Recombinant Saccharomyces cerevisiae Uncharacterized protein YDR182W-A (YDR182W-A)

What is YDR182W-A and what are its fundamental properties?

YDR182W-A is an uncharacterized protein from the budding yeast Saccharomyces cerevisiae with a full length of 67 amino acids. The complete amino acid sequence is MNKRYKLYRVWYYYAHQTVCITSTGFALCFVVQAKTAGLGVTPITSLYGDKKEHLGKLLVPLVLYQI . As an uncharacterized protein, its specific biological function remains to be elucidated, creating opportunities for novel research directions. The protein can be recombinantly expressed with an N-terminal His-tag in E. coli expression systems, facilitating purification and subsequent functional studies .

Current structural analyses suggest the protein may contain functional domains that could provide insights into its role in yeast cellular processes. Researchers should approach this protein as a potential component in unidentified pathways, particularly considering the location of its encoding gene within the S. cerevisiae genome and potential regulatory elements surrounding it.

What bioinformatic approaches can predict potential functions of YDR182W-A?

To predict potential functions of this uncharacterized protein, researchers should implement a multi-layered bioinformatic approach:

• Sequence-based analysis: Begin with BLAST and PSI-BLAST searches against protein databases to identify distant homologs. Follow with multiple sequence alignment to identify conserved residues that might indicate functional importance.

• Structural prediction: Employ tools like AlphaFold, I-TASSER, or Phyre2 to predict tertiary structure, which may reveal structural similarities to proteins of known function despite low sequence identity.

• Domain prediction: Use InterProScan, SMART, and Pfam to identify potential functional domains, motifs, or signatures.

• Evolutionary analysis: Perform phylogenetic analysis to understand evolutionary relationships and potential functional conservation across species.

• Co-expression network analysis: Analyze gene expression datasets to identify genes co-expressed with YDR182W-A, which may suggest functional relationships.

• Protein-protein interaction prediction: Use tools like STRING database to predict potential interacting partners based on various evidence types .

The lack of characterized pathways involving YDR182W-A in the current literature necessitates these comprehensive approaches to generate testable hypotheses about its function .

What expression systems are optimal for recombinant YDR182W-A production?

Based on available data, E. coli has been successfully used as an expression system for recombinant YDR182W-A production . The methodology typically involves:

• Construct design: The gene encoding YDR182W-A should be codon-optimized for E. coli expression and cloned into an appropriate expression vector containing an N-terminal His-tag for purification purposes.

• Expression conditions: Optimal conditions often include:

  • E. coli strain selection (BL21(DE3), Rosetta, or Arctic Express for potentially challenging proteins)

  • Induction with IPTG at concentrations between 0.1-1.0 mM

  • Expression at lower temperatures (16-25°C) to enhance proper folding

  • Extended expression time (16-24 hours) for maximum yield

• Alternative systems: If E. coli yields improperly folded protein, consider:

  • Yeast expression systems (particularly S. cerevisiae or Pichia pastoris) which may provide more native folding conditions

  • Cell-free expression systems for rapid screening of conditions

  • Mammalian cell expression for complex folding requirements

The Creative BioMart products utilize E. coli as the expression host with high purity (>90% as determined by SDS-PAGE) , suggesting this is a viable approach for research quantities.

What purification strategies maximize yield and activity of recombinant YDR182W-A?

Efficient purification of His-tagged YDR182W-A requires a methodical approach:

• Cell lysis optimization:

  • Buffer composition (typically phosphate or Tris-based buffers, pH 7.5-8.0)

  • Inclusion of appropriate protease inhibitors

  • Mild detergents if the protein has hydrophobic regions

  • Sonication or high-pressure homogenization parameters

• Immobilized metal affinity chromatography (IMAC):

  • Ni-NTA or Co-based resins for His-tag binding

  • Optimization of imidazole concentration in wash buffers (10-40 mM) to reduce non-specific binding

  • Gradient or step elution protocols with increasing imidazole (100-500 mM)

• Secondary purification:

  • Size exclusion chromatography to remove aggregates and ensure monodispersity

  • Ion exchange chromatography if charge-based separation would improve purity

• Quality control:

  • SDS-PAGE analysis with Coomassie or silver staining

  • Western blot with anti-His antibodies

  • Mass spectrometry for identity confirmation

Storage recommendations indicate avoiding repeated freeze-thaw cycles, with working aliquots stored at 4°C for up to one week . Long-term storage should be at -20°C in a stabilizing buffer containing glycerol or other cryoprotectants.

How can researchers investigate potential protein-protein interactions of YDR182W-A?

To identify protein-protein interactions involving YDR182W-A, researchers should employ a combination of complementary techniques:

• Affinity purification coupled with mass spectrometry (AP-MS):

  • Express tagged YDR182W-A in S. cerevisiae

  • Pull-down experiments using the His-tag

  • Identify co-precipitated proteins by mass spectrometry

  • Validate with reciprocal tagging of candidate interactors

• Yeast two-hybrid (Y2H) screening:

  • This technique is especially relevant as it was mentioned in the context of identifying protein interactions in the third search result

  • Use YDR182W-A as both bait and prey in comprehensive screens

  • Validate positive interactions with co-immunoprecipitation

• Proximity-based labeling:

  • BioID or APEX2 fusion proteins to identify proximal proteins in vivo

  • Particularly useful for transient or weak interactions

• Synthetic genetic array (SGA) analysis:

  • Identify genetic interactions that may indicate functional relationships

  • This approach was indirectly referenced in the discussion of synthetic dosage lethality (SDL) methods in search result 3

• Cross-linking mass spectrometry (XL-MS):

  • Chemical cross-linking to capture direct protein-protein contacts

  • Structural insights into interaction interfaces

• Surface plasmon resonance (SPR) or bio-layer interferometry (BLI):

  • For quantitative binding kinetics of candidate interactions

The TORC2-Ypk1 signaling pathway analysis described in search result 3 provides a methodological template for how such interaction studies might be structured, even though it does not directly mention YDR182W-A .

What approaches can determine the subcellular localization of YDR182W-A?

Determining the subcellular localization of YDR182W-A is crucial for understanding its function. Researchers should consider these methodological approaches:

• Fluorescent protein tagging:

  • C-terminal or N-terminal GFP/mCherry fusion constructs

  • Expression from native promoter to maintain physiological levels

  • Live-cell imaging under various growth conditions

  • Co-localization with known organelle markers

• Immunofluorescence microscopy:

  • Generation of specific antibodies against YDR182W-A

  • Fixation and permeabilization optimization for yeast cells

  • Double labeling with organelle markers

• Biochemical fractionation:

  • Differential centrifugation to separate cellular compartments

  • Western blot analysis of fractions using anti-His antibodies

  • Comparison with known compartment markers

• Proximity-dependent biotinylation:

  • BioID or APEX2 fusion for in vivo proximity labeling

  • Identification of biotinylated proteins to infer localization

• Computational prediction:

  • Analysis of protein sequence for localization signals

  • Tools like PSORT, TargetP, and DeepLoc for prediction

• Electron microscopy:

  • Immunogold labeling for high-resolution localization

  • Correlative light and electron microscopy for functional context

The knowledge that YDR182W-A can be expressed as a recombinant protein with a His-tag suggests that epitope tagging approaches are feasible and likely to yield meaningful results.

How might YDR182W-A relate to known metabolic pathways in S. cerevisiae?

While YDR182W-A's function remains uncharacterized, researchers can investigate its potential involvement in yeast metabolic pathways through systematic approaches:

• Transcriptional co-regulation analysis:

  • Examine expression profiles under various conditions

  • Identify co-regulated genes with known pathway associations

  • Analyze promoter regions for common regulatory elements

• Metabolomic profiling:

  • Compare metabolite profiles between wild-type and YDR182W-A deletion/overexpression strains

  • Focus on changes in key metabolic intermediates

  • Use stable isotope labeling to track metabolic flux

• Integration with existing pathway models:

  • Sphingolipid metabolism pathways may be relevant as the search results mention ceramide synthase regulation

  • Carotenoid biosynthesis pathways as mentioned in search result 2 could provide a methodological framework

• Growth phenotype analysis:

  • Systematic testing of growth under various carbon sources, stress conditions

  • Chemical genomics approaches with inhibitors of known pathways

• Flux balance analysis:

  • Incorporate YDR182W-A into genome-scale metabolic models

  • Predict metabolic consequences of altering YDR182W-A activity

  • Similar to the approach mentioned in the β-carotene/β-ionone study

The systematic assessment of variables that was used in engineering S. cerevisiae for β-ionone production represents a methodological template that could be adapted to study YDR182W-A's potential metabolic functions.

What genetic approaches can reveal the function of YDR182W-A?

Comprehensive genetic analysis can provide significant insights into YDR182W-A function:

• Gene deletion and overexpression studies:

  • Creation of YDR182W-A knockout strains

  • Controlled overexpression using inducible promoters

  • Phenotypic characterization under various conditions

• Synthetic genetic array analysis:

  • Systematic creation of double mutants

  • Identification of genetic interactions (synthetic lethality/sickness)

  • The synthetic dosage lethality (SDL) method described in the third search result provides a relevant methodological framework

• CRISPR-Cas9 genome editing:

  • Precise modification of YDR182W-A sequence

  • Introduction of point mutations at predicted functional sites

  • Similar to the markerless genome editing approach mentioned in the β-carotene study

• Suppressor screens:

  • Identify mutations that suppress phenotypes of YDR182W-A deletion/overexpression

  • Second-site suppressors can reveal pathway connections

• Transcriptional response analysis:

  • RNA-seq to identify genes affected by YDR182W-A manipulation

  • ChIP-seq if YDR182W-A has potential DNA-binding domains

• Protein domain analysis:

  • Construction of chimeric proteins

  • Deletion of specific protein regions to identify functional domains

The chemical genetic approach described in search result 3, which scores deleterious effects from overexpression when a kinase of interest is inhibited , could be particularly valuable for investigating YDR182W-A's potential involvement in signaling pathways.

What structural biology techniques would be most appropriate for determining YDR182W-A's three-dimensional structure?

Determining the structure of a small, uncharacterized protein like YDR182W-A (67 amino acids) requires careful selection of appropriate techniques:

Given YDR182W-A's small size, NMR spectroscopy would likely be the most appropriate experimental technique, providing both structural information and insights into potential conformational dynamics.

How can researchers address challenges in functional annotation of uncharacterized proteins like YDR182W-A?

Functional annotation of uncharacterized proteins presents significant challenges that require integrated approaches:

• Multi-omics integration:

  • Combine transcriptomics, proteomics, metabolomics, and phenomics data

  • Network-based approaches to predict function through guilt by association

  • Machine learning algorithms to identify patterns across multiple data types

• Activity-based protein profiling:

  • Chemical probes to detect specific enzymatic activities

  • Metabolite affinity purification to identify binding partners

  • Systematic screening against metabolite libraries

• Comparative genomics across yeast species:

  • Analysis of YDR182W-A orthologs in other fungi

  • Investigation of gene neighborhood conservation

  • Identification of correlated gene loss/gain patterns

• High-throughput phenotyping:

  • Automated microscopy to detect subtle morphological changes

  • Growth measurements under thousands of conditions

  • Chemogenomic profiling with diverse chemical libraries

• CRISPR-based functional genomics:

  • Genome-wide screens to identify genetic interactions

  • CRISPRi/CRISPRa for modulating expression levels

  • Domain-focused mutagenesis to map functional regions

• Systems biology modeling:

  • Integration of YDR182W-A into existing models of yeast metabolism or signaling

  • Flux balance analysis to predict metabolic roles

  • Similar to the contextualized genome-scale metabolic model approach mentioned in the β-ionone production study

The systematic, multi-tiered approach described in search result 3 for identifying kinase substrates demonstrates how combining chemical genetics, bioinformatics, and biochemical validation can successfully annotate previously unknown functions .

What are the key considerations for designing gene expression studies to investigate YDR182W-A regulation?

Investigating the regulation of YDR182W-A expression requires careful experimental design:

• Promoter analysis:

  • Bioinformatic identification of potential regulatory elements

  • Reporter gene assays with serial promoter deletions

  • ChIP studies to identify transcription factor binding

  • Consider approaches similar to those used for optimizing transcriptional unit architecture in the β-carotene study

• Transcriptional analysis:

  • qRT-PCR for targeted quantification under various conditions

  • RNA-seq for genome-wide expression context

  • Single-cell RNA-seq to detect population heterogeneity

  • CAGE-seq or similar techniques to precisely map transcription start sites

• Translation regulation:

  • Ribosome profiling to assess translational efficiency

  • Analysis of 5' and 3' UTR sequences for regulatory elements

  • Investigation of potential upstream open reading frames (uORFs)

• Epigenetic regulation:

  • ChIP-seq for histone modifications near the YDR182W-A locus

  • DNA methylation analysis if relevant to the study system

  • Chromatin accessibility assays (ATAC-seq, DNase-seq)

• Environmental response profiling:

  • Systematic analysis of YDR182W-A expression under:

    • Different carbon sources

    • Stress conditions (oxidative, osmotic, temperature)

    • Growth phases

    • Nutrient limitations

• Integration with signaling pathways:

  • Investigation of potential regulation by TORC2-Ypk1 or other signaling pathways

  • Kinase inhibitor studies to identify regulatory connections

  • Phosphoproteomic analysis to detect post-translational modifications

The approach used in the β-carotene and β-ionone production study, which systematically optimized gene expression through careful manipulation of transcriptional unit architecture, integration sites, and gene dosage , provides a methodological framework that could be adapted for studying YDR182W-A regulation.