At3g17400 Antibody

What is At3g17400 and why is it studied in plant research?

At3g17400 refers to a specific gene locus in Arabidopsis thaliana (mouse-ear cress), a model organism widely used in plant molecular biology. This protein (UniProt: Q9LUT1) is studied to understand plant cellular processes. The antibody against this protein enables researchers to detect and quantify the At3g17400 protein in various experimental contexts, contributing to our understanding of plant protein function and regulation. When designing experiments, researchers should consider the specific cellular localization and expression patterns of the At3g17400 protein to properly interpret antibody detection results .

What are the key specifications of the At3g17400 antibody?

The At3g17400 antibody is a polyclonal antibody raised in rabbits using recombinant Arabidopsis thaliana At3g17400 protein as the immunogen. The antibody is provided in liquid form in a storage buffer containing 50% glycerol, 0.01M PBS (pH 7.4), and 0.03% Proclin 300 as a preservative. It has been purified using antigen affinity methods to enhance specificity. This antibody has been tested for applications including ELISA and Western Blot (WB), making it suitable for protein detection and quantification in plant research .

Table 1: At3g17400 Antibody Specifications

How should the At3g17400 antibody be stored to maintain activity?

Upon receipt, the At3g17400 antibody should be stored at -20°C or -80°C to maintain its activity. Repeated freeze-thaw cycles should be avoided as they can degrade the antibody and reduce its effectiveness. If frequent use is anticipated, aliquoting the antibody into smaller volumes before freezing is recommended to minimize freeze-thaw cycles. When thawed for use, the antibody should be kept at 4°C for short-term storage (up to one month under sterile conditions). Proper storage is critical for maintaining antibody functionality and experimental reproducibility .

What are the validated applications for At3g17400 antibody?

The At3g17400 antibody has been validated for enzyme-linked immunosorbent assay (ELISA) and Western blotting (WB) applications. For Western blotting, this antibody can detect the At3g17400 protein in plant extracts, allowing researchers to determine protein expression levels and molecular weight. In ELISA, it enables quantitative measurement of the protein in solution. While these are the validated applications, researchers may need to optimize conditions for their specific experimental systems, as antibody performance can vary depending on sample preparation methods and buffer conditions .

How should I design control experiments when using the At3g17400 antibody?

Proper control experiments are essential for ensuring the reliability of results when using the At3g17400 antibody. Based on antibody characterization principles, the following controls are recommended:

• Positive control: Use samples known to express At3g17400 protein, such as wild-type Arabidopsis thaliana tissue.

• Negative control: Include samples where At3g17400 is not expressed or has been knocked out.

• Isotype control: Use a non-specific antibody of the same isotype (IgG) and host species (rabbit) to identify non-specific binding.

• Blocking peptide control: Pre-incubate the antibody with the immunizing peptide to demonstrate binding specificity.

• Loading control: For Western blots, include detection of a housekeeping protein to normalize protein loading.

These controls help identify false positives, non-specific binding, and validate the specificity of the antibody, addressing key concerns in antibody research reproducibility .

What is the optimal dilution range for At3g17400 antibody in different applications?

The optimal dilution for At3g17400 antibody varies by application and should be determined empirically for each experimental setup. Based on general polyclonal antibody principles, start with these recommended ranges:

• Western blotting: 1:500 to 1:2000 dilution

• ELISA: 1:1000 to 1:5000 dilution

To determine the optimal dilution, a titration experiment should be performed using a series of antibody dilutions while keeping all other variables constant. The optimal dilution will provide the strongest specific signal with minimal background. Factors that can affect the optimal dilution include protein abundance, sample preparation method, detection system sensitivity, and incubation conditions .

What are the common reasons for weak or absent signals when using At3g17400 antibody?

Several factors can contribute to weak or absent signals when using the At3g17400 antibody:

• Low target protein expression: At3g17400 may be expressed at low levels in your sample. Consider using enrichment techniques or more sensitive detection methods.

• Improper sample preparation: Inadequate protein extraction or denaturation can reduce antibody accessibility to the target. Ensure proper lysis buffers and denaturation procedures.

• Antibody degradation: Improper storage or excessive freeze-thaw cycles can degrade antibody activity. Always follow storage recommendations.

• Insufficient blocking: Inadequate blocking can increase background noise, making specific signals difficult to detect. Optimize blocking conditions.

• Suboptimal antibody concentration: Too low or too high antibody concentrations can lead to weak signals or high background. Perform dilution series to determine optimal concentration.

• Inappropriate detection method: The selected detection method may not be sensitive enough. Consider enhanced chemiluminescence (ECL) or fluorescent secondary antibodies for increased sensitivity .

How can I verify the specificity of the At3g17400 antibody?

Verifying antibody specificity is crucial for reliable experimental results. For At3g17400 antibody, consider these approaches:

• Knockout or knockdown validation: Test the antibody on samples from At3g17400 knockout plants or RNAi-silenced plants. The absence of signal in these samples suggests specificity.

• Protein overexpression: Test the antibody on samples overexpressing At3g17400. Increased signal intensity correlates with increased protein expression.

• Peptide competition assay: Pre-incubate the antibody with the immunizing peptide before application. Specific binding should be blocked, resulting in signal reduction.

• Multiple antibody comparison: Use different antibodies targeting different epitopes of At3g17400 and compare detection patterns.

• Mass spectrometry validation: Immunoprecipitate using the antibody and identify pulled-down proteins by mass spectrometry to confirm target specificity.

These approaches collectively provide robust validation of antibody specificity, addressing a major concern in antibody-based research .

What sample preparation techniques are recommended for optimal At3g17400 detection?

Effective sample preparation is critical for successful At3g17400 detection. The following methods are recommended:

• Plant tissue extraction: Use a buffer containing 50 mM Tris-HCl (pH 7.5), 150 mM NaCl, 1% Triton X-100, 0.5% sodium deoxycholate, and protease inhibitor cocktail. Grind tissue in liquid nitrogen before adding buffer.

• Protein denaturation: For Western blotting, heat samples at 95°C for 5 minutes in Laemmli buffer containing SDS and β-mercaptoethanol to ensure proper protein denaturation.

• Membrane protein enrichment: If At3g17400 is membrane-associated, consider using membrane fraction enrichment protocols before antibody application.

• Fixation for immunohistochemistry: If performing tissue localization, use 4% paraformaldehyde fixation followed by appropriate antigen retrieval methods.

• Protein concentration determination: Accurately measure protein concentration using Bradford or BCA assays to ensure consistent loading and comparative analysis.

These preparation techniques help ensure that the target protein is accessible to the antibody and minimize potential artifacts due to inadequate sample processing .

How can At3g17400 antibody be used for protein-protein interaction studies?

The At3g17400 antibody can be valuable for investigating protein-protein interactions through several techniques:

• Co-immunoprecipitation (Co-IP): Use the antibody to pull down At3g17400 along with its interacting partners. The precipitated complex can be analyzed by Western blotting or mass spectrometry to identify interaction partners.

• Proximity ligation assay (PLA): This technique allows visualization of protein interactions in situ. By combining the At3g17400 antibody with antibodies against suspected interaction partners, PLA can detect proteins that are in close proximity (< 40 nm).

• Chromatin immunoprecipitation (ChIP): If At3g17400 is involved in transcriptional regulation, ChIP using this antibody can identify DNA binding sites and potential co-factors.

• Bimolecular fluorescence complementation (BiFC) complementary approach: While BiFC involves fusion proteins, the antibody can be used for validation of interactions observed in BiFC experiments.

When designing protein interaction experiments, consider potential epitope masking when proteins are in complexes, which might affect antibody binding and detection sensitivity .

Can At3g17400 antibody be used for studying post-translational modifications?

Studying post-translational modifications (PTMs) with the At3g17400 antibody requires careful experimental design:

• PTM-specific detection: The standard At3g17400 antibody recognizes the protein regardless of most PTMs. To study specific modifications, use complementary approaches:

  • Use phospho-specific or other PTM-specific antibodies in parallel

  • Perform immunoprecipitation with At3g17400 antibody followed by PTM-specific antibody detection

  • Combine with mass spectrometry to identify modifications on immunoprecipitated protein

• Mobility shift analysis: Some PTMs alter protein migration in SDS-PAGE. The At3g17400 antibody can detect these shifts in Western blots, suggesting potential modifications.

• Enzymatic treatments: Treat samples with phosphatases, deubiquitinases, or other enzymes that remove specific PTMs before antibody detection to confirm the presence of modifications.

• Stimulation experiments: Compare At3g17400 antibody detection patterns before and after treatments known to induce specific PTMs in plants (e.g., stress responses, hormone treatments).

These approaches can provide valuable insights into how At3g17400 is regulated through post-translational mechanisms .

How can computational modeling enhance At3g17400 antibody experimental design?

Computational approaches can significantly improve experimental design when using the At3g17400 antibody:

• Epitope prediction: Computational tools can predict the likely epitopes recognized by the polyclonal At3g17400 antibody, informing experimental design when protein domains are of interest.

• Cross-reactivity assessment: Sequence alignment and structural modeling can identify potential cross-reactive proteins with similar epitopes, helping design appropriate controls.

• Binding mode prediction: Computational docking can model antibody-antigen interactions, providing insights into binding properties and potential interference with protein functions.

• Experimental optimization: Machine learning approaches trained on antibody-antigen interaction data can suggest optimal conditions for detection, including buffer composition and incubation parameters.

• Data integration: Computational frameworks can integrate antibody-generated data with other -omics datasets, enhancing interpretation of results in broader biological contexts.

These computational approaches can enhance the specificity and reliability of experiments using the At3g17400 antibody, particularly important when studying complex plant protein networks .

What are the best practices for quantifying At3g17400 expression in Western blotting?

Accurate quantification of At3g17400 expression requires rigorous methodological approaches:

• Appropriate loading controls: Use plant-specific housekeeping proteins (e.g., actin, tubulin, or GAPDH) that maintain stable expression under your experimental conditions.

• Linear dynamic range determination: Perform dilution series experiments to determine the linear range of detection for both At3g17400 and loading control antibodies.

• Replication and statistical analysis: Include biological replicates (n≥3) and perform appropriate statistical tests to validate observed differences.

• Densitometry software: Use specialized software (ImageJ, Image Lab, etc.) with consistent background subtraction methods for signal quantification.

• Normalization approach: Calculate relative expression by dividing the At3g17400 signal by the loading control signal, accounting for lane-to-lane variations.

• Standards and calibration: Include known quantities of recombinant At3g17400 protein to create a standard curve for absolute quantification when needed.

These practices ensure reliable quantification and valid comparisons across different experimental conditions or genotypes .

How should I address inconsistent results between different detection methods using At3g17400 antibody?

Inconsistencies between different detection methods are common challenges in antibody-based research. When encountering discrepancies using the At3g17400 antibody:

• Method-specific validation: Each method (Western blot, ELISA, etc.) may have different sensitivity and specificity profiles. Validate the antibody separately for each method.

• Epitope accessibility analysis: Different sample preparation methods may affect epitope exposure. Consider whether native vs. denatured conditions impact antibody recognition.

• Cross-validation approaches: Use complementary methods such as RT-qPCR for mRNA expression or mass spectrometry for protein identification to triangulate results.

• Sample composition considerations: Buffer components, detergents, or salt concentrations may affect antibody binding differently across methods. Optimize conditions for each technique.

• Threshold standardization: Establish consistent detection thresholds across methods based on controls and standards.

• Reporting comprehensive results: When publishing, report results from multiple detection methods, including discrepancies, to provide a more complete picture of At3g17400 expression or function .

What statistical approaches are recommended for analyzing At3g17400 detection across experimental conditions?

• Normality testing: Before selecting statistical tests, determine whether your data follow normal distribution using Shapiro-Wilk or Kolmogorov-Smirnov tests.

• Appropriate statistical tests:

  • For comparing two conditions: t-test (parametric) or Mann-Whitney U test (non-parametric)

  • For multiple conditions: ANOVA with post-hoc tests (parametric) or Kruskal-Wallis test (non-parametric)

  • For time-course experiments: repeated measures ANOVA or mixed-effects models

• Effect size calculation: Report not only p-values but also effect sizes (Cohen's d, fold change, etc.) to indicate biological significance.

• Power analysis: Determine appropriate sample sizes through power analysis to ensure sufficient statistical power for detecting biologically relevant differences.

• Multiple testing correction: When performing multiple comparisons, apply corrections (Bonferroni, Benjamini-Hochberg, etc.) to control false discovery rates.

• Data visualization: Use appropriate graphical representations (box plots, violin plots) that display both individual data points and statistical summaries.

How can At3g17400 antibody be adapted for emerging single-cell technologies?

Adapting the At3g17400 antibody for single-cell analysis requires specialized approaches:

• Single-cell Western blotting: Microfluidic platforms now enable Western blot analysis at the single-cell level. The At3g17400 antibody can be optimized by determining minimum detectable protein amounts and adjusting concentration accordingly.

• Mass cytometry (CyTOF): For this technique, the At3g17400 antibody would need metal conjugation (e.g., lanthanide metals). Test multiple conjugation ratios to maintain binding affinity while providing sufficient signal.

• Single-cell immunofluorescence: Optimize fixation, permeabilization, and detection protocols specifically for plant cells, considering their cell wall barrier. Signal amplification systems like tyramide signal amplification may enhance sensitivity.

• Proximity extension assays: These highly sensitive assays can detect proteins in minute samples by combining antibody binding with DNA-based signal amplification. Antibody conjugation to oligonucleotides would be required.

• Spatial transcriptomics integration: Combine immunodetection of At3g17400 with in situ RNA analysis to correlate protein expression with transcriptional states at tissue resolution.

These adaptations can provide unprecedented insights into cell-to-cell variation in At3g17400 expression and function within plant tissues .

What considerations are important when using At3g17400 antibody in cross-species studies?

When applying the At3g17400 antibody to study related proteins in other plant species:

• Sequence homology analysis: Before experimental work, conduct bioinformatic analysis to identify homologs in target species and assess sequence conservation at epitope regions. Higher conservation suggests higher cross-reactivity probability.

• Validation in each species: Perform species-specific validation using positive and negative controls from each target organism. Western blotting with tissue from knockout mutants provides the strongest validation.

• Epitope mapping: Consider epitope mapping to determine which regions of At3g17400 are recognized by the antibody, then assess conservation of these specific regions across species.

• Preabsorption controls: If studying closely related species, perform preabsorption with recombinant proteins from the target species to reduce non-specific binding.

• Comparative sensitivity analysis: Determine detection thresholds for each species, as antibody affinity may vary even with conserved epitopes.

• Alternative antibody development: For distantly related species, consider developing species-specific antibodies using conserved peptide regions as immunogens.

These approaches increase confidence in cross-species studies and help avoid misinterpretation of results due to variable antibody performance across species .

How does antibody batch variation affect experimental reproducibility with At3g17400 antibody?

Antibody batch variation is a significant concern for experimental reproducibility:

• Batch validation protocol: Establish a standardized protocol to validate each new batch against previous ones using:

  • Side-by-side Western blot comparison with standardized samples

  • ELISA to quantitatively compare antigen recognition

  • Immunoprecipitation efficiency testing with consistent input material

• Reference sample banking: Maintain frozen aliquots of reference samples (positive controls) that can be used to test new antibody batches for consistent performance.

• Batch information documentation: Record batch numbers, production dates, and validation results in laboratory notebooks and publications to enable proper replication.

• Dilution optimization: Each batch may require different working dilutions for optimal results. Determine these through titration experiments.

• Long-term planning: When critical experiments span extended periods, consider securing sufficient antibody from a single batch or validate batch equivalence before switching.

• Manufacturer communication: Maintain communication with the antibody supplier about production methods and quality control procedures that might affect batch consistency.

These practices mitigate the impact of batch variation on experimental outcomes and enhance reproducibility in At3g17400 research .