Dataset Information

Contributions of Mass Spectrometry-Based Proteomics to Understanding Salmonella-Host Interactions.

ABSTRACT: As a model pathogen, Salmonella invades both phagocytic and non-phagocytic host cells and adopts an intracellular lifestyle in a membrane-bound compartment during infection. Therefore, a systemic overview of Salmonella adaptations to distinct host cells together with host remodeling will assist us in charting the landscape of host-pathogen interactions. Central to the Salmonella-host interplay are bacterial virulence factors (effectors) that are injected into host cells by type III secretion systems (T3SSs). Despite great progress, functional studies of bacterial effectors have experienced daunting challenges as well. In the last decade, mass spectrometry-based proteomics has evolved into a powerful technological platform that can quantitatively measure thousands of proteins in terms of their expression as well as post-translational modifications. Here, we will review the applications of high-throughput proteomic technologies in understanding the dynamic reprogramming of both Salmonella and host proteomes during the course of infection. Furthermore, we will summarize the progress in utilizing affinity purification-mass spectrometry to screen for host substrates of Salmonella T3SS effectors. Finally, we will critically discuss some limitations/challenges with current proteomic platforms in the context of host-pathogen interactions and highlight some emerging technologies that may offer the promise of tackling these problems.

SUBMITTER: Zhang B

PROVIDER: S-EPMC7400052 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Contributions of Mass Spectrometry-Based Proteomics to Understanding Salmonella-Host Interactions.

Zhang Buyu B Liu Bohao B Zhou Yinglin Y Zhang Xinxiang X Zou Qinghua Q Liu Xiaoyun X

Pathogens (Basel, Switzerland) 20200717 7

As a model pathogen, Salmonella invades both phagocytic and non-phagocytic host cells and adopts an intracellular lifestyle in a membrane-bound compartment during infection. Therefore, a systemic overview of Salmonella adaptations to distinct host cells together with host remodeling will assist us in charting the landscape of host-pathogen interactions. Central to the Salmonella-host interplay are bacterial virulence factors (effectors) that are injected into host cells by t ...[more]

PMID: 32708900

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Project description:BackgroundOsteoarthritis (OA) is a slowly developing and debilitating disease, and there are no validated specific biomarkers for its early detection. To improve therapeutic approaches, identification of specific molecules/biomarkers enabling early determination of this disease is needed. This study aimed at identifying, with the use of proteomics/mass spectrometry, novel OA-specific serum biomarkers. As obesity is a major risk factor for OA, we discriminated obesity-regulated proteins to target only OA-specific proteins as biomarkers.MethodsSerum from the Osteoarthritis Initiative cohort was used and divided into 3 groups: controls (n=8), OA-obese (n=10) and OA-non-obese (n=10). Proteins were identified and quantified from the liquid chromatography-tandem mass spectrometry analyses using MaxQuant software. Statistical analysis used the Limma test followed by the Benjamini-Hochberg method. To compare the proteomic profiles, the multivariate unsupervised principal component analysis (PCA) followed by the pairwise comparison was used. To select the most predictive/discriminative features, the supervised linear classification model sparse partial least squares regression discriminant analysis (sPLS-DA) was employed. Validation of three differential proteins was performed with protein-specific assays using plasma from a cohort derived from the Newfoundland Osteoarthritis.ResultsIn total, 509 proteins were identified, and 279 proteins were quantified. PCA-pairwise differential comparisons between the 3 groups revealed that 8 proteins were differentially regulated between the OA-obese and/or OA-non-obese with controls. Further experiments using the sPLS-DA revealed two components discriminating OA from controls (component 1, 9 proteins), and OA-obese from OA-non-obese (component 2, 23 proteins). Proteins from component 2 were considered related to obesity. In component 1, compared to controls, 7 proteins were significantly upregulated by both OA groups and 2 by the OA-obese. Among upregulated proteins from both OA groups, some of them alone would not be a suitable choice as specific OA biomarkers due to their rather non-specific role or their strong link to other pathological conditions. Altogether, data revealed that the protein CRTAC1 appears to be a strong OA biomarker candidate. Other potential new biomarker candidates are the proteins FBN1, VDBP, and possibly SERPINF1. Validation experiments revealed statistical differences between controls and OA for FBN1 (p=0.044) and VDPB (p=0.022), and a trend for SERPINF1 (p=0.064).ConclusionOur study suggests that 4 proteins, CRTAC1, FBN1, VDBP, and possibly SERPINF1, warrant further investigation as potential new biomarker candidates for the whole OA population.

Dataset Information

Contributions of Mass Spectrometry-Based Proteomics to Understanding Salmonella-Host Interactions.

Publications

Contributions of Mass Spectrometry-Based Proteomics to Understanding <i>Salmonella</i>-Host Interactions.

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