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Approximately half a century ago, Sydney Brenner introduced Caenorhabditis elegans (C. elegans) as a model system to study development and neurobiology, as this small (1 mm in length), transparent nematode worm is easy to manipulate genetically and to maintain in the laboratory1. Today, C. elegans is used to study a wide variety of biological processes including apoptosis, cell signaling, the nature of the cell cycle, gene regulation, metabolism, and ageing2. Furthermore, the cellular and tissue complexity, protein expression patterns and the conservation of disease pathways between C. elegans and higher organisms (80% of worm genes have a human orthologue), linked with the simplicity and cost-effectiveness of cultivation, make it an effective in vivo model organism amenable to high-throughput genetic3,4,5,6,7,8,9,10,11,12,13 and drug14,15,16 screenings. For all these reasons, C. elegans has been employed for the characterization of normal and disease-related molecular pathways; in the field of neurodegeneration, for example, it has enabled the exploration of the effects of ageing on protein aggregation3,4,7,15,17,18, and the characterization of promoters and inhibitors of protein aggregation3,4,5,6,7,14,18.
The overall fitness of the worms, which is an important behavioral parameter to be defined in this type of study, can be measured manually in a variety of ways, such as by counting the number of body bends per minute (BPM)4,6,19, or by measuring the speed of movement20,21,22, as well as by measuring the average lifespan and rates of paralysis. Although manual measurements of body bends and speed of movement have led to many important insights into a variety of molecular pathways and mechanisms3,4,14,19,20,23, manual assays remain currently low-throughput, highly labor-intensive, and time-consuming whilst being prone to errors and to human biases. These issues present considerable challenges in the collection of data with sufficient statistical power to distinguish subtle behavioral changes. This limitation is particularly relevant for drug screening as treatments with potential drug molecules often lead to small phenotypic changes24, therefore requiring the study of large numbers of animals in order to acquire reproducible results. To illustrate this point, recent studies have shown that a high power of detection (POD) is necessary to define with confidence any significant changes in behavior and to limit false positive results25. This has resulted in a strong motivation in the C. elegans community to replace manual counting with reproducible, automated, time- and cost-effective measurements. To meet this demand, several laboratories have recently developed methods for high-sensitivity measurements and accurate worm tracking of larger number of worms22,26,27,28,29,30,31,32,33.
In order to expand further the process of automation to the large cohorts of animals needed for statistically significant measurements, we have recently developed a wide field-of-view nematode tracking platform (WF-NTP)15,34,35,36, which enables the simultaneous investigation of multiple phenotypic readouts on very large worm populations, a key factor in statistically relevant phenotypical detection25. Not only can the WF-NTP currently monitor up to 5,000 animals in parallel, but the phenotypic readouts also include multiple parameters, including the rate and amplitude of body bends, the speed of movement, the fraction of the population that is paralyzed, and the size of the animals. It is therefore readily possible to screen thousands of worms in parallel and to combine the different readouts into a behavioral map to create a multidimensional fingerprint36. The associated open-source software is written in Python, which is also required to operate it and is completely customizable. A graphical user interface (GUI) is also provided to enable users to adopt this technology.
Here, we present a series of protocols that illustrate some of the potential applications of the WF-NTP. In particular, we discuss the administration of compounds, ranging from small molecules to protein therapeutics, and describe how to screen their effects directly over large populations of worms, thus effectively removing the need to sample small sub-populations. The use of the WF-NTP for such a purpose has already brought significant advantages in procedures aimed to design drug discovery programs of Alzheimer's disease (AD)15,34,35 and Parkinson's disease (PD)18 using in vivo data for the assessment of therapeutic candidates35,37.