Proteomic and bioinformatic pipeline to screen the ligands of S. pneumoniae interacting with human brain microvascular endothelial cells.

The mechanisms by which Streptococcus pneumoniae penetrates the blood-brain barrier (BBB), reach the CNS and causes meningitis are not fully understood. Adhesion of bacterial cells on the brain microvascular endothelial cells (BMECs), mediated through protein-protein interactions, is one of the crucial steps in translocation of bacteria across BBB. In this work, we proposed a systematic workflow for identification of cell wall associated ligands of pneumococcus that might adhere to the human BMECs. The proteome of S. pneumoniae was biotinylated and incubated with BMECs. Interacting proteins were recovered by affinity purification and identified by data independent acquisition (DIA). A total of 44 proteins were identified from which 22 were found to be surface-exposed. Based on the subcellular location, ontology, protein interactive analysis and literature review, five ligands (adhesion lipoprotein, endo-β-N-acetylglucosaminidase, PhtA and two hypothetical proteins, Spr0777 and Spr1730) were selected to validate experimentally (ELISA and immunocytochemistry) the ligand-BMECs interaction. In this study, we proposed a high-throughput approach to generate a dataset of plausible bacterial ligands followed by systematic bioinformatics pipeline to categorize the protein candidates for experimental validation. The approach proposed here could contribute in the fast and reliable screening of ligands that interact with host cells.