An integrative multi-omics approach uncovers the regulatory role of CDK7 and CDK4 in autophagy activation induced by silica nanoparticles

Dysfunction of macroautophagy/autophagy has been postulated as a major cellular toxicological response to nanomaterials. It has been reported that excessive autophagy activation, induced by silica nanoparticles (SiNPs), contributes to autophagy dysfunction, whereas little is known how SiNPs trigger autophagy activation. Here, we treated normal rat kidney (NRK) cells using 3 different sizes of SiNPs (16, 29, and 51 nm) and observed that 16-nm SiNPs, with a final concentration of 60 μg/mL, dramatically induce autophagy activation without reducing cell viability. We further conducted a transcriptomic, proteomic, and phosphoproteomic profiling, and detected 23 autophagy-related (Atg) genes and 35 autophagy regulators regulated on at least one omic layer. To identify key regulators from the multi-omics data, we developed a new algorithm of computational prediction of master autophagy-regulating kinases (cMAK) to detect 21 candidates and revealed the CDK7-CDK4 cascade to be functional. The silence or inhibition of Cdk7 or Cdk4 significantly attenuated autophagic activation but not influenced autophagic flux blockage induced by 16-nm SiNPs. Further computational modeling indicated that the CDK7-CDK4 signaling axis potentially triggers autophagy activation by phosphorylating RB1 (RB transcriptional corepressor 1), activating two critical transcription factors, E2F1 (E2F transcription factor 1) and FOXO3 (forkhead box O3), and enhancing the transcriptional levels of at least 8 Atg genes and autophagy regulators in response to SiNPs. Our studies not only established a powerful method for predicting regulatory kinases from the multi-omics data but also revealed a potential mechanism of SiNP-triggered autophagy activation through modulating the CDK7-CDK4 cascade.Abbreviations: 3-MA: 3-methyladenine; Atg: autophagy-related; BECN1: beclin 1; CCK-8: cell counting kit-8; CDK4: cyclin dependent kinase 4; CDK7: cyclin dependent kinase 7; cMAK: computational prediction of master autophagy-regulating kinases; CQ: chloroquine; DMEM: Dulbecco's modified Eagle's medium; DMSO: dimethyl sulfoxide; E-ratio: enrichment ratio; E2F1: E2F transcription factor 1; EBSS: Earle's balanced salt solution; ER: endoplasmic reticulum; FOXO3: forkhead box O3; FPKM: fragments per kilobase of exon per million fragments mapped; GO: gene ontology; H2O2: hydrogen peroxide; iGPS: in vivo GPS; KEGG: Kyoto Encyclopedia of Genes and Genomes; LC-MS/MS: liquid chromatography–tandem mass spectrometry; LDH: lactate dehydrogenase; MAP1LC3B/LC3: microtubule associated protein 1 light chain 3 beta; NRK: normal rat kidney; p-site: phosphorylation site; PBS: phosphate-buffered saline; PDI: polydispersity index; PTM: post-translational modification; QKS: quantitative kinase state; RB1: RB transcriptional corepressor 1; RBHs: reciprocal best hits; RNA-Seq: RNA sequencing; ROS: reactive oxygen species; rSiNPs: SiNPs fluorescently labeled with rhodamine B; SEM: scanning electronic microscopy; SiNPs: silica nanoparticles; siRNA: small interfering RNA; SQSTM1/p62: sequestosome 1; ssKSR: site-specific kinase-substrate relation; TEM: transmission electron microscopy; tfLC3: mRFP-GFP tandem fluorescent-tagged LC3.