At5g19172 Antibody

What is At5g19172 and what organism is it associated with?

At5g19172 is a gene found in Arabidopsis thaliana (Mouse-ear cress), a model organism widely used in plant molecular biology research . The protein encoded by this gene serves as the target antigen for the At5g19172 antibody. Arabidopsis thaliana is particularly valuable in research due to its relatively small genome, short generation time, and extensive genetic and molecular tools available for its study. The At5g19172 antibody is specifically raised against recombinant Arabidopsis thaliana At5g19172 protein, making it a valuable tool for investigating this particular plant protein .

What are the general characteristics of the At5g19172 Antibody?

The At5g19172 Antibody is a polyclonal antibody raised in rabbits using recombinant Arabidopsis thaliana At5g19172 protein as the immunogen . It is supplied in liquid form with a storage buffer containing 50% Glycerol, 0.01M PBS (pH 7.4), and 0.03% Proclin 300 as a preservative . This antibody has been purified using antigen affinity methods and is specifically designed to react with Arabidopsis thaliana samples . The antibody is intended exclusively for research applications, particularly in techniques such as ELISA and Western Blotting where identification of the At5g19172 antigen is required .

How should At5g19172 Antibody be stored for optimal performance?

For optimal performance and longevity, the At5g19172 Antibody should be stored at -20°C or -80°C upon receipt . It's crucial to avoid repeated freeze-thaw cycles as this can lead to antibody degradation and loss of activity. The antibody is supplied in a buffer containing 50% glycerol, which helps prevent freeze damage and maintains stability during storage . For short-term use, small aliquots can be prepared to minimize the number of freeze-thaw cycles. Proper storage is essential for maintaining the antibody's specificity and sensitivity in research applications such as Western blotting and ELISA.

How should experiments using At5g19172 Antibody be designed for optimal results?

When designing experiments with At5g19172 Antibody, researchers should follow a systematic approach that begins with proper experimental controls. For Western blotting or ELISA experiments, it's advisable to include both positive controls (known samples containing At5g19172) and negative controls (samples without the target) . Power calculations should be performed to determine appropriate sample sizes, similar to antibody characterization studies where five animals per group provides 80% power to detect significant differences .

When determining optimal antibody concentrations, a titration experiment should be conducted using serial dilutions to establish the minimum concentration that provides specific signal without background. Based on general antibody methodologies, the following experimental design is recommended:

The experimental design should also account for the specific properties of plant tissue samples, which may require additional optimization of protein extraction and sample preparation protocols .

What methods are recommended for validating the specificity of At5g19172 Antibody?

Validating antibody specificity is critical for ensuring reliable research results. For At5g19172 Antibody, multiple validation approaches should be employed:

First, perform Western blotting with recombinant At5g19172 protein alongside plant extracts to confirm specific binding . The antibody should detect a band of the expected molecular weight in wild-type samples.

Second, include appropriate controls such as knockout/knockdown plant lines lacking At5g19172 expression, which should show reduced or absent signal . This genetic validation approach provides strong evidence of specificity.

Third, conduct immunoprecipitation followed by mass spectrometry to confirm that the antibody is capturing the intended target protein. This technique can identify both the target protein and any potential cross-reactive proteins .

Fourth, perform immunohistochemistry with competing peptide blocking to demonstrate that pre-incubation with the immunizing peptide eliminates specific staining, a technique commonly used for antibody validation in neural tissue research .

These multi-modal validation approaches collectively provide robust evidence for antibody specificity, which is essential for confident interpretation of experimental results.

What are the validated applications for At5g19172 Antibody?

The At5g19172 Antibody has been specifically validated for two primary applications: Enzyme-Linked Immunosorbent Assay (ELISA) and Western Blotting (WB) . These techniques allow researchers to detect and quantify the presence of At5g19172 protein in various samples.

In ELISA applications, the antibody can be used to detect the presence of At5g19172 in solution, providing a quantitative measurement of protein concentration. This method is particularly useful for high-throughput screening and quantitative analysis of protein levels across multiple samples .

For Western Blotting, the antibody enables the detection of At5g19172 protein in complex mixtures after separation by gel electrophoresis. This technique allows researchers to confirm the molecular weight of the detected protein and assess its expression levels in different experimental conditions .

While not explicitly validated by the manufacturer, similar polyclonal antibodies may potentially be used in immunohistochemistry, immunofluorescence, or immunoprecipitation after proper optimization and validation by the researcher.

How can I optimize Western Blotting protocols for At5g19172 Antibody?

Optimizing Western Blotting protocols for At5g19172 Antibody requires attention to several key parameters to ensure specific signal detection while minimizing background noise. Based on antibody methodology principles, the following optimization steps are recommended:

• Sample Preparation: For plant tissues containing At5g19172, use a buffer containing phosphatase and protease inhibitors to prevent protein degradation. Typical extraction buffers include 50mM Tris-HCl (pH 7.5), 150mM NaCl, 1% Triton X-100, and protease inhibitor cocktail.

• Protein Loading: Load 20-50μg of total protein per lane, as determined by Bradford or BCA protein assay, to ensure adequate detection of At5g19172.

• Blocking Optimization: Test both 5% non-fat milk and 5% BSA in TBST as blocking agents to determine which provides lower background with this specific antibody .

• Antibody Dilution: Begin with a 1:1000 dilution and adjust based on signal intensity. A titration experiment using dilutions from 1:500 to 1:5000 can help identify the optimal concentration that maximizes specific signal while minimizing background.

• Incubation Conditions: For primary antibody incubation, compare overnight at 4°C versus 2 hours at room temperature to determine optimal binding conditions.

• Detection System: For plant proteins like At5g19172, HRP-conjugated secondary antibodies with enhanced chemiluminescence detection typically provide good sensitivity and signal-to-noise ratio.

Implementing these optimization steps will help ensure reliable and reproducible Western blotting results when using the At5g19172 Antibody.

How should researchers analyze data from experiments using At5g19172 Antibody?

Data analysis from At5g19172 Antibody experiments requires rigorous statistical approaches tailored to the specific application. For quantitative Western blotting, densitometric analysis should be performed using specialized software, with normalization to loading controls such as actin or GAPDH. Data should be expressed as relative intensity ratios rather than absolute values .

For ELISA data, standard curves should be generated using four-parameter logistic (4PL) models with the following functional form: y = L+(U − L)/(1 + (x/ID50)^h), where L is the minimum value, U is the maximum value, ID50 is the inflection point, and h is the Hill slope . This model provides more accurate quantification than linear regression, especially for sigmoidal dose-response relationships common in antibody studies.

Statistical analysis should include tests for normality (Shapiro-Wilk) before applying parametric tests. For comparison between multiple experimental groups, ANOVA followed by appropriate post-hoc tests should be employed. Power analysis prior to experimentation helps ensure sufficient sample sizes are used; current experimental designs using five samples per group provide 80% power to detect 2.9-fold differences in signal intensity .

When analyzing data from multiple experiments, finite mixture models based on scale mixtures of Skew-Normal distributions may be appropriate, particularly when dealing with asymmetric distributions commonly observed in antibody data .

What statistical approaches are appropriate for analyzing antibody dilution series experiments?

When analyzing antibody dilution series experiments with At5g19172 Antibody, researchers should employ robust statistical methods that account for the non-linear relationship between antibody concentration and signal intensity. Four-parameter logistic (4PL) models are recommended for fitting dilution curves as they accurately capture the upper and lower plateaus as well as the inflection point of typical sigmoidal antibody responses .

The 4PL model is represented by the equation: y = L+(U − L)/(1 + (x/ID50)^h), where:

• L is the minimum signal (lower asymptote)

• U is the maximum signal (upper asymptote)

• ID50 is the dilution producing 50% of maximum signal

• h is the Hill slope determining curve steepness

For determining optimal antibody concentration, researchers should calculate the coefficient of variation (CV) across replicates at each dilution point. The dilution with the lowest CV while maintaining adequate signal strength typically represents the optimal working concentration.

When comparing the performance of At5g19172 Antibody across different experimental conditions, statistical significance should be assessed using paired t-tests (for comparing two conditions) or repeated measures ANOVA (for multiple conditions). For non-normally distributed data, non-parametric alternatives such as Wilcoxon signed-rank test or Friedman test should be employed .

Power analysis should be conducted prior to experimentation to ensure adequate sample size; typically, experiments with 4-5 technical replicates provide sufficient statistical power for dilution series analysis .

How can researchers troubleshoot non-specific binding issues with At5g19172 Antibody?

Non-specific binding is a common challenge when working with antibodies including At5g19172 Antibody. Several methodological approaches can address this issue:

First, optimize blocking conditions by testing different blocking agents (5% BSA, 5% non-fat milk, commercial blocking buffers) and extending blocking time to 2 hours at room temperature. Different blocking agents perform differently depending on the specific antibody and sample type .

Second, adjust antibody concentration, as excessive antibody often increases background. Perform a titration series (1:500, 1:1000, 1:2000, 1:5000) to identify the optimal dilution that maximizes specific signal while minimizing background .

Third, increase washing stringency by adding additional wash steps (5-6 washes instead of 3) and including detergents (0.1-0.3% Tween-20 or 0.05% Triton X-100) in wash buffers to reduce non-specific hydrophobic interactions .

Fourth, pre-adsorb the antibody with proteins from a similar species that doesn't express the target protein. This can reduce cross-reactivity with non-target proteins that share epitopes with At5g19172 .

Finally, consider adding divalent cation chelators (1-5mM EDTA) to blocking and antibody dilution buffers when working with plant samples, as this can reduce non-specific interactions mediated by divalent cations common in plant tissues .

Implementing these strategic approaches systematically will help identify and resolve the specific source of non-specific binding in your experimental system.

What are the limitations of using At5g19172 Antibody across different plant species?

The At5g19172 Antibody was specifically raised against recombinant Arabidopsis thaliana At5g19172 protein, which introduces important limitations when considering its use across different plant species .

First, the antibody's cross-reactivity with homologous proteins in other plant species depends on epitope conservation. Even closely related species may have sequence variations at the antibody binding site that reduce or eliminate recognition. Unlike monoclonal antibodies that recognize single epitopes, this polyclonal antibody recognizes multiple epitopes, which may offer some advantage for cross-species applications but still requires validation .

Second, plant-specific post-translational modifications vary across species and affect antibody binding. Glycosylation patterns, in particular, may differ substantially between Arabidopsis and other plants, potentially altering epitope accessibility or structure .

Third, background protein composition varies significantly across plant species, potentially introducing new sources of cross-reactivity not present in Arabidopsis. This necessitates more stringent blocking and washing conditions when working with non-target species .

A systematic validation approach is essential when using this antibody in non-Arabidopsis species:

How can At5g19172 Antibody be integrated with genomic approaches?

Integrating At5g19172 Antibody with genomic approaches represents an advanced research strategy that combines protein-level detection with genetic analysis. Researchers can correlate antibody-based protein detection with genomic data from platforms such as easyGWAS, which provides SNP (Single Nucleotide Polymorphism) analysis relevant to At5g19172 .

One powerful approach is ChIP-seq (Chromatin Immunoprecipitation followed by sequencing), which could potentially use At5g19172 Antibody to identify DNA binding sites if the protein has DNA-binding properties. This technique would require additional validation of the antibody for immunoprecipitation applications beyond its current validated uses in ELISA and Western blotting .

For expression Quantitative Trait Loci (eQTL) studies, researchers can correlate genetic variations identified through genomic approaches with protein expression levels detected by the At5g19172 Antibody. This integration enables the identification of genetic variants that influence At5g19172 protein expression.

When combining antibody-based detection with transcriptomic data, researchers should be aware that mRNA and protein levels may not always correlate perfectly due to post-transcriptional regulation. The following analytical framework is recommended:

• Quantify At5g19172 protein levels using the antibody in Western blotting or ELISA

• Measure At5g19172 transcript levels using RT-qPCR or RNA-seq

• Analyze genetic variation in the At5g19172 locus using SNP data

• Apply statistical models such as finite mixture models to integrate these multi-omics datasets

This integrated approach provides a more comprehensive understanding of At5g19172 function and regulation than any single method alone.

What are emerging applications for At5g19172 Antibody in plant stress response research?

Although At5g19172 Antibody was primarily developed for basic detection applications in ELISA and Western blotting , recent advances in plant molecular biology suggest potential applications in stress response research. As with other plant proteins, At5g19172 may play roles in specific stress response pathways that can be investigated using this antibody.

For abiotic stress studies, the antibody can be used to track changes in At5g19172 protein levels across different stress conditions (drought, salt, temperature, light) and time points. Western blotting with the antibody allows quantification of protein expression changes that may not be detected at the transcriptional level due to post-transcriptional regulation .

In biotic stress research, the antibody could potentially reveal interactions between At5g19172 and pathogen-associated molecular patterns (PAMPs) if the protein participates in immune response pathways. Co-immunoprecipitation followed by mass spectrometry could identify interaction partners that appear specifically during pathogen challenge.

For subcellular localization studies, researchers could optimize the antibody for immunohistochemistry to determine whether At5g19172 undergoes stress-induced relocalization, which often occurs with signaling proteins involved in stress responses.

A comprehensive experimental design for stress response studies would include:

• Time-course analysis of protein expression across multiple stress conditions

• Correlation of protein levels with physiological parameters of stress response

• Comparison between wild-type and mutant/transgenic lines with altered At5g19172 expression

• Potential co-localization studies with known stress response markers

While these applications extend beyond the manufacturer-validated uses, they represent logical extensions based on established principles of plant molecular biology research.

What are the key considerations for researchers planning to use At5g19172 Antibody?

Researchers planning to use At5g19172 Antibody should consider several critical factors to ensure experimental success. First, proper experimental design is essential, including appropriate controls and sample sizes determined through power analysis . The antibody has been specifically validated for ELISA and Western blotting applications in Arabidopsis thaliana samples, so researchers should exercise caution when extending to other applications or species without thorough validation .

Storage conditions significantly impact antibody performance; the At5g19172 Antibody should be stored at -20°C or -80°C with minimal freeze-thaw cycles to maintain reactivity . For optimal results in Western blotting, researchers should optimize blocking conditions, antibody dilutions, and washing protocols through systematic testing .

Specificity validation is paramount and should include multiple approaches such as knockout/knockdown controls, peptide competition assays, and potentially mass spectrometry confirmation of target identity . When analyzing data, appropriate statistical methods should be employed, including four-parameter logistic models for dilution series and proper normalization for quantitative comparisons .