Real-time Three-dimensional Tracking of Endocytic Vesicles
Bibliographic record
Abstract
Endocytic trafficking and recycling are fundamental cellular processes that control essential functions such as signaling protein complexes transport and membrane identity. The small GTPase Rabs are indispensable component of the endosomal recycling machinery. The Rabs bind to effectors to mediate their functions, such as protein sorting and degradation, membrane tethering or lipid modification, and organelle motility. Due to the complex and dynamic nature of endosomal compartments and tracking route, detailed multiparametric analyses of three-dimensional data by quantitative methods are challenging. Here, we describe a detailed time-lapse imaging protocol designed for the quantitative tracking of single endosomal vesicles, using GFP-Rab4-positive recycling endosomes. This method permits automated tracking of single endocytic vesicles in three-dimensional live cell imaging, allowing the study of multiple parameters such as abundance, speed, directionality, and subcellular localization, as well as protein colocalization. This protocol can be broadly used in any kind of cellular models, under various contexts, including growth factors stimulation, gene knockdowns, drug treatments, and is suitable for high throughput screens., [摘要]内吞运输和再循环是基本的细胞过程，它们控制诸如信号蛋白复合物运输和膜特性等基本功能。小GTPase-Rabs是内质体回收机械中不可缺少的组成部分。Rabs结合效应器介导其功能，如蛋白质的分类和降解，膜栓系或脂质修饰，以及细胞器的运动。由于内体隔室和追踪路线的复杂性和动态性，用定量方法对三维数据进行详细的多参数分析是一项具有挑战性的工作。在这里，我们描述了一个详细的延时成像协议，设计用于定量跟踪单个内囊泡，使用GFP-Rab4阳性循环内体。这种方法允许在三维活体细胞成像中自动跟踪单个内吞小泡，允许研究多个参数，如丰度、速度、方向性、亚细胞定位以及蛋白质共定位。该协议可广泛应用于各种环境下的细胞模型，包括生长因子刺激、基因敲除、药物治疗等，适用于高通量筛选。 [背景] 越来越多的证据强调了在细胞迁移、粘附、形态发生、增殖、胞质分裂以及学习和记忆等不同过程中协调的内质体再循环的重要性（Grant和Donaldson，2009年；Parachoniak和Park，2012年；Wandinger Ness和Zerial，2014年；Zaoui等人，2019a和2019b）. 哺乳动物中有70多种Rab-gtpase，它们在膜转运中具有不同的定位和功能。更复杂的是，虽然大多数Rab-gtpase是普遍存在的，但有些表现出组织特异性表达（van der Sluijs等人，1992年；McCaffrey等人，2001年；Grant和Donaldson，2009年；Wandinger Ness和Zerial，2014年）. 其中，定位于早期内体的小GTPase Rab4调节着从早期和再循环的内体到质膜的内吞过程。Rab4参与了Tfn和Tfn等受体的循环受体酪氨酸激酶整合素、泛素连接酶以及与小泡形成、出芽、运输和融合相关的其他机械调节因子(McCaffrey等人，2001年;格兰特和唐纳森，2009年；Stenmark，2009年；Parachoniak等人，2011年；Wandinger Ness和Zerial，2014年;Zaoui等人，2019a). 我们最近报告了对机器翻译的严格要求加末端追踪蛋白用于Rab4介导Met的CLIP-170RTK公司肝细胞生长因子（HGF）在质膜上循环。Met/Rab4小泡向MT plus端的定位增加，导致细胞突起动力学和细胞迁移增强(Zaoui等人，2019a).因此，通过介导细胞内吞途径分为早期、再循环、晚期和溶酶体追踪途径，并通过调控从囊泡出芽到融合的转运，Rabs是细胞信号的重要整合因子。Rabs控制信号输出的定位、强度和持续时间，以实现信号转导的时空调控（McCaffrey等人，2001；Stenmark，2009；Grant和Donaldson，2009；Parachoniak和Park，2012；Wandinger Ness和Zerial，2014；Zaoui等人，2019a）。在许多恶性肿瘤中可观察到内吞改变，并可导致持续增殖、生存、侵袭性和治疗抵抗（；Mellman和Yarden，2013；Zaoui等人，2019a和2019b）。我们的研究旨在了解细胞信号在致癌环境中调节细胞骨架重排、细胞迁移和侵袭的内吞循环改变。Parachoniak和Park，2012年本文所述的协议允许在三维活体细胞成像中自动跟踪内吞囊泡，允许在生理和肿瘤发生条件下研究和量化多个参数。此外，这种方法可以很容易地扩展到评估其他Rab家族成员或任何其他细胞囊泡的移动性。
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".