Recombinant Saccharomyces cerevisiae Putative uncharacterized protein YLR111W (YLR111W)

What is known about the structure and basic characteristics of YLR111W protein?

YLR111W is a putative uncharacterized protein in Saccharomyces cerevisiae with a full length of 110 amino acids. Recombinant versions are available with His-tags for purification purposes . As an uncharacterized protein (a "y-gene"), it belongs to a category of proteins whose functions have not yet been fully elucidated through traditional biochemical or genetic methods. The protein's relatively small size (110 amino acids) suggests it may function as part of a complex or as a regulatory element rather than as an enzyme with catalytic activity.

For basic characterization, researchers should consider:

• Expression analysis using PrimePCR™ Probe Assay available for YLR111W

• Structural prediction through homology modeling using tools like SWISS-MODEL

• Subcellular localization studies with fluorescent protein tagging

• Analysis of expression patterns under different growth conditions

What experimental approaches are recommended for initial characterization of uncharacterized proteins like YLR111W in yeast?

Initial characterization should follow a systematic workflow:

• Expression analysis: Determine if and when YLR111W is expressed using RNA-seq or qPCR with gene-specific primers. PrimePCR™ Probe Assay specifically designed for YLR111W can facilitate accurate quantification of expression levels .

• Phylogenetic profiling: Compare the presence/absence pattern of YLR111W across different species using computational methods to predict functional linkages. This approach is based on the premise that functionally linked proteins evolve in a correlated fashion—they tend to be either preserved or eliminated together during evolution .

• Subcellular localization: Create YLR111W-GFP fusion constructs to determine where the protein localizes, providing clues about its function.

• Gene deletion analysis: Generate a ΔyLR111w strain and assess phenotypic changes across various growth conditions. This can be accomplished using standard homologous recombination techniques in S. cerevisiae.

• Protein-protein interaction studies: Implement TAP-tagging (Tandem Affinity Purification) of YLR111W followed by mass spectrometry to identify potential interaction partners. When designing the TAP-tag experiment, consider using gentle lysis methods such as grinding deep-frozen cells at ultra-low temperatures to preserve protein-protein and protein-RNA interactions .

How does the gene deletion approach work for studying YLR111W function?

For systematic gene deletion of YLR111W:

• Design deletion cassette: Create a deletion cassette containing a selectable marker (typically HIS3, LEU2, TRP1, or a drug resistance gene) flanked by 40-60 bp sequences homologous to the regions upstream and downstream of YLR111W.

• Transformation: Transform the deletion cassette into S. cerevisiae using the lithium acetate method as described in multiple studies .

• Selection and verification: Select transformants on appropriate media and verify deletion by PCR using primers that anneal outside the targeted region.

• Phenotypic analysis: Systematically test the ΔyLR111w strain under various conditions including:

  • Different carbon sources (glucose, xylose, galactose)

  • Nitrogen limitation

  • Temperature stress (15°C, 30°C, 37°C)

  • Oxidative stress (H₂O₂ exposure)

  • Cell wall stress (Congo red, calcofluor white)

• Complementation test: Reintroduce YLR111W on a plasmid to confirm phenotypes are specifically due to its deletion.

For growth curve analysis, use automated plate readers to track growth at OD600 over 24-72 hours, comparing ΔyLR111w to wild-type strains under identical conditions.

How can transcriptional regulation of YLR111W be comprehensively assessed?

Investigating the transcriptional regulation of YLR111W requires a multi-faceted approach:

• Promoter analysis: Identify putative transcription factor binding sites in the promoter region of YLR111W using bioinformatic tools like MEME software suite (E-value < 1e-3) .

• ChIP-exo analysis: To identify transcription factors that bind the YLR111W promoter, perform ChIP-exo experiments as described by unraveling uncharacterized transcription factors .

• Reporter gene assays: Create reporter constructs where the YLR111W promoter drives expression of a fluorescent protein or luciferase. Test regulation under different conditions.

• Differential expression analysis: Using RNA-seq data, calculate:

  • Fold change (log₂(fold-change) ≥ log₂(2.0))

  • Statistical significance (adjusted P-value < 0.05)

For RNA-seq analysis, follow these steps :

• Map reads using bowtie v1.2.3 with maximum insert size of 1000 bp

• Quantify transcript abundance using summarizeOverlaps from R GenomicAlignments package

• Calculate dispersion and differential expression using DESeq2

• Calculate Transcripts Per Million (TPM) for relative expression levels

What approaches can be used to investigate potential involvement of YLR111W in carbon metabolism pathways?

Since several uncharacterized yeast proteins have been found to play roles in carbon metabolism, YLR111W might be involved in these pathways. To investigate:

• Comparative growth analysis: Compare growth of wild-type and ΔyLR111w strains in media with different carbon sources (glucose, xylose, ethanol). For xylose utilization studies, use YPX40 medium (4 g/L yeast extract, 3 g/L peptone, 40 g/L xylose) .

• Metabolic flux analysis: Use 13C-labeled carbon sources and track metabolite distribution using mass spectrometry to detect alterations in carbon flux.

• Expression profiling during carbon source shifts: Monitor YLR111W expression when shifting between glucose and alternative carbon sources.

• Genetic interaction studies: Create double deletions with known carbon metabolism genes (e.g., NGG1, ADR1, CAT8). NGG1 has been shown to be a global regulator for carbon metabolism in S. cerevisiae, and manipulation of transcription factors like CAT8 or ADR1 generates significant changes in carbon metabolism behavior .

• Recombinant expression analysis: Express YLR111W in a heterologous system or overexpress it in S. cerevisiae to assess effects on carbon metabolism.

How can potential protein-protein interactions of YLR111W be identified and validated?

For comprehensive protein interaction mapping:

• TAP-tagging approach:

  • Generate a TAP-tagged YLR111W strain by transforming PCR products using the lithium acetate method

  • For PCR, use primers with appropriate homology to the C-terminus of YLR111W and the TAP-tag sequence

  • Perform cell lysis using grinding of deep-frozen cells at ultra-low temperature to preserve complex integrity

  • Purify protein complexes using the TAP protocol

  • Identify interacting partners by mass spectrometry

• Yeast two-hybrid screening:

  • Create bait constructs with YLR111W fused to a DNA-binding domain

  • Screen against prey libraries containing activation domain fusions

  • Validate positive interactions with secondary assays

• Co-immunoprecipitation validation:

  • Express epitope-tagged versions of YLR111W and candidate interactors

  • Perform co-immunoprecipitation experiments

  • Analyze by Western blotting

• Proximity-dependent biotin labeling:

  • Create a YLR111W-BirA fusion protein

  • Identify proteins in close proximity through biotinylation

  • Analyze by streptavidin pulldown and mass spectrometry

• Structural validation:

  • For confirmed interactions, use homology modeling with SWISS-MODEL pipeline to predict structural interfaces

  • Analyze interface conservation scores to existing complexes of similar sequence identity

What bioinformatic approaches can predict the function of YLR111W?

Several computational approaches can be employed to predict YLR111W function:

• Phylogenetic profiling: Create a binary string representing presence (1) or absence (0) of YLR111W homologs across multiple genomes. Proteins with similar phylogenetic profiles often have related functions. On average, 18% of neighbor keywords overlap with known keywords of query proteins (compared to 4% for random proteins) .

• Protein domain analysis: Scan YLR111W sequence for conserved domains using tools like Pfam, SMART, or InterPro.

• Structure prediction: Use AlphaFold2 or SWISS-MODEL to predict tertiary structure, which may provide clues about function.

• Gene neighborhood analysis: Examine the genomic context of YLR111W, as functionally related genes are often clustered.

• Functional enrichment of interacting partners: If protein interaction data is available, perform COG (clusters of orthologous groups) functional enrichment analysis of interacting partners using hypergeometric tests (P-value < 0.01 considered significant) .

• Expression correlation analysis: Identify genes whose expression patterns correlate with YLR111W across different conditions, suggesting functional relationships.

What are optimal methods for recombinant expression and purification of YLR111W?

For effective recombinant expression and purification:

• Expression system selection:

  • E. coli: BL21(DE3) strain with pET-based vectors is suitable for YLR111W expression with a His-tag

  • S. cerevisiae: Consider using pVSec plasmid systems with α-factor secretion signal if native conformation is critical

• Construct design for bacterial expression:

  • Clone YLR111W with an N- or C-terminal His-tag for purification

  • Optimize codon usage for E. coli

  • Include a TEV protease cleavage site for tag removal

• Expression conditions optimization:

  • Test various induction temperatures (16°C, 25°C, 37°C)

  • Vary IPTG concentrations (0.1 mM to 1 mM)

  • Test expression duration (3h to overnight)

• Purification protocol:

  • Lyse cells using sonication or French press

  • Perform IMAC (Immobilized Metal Affinity Chromatography) with Ni-NTA resin

  • Include size exclusion chromatography as a polishing step

• Quality control:

  • Verify purity by SDS-PAGE

  • Confirm identity by mass spectrometry

  • Assess folding by circular dichroism

For yeast-based expression, consider the strain EBY100 [MATa AGA1::GAL1-AGA1::URA3 ura3–52 trp1 leu2-delta200 his3-delta200 pep4::HIS3 prb11.6R can1 GAL], which has been successfully used for expressing and secreting heterologous proteins .

How can RNA-associated functions of YLR111W be investigated?

To explore potential RNA-binding capabilities:

• RNA immunoprecipitation (RIP):

  • Express epitope-tagged YLR111W

  • Perform immunoprecipitation under conditions that preserve RNA-protein interactions

  • Extract and identify associated RNAs by RT-PCR or RNA-seq

  • Use deep-frozen cell grinding at ultra-low temperatures to preserve RNA integrity during lysis

• Electrophoretic Mobility Shift Assay (EMSA):

  • Express and purify recombinant YLR111W

  • Incubate with labeled RNA probes

  • Assess binding by gel electrophoresis

• RNA recognition motif (RRM) analysis:

  • Conduct computational analysis to identify potential RNA-binding domains

  • If YLR111W contains an RRM similar to Nrp1p (which contains one RRM), design experiments accordingly

• CLIP-seq (Cross-linking immunoprecipitation):

  • Cross-link RNA-protein interactions in vivo

  • Immunoprecipitate YLR111W

  • Sequence associated RNAs

  • Map binding sites at nucleotide resolution

• Functional validation:

  • Mutate predicted RNA-binding residues

  • Assess effects on RNA binding and cellular phenotypes

  • Evaluate impact on RNA stability or processing

What are the best approaches for investigating the potential role of YLR111W in stress response?

To investigate stress response connections:

• Stress exposure experiments:

  • Subject wild-type and ΔyLR111w strains to various stressors:

    • Heat shock (37°C, 42°C)

    • Oxidative stress (H₂O₂, menadione)

    • Osmotic stress (NaCl, sorbitol)

    • Nutrient limitation

    • UV radiation exposure (follow protocols similar to those using UV-B transilluminator or Stratalinker as described in )

• Quantitative fitness analysis (QFA):

  • Perform systematic growth measurements under different stress conditions

  • Compare colony size and growth rate between wild-type and ΔyLR111w strains

  • Create searchable data tables of key numerical summaries using tools like DT

• Transcriptional response analysis:

  • Use RNA-seq to compare transcriptional responses to stress between wild-type and ΔyLR111w strains

  • Apply differential expression analysis using DESeq2

  • Consider significant those genes with log₂(fold-change) ≥ log₂(2.0) and adjusted P-value < 0.05

• Stress resistance phenotyping:

  • For UV sensitivity, expose plated cells to UV radiation for different time intervals (0, 5, 10, 15, 20, 30 seconds)

  • Calculate survival percentages based on colony counts

  • Compare survival curves between wild-type and mutant strains

• Epigenetic regulation:

  • Investigate if YLR111W interacts with chromatin modifiers like the SAGA complex (which contains NGG1)

  • Perform ChIP-seq to identify potential binding sites

What are the main challenges in functional characterization of uncharacterized proteins like YLR111W?

Researchers face several key challenges when studying uncharacterized proteins:

• Phenotypic subtlety:

  • Deletion mutants often show no obvious phenotype under standard laboratory conditions

  • Solution: Implement systematic phenotyping under diverse conditions including alternative carbon sources, nitrogen limitation, and various stressors

• Functional redundancy:

  • Paralogous proteins may compensate for YLR111W deletion

  • Solution: Create double or triple mutants by combining ΔyLR111w with deletions of genes encoding similar proteins

• Condition-specific expression:

  • YLR111W might function only under specific conditions not routinely tested

  • Solution: Perform global expression profiling across diverse conditions to identify when YLR111W is expressed

• Protein complex dependency:

  • Function may depend on incorporation into larger complexes

  • Solution: Use gentle lysis methods such as grinding deep-frozen cells at ultra-low temperature to preserve complex integrity

• Technical limitations in detection:

  • Low abundance proteins are difficult to detect in standard proteomics experiments

  • Solution: Use targeted proteomics approaches or overexpression systems to enhance detection

How can conflicting experimental results regarding YLR111W function be reconciled?

When faced with contradictory experimental results:

What considerations should be made when designing CRISPR-Cas9 experiments for YLR111W modification?

For effective CRISPR-Cas9 modification:

• Guide RNA design:

  • Select target sites with minimal off-target effects

  • Ensure guide RNAs have high on-target efficiency

  • Design multiple guides targeting different regions of YLR111W

  • Test guide RNA efficiency in preliminary experiments

• Repair template design:

  • For knockouts: Design repair templates with ~50 bp homology arms flanking the deletion

  • For tagging: Include flexible linkers between YLR111W and the tag

  • For point mutations: Keep mutation site central within the repair template

• Delivery method optimization:

  • Transform assembled Cas9-gRNA ribonucleoprotein complexes directly

  • Alternatively, express Cas9 from a plasmid with galactose-inducible promoter

• Verification strategies:

  • Screen transformants by PCR, Sanger sequencing, and phenotypic analysis

  • Verify absence of off-target modifications by whole-genome sequencing

  • Confirm expression/localization of tagged variants by Western blot/microscopy

• Controls and safeguards:

  • Include wild-type controls in all experiments

  • Design reversion strategies to confirm phenotype causality

  • Consider using nickase variants to reduce off-target effects