At3g47420 Antibody

What is the At3g47420 antibody and what organism is it specific for?

At3g47420 antibody is a polyclonal antibody raised in rabbits against recombinant Arabidopsis thaliana At3g47420 protein. This antibody has been specifically designed to recognize and bind to At3g47420 protein in Arabidopsis thaliana (Mouse-ear cress), making it a valuable tool for researchers studying this model plant organism . The antibody has been affinity-purified against the target antigen to enhance its specificity and reduce background binding to non-target proteins.

What are the validated applications for At3g47420 antibody?

The At3g47420 antibody has been validated for use in Enzyme-Linked Immunosorbent Assay (ELISA) and Western Blot (WB) applications. These techniques allow researchers to detect and quantify the target protein in different experimental contexts. ELISA provides quantitative measurement of the target protein in solution, while Western Blotting enables visualization of the protein in cell or tissue lysates, confirming its molecular weight and expression levels . When designing experiments with this antibody, researchers should prioritize these validated applications to ensure reliable results.

What is the molecular basis for the antibody's recognition of At3g47420?

The At3g47420 antibody recognizes specific epitopes on the At3g47420 protein (UniProt accession: Q9C5L3). The antibody was generated using a recombinant Arabidopsis thaliana At3g47420 protein as the immunogen . The polyclonal nature of this antibody means it contains a heterogeneous mixture of antibodies that recognize different epitopes on the target protein, potentially providing robust detection across various experimental conditions. This multi-epitope recognition can be particularly valuable when studying proteins that undergo post-translational modifications or exist in different conformational states.

What are the optimal storage conditions for maintaining At3g47420 antibody activity?

For optimal preservation of At3g47420 antibody activity, storage at -20°C or -80°C is recommended. It is crucial to avoid repeated freeze-thaw cycles as they can lead to protein denaturation and loss of antibody functionality . The antibody is typically provided in a storage buffer containing 0.03% Proclin 300, 50% Glycerol, and 0.01M PBS at pH 7.4, which helps maintain stability during storage. For long-term storage planning, it's advisable to aliquot the antibody upon receipt to minimize freeze-thaw cycles and preserve antibody performance across multiple experiments.

How should aliquoting be performed to maintain antibody integrity?

When aliquoting the At3g47420 antibody, researchers should:

• Thaw the stock antibody slowly on ice

• Prepare sterile microcentrifuge tubes

• Dispense small working volumes (typically 10-20 μl) into each tube

• Quickly return unused aliquots to -20°C or -80°C storage

• Document the freeze-thaw history of each aliquot

This approach minimizes exposure to room temperature and prevents bacterial contamination that could degrade the antibody. Proper aliquoting is especially important for valuable antibodies with long lead times, such as the At3g47420 antibody which has a 14-16 week lead time for production .

What reconstitution protocols are recommended for lyophilized antibody formats?

If the At3g47420 antibody is provided in lyophilized format, it should be reconstituted by adding a precise volume of sterile water or buffer. Based on similar antibody products, approximately 50 μl of sterile water should be added to reconstitute 50 μg of lyophilized antibody . After adding the reconstitution solution, the vial should be gently rotated (not vortexed) to ensure complete dissolution without causing protein denaturation. Once reconstituted, the antibody should be aliquoted and stored as described above to prevent degradation from repeated freeze-thaw cycles.

How should antibody concentration be optimized for Western blot applications?

Optimizing antibody concentration for Western blot applications requires a systematic titration approach. Based on research with other antibodies, the optimal concentration often falls between 0.625 and 2.5 μg/mL, rather than the higher 5-10 μg/mL range commonly recommended by commercial vendors . Researchers should:

• Perform an initial titration experiment using a dilution series (e.g., 2.5, 1.25, 0.625, 0.3125 μg/mL)

• Evaluate signal-to-noise ratio at each concentration

• Select the lowest concentration that provides clear specific signal with minimal background

This optimization process is particularly important when working with polyclonal antibodies like At3g47420, as excessive antibody concentration can lead to high background without improving specific signal detection .

What controls should be included when validating At3g47420 antibody specificity?

When validating the specificity of the At3g47420 antibody, several controls should be included:

How can signal-to-noise ratio be improved when working with At3g47420 antibody?

To improve signal-to-noise ratio with At3g47420 antibody, researchers should consider implementing several optimization strategies:

• Optimize blocking conditions by testing different blocking agents (BSA, non-fat milk, commercial blockers) and concentrations

• Increase washing duration and frequency between antibody incubations

• Reduce primary antibody concentration if high background persists

• Optimize incubation times and temperatures for primary antibody binding

• Consider using more sensitive detection systems for low-abundance targets

What are common causes of false negative results with At3g47420 antibody and how can they be addressed?

False negative results when using At3g47420 antibody can stem from multiple factors:

Given that At3g47420 antibody is species-specific for Arabidopsis thaliana, researchers should also verify that their experimental system expresses the target protein at detectable levels .

How can the specificity of At3g47420 antibody be validated using molecular techniques?

Validating antibody specificity is crucial for reliable research outcomes. For At3g47420 antibody, researchers can employ these molecular validation strategies:

• Genetic knockout validation: Compare antibody signal between wild-type and At3g47420 knockout plants.

• RNAi verification: Correlate reduced protein signal with degree of target gene knockdown.

• Heterologous expression: Express tagged At3g47420 protein and confirm co-detection with tag-specific antibody.

• Mass spectrometry validation: Immunoprecipitate with At3g47420 antibody and confirm target identity via mass spectrometry.

• Peptide competition: Pre-incubate antibody with immunizing peptide to block specific binding.

These approaches provide complementary evidence for antibody specificity, strengthening confidence in experimental results obtained with At3g47420 antibody .

What strategies can address non-specific binding issues with At3g47420 antibody?

Non-specific binding can compromise experimental results with At3g47420 antibody. To address this issue:

• Increase blocking stringency using higher concentrations of blocking agents

• Add carrier proteins (0.1-0.5% BSA) to antibody dilution buffer

• Pre-adsorb the antibody against tissues lacking the target protein

• Include competitors for common non-specific interactions (e.g., non-immune IgG)

• Optimize washing buffer composition (consider adding 0.1-0.5% Triton X-100 or Tween-20)

• Titrate antibody concentration to identify the minimal effective concentration

Research on antibody optimization indicates that higher antibody concentrations often contribute disproportionately to background signal without improving specific detection , making careful titration a key strategy for reducing non-specific binding.

How can At3g47420 antibody be integrated into multi-parameter experimental designs?

Integrating At3g47420 antibody into multi-parameter experimental designs requires careful planning and optimization. For complex experimental approaches:

• Multiplex immunoblotting: When combining At3g47420 antibody with other antibodies, ensure sufficient separation of target proteins by molecular weight and use antibodies raised in different host species to allow simultaneous detection with species-specific secondary antibodies.

• Sequential immunodetection: For targets with similar molecular weights, consider sequential probing with stripping between detections, validating that the stripping procedure does not affect remaining epitopes.

• Co-immunoprecipitation studies: When using At3g47420 antibody for co-IP studies, optimize antibody concentration for efficient target capture while minimizing non-specific binding that could lead to false identification of interaction partners.

• Cross-linking strategies: For studying transient protein interactions, combine antibody detection with chemical cross-linking approaches, validating that cross-linking doesn't interfere with antibody epitope recognition.

Recent advances in active learning approaches for antibody-antigen binding prediction can help optimize experimental design when working with multiple antibodies simultaneously .

What considerations are important when using At3g47420 antibody in plant tissues with complex matrices?

Working with plant tissues presents unique challenges for antibody applications due to complex matrices containing polyphenols, polysaccharides, and proteases. When using At3g47420 antibody in plant tissue experiments:

• Include extraction buffer additives to neutralize interfering compounds (PVPP for polyphenols, protease inhibitors)

• Optimize extraction buffer composition based on tissue type (roots, leaves, reproductive tissues)

• Consider protein fractionation to enrich for the cellular compartment containing the target protein

• Validate antibody performance across different tissue types to identify matrix-specific interference

• Implement additional purification steps (e.g., ammonium sulfate precipitation, ion exchange chromatography) before immunodetection in particularly challenging tissues

Since At3g47420 antibody is specifically designed for Arabidopsis thaliana, researchers should be aware that tissue-specific expression patterns may affect detection sensitivity across different plant organs .

How can active learning approaches improve experimental design when using At3g47420 antibody for novel applications?

Active learning strategies can significantly enhance experimental efficiency when exploring novel applications for At3g47420 antibody. These approaches involve:

• Starting with small-scale pilot experiments to generate initial data

• Using computational models to predict optimal conditions for subsequent experiments

• Iteratively expanding the experimental dataset based on model predictions

• Focusing resources on the most informative experiments rather than exhaustive parameter screening

Recent research demonstrated that active learning strategies improved antibody-antigen binding prediction by reducing the number of required variants by up to 35% and accelerating the learning process compared to random sampling approaches . For researchers exploring At3g47420 antibody in new experimental contexts, implementing such data-driven experimental design can maximize research efficiency while minimizing resource expenditure.