The ACT11 antibody (mAb2345a) is validated using:
Western Blot (WB): Detects a single band at ~45 kDa in Arabidopsis lysates, aligning with ACT11's molecular weight .
Immunofluorescence (IF): Localizes to cytoskeletal structures in plant tissues, consistent with actin's role .
Cross-reactivity testing: No reactivity observed with non-plant actins (e.g., mammalian or fungal) .
Assay | Target Reactivity | Non-target Reactivity | Citation |
---|---|---|---|
Western Blot | ACT11 (45 kDa band) | None detected | |
Immunofluorescence | Cytoskeletal staining | No off-target binding |
Negative controls: Use tissue/cell lysates from ACT11-knockout mutants.
Isotype controls: Mouse IgG1 to rule out nonspecific binding .
Competition assays: Pre-incubate antibody with purified ACT11 antigen to confirm signal loss .
The antibody recognizes epitopes in Thr43 (plant actin) and Thr41 (Dictyostelium), enabling subclass-specific detection:
Vegetative actins: Binds subclasses 2 and 3 via conformational epitopes .
Pollen actins: Targets subclasses 4 and 5 due to post-translational modifications (e.g., phosphorylation) .
Epitope mapping: Compare ACT11 sequences to identify conserved regions (e.g., Thr43) .
Peptide blocking: Synthesize Thr43-containing peptides to test cross-reactivity .
Structural analysis: Use cryo-EM or X-ray crystallography to assess antibody-antigen binding dynamics .
Signal amplification: Pair with tyramide-based systems in IF .
Pre-clearing lysates: Remove nonspecific proteins via protein G beads .
Multiplex assays: Combine with antibodies against co-expressed markers (e.g., tubulin) for dual staining .
Issue | Solution | Citation |
---|---|---|
Weak WB signal | Optimize SDS-PAGE conditions (e.g., 12% gel) | |
Background in IF | Increase blocking time (e.g., 2% BSA for 2 hrs) |
Enzymatic deglycosylation: Treat lysates with PNGase F to assess glycan dependency .
LC-MS/MS: Compare glycopeptide profiles under stress vs. control conditions .
Functional assays: Corrogate actin polymerization rates with antibody binding efficiency .
Molecular docking: Use tools like Rosetta or HADDOCK to model Thr43 interactions .
Machine learning: Train models on plant actin epitope databases to predict cross-species reactivity .