YHR139C-A Antibody

What is YHR139C-A and why is an antibody against it important in research?

YHR139C-A is a systematic gene designation in yeast Saccharomyces cerevisiae, where YHR indicates it's located on chromosome VIII (H), on the right arm (R). The coding product of this gene represents an important target for studying yeast cellular functions. Antibodies against this protein are critical research tools that enable:

• Detection of protein expression levels in different conditions or genetic backgrounds

• Identification of protein localization within cellular compartments

• Analysis of protein interactions through immunoprecipitation techniques

• Monitoring of post-translational modifications

• Investigation of functional roles through comparative studies

The systematic study of YHR139C-A using antibody-based approaches contributes to our understanding of fundamental cellular processes in yeast, which often have parallels in higher eukaryotes .

How are YHR139C-A antibodies typically generated and validated?

Generation of reliable YHR139C-A antibodies typically follows several methodological approaches:

Production Methods:

• Recombinant protein expression of full-length or fragment YHR139C-A protein

• Synthetic peptide design from predicted antigenic regions

• Animal immunization (typically rabbits or mice) with purified antigen

• Hybridoma technology for monoclonal antibody development

• Computational antibody design approaches using platforms like RosettaAntibodyDesign

Validation Protocols:

• Western blot analysis comparing wild-type and YHR139C-A deletion strains

• Immunoprecipitation followed by mass spectrometry confirmation

• Peptide competition assays to verify epitope specificity

• Cross-reactivity testing against homologous yeast proteins

• Immunofluorescence comparison with GFP-tagged YHR139C-A constructs

Proper validation is essential as antibody specificity directly impacts experimental reliability and reproducibility. The validation process should follow a multi-technique approach to confirm target recognition under different experimental conditions .

What are the optimal storage conditions for maintaining YHR139C-A antibody activity?

Long-term stability and activity of YHR139C-A antibodies depend significantly on proper storage conditions:

Activity testing should be performed periodically using consistent positive controls. Antibody solutions showing precipitation or clouding should be centrifuged before use. Documentation of lot numbers, receipt dates, and thaw cycles is recommended for quality control purposes .

What are the optimal conditions for using YHR139C-A antibodies in Western blotting?

Successful Western blotting with YHR139C-A antibodies requires optimization across multiple parameters:

Sample Preparation:

• Extract yeast proteins using glass bead lysis in buffer containing protease inhibitors

• Denature samples at 95°C for 5 minutes in standard SDS loading buffer

• Load 20-50 μg total protein per lane for standard detection

Gel Electrophoresis and Transfer:

• Use 10-12% SDS-PAGE gels for optimal separation

• Transfer to PVDF membrane at 100V for 1 hour or 30V overnight at 4°C

• Verify transfer efficiency with reversible protein stain

Antibody Incubation:

• Block membrane with 5% non-fat dry milk in TBS-T for 1 hour at room temperature

• Dilute primary YHR139C-A antibody 1:1000 to 1:5000 in blocking buffer

• Incubate overnight at 4°C with gentle agitation

• Use HRP-conjugated secondary antibody at 1:5000 dilution for 1 hour at room temperature

Detection and Controls:

• Develop using enhanced chemiluminescence (ECL) reagents

• Include positive control (wild-type extract) and negative control (YHR139C-A deletion strain)

• Use loading control antibody (e.g., anti-actin) to normalize expression levels

How can YHR139C-A antibodies be effectively used in immunoprecipitation experiments?

Immunoprecipitation (IP) with YHR139C-A antibodies enables isolation of protein complexes for interaction studies:

Protocol Optimization:

• Harvest yeast cells during logarithmic growth phase

• Lyse cells in non-denaturing buffer (50 mM Tris-HCl pH 7.5, 150 mM NaCl, 1% NP-40, protease inhibitors)

• Pre-clear lysate with Protein A/G beads to reduce background

• Incubate cleared lysate with YHR139C-A antibody (2-5 μg per mg of total protein)

• Capture antibody-protein complexes using Protein A/G beads

• Wash extensively with decreasing salt concentrations

• Elute bound proteins using either SDS buffer (denaturing) or peptide competition (native)

Critical Controls:

• Input sample (pre-IP lysate)

• Non-specific IgG control

• Knockout/deletion strain control

• "No antibody" bead-only control

Downstream Applications:

• Western blotting to confirm specific precipitation

• Mass spectrometry to identify interaction partners

• Enzyme activity assays on native-eluted complexes

• RNA analysis for RNA-binding proteins

What approaches can resolve contradictory data when using YHR139C-A antibodies?

Conflicting results with YHR139C-A antibodies require systematic troubleshooting:

Technical Validation:

• Confirm antibody specificity using knockout controls

• Test multiple antibody lots or sources

• Validate using different detection methods

• Optimize experimental conditions (buffer composition, incubation times)

Biological Considerations:

• Different yeast strains may express variant forms of the protein

• Growth conditions can affect expression levels and post-translational modifications

• Cell cycle stage may influence protein localization or abundance

• Stress responses might alter protein structure or interactions

Resolution Strategies:

• Orthogonal Methods Approach: Compare antibody-based results with:

  • GFP-tagged YHR139C-A microscopy

  • Quantitative proteomics

  • RNA-seq expression correlation

  • Functional assays

• Quantitative Analysis:

  • Apply statistical methods to assess significance of differences

  • Use ratiometric measurements rather than absolute values

  • Implement time-course experiments to capture dynamic changes

• Computational Modeling:

  • Use tools like RosettaAntibodyDesign to optimize antibody specificity

  • Apply computational modeling to predict protein behavior

  • Leverage bioinformatics to identify potential confounding factors

How can computational approaches enhance YHR139C-A antibody design and performance?

Modern computational tools offer significant advantages for antibody optimization:

RosettaAntibodyDesign (RAbD) Applications:
The RAbD framework samples "the diverse sequence, structure, and binding space of an antibody to an antigen in highly customizable protocols for the design of antibodies in a broad range of applications" . For YHR139C-A antibodies, this enables:

• Epitope Optimization:

  • Identification of highly specific, accessible epitopes

  • Analysis of protein surface properties to target stable regions

  • Design of antibodies against conformational epitopes

• Affinity Enhancement:

  • Computational redesign of complementarity-determining regions (CDRs)

  • "RAbD can be used to redesign a single CDR or multiple CDRs with loops of different length, conformation, and sequence"

  • Experimental validation has shown "successfully improving affinities 10 to 50 fold by replacing individual CDRs"

• Cross-Reactivity Minimization:

  • Screening against related yeast proteins in silico

  • Identification and elimination of shared epitopes

  • Optimization of antibody specificity through targeted mutations

• Experimental Implementation:

  • Design multiple candidate antibodies for experimental testing

  • Prioritize designs based on predicted binding energy

  • Validate computationally designed antibodies using standard methodologies

What techniques enable characterization of post-translational modifications using YHR139C-A antibodies?

Detecting post-translational modifications (PTMs) of YHR139C-A requires specialized approaches:

Modification-Specific Antibodies:

• Generate phospho-specific antibodies targeting predicted phosphorylation sites

• Develop antibodies recognizing other PTMs (ubiquitination, acetylation, etc.)

• Validate specificity using phosphatase-treated or mutagenized samples

Combined Methodological Approaches:

• Immunoprecipitation-Mass Spectrometry:

  • IP with general YHR139C-A antibody followed by MS analysis

  • Enrichment of modified peptides using IMAC or TiO₂ (for phosphopeptides)

  • Quantitative comparison across conditions

• 2D Gel Electrophoresis:

  • Separation by isoelectric point and molecular weight

  • Detection of PTM-induced shifts with YHR139C-A antibody

  • Comparison with phosphatase-treated controls

• Phos-tag SDS-PAGE:

  • Enhanced separation of phosphorylated proteins

  • Western blotting with general YHR139C-A antibody

  • Identification of phosphorylated forms by mobility shift

• Multiplexed Detection Systems:

  • Fluorescent labeling of different modification-specific antibodies

  • Simultaneous visualization of multiple PTM states

  • Quantitative analysis of modification stoichiometry

How can YHR139C-A antibodies be applied in chromatin immunoprecipitation studies?

Chromatin immunoprecipitation (ChIP) with YHR139C-A antibodies presents specific challenges and opportunities:

Experimental Design Considerations:

• Determine if YHR139C-A associates with DNA directly or as part of a complex

• Optimize crosslinking conditions (typically 1% formaldehyde for 10-15 minutes)

• Develop appropriate sonication parameters for yeast chromatin fragmentation

• Consider dual crosslinking (formaldehyde + protein-specific crosslinkers)

Protocol Adaptations for Yeast Cells:

• Spheroplast formation using zymolyase treatment

• Careful lysis to preserve protein-DNA interactions

• Chromatin shearing to 200-500 bp fragments

• Immunoprecipitation with YHR139C-A antibody

• Reverse crosslinking and DNA purification

• Analysis by qPCR or next-generation sequencing

Advanced ChIP Applications:

• ChIP-seq: Genome-wide mapping of YHR139C-A binding sites

• ChIP-exo: Higher-resolution mapping with exonuclease treatment

• Sequential ChIP: Analysis of co-occupancy with other factors

• Developmental ChIP: Temporal analysis across yeast life cycle phases

Critical Controls and Analysis:

• Input chromatin sample

• IgG control ChIP

• Positive control regions (known binding sites)

• Negative control regions (non-binding sites)

• Normalization to input and background controls

What are common sources of false positives/negatives in YHR139C-A antibody experiments?

Understanding potential artifacts is crucial for accurate data interpretation:

False Positive Sources:

• Cross-reactivity with related proteins:

  • Yeast proteome contains numerous similar proteins

  • Highly conserved domains can be recognized non-specifically

  • Validation using knockout controls is essential

• Technical artifacts:

  • Secondary antibody binding directly to yeast proteins

  • Protein A/G in yeast cell wall binding to antibodies

  • Inadequate blocking leading to non-specific binding

• Sample preparation issues:

  • Protein aggregation creating misleading signals

  • Contamination from handling

  • Non-specific precipitation during concentration steps

False Negative Sources:

• Epitope masking:

  • Protein-protein interactions blocking antibody access

  • Conformational changes under experimental conditions

  • Post-translational modifications altering epitope structure

• Technical limitations:

  • Insufficient protein extraction efficiency

  • Inadequate sensitivity of detection system

  • Protein degradation during sample preparation

• Experimental variables:

  • Growth conditions affecting expression levels

  • Cell cycle-dependent expression or localization

  • Strain-specific variations in protein structure

Validation Approaches:

• Multi-technique confirmation (Western, IP, IF)

• Genetic controls (knockout, overexpression)

• Tagged protein comparisons (GFP, FLAG, etc.)

• Orthogonal detection methods (mass spectrometry)

How should researchers address non-specific binding and cross-reactivity issues?

Maximizing specificity requires systematic optimization:

Cross-reactivity Identification:

• Bioinformatic analysis to identify proteins with similar epitopes

• Testing antibody against YHR139C-A deletion strain

• Mass spectrometry analysis of all bound proteins

• Western blot analysis against predicted cross-reactive proteins

Experimental Mitigation Strategies:

Alternative Approaches:

• Epitope tagging: Generating YHR139C-A with FLAG, HA, or other tags

• Monoclonal antibody development: Increasing specificity through single epitope targeting

• Recombinant antibody fragments: Using Fab or scFv with higher specificity

• Computational redesign: Applying RAbD methodology to optimize antibody specificity

What methodologies enable quantitative analysis of YHR139C-A expression levels?

Accurate quantification requires appropriate techniques and controls:

Western Blot Quantification:

• Use gradient loading of standards for calibration curve

• Ensure detection is within linear range of signal

• Apply appropriate normalization controls (total protein or housekeeping genes)

• Use digital imaging systems with validated analysis software

• Perform technical replicates and biological repeats

ELISA Development:

• Sandwich ELISA with capture and detection antibodies

• Competitive ELISA for higher sensitivity

• Standard curve generation using recombinant YHR139C-A protein

• Careful optimization of antibody concentrations and incubation times

Flow Cytometry Applications:

• Fixation and permeabilization of yeast cells

• Staining with fluorophore-conjugated YHR139C-A antibody

• Calibration using fluorescence standards

• Multi-parameter analysis for heterogeneity assessment

Mass Spectrometry-Based Quantification:

• Targeted MS/MS for absolute quantification

• SILAC labeling for comparative studies

• Addition of isotope-labeled peptide standards

• Immunoprecipitation combined with MS for specific analysis

Data analysis should include appropriate statistical methods, with consideration of biological variance across conditions and strains. Expression changes should be validated using orthogonal methods when possible, particularly for subtle or unexpected differences in expression .