A Methodology for Comprehensive Analysis of Toll-Like Receptor Signaling in Macrophages

TLR7 mediates increased vulnerability to ischemic acute kidney injury in diabetes

OBJECTIVE

Diabetes is a risk factor for acute kidney injury (AKI). However, its mechanism of pathogenesis has not been elucidated. The aim of the study was to investigate the role of inflammation and the toll-like receptor 7 (TLR7) in ischemic AKI for diabetes.

METHODS

A high glucose hypoxia-reoxygenation model of human renal tubular epithelial (HK-2) cells was used to generate AKI induced by ischemia-reperfusion in diabetes. The activity of cells was measured by CCK-8 assay and LDH activity. Inflammatory cytokines were assessed by ELISA. TLR7, MyD88, and NF-κB expressions were examined by western blotting. Apoptosis was evaluated by flow cytometry.

RESULTS

The high glucose group and low glucose group were subjected to hypoxia-reoxygenation. The low glucose group developed only mild cell damage, apoptosis, and inflammatory response. In contrast, an equivalent hypoxia-reoxygenation injury provoked severe cell damage, apoptosis, and inflammatory response in the high glucose group. Expression of TLR7 and its related proteins were measured in the high glucose group before and after hypoxia-reoxygenation. The high glucose group exhibited more significant increases in TLR7 expression following hypoxia-reoxygenation than the low glucose group. In addition, the expression of TLR7 and its related proteins after hypoxia-reoxygenation were higher in the high glucose group than in the low glucose group. Inhibition of TLR7 provides significant protection against ischemic injury in diabetes.

CONCLUSION

Our results suggest that diabetes increases the vulnerability to ischemia-induced renal injury. This increased vulnerability originates from a heightened inflammatory response involving the TLR7 signal transduction pathway.

Multi-Omics Strategies Uncover Host-Pathogen Interactions

With the success of the Human Genome Project, large-scale systemic projects became a reality that enabled rapid development of the systems biology field. Systems biology approaches to host-pathogen interactions have been instrumental in the discovery of some specifics of Gram-negative bacterial recognition, host signal transduction, and immune tolerance. However, further research, particularly using multi-omics approaches, is essential to untangle the genetic, immunologic, (post)transcriptional, (post)translational, and metabolic mechanisms underlying progression from infection to clearance of microbes. The key to understanding host-pathogen interactions lies in acquiring, analyzing, and modeling multimodal data obtained through integrative multi-omics experiments. In this article, we will discuss how multi-omics analyses are adding to our understanding of the molecular basis of host-pathogen interactions and systemic maladaptive immune response of the host to microbes and microbial products.