用于构建化学计量宿主-病原体表面密度模型的靶向蛋白质组学与绝对蛋白质定量

Targeted Proteomics and Absolute Protein Quantification for the Construction of a Stoichiometric Host-Pathogen Surface Density Model.

作者信息

Sjöholm Kristoffer, Kilsgård Ola, Teleman Johan, Happonen Lotta, Malmström Lars, Malmström Johan

机构信息

From the ‡Department of Immunotechnology, Faculty of Engineering, Lund University, Sweden.

§Division of Infection Medicine, Department of Clinical Sciences, Lund University, Sweden.

出版信息

Mol Cell Proteomics. 2017 Apr;16(4 suppl 1):S29-S41. doi: 10.1074/mcp.M116.063966. Epub 2017 Feb 9.

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 as a model system to establish a mass spectrometry based workflow for the construction of a stoichiometric surface density model between the 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 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 bacterial surface, revealing a dense and highly organized protein interaction network. Removal of the M-protein from introduces a drastic change in the network topology, validated by electron microscopy. We propose that the stoichiometric surface density model of 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.

摘要

脓毒症是一种导致相当高发病率和死亡率的全身性免疫反应。疾病状态下宿主与病原体相互作用的分子建模是一种很有前景的策略,可用于确定从浅表性传染病向侵袭性传染病转变过程中重要的分子事件。在此,我们以革兰氏阳性菌为模型系统,建立了一种基于质谱的工作流程,用于构建细菌表面、表面毒力因子M蛋白与黏附的人血浆蛋白之间的化学计量表面密度模型。该工作流程依赖于稳定同位素标记的参考肽以及对野生型菌株和M蛋白缺陷突变菌株进行选择反应监测质谱分析,以生成细菌与相互作用血浆蛋白之间的绝对定量蛋白质化学计量比。化学计量比与一种用于测量细胞数量的新型靶向质谱方法相结合,使得能够利用蛋白质数据库中可得的蛋白质结构构建化学计量表面密度模型。该模型勾勒出细菌表面宿主 - 病原体蛋白质相互作用网络的拓扑结构和密度,揭示出一个密集且高度有序的蛋白质相互作用网络。通过电子显微镜验证,从细菌表面去除M蛋白会导致网络拓扑结构发生剧烈变化。我们提出,人血浆中细菌的化学计量表面密度模型代表了一个可扩展的框架,能够随着新结果的出现不断完善。新结果的未来整合将增进对蛋白质 - 蛋白质相互作用及其对细菌毒力重要性的理解。此外,我们预计所开发工作流程的一般特性将有助于生成其他类型宿主 - 病原体相互作用的化学计量表面密度模型。

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