Let's talk about flux: the rising potential of autophagy rate measurements in disease.

Autophagy Pub Date : 2024-11-01 Epub Date: 2024-07-10 DOI:10.1080/15548627.2024.2371708
Nitin Sai Beesabathuni, Matthew W Kenaston, Ritika Gangaraju, Neil Alvin B Adia, Vardhan Peddamallu, Priya S Shah
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Abstract

Macroautophagy/autophagy is increasingly implicated in a variety of diseases, making it an attractive therapeutic target. However, many aspects of autophagy are not fully understood and its impact on many diseases remains debatable and context-specific. The lack of systematic and dynamic measurements in these cases is a key reason for this ambiguity. In recent years, Loos et al. 2014 and Beesabathuni et al. 2022 developed methods to quantitatively measure autophagy holistically. In this commentary, we pose some of the unresolved biological questions regarding autophagy and consider how quantitative measurements may address them. While the applications are ever-expanding, we provide specific use cases in cancer, virus infection, and mechanistic screening. We address how the rate measurements themselves are central to developing cancer therapies and present ways in which these tools can be leveraged to dissect the complexities of virus-autophagy interactions. Screening methods can be combined with rate measurements to mechanistically decipher the labyrinth of autophagy regulation in cancer and virus infection. Taken together, these approaches have the potential to illuminate the underlying mechanisms of various diseases.Abbreviation MAP1LC3/LC3: microtubule-associated protein 1 light chain 3; R1: rate of autophagosome formation; R2: rate of autophagosome-lysosome fusion; R3: rate of autolysosome turnover.

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让我们来谈谈通量:自噬率测量在疾病中不断提升的潜力。
大自噬/自噬与多种疾病的关系日益密切,使其成为一个极具吸引力的治疗靶点。然而,人们对自噬的许多方面并不完全了解,自噬对许多疾病的影响仍有待商榷,而且要视具体情况而定。在这些情况下缺乏系统和动态的测量是造成这种模糊性的关键原因。近年来,Loos 等人 2014 年和 Beesabathuni 等人 2022 年开发出了全面定量测量自噬的方法。在这篇评论中,我们提出了一些有关自噬的悬而未决的生物学问题,并考虑如何通过定量测量来解决这些问题。虽然自噬的应用范围不断扩大,但我们提供了癌症、病毒感染和机理筛选方面的具体用例。我们探讨了速率测量本身如何成为开发癌症疗法的核心,并介绍了如何利用这些工具来剖析病毒与自噬相互作用的复杂性。筛选方法可与速率测量相结合,从机理上破解癌症和病毒感染中自噬调控的迷宫。缩写 MAP1LC3/LC3:微管相关蛋白 1 轻链 3;R1:自噬体形成率;R2:自噬体与溶酶体融合率;R3:自溶酶体周转率。
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