KEGG: ath:AT1G60989
UniGene: At.36556
SCRL7 antibody is a research reagent designed for the detection and characterization of its target protein. Based on available data, it is typically used in immunological applications such as ELISA and Western blotting . The antibody is available in polyclonal format derived from rabbit hosts, with purification typically performed via antigen affinity methods . Like other research antibodies, its primary purpose is to enable sensitive and specific detection of its target protein in experimental contexts.
Antibody specificity is most rigorously assessed using genetic approaches that employ knockout (KO) cell lines as negative controls. This methodology involves:
Testing the antibody against wild-type cells expressing the target protein
Testing the antibody against isogenic CRISPR knockout cells lacking the target protein
Comparing the results to determine if the signal disappears in the knockout samples
This knockout-based validation approach is considered the gold standard, providing more reliable results than orthogonal approaches that rely solely on known properties of the target protein . Research indicates that approximately 80% of antibodies recommended based on orthogonal strategies and 89% recommended based on genetic strategies could successfully detect their intended target in Western blot applications .
The three main antibody formats differ significantly in production method and characteristics:
| Antibody Type | Production Method | Characteristics | Typical Performance |
|---|---|---|---|
| Polyclonal | Immunization of animals (e.g., rabbits) | Recognizes multiple epitopes, batch-to-batch variation | Variable specificity |
| Monoclonal | Hybridoma technology | Recognizes single epitope, more consistent | Moderate consistency |
| Recombinant | DNA technology in expression systems | Defined sequence, renewable resource | Highest consistency |
SCRL7 antibody is available in polyclonal format derived from rabbit hosts . Large-scale antibody validation studies indicate that recombinant antibodies typically outperform both monoclonal and polyclonal antibodies in terms of specificity and reproducibility .
A comprehensive validation protocol for antibodies like SCRL7 should include testing in multiple applications using appropriate controls:
Western Blot (WB): Test antibody on cell lysates with positive and negative controls (ideally knockout cells). Evaluate for expected band size, signal intensity, and absence of non-specific bands.
Immunoprecipitation (IP): Perform on non-denaturing cell lysates, followed by Western blot with a validated antibody to confirm target capture.
Immunofluorescence (IF): Test subcellular localization pattern in cells known to express the target, with parallel testing in knockout or knockdown cells.
Research has shown that only 34-46% of commercial antibodies pass rigorous validation in all three applications (WB, IP, IF), with many showing non-specific binding or failing to detect their intended targets . Therefore, it is essential to validate SCRL7 antibody for your specific experimental conditions and cell types before proceeding with critical experiments.
Dilution optimization is critical for balancing signal strength with background noise:
Initial Testing: Begin with manufacturer's recommended dilutions (typically 1:500-1:1000 for WB, 1:100-1:500 for IF)
Serial Dilution Series: Prepare 3-5 dilutions in a 2-5 fold range around the recommended concentration
Positive and Negative Controls: Include controls for each dilution
Signal-to-Noise Assessment: Quantify specific signal versus background for each dilution
Optimization Criteria:
For WB: Optimal balance between specific band intensity and minimal background
For IF: Clearest subcellular localization with minimal diffuse staining
Data from large-scale antibody testing suggests that even well-performing antibodies often require optimization beyond manufacturer recommendations to achieve optimal results in specific experimental contexts .
Essential controls include:
Negative Controls:
Positive Controls:
Procedural Controls:
Secondary antibody only (to detect non-specific binding)
Blocking peptide competition (if available)
Research indicates that laboratories that implement rigorous control strategies report 20-30% fewer false positive results in their antibody-based experiments .
Common causes of problematic results include:
| Issue | Potential Causes | Troubleshooting Approaches |
|---|---|---|
| False Positives | Cross-reactivity with similar epitopes | Validate with knockout controls |
| Non-specific binding | Optimize blocking conditions | |
| Secondary antibody issues | Test secondary alone | |
| False Negatives | Target epitope inaccessible | Try different extraction methods |
| Target expression too low | Increase sample concentration | |
| Antibody degradation | Check storage conditions | |
| Interfering buffer components | Test alternative buffers |
Large-scale antibody validation studies have found that more than 50% of commercial antibodies fail in one or more applications, with many showing non-specific binding or failing to detect their intended targets altogether . Therefore, methodical troubleshooting is often necessary even with commercially validated antibodies.
To distinguish between specific and non-specific binding:
Genetic Validation: The gold standard involves using knockout or knockdown models where the target protein is absent. In Western blots, specific bands should disappear in knockout samples while non-specific bands remain .
Molecular Weight Assessment: Specific binding should produce bands at the predicted molecular weight of the target protein (plus any post-translational modifications).
Peptide Competition: Pre-incubation of the antibody with purified target peptide should reduce or eliminate specific signals but not affect non-specific binding.
Multiple Antibody Validation: Use multiple antibodies targeting different epitopes of the same protein to confirm specific binding patterns.
Research indicates that 30-40% of antibodies that appear specific by orthogonal validation methods (e.g., expected molecular weight) still fail when tested against knockout controls, highlighting the importance of genetic validation approaches .
Quantitative assessment of antibody performance should include:
Signal-to-Noise Ratio (SNR): Calculate as (specific signal intensity) / (background signal intensity)
For Western blot: SNR = (target band intensity) / (average background intensity)
For immunofluorescence: SNR = (specific subcellular staining) / (non-specific diffuse staining)
Limit of Detection (LOD): Determine the minimum amount of target protein detectable above background
Dynamic Range: Assess the range of target concentrations over which signal maintains linearity
Coefficient of Variation (CV): Calculate across replicates to assess reproducibility:
CV (%) = (Standard Deviation / Mean) × 100
Z-factor: For high-throughput applications:
Z' = 1 - [(3σp + 3σn) / |μp - μn|]
Where σp and σn are standard deviations of positive and negative controls, and μp and μn are their means
Comprehensive antibody validation studies suggest that well-performing antibodies should achieve SNR > 5, CV < 15%, and Z' > 0.5 for reliable research applications .
Antibody performance can vary significantly based on sample preparation:
Fixation Effects: Different fixation methods (formalin, methanol, acetone) can alter epitope accessibility
Formaldehyde creates crosslinks that may mask epitopes
Alcohol fixatives preserve protein structure differently
Extraction Methods: Different lysis buffers affect protein solubilization and epitope exposure
RIPA buffers may denature some epitopes while preserving others
Non-ionic detergents (Triton X-100, NP-40) better preserve protein-protein interactions
Sample Processing: Fresh vs. frozen samples can show different antibody reactivity patterns
Studies indicate that approximately 20-30% of antibodies show differential performance depending on sample preparation methods, with some recognizing only native or only denatured forms of their target proteins .
Current limitations in antibody validation include:
Knockout Model Availability: Not all targets have readily available knockout cell lines or models
Context Dependency: Validation in one cell type or condition doesn't guarantee performance in others
Publication Bias: An estimated 20-30% of published research uses antibodies that do not recognize their intended targets, with 88% of these publications containing no validation data
Renewable Resource Limitations: Despite better performance, renewable antibodies (recombinant) do not yet cover the entire proteome
Standardization Challenges: Different manufacturers use different validation criteria
Research indicates that only approximately 50-75% of proteins have at least one high-performing commercial antibody available, depending on the application .
Post-translational modifications (PTMs) and protein interactions can significantly impact antibody recognition:
PTM Effects:
Phosphorylation near epitopes can create or block antibody binding sites
Glycosylation can mask epitopes through steric hindrance
Ubiquitination or SUMOylation can alter protein conformation
Protein Complex Formation:
Protein-protein interactions may block antibody access to epitopes
Conformational changes due to binding partners can expose or hide epitopes
Detection Strategies for Modified Proteins:
Use modification-specific antibodies when targeting specific PTM states
Employ protein complex disruption techniques (high salt, detergents) when necessary
Consider multiple antibodies targeting different epitopes to ensure detection regardless of modification status
Research indicates that approximately 15-25% of antibodies show differential recognition of modified versus unmodified forms of their target proteins .
Analysis of large-scale antibody validation studies reveals application-specific performance patterns:
| Application | Average Pass Rate | Common Failure Modes | Performance Metrics |
|---|---|---|---|
| Western Blot (WB) | 50-70% | Multiple bands, wrong MW | Band specificity, signal-to-noise ratio |
| Immunoprecipitation (IP) | 30-50% | Low pulldown efficiency | % target captured, non-specific binding |
| Immunofluorescence (IF) | 40-60% | Non-specific staining | Localization accuracy, background |
Research indicates that only approximately 25-35% of antibodies perform well across all three applications, highlighting the importance of application-specific validation . For SCRL7 antibody specifically, validation for its recommended applications (ELISA, WB) should be prioritized .
Factors affecting inter-laboratory reproducibility include:
Antibody Variables:
Lot-to-lot variation (especially significant for polyclonal antibodies)
Storage conditions and freeze-thaw cycles
Age of antibody (potential degradation over time)
Protocol Variables:
Blocking agents and incubation times
Buffer compositions and pH differences
Detection systems and their sensitivity
Sample Variables:
Cell culture conditions (passage number, confluence, media)
Tissue processing methods
Protein extraction protocols
Research indicates that standardization of protocols can reduce inter-laboratory variability by 40-60%, with the most significant improvements seen with detailed standard operating procedures and shared positive and negative controls .