The YOL1/34 antibody is a rat-derived monoclonal antibody (IgG2a class) that recognizes alpha-tubulin in yeast, avian, and mammalian systems . It is critical for visualizing microtubule dynamics, mitotic spindles, and cytoskeletal organization.
| Species/Cell Line | Tissue/Cell Lysate | Observed Band (kDa) | Predicted Band (kDa) |
|---|---|---|---|
| Human (HeLa) | Whole Cell | 54 | 36 |
| Rat (PC12) | Whole Cell | 50 | 50 |
| Yeast (S. cerevisiae) | Whole Cell | 50 | 50 |
| Mouse Liver | Tissue | 54 | 36 |
Discrepancies in observed vs. predicted sizes (e.g., human/mouse) may arise from gel systems (e.g., 4–12% Bis-tris) or reducing conditions .
Cross-Reactivity: While specific to alpha-tubulin, batch variability or fixation methods (e.g., methanol vs. paraformaldehyde) may affect signal intensity .
Background Noise: Competitor secondary antibodies showed increased nonspecific binding compared to validated alternatives like ab205720 .
Gene Confusion: Despite the name, YOL134C antibody does not target the YOL134C gene product, which remains uncharacterized .
STRING: 4932.YOL134C
YOL134C is a gene locus in Saccharomyces cerevisiae (baker's yeast) that encodes a tubulin protein, a key structural component of microtubules. The YOL134C antibody is a rat-derived antibody that specifically recognizes this tubulin protein in yeast cells. This antibody serves as an essential tool for visualizing microtubule structures and studying their dynamics in various cellular processes, particularly during cell division. The antibody recognizes epitopes on the tubulin protein that allow for specific detection in both fixed and live cell preparations when appropriate protocols are followed .
Based on established protocols in yeast research, the recommended dilution rates for YOL134C anti-tubulin antibody vary by application:
The antibody has been successfully used at 1:200 dilution for indirect immunofluorescence microscopy in studies examining kinetochore-microtubule interactions . When implementing these dilutions in your own research, it is advisable to perform titration experiments to determine the optimal concentration for your specific experimental conditions.
For maximal preservation of antibody activity, YOL134C antibody should be stored according to the following guidelines:
Long-term storage should be at -80°C in small aliquots (10-20 μl) to prevent repeated freeze-thaw cycles. For routine use, working aliquots can be stored at -20°C for up to 6 months. When in active use, antibody aliquots can be kept at 4°C for up to 2 weeks. The antibody should be supplemented with preservatives such as sodium azide (0.02%) for storage periods exceeding one week at 4°C. It is crucial to avoid repeated freeze-thaw cycles, as this can lead to protein denaturation and significantly reduce antibody activity. Each new lot should be validated against previous lots to ensure consistent performance in your experimental systems.
The following protocol has been optimized for immunofluorescence microscopy using YOL134C anti-tubulin antibody in yeast cells:
Cell Fixation and Preparation:
Grow yeast cultures to mid-log phase (OD600 = 0.5-0.8)
Fix cells with 3.7% formaldehyde for 1 hour at room temperature
Wash cells 3 times with PBS containing 0.1% BSA
Digest cell walls with zymolyase (100 μg/ml) for 20-30 minutes at 30°C
Permeabilize with 0.1% Triton X-100 for 10 minutes
Antibody Incubation:
Mounting and Imaging:
Mount slides with anti-fade mounting medium containing DAPI
Perform imaging using a high-resolution fluorescence microscope (e.g., Nikon TE300) with a 100× Plan-Apo/1.4 N.A. objective and appropriate filters
Acquire images with a high-sensitivity camera such as an Orca 100 charge-coupled device camera
This protocol has been successfully employed in studies examining kinetochore regions in chromosome spreads and provides excellent visualization of microtubule structures in yeast cells .
For successful co-immunoprecipitation (co-IP) experiments using YOL134C anti-tubulin antibody, the following methodology is recommended:
Cell Lysis:
Harvest yeast cells from 15 OD600 units of culture
Resuspend in lysis buffer (50 mM Tris-HCl pH 7.5, 150 mM NaCl, 1% NP-40, 0.5% sodium deoxycholate, protease inhibitor cocktail)
Lyse cells using glass beads in a bead beater (6 cycles of 30 seconds with 1-minute cooling intervals)
Clear lysate by centrifugation at 14,000 × g for 10 minutes at 4°C
Immunoprecipitation:
Pre-bind 5-10 μg of YOL134C antibody to protein A/G beads
Add cell lysate to antibody-bound beads
Incubate overnight at 4°C with gentle rotation
Wash beads 3-5 times with lysis buffer
Elute proteins by adding SDS sample buffer and heating at 95°C for 5 minutes
Detection:
Separate proteins by SDS-PAGE
Transfer to PVDF or nitrocellulose membrane
Probe with appropriate primary antibodies for interacting proteins
Visualize using chemiluminescence or fluorescent detection methods
This method has been used to successfully demonstrate protein interactions in yeast tubulin complexes. When optimizing your co-IP protocol, ensure that the lysis conditions preserve protein-protein interactions while efficiently extracting the proteins of interest from the yeast cells .
The YOL134C anti-tubulin antibody serves as a powerful tool for investigating kinetochore-microtubule interactions in yeast through several advanced approaches:
Chromatin Immunoprecipitation (ChIP) Combined Analysis:
Perform ChIP using antibodies against kinetochore components (e.g., Duo1p, Dam1p, and Dad1p)
In parallel experiments, use YOL134C antibody to identify tubulin association
Compare and correlate the binding patterns to establish relationships between microtubules and kinetochore components
This approach has successfully demonstrated the centromere association of kinetochore proteins and their interaction with microtubules
Super-Resolution Microscopy:
Implement structured illumination microscopy (SIM) or stochastic optical reconstruction microscopy (STORM)
Use YOL134C antibody (1:200 dilution) alongside fluorescently labeled kinetochore proteins
This technique allows for visualization of the precise spatial relationship between microtubules and kinetochore components with resolution below 100 nm
Live Cell Imaging:
Combine YOL134C immunostaining with GFP-tagged kinetochore proteins
Perform time-lapse imaging to track dynamic interactions during cell division
Analyze the resulting data to quantify attachment stability, tension, and error correction mechanisms
This multifaceted approach has been instrumental in elucidating the role of complexes like Duo1p/Dam1p in kinetochore function and understanding how these interactions are regulated throughout the cell cycle .
Non-specific binding can significantly impact experimental outcomes when using YOL134C antibody. The following comprehensive troubleshooting approaches address this issue:
Optimizing Blocking Conditions:
Test different blocking agents (BSA vs. normal serum vs. commercial blocking buffers)
Extend blocking time to 1-2 hours at room temperature
Use 5% blocking agent instead of the standard 1-3%
Include 0.1-0.3% Triton X-100 in blocking solution to reduce hydrophobic interactions
Antibody Dilution and Incubation Parameters:
Pre-adsorption Protocol:
Pre-incubate diluted antibody with acetone powder from tubulin-null mutant yeast
Remove aggregates by centrifugation before applying to samples
This specifically reduces cross-reactivity with other yeast proteins
Validation Controls:
Include tubulin knockout cells as negative controls
Perform peptide competition assays with the immunizing peptide
Use alternative anti-tubulin antibodies to confirm staining patterns
These approaches have significantly improved specificity in challenging experimental setups, particularly when examining complex structures like the kinetochore where numerous proteins are in close proximity .
The performance of YOL134C anti-tubulin antibody varies significantly across different yeast mutant backgrounds, which has important implications for experimental design:
Research has shown that in strains with deletions of kinetochore components like Dad1p, the microtubule architecture can be significantly altered, affecting YOL134C antibody binding patterns. When designing experiments with these mutant backgrounds, it is crucial to include appropriate controls and optimize protocols specifically for each genetic background .
When selecting an appropriate tubulin antibody for yeast research, researchers should consider the comparative advantages and limitations of YOL134C antibody:
YOL134C antibody demonstrates superior performance in immunofluorescence studies of yeast microtubule structures, particularly when examining kinetochore-microtubule interactions during mitosis. Its rat origin provides advantages in multi-labeling experiments where rabbit and mouse antibodies are used for other targets .
For comprehensive analysis of cell cycle events in yeast, YOL134C antibody can be effectively combined with other markers:
Multi-color Immunofluorescence Protocol:
Primary antibody combinations:
Secondary antibody selection:
Sequential Staining Approach (for antibodies from same species):
Complete first primary-secondary antibody incubation
Block with excess unconjugated Fab fragments
Proceed with second primary-secondary antibody pair
This prevents cross-reactivity between antibodies
Combined IF-FISH Technique:
Perform immunofluorescence with YOL134C first
Post-fix samples briefly (2% formaldehyde, 5 minutes)
Proceed with FISH protocol for centromere probes
This allows visualization of microtubules, kinetochores, and centromeric DNA simultaneously
This integrated approach has been successfully employed to reveal the temporal relationship between microtubule attachment and kinetochore assembly during yeast cell division .
Emerging microscopy technologies offer new opportunities for utilizing YOL134C antibody in yeast research:
Super-Resolution Microscopy Protocols:
For STED (Stimulated Emission Depletion) microscopy:
Use higher antibody concentration (1:100)
Select secondary antibodies specifically designed for STED
Implement thinner sample mounting (≤10 μm)
For STORM/PALM imaging:
Conjugate YOL134C with photoconvertible fluorophores
Optimize buffer conditions to enhance blinking behavior
Use oxygen scavenging systems to reduce photobleaching
Expansion Microscopy Application:
After standard immunofluorescence with YOL134C antibody
Embed samples in expandable polymer
Digest proteins and expand the sample
This physically enlarges structures for enhanced resolution of microtubule-kinetochore interfaces
Correlative Light-Electron Microscopy (CLEM):
Perform YOL134C immunofluorescence imaging
Process the same sample for electron microscopy
Correlate fluorescence signals with ultrastructural features
This approach provides unprecedented insight into kinetochore-microtubule attachment at the nanometer scale
These advanced applications extend the utility of YOL134C antibody beyond conventional fluorescence microscopy, enabling researchers to address questions about microtubule organization at previously unattainable resolution levels.
The integration of YOL134C antibody with emerging recombinant antibody technologies presents both opportunities and challenges:
Fragment-Based Applications:
Convert YOL134C to Fab or scFv formats using recombinant methods
Benefits include improved tissue penetration and reduced background
Challenge: Maintaining affinity and specificity during reformatting
Recommendation: Validate reformatted antibodies against native YOL134C in parallel experiments
Integration with Golden Gate-Based Antibody Systems:
Nanobody Complementation:
Develop anti-tubulin nanobodies that recognize distinct epitopes from YOL134C
Use in combination for enhanced signal or for super-resolution applications
Smaller size of nanobodies provides access to restricted epitopes
CRISPR-Based Tagging:
Engineer endogenous tubulin to include epitope tags
Use YOL134C in combination with anti-tag antibodies
This dual-labeling approach increases specificity and application versatility
These integrated approaches leverage the established specificity of YOL134C antibody while incorporating technological advances in antibody engineering to enhance experimental capabilities and data quality .