Silica-coated magnetic-nanoparticle-induced cytotoxicity is reduced in microglia by glutathione and citrate identified using integrated omics

Abstract

Background Nanoparticles have been utilized in brain research and therapeutics, including imaging, diagnosis, and drug delivery, owing to their versatile properties compared to bulk materials. However, exposure to nanoparticles leads to their accumulation in the brain, but drug development to counteract this nanotoxicity remains challenging. To date, concerns have risen about the potential toxicity to the brain associated with nanoparticles exposure via penetration of the brain blood barrier to address this issue. Methods Here the effect of silica-coated-magnetic nanoparticles containing the rhodamine B isothiocyanate dye [MNPs@SiO2(RITC)] were assessed on microglia through toxicological investigation, including biological analysis and integration of transcriptomics, proteomics, and metabolomics. MNPs@SiO2(RITC)-induced biological changes, such as morphology, generation of reactive oxygen species, intracellular accumulation of MNPs@SiO2(RITC) using transmission electron microscopy, and glucose uptake efficiency, were analyzed in BV2 murine microglial cells. Each omics data was collected via RNA-sequencing-based transcriptome analysis, liquid chromatography-tandem mass spectrometry-based proteome analysis, and gas chromatography- tandem mass spectrometry-based metabolome analysis. The three omics datasets were integrated and generated as a single network using a machine learning algorithm. Nineteen compounds were screened and predicted their effects on nanotoxicity within the triple-omics network. Results Intracellular reactive oxygen species production, an inflammatory response, and morphological activation of cells were greater, but glucose uptake was lower in MNPs@SiO2(RITC)-treated BV2 microglia and primary rat microglia in a dose-dependent manner. Expression of 121 genes (from 41,214 identified genes), and levels of 45 proteins (from 5918 identified proteins) and 17 metabolites (from 47 identified metabolites) related to the above phenomena changed in MNPs@SiO2(RITC)-treated microglia. A combination of glutathione and citrate attenuated nanotoxicity induced by MNPs@SiO2(RITC) and ten other nanoparticles in vitro and in the murine brain, protecting mostly the hippocampus and thalamus. Conclusions Combination of glutathione and citrate can be one of the candidates for nanotoxicity alleviating drug against MNPs@SiO2(RITC) induced detrimental effect, including elevation of intracellular reactive oxygen species level, activation of microglia, and reduction in glucose uptake efficiency. In addition, our findings indicate that an integrated triple omics approach provides useful and sensitive toxicological assessment for nanoparticles and screening of drug for nanotoxicity. Graphical Abstract

The Impact of Fine Particulate Matter 2.5 on the Cardiovascular System: A Review of the Invisible Killer

“…Recently, it has been suggested that glutathione and citrate attenuate cytotoxicity induced by urban PM in microglia [ 198 ]. The combination of glutathione and citrate reduces the toxicity of PM exposed to cells through mechanisms such as ROS scavenging, organic acid supplementation in the tricarboxylic acid cycle, and chelating Ca 2+ ions.…”

Cerebrospinal Fluid Metabolome in Parkinson’s Disease and Multiple System Atrophy

“…To compensate for the weakness of metabolomics, integration of omics technologies is highly recommended, but the development of this strategy is challenging [102]. Integrated omics studies have identified novel biological changes underlying various conditions in vitro [18,85,[103][104][105][106][107]. There have been limitations in the analysis of other omics data, except for metabolites, from CSF samples due to technical issues.…”

“…Machine learning is used for handling large-scale datasets, including integrated omics data [105]. Machine learning is divided into supervised learning, unsupervised learning, and reinforcement learning [55,110].…”

“…Large-scale multi-omics datasets can be reduced in dimension by performing PCA and organized through a clustering algorithm for unsupervised learning. The application of machine learning algorithms will help reduce biases in the analysis and trimming of integrated omics data, including metabolomic, proteomic, and microRNA data from the CSF of PD and MSA patients [105].…”

Reduction in the Migration Activity of Microglia Treated with Silica-Coated Magnetic Nanoparticles and their Recovery Using Citrate

“…For example, integration of transcriptomics and metabolomics, namely metabotranscriptomics, demonstrated novel cellular responses and in-depth toxicological intracellular pathways associated with NPs of MNPs@SiO 2 (RITC) [ 29 , 30 , 31 , 32 , 33 , 34 ]. In addition, artificial intelligence (AI) approaches, such as machine learning, have been applied to classify the integration of omics data and predict nanotoxicity, which are massive and heterogeneous for generating a single network with integrated transcriptomics, proteomics, and metabolomics [ 35 , 36 ].…”