Recombinant Saccharomyces cerevisiae Putative uncharacterized protein YLR339C (YLR339C)

What expression systems are most effective for producing recombinant YLR339C?

Multiple expression systems have been successfully employed for producing recombinant YLR339C, each with distinct advantages:

For structural studies requiring substantial protein amounts, E. coli expression is commonly used, achieving purity levels of ≥85% as determined by SDS-PAGE . For functional studies where post-translational modifications may be critical, yeast or mammalian expression systems are preferable. Cell-free expression systems have also been employed for rapid production of YLR339C when studying protein-protein interactions .

What are the optimal storage and handling conditions for recombinant YLR339C?

For optimal stability and activity preservation of recombinant YLR339C, the following protocol is recommended:

• Short-term storage (up to one week): Store working aliquots at 4°C

• Medium-term storage (up to 6 months): Store in liquid form at -20°C

• Long-term storage (up to 12 months): Store in lyophilized form at -20°C/-80°C

Buffer composition significantly impacts stability. The recommended storage buffer contains Tris-based buffer with 50% glycerol, optimized specifically for this protein . It is critical to avoid repeated freeze-thaw cycles as these can lead to protein degradation and aggregation. For reconstitution of lyophilized protein, use deionized sterile water to a concentration of 0.1-1.0 mg/mL, followed by addition of glycerol to a final concentration of 50% .

What methodological approaches are most effective for verifying the purity and integrity of recombinant YLR339C?

Comprehensive quality assessment of recombinant YLR339C should employ multiple complementary techniques:

• SDS-PAGE analysis: The primary method for purity assessment, with commercial preparations typically showing ≥85% purity . Run both reducing and non-reducing conditions to evaluate disulfide bond formation.

• Western blotting: Utilize anti-YLR339C polyclonal antibodies for specific detection . This is particularly important when working with low concentration samples or complex mixtures.

• Mass spectrometry:

  • Intact mass analysis to confirm the expected molecular weight (approximately 20 kDa)

  • Peptide mapping after tryptic digestion to verify sequence coverage

  • Analysis of potential post-translational modifications

• Size exclusion chromatography: To assess aggregation state and homogeneity

• Dynamic light scattering: For evaluation of size distribution and potential aggregation

This multi-method approach allows researchers to comprehensively evaluate both the purity and structural integrity of the recombinant protein before proceeding with functional studies.

What experimental strategies can be employed to characterize the function of the uncharacterized YLR339C protein?

Elucidating the function of YLR339C requires a systematic, multi-faceted approach:

• Computational prediction:

  • Sequence homology analysis with characterized proteins

  • Structural prediction using algorithms like AlphaFold2

  • Identification of conserved domains and motifs

• Gene knockout/knockdown studies:

  • Generate YLR339C deletion strains using CRISPR-Cas9 or traditional homologous recombination

  • Assess phenotypic changes under various growth conditions

  • Utilize the available S. cerevisiae single gene deletion collection (EUROSCARF)

• Protein-protein interaction studies:

  • Yeast two-hybrid screening

  • Co-immunoprecipitation with anti-YLR339C antibodies

  • Proximity-dependent biotin labeling (BioID)

• Transcriptomic/proteomic profiling:

  • RNA-Seq analysis comparing wild-type and YLR339C deletion strains

  • Quantitative proteomics to identify differentially expressed proteins

  • Phosphoproteomics to identify potential signaling pathways

• Subcellular localization:

  • Fluorescence microscopy using YLR339C-GFP fusion proteins

  • Subcellular fractionation followed by Western blotting

This integrated approach allows researchers to generate hypotheses about YLR339C function that can then be tested with targeted biochemical assays.

How does S. cerevisiae strain selection impact recombinant YLR339C expression and downstream applications?

Strain selection critically influences recombinant protein expression outcomes:

The choice of strain significantly impacts recombinant protein yield, with the respiratory TM6* strain demonstrating improved volumetric yields compared to standard fermentative strains . Additionally, maximum recombinant protein yields are typically highest before cells reach the diauxic shift from the respiro-fermentative to the respiratory phase .

For YLR339C specifically, consider that strain-specific differences in protein glycosylation may alter protein function if YLR339C is indeed subject to post-translational modifications. Laboratory strains with well-characterized genetics facilitate subsequent functional studies, while industrial strains may offer advantages in protein yield and stability .

What are the optimal experimental designs for investigating protein-protein interactions involving YLR339C?

Investigating protein-protein interactions for an uncharacterized protein like YLR339C requires a strategic experimental approach:

• Primary interaction screening:

  • Yeast two-hybrid (Y2H): Create a bait construct with YLR339C fused to a DNA-binding domain and screen against a prey library of S. cerevisiae proteins

  • Affinity purification-mass spectrometry (AP-MS): Express tagged YLR339C (His-tag recommended based on available constructs ), perform pull-down, and identify binding partners by mass spectrometry

• Validation of candidate interactions:

  • Bimolecular Fluorescence Complementation (BiFC): Split fluorescent protein fragments are fused to YLR339C and candidate interactor

  • Förster Resonance Energy Transfer (FRET): Measures energy transfer between fluorescently labeled proteins in close proximity

  • Co-immunoprecipitation: Use anti-YLR339C antibodies to pull down protein complexes from cell lysates

• Interaction dynamics:

  • Surface Plasmon Resonance (SPR): For quantitative binding kinetics using purified recombinant YLR339C

  • Isothermal Titration Calorimetry (ITC): For thermodynamic parameters of binding

  • Hydrogen-Deuterium Exchange Mass Spectrometry (HDX-MS): To map interaction interfaces

• Functional validation:

  • Co-expression/co-deletion studies: Examine phenotypic consequences when both YLR339C and interacting partner are manipulated

  • Protein localization: Determine if interacting proteins co-localize in the same subcellular compartment

When designing these experiments, consider using the TM6* S. cerevisiae strain for improved protein expression , and incorporate appropriate controls to distinguish specific from non-specific interactions.

How can deep research computational approaches be applied to predict the function of YLR339C?

Advanced computational methods can generate testable hypotheses about YLR339C function:

• Sequence-based function prediction:

  • Hidden Markov Models (HMMs): Identify distant homologs not detectable by standard BLAST

  • Conserved domain analysis: Identify functional motifs using CDD, PFAM, and InterPro databases

  • Evolutionary analysis: Examine conservation patterns across fungal species to identify functionally important residues

• Structure-based function prediction:

  • AlphaFold2/RoseTTAFold: Generate high-confidence structural models

  • Structural comparison: Compare predicted structure against known protein structures using DALI or PDBeFold

  • Binding site prediction: Identify potential ligand binding pockets using tools like SiteMap or FTMap

• Network-based approaches:

  • Protein-protein interaction networks: Analyze placement of YLR339C in known interaction networks

  • Gene co-expression analysis: Identify genes with similar expression patterns across conditions

  • Genetic interaction profiles: Compare synthetic lethal/sick interactions with those of characterized genes

• Integration with experimental data:

  • Utilizing ChatGPT's deep research capabilities: As demonstrated in search result1, AI-assisted research tools can accelerate literature review and hypothesis generation

  • Meta-analysis of proteomics data: Examine existing datasets for YLR339C expression patterns under various conditions

These computational approaches could significantly reduce experimental time by narrowing the functional hypothesis space before laboratory validation1.

What methodological considerations are critical when designing CRISPR-Cas9 experiments to study YLR339C function?

When designing CRISPR-Cas9 experiments to study YLR339C, several critical methodological considerations must be addressed:

• Guide RNA design:

  • Design multiple sgRNAs targeting different regions of YLR339C to account for variable editing efficiency

  • Verify specificity using yeast genome databases to minimize off-target effects

  • Consider the GC content (40-60% optimal) and secondary structure prediction for efficient Cas9 recruitment

• Repair template design:

  • For gene knockout: Design homology arms (40-60bp) flanking the cut site

  • For tagging: Ensure in-frame fusion with reporter genes like GFP or epitope tags

  • For point mutations: Include silent mutations in the PAM sequence to prevent re-cutting

• Delivery method optimization:

  • Transformation efficiency varies between S. cerevisiae strains; optimize protocols accordingly

  • Consider using a single plasmid containing both Cas9 and sgRNA for improved efficiency

  • For industrial strains, electroporation may yield better results than chemical transformation

• Phenotypic validation strategies:

  • Growth characterization under various environmental conditions, particularly focusing on:

    • Temperature stress (heat/cold shock)

    • Nutrient limitation

    • Cell wall/membrane stressors

  • Analyze metabolic profiles using techniques like metabolomics or Phenotype MicroArrays

  • Transcriptome profiling to identify compensatory responses

• Controls and verification:

  • Include wild-type and empty vector controls

  • Verify editing by sequencing and protein expression analysis

  • Perform complementation with wild-type YLR339C to confirm phenotype specificity

This systematic approach will help generate reliable data on YLR339C function while minimizing experimental artifacts and misinterpretation.

What strategies can be employed to investigate potential post-translational modifications of YLR339C?

Investigating post-translational modifications (PTMs) of YLR339C requires a comprehensive analytical approach:

• Prediction and prioritization:

  • In silico prediction: Use algorithms like NetPhos, NetOGlyc, NetNGlyc, and SUMOplot to predict potential modification sites

  • Conservation analysis: Examine if predicted PTM sites are conserved across related yeast species, suggesting functional importance

• Mass spectrometry-based identification:

  • Sample preparation considerations:

    • Express recombinant YLR339C in both prokaryotic (E. coli) and eukaryotic systems (preferably S. cerevisiae)

    • Compare PTM profiles to identify yeast-specific modifications

    • Use phosphatase/glycosidase inhibitors during purification to preserve labile modifications

  • MS analysis approaches:

    • Employ both bottom-up (peptide) and top-down (intact protein) proteomics

    • Use electron transfer dissociation (ETD) for improved PTM site localization

    • Consider enrichment strategies for specific PTMs (TiO₂ for phosphopeptides, lectin affinity for glycopeptides)

• Site-directed mutagenesis validation:

  • Generate mutants at predicted PTM sites (e.g., S/T→A for phosphorylation, K→R for ubiquitination)

  • Compare phenotypes of wild-type and mutant YLR339C

  • Assess protein stability, localization, and interaction profiles of mutants

• PTM-specific antibodies:

  • Develop modification-specific antibodies if key PTMs are identified

  • Use for western blotting and immunoprecipitation to study dynamics of modifications

• Glycosylation analysis:

  • S. cerevisiae is known to hyperglycosylate N-linked sites, potentially affecting protein function

  • Compare YLR339C expressed in S. cerevisiae with that expressed in P. pastoris, which produces shorter oligosaccharide chains

These methodologies will help determine if PTMs are critical for YLR339C function and may provide insights into regulatory mechanisms governing this uncharacterized protein.