YLR347W-A Antibody

What is YLR347W-A and why is it studied in yeast research?

YLR347W-A is a gene/protein in Saccharomyces cerevisiae (strain ATCC 204508 / S288c), commonly known as baker's yeast. It is part of the reference genome derived from the laboratory strain S288C. Researchers study this protein to understand its specific functions within yeast cellular processes, contributing to our broader understanding of eukaryotic cellular biology. The YLR347W-A protein (UniProt ID: Q8TGM2) serves as a model for investigating protein expression, localization, and function in a well-characterized eukaryotic system . Studying yeast proteins like YLR347W-A provides insights into fundamental cellular processes that may have homologs in more complex organisms, including humans.

What types of YLR347W-A antibodies are available for research?

Research-grade YLR347W-A antibodies are available as polyclonal and monoclonal formats from specialized suppliers. The most common commercial product is identified as CSB-PA840595XA01SVG (Cusabio), which is designed specifically for detecting the YLR347W-A protein in Saccharomyces cerevisiae. These antibodies typically come in standard research quantities of 0.1ml or 2ml and are developed for applications such as Western blotting, immunohistochemistry, and immunofluorescence . When selecting an antibody, researchers should consider the validation data, target epitope, and specific applications for which the antibody has been validated.

What experimental applications are YLR347W-A antibodies typically used for?

YLR347W-A antibodies are primarily used in fundamental yeast research applications including:

• Western blotting for protein expression analysis

• Immunoprecipitation for protein-protein interaction studies

• Immunolocalization to determine subcellular localization

• ChIP (Chromatin Immunoprecipitation) assays if the protein interacts with DNA

• Functional inhibition studies in living yeast cells

These applications allow researchers to investigate the expression patterns, interactions, and functions of the YLR347W-A protein in various experimental conditions and genetic backgrounds .

How should I validate the specificity of a YLR347W-A antibody?

Proper validation of YLR347W-A antibodies is critical for ensuring experimental rigor. Following the International Working Group for Antibody Validation pillars, researchers should:

• Perform genetic validation by comparing signals in wild-type yeast strains versus YLR347W-A knockout strains

• Check for cross-reactivity with homologous proteins through sequence analysis and control experiments

• Use orthogonal methods to confirm antibody specificity (e.g., mass spectrometry)

• Compare results from multiple antibodies targeting different epitopes of YLR347W-A

• Conduct expression validation with independent methods like RT-PCR

Particular attention should be paid to potential cross-reactivity with homologous proteins. As demonstrated in studies of Y-chromosome antibodies in mammals, homologous proteins can share over 90% amino acid identity, presenting unique specificity challenges that must be addressed experimentally .

What are the optimal conditions for Western blotting with YLR347W-A antibodies?

For optimal Western blotting with YLR347W-A antibodies:

• Sample preparation: Extract total protein from yeast cells in log phase using glass bead lysis or enzymatic methods in the presence of protease inhibitors

• Protein denaturation: Heat samples at 95°C for 5 minutes in loading buffer containing SDS and DTT

• Gel selection: Use 10-12% polyacrylamide gels (adjust based on protein size)

• Transfer conditions: Transfer to PVDF membrane at 100V for 1 hour in standard transfer buffer

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

• Primary antibody: Dilute YLR347W-A antibody 1:1000 in blocking buffer and incubate overnight at 4°C

• Detection: Use appropriate HRP-conjugated secondary antibody with ECL detection system

Always include wild-type and YLR347W-A deletion strains as positive and negative controls to verify specificity and minimize false positives that can undermine experimental rigor .

How do I optimize immunoprecipitation experiments with YLR347W-A antibodies?

For successful immunoprecipitation of YLR347W-A protein:

• Cell lysis: Use gentle lysis conditions (non-ionic detergents like NP-40 or Triton X-100) to preserve protein-protein interactions

• Pre-clearing: Pre-clear lysate with protein A/G beads to reduce non-specific binding

• Antibody binding: Incubate lysate with YLR347W-A antibody (2-5 μg per 1 mg protein) for 2-4 hours at 4°C

• Bead capture: Add protein A/G beads and incubate for additional 1-2 hours

• Washing: Perform at least 4-5 washes with decreasing salt concentrations to remove non-specific interactions

• Elution: Elute bound proteins using low pH buffer or by boiling in SDS sample buffer

For investigating protein complexes, consider using cross-linking agents before lysis to stabilize transient interactions. Always validate results with reciprocal IPs using antibodies against suspected interaction partners to confirm genuine interactions .

How can I assess potential cross-reactivity of YLR347W-A antibodies with homologous proteins?

Cross-reactivity assessment is critical for antibody specificity. For YLR347W-A antibodies:

• Perform sequence alignment analysis of YLR347W-A with potential homologs to identify regions of high similarity

• Test the antibody in multiple yeast strains with different genetic backgrounds

• Use knockout strains for YLR347W-A as negative controls

• If available, test the antibody against purified recombinant proteins of YLR347W-A and its homologs

• Employ epitope mapping to determine the exact binding site of the antibody

Studies of antibodies targeting Y chromosome-encoded genes in humans highlight the importance of this step, as many commercial antibodies fail to distinguish between highly homologous gene products. Among 65 antibodies targeting Y chromosome genes, only two had disclaimers warning about potential cross-reactivity with X chromosome homologs, and only 3% provided validation data confirming negative results in female tissue .

What machine learning approaches can improve antibody-antigen binding prediction for YLR347W-A studies?

Recent advances in machine learning offer powerful approaches for antibody research:

• Library-on-library approaches: These methods probe many antigens against many antibodies to identify specific interacting pairs, which can be valuable for studying YLR347W-A interactions

• Active learning strategies: These can reduce experimental costs by starting with a small labeled dataset and iteratively expanding it based on model predictions

• Out-of-distribution prediction models: These are designed to predict interactions when test antibodies and antigens are not represented in training data

In a recent study, three out of fourteen active learning algorithms significantly outperformed random data selection, reducing the number of required antigen mutant variants by up to 35% and accelerating the learning process by 28 steps. These approaches can be adapted to YLR347W-A antibody research to improve binding prediction accuracy while minimizing experimental costs .

How should discrepancies in YLR347W-A localization between different antibodies be resolved?

When different antibodies against YLR347W-A yield conflicting localization results:

• Compare epitope regions of each antibody – different epitopes might be accessible in different cellular compartments

• Validate with genetic approaches – tag the endogenous protein with GFP or similar tags

• Use orthogonal methods – fractionation studies or mass spectrometry of isolated compartments

• Consider fixation artifacts – different fixation methods may affect epitope accessibility

• Test for post-translational modifications that might affect antibody recognition in specific compartments

Combining multiple approaches provides the most reliable data on protein localization. Document all relevant experimental conditions, as differences in strain background, growth conditions, or cell cycle stage can lead to genuine biological variation in localization patterns .

How can I quantitatively analyze YLR347W-A expression across different experimental conditions?

For accurate quantitative analysis of YLR347W-A expression:

• Western blot quantification:

  • Use housekeeping proteins (e.g., actin, tubulin) for normalization

  • Ensure signal is within linear range of detection

  • Use biological and technical replicates (minimum n=3)

  • Apply appropriate statistical tests (ANOVA, t-test)

• Immunofluorescence quantification:

  • Standardize image acquisition parameters

  • Use automated analysis software for unbiased quantification

  • Measure relative fluorescence intensity normalized to cell size

  • Analyze sufficient number of cells (typically >100)

• Flow cytometry (if applicable):

  • Gate properly on relevant cell populations

  • Use geometric mean of fluorescence intensity

  • Include appropriate controls for autofluorescence

Regardless of method, always report both the raw data and normalized values to ensure transparency and reproducibility of findings .

What controls are essential when developing an ELISA assay for detecting YLR347W-A?

When developing an ELISA for YLR347W-A detection:

• Positive controls:

  • Recombinant YLR347W-A protein at known concentrations

  • Lysates from wild-type yeast strains with confirmed expression

• Negative controls:

  • Lysates from YLR347W-A knockout strains

  • Buffer-only wells

  • Irrelevant antibody of same isotype and concentration

• Specificity controls:

  • Competitive inhibition with excess purified antigen

  • Pre-adsorption of antibody with purified antigen

• Validation parameters to establish:

  • Lower limit of detection (typically requiring signal 2-3 standard deviations above background)

  • Dynamic range of the assay

  • Inter- and intra-assay variation coefficients (<15% is generally acceptable)

The ELISA development approach demonstrated for Yellow Fever virus detection, where monoclonal antibodies enabled detection of viral antigens in samples containing approximately 1,000 focus-forming units, provides a model for developing sensitive detection assays .

How can I resolve contradictory results between antibody-based detection and genomic/transcriptomic data for YLR347W-A?

When antibody-based detection of YLR347W-A contradicts genomic or transcriptomic data:

• Verify antibody specificity using the validation approaches described earlier

• Consider post-transcriptional regulation:

  • mRNA stability may affect correlation between transcript and protein levels

  • Alternative splicing might generate isoforms not detected by all antibodies

  • RNA interference mechanisms might suppress translation

• Examine post-translational modifications:

  • Modifications may mask epitopes in certain cellular contexts

  • Some antibodies may preferentially recognize modified forms

• Check experimental conditions:

  • Different growth conditions may affect expression

  • Cell cycle-dependent expression may cause apparent discrepancies

• Integrate multiple data types:

  • Combine proteomics, transcriptomics, and antibody-based detection

  • Use CRISPR/Cas9 tagging to validate findings with orthogonal methods

What strategies can address weak or inconsistent YLR347W-A antibody signals?

For improving weak or inconsistent YLR347W-A antibody signals:

• Sample preparation optimization:

  • Test different lysis buffers (RIPA, NP-40, etc.)

  • Add phosphatase and protease inhibitors freshly

  • Reduce sample processing time to minimize degradation

• Antibody conditions:

  • Optimize antibody concentration through titration experiments

  • Test different incubation times and temperatures

  • Consider alternative blocking agents (BSA vs. milk)

  • Try signal amplification systems (biotin-streptavidin, tyramine)

• Detection enhancement:

  • Use more sensitive substrates for Western blotting

  • Increase exposure time (within linear range)

  • Try super-resolution microscopy for immunofluorescence

• Epitope retrieval for fixed samples:

  • Test different antigen retrieval methods (heat, pH, enzymatic)

  • Optimize fixation protocol to preserve epitope structure

Remember that the cellular abundance of many yeast proteins can vary significantly under different growth conditions, which may explain inconsistent detection across experiments .

How can I design experiments to determine the functional significance of YLR347W-A in yeast cells?

To determine the functional significance of YLR347W-A:

• Genetic approaches:

  • Generate knockout strains using CRISPR/Cas9 or traditional homologous recombination

  • Create conditional expression systems (e.g., GAL promoter)

  • Introduce point mutations to disrupt specific domains

• Phenotypic assays:

  • Growth curve analysis under various conditions

  • Stress response profiling (temperature, oxidative, osmotic)

  • Microscopic examination of cellular morphology

  • Cell cycle analysis using flow cytometry

• Interaction studies:

  • Affinity purification coupled with mass spectrometry (AP-MS)

  • Yeast two-hybrid screening

  • Proximity labeling approaches (BioID, APEX)

• Transcriptional profiling:

  • RNA-seq comparing wild-type and mutant strains

  • ChIP-seq if the protein might have DNA-binding properties

These approaches, combined with antibody-based detection methods, provide a comprehensive understanding of YLR347W-A function in cellular processes and regulatory networks .

What are the best practices for antibody storage and handling to maintain YLR347W-A antibody performance?

To maintain optimal YLR347W-A antibody performance:

• Storage conditions:

  • Store antibody aliquots at -20°C or -80°C for long-term stability

  • Avoid repeated freeze-thaw cycles (create single-use aliquots)

  • For working solutions, store at 4°C with preservatives (0.02% sodium azide)

• Handling precautions:

  • Never vortex antibody solutions (gentle mixing only)

  • Centrifuge briefly before opening to collect solution

  • Use appropriate pipette tips and clean tubes

  • Avoid contamination with bacteria or fungi

• Quality control:

  • Record lot numbers and compare performance between lots

  • Routinely test antibody against positive and negative controls

  • Monitor signal-to-noise ratio over time

  • Check expiration dates and storage conditions

• Documentation:

  • Maintain detailed records of antibody source, catalog number, and lot

  • Document dilution factors and incubation conditions that yield optimal results

  • Record any signs of deterioration for future reference

Proper storage and handling are essential for maintaining antibody specificity and sensitivity, particularly for long-term research projects requiring consistent reagent performance .