AUTHOR=Kánová Evelína , Jiménez-Munguía Irene , Majerová Petra , Tkáčová Zuzana , Bhide Katarína , Mertinková Patrícia , Pulzová Lucia , Kováč Andrej , Bhide Mangesh
TITLE=Deciphering the Interactome of Neisseria meningitidis With Human Brain Microvascular Endothelial Cells
JOURNAL=Frontiers in Microbiology
VOLUME=9
YEAR=2018
URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2018.02294
DOI=10.3389/fmicb.2018.02294
ISSN=1664-302X
ABSTRACT=
Neisseria meningitidis is able to translocate the blood-brain barrier and cause meningitis. Bacterial translocation is a crucial step in the onset of neuroinvasion that involves interactions between pathogen surface proteins and host cells receptors. In this study, we applied a systematic workflow to recover and identify proteins of N. meningitidis that may interact with human brain microvascular endothelial cells (hBMECs). Biotinylated proteome of N. meningitidis was incubated with hBMECs, interacting proteins were recovered by affinity purification and identified by SWATH-MS. Interactome of N. meningitidis comprised of 41 potentially surface exposed proteins. These were assigned into groups based on their probability to interact with hBMECs: high priority candidates (21 outer membrane proteins), medium priority candidates (14 inner membrane proteins) and low priority candidates (six secretory proteins). Ontology analysis provided information for 17 out of 41 surface proteins. Based on the series of bioinformatic analyses and literature review, five surface proteins (adhesin MafA1, major outer membrane protein P.IB, putative adhesin/invasion, putative lipoprotein and membrane lipoprotein) were selected and their recombinant forms were produced for experimental validation of interaction with hBMECs by ELISA and immunocytochemistry. All candidates showed interaction with hBMECs. In this study, we present a high-throughput approach to generate a dataset of plausible meningococcal ligands followed by systematic bioinformatic pipeline to categorize the proteins for experimental validation.