Name: Lifespan Machine Experiment Preparation and Setup for Lifespan and Behavioral Aging Assays on Caenorhabditis elegans
Uploaded: 2024-01-26T13:00:00
Description: Watch this Scientific Journal Video about Lifespan Machine Experiment Preparation and Setup for Lifespan and Behavioral Aging Assays on Caenorhabditis elegans at JoVE.com

lifespan machine experiment preparation and setup for lifespan and behavioral aging assays on caenorhabditis elegans

揭开老化的奥秘：用于高通量洞察的 Lifespan Machine

Aging is a complex, multifaceted process characterized by a decline in the physiological function of an organism, which leads to an increase in the risk of disease and death over time1. Lifespan, measured as the time from birth or the onset of adulthood until death, provides an unambiguous outcome of aging2 and an indirect but rigorously quantitative proxy for measuring the relative rate of aging between populations3. Aging studies often depend on accurate measurements of lifespan, similar to clinical trials, to compare outcomes between one population exposed to an intervention and an unexposed control group. Unfortunately, reproducibility issues pervade aging research, sometimes due to statistically underpowered experiments4 and often because of the inherent sensitivity of lifespan assays to subtle variations in the environment5. Robust experiments require multiple replicates of large populations, and this process particularly benefits from the experimental scalability offered by automation6.
The rigorous demands of lifespan assays originate from the unpredictability of the aging process itself. Isogenic individuals housed in identical environments display different death times and rates of physiological decline7, suggesting that lifespan involves a high degree of stochasticity7,8. Therefore, large populations are required to measure quantitative changes in the aging process, such as changes in the mean or maximum lifespan, and to overcome biases arising from individual variability. In addition, a capacity for high-throughput lifespan assays is crucial to support studies of survival curve shapes and models of the dynamics of aging9.
The nematode Caenorhabditis elegans is an invaluable model for aging research due to its short lifespan, genetic tractability, and rapid generation time, which underscore its suitability for high-throughput aging and lifespan assays. Traditionally, the lifespan in C. elegans has been measured by following a synchronized, small population of about 50-100 animals over time on solid media and writing down the time of individual deaths. As animals age and lose mobility, manually scoring the death times requires individually prodding the animals and checking for small movements of the head or tail. This is usually a tedious and laborious process, though efforts have been made to accelerate it10,11,12. Importantly, slow experimental pipelines hinder progress in our understanding of aging and the effectiveness of tested interventions.
To meet the demands of aging research for quantitative data, many technologies have been developed for automating data collection, including a remarkable range of approaches from microfluidic chambers to flatbed scanners13,14,15,16,17,18. The LSM differs from other methods in its extensive optimization for the collection of highly precise and accurate lifespan data, which is achieved through the development of careful equipment calibration protocols combined with an extensive software suite that allows users to validate, correct, and refine automated analyses13. Though the software can, in principle, be applied to diverse imaging modalities, in practice, most users use flatbed scanners modified to allow for fine-tuned control over the environmental temperature and humidity - factors of critical importance due to their major effect on lifespan19. The LSM takes images of nematodes every 20 min over intervals ranging from days to months, depending on the environmental conditions and genotype. The data produced are of much higher temporal resolution compared to data from manual assays, and the images collected provide a permanent visual record of the nematode position across the lifespan. Using machine-learning methods, death times are automatically assigned to each individual. These results can be rapidly, manually validated using a client software called &#34;Worm Browser&#34;. As a result of its hardware and software, the LSM can generate survival curves that are statistically indistinguishable from manual death scoring at the hands of experienced researchers, with the added advantage of decreased workload and higher scalability13.
The latest version of the LSM also allows for the study of behavioral aging by collecting morphological and behavioral data throughout the nematode&#39;s life and reporting it along with the lifespan of each individual. In particular, the LSM captures the time of each animal&#39;s vigorous movement cessation (VMC), a landmark often used to quantify the &#34;healthspan&#34; of an individual as distinct from its lifespan. By simultaneously collecting lifespan and behavioral aging data, the LSM supports the study of interventions that may have differential effects on different phenotypic outcomes of aging20. A variety of macroscopically observable phenotypes can be used to study behavioral aging, such as body movement or pharyngeal pumping21, tissue integrity22, and movement speed or stimulus-induced turning17. Comparisons between different aging phenotypes can support analyses of the causal structure of aging processes. For instance, the comparison between VMC and lifespan was recently used to characterize two distinct aging processes in C. elegans23.
While initially developed to measure lifespan in C. elegans, the LSM supports the collection of survival and behavioral data from a range of nematode species, including C. briggsae, C. tropicalis, C. japonica, C. brenneri, and P. pacificus23. The technology facilitates the study of the effect of biological and environmental interventions on lifespan, stress resistance, and pathogen resistance and can be coupled to experimental tools such as targeted assays of RNA interference or auxin-inducible protein degradation systems. To date, it has been used in the scientific literature for a wide range of applications6,24,25,26,27,28,29,30.
Here, we outline a step-by-step protocol for performing a Lifespan Machine experiment using agar plates, from the initial stages of the experimental setup to the output of the resulting survival curves. A distinctive feature of the LSM is that the effort is highly front-loaded, meaning that the majority of the researcher&#39;s time is spent during experimental setup and, to a small degree, during post-image&#160;acquisition. The data collection is completely automated for the whole duration of the experiment and allows the researcher to have a &#34;hands-free&#34; experience. The steps described here are held in common among many different types of survival assays - the same experimental setup is performed for lifespan, thermotolerance, oxidative stress, and pathogenesis assays. In the representative results section, we discuss a subset of data from a recently published manuscript to illustrate the effectiveness of the analysis pipeline and highlight the most important steps during image analysis23.

作者聚焦：自动寿命监测 – 使用 Lifespan Machine 发现衰老动态 

使用 Lifespan 机器进行高通量行为老化和寿命检测

In our lab, we study the physiological and molecular determinants of aging and lifespan, and we do so in a quantitative manner. For this, we use the nematode C.elegans as a fast-aging genetically tractable model, and we use it with a combination of tools such as the Lifespan Machine. Reproducibility is an important issue in aging research.To overcome this, large population of animals are often required for measuring robust changes in lifespan, and therefore, this process really benefits from automated high-throughput protocols. Lots of people have used the Lifespan Machine for many different purposes and are really happy about that. For our own applications, the two most significant findings are, first, in 2016, our discovery of temporal scaling as a common outcome of many interventions in aging.And second, in 2022, our discovery that healthspan and lifespan are determined by distinct underlying physical declines. The Lifespan Machine adapts commonly used agar plate protocols to collect survival and behavioral aging data from large populations of nematodes. By automation and high-frequency of image acquisition, it eliminates the daily tedious process of by-hand survival assays and gathers previously unattainable datasets on nematode behavior.

Watch this Scientific Journal Video about Lifespan Machine Experiment Preparation and Setup for Lifespan and Behavioral Aging Assays on Caenorhabditis elegans at JoVE.com

Lifespan Machine Experiment Preparation and Setup for Lifespan and Behavioral Aging Assays on Caenorhabditis elegans   

秀丽隐杆线虫寿命和行为衰老测定的寿命机器实验准备和设置

首先，确保扫描仪板已准备好装载线虫。一般来说，每个盘子大约有40只动物和200微升的细菌草坪是长寿命实验的最佳条件。通过在支撑扫描仪板的玻璃板的两侧应用防雾玻璃清洁剂来开始实验设置。然后在将与扫描仪板接触的玻璃侧面进行保护性疏水玻璃处理。等待 5 到 10 分钟，然后清除玻璃板上的所有残留物。涂抹 70% 乙醇对将与扫描仪板接触的玻璃一侧进行消毒。静置一到两分钟，然后用布或纸巾除去乙醇。要将印版加载到扫描仪上，请将高压灭菌器橡胶垫放在处理过的印版支撑玻璃的顶部。拿起用于对加载的线虫进行成像的扫描仪板，并取下盖子。将板放在面向玻璃表面的橡胶垫位置。拔下扫描器风扇的插头，以在板加载过程中保护实验者的手指。轻轻地将印版和支撑它们的玻璃板滑到扫描仪的表面上。重新激活扫描仪风扇，并确认正面和侧面风扇已通电。此时打开扫描仪。在开始实验之前，请执行必要的图像采集前步骤，包括获取整个扫描仪表面的预览捕获图像。使用 Web 界面，找到主页的图像采集部分，然后点击名为“捕获设备和图像服务器”的链接。在打开的框中，单击“搜索新设备”，并确保连接到服务器的每个扫描仪都显示在“图像捕获设备”框中。选中与包含新加载的印版的每个扫描仪相对应的复选框，然后单击请求预览捕获按钮。接下来，在蠕虫浏览器上，选择文件打开图像，然后选择所需的图像以打开每个预览捕获图像。对于每个图像，单击以选择与包含板的区域相对应的列。定义所有图像后，选择图像采集。定义扫描区域，将选定的扫描区域保存到光盘，然后选择所需位置以将该区域的规格导出到光盘。组装一个包含实验名称、扫描仪上每列的物理位置、实验的总持续时间和图像捕获频率的文件。将其另存为文本和 XML 文件。在蠕虫浏览器上，单击图像采集，提交实验计划，然后选择生成的 XML 文件。蠕虫浏览器将询问是输出计划摘要还是运行实验。生成摘要文件，验证计划捕获的日期、位置、名称和摘要中的扫描仪数量。同样，如图所示，加载实验计划的 XML 文件。蠕虫浏览器将再次提示是输出计划摘要还是运行实验。这一次，选择运行实验。生命周期机器现在将自主工作，直到完成实验计划中指定的最终扫描。实验结束后，执行了所有图像和邮资获取步骤，使用 Worm 浏览器手动验证自动结果。在蠕虫浏览器菜单上，单击文件，选择当前实验，然后选择所需的实验。要生成情节提要，请单击“验证”，浏览整个实验，然后在每个蠕虫死亡后立即选择。右键单击对象的图像以从情节提要中排除非蠕虫对象。要同时排除页面上的所有对象，请按住 Control 键并右键单击任何对象。右键单击两次可将排除的对象重新包含在分析中。要保存在情节提要注释期间所做的注释，请单击保存按钮。在情节提要的任何对象上单击鼠标左键，打开一个新窗口，该窗口显示有关该对象的详细时间序列信息。要手动注释死亡时间，请左键单击与死亡时间相对应的点的底部栏。使用空格键和键盘的向右或向左箭头在时间范围内移动，或在所需的时间范围内直接单击该按钮。通过在所需时间范围内右键单击底部栏来手动注释收缩和膨胀事件。请参阅左侧的生存曲线和散点图，将剧烈运动停止的时间与故事板右侧的每个人的死亡时间进行比较。若要生成实验的死亡时间，请在 Worm 浏览器上选择“数据文件”和“死亡时间”，然后单击“为当前实验生成死亡时间”。此处显示了手动数据验证对生存曲线的影响。在故事板注释之前生成的初始生存曲线因不恰当地包含非蠕虫对象而失真。在手动故事板注释过程中排除非蠕虫对象后，生成的生存曲线显示出显着提高的分辨率。图形表示显示了图像采集后分析不同步骤的估计平均剩余寿命，及其与蠕虫寿命的相关性。研究发现，在行为衰老分析中手动注释死亡时间对于长寿蠕虫尤为重要。在这种情况下，那些暴露于最低浓度的牛的人。总之，寿命机器自动死亡时间估计对于生存测定来说足够准确。而行为老化检测可以从手动注释中受益。

Research

JoVE Journal

Biology

Lifespan Machine Experiment Preparation and Setup for Lifespan and Behavioral Aging Assays on Caenorhabditis elegans

High-Throughput Behavioral Aging and Lifespan Assays Using the Lifespan Machine

Genetically identical animals kept in a constant environment display a wide distribution of lifespans, reflecting a large non-genetic, stochastic aspect ...