YMR173W-A Antibody

What is YMR173W-A and why is it studied in research?

YMR173W-A is a protein encoded in the Saccharomyces cerevisiae genome (strain ATCC 204508/S288c), commonly known as baker's yeast. This protein is studied primarily in basic yeast research as part of understanding the yeast proteome. The antibody against this protein (UniProt accession: A0A023PXQ4) is typically used for detecting and studying the native protein in yeast samples .

When studying this protein, researchers should consider using knockout validation approaches, as studies have shown that genetic approaches to antibody validation are more reliable than orthogonal approaches. For instance, YCharOS has demonstrated that 89% of antibodies recommended based on genetic strategies could successfully detect their intended target proteins, compared to 80% of those validated through orthogonal strategies .

How should I validate the specificity of a YMR173W-A antibody for my experiments?

For rigorous validation of YMR173W-A antibody specificity, implement a multi-step approach:

• Genetic validation: Use wild-type and YMR173W-A knockout yeast strains in parallel experiments. The antibody should only produce a signal in wild-type samples and show no reactivity in knockout samples .

• Western blot validation: Run lysates from wild-type and knockout strains side by side. A specific antibody will show bands only in the wild-type lane at the expected molecular weight .

• Positive and negative controls: Include known positive samples (purified YMR173W-A protein or overexpression systems) and negative controls (unrelated yeast strains) .

Recent large-scale antibody validation studies have shown that only 38% of antibodies recommended by manufacturers based on orthogonal strategies could be confirmed using knockout cell controls in immunofluorescence applications, emphasizing the importance of proper validation .

What are the recommended storage conditions for YMR173W-A antibody?

The YMR173W-A antibody should be stored at -20°C or -80°C upon receipt. Avoid repeated freeze-thaw cycles as these can degrade the antibody and reduce its effectiveness. The antibody is typically supplied in a storage buffer containing 50% glycerol, 0.01M PBS (pH 7.4), and 0.03% Proclin 300 as a preservative .

For working solutions, aliquot the antibody into smaller volumes before freezing to minimize freeze-thaw cycles. When handling, keep the antibody on ice and return to storage promptly after use to maintain its activity and specificity.

What experimental applications is the YMR173W-A antibody validated for?

The YMR173W-A antibody has been validated specifically for:

• ELISA (Enzyme-Linked Immunosorbent Assay): Useful for quantitative detection of the target protein in solution.

• Western Blot (WB): For detecting the denatured protein in cell lysates and identifying its molecular weight .

When designing experiments with this antibody, remember that application-specific validation is crucial. An antibody performing well in Western blotting may not necessarily work effectively in other applications like immunoprecipitation or immunofluorescence. YCharOS data indicates that antibody performance varies significantly across applications, with many antibodies showing strong specificity in Western blot but reduced specificity in immunofluorescence .

How do I optimize Western blot conditions when using YMR173W-A antibody?

For optimal Western blot results with YMR173W-A antibody:

• Sample preparation: Prepare yeast lysates using a method that effectively extracts YMR173W-A (e.g., mechanical disruption with glass beads in an appropriate lysis buffer containing protease inhibitors).

• Blocking optimization: Test different blocking agents (BSA vs. non-fat milk) to determine which provides the best signal-to-noise ratio. For polyclonal antibodies like YMR173W-A, 5% BSA often provides better results.

• Antibody dilution series: Perform a dilution series (e.g., 1:500, 1:1000, 1:2000) to identify the optimal concentration that provides specific binding with minimal background.

• Incubation conditions: Test both room temperature (1-2 hours) and 4°C (overnight) incubation to determine optimal binding conditions.

• Detection system selection: Choose between chemiluminescence, fluorescence, or chromogenic detection based on required sensitivity.

According to antibody validation studies, using knockout controls in Western blot is particularly effective - the best-performing antibodies will show bands only in the wild-type lane while showing no signal in knockout samples .

Can YMR173W-A antibody be used for immunoprecipitation studies?

While the YMR173W-A antibody is not specifically validated for immunoprecipitation (IP) according to the product information , researchers working with similar polyclonal antibodies often adapt them for IP experiments.

If attempting IP with this antibody:

• Preliminary testing: First verify robust detection in Western blot before attempting IP.

• Optimization strategy:

  • Test different antibody amounts (2-5 μg per reaction)

  • Compare various buffers (RIPA vs. gentler NP-40 buffer)

  • Try different bead types (Protein A vs. Protein G)

  • Optimize incubation times (2 hours vs. overnight)

• Validation approach: Confirm IP results by Western blotting the immunoprecipitated material using the same or a different validated YMR173W-A antibody.

It's important to note that IP data alone does not imply selectivity. As YCharOS reports indicate, additional controls are necessary when validating antibodies for immunoprecipitation applications .

How can I perform cross-reactivity testing to ensure my YMR173W-A antibody is specific only to S. cerevisiae?

For comprehensive cross-reactivity testing:

• Multi-species panel: Test the antibody against lysates from:

  • Different yeast species (S. pombe, C. albicans)

  • Related fungi

  • Mammalian cell lines if your research involves cross-kingdom comparisons

• Sequence homology analysis: Perform bioinformatic analysis to identify proteins with sequence similarity to YMR173W-A in other species, then specifically test against those proteins.

• Competition assays: Pre-incubate the antibody with purified YMR173W-A protein before application to samples. Signal elimination indicates specificity.

• Knockout verification: Include YMR173W-A deletion strains alongside wild-type samples as the gold standard control .

Studies on antibody validation have shown that genetic approaches using knockout controls are significantly more reliable than other validation methods, with 89% of antibodies recommended based on genetic strategies successfully detecting their intended targets .

What controls should I include when using YMR173W-A antibody for studying protein-protein interactions?

When studying protein-protein interactions involving YMR173W-A:

Essential controls:

• Input control: Analyze a small portion of the pre-immunoprecipitation lysate to verify target protein presence.

• Negative antibody control: Use an isotype-matched irrelevant antibody (e.g., normal rabbit IgG for rabbit-derived YMR173W-A antibody).

• Bead-only control: Include a sample with beads but no antibody to identify proteins that bind non-specifically to the beads.

• Knockout/knockdown control: Compare results between wild-type and YMR173W-A knockout strains.

• Reciprocal IP: Perform reverse immunoprecipitation using antibodies against suspected interaction partners.

• Denaturing conditions control: Compare native versus denaturing conditions to distinguish direct from indirect interactions.

In antibody-based interaction studies, large-scale validation efforts have demonstrated that many antibodies exhibit non-specific binding, emphasizing the importance of rigorous controls .

How can I verify YMR173W-A antibody performance in different subcellular fractionation experiments?

To verify antibody performance in subcellular fractionation studies:

• Fractionation quality control: First confirm successful fractionation using established marker proteins for each cellular compartment (e.g., Pma1 for plasma membrane, Pgk1 for cytosol, Nop1 for nucleolus).

• Antibody validation in fractions:

  • Test the YMR173W-A antibody against each fraction

  • Compare distribution pattern with published localization data

  • Include a YMR173W-A knockout strain as negative control

• Complementary methods: Confirm subcellular localization using orthogonal methods:

  • Fluorescent tagging of YMR173W-A

  • Immunofluorescence with alternative antibodies

  • Mass spectrometry analysis of fractions

• Quantitative analysis: Perform densitometry to quantify signal distribution across fractions and compare with expected distribution based on literature.

Research has shown that many antibodies may perform differently across applications, making application-specific validation critical .

What are the most common causes of false positives when using YMR173W-A antibody, and how can I address them?

Common causes of false positives with YMR173W-A antibody include:

• Cross-reactivity issues:

  • Solution: Include YMR173W-A knockout controls

  • Validate with peptide competition assays

  • Use more stringent washing conditions

• Non-specific secondary antibody binding:

  • Solution: Include secondary-only controls

  • Use appropriate blocking conditions (test 5% BSA vs. 5% milk)

  • Consider species-specific secondary antibodies with minimal cross-reactivity

• Sample preparation artifacts:

  • Solution: Compare different lysis methods

  • Include protease inhibitors

  • Test fresh vs. frozen samples

• Detection system issues:

  • Solution: Optimize exposure times

  • Compare different detection methods (chemiluminescence vs. fluorescence)

  • Use fresh detection reagents

According to large-scale antibody validation studies, even manufacturer-recommended antibodies can show non-specific binding, with up to 20% of antibodies validated by orthogonal strategies failing to detect their intended targets specifically .

How should I interpret multiple bands in Western blots using YMR173W-A antibody?

When multiple bands appear in Western blots:

• Expected size band plus additional bands:

  • Potential post-translational modifications

  • Proteolytic fragments

  • Alternative splice variants

  • Protein complexes not fully denatured

• Methodical investigation approach:

  • Compare with YMR173W-A knockout control to identify which bands are specific

  • Test different sample preparation methods to distinguish artifacts

  • Vary reducing conditions to identify disulfide-linked complexes

  • Use phosphatase treatment to identify phosphorylated forms

• Band verification techniques:

  • Peptide competition assays

  • Mass spectrometry identification of excised bands

  • Size comparison with tagged versions of YMR173W-A

YCharOS data suggests that selective antibodies may display multiple wild-type bands that could represent truncated splice isoforms, multimers, or post-translationally modified forms of the protein of interest .

What strategies can improve signal strength when the YMR173W-A antibody produces weak signals?

To enhance signal strength:

• Sample enrichment techniques:

  • Concentrate proteins using TCA precipitation

  • Enrich for YMR173W-A through subcellular fractionation

  • Use larger amounts of starting material

• Signal amplification methods:

  • Employ more sensitive detection systems (e.g., enhanced chemiluminescence)

  • Use signal enhancing systems like biotinylated secondary antibodies with streptavidin-HRP

  • Try tyramide signal amplification for extremely low abundance targets

• Protocol optimization:

  • Increase antibody concentration (careful titration)

  • Extend primary antibody incubation time (overnight at 4°C)

  • Reduce washing stringency slightly (shorter washes or lower detergent concentration)

  • Test different membrane types (PVDF vs. nitrocellulose)

• Protein expression modulation:

  • Consider conditions that might upregulate YMR173W-A expression

  • Use strains with tagged or overexpressed YMR173W-A as positive controls

According to antibody validation studies, confirming that your antibody actually detects the intended target is crucial before attempting signal optimization .

How can YMR173W-A antibody be adapted for chromatin immunoprecipitation (ChIP) experiments?

While YMR173W-A antibody is not specifically validated for ChIP , researchers can attempt adaptation for this technique:

• Preliminary assessment: First confirm antibody specificity via Western blot using wild-type and knockout strains.

• ChIP protocol customization:

  • Test different crosslinking conditions (1% formaldehyde for various times)

  • Optimize sonication parameters for yeast cells (typically shorter times than mammalian cells)

  • Compare different antibody amounts (2-10 μg per reaction)

  • Test various washing stringencies

• Validation strategies:

  • Include negative control regions (regions not expected to contain YMR173W-A)

  • Use YMR173W-A knockout strain as negative control

  • Compare with ChIP using tagged versions of YMR173W-A

  • Validate enriched regions by orthogonal methods

For reliable ChIP results, prior understanding of expected DNA-binding sites is valuable. Methods like "Calling Cards for DNA-Binding Proteins" can help identify such sites before attempting ChIP with antibodies .

What considerations are important when designing super-shift experiments with YMR173W-A antibody?

For super-shift assays investigating YMR173W-A DNA interactions:

• Experimental design:

  • Prepare nuclear extracts from yeast under conditions preserving YMR173W-A activity

  • Design labeled DNA probes containing suspected binding sites

  • Establish baseline EMSA conditions before adding antibody

• Super-shift optimization:

  • Test different antibody amounts (0.5-2 μg per reaction)

  • Compare pre-incubation of antibody with extract before adding DNA vs. adding antibody after DNA-protein complex formation

  • Optimize incubation times and temperatures

• Critical controls:

  • Include extract from YMR173W-A knockout strain

  • Test specificity with unlabeled competitor probes

  • Use non-specific antibody (same species) as negative control

  • Include specific competitor with mutated binding sites

The super-shift assay relies on antibody recognition of the protein in a DNA-protein complex. As described in the literature, "The antibody is added to the binding reaction, and if the antibody recognizes the protein, an antibody-protein-DNA complex will be formed and cause a further shift (super shift) relative to the protein-DNA complex" .

What methodological approaches should be considered when using YMR173W-A antibody in multiplexed protein detection systems?

For multiplexed detection incorporating YMR173W-A antibody:

• Antibody compatibility assessment:

  • Verify no cross-reactivity between antibodies in the multiplex panel

  • Test for signal interference by comparing single vs. multiplexed staining

  • Ensure primary antibodies are from different host species or use isotype-specific secondaries

• Detection system selection:

  • For fluorescence multiplexing: select spectrally distinct fluorophores

  • For chemiluminescence: consider sequential detection with stripping between detections

  • For mass cytometry/imaging mass cytometry: use metal-conjugated antibodies

• Optimization strategies:

  • Titrate each antibody individually before multiplexing

  • Test different fixation methods compatible with all targets

  • Develop blocking strategy preventing cross-reactivity

• Validation approach:

  • Compare multiplexed results with single-antibody controls

  • Include knockout controls for each target

  • Validate co-localization with orthogonal methods

Recent advancements in antibody characterization, such as those from YCharOS, emphasize the importance of validating antibodies in the specific application and context in which they will be used .

What quantitative analysis methods are most appropriate for Western blot data using YMR173W-A antibody?

For robust quantification of YMR173W-A Western blot data:

Recommended quantification workflow:

• Image acquisition:

  • Capture images within the linear dynamic range

  • Use a calibration curve with known protein amounts

  • Include multiple exposure times to ensure non-saturation

• Software selection:

  • Use specialized software (ImageJ/Fiji, Image Lab, etc.)

  • Apply consistent analysis parameters across all blots

• Normalization strategy:

  • Normalize to total protein (Ponceau S, SYPRO Ruby) rather than housekeeping proteins

  • If using loading controls, verify their stability under your experimental conditions

  • Consider multiple reference proteins for more robust normalization

• Statistical analysis:

  • Perform replicate experiments (minimum n=3)

  • Apply appropriate statistical tests based on data distribution

  • Report variability measures (SD or SEM)

The YCharOS initiative has demonstrated the importance of quantitative approaches in antibody validation, showing that selective antibodies can demonstrate quantifiable differences between wild-type and knockout samples .

How should I approach contradictory results between YMR173W-A antibody detection and other methods of protein quantification?

When facing contradictory results:

• Systematic investigation strategy:

  • Verify antibody specificity using knockout controls

  • Compare protein vs. mRNA levels (Western blot vs. RT-qPCR)

  • Assess protein stability and turnover rates

  • Consider post-translational modifications affecting antibody recognition

• Technical considerations:

  • Evaluate extraction efficiency for different methods

  • Assess whether epitopes might be masked in certain contexts

  • Compare denatured vs. native detection methods

• Reconciliation approaches:

  • Use orthogonal detection methods (mass spectrometry)

  • Employ tagged versions of the protein

  • Consider absolute quantification methods for both approaches

• Documentation recommendations:

  • Document all experimental conditions in detail

  • Report contradictory results transparently

  • Propose biological explanations for discrepancies

According to large-scale antibody validation studies, discrepancies between different detection methods are common and may reflect biological reality rather than technical issues .

What are the best practices for presenting and publishing data generated using YMR173W-A antibody?

For optimal presentation of YMR173W-A antibody data:

• Essential reporting elements:

  • Full antibody details (manufacturer, catalog number, lot number, RRID)

  • Complete validation data (Western blot showing specificity)

  • Detailed methods including dilutions, incubation times, and buffers

  • All controls (positive, negative, knockout)

• Image presentation:

  • Show representative full blots including molecular weight markers

  • Indicate any image adjustments (contrast, brightness) applied uniformly

  • Clearly mark any blot splicing with lines

  • Include all relevant controls on the same blot where possible

• Quantification reporting:

  • Describe normalization methods in detail

  • Show individual data points alongside averages

  • Report statistical methods and significance levels

  • Consider sharing raw image files through repositories

• Validation documentation:

  • Reference appropriate validation studies

  • Include supplementary data showing antibody specificity

  • Acknowledge limitations of the antibody-based approach

Recent initiatives like YCharOS highlight the importance of comprehensive reporting to enhance reproducibility in antibody-based research .

How might YMR173W-A antibody be incorporated into advanced proteomics workflows?

YMR173W-A antibody could be integrated into advanced proteomics approaches:

• Antibody-based enrichment for mass spectrometry:

  • Immunoprecipitate YMR173W-A and associated complexes

  • Analyze by LC-MS/MS to identify interaction partners

  • Compare results with control IPs to identify specific interactions

• Targeted proteomics applications:

  • Develop SISCAPA (Stable Isotope Standards and Capture by Anti-Peptide Antibodies) methods

  • Create immuno-MRM (multiple reaction monitoring) assays for sensitive quantification

  • Use parallel reaction monitoring with antibody enrichment

• Spatial proteomics integration:

  • Apply for imaging mass spectrometry with antibody guidance

  • Combine with proximity labeling methods (BioID, APEX)

  • Develop correlative microscopy workflows

• Single-cell applications:

  • Adapt for mass cytometry (CyTOF) if metal-conjugated

  • Explore microfluidic antibody capture for single-cell proteomics

  • Consider integration with single-cell genomics data

Comprehensive antibody characterization, as demonstrated by YCharOS for other antibodies, provides essential validation data for these advanced applications .

What considerations are important when adapting YMR173W-A antibody for CRISPR-based genomic studies?

When integrating YMR173W-A antibody with CRISPR technologies:

• Experimental design strategy:

  • Design CRISPR editing to maintain or specifically modify antibody epitopes

  • Create epitope-tagged versions that can be detected by both anti-tag and anti-YMR173W-A antibodies

  • Consider domain-specific knockouts to map antibody recognition sites

• Validation in edited cells:

  • Compare antibody recognition in wild-type vs. edited cells

  • Use multiple detection methods to confirm CRISPR outcomes

  • Sequence the targeted region to confirm precise edits

• Functional validation approaches:

  • Correlate antibody detection with functional assays

  • Develop reporter systems to monitor edited gene expression

  • Compare protein localization before and after editing

• Advanced applications:

  • Use for CUT&Tag or CUT&RUN experiments when studying chromatin interactions

  • Integrate with CRISPR activation/repression systems

  • Combine with degron technologies for temporal control

Current antibody validation methods heavily rely on CRISPR knockout controls, demonstrating the synergy between these technologies in research applications .

How might AI and machine learning improve experimental design and data interpretation when using YMR173W-A antibody?

AI and machine learning offer several advantages for YMR173W-A antibody research:

• Experimental design optimization:

  • Predict optimal antibody dilutions based on similar antibodies

  • Identify potential cross-reactivity through sequence homology analysis

  • Suggest optimal buffer conditions based on antibody properties

• Image analysis enhancements:

  • Automated Western blot band identification and quantification

  • Improved signal-to-noise differentiation

  • Detection of subtle differences between experimental conditions

• Multi-omics data integration:

  • Correlate antibody-based detection with transcriptomics data

  • Identify potential post-translational modifications affecting detection

  • Predict protein interactions based on co-expression patterns

• Literature-based discovery:

  • Automatically extract relevant information about YMR173W-A from publications

  • Compare your results with published datasets

  • Identify contradictions or confirmations in the literature

The growing databases of antibody validation data, such as those from YCharOS, provide valuable training datasets for machine learning algorithms to improve antibody selection and experimental design .