Recombinant Saccharomyces cerevisiae Uncharacterized protein YHR213W-A (YHR213W-A)

What is known about the basic structure and properties of YHR213W-A?

YHR213W-A is a small protein consisting of 77 amino acids in length, classified as an uncharacterized or putative protein with unknown function in Saccharomyces cerevisiae S288C . The protein has been identified through multiple genomic analysis techniques including gene-trapping, microarray-based expression analysis, and genome-wide homology searching . The protein's small size suggests it might function as a regulatory peptide or as part of a larger protein complex rather than possessing enzymatic activity independently.

For recombinant expression studies, YHR213W-A is available as a His-tagged construct expressed in E. coli expression systems . This recombinant version maintains the full-length sequence (1-77 amino acids) and has been used in preliminary biochemical characterization studies. The histidine tag facilitates purification through metal affinity chromatography, enabling researchers to obtain pure protein for further functional and structural studies.

How was YHR213W-A identified and what genomic information is available?

YHR213W-A was identified through comprehensive genomic analysis of the Saccharomyces cerevisiae genome, specifically as part of the genome-wide efforts following the complete sequencing of yeast in 1996 . The gene encoding this protein is located on chromosome VIII of S. cerevisiae, and has been assigned the Entrez Gene ID 1466533 .

The identification methodology involved:

• Gene-trapping techniques that inserted reporter constructs randomly into the genome

• Microarray-based expression analysis to detect transcriptionally active regions

• Genome-wide homology searching using computational approaches

The protein was annotated after the pioneering "Life with 6000 genes" project that completely sequenced the S. cerevisiae genome . The YHR prefix in its systematic name indicates its position on chromosome VIII, with "Y" representing yeast, "H" designating the chromosome, "R" indicating the right arm of the chromosome, and "213W" specifying its sequential position.

What expression patterns have been documented for YHR213W-A?

According to the Saccharomyces Genome Database (SGD), there is currently no comprehensive expression data available specifically for YHR213W-A . This indicates that either the expression levels of this gene are below detection thresholds in standard conditions tested, or that it might be expressed only under specific environmental conditions that have not been thoroughly investigated.

The lack of expression data in standard conditions suggests several research possibilities:

• The protein may be expressed only under specific stress conditions

• Expression might be limited to particular developmental stages or growth phases

• The gene might be expressed at very low levels requiring more sensitive detection methods

• Regulatory mechanisms might tightly control its expression

Researchers interested in studying YHR213W-A expression could employ more sensitive techniques such as quantitative RT-PCR, RNA-Seq with deep coverage, or ribosome profiling to detect low-abundance transcripts or translation events. Additionally, testing expression under various stress conditions or growth phases may reveal condition-specific expression patterns.

What protein-protein interaction networks involve YHR213W-A?

YHR213W-A participates in a complex protein interaction network with multiple yeast proteins as revealed by STRING database analysis . The interaction network shows significant enrichment (p-value: 2.47e-9) with 34 edges detected among its interaction partners at an average node degree of 6.18. The high average local clustering coefficient (0.958) suggests that YHR213W-A is part of a tightly connected functional module.

The top predicted functional partners include:

These interactions were identified through various experimental techniques, computational predictions, and text mining approaches. The strong interaction with YHR214C-E and YHR213W-B suggests potential functional relationships, particularly since they were identified through similar genomic approaches . The connections to copper and zinc regulated proteins (YPL278C, YHR214W-A, YPL277C) may indicate a role in metal homeostasis or stress response pathways.

What approaches can be used to determine the subcellular localization of YHR213W-A?

Determining the subcellular localization of YHR213W-A is crucial for understanding its potential function. Several complementary approaches can be employed:

• Fluorescent Protein Tagging:

  • Create C- or N-terminal fusions with GFP, mCherry, or other fluorescent proteins

  • Express from the native promoter to maintain physiological expression levels

  • Employ confocal microscopy to visualize localization patterns

  • Use co-localization with known compartment markers to confirm specific locations

• Immunofluorescence Microscopy:

  • Generate specific antibodies against YHR213W-A or use anti-tag antibodies

  • Perform indirect immunofluorescence with fixed yeast cells

  • Use counterstaining with compartment-specific markers

• Subcellular Fractionation:

  • Fractionate yeast cells into different compartments (nucleus, mitochondria, ER, etc.)

  • Perform Western blotting to detect the tagged protein in different fractions

  • Use markers for each compartment as controls

• High-throughput Localization Studies:

  • Leverage existing datasets from the Yeast GFP Fusion Localization Database

  • Cross-reference with SWAT-GFP and mCherry fusion protein localization data

  • Note that some interaction partners like YFL068W have been observed in the cytosol

• Computational Prediction:

  • Use algorithms such as PSORT, TargetP, or DeepLoc to predict localization

  • Search for subcellular targeting sequences (nuclear localization signals, ER retention signals, etc.)

How can CRISPR-Cas9 technology be applied to study YHR213W-A function?

CRISPR-Cas9 technology offers powerful approaches for studying YHR213W-A function through precise genome editing. Based on current methodologies described in the literature , several strategies can be implemented:

• Gene Knockout/Disruption:

  • Design guide RNAs (gRNAs) targeting the YHR213W-A coding sequence

  • Use Cas9-induced double-strand breaks (DSBs) to create null mutants through non-homologous end joining (NHEJ)

  • Verify complete protein loss through PCR, sequencing, and Western blotting

  • Analyze resulting phenotypes under various growth conditions

• Precision Editing:

  • Introduce specific mutations within the YHR213W-A coding sequence

  • Create single strand template repair (SSTR) donors for precise modifications

  • Target mutations to predicted functional domains or post-translational modification sites

  • This approach typically requires Rad51-independent pathways for small mutations

• Transcriptional Regulation:

  • Employ CRISPRi (CRISPR interference) with catalytically inactive Cas9 (dCas9)

  • Target the YHR213W-A promoter to repress transcription

  • Use CRISPRa (CRISPR activation) with VP64 or other activator domains to enhance expression

  • Create an inducible system to control expression levels

• Tagging Approaches:

  • Introduce fluorescent protein tags or epitope tags at the endogenous locus

  • Design homology-directed repair (HDR) templates with appropriate tags

  • Maintain the native promoter to preserve normal expression patterns

  • Use synthesized single-stranded oligodeoxynucleotides (ssODNs) as repair templates

• Base and Prime Editing:

  • Use cytosine or adenine base editors for precise nucleotide changes without DSBs

  • Apply prime editing for more flexible sequence modifications

  • Create specific codon changes to analyze amino acid functions

The genetic requirements for CRISPR-mediated editing in yeast depend on the template design, with single-stranded template repair showing Rad51-independence but potential involvement of Rad52 and Rad59 . Careful design of guide RNAs and repair templates is essential, considering that mismatch repair mechanisms may act differently at the 5' and 3' ends of single-stranded oligonucleotide donors .

What comparative genomics approaches can reveal about YHR213W-A function?

Comparative genomics offers valuable insights into potential functions of uncharacterized proteins like YHR213W-A by examining evolutionary patterns across species:

• Sequence Homology Analysis:

  • Conduct BLAST searches against fungal and non-fungal genomes

  • Identify orthologs in other yeast species and related fungi

  • Examine conservation patterns across evolutionary distances

  • Map conserved domains or motifs that might suggest function

• Synteny Analysis:

  • Examine gene neighborhood conservation across species

  • Identify conserved gene clusters that might indicate functional relationships

  • Analyze chromosomal rearrangements affecting YHR213W-A locus

• Phylogenetic Profiling:

  • Create presence/absence profiles across multiple species

  • Identify proteins with similar evolutionary distribution patterns

  • Correlate evolutionary co-occurrence with potential shared functions

• Structural Prediction and Comparison:

  • Predict protein structure using AlphaFold or similar algorithms

  • Compare structural features with proteins of known function

  • Identify potential binding sites or functional domains

  • Examine structural conservation patterns across homologs

• Evolutionary Rate Analysis:

  • Calculate evolutionary rates (dN/dS ratios) for YHR213W-A

  • Compare with rates of interacting partners

  • Identify regions under purifying or positive selection

The paralogous relationship between YHR213W-B and YAR064W noted in the search results suggests a potential gene duplication event. Similarly, YHR214W-A has a paralog, YAR068W, arising from segmental duplication. This pattern of duplication in this chromosomal region might provide clues about the evolutionary history and potential functional redundancy among these genes.

How can high-throughput phenotypic screening be applied to characterize YHR213W-A?

High-throughput phenotypic screening provides a systematic approach to identifying conditions where YHR213W-A might play a crucial role:

• Deletion Strain Analysis:

  • Generate YHR213W-A deletion strains using the yeast deletion collection methodology

  • Include unique molecular barcodes for identification in pooled screens

  • Test growth under hundreds of conditions (chemical stressors, temperatures, pH, carbon sources)

  • Use quantitative fitness measurements through competitive growth assays

• Synthetic Genetic Array (SGA) Analysis:

  • Cross YHR213W-A deletion with the entire yeast deletion collection

  • Identify synthetic lethal or synthetic sick interactions

  • Map genetic interaction networks to reveal pathway connections

  • Calculate genetic interaction scores to quantify interaction strengths

• Chemical-Genetic Profiling:

  • Screen YHR213W-A deletion against diverse chemical compounds

  • Identify chemical sensitivities or resistances compared to wild-type

  • Compare chemical-genetic profiles with those of known genes

  • Use profile similarity to infer functional relationships

• Overexpression Phenotypic Analysis:

  • Create strains overexpressing YHR213W-A from inducible promoters

  • Screen for phenotypic changes under various growth conditions

  • Identify dosage-sensitive interactions with other genes

  • Test for suppression of known mutant phenotypes

• Environmental Stress Response Profiling:

  • Examine response to metal stress given the connections to copper and zinc regulated genes

  • Test heat shock, oxidative stress, and osmotic stress responses

  • Analyze cell wall integrity under different conditions

  • Examine metabolic adaptations to different carbon and nitrogen sources

The utility of such approaches has been demonstrated in comprehensive studies of yeast gene function, including the analysis of uncharacterized open reading frames, and has been instrumental in transitioning yeast from a model for cell biology to a pioneer organism in functional genomics and systems biology .

What proteomics approaches are most effective for studying YHR213W-A?

Proteomics offers powerful techniques to analyze the expression, modifications, and interactions of YHR213W-A at the protein level:

• Affinity Purification-Mass Spectrometry (AP-MS):

  • Express epitope-tagged YHR213W-A (FLAG, HA, or TAP-tag)

  • Perform affinity purification under native conditions

  • Identify interacting proteins using mass spectrometry

  • Validate interactions through reciprocal tagging and co-immunoprecipitation

  • This approach could expand upon the predicted interactions identified in STRING

• Proximity-Dependent Biotin Identification (BioID/TurboID):

  • Fuse YHR213W-A with a biotin ligase (BirA* or TurboID)

  • Express in yeast cells and provide biotin substrate

  • Identify proximal proteins through streptavidin pulldown and mass spectrometry

  • Map the protein neighborhood regardless of direct physical interactions

• Protein Stability and Turnover Analysis:

  • Employ cycloheximide chase assays to determine protein half-life

  • Use N-end rule reporter constructs to analyze degradation mechanisms

  • Apply SILAC labeling for quantitative proteomics of turnover rates

  • Determine cell cycle-dependent or stress-dependent stability changes

• Post-Translational Modification Mapping:

  • Use phosphoproteomics to identify phosphorylation sites

  • Analyze other modifications (ubiquitination, sumoylation, acetylation)

  • Map modification changes under different cellular conditions

  • Create modification-specific antibodies for functional studies

• Cross-Linking Mass Spectrometry (XL-MS):

  • Apply chemical cross-linkers to stabilize protein complexes

  • Identify interaction interfaces through mass spectrometry

  • Determine spatial relationships within multi-protein complexes

  • Validate structural predictions from computational models

Given the small size of YHR213W-A (77 amino acids), careful optimization of proteomics protocols is essential. The recombinant His-tagged version of the protein available from commercial sources could serve as a valuable resource for generating antibodies or as a positive control in proteomics experiments.

How can network biology approaches predict YHR213W-A function?

Network biology provides computational frameworks to predict functions of uncharacterized proteins by analyzing their position within biological networks:

• Protein-Protein Interaction Network Analysis:

  • Analyze the position of YHR213W-A in the yeast interactome

  • Calculate network metrics (centrality, clustering coefficient, etc.)

  • Identify network modules containing YHR213W-A

  • Apply guilt-by-association principles for functional prediction

• Functional Enrichment Analysis:

  • Examine functional annotations of interaction partners

  • Perform Gene Ontology (GO) enrichment analysis

  • Identify overrepresented pathways or biological processes

  • Calculate statistical significance of observed enrichments

• Network-Based Function Prediction:

  • Apply machine learning algorithms trained on network features

  • Use random walk or diffusion-based approaches

  • Integrate multiple data types (genetic interactions, co-expression)

  • Calculate confidence scores for predicted functions

• Weighted Functional Association Networks:

  • Integrate evidence from multiple data sources with appropriate weights

  • Include STRING-based interaction data (0.696-0.802 confidence scores)

  • Incorporate co-expression data when available

  • Use Bayesian approaches to calculate posterior probabilities of functional associations

• Cross-Species Network Comparison:

  • Compare network positions of orthologs across species

  • Identify conserved network modules

  • Transfer functional annotations from well-studied organisms

The STRING database analysis reveals that YHR213W-A has significant interactions with several uncharacterized proteins, many of which are also located in proximity on chromosome VIII . This clustering of interacting partners in both network space and genomic space suggests potential functional relationships, possibly involving coordinated regulation or participation in a common cellular process.

What transcriptomic approaches can reveal YHR213W-A function?

Transcriptomic analyses can provide insights into YHR213W-A function by examining its expression patterns and impact on global gene expression:

• RNA-Seq Analysis:

  • Compare transcriptomes of wild-type and YHR213W-A deletion strains

  • Identify differentially expressed genes upon deletion or overexpression

  • Examine expression changes under various stress conditions

  • Perform time-course experiments to capture dynamic responses

• Co-Expression Network Analysis:

  • Identify genes with expression patterns correlated with YHR213W-A

  • Construct co-expression modules using WGCNA or similar methods

  • Infer potential functional relationships from co-expression patterns

  • Map co-expression relationships onto protein interaction networks

• Single-Cell RNA-Seq:

  • Examine cell-to-cell variability in YHR213W-A expression

  • Identify potential subpopulations with distinct expression patterns

  • Correlate with cell cycle stages or stress responses

  • Map expression heterogeneity in colony or biofilm structures

• Ribosome Profiling:

  • Analyze translation efficiency of YHR213W-A

  • Identify potential regulatory mechanisms affecting translation

  • Examine upstream open reading frames or other regulatory features

  • Compare transcription and translation levels to identify post-transcriptional regulation

• CRISPR Screens with Transcriptomic Readouts:

  • Combine CRISPR-based perturbations with RNA-seq

  • Identify genetic interactions that affect YHR213W-A expression

  • Map regulatory relationships in YHR213W-A expression networks

  • Apply Perturb-seq approaches for large-scale functional genomics

It's worth noting that current expression data for YHR213W-A appears limited in the Saccharomyces Genome Database , suggesting that specialized approaches or specific conditions may be needed to detect meaningful expression patterns. Integration with SPELL (Serial Pattern of Expression Levels Locator) might help identify conditions where YHR213W-A shows significant expression changes.

What are the optimal conditions for recombinant expression and purification of YHR213W-A?

The efficient expression and purification of recombinant YHR213W-A protein is critical for biochemical and structural studies:

• Expression System Selection:

  • E. coli-based expression:

    • Use BL21(DE3) or Rosetta strains for improved expression

    • Consider codon optimization for bacterial expression

    • Test multiple fusion tags (His, GST, MBP) for optimal solubility

    • Available as His-tagged construct from commercial sources

  • Yeast-based expression:

    • Express in S. cerevisiae for native folding and modifications

    • Use strong inducible promoters (GAL1, CUP1) for controlled expression

    • Test secretion signals for extracellular production if appropriate

    • Consider S. pombe as an alternative expression host

• Optimization Parameters:

  • Induction conditions:

    • Test various temperatures (16°C, 25°C, 30°C, 37°C)

    • Optimize inducer concentration and induction duration

    • Examine different growth media formulations

    • Consider auto-induction media for E. coli expression

  • Solubility enhancement:

    • Test with solubility-enhancing fusion partners (SUMO, Thioredoxin)

    • Add stabilizing agents (glycerol, arginine, trehalose)

    • Optimize buffer conditions (pH, salt concentration)

    • Consider membrane-mimicking environments if membrane-associated

• Purification Strategy:

  • Primary capture:

    • Use immobilized metal affinity chromatography (IMAC) for His-tagged protein

    • Apply appropriate elution gradients to improve purity

    • Consider on-column refolding if expressed in inclusion bodies

  • Secondary purification:

    • Size exclusion chromatography for final polishing

    • Ion exchange chromatography for charge variant separation

    • Hydrophobic interaction chromatography for additional selectivity

• Quality Control Metrics:

  • SDS-PAGE and Western blotting to confirm identity and purity

  • Mass spectrometry for molecular weight confirmation

  • Dynamic light scattering to assess aggregation state

  • Circular dichroism for secondary structure evaluation

• Scale-up Considerations:

  • Transition from shake flask to bioreactor if larger quantities needed

  • Implement fed-batch strategies for higher cell densities

  • Optimize oxygen transfer rates for improved growth

  • Develop scalable purification protocols

Given the small size of YHR213W-A (77 amino acids) , special attention should be paid to preventing loss during purification steps. The fusion tag approach, particularly with larger solubility-enhancing partners, might be crucial for successful expression and purification of this small protein.

How can CRISPR-based screens be designed to identify genetic interactions of YHR213W-A?

CRISPR-based genetic screens offer powerful approaches to systematically map genetic interactions of YHR213W-A:

• Knockout Screen Design:

  • Library construction:

    • Design genome-wide sgRNA library targeting all yeast ORFs

    • Include multiple sgRNAs per gene for robust phenotypic assessment

    • Incorporate non-targeting controls and essential gene controls

    • Create a strain with YHR213W-A deletion or conditional expression

  • Screening conditions:

    • Test standard growth conditions and stress conditions

    • Consider metal stresses given potential connections to metal-regulated genes

    • Include chemical perturbations to probe specific pathways

    • Examine various carbon sources and nutrient limitations

• Dosage-Dependent Screens:

  • CRISPRi approach:

    • Express dCas9-repressor to tune down gene expression

    • Target promoter regions with variable efficiency guides

    • Create an expression gradient to identify dosage-sensitive interactions

    • Combine with YHR213W-A overexpression or deletion

  • CRISPRa implementation:

    • Express dCas9-activator to upregulate expression

    • Target minimal promoters for activation

    • Create gain-of-function genetic interaction maps

    • Identify genes that suppress or enhance YHR213W-A phenotypes

• Combinatorial CRISPR Approaches:

  • Dual-guide systems:

    • Simultaneously target YHR213W-A and other genes

    • Identify synthetic lethal or synthetic rescue interactions

    • Map epistatic relationships in relevant pathways

    • Implement orthogonal Cas systems for multiplexed targeting

  • CRISPR scanning:

    • Target tiling guides across YHR213W-A locus

    • Identify critical regions for function

    • Map domain importance through partial disruptions

    • Create allelic series through precision editing

• Readout Methodologies:

  • Growth-based selection:

    • Use competitive growth to identify fitness effects

    • Implement barcode sequencing for pooled analysis

    • Quantify growth rates in continuous culture

    • Apply colony size measurements for solid media screens

  • Reporter-based readouts:

    • Couple genetic interactions to fluorescent reporters

    • Implement flow cytometry-based sorting and analysis

    • Use luciferase reporters for high-sensitivity detection

    • Apply multiplexed reporters for pathway-specific readouts

• Data Analysis Frameworks:

  • Calculate genetic interaction scores from depletion/enrichment patterns

  • Implement normalization methods for systematic biases

  • Apply appropriate statistical tests for hit calling

  • Integrate with existing genetic interaction networks

The design of CRISPR-based screens should consider the DNA repair mechanisms in yeast, particularly the roles of Rad51-independent pathways in single-stranded template repair and the involvement of Rad52 and Rad59 in strand annealing, as highlighted in the search results .

What are the emerging research directions for understanding YHR213W-A function?

The investigation of YHR213W-A function represents an ongoing challenge in yeast functional genomics, with several promising research directions:

• Integrative Multi-Omics Approaches:

  • Combine proteomics, transcriptomics, and metabolomics data

  • Implement machine learning algorithms for integrated analysis

  • Apply network-based data integration methods

  • Develop predictive models of YHR213W-A function

• Structural Biology Investigations:

  • Determine the three-dimensional structure using X-ray crystallography or NMR

  • Apply cryo-EM for structural analysis of protein complexes

  • Implement molecular dynamics simulations to predict functional properties

  • Examine protein-protein interaction interfaces at atomic resolution

• Evolutionary Context Exploration:

  • Investigate the evolutionary history of YHR213W-A and related genes

  • Examine the role of segmental duplications in functional diversification

  • Compare function across diverse yeast species

  • Reconstruct the ancestral state and functional trajectory

• Systematic Perturbation Studies:

  • Apply CRISPR-based methods for precise genetic manipulation

  • Implement chemical genomics approaches to probe function

  • Develop conditional alleles for temporal control of function

  • Create systematic domain swaps to test functional hypotheses

• Cell Biology and Imaging:

  • Apply super-resolution microscopy to examine subcellular localization

  • Implement live-cell imaging to track dynamic behaviors

  • Examine protein-protein interactions in situ using proximity ligation

  • Apply correlative light and electron microscopy for multi-scale analysis

The interconnected nature of YHR213W-A with multiple other uncharacterized proteins suggests that understanding its function may require a systems-level approach that simultaneously investigates several interacting components . The significant enrichment of protein-protein interactions (p-value: 2.47e-9) indicates that YHR213W-A functions as part of a larger protein network rather than in isolation.

How can researchers contribute to the functional annotation of YHR213W-A?

Researchers can contribute to the functional annotation of YHR213W-A through several complementary approaches:

• Community-Based Annotation Efforts:

  • Submit experimental data to the Saccharomyces Genome Database (SGD)

  • Contribute to Gene Ontology annotation through evidence-based assertions

  • Participate in community curation initiatives

  • Share reagents and strains through repositories

• Standardized Phenotypic Reporting:

  • Use controlled vocabulary for phenotypic descriptions

  • Apply quantitative metrics for phenotypic severity

  • Document environmental conditions precisely

  • Implement reproducible workflows and protocols

• Functional Prediction Validation:

  • Test computational predictions with targeted experiments

  • Validate network-based functional hypotheses

  • Examine predictions from protein structure modeling

  • Assess evolutionary inference-based functional hypotheses

• Data Integration and Reanalysis:

  • Integrate published datasets for meta-analysis

  • Apply novel computational methods to existing data

  • Reanalyze raw data with improved algorithms

  • Implement Bayesian approaches for evidence integration

• Technology Development:

  • Create improved tools for yeast genetic manipulation

  • Develop new reporters for functional readouts

  • Implement single-cell technologies for heterogeneity analysis

  • Design novel computational frameworks for function prediction