Workflow and performance of the WormToolbox. (a) Starting from a bright field image we (b) remove variations in illumination and separate objects from background. (c) We create a worm model from non-touching training worms and (d) untangle individual worms from clusters and debris using the model. Each worm is given a uniquely colored outline. (e) Automated detection of adult worms in the presence of eggs and progeny in images from a 384-well plate, each well containing a predetermined percentage of adults, and counted with or without untangling. The number of adult worms counted by image analysis is plotted against the known number of adult worms sorted into each well. Error bars, s.d. (n = 16 images).(f) The images show the morphology of E. faecalis-infected worms without (top; worms are dead) and with (bottom; worms are alive) treatement with Ampicillin. (h) Automated viability scoring based on shape and texture measurements from individual worms compared to visual scoring of positive (Ampicillin treated) and negative (untreated) control wells. Scale bars, 1mm.

Scoring fluorescence signal distribution with the WormToolbox. (a) The images show clec-60::GFP expression (green) in wild type worms (top) and in pmk-1(km25) mutants (bottom). The pharynx is marked with myo-2::mCherry (red). (b) Automated worm detection and straightening of the worms in (a) enables feature measurements in relation to (c) a low-resolution worm atlas. (d) Comparison of standard deviation of GFP fluorescence intensity in transversal T_2 of 6 of worms in 48 wells containing either positive (pmk-1 mutant, blue stars) or negative controls (wild type, magenta diamonds).