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Direct proteomic quantification of the secretome of activated immune cells

ABSTRACT: Protein secretion can mediate communication of distant cells in a multicellular organism and can control a broad range of physiological functions. Regulation of this process is crucial, especially for cells of the immune system that sense pathogens through specific receptors and release proteins that initiate and orchestrate the immune response. This secretome is today analyzed using antibody-based assays, but mass spectrometry could provide an unbiased and comprehensive alternative. Here we developed a quantitative, high resolution mass spectrometric workflow to detect and quantify proteins that are released from macrophages upon Toll-like receptor 4 (TLR4) activation by the microbial component lipopolysaccharide (LPS)5. We quantified the time-resolved release of 775 proteins, including 52 annotated cytokines, from only 150.000 primary cells per condition. The dynamic range of the secretory induction was at least 10,000 fold and we achieved sensitivity in the low picogram range. Comparison to the transcriptome revealed high correlation for some protein classes but also anti-correlation resulting from the transcriptionally decoupled release of lysosomal proteins. Using gene knockout (KO) mouse strains as genetic models with intracellular signaling adaptor deficiencies, we defined distinct secretory profiles depending on which arms of the signaling pathways are missing. We show that MyD88 dominates over TRIF in the number and fold-induction of secreted proteins6,7. Interestingly, the sum of the two signaling arms does not equal the wild-type response; instead, protein secretion is tuned by synergistic and predominantly redundant mechanisms. The kinetic data reveals that the release of anti-inflammatory proteins dampens the initial pro-inflammatory response. Our study provides a paradigm for the sensitive and time-resolved identification of receptor activation induced cellular secretomes, including proteins with unexpected extracellular presence, and allows the characterization of the underlying signal transduction pathways.

ORGANISM(S): Mus musculus

PROVIDER: GSE41490 | GEO | 2013/04/11

SECONDARY ACCESSION(S): PRJNA177213

REPOSITORIES: GEO

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Project description:This a model from the article: Modelling the hypothalamic control of growth hormone secretion. MacGregor DJ, Leng G. J Neuroendocrinol 2005;17(12):788-803 16280026 , Abstract: Here, we construct a mathematical model of the hypothalamic systems that control the secretion of growth hormone (GH). The work extends a recent model of the pituitary GH system, adding representations of the hypothalamic GH-releasing hormone (GHRH) and somatostatin neurones, each modelled as a single synchronised unit. An unpatterned stochastic input drives the GHRH neurones generating pulses of GHRH release that trigger GH pulses. Delayed feedback from GH results in increased somatostatin release, which inhibits both GH secretion and GHRH release, producing an overall pattern of 3-h pulses of GH secretion that is very similar to the secretory profile observed in male rats. Rather than directly stimulating somatostatin release, GH feedback triggers a priming effect, increasing releasable stores of somatostatin. Varying this priming effect to reduce the effect of GH can reproduce the less pulsatile form of GH release observed in the female rat. The model behaviour is tested by comparison with experimental observations with a range of different experimental protocols involving GHRH injections and somatostatin and GH infusion. This model was taken from the CellML repository and automatically converted to SBML. The original model was: MacGregor DJ, Leng G. (2005) - version02 The original CellML model was created by: Lloyd, Catherine, May c.lloyd@aukland.ac.nz The University of Auckland The Bioengineering Institute This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

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Direct proteomic quantification of the secretome of activated immune cells

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