At5g38396 Antibody

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Description

Basic Characteristics of At5g38396 Antibody

The antibody is designed for specificity and sensitivity in protein detection. Key technical details include:

PropertySpecification
HostRabbit
ReactivityArabidopsis thaliana (Mouse-ear cress)
ImmunogenRecombinant Arabidopsis thaliana At5g38396 protein
Purification MethodAntigen-affinity purification
IsotypeIgG
ClonalityPolyclonal
ConjugateNon-conjugated
Storage Buffer50% Glycerol, 0.01M PBS, pH 7.4 (with 0.03% Proclin 300 preservative)
ApplicationsELISA, WB (validated for antigen identification)
Product CodesMBS7193744 (MyBioSource), CSB-PA659051XA01DOA (Cusabio)

Data compiled from .

Potential Challenges and Considerations

  • Specificity: Polyclonal antibodies may cross-react with homologous proteins. Validation via WB is critical to confirm target specificity .

  • Availability: The antibody is made-to-order (14–16 weeks lead time for Cusabio product), which may limit rapid experimental workflows .

  • Unresolved Research Gaps: No peer-reviewed studies explicitly citing At5g38396 Antibody use were identified in the reviewed sources. This underscores the need for further validation in experimental contexts.

Comparative Analysis with Other Arabidopsis Antibodies

The At5g38396 Antibody shares characteristics with other plant-specific antibodies but lacks documented use in high-throughput studies. Below is a comparison with antibodies targeting related F-box proteins:

Antibody TargetHostApplicationsKey Differentiators
At5g38396 AntibodyRabbitELISA, WBTargets F-box/LRR-repeat protein; limited published data
TIR1 (F-box protein)MouseIP, WBExtensively studied in auxin signaling pathways
SKP2 (F-box protein)RabbitIP, ChIPRole in cell cycle regulation

Future Directions

To expand the utility of the At5g38396 Antibody, researchers should:

  1. Validate cross-reactivity: Test against homologs in Brassica or other model plants.

  2. Optimize protocols: Develop standardized WB/ELISA conditions for Arabidopsis tissue lysates.

  3. Integrate with omics: Combine antibody-based detection with transcriptomic/proteomic datasets to map At5g38396’s functional networks.

Product Specs

Buffer
Preservative: 0.03% Proclin 300
Composition: 50% Glycerol, 0.01M PBS, pH 7.4
Form
Liquid
Lead Time
Made-to-order (14-16 weeks)
Synonyms
At5g38396 antibody; MXI10F-box/LRR-repeat protein At5g38396 antibody
Target Names
At5g38396
Uniprot No.

Q&A

FAQs for At5g38396 Antibody in Academic Research

How do I validate At5g38396 antibody specificity in Arabidopsis thaliana studies?

  • Methodological Answer:

    • Peptide Blocking: Pre-incubate the antibody with the immunizing peptide (e.g., APTEK-26 for anti-GR antibodies ). A ≥50% reduction in signal confirms specificity.

    • Knockout Controls: Use Arabidopsis lines with CRISPR/Cas9-mediated At5g38396 deletion. Compare Western blot signals between wild-type and knockout lysates .

    • Cross-Reactivity Testing: Test against lysates from plants expressing homologs (e.g., F-box/RNI-like proteins) to rule out off-target binding .

What experimental designs optimize At5g38396 detection in plant tissues?

  • Methodological Answer:

    • Tissue-Specific Extraction: Use extraction buffers with 1% Triton X-100 + protease inhibitors for membrane-bound proteins .

    • Multiplex Controls: Include housekeeping proteins (e.g., actin) and empty vector-transfected samples to normalize and validate signal specificity .

    • Dose-Response Curves: Titrate antibody concentrations (0.1–2 µg/mL) to identify the linear detection range .

How to resolve contradictory data in At5g38396 localization studies?

  • Methodological Answer:

    • Epitope Mapping: Perform alanine-scanning mutagenesis on the At5g38396 protein to identify critical residues for antibody binding .

    • Orthogonal Techniques: Combine immunofluorescence with in situ hybridization or GFP-tagged At5g38396 constructs to confirm subcellular localization .

    • IP-MS Validation: Use immunoprecipitation followed by mass spectrometry (IP-MS) to identify co-purifying proteins and rule out cross-reactivity (e.g., TRIM28/AMPD2 in anti-GR studies ).

What strategies improve At5g38396 epitope characterization?

  • Methodological Answer:

    • Cryo-EM/Structural Analysis: Resolve antibody-antigen complexes to define binding interfaces (e.g., class 6 SARS-CoV-2 antibodies in ).

    • Affinity Maturation: Use phage display or yeast display libraries to engineer higher-affinity variants, enabling precise epitope discrimination .

    • Computational Modeling: Predict conformational epitopes using tools like AlphaFold2 or RosettaAntibody .

How to quantify At5g38396 expression dynamics under stress conditions?

  • Methodological Answer:

    • SPR-Based Quantification: Use surface plasmon resonance (SPR) with purified At5g38396 protein for kinetic measurements (association/dissociation rates) .

    • Competitive ELISA: Develop a standard curve with recombinant At5g38396 to quantify ng/mL-level changes in plant extracts .

    • Normalization: Pair with RNA-seq or RT-qPCR data to correlate protein abundance with transcriptional regulation .

Table 1: Validation Methods for At5g38396 Antibody

MethodKey MetricsLimitationsCitations
Peptide Blocking≥50% signal reductionDoes not confirm native conformation
Knockout ControlsComplete signal loss in null mutantsRequires genetic modification
IP-MSIdentifies co-purifying proteinsResource-intensive

Table 2: Structural Techniques for Epitope Analysis

TechniqueResolutionThroughputApplicability to At5g38396
Cryo-EM2–4 ÅLowLarge complexes (>150 kDa)
X-Ray Crystallography1.5–3 ÅMediumRequires stable crystals
HDX-MS5–10 ÅHighDynamic epitope mapping

Table 3: Troubleshooting Cross-Reactivity

IssueSolutionExample from Literature
Off-target bandsPre-adsorb with lysate from null mutantsAMPD2/TRIM28 in anti-GR studies
Non-linear signalOptimize antibody:antigen ratioDyAb-guided affinity maturation
Tissue variabilityValidate across developmental stagesABA-induced gene regulation in

Emerging Methodologies

  • Machine Learning-Guided Design: Tools like DyAb (Deep-learning-based Antibody design) predict affinity-enhancing mutations using sequence-variant datasets .

  • Single-Cell Western Blotting: Resolve At5g38396 expression heterogeneity in plant cell populations .

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