Different Morphotypes of Physarum polycephalum as Models for Chemotaxis and Locomotion.
Locomotion
Networks
Oscillations
Signaling
Slime mold
Journal
Methods in molecular biology (Clifton, N.J.)
ISSN: 1940-6029
Titre abrégé: Methods Mol Biol
Pays: United States
ID NLM: 9214969
Informations de publication
Date de publication:
2024
2024
Historique:
medline:
16
8
2024
pubmed:
16
8
2024
entrez:
15
8
2024
Statut:
ppublish
Résumé
The acellular slime mold Physarum polycephalum is a large, unicellular amoeba, which, due to its huge size, is well suited to investigate chemotaxis and cellular locomotion. The myxomycete has an astonishing behavioral repertoire and is highly responsive to changes in its environment, which map to changes in its tubular network, internal cytoplasm flow, and cytoskeleton. The behavioral repertoire includes problem-solving, decision-making, and memory. P. polycephalum's chemo- and phototaxis are especially well studied. This chapter describes how to cultivate different morphotypes of P. polycephalum (micro-, meso-, and macroplasmodia). Furthermore, the setup of a chemotaxis experiment and the acquisition and analysis of chemotaxis data is described.
Identifiants
pubmed: 39147971
doi: 10.1007/978-1-0716-4023-4_7
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
69-78Informations de copyright
© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.
Références
Nakagaki T, Yamada H, Tóth Á (2000) Intelligence: maze-solving by an amoeboid organism. Nature 407:470
doi: 10.1038/35035159
pubmed: 11028990
Boussard A, Delescluse J, Pérez-Escudero A, Dussutour A (2019) Memory inception and preservation in slime moulds: the quest for a common mechanism. Philos Trans R Soc London, Ser B 374:20180368
doi: 10.1098/rstb.2018.0368
pubmed: 31006372
pmcid: 6553583
Reid CR, Latty T, Dussutour A, Beekman M (2012) Slime mold uses an externalized spatial “memory” to navigate in complex environments. Proc Natl Acad Sci USA 109:17490–17494. https://doi.org/10.1073/pnas.1215037109
doi: 10.1073/pnas.1215037109
pubmed: 23045640
pmcid: 3491460
Boisseau RP, Vogel D, Dussutour A (2016) Habituation in non-neural organisms: evidence from slime moulds. Proc R Soc London, Ser B 283:20160446
de Lacy Costello BPJ, Adamatzky AI (2013) Assessing the chemotaxis behavior of Physarum polycephalum to a range of simple volatile organic chemicals. Commun Integr Biol 6:e25030. https://doi.org/10.4161/cib.25030
doi: 10.4161/cib.25030
pubmed: 24265848
pmcid: 3829954
Teplov VA, Romanovsky YM, Pavlov DA, Alt W (1997) Auto-oscillatory processes and feedback mechanisms in physarum plasmodium motility. In: Alt W, Deutsch A, Dunn GA (eds) Dynamics of cell and tissue motion. Birkhäuser, Basel, pp 83–92
doi: 10.1007/978-3-0348-8916-2_10
Oettmeier C, Döbereiner H-G (2019) A lumped parameter model of endoplasm flow in Physarum polycephalum explains migration and polarization-induced asymmetry during the onset of locomotion. PLoS One 14:e0215622
doi: 10.1371/journal.pone.0215622
pubmed: 31013306
pmcid: 6478327
Boussard A, Fessel A, Oettmeier C et al (2021) Adaptive behaviour and learning in slime moulds: the role of oscillations. Philosophical Transactions of the Royal Society B: Biological Sciences 376:20190757. https://doi.org/10.1098/rstb.2019.0757
doi: 10.1098/rstb.2019.0757
Satoh H, Ueda T, Kobatake Y (1982) Primary oscillator of contractional rhythm in the plasmodium of Physarum polycephalum: role of mitochondria. Cell Struct Funct 7:275–283
doi: 10.1247/csf.7.275
Satoh H, Ueda T, Kobatake Y (1985) Oscillations in cell shape and size during locomotion and in contractile activities of Physarum polycephalum, Dictyostelium discoideum, Amoeba proteus and macrophages. Exp Cell Res 156:79–90
doi: 10.1016/0014-4827(85)90263-0
pubmed: 3965294
Ueda T, Kobatake Y (1982) Chapter 4—chemotaxis in plasmodia of Physarum polycephalum. In: Aldrich HC, Daniel JW (eds) Cell biology of physarum and didymium. Academic, pp 111–143
doi: 10.1016/B978-0-12-049601-3.50009-2
Beylina SI, Matveyeva NB, Teplov VA (1996) Autonomous motile activity and chemotactical behaviour of physarum polycephalum plasmodium. Biophysics 1:137–143
Durham AC, Ridgway EB (1976) Control of chemotaxis in Physarum polycephalum. J Cell Biol 69:218–223
doi: 10.1083/jcb.69.1.218
pubmed: 943401
Oettmeier C, Lee J, Döbereiner H-G (2018) Form follows function: ultrastructure of different morphotypes of Physarum polycephalum. J Phys D Appl Phys 51:134006. https://doi.org/10.1088/1361-6463/aab147
doi: 10.1088/1361-6463/aab147
Fessel A, Oettmeier C, Bernitt E et al (2012) Physarum polycephalum percolation as a paradigm for topological phase transitions in transportation networks. Phys Rev Lett 109:078103
doi: 10.1103/PhysRevLett.109.078103
pubmed: 23006405
Lee J, Oettmeier C, Döbereiner H-G (2018) A novel growth mode of Physarum polycephalum during starvation. J Phys D Appl Phys 51:244002. https://doi.org/10.1088/1361-6463/aac2b0
doi: 10.1088/1361-6463/aac2b0
Horn BKP, Schunck BG (1981) Determining optical flow. Artif Intell 17:185–203
doi: 10.1016/0004-3702(81)90024-2
Ng L, Solo V (1997) A data-driven method for choosing smoothing parameters in optical flow problems. Proceedings 1997 International Conference on Image Processing, ICIP’97, Santa Barbara, CA., October 26–29, 1997, pp 360–363
Bronštejn IN, Semendyayev KA (2013) Handbook of mathematics, 3rd edn. Springer Science & Business Media