alignment algorithms. This integration can place YHL050W-A within specific biological processes or cellular compartments based on the enrichment of genetic interactions with genes of known function.

Consider complementing SGA with chemical-genetic profiling to identify compounds that differentially affect growth of YHL050W-A mutants, providing additional functional insights. The comprehensive gene-protein-reaction associations and compartmentalized metabolic models developed for S. cerevisiae provide valuable frameworks for interpreting genetic interaction data in a systems biology context . This approach has been successfully used to characterize functions of previously uncharacterized genes in S. cerevisiae and can provide detailed functional insights for YHL050W-A.

What strategies can be employed to study post-translational modifications of YHL050W-A and their functional significance?

Investigating post-translational modifications (PTMs) of YHL050W-A requires a comprehensive analytical strategy combining multiple complementary approaches. Begin with in silico prediction of potential modification sites using specialized tools for phosphorylation (NetPhos, GPS), ubiquitination (UbiSite), SUMOylation (GPS-SUMO), and other relevant PTMs based on the protein sequence. For experimental validation and discovery, implement a mass spectrometry-based proteomics approach using both bottom-up and top-down strategies. For bottom-up analysis, optimize protein extraction and enrichment protocols specific for each PTM type (e.g., TiO2 for phosphopeptides, antibody-based enrichment for ubiquitination).

Employ multiple proteases beyond trypsin (e.g., chymotrypsin, AspN) to increase sequence coverage, especially for regions with few tryptic cleavage sites. For site-specific functional studies, generate point mutations of identified modification sites to non-modifiable residues (e.g., S→A for phosphorylation sites) and assess the impact on protein function, localization, and stability. Combine these approaches with time-course analyses after relevant cellular stimuli to capture dynamic changes in modification patterns. For challenging PTMs with low stoichiometry, consider implementing proximity labeling approaches to enrich for the neighborhood proteome around YHL050W-A, potentially capturing transient interactions with modifying enzymes.

The functional significance of identified PTMs can be assessed through integration with phenotypic data and pathway analysis, placing YHL050W-A modifications within known regulatory networks. This comprehensive approach to PTM analysis has successfully revealed regulatory mechanisms for many yeast proteins and can provide critical insights into the regulation and function of putative proteins like YHL050W-A.

How can heterologous expression systems be optimized for high-yield production of functionally active YHL050W-A for structural studies?

Optimizing heterologous expression of YHL050W-A for structural studies requires systematic testing of multiple expression systems and conditions. For bacterial expression in E. coli, test both BL21(DE3) and its derivatives including Rosetta (for rare codon optimization) and SHuffle (for disulfide bond formation). Compare multiple expression vectors with different fusion tags (His, GST, MBP, SUMO) positioned at either N- or C-terminus to identify configurations that maximize solubility and stability. If bacterial expression yields poorly folded protein, transition to eukaryotic expression systems including Pichia pastoris, insect cells (Sf9, Hi5), or mammalian cells (HEK293, CHO), which provide more sophisticated folding machinery and post-translational modifications.

For S. cerevisiae expression, consider implementing strategies that enhance protein secretion, such as disruption of YGP1 or overexpression of SED5, which have been shown to increase heterologous protein secretion by up to 2.2-fold . Optimize culture conditions through factorial design experiments varying temperature (16-30°C), induction strength (variable inducer concentration), induction timing (early, mid, or late log phase), and duration (4 hours to several days). For membrane-associated proteins, test detergent screening panels (including DDM, LMNG, GDN) for optimal extraction and stability. Implement quality control measures at each step using techniques like size-exclusion chromatography coupled with multi-angle light scattering (SEC-MALS) to assess protein homogeneity and thermal shift assays to evaluate stability.

For structural studies specifically, perform limited proteolysis to identify stable domains if the full-length protein proves recalcitrant to crystallization. Consider implementing surface entropy reduction mutations to promote crystal contacts or adding fusion proteins known to facilitate crystallization (T4 lysozyme, BRIL). For cryo-EM studies, optimize grid preparation protocols with multiple grid types and freezing conditions. This systematic approach to protein production has been successfully applied to challenging proteins and provides the best foundation for structural studies of YHL050W-A.