Work

Comprehensive analyses of transcriptomes induced by Lyme spirochete infection to CNS model system

Year: 2022

Type: article

Abstract: BACKGROUND: Lyme disease is a zoonotic disease caused by infection with Borrelia burgdorferi (Bb), the involvement of the nervous system in Lyme disease is usually referred to as Lyme neuroborreliosis (LNB). LNB has diverse clinical manifestations, most commonly including meningitis, Bell's palsy, and encephalitis. However, the molecular pathogenesis of neuroborreliosis is still poorly understood. Comprehensive transcriptomic analysis following Bb infection could provide new insights into the pathogenesis of LNB and may identify novel biomarkers or therapeutic targets for LNB diagnosis and treatment. METHODS: In the present study, we pooled transcriptomic dataset of Macaca mulatta (rhesus) from our laboratory and the human astrocyte dataset GSE85143 from the Gene Expression Omnibus database to screen common differentially expressed genes (DEGs) in the Bb infection group and the control group. Functional and enrichment analyses were applied for the DEGs. Protein-Protein Interaction network, and hub genes were identified using the Search Tool for the Retrieval of Interaction Genes database and the CytoHubba plugin. Finally, mRNA expression of hub genes was validated in vitro and ex vivo from Bb infected models and normal controls by quantitative reverse transcription PCR (qRT-PCR). RESULTS: A total of 80 upregulated DEGs and 32 downregulated DEGs were identified. Among them, 11 hub genes were selected. The pathway enrichment analyses on 11 hub genes revealed that the PI3K-Akt signaling pathway was significantly enriched. The mRNA levels of ANGPT1, TLR6, SREBF1, LDLR, TNC, and ITGA2 in U251 cells and/or rhesus brain explants by exposure to Bb were validated by qRT-PCR. CONCLUSION: Our study suggested that TLR6, ANGPT1, LDLR, SREBF1, TNC, and ITGA may be candidate mammal biomarkers for LNB, and the TLR6/PI3K-Akt signaling pathway may play an important role in LNB pathogenesis.

Source: Infection Genetics and Evolution

DOI: 10.1016/j.meegid.2022.105349