The AT1G67190 gene in Arabidopsis thaliana encodes an F-box/RNI-like superfamily protein involved in protein degradation via ubiquitination pathways . Key features include:
Chromosomal location: Chr1 (25,133,054–25,134,313)
Protein ID: Q9ZW88
Gene family: Part of orthologous groups conserved across 92 plant species .
Domain structure: Contains an F-box domain (IPR001810) and Skp2-like F-box domain (IPR022364) .
Homologs: Closely related to AT1G10780 in Arabidopsis and 143 plant proteins across 14 species .
While the search results extensively discuss antibodies (e.g., immunoglobulins, monoclonal antibodies) , none reference an antibody targeting AT1G67190. Key findings from reviewed sources include:
Monoclonal antibodies are widely used in human therapeutics (e.g., cancer, autoimmune diseases) .
Autoantibodies against G protein-coupled receptors (e.g., AT1R, ETAR) are implicated in preeclampsia and systemic sclerosis .
SARS-CoV-2 antibody dynamics were studied for diagnostic and therapeutic purposes .
If such an antibody exists, it would likely be a custom research tool for studying:
Protein-protein interactions in ubiquitination pathways.
Gene expression regulation in plant development or stress responses.
| Application | Methodology | Relevance |
|---|---|---|
| Protein localization | Immunohistochemistry (IHC) | Track AT1G67190 expression in plant tissues |
| Functional studies | Western blot (WB), Knockout mutants | Validate protein role in ubiquitination |
To address the lack of data on AT1G67190 antibodies:
Antibody generation: Develop polyclonal/monoclonal antibodies using recombinant AT1G67190 protein.
Experimental validation:
Test cross-reactivity with homologs (e.g., AT1G10780).
Publish characterization data (e.g., epitope mapping, specificity assays).
Collaborative efforts: Partner with plant biology research consortia to explore functional roles.
At1g67190 antibody is a polyclonal antibody raised in rabbits against recombinant Arabidopsis thaliana At1g67190 protein. This antibody specifically targets proteins expressed by the At1g67190 gene in Arabidopsis thaliana (Mouse-ear cress). It's primarily designed for research applications and should not be used for diagnostic or therapeutic procedures . The antibody is typically supplied in liquid form with preservation buffer containing 0.03% Proclin 300 and storage constituents of 50% Glycerol and 0.01M PBS at pH 7.4 .
The At1g67190 antibody has been validated for several standard laboratory techniques:
Enzyme-linked immunosorbent assay (ELISA)
Western blotting (WB)
These applications enable researchers to detect, quantify, and characterize the At1g67190 protein in plant tissue samples . Similar to approaches used with other plant antibodies, researchers could potentially explore additional applications such as immunofluorescence, though specific validation would be required .
Upon receipt, the At1g67190 antibody should be stored at -20°C or -80°C to maintain its activity and specificity. Researchers should avoid repeated freeze-thaw cycles as this can degrade antibody quality and performance . For working solutions, aliquoting the antibody before freezing is recommended to minimize freeze-thaw cycles. The antibody is typically shipped with cold packs, similar to other research antibodies , and proper storage upon arrival is crucial for maintaining its efficacy.
When designing experiments with the At1g67190 antibody, researchers should incorporate appropriate controls to validate results:
Positive control: Tissue or cell extracts known to express At1g67190 (preferably Arabidopsis thaliana samples)
Negative control: Samples from organisms not expressing the target protein
Secondary antibody-only control: To assess non-specific binding of the secondary detection system
Blocking peptide competition assay: Using the immunizing peptide to confirm specificity
These controls help distinguish true positive signals from background or non-specific binding . Studies with other antibodies have demonstrated that lack of proper controls can lead to misinterpretation of results, particularly with polyclonal antibodies .
Antibody validation is critical, especially given known issues with commercial antibodies. A comprehensive validation approach should include:
Western Blot Analysis: Verify the antibody detects bands of expected molecular weight in tissues known to express the target protein .
Knockout/Knockdown Validation: If available, use genetic knockout or RNAi knockdown tissues where At1g67190 expression is absent or reduced. The antibody should show corresponding reduction or absence of signal .
Overexpression Studies: Test tissues or cells overexpressing At1g67190 to confirm increased signal intensity .
Peptide Competition Assay: Pre-incubate the antibody with the immunizing peptide before application to samples; specific signals should be blocked or reduced .
Cross-reactivity Assessment: Test the antibody on closely related species to evaluate potential cross-reactivity .
This multi-faceted approach is particularly important given findings that some commercial antibodies may produce identical immunostaining patterns regardless of target protein presence, as demonstrated with AT1 receptor antibodies .
While the At1g67190 antibody is designed to be specific for Arabidopsis thaliana, potential cross-reactivity with proteins from other plant species or with structurally similar proteins within Arabidopsis remains a concern. Studies on other antibodies have revealed that even well-characterized antibodies may detect proteins unrelated to their intended targets .
Researchers should conduct cross-reactivity tests when applying this antibody to:
Non-Arabidopsis plant species
Novel experimental conditions
Different tissue types than previously validated
The lesson from studies with AT1 receptor antibodies, where six commercially available antibodies showed non-specific binding to proteins of similar molecular weight to their intended targets, underscores the importance of cross-reactivity assessment .
Experimental design significantly impacts the reliability of antibody-based results. Researchers should consider implementing robust experimental designs such as:
| Experimental Design | Strengths | Limitations | Applicability to Antibody Research |
|---|---|---|---|
| Pretest-Posttest Control Group Design | Controls for history, maturation, testing, regression effects | Requires randomization | Useful for comparing antibody performance before/after treatments |
| Solomon Four-Group Design | Controls for testing effects and interaction of testing with treatment | Complex implementation | Ideal for validating new antibody applications or conditions |
| Posttest-Only Control Group Design | Simpler implementation, eliminates testing effects | Less control over individual differences | Suitable for straightforward antibody detection experiments |
Optimizing Western blot protocols for the At1g67190 antibody requires systematic testing of several parameters:
Sample Preparation:
Test different extraction buffers to optimize protein solubilization
Include protease inhibitors to prevent degradation
Determine optimal protein loading amounts (typically 20-50 μg total protein)
Blocking Conditions:
Test different blocking agents (BSA, non-fat milk, commercial blockers)
Optimize blocking time and temperature
Antibody Dilution:
Create a dilution series (e.g., 1:500, 1:1000, 1:2000, 1:5000)
Determine optimal primary antibody incubation time and temperature
Detection System:
Compare chemiluminescence vs. fluorescence detection
Optimize exposure times for imaging
This methodical approach helps identify conditions that maximize specific signal while minimizing background, similar to optimization procedures used for other plant antibodies .
Effective protein extraction is crucial for successful At1g67190 detection. The following methods have proven effective for plant protein extraction:
RIPA Buffer Extraction:
Composition: 50 mM Tris-HCl (pH 7.5), 150 mM NaCl, 1% NP-40, 0.5% sodium deoxycholate, 0.1% SDS
Add protease inhibitor cocktail freshly before use
Most suitable for general protein extraction
Native Protein Extraction:
Composition: 50 mM Tris-HCl (pH 7.5), 150 mM NaCl, 1% NP-40
Preserves protein structure and interactions
Suitable for co-immunoprecipitation studies
Subcellular Fractionation:
Sequential extraction of cytosolic, membrane, nuclear, and cytoskeletal fractions
Helps determine protein localization
Reduces sample complexity
The extraction method should be selected based on the downstream application and the cellular localization of the At1g67190 protein. Each method should be validated specifically for Arabidopsis thaliana tissue samples to ensure optimal results.
Discrepancies between antibody-based protein detection and gene expression data are common in biological research. To resolve these discrepancies:
Verify antibody specificity: As discussed in question 2.1, confirm the antibody is detecting the correct target .
Consider post-transcriptional regulation: mRNA levels may not correlate with protein levels due to:
Differences in mRNA stability
Translational efficiency variations
Post-translational modifications
Protein degradation rates
Employ multiple detection methods:
Compare results from different antibody-based techniques (Western blot, ELISA, immunofluorescence)
Use mass spectrometry for antibody-independent protein identification
Implement genetic approaches (reporter gene fusions)
Temporal considerations: Examine whether time differences between mRNA expression and protein production could explain discrepancies.
Studies examining AT1 receptor antibodies have demonstrated that reliance on a single detection method can lead to misinterpretation, emphasizing the importance of using complementary approaches .
For Western Blot Quantification:
Normalize target protein signal to loading controls
Use ANOVA for comparing multiple treatment groups
Apply non-parametric tests (Mann-Whitney U test) for non-normally distributed data
For ELISA Data:
Generate standard curves using purified protein when possible
Apply four-parameter logistic regression for standard curve fitting
Use t-tests or ANOVA with appropriate post-hoc tests for group comparisons
For Reproducibility Assessment:
Calculate coefficient of variation (CV) between technical and biological replicates
Report confidence intervals rather than just p-values
Perform power analysis to determine appropriate sample sizes
As noted in phase 1 clinical research, descriptive statistics including arithmetic mean, standard deviation, coefficient of variation, median, minimum, and maximum are typically calculated for all parameters when appropriate .
| Problem | Possible Causes | Solutions |
|---|---|---|
| No signal in Western blot | - Insufficient protein loading - Excessive blocking - Antibody degradation - Target protein denaturation | - Increase protein amount - Optimize blocking conditions - Use fresh antibody aliquot - Test native protein extraction |
| High background | - Insufficient blocking - Antibody concentration too high - Non-specific binding - Contaminated buffers | - Increase blocking time/concentration - Dilute antibody further - Add 0.1-0.5% Tween-20 to wash buffers - Prepare fresh buffers |
| Multiple bands | - Non-specific binding - Protein degradation - Post-translational modifications - Cross-reactivity | - Increase antibody dilution - Add protease inhibitors - Perform peptide competition assay - Verify with additional detection methods |
| Variable results between replicates | - Inconsistent extraction efficiency - Antibody batch variation - Technical variations in protocol | - Standardize extraction protocol - Use same antibody lot when possible - Develop detailed SOP for all steps |
This troubleshooting guide addresses common issues encountered with antibody applications, drawing on principles that have been documented with other antibody systems .
Several emerging technologies offer complementary or alternative approaches to traditional antibody-based detection:
CRISPR/Cas9 Epitope Tagging:
Endogenous tagging of At1g67190 with HA, FLAG, or GFP tags
Enables detection using highly validated tag-specific antibodies
Preserves native expression levels and regulation
Proximity Labeling Technologies:
BioID or TurboID fusion proteins to identify interaction partners
Maps protein microenvironments in living cells
Complements traditional co-immunoprecipitation approaches
Mass Spectrometry-Based Proteomics:
Label-free quantification of At1g67190
Parallel detection of post-translational modifications
Antibody-independent validation approach
Nanobody and Aptamer Technologies:
Development of single-domain antibodies or DNA/RNA aptamers
Potentially higher specificity than conventional antibodies
Better penetration into complex tissues
These technologies address some limitations of traditional antibodies, such as the specificity concerns documented with AT1 receptor antibodies .
Research utilizing At1g67190 antibodies contributes to plant biology in several ways:
Functional Characterization:
Determination of protein expression patterns across tissues and developmental stages
Correlation with phenotypic changes under various conditions
Assessment of protein-protein interactions and complex formation
Stress Response Studies:
Examination of protein expression changes under abiotic stresses
Investigation of post-translational modifications during stress adaptation
Comparison with other plant species' stress responses
Evolutionary Biology:
Comparative studies across related plant species
Examination of protein conservation and divergence
Understanding of functional adaptations in different ecological niches
The methodological approaches developed for At1g67190 antibody research may also inform broader antibody validation practices in plant biology, addressing the challenges of antibody specificity documented in other research areas .