Ari Winbush1, Matthew Gruner2, Grant W Hennig3, Alexander M van der Linden4. 1. Department of Biology, University of Nevada, Reno, NV 89557, USA. Electronic address: awinbush237@gmail.com. 2. Department of Biology, University of Nevada, Reno, NV 89557, USA. Electronic address: matthew.gruner@gmail.com. 3. Department of Physiology and Cell Biology, University of Nevada, School of Medicine, Reno, NV 89557, USA. Electronic address: grant@medicine.nevada.edu. 4. Department of Biology, University of Nevada, Reno, NV 89557, USA. Electronic address: avanderlinden@unr.edu.
Abstract
BACKGROUND: Locomotor activity is used extensively as a behavioral output to study the underpinnings of circadian rhythms. Recent studies have required a populational approach for the study of circadian rhythmicity in Caenorhabditis elegans locomotion. NEW METHOD: We describe an imaging system for long-term automated recording and analysis of locomotion data of multiple free-crawling C. elegans animals on the surface of an agar plate. We devised image analysis tools for measuring specific features related to movement and shape to identify circadian patterns. RESULTS: We demonstrate the utility of our system by quantifying circadian locomotor rhythms in wild-type and mutant animals induced by temperature cycles. We show that 13 °C:18 °C (12:12h) cycles are sufficient to entrain locomotor activity of wild-type animals, which persist but are rapidly damped during 13 °C free-running conditions. Animals with mutations in tax-2, a cyclic nucleotide-gated (CNG) ion channel, significantly reduce locomotor activity during entrainment and free-running. COMPARISON WITH EXISTING METHOD(S): Current methods for measuring circadian locomotor activity is generally restricted to recording individual swimming animals of C. elegans, which is a distinct form of locomotion from crawling behavior generally observed in the laboratory. Our system works well with up to 20 crawling adult animals, and allows for a detailed analysis of locomotor activity over long periods of time. CONCLUSIONS: Our population-based approach provides a powerful tool for quantification of circadian rhythmicity of C. elegans locomotion, and could allow for a screening system of candidate circadian genes in this model organism.
BACKGROUND: Locomotor activity is used extensively as a behavioral output to study the underpinnings of circadian rhythms. Recent studies have required a populational approach for the study of circadian rhythmicity in Caenorhabditis elegans locomotion. NEW METHOD: We describe an imaging system for long-term automated recording and analysis of locomotion data of multiple free-crawling C. elegans animals on the surface of an agar plate. We devised image analysis tools for measuring specific features related to movement and shape to identify circadian patterns. RESULTS: We demonstrate the utility of our system by quantifying circadian locomotor rhythms in wild-type and mutant animals induced by temperature cycles. We show that 13 °C:18 °C (12:12h) cycles are sufficient to entrain locomotor activity of wild-type animals, which persist but are rapidly damped during 13 °C free-running conditions. Animals with mutations in tax-2, a cyclic nucleotide-gated (CNG) ion channel, significantly reduce locomotor activity during entrainment and free-running. COMPARISON WITH EXISTING METHOD(S): Current methods for measuring circadian locomotor activity is generally restricted to recording individual swimming animals of C. elegans, which is a distinct form of locomotion from crawling behavior generally observed in the laboratory. Our system works well with up to 20 crawling adult animals, and allows for a detailed analysis of locomotor activity over long periods of time. CONCLUSIONS: Our population-based approach provides a powerful tool for quantification of circadian rhythmicity of C. elegans locomotion, and could allow for a screening system of candidate circadian genes in this model organism.
Authors: Maria Olmedo; John S O'Neill; Rachel S Edgar; Utham K Valekunja; Akhilesh B Reddy; Martha Merrow Journal: Proc Natl Acad Sci U S A Date: 2012-11-26 Impact factor: 11.205
Authors: María Eugenia Goya; Andrés Romanowski; Carlos S Caldart; Claire Y Bénard; Diego A Golombek Journal: Proc Natl Acad Sci U S A Date: 2016-11-14 Impact factor: 11.205
Authors: Josue M Regalado; McKenna B Cortez; Jeremy Grubbs; Jared A Link; Alexander van der Linden; Yong Zhang Journal: J Genet Genomics Date: 2017-06-13 Impact factor: 4.275
Authors: Peter B Winter; Renee M Brielmann; Nicholas P Timkovich; Helio T Navarro; Andreia Teixeira-Castro; Richard I Morimoto; Luis A N Amaral Journal: Sci Rep Date: 2016-10-11 Impact factor: 4.379
Authors: Bernard T Drumm; Grant W Hennig; Matthew J Battersby; Erin K Cunningham; Tae Sik Sung; Sean M Ward; Kenton M Sanders; Salah A Baker Journal: J Gen Physiol Date: 2017-06-07 Impact factor: 4.086