Literature DB >> 24841946

Shotgun proteomics: identification of unique protein profiles of apoptotic bodies from biliary epithelial cells.

Ana Lleo1, Weici Zhang, W Hayes McDonald, Erin H Seeley, Patrick S C Leung, Ross L Coppel, Aftab A Ansari, David H Adams, Simon Afford, Pietro Invernizzi, M Eric Gershwin.   

Abstract

UNLABELLED: Shotgun proteomics is a powerful analytic method to characterize complex protein mixtures in combination with multidimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS). We used this platform for proteomic characterization of apoptotic bodies in an effort to define the complex protein mixtures found in primary cultures of human intrahepatic biliary epithelial cells (HiBEC), human renal proximal tubular epithelial cells, human bronchial epithelial cells, isolated intrahepatic biliary epithelial cells from explanted primary biliary cirrhosis (PBC), and control liver using a total of 24 individual samples. Further, as additional controls and for purposes of comparison, proteomic signatures were also obtained from intact cells and apoptotic bodies. The data obtained from LC-MS/MS, combined with database searches and protein assembly algorithms, allowed us to address significant differences in protein spectral counts and identify unique pathways that may be a component of the induction of the signature inflammatory cytokine response against BECs, including the Notch signaling pathway, interleukin (IL)8, IL6, CXCR2, and integrin signaling. Indeed, there are 11 proteins that localize specifically to apoptotic bodies of HiBEC and eight proteins that were specifically absent in HiBEC apoptotic bodies.
CONCLUSION: Proteomic analysis of BECs from PBC liver compared to normal liver are significantly different, suggesting that an immunological attack affects the repertoire of proteins expressed and that such cells should be thought of as living in an environment undergoing continuous selection secondary to an innate and adaptive immune response, reflecting an almost "Darwinian" bias.
© 2014 by the American Association for the Study of Liver Diseases.

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Year:  2014        PMID: 24841946      PMCID: PMC4175017          DOI: 10.1002/hep.27230

Source DB:  PubMed          Journal:  Hepatology        ISSN: 0270-9139            Impact factor:   17.425


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