# Cell pelotons: a model of early evolutionary cell sorting, with   application to slime mold D. discoideum

**Authors:** Hugh Trenchard

arXiv: 1902.07601 · 2019-02-21

## TL;DR

This paper introduces a theoretical model inspired by bicycle peloton dynamics to explain early evolutionary cell sorting in slime molds, demonstrating how energy constraints influence cell differentiation and spatial organization within aggregates.

## Contribution

It presents a novel energy-based model of cell sorting, applying principles of collective self-organization to biological systems like slime molds, with a computer simulation illustrating cell differentiation due to energy depletion.

## Key findings

- Cell sorting depends on energy-expenditure parameters.
- Heterogeneous cells differentiate into sub-groups.
- Simulation shows weak cells shuffle backward within the aggregate.

## Abstract

A theoretical model is presented for early evolutionary cell sorting within cellular aggregates. The model involves an energy-saving mechanism and principles of collective self-organization analogous to those observed in bicycle pelotons (groups of cyclists). The theoretical framework is applied to slime-mold slugs (Dictyostelium discoideum) and incorporated into a computer simulation which demonstrates principally the sorting of cells between the anterior and posterior slug regions. The simulation relies on an existing simulation of bicycle peloton dynamics which is modified to incorporate a limited range of cell metabolic capacities among heterogeneous cells, along with a tunable energy-expenditure parameter, referred to as an 'output-level' or 'starvation-level' to reflect diminishing energetic supply, proto-cellular dynamics are modelled for three output phases: 'active', 'suffering', and 'dying or dead.' Adjusting the starvation parameter causes cell differentiation and sorting into sub-groups within the cellular aggregate. Tuning of the starvation parameter demonstrates how weak or expired cells shuffle backward within the cellular aggregate.

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Source: https://tomesphere.com/paper/1902.07601