New insights into meningitic Escherichia coli infection of brain microvascular endothelial cells from quantitative proteomics analysis

  • J Neuroinflammation. 2018 Oct 19;15(1):291. doi: 10.1186/s12974-018-1325-z.
Wen-Tong Liu  1 Yu-Jin Lv  1  2 Rui-Cheng Yang  1 Ji-Yang Fu  1 Lu Liu  1 Huan Wang  1 Qi Cao  1 Chen Tan  1  3 Huan-Chun Chen  1  3 Xiang-Ru Wang  4  5
Affiliations
  • 1. The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
  • 2. College of Veterinary Medicine, Henan University of Animal Husbandry and Economy, Zhengzhou, 450046, Henan, China.
  • 3. State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
  • 4. The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan, 430070, Hubei, China. [email protected].
  • 5. State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, Hubei, China. [email protected].
Abstract

Background: Bacterial meningitis remains a big threat to the integrity of the central nervous system (CNS), despite the advancements in antimicrobial reagents. Escherichia coli is a Bacterial pathogen that can disrupt the CNS function, especially in neonates. E. coli meningitis occurs after bacteria invade the brain microvascular endothelial cells (BMECs) that form a direct and essential barrier restricting the entry of circulating microbes and toxins to the brain. Previous studies have reported on several cellular proteins that function during meningitic E. coli infections; however, more comprehensive investigations to elucidate the potential targets involved in E. coli meningitis are essential to better understand this disease and discover new treatments for it.

Methods: The isobaric tags for relative and absolute quantification (iTRAQ) approach coupled with LC-MS/MS were applied to compare and characterize the different proteomic profiles of BMECs in response to meningitic or non-meningitic E. coli strains. KEGG and gene ontology annotations, ingenuity pathways analysis, and functional experiments were combined to identify the key host molecules involved in the meningitic E. coli-induced tight junction breakdown and neuroinflammatory responses.

Results: A total of 13 cellular proteins were found to be differentially expressed by meningitic E. coli strains PCN033 and RS218, including one that was also affected by HB101, a non-meningitic E. coli strain. Through bioinformatics analysis, we identified the macrophage migration inhibitory factor (MIF), granzyme A, NF-κB signaling, and mitogen-activated protein kinase (MAPK) pathways as being biologically involved in the meningitic E. coli-induced tight junction breakdown and neuroinflammation. Functionally, we showed that MIF facilitated meningitic E. coli-induced production of cytokines and chemokines and also helped to disrupt the blood-brain barrier by decreasing the expression of tight junction proteins like ZO-1, occludin. Moreover, we demonstrated the significant activation of NF-κB and MAPK signaling in BMECs in response to meningitic E. coli strains, which dominantly determined the generation of the proinflammatory cytokines including IL-6, IL-8, TNF-α, and IL-1β.

Conclusions: Our work identified 12 host cellular targets that are affected by meningitic E. coli strains and revealed MIF to be an important contributor to meningitic E. coli-induced cytokine production and tight junction disruption, and also the NF-κB and MAPK signaling pathways that are mainly involved in the infection-induced cytokines production. Characterization of these distinct proteins and pathways in BMECs will facilitate further elucidation of meningitis-causing mechanisms in humans and Animals, thereby enabling the development of novel preventative and therapeutic strategies against Infection with meningitic E. coli.

Keywords
BMECs; Blood-brain barrier; Meningitic E. coli; Proteomics; iTRAQ.
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