The C. elegans Observatory: High-throughput exploration of behavioral aging

Abstract

Organisms undergo a variety of characteristic changes as they age, suggesting a substantial commonality in the mechanistic basis of aging. Experiments in model organisms have revealed a variety of cellular systems that impact lifespan, but technical challenges have prevented a comprehensive evaluation of how these components impact the trajectory of aging, and many components likely remain undiscovered. To facilitate the deeper exploration of aging trajectories at sufficient scale to enable primary screening, we have created the C. elegans Observatory, an automated system for monitoring the behavior of group-housed C. elegans throughout their lifespans. One Observatory consists of a set of computers running custom software to control an incubator containing custom imaging and motion-control hardware. In its standard configuration, the Observatory cycles through trays of standard 6 cm plates, running four assays per day on up to 576 plates per incubator. High-speed image processing captures a range of behavioral metrics including movement speed and stimulus-induced turning, and a data processing pipeline continuously computes summary statistics. The Observatory software includes a web interface that allows the user to input metadata and to view graphs of the trajectory of behavioral aging as the experiment unfolds. Compared to manual use of a plate-based C. elegans tracker, the Observatory reduces effort required by close to two orders of magnitude. Within the Observatory, reducing function of known lifespan genes with RNA interference (RNAi) gives the expected phenotypic changes, including extended motility in daf-2(RNAi) and progeria in hsf-1(RNAi). Lifespans scored manually from worms raised in conventional conditions match those scored from images captured by the Observatory. We have used the Observatory for a small candidate-gene screen and identified an extended youthful vigor phenotype for tank-1(RNAi) and a progeric phenotype for cdc-42(RNAi). By utilizing the Observatory, it is now feasible to conduct whole-genome screens for an aging-trajectory phenotype, thus greatly increasing our ability to discover and analyze new components of the aging program.

The complete cell atlas of an aging multicellular organism

“…Healthspan was measured as the decline of movement over time at 25°C with live OP50 or HT115 E. coli . It was recorded using an automated version of the Multi-Worm Tracker (MWT) computer vision system (Kerr et al 2022), with images acquired using PixeLINK PL-D725MU cameras (5 megapixels, configured to run at 50 frames per second) with Navitar NMV-25M1 lenses (25 mm focal length, F 1.4 aperture). Worms were segmented using the core Multi-Worm Tracker algorithms available from https://github.com/ichoran/mwt-core.git, and analyzed using Choreography from https://github.com/ichoran/choreography.git (Swierczek et al, 2011).…”

“…All results are reported in Table S15. Lifespans measured in parallel manually or through automated imaging provided the same results (Rex Kerr et al, 2022).…”

“…We used RNA interference (RNAi) to turn down their expression starting from early adulthood and systematically recorded animal movement rates and survival over time. To do this, we adapted a real-time computer vision "Worm Tracker" (Swierczek et al, 2011) to an automated, high throughput format (Kerr et al 2022).…”

“…0 on the Y axis corresponds to the late L4 stage. A publication dedicated to the high-throughput automated multi worm tracker is in preparation (Kerr et al 2022).…”