Literature DB >> 32897649

Quantitative Proteomic Profiling of Murine Ocular Tissue and the Extracellular Environment.

Jason Yeung1, Jeffrey Lamb2, Jonathan R Krieger3, Mihaela Gadjeva2, Jennifer Geddes-McAlister1.   

Abstract

Mass spectrometry-based proteomics provides a robust and reliable method for detecting and quantifying changes in protein abundance among samples, including cells, tissues, organs, and supernatants. Physical damage or inflammation can compromise the ocular surface permitting colonization by bacterial pathogens, commonly Pseudomonas aeruginosa, and the formation of biofilms. The interplay between P. aeruginosa and the immune system at the site of infection defines the host's ability to defend against bacterial invasion and promote clearance of infection. Profiling of the ocular tissue following infection describes the nature of the host innate immune response and specifically the presence and abundance of neutrophil-associated proteins to neutralize the bacterial biofilm. Moreover, detection of unique proteins produced by P. aeruginosa enable identification of the bacterial species and may serve as a diagnostic approach in a clinical setting. Given the emergence and prevalence of antimicrobial resistant bacterial strains, the ability to rapidly diagnose a bacterial infection promoting quick and accurate treatment will reduce selective pressure towards resistance. Furthermore, the ability to define differences in the host immune response towards bacterial invasion enhances our understanding of innate immune system regulation at the ocular surface. Here, we describe murine ocular infection and sample collection, as well as outline protocols for protein extraction and mass spectrometry profiling from corneal tissue and extracellular environment (eye wash) samples.
© 2020 Wiley Periodicals LLC. Basic Protocol 1: Murine model of ocular infection Basic Protocol 2: Murine model sample collection Basic Protocol 3: Protein extraction from eye wash Basic Protocol 4: Protein extraction from corneal tissue Basic Protocol 5: Mass spectrometry-based proteomics and bioinformatics from eye wash and corneal tissue samples. © 2020 Wiley Periodicals LLC.

Entities:  

Keywords:  Pseudomonas aeruginosa; bioinformaticszzm321990; corneal tissue; eye wash; mass spectrometry-based proteomics; murine model; murine ocular tissue; ocular keratitis; quantitative proteomic profiling

Mesh:

Substances:

Year:  2020        PMID: 32897649      PMCID: PMC7956148          DOI: 10.1002/cpmo.83

Source DB:  PubMed          Journal:  Curr Protoc Mouse Biol        ISSN: 2161-2617


  29 in total

1.  MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.

Authors:  Jürgen Cox; Matthias Mann
Journal:  Nat Biotechnol       Date:  2008-11-30       Impact factor: 54.908

Review 2.  Decoding communication patterns of the innate immune system by quantitative proteomics.

Authors:  Arjun Sukumaran; Jeremia M Coish; Jason Yeung; Benjamin Muselius; Mihaela Gadjeva; Adam J MacNeil; Jennifer Geddes-McAlister
Journal:  J Leukoc Biol       Date:  2019-09-26       Impact factor: 4.962

3.  Andromeda: a peptide search engine integrated into the MaxQuant environment.

Authors:  Jürgen Cox; Nadin Neuhauser; Annette Michalski; Richard A Scheltema; Jesper V Olsen; Matthias Mann
Journal:  J Proteome Res       Date:  2011-02-22       Impact factor: 4.466

4.  Mass Spectrometry-Based Quantitative Proteomics of Murine-Derived Polymorphonuclear Neutrophils.

Authors:  Jennifer Geddes-McAlister; Mihaela Gadjeva
Journal:  Curr Protoc Immunol       Date:  2019-09

Review 5.  Pseudomonas aeruginosa: new insights into pathogenesis and host defenses.

Authors:  Shaan L Gellatly; Robert E W Hancock
Journal:  Pathog Dis       Date:  2013-03-15       Impact factor: 3.166

6.  Exploration of the Visual System: Part 1: Dissection of the Mouse Eye for RNA, Protein, and Histological Analyses.

Authors:  Pascal Escher; Daniel F Schorderet
Journal:  Curr Protoc Mouse Biol       Date:  2011-12-01

7.  Corneal Biofilms: From Planktonic to Microcolony Formation in an Experimental Keratitis Infection with Pseudomonas Aeruginosa.

Authors:  Padmanabhan Saraswathi; Roger W Beuerman
Journal:  Ocul Surf       Date:  2015-07-26       Impact factor: 5.033

8.  Deep learning enables de novo peptide sequencing from data-independent-acquisition mass spectrometry.

Authors:  Ngoc Hieu Tran; Rui Qiao; Lei Xin; Xin Chen; Chuyi Liu; Xianglilan Zhang; Baozhen Shan; Ali Ghodsi; Ming Li
Journal:  Nat Methods       Date:  2018-12-20       Impact factor: 28.547

9.  Psl trails guide exploration and microcolony formation in Pseudomonas aeruginosa biofilms.

Authors:  Kun Zhao; Boo Shan Tseng; Bernard Beckerman; Fan Jin; Maxsim L Gibiansky; Joe J Harrison; Erik Luijten; Matthew R Parsek; Gerard C L Wong
Journal:  Nature       Date:  2013-05-08       Impact factor: 49.962

Review 10.  Mass Spectrometry-Based Proteomics of Fungal Pathogenesis, Host-Fungal Interactions, and Antifungal Development.

Authors:  Brianna Ball; Arianne Bermas; Duncan Carruthers-Lay; Jennifer Geddes-McAlister
Journal:  J Fungi (Basel)       Date:  2019-06-17
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