Anti phospho mlkl

Cellular extracts of 1x10⁶ cells or 0.5 g of tissue were homogenized in RIPA lysis buffer (1% Triton X-100, 2% SDS, 150 mM NaCl, 10 mM HEPES, 2 mM EDTA) containing protease and phosphatase inhibitor cocktail (Roche, pH 8.0). After centrifugation at 13 000 × g for 5 min, cell lysates were prepared under reducing and denaturing conditions and subjected to SDS−PAGE. Equal concentrations of proteins were fractionated by electrophoresis on 10% acrylamide gels. The proteins were transferred onto a nitrocellulose membrane (Millipore, Billerica, MA, USA), followed by blocking of nonspecific binding sites in 5% nonfat milk in TBST (50 mM Tris-HCl - pH 7.4, 150 mM NaCl, 0.05% Tween 20) for 1 h at room temperature and blotted with primary antibodies in TBST overnight at 4°C. The following antibodies were used: anti-phospho-RIPK1 (Ser166) (Cell Signaling # 31122S), anti-RIPK3 (D8J3 L) (Cell Signaling # 15828S), anti-MLKL (D2I6N) (Cell Signaling #14993S), anti-phospho-MLKL (Cell Signaling #91689S) and anti-β-actin (Sigma, #A1978). Proteins of interest were identified by incubating the membrane with IRDye^® LICOR secondary antibodies in TBST, followed by fluorescence imaging detection using the Odyssey^® system (CLx Imaging System). Protein bands were quantified by densitometric image analysis using ImageJ software. All the data were normalized by β-actin expression quantification.

For immunostaining and epi-fluorescent microscopy, cells after ait, helium NTPs or ozone exp were fixed with 2% formaldehyde and permeabilized with 0.2% Triton X-100. Subsequently, cells were stained either with rabbit polyclonal anti-phospho-MLKL (polyclonal, clone D6H3V, Cell Signaling Technologies), or rabbit polyclonal LC3A/B antibody (polyclonal, Cell Signaling Technologies), with subsequent labelling using secondary Alexa Fluor-568 antibodies (Invitrogen). Nuclei were counterstained with Hoechst 33342. Samples were covered with mounting medium (Dako) and analyzed by epi-fluorescent microscopy (Eclipse Ni-E, Nikon, Japan). ImageJ software was used for image processing and quantification.