At3g22845 refers to a specific protein encoded by the Arabidopsis thaliana genome, identified by its locus tag on chromosome 3. This protein (UniProt: Q9LIL4) is found in mouse-ear cress (Arabidopsis thaliana), a widely used model organism in plant molecular biology. While detailed functional characterization is still ongoing, antibodies against this protein enable researchers to study its expression patterns, interactions, and potential roles in plant cellular processes .
The At3g22845 Antibody is a polyclonal antibody raised in rabbits using recombinant Arabidopsis thaliana At3g22845 protein as the immunogen. It is supplied in liquid form with 50% glycerol and 0.01M PBS (pH 7.4) buffer containing 0.03% Proclin 300 as a preservative. This antibody has been affinity-purified and is of IgG isotype. It is specifically designed to react with Arabidopsis thaliana specimens and has been validated for ELISA and Western Blot applications .
For optimal stability and performance, the At3g22845 Antibody should be stored at either -20°C or -80°C immediately upon receipt. The antibody is supplied in a storage buffer containing 50% glycerol, which helps prevent freezing damage. It's critical to avoid repeated freeze-thaw cycles as these can lead to protein denaturation and loss of antibody activity. When working with the antibody, aliquot the stock solution into smaller volumes to minimize freeze-thaw cycles for portions not immediately needed .
The At3g22845 Antibody has been specifically validated for ELISA (Enzyme-Linked Immunosorbent Assay) and Western Blot (WB) applications. These techniques allow researchers to detect and quantify the target protein in complex samples. ELISA provides quantitative detection of the target in solution, while Western Blot enables visualization of the protein's molecular weight and relative abundance in tissue or cell lysates. Both applications ensure proper identification of the antigen when used with appropriate controls and optimization .
For optimal Western Blot results with At3g22845 Antibody, follow this methodological approach:
Sample preparation:
Extract proteins from Arabidopsis tissues using an appropriate lysis buffer containing protease inhibitors
Quantify total protein concentration using Bradford or BCA assay
Prepare samples containing 20-50 μg total protein per lane
Gel electrophoresis and transfer:
Separate proteins on 10-12% SDS-PAGE
Transfer to PVDF or nitrocellulose membrane (0.45 μm pore size recommended)
Immunoblotting:
Block membrane with 5% non-fat milk in TBST for 1 hour at room temperature
Dilute At3g22845 Antibody 1:1000 to 1:2000 in blocking solution
Incubate membrane with diluted antibody overnight at 4°C
Wash 3-5 times with TBST
Incubate with HRP-conjugated anti-rabbit secondary antibody
Develop using chemiluminescent substrate and document results
Controls:
To optimize ELISA protocols with At3g22845 Antibody:
Coating conditions:
Determine optimal antigen concentration (typically 1-10 μg/ml) for coating plates
Use carbonate/bicarbonate buffer (pH 9.6) for coating
Incubate overnight at 4°C for efficient binding
Antibody dilution optimization:
Perform a titration series of At3g22845 Antibody (1:500 to 1:10,000)
Select the dilution providing the best signal-to-noise ratio
Sample preparation:
Ensure consistent sample processing to minimize variability
Consider using calibration curves with recombinant protein standards
Detection system:
Use HRP-conjugated anti-rabbit secondary antibody at manufacturer's recommended dilution
Develop with TMB substrate and measure absorbance at 450 nm
Quality control:
Addressing specificity concerns requires methodical validation:
Experimental validation approaches:
Compare signal between wild-type and knockout/knockdown plant lines
Perform pre-adsorption tests using recombinant At3g22845 protein
Analyze peptide competition assays to confirm epitope specificity
Cross-reactivity assessment:
Test the antibody against related Arabidopsis proteins
Examine signal in non-Arabidopsis plant species to confirm specificity
Signal verification methods:
Compare detection patterns with published gene expression data
Validate results using orthogonal methods (e.g., mass spectrometry)
Confirm protein size matches predicted molecular weight
Positive controls:
| Challenge | Potential Causes | Resolution Strategies |
|---|---|---|
| Weak or no signal | Insufficient protein, antibody degradation, inefficient transfer | Increase protein loading (50-100 μg), verify antibody activity with positive control, optimize transfer conditions |
| Multiple bands | Cross-reactivity, protein degradation, post-translational modifications | Increase blocking stringency, add protease inhibitors during extraction, validate with knockout controls |
| High background | Insufficient blocking, contaminated buffers, excessive antibody | Increase blocking time (overnight at 4°C), prepare fresh buffers, further dilute primary antibody |
| Inconsistent results | Variable sample preparation, inconsistent transfer, antibody batch variation | Standardize extraction protocol, use internal loading controls, create large antibody aliquots from single lot |
Applying these troubleshooting approaches systematically will help resolve common technical issues when working with At3g22845 Antibody .
When faced with contradictory Western Blot results:
Evaluate technical variables:
Verify consistent sample preparation methods across experiments
Confirm protein quantification accuracy using multiple methods
Assess gel percentage appropriateness for target protein size
Check transfer efficiency using reversible staining methods
Biological considerations:
Examine if growth conditions, developmental stages, or treatments differed
Consider post-translational modifications affecting antibody recognition
Evaluate potential protein isoforms or splice variants
Analytical approach:
Quantify band intensity using appropriate normalization controls
Perform statistical analysis across biological replicates
Compare results with published literature and database information
Validation strategies:
Integration of At3g22845 Antibody with complementary techniques enhances research depth:
Immunohistochemistry/Immunofluorescence:
Optimize fixation conditions for plant tissues (4% paraformaldehyde recommended)
Test antibody dilutions between 1:100-1:500
Use confocal microscopy to determine subcellular localization of At3g22845
Co-immunoprecipitation (Co-IP):
Use At3g22845 Antibody coupled to protein A/G beads
Identify interaction partners through mass spectrometry analysis
Verify interactions with reciprocal Co-IP experiments
Chromatin Immunoprecipitation (ChIP):
If At3g22845 has DNA-binding properties, optimize crosslinking conditions
Enrich At3g22845-bound DNA fragments for sequencing analysis
Validate binding sites with reporter gene assays
Proteomics integration:
When designing protein interaction studies:
Experimental design considerations:
Select appropriate protein extraction buffers to preserve interactions
Consider native vs. denaturing conditions based on research questions
Include appropriate negative controls (IgG, unrelated antibodies)
Co-IP optimization:
Test different lysis conditions (detergent types/concentrations)
Optimize antibody amounts and incubation times
Consider crosslinking to stabilize transient interactions
Validation approaches:
Confirm interactions through reverse Co-IP experiments
Implement orthogonal methods (yeast two-hybrid, FRET)
Perform domain mapping to identify interaction interfaces
Functional verification:
Applying At3g22845 Antibody to study physiological processes:
Experimental design for stress studies:
Expose plants to controlled stress conditions (drought, salt, pathogen)
Collect samples at multiple time points (0, 6, 12, 24, 48 hours)
Process samples consistently for protein extraction
Use At3g22845 Antibody to track protein abundance changes via Western Blot
Developmental analysis approach:
Collect tissues from different developmental stages
Quantify At3g22845 protein levels relative to housekeeping controls
Correlate protein abundance with phenotypic changes
Compare with transcriptomic data to assess transcriptional vs. post-transcriptional regulation
Tissue-specific expression:
Optimize immunohistochemistry protocols for different plant tissues
Map protein localization patterns throughout development
Compare with promoter-reporter studies for comprehensive expression analysis
Functional studies:
Emerging technologies offering new possibilities include:
Advanced microscopy applications:
Super-resolution microscopy for precise subcellular localization
Live-cell imaging using nanobody derivatives
Correlative light and electron microscopy for ultrastructural context
Proximity labeling approaches:
BioID or APEX2 fusions to identify proximal proteins in native cellular context
Spatially-resolved proteomic mapping within specific cellular compartments
Temporal tracking of protein interaction networks during stress response
Single-cell applications:
Adapting antibody for single-cell western blot technologies
Integration with single-cell proteomics approaches
Spatial transcriptomics correlation with protein localization
Computational integration:
When validating protocol modifications:
Systematic optimization approach:
Modify only one variable at a time
Include standard protocol controls alongside modifications
Quantify signal-to-noise ratio improvements objectively
Validation requirements:
Demonstrate reproducibility across multiple biological replicates
Verify specificity is maintained or improved
Ensure modifications do not introduce artifacts
Documentation and reporting:
Record detailed procedural changes and supporting evidence
Include comparative data showing improvement over standard protocols
Specify critical parameters affecting reproducibility
Cross-validation strategies:
When integrating protein and transcriptomic data:
Methodological considerations:
Account for temporal delays between transcription and translation
Consider post-transcriptional regulatory mechanisms
Normalize data appropriately for cross-platform comparisons
Statistical approach:
Calculate correlation coefficients between mRNA and protein levels
Perform time-series analysis to identify regulatory patterns
Implement multivariate analysis to identify factors affecting correlation
Biological interpretation:
Investigate discrepancies as potential regulatory mechanisms
Consider protein stability and turnover rates
Evaluate the impact of post-translational modifications
Integrated analysis framework: