Alexis Pietak
Pietak worked on computational models of bioelectric tissue and of planarian regeneration. Pietak and Levin built the BioElectric Tissue Simulation Engine (BETSE) to follow ions, voltages and currents in cell collectives1. Pietak later modelled how neurons and a small regulatory network could set the head and tail axis of cut planaria5. Later authors used both lines of work34.
- In the library
- 4 works, named in 12 passages elsewhere
The BETSE simulator
BETSE, described by Pietak and Levin in 2016, treats ions as the basic units of a bioelectrical system. It can include Na+, K+, Cl−, Ca2+, HCO3−, H+ and charged macromolecules1. Other authors then used it. One group ran it on a planarian cut twice into three pieces and extracted membrane potentials and ion concentrations over time4. A review cited it for the role of gap junction coupling and local fields in planarian form2. Another review cited it on self-organization and symmetry-breaking of a morphogenetic field3.
Planarian axis model
The 2019 paper with Bischof, LaPalme, Morokuma and Levin built a regulatory model of anterior-posterior axis regeneration. It assumed that the morphogen Hh is made in neurons and moved away from cell bodies by kinesin. A still unidentified factor, NRF, is moved back toward them5. The authors also proposed a transient wound signal, possibly reactive oxygen species, that controls the timing of head or tail change6.
Use by later authors
Later papers on bioelectric tissue cited Pietak's simulation work. A 2020 HCN2 paper cited it for the view that cell-cell connections across tissues produce non-intuitive voltage patterns, which are best understood through simulation7. Levin's 2022 paper cited the work for coupled cells holding large voltage patterns steady against perturbation8.
BETSE can consider ions relevant to most living systems: Na+, K+, Cl−, Ca2+, HCO3−, H+, and charged macromolecules, such as proteins (X−).
Pietak A, Levin M, 2016 · Exploring Instructive Physiological Signaling with the Bioelectric Tissue… · open at passage 12Bioelectric coupling via intracellular channels (gap junctions) and local field potentials between cells (Pietak and Levin, 2016) underlie changes in physiological networks
Tyler SEB, 2017 · Nature's Electric Potential: A Systematic Review of the Role of Bioelectricity… · open at passage 11One of the key concepts computational studies seek to illuminate is the idea of self-organization of a morphogenetic field, or “symmetry-breaking” of an initially homogeneous state (Pietak and Levin, 2016).
Silver BB, Nelson CM, 2018 · The Bioelectric Code: Reprogramming Cancer and Aging From the Interface of… · open at passage 40We use the BioElectric Tissue Simulation Engine (BETSE) (Pietak and Levin, 2016) to simulate the planarian regeneration process under a simple two-cut intervention (Pietak and Levin, 2017).
Moore DG, Valentini G, Walker SI, Levin M, 2018 · Inform: Efficient Information-Theoretic Analysis of Collective Behaviors · open at passage 32The morphogen Hh is assumed to be produced in neurons, and to be moved away from neural cell bodies by kinesin [64, 65], while a presently unidentified substance, Notum Regulating Factor (NRF)
Pietak A, Bischof J, LaPalme J, Morokuma J, Levin M, 2019 · Neural control of body-plan axis in regenerating planaria · open at passage 12which is proposed to be a molecular substance transiently produced by cells at the time of wounding, and to modulate the ability for head or tail probabilities to change.
Pietak A, Bischof J, LaPalme J, Morokuma J, Levin M, 2019 · Neural control of body-plan axis in regenerating planaria · open at passage 22Cell-cell connections across tissues can drive highly complex, non-intuitive, spatiotemporal changes in membrane voltage patterns that are best understood via simulations
Pai VP, Cervera J, Mafe S, Willocq V, Lederer EK, Levin M, 2020 · HCN2 Channel-Induced Rescue of Brain Teratogenesis via Local and Long-Range… · open at passage 26coupled oscillators possess emergent dynamics that now maintain large, spatial patterns of Vmem against perturbation with greater stability (Pietak and Levin, 2017, 2018;
Levin M, 2022 · Technological Approach to Mind Everywhere: An Experimentally-Grounded Framework… · open at passage 82
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