O’Brien, T.J., Navarro, E.P., Barroso, C. et al. (4 more authors) (2025) High-throughput behavioural phenotyping of 25 C. elegans disease models including patient-specific mutations. BMC Biology, 23. 281. ISSN: 1741-7007
Abstract
Background Genetic diagnosis is fast and cheap, challenging our capacity to evaluate the functional impact of novel disease-causing variants or identify potential therapeutics. Model organisms including C. elegans present the possibility of systematically modelling genetic diseases, yet robust, high‐throughput methods have been lacking.
Results Here we show that automated multi‐dimensional behaviour tracking can detect phenotypes in 25 new C. elegans disease models spanning homozygous loss‐of‐function alleles and patient‐specific single‐amino‐acid substitutions. We find that homozygous loss‐of‐function (LoF) mutants across diverse genetic pathways (including BORC, FLCN, and FNIP‐2) exhibit strong, readily detectable abnormalities in posture, locomotion, and stimulus responses compared to wild‐type animals. An smc-3 mutant strain—modelled by introducing a patient‐identified missense change—exhibited developmental anomalies and distinct behavioural profiles even though complete loss of SMC‐3 is lethal. In contrast, patient-derived missense mutations in another essential gene, tnpo-2, did not show a strong phenotype initially but it could be “sensitized” chemically (e.g., with aldicarb), potentially facilitating future drug screens.
Conclusions Our findings show that scalable behavioural phenotyping can capture a wide range of mutant effects—from strong to subtle—in patient‐avatar worm lines. We anticipate that this standardized approach will enable systematic drug repurposing for rare genetic disorders as new disease variants are discovered.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © The Author(s) 2025. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Caenorhabditis elegans, High-throughput phenotyping, Multidimensional behaviour, Disease modelling, Patient avatar, Allelic variant |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Molecular and Cellular Biology (Leeds) |
Funding Information: | Funder Grant number Wellcome Trust 304893/Z/23/Z |
Date Deposited: | 30 Sep 2025 14:19 |
Last Modified: | 30 Sep 2025 14:19 |
Status: | Published online |
Publisher: | BMC |
Identification Number: | 10.1186/s12915-025-02368-8 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:232287 |