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Several proteins which interact with ATGL16L have been identified to reveal it's function. It appears to be, that ATGL16L has an important role not only in autophagy but also in xenophagy for example during a bacterial infection, in antigen presentation and hormone secretion. |
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== Structure == |
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ATG16L1 protein consists of three main domains - N-terminal region which contains an alpha-helix required for binding to ATG5 ubiquitin-folds, a middle region (coiled-coil domain, CCD), and seven WD40 domains found in its C-terminal part. Polymorphisms and mutations in these domains are considered to be associated with several diseases. |
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ATG16L1 is considered do exist in an ~800 kDa complexes composed of several dimers, provided mostly by a CCD region of the protein and binding to ATG5. The middle region is considered to be essencial for the ATG16L1 function. Mice with CCD deletions exhibited phenotypic abnormalities as well as neonatal fatality, though non of these were observed in WD40 region deletion phenotype. |
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Mutations in the ATG16L1 gene may be linked to Crohn's disease. A coding polymorphism in ''atgl1'' gene is considered to be a risk factor for the Crohn's disease development as well as ''atgl2.'' ATG16 appeared to be an essential protein for the function of intestinal stem cells, morphological structure in the intestine and granule exocytosis pathway of the Paneth cell in animal models. It was also shown that low levels of ATG16L1 result in lower ATG16L1-NOD2 complex formation, which is crucial for bacterial autophagy in the bacterial entry site. Inhibition of autophagy leads to a NOD2 signaling through RIP2 kinase and induction of cytokine responses. This leads to an increase in mRNA expression of highly potent pro-inflammatory cytokines as interkleukin-1 (IL-1beta). |
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ATGL2 is a related protein, which is also highly conserved (both of these proteins share 94 and 83% sequence identity). It was shown, that the decrease in ATGL2 expression is correlated with Multiple Sclerosis and can be used as i marker of the disease and specifically for the prediction of relapse rates. |
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