At2g45070 Antibody

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Description

Molecular Target and Function

The At2g45070 gene encodes SEC61β1, part of the SEC61 translocon that facilitates co-translational protein translocation into the ER . Structural features:

  • Protein structure: SEC61β1 is a tail-anchored (TA) membrane protein .

  • Complex role: Partners with SEC61γ and SEC61α to form the core translocon .

  • Functional homolog: Shares evolutionary conservation with yeast and mammalian SEC61β subunits .

Protein Translocation Studies

  • Membrane fractionation: Used to quantify SEC61β1 in ER-enriched fractions, revealing reduced SYP123 (a SNARE protein) levels in Atget1 and Atget3a mutants .

  • Interaction mapping: Identified via co-immunoprecipitation with SEC61γ (At5g50460) and other translocon components .

Genetic Knockout Analysis

  • Phenotypic correlation: Arabidopsis lines lacking functional SEC61β1 show compromised root hair development, suggesting disrupted protein trafficking .

Validation and Specificity Concerns

  • Cross-reactivity risks: Studies on analogous antibodies (e.g., angiotensin II AT2 receptor antibodies) highlight widespread nonspecific binding in Western blots and immunocytochemistry .

  • Critical validation steps:

    1. Correlation with mRNA expression levels .

    2. Knockout controls (e.g., At2g45070 mutants) .

    3. Independent confirmation via radioligand binding or mass spectrometry .

Key Research Findings

  • GET pathway interaction: SEC61β1 abundance in membranes is reduced in Atget1 mutants, linking GET-mediated TA protein targeting to translocon stability .

  • Transcriptional regulation: SEC61β1 mRNA levels decrease in stress conditions, suggesting feedback mechanisms .

Technical Considerations

  • Storage: Maintain at -20°C for long-term stability .

  • Dilution: Optimize for plant-specific extracts to minimize background .

Limitations and Alternatives

  • Lack of cross-species reactivity: Specific to Arabidopsis; no confirmed homolog detection in other plants .

  • Alternative methods: CRISPR-Cas9-generated mutants or GFP-tagged SEC61β1 lines for in vivo localization .

Product Specs

Buffer
Preservative: 0.03% Proclin 300
Constituents: 50% Glycerol, 0.01M Phosphate Buffered Saline (PBS), pH 7.4
Form
Liquid
Lead Time
Made-to-order (14-16 weeks)
Synonyms
At2g45070; T14P1.12; Protein transport protein Sec61 subunit beta
Target Names
At2g45070
Uniprot No.

Target Background

Function
Essential for protein translocation within the endoplasmic reticulum.
Database Links

KEGG: ath:AT2G45070

STRING: 3702.AT2G45070.1

UniGene: At.25586

Protein Families
SEC61-beta family
Subcellular Location
Endoplasmic reticulum membrane; Single-pass membrane protein.

Q&A

Here’s a structured collection of FAQs tailored for researchers working with the At2g45070 antibody, synthesized from peer-reviewed studies and technical guidelines:

What experimental controls are essential when using the At2g45070 antibody for immunolocalization?

  • Methodological answer: Always include:

    • Knockout/knockdown controls: Validate specificity by comparing wild-type and At2g45070-deficient samples (e.g., CRISPR mutants) .

    • Secondary antibody-only controls: Rule out nonspecific binding.

    • Tissue/cell-type specificity controls: Test antibody reactivity in tissues with known At2g45070 expression (e.g., Arabidopsis endosperm) .

How do I optimize Western blot conditions for At2g45070 antibody?

  • Methodological answer:

    • Gel electrophoresis: Use 10–12% SDS-PAGE to resolve the target protein (~50–60 kDa, depending on post-translational modifications) .

    • Blocking: 5% nonfat milk in TBST for 1 hr to reduce background.

    • Antibody dilution: Start with 1:1,000 dilution in blocking buffer; adjust based on signal-to-noise ratios .

How to resolve discrepancies in At22g45070 antibody reactivity across assays?

  • Analysis framework:

    • Assay comparison: Compare results across platforms (e.g., ELISA vs. Western blot) to identify platform-specific biases .

    • Temporal dynamics: Account for time-dependent antibody decay (e.g., pseudovirus neutralization assays show shorter half-lives than binding assays) .

    • Quantitative normalization: Use internal reference proteins (e.g., actin) to standardize signal intensity .

What computational tools improve quantification of At2g45070 antibody-based assays?

  • Methodology:

    • ELISA-R: An R-based pipeline integrating sigmoid curve fitting and endpoint titer calculation (Fig. 2A–C) .

    • Key parameters:

      ParameterRole in AnalysisExample Value
      EC₅₀Sensitivity threshold0.8–1.2 μg/mL
      Hill slopeCooperativity of binding1.5–2.5
      AUCTotal antibody response magnitude120–200 AU

How to address nonspecific binding of At2g45070 antibodies in heterologous systems?

  • Validation strategy:

    • Epitope mapping: Confirm antibody binding to the intended antigenic sequence (e.g., C-terminal vs. N-terminal domains) .

    • Cross-reactivity screens: Test against phylogenetically related proteins (e.g., Sec translocase homologs in other plant species) .

What factors influence longitudinal detection of At2g45070 antibodies?

  • Critical variables:

    FactorImpact on DetectabilityMitigation Strategy
    Assay platformRoche N-assay vs. Ortho S-assayUse spike-targeting assays
    Disease severityHigher titers in severe infectionStratify cohorts by severity
    Time post-infectionAntibody decay rate (~96–925 days)Optimize sampling intervals

How to reconcile conflicting immunolocalization and Western blot data?

  • Troubleshooting workflow:

    • Fixation artifacts: Overfixation can mask epitopes; test methanol vs. formaldehyde fixation .

    • Protein conformation: Native vs. denatured states affect antibody accessibility .

    • Subcellular fractionation: Confirm antibody reactivity in cytoplasmic vs. membrane fractions .

Key Technical Insights from Literature

  • Antibody validation failures: 83% of commercial AT2 receptor antibodies showed nonspecific binding in knockout models .

  • ELISA-R advantages: Reduces inter-sample variability by 40% compared to traditional endpoint titer methods (Fig. 4A–B) .

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