Recombinant Saccharomyces cerevisiae Putative UPF0479 protein YLR466C-A (YLR466C-A)

What is the YLR466C-A protein and what are its basic characteristics?

The YLR466C-A is a putative UPF0479 protein from Saccharomyces cerevisiae. It is a full-length protein comprising 160 amino acids with the sequence: MMPAKLQLDVLRTLQSSARHGTQTLKNSNFLERFHKDRIVFCLPFFPALFLVPVQKVLQHLCLRFTQVAPYFIIQLFDLPSRHAENLAPLLASCRIQYTNCFSSSSNGQVPSIISLYLRVDLSPFYAKIFQISYRVPMIWLDVFQVFFVFLVISQHSLHS . The protein belongs to the UPF0479 family, and its function remains largely uncharacterized, making it an interesting target for foundational research. The recombinant version commonly used in laboratory settings is often expressed with an N-terminal His-tag in E. coli expression systems .

How is recombinant YLR466C-A protein typically produced for research purposes?

The recombinant YLR466C-A protein is typically produced using E. coli expression systems. The full-length protein (amino acids 1-160) is expressed with an N-terminal His-tag to facilitate purification . After expression, the protein is purified to greater than 90% purity as determined by SDS-PAGE and supplied as a lyophilized powder . The production method leverages S. cerevisiae's status as an ideal chassis organism for synthetic biology research due to its simple gene manipulation characteristics and clear regulation mechanisms of gene expression . For most laboratory applications, the protein can be reconstituted in deionized sterile water to a concentration of 0.1-1.0 mg/mL, and glycerol (5-50% final concentration) can be added for long-term storage at -20°C/-80°C .

What are the optimal storage conditions for YLR466C-A protein samples?

Based on supplier recommendations, recombinant YLR466C-A protein should be stored at -20°C/-80°C upon receipt, and aliquoting is necessary for multiple use to avoid repeated freeze-thaw cycles . The protein is typically provided in a Tris/PBS-based buffer containing 6% Trehalose at pH 8.0 . When working with the protein, it is advisable to keep working aliquots at 4°C for up to one week rather than repeatedly freezing and thawing, which can compromise protein integrity . For reconstitution, it is recommended to briefly centrifuge the vial before opening to bring the contents to the bottom, then reconstitute in deionized sterile water to a concentration of 0.1-1.0 mg/mL .

What experimental approaches can be used to elucidate the function of YLR466C-A protein?

To investigate the function of the YLR466C-A protein, researchers should implement a multi-faceted experimental strategy. Begin with bioinformatic analyses comparing YLR466C-A to its homologs, particularly other UPF0479 family proteins like YBL113W-A, YEL077W-A, and YHL050W-A that show high sequence similarity (e-values ranging from 1.67505e-73 to 6.10511e-73) . Employ gene knockout/knockdown studies using CRISPR-Cas9 systems to observe phenotypic changes in S. cerevisiae. Complementation assays can verify functional conservation between YLR466C-A and its homologs. Proteomics approaches, including co-immunoprecipitation coupled with mass spectrometry, can identify protein-protein interactions. For subcellular localization, fluorescent tagging (e.g., GFP fusion) can be utilized, particularly noting the potential signal peptide cleavage site at position 56 (score: 0.5425) . Transcriptomic analysis under various stress conditions can reveal regulatory patterns, similar to methods used for biosensor development in S. cerevisiae .

How can YLR466C-A be utilized in synthetic biology applications?

YLR466C-A can be leveraged in synthetic biology applications by exploiting S. cerevisiae's established role as an ideal chassis organism. Researchers should consider engineering YLR466C-A as part of synthetic metabolic pathways, potentially using techniques similar to those employed in biosensor development in S. cerevisiae . The protein could be modified through directed evolution or rational design approaches to enhance or alter its functionality. Utilizing promoter-reporter systems (similar to the mCherry reporter system described in biosensor development) can help evaluate the expression and activity of engineered YLR466C-A variants . S. cerevisiae's advantages for synthetic biology applications include simple gene manipulation, clear regulation mechanisms of gene expression, mature high-density fermentation technology, and biological safety . These characteristics make it suitable for potentially incorporating YLR466C-A into synthetic pathways for producing biological products, similar to how S. cerevisiae has been used for producing various biological drugs and compounds like artemisinic acid .

What is the evolutionary significance of UPF0479 protein family across different yeast species?

The evolutionary significance of the UPF0479 protein family can be assessed through comparative genomics across yeast species. The SwissProt database shows high similarity between YLR466C-A and multiple UPF0479 family proteins in S. cerevisiae, including YBL113W-A, YEL077W-A, YHL050W-A, YDR545C-A, YFL068W, YHR219C-A, and YJL225W-A, with e-values ranging from 1.67505e-73 to 2.37943e-71 . This high sequence conservation suggests important functional roles that have been maintained through evolutionary pressure. Researchers should conduct phylogenetic analyses to map the evolutionary relationships between these homologs. Synteny analysis would reveal whether genomic context is preserved across species, providing insights into potential functional relationships with neighboring genes. Patterns of selection can be evaluated using dN/dS ratios to determine whether these proteins evolved under purifying, neutral, or positive selection. Domain architecture analysis would identify conserved functional domains that might indicate shared biochemical activities across the protein family.

How should researchers design experiments to characterize YLR466C-A protein function?

When designing experiments to characterize YLR466C-A protein function, researchers should follow a systematic approach based on established experimental design principles. First, clearly define your variables: the independent variable could be YLR466C-A expression levels (wild-type, overexpression, or knockout), while dependent variables might include growth rates, stress responses, or metabolic outputs . Formulate specific, testable hypotheses about YLR466C-A function based on bioinformatic predictions and homology to other UPF0479 family proteins . Design experimental treatments that manipulate YLR466C-A expression, such as using inducible promoters or CRISPR-based modifications. Assign subjects to groups using either between-subjects design (comparing different yeast strains) or within-subjects design (measuring the same strain under different conditions) . For measuring dependent variables, consider techniques such as growth assays, RNA-seq for transcriptional effects, or metabolomics for biochemical changes. Control for extraneous variables including temperature, media composition, and genetic background of the strains . Include appropriate controls, such as wild-type strains and strains with mutations in related genes.

What considerations should be made when using recombinant YLR466C-A in interaction studies?

When conducting interaction studies with recombinant YLR466C-A, several technical considerations are critical for experimental success. The N-terminal His-tag commonly used in the recombinant protein might interfere with protein-protein interactions, so researchers should consider using both tagged and untagged versions for validation . Protein solubility must be optimized when reconstituting the lyophilized protein; start with the recommended concentration of 0.1-1.0 mg/mL in deionized sterile water, but be prepared to adjust buffer conditions if aggregation occurs . Researchers should perform binding assays under various pH and ionic strength conditions to identify optimal interaction parameters. When designing co-immunoprecipitation experiments, consider the potential signal peptide cleavage site at position 56, as this may affect protein topology and interaction surfaces . For cross-linking studies, the amino acid composition of YLR466C-A should guide the selection of appropriate cross-linking reagents. Control experiments should include proteins from the same UPF0479 family (like YBL113W-A or YEL077W-A) to distinguish between specific and non-specific interactions .

How can researchers develop a biosensor system incorporating YLR466C-A?

To develop a biosensor system incorporating YLR466C-A, researchers should adapt methodologies similar to those used for developing the 1-butanol biosensor in S. cerevisiae . Begin by conducting transcriptomic analysis to understand how YLR466C-A responds to various environmental stresses or metabolites of interest. Design gene cassettes containing promoters responsive to these conditions, followed by a reporter gene (such as mCherry) and a terminator (such as TEF1-terminator) . When testing the biosensor, use a defined minimal medium like SC-LEU rather than rich media like YPAD to reduce background signals and enable effective discrimination of response . Include appropriate controls: a strong constitutive promoter (like PTEF1-mCherry) as a positive control and a promoterless construct (Empty-mCherry) as a negative control . Test the biosensor's response by growing engineered strains to early exponential growth phase before adding the stimulus of interest. Consider multiple reporter systems for verification and to expand the dynamic range of detection. Optimize the system through promoter engineering or protein modification to enhance specificity and sensitivity.

What statistical approaches are recommended for analyzing YLR466C-A functional studies?

When analyzing data from YLR466C-A functional studies, researchers should employ a comprehensive statistical approach tailored to the experimental design. For comparing expression levels or phenotypic differences between wild-type and mutant strains, t-tests or ANOVA are appropriate, depending on the number of conditions being compared . Time-series data from growth assays should be analyzed using repeated measures ANOVA or mixed-effects models to account for temporal correlations. For transcriptomic studies, consider differential expression analysis tools specific to RNA-seq data, with appropriate correction for multiple testing (e.g., Benjamini-Hochberg procedure). When analyzing protein-protein interaction data, statistical methods for determining significance of interactions above background should be implemented, possibly including permutation tests to establish empirical p-values. For biosensor development utilizing YLR466C-A, dose-response curves should be fitted to determine sensitivity and dynamic range, with statistical comparison of parameters across different biosensor designs . In all analyses, appropriate sample sizes should be determined through power analysis to ensure statistical validity while minimizing experimental resources.

How should researchers interpret contradictory findings about YLR466C-A function?

When encountering contradictory findings about YLR466C-A function, researchers should implement a systematic approach to resolve discrepancies. First, critically evaluate experimental conditions across studies, as differences in media composition, temperature, or strain background can significantly impact results. Create a comprehensive table comparing methodological approaches, S. cerevisiae strains, and key findings to identify patterns in the contradictions. Consider that YLR466C-A may have context-dependent functions, possibly interacting with different partners under different conditions as suggested by its sequence similarity to multiple UPF0479 family proteins . Design validation experiments that specifically address contradictions by systematically varying critical parameters identified in the comparative analysis. Employ orthogonal experimental techniques to verify findings through independent methodologies. For instance, if protein localization studies show discrepancies, combine fluorescence microscopy with subcellular fractionation approaches. Assess whether post-translational modifications might explain functional differences by examining the protein under various cellular states. Collaborate with laboratories reporting contradictory results to conduct parallel experiments under standardized conditions. Finally, consider developing computational models that might reconcile apparently contradictory observations by identifying hidden variables or complex regulatory relationships.

What structural biology approaches can reveal insights about YLR466C-A function?

Elucidating the structure of YLR466C-A requires a multi-technique approach in structural biology. X-ray crystallography can provide high-resolution structures, though researchers must optimize crystallization conditions for this specific protein—the recombinant His-tagged version may facilitate crystal formation . For challenging crystallization, cryo-electron microscopy (cryo-EM) offers an alternative approach, particularly useful if YLR466C-A forms larger complexes with binding partners. NMR spectroscopy can provide insights into protein dynamics and identify binding interfaces with potential interaction partners. Researchers should note that the available recombinant protein with >90% purity is suitable for these structural studies . Computational approaches, including homology modeling based on similar UPF0479 family proteins and molecular dynamics simulations, can predict structure-function relationships. For membrane association analysis, suggested by the potential signal peptide cleavage site at position 56 , techniques like circular dichroism spectroscopy can characterize secondary structure elements that might interact with membranes. Integration of these structural insights with functional data will be crucial for developing a comprehensive understanding of YLR466C-A's biological role.

How can CRISPR-Cas9 technology be applied to study YLR466C-A in vivo?

CRISPR-Cas9 technology offers powerful approaches for studying YLR466C-A function in vivo. For gene knockout studies, design guide RNAs targeting the YLR466C-A coding sequence, followed by phenotypic characterization comparing growth rates, stress responses, and metabolic profiles between knockout and wild-type strains. For more subtle modifications, implement CRISPR-based base editing to introduce specific mutations that alter key amino acids identified through sequence conservation analysis among UPF0479 family proteins . To study protein dynamics and interactions, use CRISPR to generate endogenous fluorescent protein fusions by inserting tags at either the N- or C-terminus, considering the potential signal peptide cleavage site at position 56 . For temporal control of expression, combine CRISPR with inducible degradation systems like auxin-inducible degron technology. To assess potential genetic interactions, perform CRISPR screens targeting other genes in combination with YLR466C-A mutations. When designing these experiments in S. cerevisiae, take advantage of its efficient homologous recombination machinery to improve editing precision. Validate all CRISPR-generated modifications through sequencing to confirm the intended genetic alterations and rule out off-target effects.

What high-throughput approaches can be used to identify YLR466C-A interaction partners?

Identifying YLR466C-A interaction partners requires systematic high-throughput approaches. Affinity purification coupled with mass spectrometry (AP-MS) should be performed using the recombinant His-tagged YLR466C-A protein as bait . To distinguish between specific and non-specific interactions, include stringent controls and perform replicate experiments with varying wash stringency. Yeast two-hybrid (Y2H) screening can identify binary protein-protein interactions; construct a bait plasmid containing YLR466C-A and screen against a comprehensive S. cerevisiae genomic library. Proximity-labeling techniques like BioID or APEX2 can identify transient or weak interactions by fusing YLR466C-A to a promiscuous biotin ligase and identifying biotinylated proteins via streptavidin pull-down and mass spectrometry. For RNA interactions, if relevant, perform CLIP-seq (crosslinking immunoprecipitation followed by sequencing) using antibodies against the His-tagged YLR466C-A . Genetic interaction screening using synthetic genetic array (SGA) analysis can identify functional relationships by crossing YLR466C-A mutants with a deletion library. For in vitro validation of high-throughput hits, surface plasmon resonance or isothermal titration calorimetry can provide quantitative binding parameters. Finally, network analysis of the resulting interaction data can reveal functional clusters and place YLR466C-A within the broader cellular context.

What are the potential applications of YLR466C-A in biotechnology?

YLR466C-A has significant potential for biotechnological applications, building on S. cerevisiae's established role as an ideal chassis organism for synthetic biology . Researchers could engineer YLR466C-A as part of synthetic genetic circuits for sensing specific environmental conditions, similar to the biosensor development approaches used for 1-butanol detection . The protein might be incorporated into metabolic engineering strategies for producing high-value compounds, leveraging S. cerevisiae's proven capacity for producing substances ranging from pharmaceuticals to biofuels . Since S. cerevisiae has been successfully used to produce various biological drugs, including hepatitis B surface antigen, hirudin, insulin, and others , YLR466C-A could potentially be engineered as part of these production pathways to enhance yield or stability. The protein's potential membrane association, suggested by the signal peptide cleavage site , could be exploited for developing membrane-based biotechnological applications such as selective transport systems or environmental sensors. Given S. cerevisiae's biological safety credentials and mature high-density fermentation technology , any YLR466C-A-based applications would benefit from established industrial-scale production protocols.

How might systems biology approaches enhance our understanding of YLR466C-A?

Systems biology approaches offer comprehensive frameworks for understanding YLR466C-A's role within the broader cellular context. Researchers should integrate multi-omics data sets (genomics, transcriptomics, proteomics, and metabolomics) to place YLR466C-A within functional networks and identify emergent properties not apparent from isolated studies. Flux balance analysis can model how perturbations in YLR466C-A expression affect metabolic pathways, providing insights into its potential metabolic functions. The comparative systems approach should examine how YLR466C-A and its homologs in the UPF0479 family (e.g., YBL113W-A, YEL077W-A) function across different genetic backgrounds and environmental conditions . Mathematical modeling of gene regulatory networks incorporating YLR466C-A can predict its behavior under various conditions and generate testable hypotheses. For experimental validation, researchers should design systematic perturbation studies where multiple genes, including YLR466C-A, are manipulated simultaneously to reveal synergistic or antagonistic relationships. When analyzing data from these systems-level approaches, advanced computational methods like machine learning can identify non-obvious patterns and relationships. This integrated approach will provide a more complete understanding of YLR466C-A's functional significance than isolated molecular studies.