C. elegans is a powerful model organism for biomedical studies. However, the traditional proto- cols, which continue to be broadly used, rely on manual handling, making them labor-intensive and time-consuming. Automation of these processes would greatly benefit long-term studies of C. elegans. Significant progress has been achieved over the past decade in the techniques to study worm’s biology: the introduction of microfluidic approaches for different assay types and the use of machine learning-based algorithms for data processing offer an increase in experimental throughput and a better control of experimental conditions.
We propose here a novel solution for automated developmental and aging studies in C. elegans aggregating these new mentioned methodologies. Our microfluidic-based robotic plat- form is capable to fully automate all the key aspects of C. elegans experimentation, including worm culture, treatment, imaging, as well as data recording and analysis. The unique characteristics of the platform allow high content phenotypic studies on multiple worm populations in parallel that go beyond a simple tracing of growth or survival curves. We present here a panel of standardized bioassays allowing automated: (1) monitoring of C. elegans lifespan, (2) assessment of worm fitness, (3) testing of different stress responses activation and (4) identification of devel- opmental and reproductive phenotypes that can serve as potential predictors of ageing.
To validate the performance of the assays, we mapped the genetic determinants of lifespan in a worm genetic reference population – the recombinant intercross advanced inbred lines (RIAILs). From 85 worm lines, we assessed the life-history traits on-chip, including the development time, growth dynamics, and reproduction. RIAIL lifespans, previously generated with the traditional on-plate method, exhibited large variations, and were positively correlated with developmental time on-chip. Among the top candidates obtained from QTL mapping, novel longevity modulators were identified and validated.