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

Afsløring af aldringsmysterier: Levetidsmaskine til indsigt i høj kapacitet

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.

Forfatter Spotlight: Automatiseret levetidsovervågning - Opdag aldringsdynamik med levetidsmaskinen 

Adfærdsmæssig aldring og levetidsanalyser med høj kapacitet ved hjælp af levetidsmaskinen

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   

Forberedelse og opsætning af levetidsmaskineksperiment til levetids- og adfærdsmæssige aldringsassays på Caenorhabditis elegans

Til at begynde med skal du sikre dig, at scannerpladerne er klar med nematoder indlæst. Generelt er omkring 40 dyr og 200 mikroliter bakteriel græsplæne pr. Plade optimale betingelser for et livslangt eksperiment. Start den eksperimentelle opsætning ved at anvende en anti-dug glasrenser på begge sider af ruderne, der understøtter scannerpladerne.Påfør derefter en beskyttende hydrofob glasbehandling på den side af glasset, der kommer i kontakt med scannerpladerne. Vent fem til 10 minutter, og fjern eventuelle rester på ruden. Påfør 70% ethanol for at desinficere den side af glasset, der skal være i kontakt med scannerpladerne.Lad stå i et til to minutter, og fjern derefter ethanolen med en klud eller køkkenrulle. For at lægge pladerne på scannerne skal du placere autoklavgummimåtterne oven på det behandlede pladestøtteglas. Tag scannerpladerne, der bruges til billeddannelse med indlæste nematoder, og fjern låget.Placer pladerne på gummimåtter mod glasoverfladen. Tag stikket ud af scannerventilatorerne for at beskytte eksperimentatorens fingre under pladeindlæsning. Skub forsigtigt pladerne og glaspladerne, der understøtter dem, på scannerens overflade.Genaktiver scannerblæserne, og bekræft, at front- og sideblæserne er tændt. Tænd scannerne på dette tidspunkt. Før du starter eksperimentet, skal du udføre de væsentlige trin til erhvervelse af forbillede, herunder opnåelse af et eksempeloptagelsesbillede af hele scanneroverfladen.Brug webgrænsefladen til at finde billedoptagelsesafsnittet på hovedsiden og følg linket kaldet Capture Devices and Image Servers. I den åbnede boks skal du klikke på søg efter nye enheder og sikre, at hver scanner, der er tilsluttet serveren, vises i boksen til billedoptagelsesenheder. Marker afkrydsningsfeltet, der svarer til hver scanner, der indeholder nyligt indlæste plader, og klik derefter på knappen Anmod om forhåndsvisning.Vælg derefter Åbn billede fil i ormebrowseren, og vælg derefter det ønskede billede for at åbne hvert eksempeloptagelsesbillede. For hvert billede skal du klikke for at markere de kolonner, der svarer til områder, der indeholder plader. Når alle billederne er defineret, skal du vælge billedoptagelse.Definer scanningsområder, gem valgte scanningsområder på disken, og vælg derefter den ønskede placering for at eksportere områdets specifikationer til disken. Saml en fil, der indeholder eksperimentnavnet, de fysiske placeringer af hver kolonne på scannerne, eksperimentets samlede varighed og billedoptagelsesfrekvensen. Gem dette som en tekst og en XML-fil.Klik på billedanskaffelse i Worm-browseren, indsend eksperimentplan, og vælg den genererede XML-fil. Ormebrowseren spørger, om der skal vises en oversigt over tidsplanen, eller om eksperimentet skal køres. Generer en oversigtsfil, kontroller datoerne for planlagte optagelser, placeringen, navnet og antallet af scannere i oversigten.Indlæs igen XML-filen for eksperimentplanen som vist. Ormebrowseren spørger endnu en gang, om der skal vises en oversigt over tidsplanen, eller om eksperimentet skal køres. Denne gang skal du vælge at køre eksperimentet.Levetidsmaskinen fungerer nu autonomt, indtil de endelige scanninger, der er angivet i eksperimentplanen, er fuldført. Når eksperimentet er afsluttet, og alle trin til hentning af billeder og porto er udført, skal du manuelt validere de automatiserede resultater ved hjælp af ormebrowseren. Klik på filen i menuen Ormbrowser, vælg aktuelt eksperiment, og vælg det ønskede eksperiment.For at generere storyboardet skal du klikke på validering, gennemse hele eksperimentet og derefter vælge umiddelbart efter hver orms død. Højreklik på objektets billede for at udelukke objekter, der ikke er orme, fra storyboardet. For at udelukke alle objekter på en side samtidigt skal du holde kontroltasten nede og højreklikke på et hvilket som helst objekt.Højreklik to gange for at medtage et ekskluderet objekt i analysen igen. For at gemme de kommentarer, der er foretaget under storyboard-kommentaren, skal du klikke på knappen Gem. Venstreklik én gang på et objekt på storyboardet for at åbne et nyt vindue, der viser detaljerede tidsserieoplysninger om det pågældende objekt.For manuelt at kommentere dødstiderne skal du venstreklikke på den nederste bjælke på det punkt, der svarer til dødstidspunktet. Brug mellemrumstasten og højre eller venstre pil på tastaturet til at bevæge dig gennem tidsrammerne, eller klik direkte på linjen inden for den ønskede tidsramme. Anmærk manuelt sammentræknings- og udvidelsesbegivenhederne ved at højreklikke på den nederste bjælke inden for den ønskede tidsramme.Se overlevelseskurverne på venstre side og spredningsplottet, der sammenligner tidspunktet for kraftig bevægelsesophør med dødstidspunktet for hver enkelt person på højre side af storyboardet. For at generere dødstiderne for et eksperiment skal du i Worm-browseren vælge datafiler, dødstider og derefter klikke på generer dødstider for det aktuelle eksperiment. Effekten af manuel datavalidering på overlevelseskurver er vist her.De oprindelige overlevelseskurver, der blev produceret før storyboard-annotation, blev forvrænget af forkert inkludering af ikke-ormobjekterne. Efter at have ekskluderet objekter uden orm under manuel storyboard-annotering, viste de resulterende overlevelseskurver signifikant forbedret opløsning. Den grafiske repræsentation viser den estimerede gennemsnitlige resterende levetid på tværs af forskellige trin i analysen efter billedanskaffelse og dens korrelation med ormens levetid.Det blev konstateret, at manuel annotering af dødstider i adfærdsmæssig aldringsanalyse er særlig vigtig i længerelevende orme. I dette tilfælde dem, der udsættes for de laveste koncentrationer af okser. Afslutningsvis er levetidsmaskinens automatiserede estimering af dødstid tilstrækkelig nøjagtig til overlevelsesanalyser.Mens adfærdsmæssige aldringsanalyser kan drage fordel af manuel annotering.

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 ...