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      Computational modeling of the effects of autophagy on amyloid-β peptide levels

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          Abstract

          Background

          Autophagy is an evolutionarily conserved intracellular process that is used for delivering proteins and organelles to the lysosome for degradation. For decades, autophagy has been speculated to regulate amyloid-β peptide (Aβ) accumulation, which is involved in Alzheimer’s disease (AD); however, specific autophagic effects on the Aβ kinetics only have begun to be explored.

          Results

          We develop a mathematical model for autophagy with respect to Aβ kinetics and perform simulations to understand the quantitative relationship between Aβ levels and autophagy activity. In the case of an abnormal increase in the Aβ generation, the degradation, secretion, and clearance rates of Aβ are significantly changed, leading to increased levels of Aβ. When the autophagic Aβ degradation is defective in addition to the increased Aβ generation, the Aβ-regulation failure is accompanied by elevated concentrations of autophagosome and autolysosome, which may further clog neurons.

          Conclusions

          The model predicts that modulations of different steps of the autophagy pathway (i.e., Aβ sequestration, autophagosome maturation, and intralysosomal hydrolysis) have significant step-specific and combined effects on the Aβ levels and thus suggests therapeutic and preventive implications of autophagy in AD.

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          Most cited references46

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          Selective autophagy mediated by autophagic adapter proteins

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            Amino acid signalling upstream of mTOR.

            Mammalian target of rapamycin (mTOR) is a conserved Ser/Thr kinase that is part of mTOR complex 1 (mTORC1), a master regulator that couples amino acid availability to cell growth and autophagy. Multiple cues modulate mTORC1 activity, such as growth factors, stress, energy status and amino acids. Although amino acids are key environmental stimuli, exactly how they are sensed and how they activate mTORC1 is not fully understood. Recently, a model has emerged whereby mTORC1 activation occurs at the lysosome and is mediated through an amino acid sensing cascade involving RAG GTPases, Ragulator and vacuolar H(+)-ATPase (v-ATPase).
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              Selective autophagy: ubiquitin-mediated recognition and beyond.

              Eukaryotic cells use autophagy and the ubiquitin-proteasome system as their major protein degradation pathways. Whereas the ubiquitin-proteasome system is involved in the rapid degradation of proteins, autophagy pathways can selectively remove protein aggregates and damaged or excess organelles. Proteasome-mediated degradation requires previous ubiquitylation of the cargo, which is then recognized by ubiquitin receptors directing it to 26S proteasomes. Although autophagy has long been viewed as a random cytoplasmic degradation system, the involvement of ubiquitin as a specificity factor for selective autophagy is rapidly emerging. Recent evidence also suggests active crosstalk between proteasome-mediated degradation and selective autophagy. Here, we discuss the molecular mechanisms that link autophagy and the proteasome system, as well as the emerging roles of ubiquitin and ubiquitin-binding proteins in selective autophagy. On the basis of the evolutionary history of autophagic ubiquitin receptors, we propose a common origin for metazoan ubiquitin-dependent autophagy and the cytoplasm-to-vacuole targeting pathway of yeast.
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                Author and article information

                Contributors
                kyungreem.han@nih.gov
                mychoi@snu.ac.kr
                Journal
                Theor Biol Med Model
                Theor Biol Med Model
                Theoretical Biology & Medical Modelling
                BioMed Central (London )
                1742-4682
                26 February 2020
                26 February 2020
                2020
                : 17
                : 2
                Affiliations
                [1 ]GRID grid.94365.3d, ISNI 0000 0001 2297 5165, Laboratory of Computational Biology, National Heart, , Lung and Blood Institute, National Institutes of Health, ; Bethesda, MD USA
                [2 ]GRID grid.31501.36, ISNI 0000 0004 0470 5905, Department of Physics and Astronomy and Center for Theoretical Physics, , Seoul National University, ; Seoul, South Korea
                Author information
                http://orcid.org/0000-0001-8070-7716
                Article
                119
                10.1186/s12976-020-00119-6
                7045373
                32102666
                9a1c2d76-dd84-499e-ac69-4dfdbb06e3f1
                © The Author(s) 2020

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 19 December 2019
                : 11 February 2020
                Funding
                Funded by: National Research Foundation (KR)
                Award ID: 2019R1F1A1046285
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2020

                Quantitative & Systems biology
                autophagy model,amyloid-β peptide,alzheimer’s disease
                Quantitative & Systems biology
                autophagy model, amyloid-β peptide, alzheimer’s disease

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