Cationic liposomes induce cytotoxicity in HepG2 via regulation of lipid metabolism based on whole-transcriptome sequencing analysis

Abstract

Backgroud: Cationic liposomes (CLs) can be used as non-viral vectors in gene transfer and drug delivery. However, the underlying molecular mechanism of its cytotoxicity has not been well elucidated yet.

Methods: We herein report a systems biology approach based on whole-transcriptome sequencing coupled with computational method to identify the predominant genes and pathways involved in the cytotoxicity of CLs in HepG2 cell line.

Results: Firstly, we validated the concentration-dependent cytotoxicity of CLs with an IC₅₀ of 120 μg/ml in HepG2 exposed for 24 h. Subsequently, we used whole-transcriptome sequencing to identify 220 (77 up- and 143 down-regulated) differentially expressed genes (DEGs). Gene ontology (GO) and pathway analysis showed that these DEGs were mainly related to cholesterol, steroid, lipid biosynthetic and metabolic processes. Additionally, "key regulatory" genes were identified using gene act, pathway act and co-expression network analysis, and expression levels of 11 interested altered genes were confirmed by quantitative real time PCR. Interestingly, no cell cycle arrest was observed through flow cytometry.

Conclusions: These data are expected to provide deep insights into the molecular mechanism of CLs cytotoxicity.

Keywords: Cationic liposomes; Cytotoxicity; Lipid metabolism; Nanoparticle; RNA-seq.

Fig. 1

HepG2 cytotoxicity of CLs at a series of concentrations (exposure for 24 h)

Fig. 2

a Expression profile heat map of DEGs in HepG2 cells following exposure to CLs. A total of 77 up-regulated and 143 down-regulated genes are shown. b GO analysis of DEGs. c GO tree analysis of enriched GO terms. Red circles represent up-regulated genes; Green circles represent down-regulated genes; Yellow circles represent ambiguous-regulated genes

Fig. 3

a Pathway analysis of DEGs. Red represents the significant pathway. b Pathway act network. c Gene act network

Fig. 4

Co-expression network of DEGs in the control (a) and CLs-treated (b) groups. Solid lines represent positive correlation, and dashed lines represent negatively correlation. The size and color of the nodes correspond to their co-expression ability. The greater the size of the node, the greater the number of its direct neighbors

Fig. 5

a, b qRT-PCR verification of selected DEGs including 8 down-regulated and 3 up-regulated genes. The relative expression levels of these genes were normalized to GAPDH. c HepG2 cell cycle analysis was performed by flow cytometry. The percent of cells in each phase of the cell cycle was shown

Fig. 6

The schematic diagram of this study. The procedure included three steps. Firstly, the cytotoxicity of cationic liposomes (CLs) was detected in HepG2 cell and DEGs in the CLs group comparing with control were identified through next generation RNA-seq technology. Then, functional analysis and bioinformatics computing were employed to explore the key genes and pathways. Finally, expression levels of these genes were confirmed by qPCR, and the cell cycle was assessed by flow cytometry