Abstract
Sepsis is a systemic immune response responsible for considerable morbidity and mortality. Molecular modeling of host-pathogen interactions in the disease state represents a promising strategy to define molecular events of importance for the transition from superficial to invasive infectious diseases. Here we used the Gram-positive bacterium Streptococcus pyogenes as a model system to establish a mass spectrometry based workflow for the construction of a stoichiometric surface density model between the S. pyogenes surface, the surface virulence factor M-protein, and adhered human blood plasma proteins. The workflow relies on stable isotope labeled reference peptides and selected reaction monitoring mass spectrometry analysis of a wild-type strain and an M-protein deficient mutant strain, to generate absolutely quantified protein stoichiometry ratios between S. pyogenes and interacting plasma proteins. The stoichiometry ratios in combination with a novel targeted mass spectrometry method to measure cell numbers enabled the construction of a stoichiometric surface density model using protein structures available from the protein data bank. The model outlines the topology and density of the host-pathogen protein interaction network on the S. pyogenes bacterial surface, revealing a dense and highly organized protein interaction network. Removal of the M-protein from S. pyogenes introduces a drastic change in the network topology, validated by electron microscopy. We propose that the stoichiometric surface density model of S. pyogenes in human blood plasma represents a scalable framework that can continuously be refined with the emergence of new results. Future integration of new results will improve the understanding of protein-protein interactions and their importance for bacterial virulence. Furthermore, we anticipate that the general properties of the developed workflow will facilitate the production of stoichiometric surface density models for other types of host-pathogen interactions.
Highlights
From the ‡Department of Immunotechnology, Faculty of Engineering, Lund University, Sweden; §Division of Infection Medicine, Department of Clinical Sciences, Lund University, Sweden; ¶S3IT, University of Zurich, Zurich, Switzerland
Determining Bacterial Concentration Using Mass spectrometry (MS)—The construction a stoichiometric surface density model of a hostpathogen interaction network in an ex vivo host environment, relies on reproducible protein quantification methods associated with high recovery
We present a novel strategy for constructing a stoichiometric surface density model of a pathogen in a relevant host location by using stable isotope labeled peptides and selected reaction monitoring (SRM) in combination with electron microscopy and advanced modeling
Summary
IgG, immunoglobulin gamma; LC, liquid chromatography; SRM, selected reaction monitoring; CFU, colony forming units; MS, Mass spectrometry. The stoichiometric relationship in combination with a new technical improvement for counting the number of bacteria using SRM enabled the construction of the first model of S. pyogenes surface interaction network in a host environment. This model includes the stoichiometric relations between host proteins, surface proteins, and the surface of the pathogen and it visualizes the density of this plethora of interactions in a stoichiometric surface density model
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