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Updated: Sep 26, 2025

Low Molecular Weight Protein Enrichment on Mesoporous Silica Thin Films for Biomarker Discovery
Published on: April 17, 2012
Integrative proteomics and metabolomics approach to elucidate metabolic dysfunction induced by silica nanoparticles
Ye Zhu1, Yukang Zhang1, Yanbo Li1
1aDepartment of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing 100069, PR China; bBeijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing 100069, PR China.
Abstract:
Silica nanoparticles (SiNPs) are derived from manufactured materials and the natural environment, and they cause detrimental effects on human health via various exposure routes. The liver is proven to be a key target organ for SiNP toxicity; however, the mechanisms causing toxicity remain largely uncertain. Here, we investigated the effects of SiNPs on the metabolic spectrum in hepatocytes via integrative analyses of proteomics and metabolomics. First, a proteomic analysis was used to screen for critical proteins (including RPL3, HSP90AA1, SOD, PGK1, GOT1, and PNP), indicating that abnormal protein synthesis, protein misfolding, oxidative stress, and metabolic dysfunction may contribute to SiNP-induced hepatotoxicity. Next, metabolomic data demonstrated that SiNPs caused metabolic dysfunction by altering vital metabolites (including glucose, alanine, GSH, CTP, and ATP). Finally, a systematic bioinformatic analysis of protein-metabolite interactions showed that SiNPs disturbed glucose metabolism (glycolysis and pentose phosphate pathways, amino acid metabolism (alanine, aspartate, and glutamate), and ribonucleotide metabolism (purine and pyrimidine). These metabolic dysfunctions could exacerbate oxidative stress and lead to liver injury. Moreover, SOD, TKT, PGM1, GOT1, PNP, and NME2 may be key proteins for SiNP-induced hepatotoxicity. This study revealed the metabolic mechanisms underlying SiNP-induced hepatotoxicity and illustrated that integrative omics analyses can be a powerful approach for toxicity evaluations and risk assessments of nanoparticles.

