YPR136C Antibody

What is YPR136C and why is it studied in yeast research?

YPR136C is a putative uncharacterized protein in Saccharomyces cerevisiae that appears in chromatin studies. It has been identified in analyses examining binding patterns of proteins like Arp6 and Swr1 on chromosomes, suggesting potential roles in chromatin organization or gene expression regulation . The protein is included in genome-wide studies as shown in comprehensive proteomic analyses where it's been examined alongside other yeast proteins during different growth conditions . YPR136C represents one of many proteins that researchers are characterizing to build a complete functional map of the yeast proteome, which serves as a model for understanding eukaryotic cellular processes.

How can researchers validate the specificity of a YPR136C antibody?

Validating YPR136C antibody specificity requires multiple complementary approaches:

• Knockout validation: Testing in wild-type versus YPR136C knockout strains to confirm signal absence in knockout samples

• Western blot analysis: Verifying detection of a protein with the expected molecular weight

• Immunoprecipitation with mass spectrometry: Confirming the antibody pulls down YPR136C rather than other proteins

• Cross-reactivity assessment: Testing against similar yeast proteins or in different strains

• Epitope competition: Using the immunizing peptide to compete for antibody binding

This multi-method approach aligns with practices championed by YCharOS, which provides comprehensive knockout characterization data for antibodies using Western blot, immunoprecipitation, and immunofluorescence techniques . For YPR136C specifically, validation is particularly important given its uncharacterized nature and potential sequence similarities with other yeast proteins.

What expression systems are suitable for producing recombinant YPR136C protein for antibody development?

Producing recombinant YPR136C requires careful consideration of expression systems:

• Bacterial expression: Can be efficient for small domains, but yeast proteins may require eukaryotic folding machinery

• Homologous expression: Using S. cerevisiae itself ensures proper folding and modifications, though yields may be lower

• Other yeast systems: Pichia pastoris often provides higher yields than S. cerevisiae while maintaining eukaryotic processing

• Insect cells: Baculovirus expression systems offer good compromise between yield and eukaryotic processing

For YPR136C specifically, researchers have produced recombinant protein preparations that are commercially available . Expression constructs should ideally include purification tags (His, GST) that can be removed if needed for immunization. When expressing in bacteria, codon optimization for E. coli is recommended as yeast genes can contain codons rarely used in bacteria.

How can YPR136C antibody be utilized in chromatin immunoprecipitation (ChIP) studies?

YPR136C antibody can be used in ChIP studies following methodologies demonstrated for other yeast proteins:

• Crosslinking protocol: Yeast cells should be cross-linked with 1% formaldehyde for 15 minutes at room temperature to stabilize protein-DNA interactions

• Chromatin shearing: Sonication to generate fragments of 200-500 bp

• Immunoprecipitation: Use 2-5 μg of YPR136C antibody per sample, adding protein A/G beads for capture

• Washing and elution: Apply stringent washing followed by elution of complexes

• Reverse crosslinking: Typically performed at 65°C overnight

• Analysis: qPCR, sequencing, or microarray to identify binding regions

For quantification, ChIP signals can be calculated using the formula: 2^-IP(CT target − CT control)/input(CT target − CT control) . Essential controls include input DNA samples, immunoprecipitation with non-specific IgG, and a verified non-target gene like NUP85 as internal control, which has been successfully used in previous yeast ChIP studies .

What approaches can identify interaction partners of YPR136C using antibody-based methods?

Identifying YPR136C interaction partners requires combining multiple complementary techniques:

• Co-immunoprecipitation (Co-IP): Using YPR136C antibody to pull down protein complexes followed by mass spectrometry analysis

• Proximity labeling: Expressing YPR136C fused to BioID or APEX2 to biotinylate proximal proteins

• Yeast two-hybrid screening: Complementary approach to validate direct protein-protein interactions

• Reciprocal Co-IP: Confirmation using antibodies against potential interaction partners

• ChIP-reChIP: For chromatin-associated proteins, sequential ChIP with YPR136C antibody followed by another antibody

Researchers investigating chromatin-associated proteins like Arp6 and Swr1 have used similar approaches to map interaction networks on chromosomes . Mass spectrometry analysis should include quantitative approaches (such as SILAC or TMT labeling) to distinguish specific interactions from background. Correlation with existing yeast protein interaction databases can provide context for newly identified interactions.

How does YPR136C expression and localization change in response to metabolic state transitions?

Examining YPR136C dynamics during metabolic transitions requires systematic profiling:

• Culture conditions: Compare YPR136C expression in fermentation (glucose-rich) versus respiration (acetate-rich) conditions as described in comprehensive studies of yeast protein dynamics

• Protein detection methods:

  • Western blotting to quantify total protein levels

  • Immunofluorescence to track subcellular localization changes

  • ChIP to monitor chromatin association patterns

• Time-course analysis: Sample at multiple timepoints during metabolic shift

• Integration with transcriptome data: Correlate protein-level changes with mRNA expression

Previous studies have shown that the yeast proteome undergoes significant remodeling during transitions between fermentation and respiration . For proteins like YPR136C that may be involved in chromatin regulation, these transitions often correlate with changes in genome-wide binding patterns. Utilizing comprehensive genomics approaches can provide insight into the interplay between the transcriptome and proteome during these metabolic shifts .

What are the optimal conditions for using YPR136C antibody in Western blotting?

Optimizing Western blot conditions for YPR136C antibody requires systematic parameter testing:

• Sample preparation:

  • Cell lysis: Glass bead disruption in the presence of protease inhibitors

  • Protein denaturation: Standard SDS sample buffer with 5-10 minutes boiling

  • Loading: 20-50 μg total protein per lane

• Gel electrophoresis and transfer:

  • 10-12% polyacrylamide gels separate proteins in YPR136C's size range effectively

  • PVDF membranes provide better protein retention than nitrocellulose

  • Transfer in Tris-glycine buffer containing 20% methanol at 100V for 1 hour

• Antibody conditions:

  • Blocking: 5% non-fat milk in TBST for 1 hour at room temperature

  • Primary antibody: Start at 1:1000 dilution in blocking buffer overnight at 4°C

  • Secondary antibody: HRP-conjugated at 1:5000 dilution for 1 hour

• Controls:

  • Positive control: Recombinant YPR136C protein

  • Negative control: Lysate from YPR136C knockout strain

  • Loading control: Anti-tubulin or anti-GAPDH antibody

These parameters should be systematically optimized based on initial results, with particular attention to reducing background signal while maintaining specific detection of YPR136C. This methodological approach follows established practices for yeast protein analysis .

How should immunoprecipitation protocols be modified specifically for YPR136C studies?

Immunoprecipitation of YPR136C requires careful protocol optimization:

• Lysis buffer composition:

  • Base buffer: 50 mM Tris-HCl pH 7.5, 150 mM NaCl

  • Detergent options: 0.5% NP-40, 1% Triton X-100, or 0.3% CHAPS

  • Additives: 5% glycerol, 1 mM EDTA, protease inhibitor cocktail

  • For nuclear proteins: Consider including 1-5 mM MgCl₂

• IP procedure:

  • Pre-clear lysate with Protein A/G beads for 1 hour

  • Incubate with YPR136C antibody (2-5 μg) overnight at 4°C

  • Add fresh Protein A/G beads for 2-3 hours at 4°C

  • Wash 4× with decreasing detergent concentrations

• Elution options:

  • Denaturing: SDS sample buffer at 95°C for 5 minutes

  • Native: Competition with excess immunizing peptide

  • For mass spectrometry: On-bead digestion with trypsin

• Validation:

  • Western blot of IP samples alongside input and unbound fractions

  • Mass spectrometry confirmation of pulled-down proteins

  • Comparison with IgG control IP

The optimal conditions may vary based on YPR136C's expression level and subcellular localization. Researchers should test different detergent types and concentrations to maximize specific capture while minimizing background binding. Additional considerations for chromatin-associated proteins include testing native versus crosslinked IPs .

What controls are essential for interpreting YPR136C immunofluorescence microscopy data?

Reliable immunofluorescence with YPR136C antibody requires comprehensive controls:

• Specificity controls:

  • Parallel staining of YPR136C knockout strain

  • Competition with immunizing peptide/antigen

  • Comparison with GFP-tagged YPR136C localization pattern

• Technical controls:

  • Secondary antibody-only control for background assessment

  • Unstained samples to evaluate autofluorescence

  • Pre-immune serum control (for polyclonal antibodies)

• Fixation and permeabilization validation:

  • Compare ethanol fixation (70% for 1 hour) versus formaldehyde (4% for 15 minutes)

  • Test different permeabilization methods (0.1% Triton X-100, digitonin)

  • Optimize epitope retrieval if needed

• Colocalization markers:

  • Nuclear: DAPI for DNA (1 μg/ml)

  • Nucleolus: Anti-fibrillarin antibody

  • Chromatin: Anti-histone antibodies

  • Other organelles: Specific markers depending on hypothesized localization

Image acquisition should use consistent exposure settings across all samples and controls, with Z-stack imaging to capture the full cellular distribution. Quantitative analysis should include multiple cells across independent experiments with statistical validation. These methodological controls ensure accurate interpretation of localization patterns .

How can researchers address cross-reactivity issues with YPR136C antibodies?

Cross-reactivity challenges with YPR136C antibodies can be systematically addressed:

• Epitope analysis and antibody redesign:

  • Perform in silico epitope mapping to identify unique regions

  • Generate new antibodies against highly specific peptides

  • Consider monoclonal antibodies for improved specificity

• Absorption techniques:

  • Pre-incubate antibody with lysates from YPR136C knockout strains

  • Perform affinity depletion against cross-reactive proteins

• Validation approaches:

  • Western blot under highly denaturing conditions

  • Two-dimensional gel electrophoresis to separate similar proteins

  • Immunoprecipitation followed by mass spectrometry to identify all recognized proteins

• Experimental design modifications:

  • Use multiple antibodies against different YPR136C epitopes

  • Test different antibody clones as done in CD26 immunophenotyping studies

  • Consider epitope tagging (HA, FLAG, V5) as alternative approach

• Data analysis strategies:

  • Compare signal patterns across multiple detection methods

  • Develop computational approaches to differentiate specific from non-specific signal

  • Use machine learning for pattern recognition in complex datasets

When testing multiple antibody clones, validation through competition and cross-blocking experiments is essential, as demonstrated in studies of other proteins where researchers encountered similar challenges .

How can researchers resolve contradictory data from different YPR136C antibody experiments?

Resolving contradictory YPR136C antibody data requires systematic analytical approaches:

• Antibody validation reassessment:

  • Re-validate antibody specificity under your specific experimental conditions

  • Compare multiple antibodies targeting different epitopes

  • Check for lot-to-lot variation that might explain discrepancies

• Technical approach diversification:

  • Employ orthogonal techniques (e.g., mass spectrometry, genetic approaches)

  • Compare antibody-based and non-antibody methods

  • Use complementary detection systems

• Experimental variables analysis:

  Variable	Potential Impact	Assessment Method
  Fixation method	Epitope accessibility	Compare multiple methods
  Cell lysis conditions	Protein conformation	Test native vs. denaturing
  Growth conditions	Expression levels	Standardize culture protocols
  Yeast strain	Genetic background effects	Test in multiple strains
  Antibody concentration	Signal-to-noise ratio	Perform titration experiments

• Integrated data analysis:

  • Combine transcriptomic and proteomic data as demonstrated in integrated genomics studies

  • Perform meta-analysis across multiple experimental replicates

  • Apply statistical approaches to identify significant patterns despite variability

• Collaborative validation:

  • Share reagents between labs for independent confirmation

  • Standardize protocols across research groups

  • Consider submitting antibodies to validation initiatives like YCharOS

What strategies improve signal-to-noise ratio when detecting low-abundance YPR136C?

Enhancing detection of low-abundance YPR136C requires optimized protocols:

• Sample enrichment approaches:

  • Subcellular fractionation to concentrate relevant compartments

  • Affinity purification to enrich for YPR136C complexes

  • Synchronization of yeast cultures if expression is cell-cycle dependent

• Signal amplification methods:

  • Tyramide signal amplification for immunofluorescence

  • Enhanced chemiluminescence substrates for Western blots

  • Polymer-based detection systems for increased sensitivity

• Instrumentation optimization:

  • Confocal microscopy with optimal pinhole settings

  • Highly-sensitive CCD cameras for immunofluorescence

  • Advanced proteomics approaches using targeted mass spectrometry

• Protocol refinements:

  • Extended primary antibody incubation (overnight at 4°C)

  • Optimized blocking to reduce background (5% BSA often superior to milk)

  • Increased washing stringency with detergent-containing buffers

• Quantitative analysis:

  • Background subtraction based on negative controls

  • Digital image processing with deconvolution algorithms

  • Statistical methods to distinguish signal from noise

For immunofluorescence specifically, mounting samples in antifade solution containing DAPI helps preserve signal while providing nuclear counterstaining . For Western blots, extended exposure times with low-background substrates can reveal low-abundance proteins while maintaining acceptable background levels.

How does YPR136C expression and function compare across different yeast strains?

Comparative analysis of YPR136C across yeast strains provides evolutionary and functional insights:

• Sequence comparison approach:

  • Align YPR136C sequences from laboratory strains (S288C, W303, BY4741) and wild isolates

  • Identify conserved domains indicating functional importance

  • Analyze strain-specific polymorphisms and their potential impacts

• Expression pattern analysis:

  • Compare YPR136C expression levels across strains using RT-qPCR and Western blotting

  • Assess expression changes under different growth conditions (fermentation vs. respiration)

  • Determine if regulation mechanisms are conserved

• Phenotypic characterization:

  • Systematic phenotyping of YPR136C deletion in multiple backgrounds

  • Growth assays under various stress conditions (temperature, nutritional limitation, drug sensitivity)

  • Complementation experiments across strains to test functional conservation

• Interaction network comparison:

  • Map protein-protein and genetic interactions in different backgrounds

  • Identify conserved versus strain-specific interaction partners

  • Assess the impact of natural genetic variation on networks

This comparative approach has been successfully applied to other yeast genes, revealing how genetic background affects protein function and interaction networks . For YPR136C specifically, expression analysis during metabolic transitions (glucose to acetate media) could reveal strain-specific differences in regulation patterns.

How can computational approaches predict YPR136C function based on structural features?

Computational prediction of YPR136C function requires multi-faceted bioinformatic analysis:

• Sequence-based predictions:

  • Identification of conserved domains and motifs

  • Prediction of secondary structure elements

  • Detection of sequence patterns associated with specific functions

• Structural modeling:

  • Generation of 3D models using AlphaFold or similar tools

  • Structural comparison with proteins of known function

  • Identification of potential binding pockets or active sites

• Network-based inference:

  • Guilt-by-association analysis using known interaction partners

  • Functional prediction based on genomic context

  • Integration with gene expression correlation networks

• Evolutionary analysis:

  • Phylogenetic profiling across species

  • Analysis of selection pressure to identify functional constraints

  • Identification of co-evolving gene pairs suggesting functional relationships

• Integration with experimental data:

  • Correlation with ChIP-seq binding patterns

  • Mapping of protein-protein interaction data onto structural models

  • Incorporation of phenotypic data from deletion studies

These computational approaches can generate testable hypotheses about YPR136C function, potentially guiding experimental design. Similar approaches have been used for other uncharacterized yeast proteins, as described in comprehensive antibody and protein databases like PLAbDab, which contains over 150,000 paired antibody sequences and 3D structural models .

How has our understanding of YPR136C evolved through various antibody-based characterization approaches?

Tracking the evolution of YPR136C research reveals methodological progress in yeast protein characterization:

• Historical perspective:

  • Early studies: Initial identification through genome sequencing projects

  • Middle period: Inclusion in large-scale deletion and localization studies

  • Recent developments: Integration into multi-omics datasets

• Technological advancement impacts:

  • Transition from polyclonal to monoclonal and recombinant antibodies

  • Integration with emerging technologies like mass spectrometry

  • Development of databases like YAbS and PLAbDab for antibody research

• Functional insights progression:

  • Initial localization and expression pattern studies

  • Advancement to interaction partner identification

  • Connection to known cellular pathways through systematic analyses

• Integration with systems biology:

  • Placement in global protein interaction networks

  • Contributions to understanding yeast chromatin regulation

  • Comparative studies with related proteins

This evolutionary perspective on YPR136C research highlights how antibody-based approaches continue to advance our understanding of uncharacterized proteins. Recently, initiatives like YCharOS have improved antibody characterization standards, using comprehensive knockout validation approaches across multiple applications , which will likely benefit future YPR136C studies.