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Assessing motor-related phenotypes of Caenorhabditis elegans with the wide field-of-view nematode tracking platform

Nature Protocols volume 15, pages 2071–2106 (2020)Cite this article

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Abstract

Caenorhabditis elegans is a valuable model organism in biomedical research that has led to major discoveries in the fields of neurodegeneration, cancer and aging. Because movement phenotypes are commonly used and represent strong indicators of C. elegans fitness, there is an increasing need to replace manual assessments of worm motility with automated measurements to increase throughput and minimize observer biases. Here, we provide a protocol for the implementation of the improved wide field-of-view nematode tracking platform (WF-NTP), which enables the simultaneous analysis of hundreds of worms with respect to multiple behavioral parameters. The protocol takes only a few hours to complete, excluding the time spent culturing C. elegans, and includes (i) experimental design and preparation of samples, (ii) data recording, (iii) software management with appropriate parameter choices and (iv) post-experimental data analysis. We compare the WF-NTP with other existing worm trackers, including those having high spatial resolution. The main benefits of WF-NTP relate to the high number of worms that can be assessed at the same time on a whole-plate basis and the number of phenotypes that can be screened for simultaneously.

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Fig. 1: Different assays for assessing movement capacity in C. elegans.
Fig. 2: WF-NTP platform and software.
Fig. 3: Measurements of the eccentricity of the particles and of the coilers.
Fig. 4: Speed–bend and cut-off filters improve the accuracy of the WF-NTP analysis.
Fig. 5: Maximal velocity can be analyzed with the WF-NTP.
Fig. 6: Tracking accuracy at different worm densities and time intervals in 9-cm plates.
Fig. 7: Aldicarb and chemotactic assays can be performed with the WF-NTP.
Fig. 8: Experimental workflow and outline.
Fig. 9: Background subtraction example files.
Fig. 10: Examples of color-coded tracks made by the WF-NTP.
Fig. 11: Examples of faulty parameters.
Fig. 12: Guidance images for platform assembly.
Fig. 13: Examples of analyses carried out with the WF-NTP.
Fig. 14: Effect of sample size on statistical significance.

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Data availability

The associated raw data from Figs. 3, 4, 5, 6, 7, 13 and 14 can be accessed via https://doi.org/10.17863/CAM.48480 and demo-data can be accessed via https://doi.org/10.17863/CAM.46983. All other images and movies can be requested via the corresponding authors.

Code availability

The WF-NTP software and plugins can be downloaded from https://github.com/impact27/WF_NTP or https://doi.org/10.5281/zenodo.3630199 (to ensure the version described in this paper: v.3.3.3). We highly recommend downloading the software from GitHub to ensure the latest updates and improvements. The software runs under the license of Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0): https://creativecommons.org/licenses/by-nc-sa/4.0/. The code in this protocol has been peer reviewed.

References

  1. Antoscheckin, I. & Sternberg, P. W. The versatile worm: genetic and genomic resources for Caenorhabditis elegans research. Nat. Rev. Genet. 8, 518–532 (2007).

    Article  CAS  Google Scholar 

  2. Hope, I. A. Background on Caenorhabditis elegans. in C. elegans: A Practical Approach (ed Hope I. A.) 1–15 (Oxford University Press, 1999).

  3. Kaletta, T. & Hengartner, M. O. Finding function in novel targets: C. elegans as a model organism. Nat. Rev. Drug Disco. 5, 387–399 (2006).

    Article  CAS  Google Scholar 

  4. Leung, M. C. K. et al. Caenorhabditis elegans: an emerging model in biomedical and environmental toxicology. Toxicol. Sci. 106, 5–28 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Morley, J. F. et al. The threshold for polyglutamine-expansion protein aggregation and cellular toxicity is dynamic and influenced by aging in Caenorhabditis elegans. Proc. Natl Acad. Sci. USA 99, 10417–10422 (2002).

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  6. Dillin, A. et al. Rates of behavior and aging specified by mitochondrial function during development. Science 298, 2398–2401 (2002).

    Article  CAS  PubMed  Google Scholar 

  7. Lee, S. S. et al. DAF-16 target genes that control C. elegans life-span and metabolism. Science 300, 644–647 (2003).

    Article  CAS  PubMed  Google Scholar 

  8. Nollen, E. A. A. et al. Genome-wide RNA interference screen identifies previously undescribed regulators of polyglutamine aggregation. Proc. Natl Acad. Sci. USA 101, 6403–6408 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Kim, Y. & Sun, H. Functional genomic approach to identify novel genes involved in the regulation of oxidative stress resistance and animal lifespan. Aging Cell 6, 489–503 (2007).

    Article  CAS  PubMed  Google Scholar 

  10. Van Ham, T. J. et al. C. elegans model identifies genetic modifiers of α-synuclein inclusion formation during aging. PLoS Genet. 4, e1000027–11 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  11. Habchi, J. et al. An anticancer drug suppresses the primary nucleation reaction that initiates the production of the toxic Aβ42 aggregates linked with Alzheimer’s disease. Sci. Adv. 2, e1501244 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Javer, A., Ripoll-Sánchez, L. & Brown, A. E. X. Powerful and interpretable behavioral features for quantitative phenotyping of Caenorhabdities elegans. Philos. Trans. R. Soc. Lond. B Biol. Sci. 373, 20170375 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Omura, D. T., Clark, D. A., Samuel, A. D. T. & Horvitz, H. R. Dopamine signaling is essential for precise rates of locomotion by C. elegans. PLoS ONE 7, e38649 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Vidal-Gadea, A. et al. Caenorhabdities elegans selects distinct crawling and swimming gaits via dopamine and serotonin. Proc. Natl Acad. Sci. USA 108, 17504–17509 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Butler, V. J. et al. A consistent muscle activation strategy underlies crawling and swimming in Caenorhabditis elegans. J. R. Soc. Interface 12, 20140963 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. van Ham, T. J. et al. Identification of MOAG-4/SERF as a regulator of age-related proteotoxicity. Cell 142, 601–612 (2010).

    Article  PubMed  CAS  Google Scholar 

  17. Brignull, H. R., Moore, F. E., Tang, S. J. & Morimoto, R. I. Polyglutamine proteins at the pathogenic threshold display neuron-specific aggregation in a pan-neuronal Caenorhabditis elegans model. J. Neurosci. 26, 7597–7606 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Ash, P. E. A. et al. Neurotoxic effects of TDP-43 overexpression in C. elegans. Hum. Mol. Genet. 19, 3206–3218 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Sorrentino, V. et al. Enhancing mitochondrial proteostasis reduces amyloid-β proteotoxicity. Nature 552, 187–193 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Hahm, J.-H. et al. C. elegans maximum velocity correlates with healthspan and is maintained in worms with an insulin receptor mutation. Nat. Commun. 6, 8919 (2015).

    Article  CAS  PubMed  Google Scholar 

  21. Sleigh, J. N. et al. A novel Caenorhabditis elegans allele, smn-1(cb131), mimicking a mild form of spinal muscular atrophy, provides a convenient drug screening platform highlighting new and pre-approved compounds. Hum. Mol. Genet 20, 245–260 (2010).

    Article  PubMed  CAS  Google Scholar 

  22. Briese, M. et al. Deletion of smn-1, the Caenorhabditis elegans ortholog of the spinal muscular atrophy gene, results in locomotor dysfunction and reduced lifespan. Hum. Mol. Genet 18, 97–104 (2009).

    Article  CAS  PubMed  Google Scholar 

  23. Hewtitt, J. E. et al. Muscle strength deficiency and mitochondrial dysfunction in a muscular dystrophy model of Caenorhabditis elegans and its functional response to drugs. Dis. Model. Mech. 11, dmm036137 (2018).

    Article  CAS  Google Scholar 

  24. Wang, J. et al. An ALS-linked mutant SOD1 produces a locomotor defect associated with aggregation and synaptic dysfunction when expressed in neurons of Caenorhabditis elegans. PLoS Genet. 5, e1000350 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Haroon, S. et al. Multiple molecular mechanisms reduce mtDNA disease in C. elegans. Cell Rep. 22, 3115–3125 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Park, E. C. & Horvitz, H. R. Mutations with dominant effects on the behavior and morphology of the nematode Caenorhabditis elegans. Genetics 113, 821–852 (1986).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Syntichaki, P. & Tavernarakis, N. Genetic models of mechanotransduction: the nematode Caenorhabdities elegans. Physiol. Rev. 84, 1097–1153 (2004).

    Article  CAS  PubMed  Google Scholar 

  28. Glenn, C. F. et al. Behavioral deficits during early stages of aging in Caenorhabditis elegans result from locomotory deficits possibly linked to muscle frailty. J. Gerontol. A 59, 1251–1260 (2004).

    Article  Google Scholar 

  29. Fang-Yen, C. et al. Biomechanical analysis of gait adaptation in the nematode Caenorhabditis elegans. Proc. Natl Acad. Sci. USA 107, 323–328 (2010).

    Article  Google Scholar 

  30. Karbowski, J. et al. Conservation rules, their breakdown, and optimality in Caenorhabditis sinusoidal locomotion. J. Theor. Biol. 242, 652–669 (2006).

    Article  PubMed  Google Scholar 

  31. Pierce-Shimomura, J. T. et al. Genetic analysis of crawling and swimming locomotory patterns in C. elegans. Proc. Natl Acad. Sci. USA 105, 20982–20987 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Korta, J., Clark, D. A., Gabel, C. V., Mahadevan, L. & Samuel, A. D. T. Mechanosensation and mechanical load modulate the locomotory gait of swimming C. elegans. J. Exp. Biol. 210, 2383–2389 (2007).

    Article  PubMed  Google Scholar 

  33. Houle, D., Govindaraju, D. R. & Omholt, S. Phenomics: the next challenge. Nat. Rev. Genet. 11, 855–866 (2010).

    Article  CAS  PubMed  Google Scholar 

  34. Swierczek, N. A., Giles, A. C., Rankin, C. H. & Kerr, R. A. High-throughput behavioral analysis in C. elegans. Nat. Methods 8, 592–598 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Perni, M. et al. Massively parallel C. elegans tracking provides multi-dimensional fingerprints for phenotypic discovery. J. Neurosci. Methods 306, 57–67 (2018).

    Article  PubMed  Google Scholar 

  36. Tsibidis, G. D. & Tavernarakis, N. Nemo: a computational tool for analysing nematode locomotion. BMC Neurosci. 8, 86 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Stephens, G., Bialek, W. & Ryu, W. S. Dimensionality and dynamics in the behavior of C. elegans. PLoS Comput. Biol. 4, e1000028 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  38. Brown, A. E. X., Yemini, E. I., Grundy, L. J., Jucikas, T. & Schafer, W. A dictionary of behavioral motifs reveals clusters of genes affecting Caenorhabditis elegans locomotion. Proc. Natl Acad. Sci. USA 110, 791–796 (2013).

    Article  CAS  PubMed  Google Scholar 

  39. Ramot, D., Johnson, B. E., Berry, T. L., Carnell, L. & Goodman, M. B. The parallel worm tracker: a platform for measuring average speed and drug-induced paralysis in nematodes. PLoS ONE 3, e2208 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Wang, S. J. & Wang, Z.-W. Track-A-Worm, an open-source system for quantitative assessment of C. elegans locomotory and bending behavior. PLoS ONE 8, e69653 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Stirman, J. N. et al. Real-time multimodel optical control of neurons and muscles in freely behaving Caenorhandities elegans. Nat. Methods 8, 153–158 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Leifer, A. M., Fang-Yen, C., Hershow, M., Alkema, M. J. & Samuel, A. D. T. Optogenetic manipulation of neural activity in freely moving Caenorhabdities elegans. Nat. Methods 8, 147–152 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Lee, J. & Park., M. An adaptive background subtraction method based on kernel density estimation. Sens. (Basel) 12, 12279–12300 (2012).

    Article  Google Scholar 

  44. Chiu, S.-Y., Chiu, C.-C., Xu, S., S.-D. A background subtraction algorithm in complex environments based on category entropy analysis. Appl. Sci. 8, 885 (2018).

    Article  Google Scholar 

  45. Allan, D. B., Caswell, T. A. & Keim, N. C. Trackpy v0. 2. ACS Nano 8, 5891–5897 (2014).

    Article  CAS  Google Scholar 

  46. Restif, C. et al. CeleST: computer vision software for quantitative analysis of C. elegans swim behavior reveals novel features of locomotion. PLoS Comput. Biol. 17, e1003702 (2014).

    Article  CAS  Google Scholar 

  47. Kwon, N., Pyo, J., Lee, S. J. & Je, J. H. 3-D worm tracker for freely moving C. elegans. PLoS ONE 8, e57484 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Faumont, S. et al. An image-free opto-mechanical system for creating virtual environments and imaging neuronal activity in freely moving Caenorhabditis elegans. PLoS ONE 6, e24666 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Ghosh, R., Mohammadi, A., Kruglyak, L. & Ryu, W. S. Multiparameter behavioral profiling reveals distinct thermal response regimes in Caenorhabditis elegans. BMC Biol. 10, 85 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Buckingham, S. D. & Sattelle, D. B. Fast, automated measurement of nematode swimming (thrashing) without morphometry. BMC Neurosci. 10, 84 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  51. Oh, K. H. & Kim, H. Aldicarb-induced paralysis assay to determine defects in synaptic transmission in Caenorhabdities elgans. Bio. Protoc. 7, e2400 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  52. Mahoney, T. R., Luo, S. & Nonet, M. L. Analysis of synaptic transmission in Caenorhabditis elgans using an aldicarb-sensitivity assay. Nat. Protoc. 1, 1772–1777 (2006).

    Article  CAS  PubMed  Google Scholar 

  53. Porta-de-la-Riva, M., Fontrodona, L., Villanueva, A. & Cerón, J. Basic Caenorhabditis elegans methods: synchronization and observation. J. Vis. Exp. 10, e4019 (2012).

    Google Scholar 

  54. Koopman, M. et al. A screening-based platform for the assessment of cellular respiration in Caenorhabditis elegans. Nat. Protoc. 11, 1798–1816 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Mitchell, D. H., Stiles, J. W., Santelli, J. & Sanadi, D. R. Synchronous growth and aging of Caenorhabditis elegans in the presence of fluorodeoxyuridine. J. Gerontol. 34, 28–36 (1979).

    Article  CAS  PubMed  Google Scholar 

  56. Davies, S. K., Leroi, A. M. & Bundy, J. G. Fluorodeoxyuridine affects the identification of metabolic responses to daf-2 status in Caenorhabditis elegans. Mech. Ageing Dev. 133, 46–49 (2012).

    Article  CAS  PubMed  Google Scholar 

  57. Rooney, J. P. et al. Effects of 5ʹ-fluoro-2-deoxyuridine on mitochondrial biology in Caenorhabditis elegans. Exp. Gerontol. 56, 69–76 (2014).

    Article  CAS  PubMed  Google Scholar 

  58. Gruber, J., Ng, L. F., Poovathingsal, S. K. & Halliwell, B. Deceptively simple but simply deceptive – Caenorhabditis elegans lifespan studies: consideration for aging and antioxidant effects. FEBS Lett. 583, 3377–3387 (2009).

    Article  CAS  PubMed  Google Scholar 

  59. Lüersen, K., Faust, U., Gottschling, D.-C. & Döring, F. Gait-specific adaptation of locomotor activity in response to dietary restriction in Caenorhabditis elegans. J. Exp. Biol. 217, 2480–2488 (2014).

    Article  PubMed  Google Scholar 

  60. van der Goot, A. T. et al. Delaying aging and the aging-associated decline in protein homeostasis by inhibition of tryptophan degradation. Proc. Natl Acad. Sci. USA 109, 14912–14197 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Zhang, G. et al. A Na+/CL−–coupled GABA transporter, GAT-1, from Caenorhabditis elgans: structural and functional features, specific expression in GABA-ergic neurons, and involvement in muscle function. J. Biol. Chem. 280, 2065–2077 (2005).

    Article  CAS  Google Scholar 

  62. Stiernagle, T. Maintenance of C. elegans in WormBook (ed. The C. elegans Research Community) https://doi.org/10.1895/wormbook.1.101.1 (2006).

  63. Fraser, A. et al. Functional genomic analysis of C. elegans chromosome I by systematic RNA interference. Nature 408, 325–330 (2000).

    Article  CAS  PubMed  Google Scholar 

  64. Kamath, R. S. et al. Systematic functional analysis of the C. elegans genome using RNAi. Nature 421, 231–237 (2003).

    Article  CAS  PubMed  Google Scholar 

  65. Faul, F., Erdfelder, E., Lang, A. G. & Buchner, A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav. Res. Methods 39, 175–191 (2007).

    Article  PubMed  Google Scholar 

  66. Rand, J. B. & Johnson, C. D. Genetic pharmacology: interactions between drugs and gene products in Caenorhabditis elegans. Methods Cell Biol. 48, 187–204 (1995).

    Article  CAS  PubMed  Google Scholar 

  67. Burns, A. R. et al. A predictive model for drug bioaccumulation and bioactivity in Caenorhabditis elegans. Nat. Chem. Biol. 6, 549–557 (2010).

    Article  CAS  PubMed  Google Scholar 

  68. Zheng, S.-Q., Ding, A.-J., Li, G.-P., Wu, G.-S. & Luo, H.-R. Drug absorption efficiency in Caenorhabditis elegans delivered by different methods. PLoS ONE 8, e56877 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Partridge, F. A., Tearle, A. W., Gravato-Nobre, M. J., Schafer, W. R. & Hodgkin, J. The C. elegans glycosyltransferase BUS-8 has two distinct and essential roles in epidermal morphogenesis. Dev. Biol. 317, 549–559 (2008).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank the Houtkooper lab for feedback and questions on the WF-NTP software. This project was funded by a European Research Council (ERC) starting grant (281622 PDControl to E.A.A.N.); the Alumni chapter Gooische Groningers, facilitated by the Ubbo Emmius Fonds (to E.A.A.N.); and an Aspasia Fellowship from NWO (015.014.005 to E.A.A.N.).

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Authors and Affiliations

  1. European Research Institute for the Biology of Ageing, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands

    Mandy Koopman, Renée I. Seinstra & Ellen A. A. Nollen

  2. Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, Cambridge, UK

    Quentin Peter, Michele Perni, Michele Vendruscolo, Christopher M. Dobson & Tuomas P. J. Knowles

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  1. Mandy Koopman
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Contributions

M.K. performed most experiments, optimized the final experimental pipeline, adjusted the current WF-NTP software and added new applications and wrote the manuscript together with R.I.S. and E.A.A.N., with contributions from all authors. Q.P. was extensively involved in rewriting, problem solving, editing and optimization of the WF-NTP software. R.I.S. performed experiments on the neurodegenerative strains and helped to verify parameters of the WF-NTP software. M.P., M.V., C.M.D. and T.P.J.K. pioneered the use of the WF-NTP and developed the initial software and platform. M.K., R.I.S. and E.A.A.N. were extensively involved in discussions and interpretations of results.

Corresponding authors

Correspondence to Mandy Koopman or Ellen A. A. Nollen.

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Key references using this protocol

Limbocker, R. et al. Nat. Commun. 10, 225 (2019): https://doi.org/10.1038/s41467-018-07699-5

Sinnige, T. et al. PLoS ONE 14, e0217746 (2019): https://doi.org/10.1371/journal.pone.0217746

Delivoria, D. C. et al. Sci. Adv. 5, eaax5108 (2019): https://doi.org/10.1126/sciadv.aax5108

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Koopman, M., Peter, Q., Seinstra, R.I. et al. Assessing motor-related phenotypes of Caenorhabditis elegans with the wide field-of-view nematode tracking platform. Nat Protoc 15, 2071–2106 (2020). https://doi.org/10.1038/s41596-020-0321-9

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