Here’s a structured collection of FAQs tailored for academic researchers working with MPST-4 antibodies, integrating technical depth, methodological guidance, and evidence-based insights:
MPST-4 antibody (IgG1 κ mouse monoclonal) is optimized for:
Western blot (WB): Detects MPST (~33 kDa) in mouse, rat, and human lysates under denaturing conditions .
Immunohistochemistry (IHC): Requires antigen retrieval for formalin-fixed, paraffin-embedded tissues .
Immunofluorescence (IF): Suitable for detecting cytoplasmic MPST in frozen sections .
ELISA: Use non-conjugated forms for direct antigen quantification .
For WB, reduce sample processing variability by using fresh lysates with protease inhibitors and validating with MPST-knockout controls .
For IHC, optimize blocking conditions (e.g., 5% BSA in PBS) to minimize background .
Follow a three-step validation framework:
Genetic controls: Compare wild-type vs. MPST-knockout cell lines or tissues .
Orthogonal validation: Use siRNA-mediated MPST knockdown alongside antibody staining .
Cross-reactivity profiling: Test against related sulfurtransferases (e.g., TST) to rule off-target binding .
| Validation Method | Expected Outcome | Citation |
|---|---|---|
| WB (MPST-KO lysate) | No band at ~33 kDa | |
| IHC (human liver) | Cytoplasmic staining |
Case Study:
In a study of MPST’s role in cysteine metabolism, inconsistent WB results were traced to variable β-mercaptoethanol concentrations during sample prep. Standardizing reducing conditions resolved the issue .
Fixation: Use 4% PFA for 15 min to preserve MPST epitopes while retaining small-molecule probe integrity .
Sequential staining:
Imaging: Use spectral unmixing to separate signals (e.g., Cy3 vs. Alexa Fluor 647 channels) .
Critical Consideration:
Validate probe-antibody compatibility via control experiments omitting either component .
Adopt finite mixture models to distinguish antibody-positive/negative populations in heterogeneous samples:
Model: Skew-Normal distributions to account for asymmetric signal intensities .
Validation: Compare AIC/BIC values across 2-4 component models .