Behavioural Phenomics

“We use phenotypic screens in the roundworm C. elegans to model rare diseases and discover neuroactive molecules.”

The long-term goal of the Behavioural Phenomics lab is to use molecular level perturbations to modify neural states to understand physiology and treat disease. We work towards this goal by improving imaging and analysis methods to capture quantitative behavioural phenotypes and through experiments with chemical and genetic perturbations that affect those phenotypes. We are developing models of rare genetic diseases using the roundworm C. elegans and performing phenotypic screens to repurpose approved drugs and evolve effective drug combinations. We are also working to expand the neuroactive pharmacopeia by discovering diverse wild and engineered microbes that have effects on worm behaviour. Microbial natural products are underexploited as sources of potential neuroactive molecules and phenotypic screens in C. elegans offer an efficient way to explore this vast chemical space.

The Behavioural Phenomics lab includes scientists with diverse backgrounds from physics and engineering to microbiology and genetics. Our work combines behaviour and wet lab experiments with the development of new imaging technology and open source software.

Find out more at:

Behavioural Phenomics

A worm’s posture can be represented as a point in a compact “shape space”. In this representation, the series of postures a worm adopts while crawling traces out a line (the colour represents the position in the fourth dimension of the shape space). Each ‘bird’s nest’ in the image represents 15 minutes of crawling behaviour for a single worm. Some mutant worms cannot crawl smoothly or spend more time paused and their shape trajectories can be irregular or show spots. By quantitatively comparing worm shapes over time, it is possible to relate mutants to each other and make hypotheses for new genetic relationships.

Selected Publications

McDermott-Rouse A, Minga E, Barlow I, Feriani L, Harlow P, Flemming A, Brown AEX. (2021). Behavioral fingerprints predict insecticide and anthelmintic mode of action. Molecular Systems Biology ISSN: 1744-4292 (accepted)

Hadjieconomou D, King G, Gaspar P, Mineo A, Blackie L, Ameku T, Studd C, de Mendoza A, Diao F, White BH, Brown AEX, Plaçais P, Preat T, Miguel-Aliaga I. (2020). Enteric neurons increase maternal food intake during reproduction. Nature 587, 455–459.

Ding SS, Romenskyy M, Sarkisyan KS, Brown AEX. (2020). Measuring Caenorhabditis elegans Spatial Foraging and Food Intake Using Bioluminescent Bacteria. Genetics, 214 (3), 577-587.

Essmann CL, Martinez-Martinez D, Pryor R, Leung K-Y, Krishnan KB, Lui PP, Greene NDE, Brown AEX, Pawar VM, Srinivasan MA, Cabreiro F. (2020). Mechanical properties measured by Atomic Force Microscopy define new health biomarkers in ageing C. elegans. Nature Communications 11 (1), 1-16.

Feng W, Li Y, Dao P, Aburas J, Islam P, Elbaz B, Kolarzyk A, Brown AEX, Kratsios P. (2020). A terminal selector prevents a Hox transcriptional switch to safeguard motor neuron identity throughout life. eLife 9, e50065

Ding SS, Schumacher LJ, Javer AE, Endres RG, Brown AEX. (2019). Shared behavioral mechanisms underlie C. elegans aggregation and swarming. eLife 8, e43318

Javer A, Currie M, Lee C, Hokanson J, Li K, Martineau CN, Yemini E, Grundy LJ, Li C, Ch’ng Q, Schafer WR, Nollen EAA, Kerr R, Brown AEX. (2018). An open-source platform for analyzing and sharing worm-behavior data. Nature Methods 15:645, doi: 10.1038/s41592-018-0112-1.

Javer A, Ripoll-Sanchez L, Brown AEX. (2018). Powerful and interpretable behavioural features for quantitative phenotyping of C. elegans. Phil Trans R Soc B 373:20170375, doi: 10.1098/rstb.2017.0375.

Chew YL, Grundy LJ, Brown AEX, Beets I, Schafer WR. (2018). Neuropeptides encoded by nlp-49 modulate locomotion, arousal and egg-laying behaviours in C. elegans via the receptor SEB-3. Phil Trans R Soc B 373:20170375, doi: 10.1098/rstb.2017.0368.

Brown AEX, de Bivort BL. (2018). Ethology as a physical science. Nature Physics 14; 653–657, doi: 10.1038/s41567-018-0093-0.

Li K, Javer A, Keaveny EE, Brown AEX. (2017). Recurrent Neural Networks with Interpretable Cells Predict and Classify Worm Behaviour. BioRxiv 222208.

Gomez-Marin A, Stephens GJ, Brown AEX. (2016). Hierarchical compression of C. elegans locomotion reveals phenotypic differences in the organisation of behaviour. Journal of the Royal Society Interface  , doi: 10.1098/rsif.2016.0466.

Schwarz RF, Branicky R, Grundy LJ, Schafer WR, Brown AEX. (2015). Changes in Postural Syntax Characterize Sensory Modulation and Natural Variation of C. elegans Locomotion. PLOS Computational Biology doi: 10.1371/journal.pcbi.1004322.

Brown AE, Yemini EI, Grundy LJ, Jucikas T, Schafer WR. (2013). A dictionary of behavioral motifs reveals clusters of genes affecting caenorhabditis elegans locomotion. PNAS 110(2), 791–796.

Yemini E, Jucikas T, Grundy LJ, Brown AE, Schafer WR. (2013). A database of caenorhabditis elegans behavioral phenotypes. Nature Methods 10(9), 877–879.