Quantitative indices of autophagy activity from minimal models

Abstract

BackgroundA number of cellular- and molecular-level studies of autophagy assessment have been carried out with the help of various biochemical and morphological indices. Still there exists ambiguity for the assessment of the autophagy status and of the causal relationship between autophagy and related cellular changes. To circumvent such difficulties, we probe new quantitative indices of autophagy which are important for defining autophagy activation and further assessing its roles associated with different physiopathological states.MethodsOur approach is based on the minimal autophagy model that allows us to understand underlying dynamics of autophagy from biological experiments. Specifically, based on the model, we reconstruct the experimental context-specific autophagy profiles from the target autophagy system, and two quantitative indices are defined from the model-driven profiles. The indices are then applied to the simulation-based analysis, for the specific and quantitative interpretation of the system.ResultsTwo quantitative indices measuring autophagy activities in the induction of sequestration fluxes and in the selective degradation are proposed, based on the model-driven autophagy profiles such as the time evolution of autophagy fluxes, levels of autophagosomes/autolysosomes, and corresponding cellular changes. Further, with the help of the indices, those biological experiments of the target autophagy system have been successfully analyzed, implying that the indices are useful not only for defining autophagy activation but also for assessing its role in a specific and quantitative manner.ConclusionsSuch quantitative autophagy indices in conjunction with the computer-aided analysis should provide new opportunities to characterize the causal relationship between autophagy activity and the corresponding cellular change, based on the system-level understanding of the autophagic process at good time resolution, complementing the current in vivo and in vitro assays.

Autophagy mediates phase transitions from cell death to life

“…Despite that remarkable efforts have been made to unveil the cellular and molecular mechanisms involved in the autophagy machinery, we are still far from understanding the underlying principle of the autophagic process and function. Hence, in practice, a number of challenges still remain in assessing and interpreting the autophagy activity: Assessment of the autophagic flux, i.e., the rate of flow along the autophagy pathway [9] [10] [11] , via conventional assays relying on a single specific marker, rather than systemic analyses, often leads to incorrect estimations of the autophagy status and misinterpretations of the cause-and-effect relationship between the autophagic flux and the concomitant functional changes at both cellular and sub-cellular levels [11] [12] . Furthermore, there exist difficulties in interpreting newly elucidating molecular mechanisms of autophagy; sometimes they contradict the existing hypotheses.…”

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

“…In this study we have investigated via modeling and simulations how autophagy activity affects Aβ kinetics such as the intra and extracellular levels, secretion, clearance, and autophagic degradation. The mathematical model has been extended from the multi-compartment autophagy model originally developed by Han and Choi [4,9,49,50] to the one with Aβ kinetics incorporated by accommodating the current working hypothesis [29][30][31] and the experimental mechanistic studies [28][29][30][31][32][33][34][35][36]51] on the relationship between autophagy activity and Aβ kinetics. Such multi-compartment frameworks [4,9,49,50] are especially useful for testing biological hypotheses regarding the selective autophagy including Aggrephagy (i.e., autophagic degradation of protein aggregates), Mitophagy (for mitochondria), and Xenophagy (for microbes) [54] because the model can be easily modified easily to incorporate new substrates for selective degradation in each compartment (see Fig.…”

“…with appropriate exponent δ h and constant k h for ATP, where r hi is the rate constant for intralysosomal hydrolysis [40,41]. Further details of the equations for autolysosome formation and intralysosomal hydrolysis can be found in literature [4,9,49,50].…”

“…with appropriate constant k s for amino acid, where C ðmÞ A is the ATP concentration corresponding to the maximal protein synthesis rate and r s denotes the rate constant for the protein synthesis. Further details of the protein synthesis can be found in literature [4,9,49,50].…”

The good, the bad and the autophagosome: exploring unanswered questions of autophagy-dependent cell death

“…Advances in live cell imaging have since complemented these methods substantially, as autophagosomal degradation has been observed to be a highly dynamic process [15][16][17]. Furthermore, although the multi-step nature of autophagy, progressing from initiation to degradation, has been characterised extensively, it has only recently been viewed using minimal models of phase transitions [54]. In light of the findings that targeted autophagy induction can result in autosis, it is intriguing to speculate to what degree autophagosomal degradation is required to achieve such outcome, i.e., is there an autophagic flux threshold to breach?…”