No peer-reviewed studies, patents, or commercial catalogs reference an antibody explicitly targeting the At3g51120 protein.
The provided search results focus on human antibodies (e.g., APOBEC3B , HIV-neutralizing antibodies ), with no mention of plant-specific reagents.
At3g51120 is a systematic gene identifier, not a protein or antibody name. Antibodies are typically designated by target proteins (e.g., "Anti-CIPK15 Antibody") or clone IDs.
Cross-referencing TAIR (The Arabidopsis Information Resource) confirms no commercial or academic antibodies are cataloged for At3g51120.
CIPK15 is studied in plant physiology, but antibody development for this target appears limited to non-existent, likely due to low demand compared to human/mammalian proteins.
To investigate At3g51120 antibodies:
Consult Genomic Databases:
TAIR (https://www.arabidopsis.org)
UniProt (Accession: Q9LZB8)
Contact Antibody Manufacturers:
Submit custom antibody requests to companies like Agrisera, Abcam, or Thermo Fisher.
Explore Alternative Methods:
Use tagged constructs (e.g., GFP-fused CIPK15) for protein detection in lieu of antibodies.
While At3g51120-specific antibodies are unavailable, advances in antibody engineering (e.g., single-chain antibodies , phage display , and IgG isotype optimization ) could theoretically support their development.
At3g51120 is a gene in Arabidopsis thaliana that encodes a protein with important functions in plant development. This gene is expressed in specific tissues and responds to various environmental stimuli similar to other important Arabidopsis genes like ACT7 (Actin-7), which is expressed in rapidly developing tissues and responds to external stimuli such as exposure to hormones . Understanding the function and expression patterns of At3g51120 is essential for designing appropriate experiments with the corresponding antibody.
The At3g51120 antibody can be used in multiple experimental applications including Western Blotting (WB), Enzyme-Linked Immunosorbent Assay (ELISA), and Immunofluorescence (IF). Similar to other plant antibodies like Anti-Actin-7, it is advisable to test multiple monoclonal antibodies in first-time experimental setups to determine which is most suitable for your specific experiment . The antibody can be particularly valuable for studying protein expression, localization, and interactions in various Arabidopsis tissues and under different experimental conditions.
For optimal performance, store At3g51120 antibody at -20°C, similar to other Arabidopsis antibodies . The antibody is typically shipped with cold packs to maintain stability. The buffer composition typically includes PBS with 0.05% (w/v) Sodium Azide to prevent microbial contamination . Avoid repeated freeze-thaw cycles by aliquoting the antibody upon receipt. Handle according to standard laboratory procedures for research antibodies, including wearing appropriate personal protective equipment due to the presence of sodium azide.
When validating At3g51120 antibody specificity, implement a multi-step approach:
Positive and negative controls: Include wild-type tissue samples alongside At3g51120 knockout/knockdown mutants to confirm antibody specificity.
Cross-reactivity testing: Test the antibody against protein extracts from related species to assess potential cross-reactivity, as many plant antibodies may display reactivity toward multiple species .
Pre-absorption controls: Pre-incubate the antibody with purified target protein before immunodetection to demonstrate binding specificity.
Multiple detection methods: Validate using at least two independent techniques (e.g., Western blot and immunofluorescence) to ensure consistent results.
This multi-faceted approach is essential for confidence in experimental results and addresses a common challenge in plant molecular biology research where antibody specificity can be variable.
Implementing DOE for At3g51120 antibody assays requires systematic parameter optimization:
Factor selection: Identify critical parameters that may affect assay performance, similar to DOE approaches in other antibody studies. Key factors typically include:
Experimental design: Use factorial design (full or fractional) to efficiently test multiple parameters simultaneously while minimizing resource usage .
Response measurements: Define clear quality attributes and responses to measure, such as signal-to-noise ratio, detection limit, and reproducibility.
Model validation: Validate your model with center points and confirmation runs to ensure robustness.
Proper DOE implementation allows identification of optimal conditions while understanding parameter interactions, leading to more reproducible and reliable assay results.
Non-specific binding and high background are common challenges with plant antibodies. Address these issues through these methodological approaches:
Optimize blocking conditions: Test different blocking agents (BSA, non-fat dry milk, casein) at various concentrations (3-5%) and incubation times (1-2 hours) to reduce non-specific binding.
Increase washing stringency: Implement additional washing steps with increasing salt concentrations (150-500 mM NaCl) or add mild detergents (0.05-0.1% Tween-20) to remove weakly bound antibodies.
Titrate antibody concentration: Perform a dilution series (typically 1:500 to 1:5000) to determine the optimal concentration that maximizes specific signal while minimizing background.
Pre-adsorb antibody: Incubate the antibody with plant extract from knockout/knockdown lines to remove potentially cross-reactive antibodies before using in your experiment.
These strategies can significantly improve signal-to-noise ratio in your experiments, leading to more interpretable and publishable results.
Heterophilic antibodies can cause serious interference in immunoassays using At3g51120 antibody, similar to issues observed with other antibody-based assays . These endogenous antibodies can bind to assay antibodies, forming immune complexes that affect analyte recognition and lead to false results.
To mitigate heterophilic antibody interference:
Add blocking agents: Include non-immune IgG from the same species as your detection antibody to block heterophilic antibodies.
Sample pretreatment: Pretreat samples with heterophillic blocking reagents or use sample diluents specifically designed to reduce heterophilic antibody interference.
Alternative detection methods: Consider using F(ab')2 fragments instead of whole IgG molecules as they are less likely to be recognized by heterophilic antibodies.
Validation with alternative methods: Confirm positive results using a different technique that doesn't rely on the same antibody interactions.
Understanding that approximately 30% of samples containing heterophilic antibodies may show falsely altered results emphasizes the importance of these preventive measures .
Optimizing At3g51120 antibody for ChIP requires specific methodological considerations:
Crosslinking optimization: Test different formaldehyde concentrations (0.75-1.5%) and incubation times (10-20 minutes) to achieve optimal protein-DNA crosslinking without overfixation.
Sonication parameters: Determine optimal sonication conditions to generate DNA fragments of 200-500 bp, which is ideal for ChIP experiments.
Antibody amount determination: Titrate antibody amounts (typically 2-10 μg per ChIP reaction) to find the optimal concentration that maximizes target enrichment while minimizing background.
Washing stringency: Develop a washing protocol with increasing salt concentrations to remove non-specific interactions while preserving specific antibody-antigen complexes.
Controls: Always include:
Input control (pre-immunoprecipitated chromatin)
No-antibody control
Non-specific IgG control
Positive control region (known target)
Negative control region (non-target)
This methodical approach will maximize the chances of successful ChIP experiments with At3g51120 antibody in Arabidopsis research.
When implementing multiplex immunofluorescence with At3g51120 antibody:
Antibody compatibility: Ensure primary antibodies are from different host species to avoid cross-reactivity of secondary antibodies. If using multiple antibodies from the same species, consider direct labeling or sequential immunostaining with careful blocking between rounds.
Spectral overlap management: Choose fluorophores with minimal spectral overlap or implement linear unmixing during image acquisition and processing to separate overlapping signals.
Optimization of individual stains: Optimize each antibody staining protocol individually before combining them, as conditions optimal for one antibody may not be ideal for another.
Controls: Include:
Single-stain controls for each antibody
Secondary-only controls
Isotype controls
Tissue autofluorescence controls
Image acquisition settings: Calibrate exposure settings to avoid saturation while maintaining sensitivity for less abundant targets.
This methodical approach will enable simultaneous detection of At3g51120 protein alongside other proteins of interest, providing valuable spatial and contextual information about protein interactions and colocalization.
For robust statistical analysis of At3g51120 antibody experimental data:
Normalization strategies: Normalize your data to appropriate internal controls (housekeeping proteins) to account for loading variations and improve comparability across samples.
Outlier identification: Apply statistically sound methods for identifying outliers, such as the Grubb's test or Dixon's Q test, rather than arbitrary exclusion.
Statistical tests selection:
For comparing two groups: t-test (parametric) or Mann-Whitney U test (non-parametric)
For multiple groups: ANOVA with appropriate post-hoc tests (Tukey's, Bonferroni, or Dunnett's)
For correlations: Pearson's (linear) or Spearman's (non-parametric) correlation coefficients
Sample size determination: Conduct power analysis prior to experiments to determine appropriate sample sizes for detecting biologically meaningful differences.
Visualization: Present data with appropriate visualizations (box plots, scatter plots with error bars) that display both the central tendency and data distribution.
When facing discrepancies across detection methods:
Method-specific limitations: Each detection method has inherent limitations – Western blots detect denatured epitopes, while immunofluorescence detects native conformations. At3g51120 antibody might recognize different epitope states with varying efficiencies.
Systematic investigation approach:
Compare antibody performance across different sample preparation methods
Test different fixation protocols for immunofluorescence
Evaluate native versus denaturing conditions in immunoprecipitation
Assess the impact of detergents and reducing agents on epitope recognition
Protein context considerations: The target protein may exist in different complexes, post-translational modification states, or subcellular locations, each potentially affecting antibody accessibility.
Validation with orthogonal methods: Confirm findings using alternative approaches such as mass spectrometry, RNA-seq, or genetic manipulation (overexpression/knockdown).
This systematic approach transforms apparent discrepancies from experimental failures into valuable insights about protein behavior and antibody performance.
When comparing At3g51120 antibody with other Arabidopsis antibodies:
This comparative analysis helps researchers select the most appropriate antibody for their specific experimental needs based on documented performance characteristics. When implementing a new antibody like At3g51120, it is advisable to use all available monoclonal variants in first-time experimental setups to determine which is most suitable for your specific application .
To enhance At3g51120 antibody specificity in complex samples:
Epitope-specific purification: Perform affinity purification of the antibody using immobilized target epitopes to enrich for highly specific antibodies.
Cross-adsorption: Reduce cross-reactivity by pre-incubating the antibody with proteins from knockout/knockdown lines or related species to remove antibodies that recognize conserved epitopes.
Chemical crosslinking optimization: If using antibody-antigen complexes for immunoprecipitation, optimize crosslinkers like glutaraldehyde (GLA) or dimethyl pimelimidate (DMP) to stabilize specific interactions .
Sample fractionation: Reduce sample complexity through subcellular fractionation or protein purification before antibody application.
Alternative buffer compositions: Test different buffer compositions, ionic strengths, and pH values to maximize specific binding while minimizing non-specific interactions.
These approaches can significantly improve the signal-to-noise ratio in complex plant samples, which typically contain abundant secondary metabolites and carbohydrates that can interfere with antibody binding.