Back

Dynamic modelling and analysis of autophagy in the clearance of aggregated α-synuclein in Parkinson's disease

Yang, B.; Yang, Z.; Liu, H.

2022-08-26 systems biology
10.1101/2022.08.26.505373 bioRxiv
Show abstract

The widely-accepted hallmark pathology of Parkinsons disease (PD) is the presence of Lewy bodies (LB) with characteristic abnormal aggregated -synuclein (Syn). Growing physiological evidences suggest that there is a pivotal role for the autophagy-lysosome pathway in the clearance of misfolded Syn (Syn*) for maintaining homeostasis and neural cell function. In this work, we establish a new mathematical model for Syn* degradation through the autophagy pathway. The qualitative simulations discover the tri-stability phenomena and dynamical behaviors of Syn*, i.e., the coexistence of three stable steady states, in which the lower, medium and upper steady states correspond to the healthy, critical and diseased stages of pathological mechanism of PD, respectively. Diverse analyses on codimension-1 and -2 bifurcations suggest that autophagy can control the switches among the stable steady states for the aggregation of Syn*. It is also found that the double negative crosstalk feedback between autophagy and apoptosis is important to the robustness of tri-stability of Syn* for this biodynamic system. Our novel results may be valuable for making further therapeutic strategies in prevention and treatment for PD. Author summarySyn* is one of the most and primary remarkable targets for the universal neurodegenerative disease of PD. Efficient clearance mechanism of autophagy, contains a lot of molecular components to maintain the cellular homeostasis and cell renewal, could be the possible therapy for PD. Understand the complexity of autophagy in degrading Syn* requires the integration of both theoretical and experimental points of view. Here, we have proposed a novel mathematical model that analyses the temporal and dynamic behaviors of the biosystem for autophagy degrades Syn* to access PD states. The model explains that the tri-stability is of particularly relevance to this biosystem that switch among the healthy, critical and disease states, and captures that the critical intermedium state exits for preventing the system transform healthy to disease state directly, and further illustrates that the molecular signaling feedback loops of autophagy may be important for the robustness of tri-stability. Our work deepens the researches of PD by uncovering the important buffering medium state and providing promising potential therapeutic insights.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

1
Chaos, Solitons & Fractals
32 papers in training set
Top 0.1%
12.0%
2
PLOS Computational Biology
1863 papers in training set
Top 4%
9.0%
3
PLOS ONE
5266 papers in training set
Top 21%
8.0%
4
Chaos: An Interdisciplinary Journal of Nonlinear Science
17 papers in training set
Top 0.1%
6.8%
5
npj Systems Biology and Applications
125 papers in training set
Top 0.3%
5.2%
6
Biosystems
31 papers in training set
Top 0.1%
4.4%
7
Scientific Reports
3612 papers in training set
Top 26%
4.1%
8
Computers in Biology and Medicine
128 papers in training set
Top 1.0%
3.5%
50% of probability mass above
9
Frontiers in Computational Neuroscience
60 papers in training set
Top 0.4%
3.3%
10
Journal of Theoretical Biology
162 papers in training set
Top 0.9%
3.2%
11
Heliyon
152 papers in training set
Top 2%
2.1%
12
Biophysics and Physicobiology
11 papers in training set
Top 0.1%
1.7%
13
Infectious Diseases of Poverty
11 papers in training set
Top 0.1%
1.5%
14
International Journal of Molecular Sciences
494 papers in training set
Top 10%
1.3%
15
Cells
249 papers in training set
Top 4%
1.3%
16
Computational and Structural Biotechnology Journal
242 papers in training set
Top 5%
1.1%
17
Frontiers in Oncology
103 papers in training set
Top 3%
1.1%
18
Bulletin of Mathematical Biology
92 papers in training set
Top 1%
1.1%
19
eLife
5828 papers in training set
Top 57%
1.1%
20
Frontiers in Physiology
106 papers in training set
Top 2%
1.1%
21
Journal of The Royal Society Interface
235 papers in training set
Top 4%
0.9%
22
iScience
1154 papers in training set
Top 34%
0.9%
23
Mathematical Biosciences and Engineering
23 papers in training set
Top 0.8%
0.9%
24
Physical Review E
112 papers in training set
Top 1%
0.9%
25
IEEE Access
35 papers in training set
Top 1%
0.9%
26
Frontiers in Molecular Biosciences
102 papers in training set
Top 2%
0.9%
27
Royal Society Open Science
214 papers in training set
Top 7%
0.6%
28
Cognitive Neurodynamics
18 papers in training set
Top 0.5%
0.6%
29
Biomolecules
100 papers in training set
Top 3%
0.6%