Image-based assays are a powerful and convenient method for capturing nematode phenotypes and drug responses. Computational image analysis can be used to extract a range of quantitative readouts from simple movement scores to complex, multidimensional behavioural profiles.

Several methods are in use to acquire images or video for analysis, from standard laboratory microscopes to custom, robotic worm-tracking cameras and microfluidic imaging chambers. The choice of equipment often involves a trade-off of information content against throughput.

With Andy Fraser, at the University of Toronto, I have developed an imaging platform that can capture high-content image data at exceptionally high-throughput.


Automated microscopy is a common choice for imaging C. elegans in drug-response or phenotypic screens. The equipment is widely available and well-suited to microplate format. We have successfully used this approach to characterize worm drug responses and applied our findings to pilot-scale drug screens. However, microscopy has two important drawbacks that limit throughput and flexibility:

  1. Uneven illumination of microplate wells and the transparency of C. elegans cause poor image contrast, which can complicate image analysis. Animals at the periphery of wells can be indistinct from the background and may be subject to optical distortion (Figure 1A)
  2. Microplate wells must be imaged serially, one at a time, reducing throughput to several minutes per plate. High-throughput tracking of worm locomotion in microplate format is not possible, since worms change position considerably in the several minutes it takes to make a complete pass of the plate and return to a particular well (Figure 1B)



Our solution

We have developed a solution that addresses both of these imaging challenges by:

  1. Generating high contrast images of transparent specimens in liquid media, simplifying image processing and object analysis (Figure 2A)
  2. Capturing all microplate wells in a single image (Figure 2B), improving throughput by several orders of magnitude and enabling video tracking for high-content behavioural analysis or genetic screening.



We are applying this system to large-scale screening for drug candidates in C. elegans using simple movement assays. For an example of a pilot-scale screen to identify muscarinic modulators, see here.

Because our technology captures multiple wells in parallel, it is possible to apply object tracking to animals in all wells, under different conditons, at the same time. This is demonstrated in the following video where tracking enables us generate movement scores for individual worms treated with aldicarb. This has exciting applications in identifying individuals with phenotypes of interest in genetic screens.  Such screens will be valuable for identification of drug targets by isolation of resistant mutants, for example.

In addition to movement scores, our platform can be applied to a range of common image-based assays, including egg laying, brood count and morphometric readouts.

Finally, benefits of this technology are not limited to nematodes; we can generate high-contrast images of any transparent biological samples. This example shows mammalian fibroblasts in a “wound healing” assay, where a scratch is made in a layer of growing cells, in order to measure the ability of cells to migrate to and repopulate the cleared area.


We are still exploring the versatility of this platform and we are always interested in new ideas. We are particularly interested in applications in the pharmaceutical and agrochemical industries: please get in touch if interested!