The At2g19630 antibody is associated with a specific gene in Arabidopsis thaliana, a model organism widely used in plant biology. This antibody targets proteins encoded by the At2g19630 gene, which plays a crucial role in various physiological and developmental processes in plants. The understanding of this antibody is essential for researchers studying plant genetics, signaling pathways, and responses to environmental stimuli.
The At2g19630 gene encodes a protein involved in the regulation of plant responses to stress and development. Studies have shown that this protein is expressed in various tissues, indicating its potential role in multiple biological processes.
Expression Patterns: The At2g19630 protein is predominantly expressed in roots and leaves, suggesting its involvement in growth and stress response mechanisms.
Characterization of the At2g19630 antibody has revealed important properties that are vital for its application in research.
| Property | Details |
|---|---|
| Type | Monoclonal antibody |
| Target | At2g19630 protein |
| Species Reactivity | Arabidopsis thaliana |
| Applications | Western blotting, immunohistochemistry |
| Concentration | Typically used at 1:500 dilution |
The At2g19630 antibody has been utilized in various studies to elucidate the function of the corresponding protein.
Western Blot Analysis: Used to detect the presence of the At2g19630 protein in plant extracts, confirming its expression levels under different stress conditions.
Immunohistochemistry: Applied to visualize the localization of the At2g19630 protein within plant tissues, providing insights into its functional roles.
The research surrounding the At2g19630 antibody contributes significantly to our understanding of plant biology. Insights gained from studies utilizing this antibody can help elucidate mechanisms of stress tolerance, growth regulation, and developmental processes in plants.
Understanding how the At2g19630 protein functions under stress conditions can lead to advancements in agricultural practices, particularly in developing crops that are more resilient to environmental challenges such as drought or salinity.
Further research is needed to explore:
The specific pathways regulated by the At2g19630 protein.
Potential interactions with other proteins involved in stress response.
The role of post-translational modifications on the function of the At2g19630 protein.
At2g19630 refers to a gene in Arabidopsis thaliana that encodes an F-box and associated interaction domains-containing protein according to the Araport11 database . The antibody against At2g19630 is designed to specifically recognize and bind to this protein. F-box proteins are crucial components of the SCF (Skp1-Cullin-F-box) complex, which facilitates protein ubiquitination and subsequent degradation through the proteasome pathway. These proteins play essential roles in various cellular processes including cell cycle regulation, signal transduction, and developmental processes in plants.
The At2g19630 antibody is typically a rabbit polyclonal antibody purified by antigen affinity chromatography, designed to detect this specific F-box protein in plant samples . The target epitope is generally derived from recombinant Arabidopsis thaliana At2g19630 protein, allowing for specific detection in experimental applications.
The At2g19630 antibody has been validated primarily for ELISA (Enzyme-Linked Immunosorbent Assay) and Western Blotting (WB) applications . These techniques enable researchers to detect, quantify, and analyze the protein in various experimental contexts:
Western Blotting: Allows for the detection of At2g19630 protein in complex mixtures, providing information about protein size, abundance, and potential modifications
ELISA: Enables quantitative analysis of At2g19630 protein levels in samples
Immunohistochemistry/Immunofluorescence: May be feasible, though specific validation for these applications should be confirmed
When designing experiments with this antibody, researchers should consider species reactivity (primarily plant species, particularly Arabidopsis thaliana) and conduct appropriate validation steps to ensure specificity in their experimental system .
Proper antibody validation is critical for ensuring reliable experimental results. Based on enhanced validation methods in the literature , implement these approaches for At2g19630 antibody:
Orthogonal Validation:
Compare antibody-based detection with an antibody-independent method like mass spectrometry
Correlate protein expression with mRNA levels using qRT-PCR or RNA-seq data
Genetic Validation:
Test the antibody in tissues from knockout/knockdown mutants where At2g19630 expression is absent or reduced
Use CRISPR-Cas9 edited plants lacking At2g19630 as negative controls
Independent Antibody Validation:
Use multiple antibodies targeting different epitopes of At2g19630
Compare staining patterns between these independent antibodies
Pre-adsorption Test:
Pre-incubate the antibody with purified antigen before application
If the antibody is specific, pre-adsorption should eliminate or significantly reduce the signal
Incorporating appropriate controls is essential for interpreting antibody-based experiments correctly:
Essential Controls for At2g19630 Antibody Experiments:
| Control Type | Example | Purpose |
|---|---|---|
| Positive Controls | Wild-type Arabidopsis tissues | Confirms antibody functionality |
| Recombinant At2g19630 protein | Establishes detection sensitivity | |
| Overexpression systems | Validates signal specificity | |
| Negative Controls | at2g19630 knockout/knockdown plants | Verifies absence of non-specific binding |
| Primary antibody omission | Assesses secondary antibody specificity | |
| Pre-immune serum | Controls for non-specific binding (polyclonal) | |
| Technical Controls | Loading control (actin/GAPDH) | Normalizes protein loading variations |
| Concentration gradient | Demonstrates dose-dependent specificity | |
| Competition with immunizing peptide | Confirms epitope specificity |
For Western blot experiments specifically, include a molecular weight marker to confirm the target protein's expected size, and consider using recombinant At2g19630 protein as a positive control when available . For immunohistochemistry, include tissues known to not express the protein as negative controls.
Research on anti-therapeutic antibodies has demonstrated that preexisting antibodies can sometimes interfere with results, so appropriate competition assays may be necessary in some experimental contexts to distinguish specific from non-specific signals .
For optimal Western blotting results with At2g19630 antibody, follow this methodological approach:
Sample Preparation:
Extract total protein from plant tissues using a buffer containing 50 mM Tris-HCl (pH 7.5), 150 mM NaCl, 1% Triton X-100, and protease inhibitors
Quantify protein concentration using Bradford or BCA assay
Prepare samples containing 20-50 μg of total protein per lane
Denature samples by heating at 95°C for 5 minutes in Laemmli buffer
SDS-PAGE and Transfer:
Separate proteins on 10-12% SDS-PAGE gels (F-box proteins typically range from 40-60 kDa)
Transfer to PVDF or nitrocellulose membrane at 100V for 1 hour or 30V overnight at 4°C
Immunodetection:
Block membrane with 5% non-fat dry milk or 3-5% BSA in TBST for 1 hour at room temperature
Incubate with At2g19630 antibody (start with 1:1000 dilution, optimize as needed) overnight at 4°C
Wash 3-5 times with TBST, 5 minutes each
Incubate with appropriate secondary antibody (e.g., anti-rabbit HRP if the primary is rabbit-derived) for 1 hour at room temperature
Wash 3-5 times with TBST, 5 minutes each
Develop using ECL substrate and detect signal using film or digital imager
Controls:
Include wild-type and At2g19630 knockout/knockdown samples if available
Consider running recombinant At2g19630 protein as a positive control
Include a loading control (e.g., anti-actin or anti-tubulin) to normalize protein loading
This protocol may require optimization based on specific research conditions. Document any modifications to establish reproducible procedures for your experimental system.
Optimizing antibody concentration is essential for achieving the best signal-to-noise ratio in your experiments:
Titration Experiment Strategy:
Prepare a dilution series of the antibody (e.g., 1:100, 1:500, 1:1000, 1:2000, 1:5000)
Keep all other experimental conditions constant
Process samples in parallel
Evaluate results based on signal strength and background levels
For Western Blotting:
Start with manufacturer's recommended dilution (typically 1:1000)
If signal is too strong with high background, increase dilution
If signal is weak, decrease dilution or extend exposure time
Consider the detection method (ECL vs. fluorescence) when optimizing
For Immunohistochemistry/Immunofluorescence:
Begin with a moderate dilution (e.g., 1:200-1:500)
Assess both signal intensity and background in positive and negative control tissues
Incrementally adjust until optimal staining is achieved
Documentation Table Format:
| Antibody Dilution | Signal Intensity | Background | Signal-to-Noise Ratio | Notes |
|---|---|---|---|---|
| 1:100 | +++ | +++ | 1:1 | Too much background |
| 1:500 | +++ | + | 3:1 | Good balance |
| 1:1000 | ++ | +/- | 4:1 | Good for low background applications |
| 1:5000 | + | - | N/A | Signal too weak |
The optimal concentration will provide maximum specific signal with minimal background. Document your optimization process thoroughly to ensure reproducibility in future experiments.
For protein localization studies using the At2g19630 antibody, implement these methodological approaches:
Subcellular Fractionation Approach:
Isolate nuclear, cytoplasmic, membrane, and organelle fractions using differential centrifugation
Analyze fractions by Western blotting using At2g19630 antibody
Include fraction-specific markers (e.g., histone H3 for nuclear, tubulin for cytoplasmic)
Quantify relative distribution across cellular compartments
Immunofluorescence Microscopy Protocol:
Fix Arabidopsis tissues or protoplasts using 4% paraformaldehyde
Permeabilize with 0.1-0.5% Triton X-100
Block with 3% BSA in PBS
Incubate with At2g19630 antibody (optimized dilution)
Use fluorophore-conjugated secondary antibody for detection
Include DAPI for nuclear staining
Analyze using confocal microscopy
Co-localization Analysis:
Perform double immunolabeling with antibodies against known subcellular markers
Calculate co-localization coefficients (Pearson's, Mander's)
Consider using specific organelle markers (e.g., ER, Golgi, vacuole)
Research on the ATG6 protein demonstrates the importance of examining both nuclear and cytoplasmic fractions separately when studying plant regulatory proteins . For example, researchers found that ATG6 co-localized with NPR1 in the nucleus, and SA treatment promoted both cytoplasmic and nuclear accumulation of ATG6, providing important insights into protein function .
When investigating protein-protein interactions with At2g19630 antibody, implement these methodological approaches:
Co-Immunoprecipitation (Co-IP) Protocol:
Harvest and lyse plant tissue in buffer containing 50 mM Tris-HCl (pH 7.5), 150 mM NaCl, 0.5% NP-40, 1 mM EDTA, and protease inhibitors
Clear lysate by centrifugation (14,000 × g, 10 min, 4°C)
Pre-clear with Protein A/G beads (1 hour, 4°C)
Incubate cleared lysate with At2g19630 antibody overnight at 4°C
Add Protein A/G beads and incubate for 2-4 hours at 4°C
Wash beads 4-5 times with lysis buffer
Elute proteins by boiling in SDS sample buffer
Analyze by SDS-PAGE and immunoblotting with antibodies against suspected interacting proteins
Proximity Ligation Assay (PLA):
Fix plant cells or tissue sections
Incubate with At2g19630 antibody and antibody against putative interacting protein
Use PLA probes specific to the primary antibody species
Perform ligation and amplification according to manufacturer's protocol
Visualize interaction signals using fluorescence microscopy
Quantify PLA signals per cell using appropriate software
Considerations Specific to At2g19630:
F-box proteins typically interact with SKP1, Cullin, and substrate proteins
Buffer conditions may need optimization to maintain these interactions
Consider the potential impact of post-translational modifications on interactions
Research on protein interactions in plants demonstrates how careful antibody-based co-localization and co-immunoprecipitation studies can reveal important functional relationships . For example, studies of ATG6-NPR1 interactions revealed that ATG6 directly interacts with NPR1 and significantly increases nuclear accumulation of NPR1, providing insight into the regulatory mechanisms of plant immunity .
Integrating multiple techniques with antibody-based detection provides more robust and comprehensive protein analysis:
Mass Spectrometry Integration:
Use immunoprecipitation with At2g19630 antibody followed by MS analysis
Identify interacting proteins and post-translational modifications
Validate MS findings with reciprocal co-immunoprecipitation
Analyze ubiquitination patterns (particularly relevant for F-box proteins)
Multi-omics Approach:
Correlate protein expression (antibody-based) with transcriptomics data
Integrate with metabolomics to understand functional consequences
Consider proteogenomics to identify novel protein variants
Example experimental design:
| Technique | Application | Integration Point |
|---|---|---|
| Antibody detection | Protein expression/localization | Primary data source |
| RNA-Seq | Transcript abundance | Correlation with protein levels |
| ChIP-Seq | Transcriptional regulation | Functional validation |
| Metabolomics | Downstream effects | Pathway analysis |
Proximity Labeling:
Combine with BioID or APEX2 techniques to identify proximal proteins
Express BioID-At2g19630 fusion in plants
Purify biotinylated proteins
Confirm interactions using At2g19630 antibody
Functional Assays:
Pair antibody detection with ubiquitination assays
Correlate protein levels with phenotypic outcomes
Use the antibody to immunodeplete At2g19630 and assess functional consequences
Based on protein microarray research, combining antibody detection with orthogonal methods significantly enhances data reliability and biological insights . As demonstrated in studies of recombinant antibody production in Arabidopsis, integrating antibody-based detection with transcriptome analysis via Tiling arrays provides a comprehensive view of protein expression and regulation .
Western Blot Quantification Protocol:
Use digital imaging systems rather than film for better dynamic range
Capture images before signal saturation occurs
Define regions of interest (ROIs) for specific bands and background
Subtract background from each band's intensity
Normalize target protein bands to loading controls (e.g., actin, GAPDH)
Calculate relative expression as: (At2g19630 signal / loading control signal)
Compare across conditions using fold change relative to control
Immunohistochemistry Quantification:
Use consistent exposure settings across all samples
Quantify signal intensity across multiple regions of interest (minimum 5-10 per condition)
Measure nuclear vs. cytoplasmic distribution for localization studies
Apply appropriate thresholding to distinguish specific from non-specific signal
Consider cell-by-cell analysis for heterogeneous tissues
ELISA Data Analysis:
Generate standard curves using purified protein if available
Ensure measurements fall within the linear range of detection
Run samples in technical triplicates to assess variability
Calculate concentration based on standard curve regression
According to research on antibody microarrays, proper normalization procedures that eliminate systematic bias are crucial for accurate interpretation . For antibody arrays, similar statistical methods as those used for cDNA arrays can be applied, including background subtraction, normalization, and differential expression analysis to identify significant changes in protein abundance across conditions .
Selecting appropriate statistical methods depends on your experimental design and data characteristics:
Statistical Analysis Recommendations by Experiment Type:
| Experiment Type | Data Type | Recommended Statistical Tests | Minimum Sample Size |
|---|---|---|---|
| Western Blot | Quantitative (band intensity) | Paired t-test (2 conditions) One-way ANOVA (3+ conditions) Two-way ANOVA (multiple factors) | n=3-5 biological replicates |
| Immunohistochemistry | Semi-quantitative (staining intensity) | Mann-Whitney (2 conditions) Kruskal-Wallis (3+ conditions) Chi-square (categorical data) | n=5-10 tissue sections |
| Co-localization | Correlation coefficients | Pearson's or Spearman's tests | n=10-20 cells/images |
| ELISA | Quantitative (concentration) | t-test (2 conditions) ANOVA (3+ conditions) | n=3-5 biological replicates |
| Time course | Longitudinal data | Repeated measures ANOVA Mixed-effects models | n=3-5 per timepoint |
Important Statistical Considerations:
Apply multiple testing correction (Bonferroni, FDR) when performing numerous comparisons
Verify data normality (Shapiro-Wilk test) before selecting parametric tests
Consider non-parametric alternatives for non-normal data
Report exact p-values and confidence intervals, not just significance level
Include effect sizes to indicate biological relevance
Contradictory results are common in antibody-based research and require systematic investigation:
Systematic Troubleshooting Approach:
Reassess Antibody Validation:
Re-validate antibody specificity using orthogonal methods
Test for lot-to-lot variability if using different antibody batches
Consider epitope accessibility issues in different experimental conditions
Verify antibody storage conditions and expiration dates
Analyze Experimental Conditions:
Document all variables between experiments (buffers, incubation times, temperatures)
Test critical parameters individually to identify sources of variation
Consider post-translational modifications that might affect antibody binding
Evaluate sample preparation differences (lysis buffers, fixation methods)
Evaluate Biological Variables:
Assess developmental stages, tissue specificity, or stress conditions
Consider circadian or seasonal effects on protein expression
Evaluate genetic background differences between sample sources
Account for environmental factors that may influence protein expression
Implement Reconciliation Strategies:
Employ orthogonal methods to confirm findings (MS, functional assays)
Use alternative antibodies targeting different epitopes
Consider targeted genetic approaches (RNAi, CRISPR) to validate findings
Design experiments that directly test competing hypotheses
According to studies on antibody validation, contradictory results often stem from insufficient validation or variable experimental conditions . Enhanced validation methods emphasize using orthogonal approaches and independent antibodies to increase confidence in results. Research on antibody quality has revealed that approximately 50% of commercial antibodies fail to meet basic standards for characterization, contributing to reproducibility issues in biological research .
At2g19630 encodes an F-box protein in Arabidopsis, which likely participates in protein degradation pathways that regulate stress responses. Here's how to utilize the antibody in stress response studies:
Temporal Expression Analysis Protocol:
Expose plants to specific stressors (drought, salt, pathogen, heat)
Harvest tissue at multiple timepoints (0, 1, 3, 6, 12, 24, 48 hours)
Extract proteins using buffer optimized for plant tissues
Analyze At2g19630 protein levels by Western blotting
Quantify relative to unstressed controls
Compare protein dynamics with mRNA expression patterns using qRT-PCR
Spatial Distribution Studies:
Use immunohistochemistry to determine tissue-specific expression changes
Investigate subcellular relocalization under stress conditions
Compare root, stem, leaf, and reproductive tissues for differential responses
Analyze protein distribution changes in response to localized vs. systemic stress
Protein Degradation Dynamics:
Use cycloheximide chase assays to determine protein stability under stress
Investigate ubiquitination patterns using immunoprecipitation followed by ubiquitin-specific antibodies
Examine proteasome involvement using inhibitors like MG132
Track protein half-life changes in response to different stress conditions
Studies on plant transcription factors like WRKY75 , which may function in the same pathways as At2g19630, provide insights into how regulatory proteins respond to various stresses. Research has identified numerous target genes of WRKY75, suggesting complex regulatory networks that may also involve F-box proteins like At2g19630 in stress response pathways .
As an F-box protein, At2g19630 likely functions in the ubiquitin-proteasome system to target substrate proteins for degradation. Here are methodological approaches to study these mechanisms:
Substrate Identification Protocol:
Generate transgenic plants expressing tagged At2g19630 (e.g., FLAG, HA, GFP)
Perform immunoprecipitation using antibodies against the tag
Identify co-precipitating proteins by mass spectrometry
Validate potential substrates using directed co-IP with At2g19630 antibody
Confirm interaction specificity using at2g19630 knockout controls
Ubiquitination Assay:
Immunoprecipitate candidate substrate proteins
Probe with anti-ubiquitin antibodies to detect ubiquitination
Compare ubiquitination levels between wild-type and at2g19630 mutant plants
Use proteasome inhibitors (MG132) to accumulate ubiquitinated intermediates
Degradation Kinetics:
Perform cycloheximide chase assays to measure substrate half-life
Compare protein stability in wild-type vs. at2g19630 mutant backgrounds
Quantify protein levels over time using At2g19630 antibody
Calculate degradation rates under various conditions
SCF Complex Analysis:
Use At2g19630 antibody to immunoprecipitate the complete SCF complex
Identify associated Skp1 and Cullin proteins by Western blotting
Study complex assembly/disassembly dynamics under different conditions
Investigate post-translational modifications that regulate F-box protein activity
Research on protein degradation mechanisms in plants has shown that F-box proteins like At2g19630 can be regulated at multiple levels, including transcription, protein stability, and subcellular localization . Studying these regulatory mechanisms requires combining antibody-based detection with genetic approaches and biochemical assays to fully understand their function in plant development and stress responses.