Studying Protista WBR and Repair Using Physarum polycephalum.

Extract Injury Networks Regeneration Signaling Slime mould

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:
2022
Historique:
entrez: 1 4 2022
pubmed: 2 4 2022
medline: 5 4 2022
Statut: ppublish

Résumé

Physarum polycephalum is a protist slime mould that exhibits a high degree of responsiveness to its environment through a complex network of tubes and cytoskeletal components that coordinate behavior across its unicellular, multinucleated body. Physarum has been used to study decision making, problem solving, and mechanosensation in aneural biological systems. The robust generative and repair capacities of Physarum also enable the study of whole-body regeneration within a relatively simple model system. Here we describe methods for growing, imaging, quantifying, and sampling Physarum that are adapted for investigating regeneration and repair.

Identifiants

pubmed: 35359302
doi: 10.1007/978-1-0716-2172-1_3
pmc: PMC9761523
doi:

Types de publication

Journal Article Research Support, U.S. Gov't, Non-P.H.S. Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

51-67

Informations de copyright

© 2022. The Author(s).

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Auteurs

Megan M Sperry (MM)

Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA.
Department of Biology, Tufts University, Medford, MA, USA.

Nirosha J Murugan (NJ)

Department of Biology, Algoma University, Sault Ste. Marie, ON, Canada. nirosha.murugan@algomau.ca.
Allen Discovery Center at Tufts University, Medford, MA, USA. nirosha.murugan@algomau.ca.

Michael Levin (M)

Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA. michael.levin@tufts.edu.
Department of Biology, Tufts University, Medford, MA, USA. michael.levin@tufts.edu.
Allen Discovery Center at Tufts University, Medford, MA, USA. michael.levin@tufts.edu.

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Classifications MeSH