At2g03931 Antibody

What is the At2g03931 protein and why is it studied?

At2g03931 encodes a Defensin-like (DEFL) family protein in Arabidopsis thaliana (Mouse-ear cress). Defensin-like proteins constitute an important group of small cysteine-rich peptides that typically play roles in plant immune responses against pathogens. The study of At2g03931 contributes to our understanding of plant immunity and defense mechanisms in model organisms. This protein is identified in various databases with UniProtKB identifiers DEF55_ARATH and A0A654EWN9_ARATH, and UniprotKB accession numbers Q2V2Q4 and A0A654EWN9 .

What are the key specifications of the At2g03931 Antibody?

The commercially available At2g03931 Antibody (product code CSB-PA648849XA01DOA) targets the Q2V2Q4 UniProt protein from Arabidopsis thaliana. This antibody is typically available in two size options: 2ml or 0.1ml, similar to other Arabidopsis antibodies in the same catalog . When selecting this antibody for your research, it's crucial to verify the validation methods used by the manufacturer to ensure specificity and sensitivity for your particular application.

What validation methods should I expect for the At2g03931 Antibody?

A properly validated At2g03931 Antibody should undergo several validation pillars as described by Uhlen et al. (2016). These include:

• Genetic validation (using knockout or knockdown samples)

• Orthogonal validation (comparing antibody results with another method)

• Independent antibody validation (using different antibodies targeting the same protein)

• Expression pattern validation (comparing observed patterns with known expression)

• Immunoprecipitation followed by mass spectrometry validation

For immunohistochemistry applications specifically, validation should include positive and negative controls, concentration gradients, and reproducibility assessments across different tissue preparations .

How should I store and handle the At2g03931 Antibody?

While specific storage recommendations for At2g03931 Antibody should be obtained from the manufacturer, general antibody handling principles apply. Store antibodies according to manufacturer recommendations, typically at -20°C for long-term storage or at 4°C for short-term use. Avoid repeated freeze-thaw cycles by preparing small aliquots. When working with the antibody, maintain cold chain and use sterile techniques to prevent contamination. Document lot numbers, receipt dates, and thawing events to track antibody performance over time.

What are the optimal conditions for using At2g03931 Antibody in immunohistochemistry of plant tissues?

When performing immunohistochemistry with At2g03931 Antibody on plant tissues, consider these methodological approaches:

• Fixation optimization: Test different fixatives including 4% paraformaldehyde, cold acetone, or ethanol-based fixatives to determine which best preserves epitope recognition while maintaining tissue architecture.

• Antigen retrieval: Plant tissues often require specialized antigen retrieval protocols. Test heat-induced epitope retrieval (HIER) with citrate buffer (pH 6.0) and EDTA buffer (pH 9.0), as well as enzymatic retrieval using proteinase K.

• Blocking optimization: Use 5-10% normal serum from the species in which the secondary antibody was raised, combined with 0.1-0.3% Triton X-100 for cell permeabilization.

• Antibody titration: Perform a concentration gradient (typically 1:100 to 1:1000) to determine optimal signal-to-noise ratio.

• Controls: Include both negative controls (no primary antibody, isotype control) and positive controls (tissues known to express the target protein) .

How can I validate the specificity of At2g03931 Antibody in my experimental system?

Validating antibody specificity for At2g03931 requires a multi-pronged approach:

• Genetic validation: Use T-DNA insertion lines or CRISPR/Cas9-generated knockout lines of At2g03931 in Arabidopsis as negative controls. The absence of signal in these lines strongly supports antibody specificity.

• Western blot analysis: Perform western blotting with plant extracts to confirm the antibody detects a band of the expected molecular weight (~7-8 kDa for typical defensin-like proteins).

• Peptide competition assay: Pre-incubate the antibody with the immunizing peptide before application to samples. Signal elimination indicates specificity.

• Orthogonal validation: Compare protein expression patterns detected by the antibody with mRNA expression data from RNA-seq or RT-qPCR.

• Mass spectrometry validation: Perform immunoprecipitation followed by mass spectrometry to confirm the identity of the pulled-down protein .

This comprehensive validation approach increases confidence in experimental results and helps identify potential cross-reactivity issues.

What are the challenges in detecting low-abundance defensin-like proteins like At2g03931?

Detecting low-abundance defensin-like proteins such as At2g03931 presents several challenges:

• Signal amplification methods: Consider employing tyramide signal amplification (TSA) or rolling circle amplification (RCA) to enhance detection sensitivity without increasing background.

• Sample enrichment: Use subcellular fractionation to concentrate the protein of interest from specific cellular compartments where defensin-like proteins typically localize.

• Cross-reactivity risk: Due to the high sequence similarity among defensin family members, validate the antibody against closely related defensins to ensure specificity.

• Protein extraction optimization: Develop specialized extraction protocols that account for the small size and potential disulfide bonding of defensin-like proteins. Using reducing agents like DTT or β-mercaptoethanol may be necessary to break disulfide bonds.

• Dynamic expression patterns: Defensin expression is often induced under specific stress conditions. Design experiments to capture the appropriate developmental stage or stress response when At2g03931 is most likely to be expressed .

How can I implement humanoid antibody approaches to improve At2g03931 detection?

While humanoid antibody approaches are primarily designed for therapeutic applications, their principles can be adapted for research antibodies:

• GAN-based design: Generative Adversarial Networks (GANs) can be used to design improved antibody variants with higher specificity for At2g03931. This computational approach can generate sequence variations that potentially improve binding characteristics.

• CDR optimization: Focus on complementarity-determining regions (CDRs) modifications to enhance specificity while maintaining the framework regions that contribute to stability.

• Transfer learning approaches: Apply bioinformatic tools that have been trained on large antibody datasets to predict modifications that would improve the performance characteristics specific to plant protein detection.

• Stability engineering: Incorporate features that improve stability under various experimental conditions, such as different fixation methods or buffer compositions used in plant research.

• Sequential screening: Generate a library of antibody variants and screen them against the target protein and potential cross-reactive defensin family members to select variants with optimal specificity profiles .

What are the key molecular identifiers for At2g03931?

This comprehensive collection of identifiers facilitates cross-referencing across different biological databases, enabling researchers to access additional information about At2g03931 .

What antibody validation techniques are most relevant for defensin-like proteins?

When validating antibodies for defensin-like proteins, combining multiple techniques provides the strongest evidence for antibody specificity and reliability .

What are common issues when using plant defensin antibodies and their solutions?

Plant defensin antibodies, including those targeting At2g03931, can present several challenges:

• Weak signal: Plant defensins are typically small and expressed at low levels. Optimize extraction methods using specialized buffers containing detergents suitable for membrane-associated proteins. Consider signal amplification methods such as biotin-streptavidin systems or tyramide signal amplification.

• High background: Implement rigorous blocking protocols using a combination of BSA, non-fat dry milk, and normal serum. Add 0.1-0.3% Tween-20 to wash buffers to reduce non-specific binding. Increase the number and duration of washing steps.

• Cross-reactivity: Pre-absorb the antibody with plant extracts from species without the target protein. Alternatively, use competitive ELISAs to assess cross-reactivity with related defensin proteins.

• Batch-to-batch variation: Always validate new antibody lots against previously working lots using standardized positive controls. Document lot numbers and performance characteristics for longitudinal studies.

• Epitope masking: Test multiple antigen retrieval methods if working with fixed tissues, as defensin proteins may form disulfide bonds that affect epitope accessibility .

How can I optimize protein extraction protocols specifically for At2g03931 detection?

Optimizing protein extraction for At2g03931 detection requires consideration of the unique characteristics of defensin-like proteins:

• Buffer composition: Use extraction buffers containing 50 mM Tris-HCl (pH 7.5), 150 mM NaCl, 1% Triton X-100, 0.5% sodium deoxycholate, and 0.1% SDS. Add protease inhibitor cocktail to prevent degradation.

• Reducing agents: Include DTT (1-5 mM) or β-mercaptoethanol (5%) to break disulfide bonds that are common in defensin-like proteins.

• Mechanical disruption: For plant tissues, use bead beating or cryogenic grinding to ensure complete tissue disruption while maintaining cold temperatures.

• Differential centrifugation: Perform sequential centrifugation steps (1,000g, 10,000g, 100,000g) to isolate different cellular fractions, as defensin-like proteins may localize to specific compartments.

• Enrichment techniques: Consider immunoprecipitation or affinity purification to concentrate the target protein before analysis.

• Sample denaturation: Heat samples at 95°C in sample buffer for 5-10 minutes to ensure complete denaturation before electrophoresis .

How is At2g03931 Antibody used in studying plant-pathogen interactions?

The At2g03931 Antibody serves as a valuable tool for investigating plant immune responses:

• Pathogen challenge studies: Track At2g03931 protein accumulation following inoculation with various pathogens to determine its role in specific defense responses.

• Subcellular localization: Use immunofluorescence microscopy to determine where At2g03931 protein localizes during pathogen attack, providing insights into its mechanism of action.

• Protein-protein interactions: Employ co-immunoprecipitation with At2g03931 Antibody to identify interacting partners during immune responses.

• Transgenic line validation: Confirm protein expression levels in At2g03931 overexpression or knockdown lines used for functional studies.

• Comparative studies: Examine At2g03931 expression across ecotypes with varying disease resistance to correlate protein levels with phenotypic responses.

This antibody enables researchers to move beyond transcriptomic studies to directly examine protein-level responses in plant defense systems .

What emerging technologies might improve antibody-based detection of plant defensin proteins?

Several emerging technologies show promise for enhancing the detection and characterization of defensin proteins like At2g03931:

• Single-molecule detection: Techniques like single-molecule localization microscopy (SMLM) can enhance sensitivity for detecting low-abundance defensin proteins.

• Proximity labeling: Methods such as BioID or APEX can identify proteins in close proximity to At2g03931 in living cells, helping map functional protein networks.

• Nanobody development: Single-domain antibodies derived from camelids could provide improved access to epitopes in complex plant tissue samples.

• Mass cytometry: CyTOF technology combining flow cytometry with mass spectrometry could enable multiplexed detection of defensin proteins alongside other markers.

• Computational antibody design: Machine learning approaches like those used in humanoid antibody development can generate improved antibodies with enhanced specificity and sensitivity for plant proteins.

• CRISPR epitope tagging: Precise genomic integration of tags can facilitate antibody-independent detection while validating antibody specificity .