Literature DB >> 22652647

Cigarette smoke enhances chemotaxis via acetylation of proline-glycine-proline.

Matthew Thomas Hardison1, Michael David Brown, Robert James Snelgrove, James Edwin Blalock, Patricia Jackson.   

Abstract

Several chronic lung diseases have been linked to cigarette smoking (Chronic Obstructive Pulmonary Disease (COPD), and cancer are associated with increased tobacco use). We recently described a collagen fragment, proline-glycine-proline (PGP), chemotactic for neutrophils, that appears to play a role in COPD, cystic fibrosis, and bronchiolitis obliterans syndrome. PGP can exist in either its native or acetylated form (NAcPGP), although the mechanism of N-terminal-acetylation remains unknown. This work investigates the possibility that cigarette smoke (CS) and its components acetylate PGP, describing a possible mechanism for some of the chronic inflammation seen in tobacco-associated disease. CSE and CSC (3.56 and 12.38 ng/ml NAcPGP respectively, p less than 0.01) and its components (acrolein, acetaldehyde, and methyl glyoxal) acetylated PGP (0.51, 1.03, and 0.23 ng/ml NAcPGP, p less than 0.01). Both N-acetyl-cysteine and carbocysteine (scavengers of reactive aldehydes) blocked chemical acetylation of PGP by CS (100 percent and 97 percent inhibition, respectively, p less than 0.01). NAcPGP is more chemoattractive to neutrophils, and less susceptible to degradation by Leukotriene-A4-Hydrolase (detected in the lung). These experiments propose a mechanism for the increased neutrophil recruitment seen in smoking-associated lung diseases.

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Year:  2012        PMID: 22652647      PMCID: PMC5796637          DOI: 10.2741/e552

Source DB:  PubMed          Journal:  Front Biosci (Elite Ed)        ISSN: 1945-0494


  24 in total

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  12 in total

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8.  The matrikine N-α-PGP couples extracellular matrix fragmentation to endothelial permeability.

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9.  Matrikines are key regulators in modulating the amplitude of lung inflammation in acute pulmonary infection.

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10.  Discriminating between lysine sumoylation and lysine acetylation using mRMR feature selection and analysis.

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