A Serial Sample Processing Strategy with Improved Performance for in-Depth Quantitative Analysis of Type III Secretion Events in Pseudomonas aeruginosa
Author(s) -
Dimitrios Lampaki,
Andreas Diepold,
Timo Glatter
Publication year - 2019
Publication title -
journal of proteome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.644
H-Index - 161
eISSN - 1535-3907
pISSN - 1535-3893
DOI - 10.1021/acs.jproteome.9b00628
Subject(s) - secretion , pseudomonas aeruginosa , effector , type three secretion system , shotgun proteomics , secretory protein , quantitative proteomics , proteomics , quantitative analysis (chemistry) , biology , bacteria , computational biology , chemistry , biochemistry , chromatography , virulence , genetics , gene
The efficient analysis of secretomes is important to study the mechanisms of bacterial secretion. However, secretome analysis of bacteria that rely on rich media for optimal secretion via modern quantitative shotgun proteomics workflows is often hampered by the higher degree of sample impurities. This may be a reason for the low number of quantitative secretome investigations in such cases. We assessed the efficiency and amenability for rich media secretome analysis of different workflows including precipitation, SP3, and a combined, serial workflow. Using the model organism Pseudomonas aeruginosa , we found that the combined TCA-SP3 strategy outperformed the other tested methods on all monitored qualitative and quantitative levels. This method proved to be most efficient in the recovery of proteins secreted by the type III secretion system (T3SS), including all known effector proteins and secretion machinery components. We monitored the compositional changes of secretome samples over time, and observed a strong increase in the secreted protein fraction by the T3SS 2 to 3 h after T3SS induction. Our study conceptually illustrates how the combination of TCA precipitation and SP3 results in orthogonality in depleting sample impurities accompanied by improved chromatographic peptide separation, and more efficient MS detection with improved quantification parameters.
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