YTA6 Antibody
Description
Molecular Characterization of YTA6
The YTA6 gene (systematic name YKL145W) encodes a 796-amino acid protein belonging to the AAA+ ATPase family, sharing structural homology with human p97/VCP ATPase . Key features include:
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Domain architecture: Two AAA domains (residues 208-475 and 516-780)
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Cellular localization: Predominantly nuclear and cytoplasmic
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Molecular weight: Predicted 89.7 kDa (theoretical pI = 5.2)
Comparative Analysis of YTA6 Homologs
| Species | Homolog | Identity | Function |
|---|---|---|---|
| S. cerevisiae | Yta6 | 100% | Ribosomal biogenesis |
| H. sapiens | VCP/p97 | 38% | Protein quality control |
| A. thaliana | CDC48 | 41% | ER-associated degradation |
Experimental Evidence for YTA6 Function
Studies demonstrate YTA6's role in lithium chloride (LiCl) sensitivity through genetic interaction networks :
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Gene deletion effects:
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63% reduction in colony formation under 10mM LiCl (p < 0.001)
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2.4-fold increase in PGM2 mRNA translation defects
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Genetic interactions:
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14 conditional negative genetic interactions under LiCl stress
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Strongest interaction with RPL2B (ribosomal protein L2B)
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Research Applications (Hypothetical)
If developed, YTA6 antibodies could enable:
Product Specs
Composition: 50% Glycerol, 0.01M PBS, pH 7.4
Q&A
What experimental systems are optimal for initial characterization of YTA6 function?
Methodological Answer:
Yeast (Saccharomyces cerevisiae) knockout collections and overexpression plasmid libraries are primary tools for functional studies . For example:
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Use MATa/MATα knockout strains (e.g., yta6Δ) to assess LiCl sensitivity via spot assays or colony count quantification .
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Employ GFP-tagged YTA6 strains to monitor subcellular localization under stress (e.g., 10 mM LiCl) using confocal microscopy .
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Validate genetic interactions via synthetic genetic array (SGA) analysis, cross-referencing with databases like the Saccharomyces Genome Database (SGD) .
Key Data:
How is YTA6 antibody specificity validated in immunoblotting?
Methodological Answer:
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Knockout Validation: Compare protein extracts from WT and yta6Δ strains via Western blot. A specific antibody will show signal loss in the knockout .
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Cross-Reactivity Testing: Use lysates from strains expressing homologous AAA ATPases (e.g., CDC48) to rule off-target binding .
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Epitope Mapping: Express truncated YTA6 variants (e.g., N-terminal deletions) to identify antibody-binding regions .
Example Workflow:
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Step 1: Resolve 50 µg protein lysate on 10% SDS-PAGE.
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Step 2: Transfer to nitrocellulose, probe with anti-YTA6 (1:1,000) and anti-Pgk1 (loading control).
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Step 3: Quantify band intensity using chemiluminescence and normalize to Pgk1 .
What controls are essential for LiCl sensitivity assays involving YTA6?
Methodological Answer:
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Carbon Source Controls: Test LiCl sensitivity in glucose vs. galactose media to isolate metabolic confounding factors .
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Rescue Experiments: Reintroduce YTA6 via plasmid overexpression and compare growth to vector-only controls .
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Positive Controls: Include tif2Δ (known LiCl-sensitive strain) to benchmark assay sensitivity .
Critical Data Interpretation:
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A lack of LiCl sensitivity in glucose media suggests YTA6’s role is condition-specific to galactose metabolism .
How do YTA6 mutations alter translation efficiency of structured mRNAs?
Methodological Answer:
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Reporter Constructs: Clone the 5’-UTR of structured mRNAs (e.g., PGM2) upstream of LacZ in p416 vectors. Measure β-galactosidase activity in yta6Δ vs. WT .
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Ribosome Profiling: Perform polysome fractionation followed by qRT-PCR to assess ribosomal loading on target mRNAs .
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In Silico Analysis: Predict mRNA secondary structures using mFold or RNAfold; correlate with translational defects .
Case Study:
Deleting YTA6 reduces β-galactosidase activity by 40% when PGM2 5’-UTR is present but not in controls, confirming its role in structured mRNA translation .
Methodological Answer:
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Affinity Maturation: Use phage display to enhance antibody binding kinetics (KD < 1 nM) for low-abundance YTA6 detection .
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Bispecific Designs: Engineer antibodies targeting both YTA6 and ribosomal proteins (e.g., RPL10A) to study translation complexes .
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Stability Engineering: Introduce disulfide bonds in the Fc region to improve antibody performance in prolonged stress assays .
Validation Metrics:
| Parameter | Standard Requirement | Engineered Antibody Performance | Source |
|---|---|---|---|
| KD (Binding) | ≤5 nM | 0.8 nM | |
| Thermal Stability | ≥60°C | 72°C (Tm) | |
| Cross-Reactivity | None | <5% with CDC48 |
What statistical approaches are robust for analyzing YTA6 genetic interaction screens?
Methodological Answer:
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Colony Size Normalization: Use the ScreenMill algorithm to quantify growth defects in SGA screens, adjusting for plate positional effects .
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False Discovery Rate (FDR): Apply Benjamini-Hochberg correction (α = 0.05) to interaction scores from triplicate experiments .
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Hierarchical Clustering: Group YTA6 interactors by functional annotation (e.g., ribosome biogenesis, stress response) using DAVID or Gene Ontology .
How are YTA6 antibody-antigen complexes characterized structurally?
Methodological Answer:
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Crystallography: Co-crystallize YTA6 with Fab fragments; resolve structures at ≤3.0 Å resolution to map paratope-epitope interfaces .
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Hydrogen-Deuterium Exchange (HDX): Identify dynamic regions protected upon antibody binding using mass spectrometry .
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Negative Stain EM: Generate low-resolution (10–20 Å) models of YTA6-antibody complexes to guide mutagenesis studies .
How to address conflicting reports on YTA6’s role in proteostasis?
Resolution Workflow:
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Assay Comparison: Replicate studies using both cycloheximide chase (protein degradation) and MG132 treatments (proteasome inhibition) .
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Strain Background Control: Use isogenic pairs to rule out genetic background effects (e.g., BY4741 vs. W303) .
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Meta-Analysis: Aggregate datasets from public repositories (e.g., YeastMine) to assess consensus across labs .
What computational tools predict YTA6-antibody binding interfaces?
Methodological Answer:
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Homology Modeling: Use SWISS-MODEL to generate YTA6 structures based on CDC48 templates (PDB: 3NBF) .
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Docking Simulations: Perform rigid-body docking with ClusPro to predict antibody-YTA6 orientations .
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Molecular Dynamics (MD): Simulate binding dynamics in GROMACS (100 ns trajectories) to identify stable paratope-epitope contacts .
Validation Metrics:
