Evolution of multicellularity by collective integration of spatial information

Abstract

10At the origin of multicellularity, cells may have evolved aggregation in 11 response to predation, for functional specialisation or to allow large-scale 12 integration of environmental cues. These group-level properties emerged 13 from the interactions between cells in a group, and determined the selection 14 pressures experienced by these cells. 15 We investigate the evolution of multicellularity with an evolutionary 16 model where cells search for resources by chemotaxis in a shallow, noisy 17 gradient. Cells can evolve their adhesion to others in a periodically chang-18 ing environment, where a cell's fitness solely depends on its distance from 19 the gradient source. 20 We show that multicellular aggregates evolve because they perform chemo-21 taxis more efficiently than single cells. Only when the environment changes 22 too frequently, a unicellular state evolves which relies on cell dispersal. Both 23 strategies prevent the invasion of the other through interference competition, 24 creating evolutionary bi-stability. Therefore, collective behaviour can be an 25 emergent selective driver for undifferentiated multicellularity. 26 1 1 Introduction 27The evolution of multicellularity is a major transition in individuality, from au-28 tonomously replicating cells to groups of interdependent cells forming a higher-29 level of organisation [1, 2]. It has evolved independently several times across the 30 tree of life [3, 4]. Comparative genomics suggests [5], and experimental evolution 31 confirms [6, 7] that the increase of cell-cell adhesion drives the early evolution 32 of (undifferentiated) multicellularity. Increased cell adhesion may be temporally 33 limited and/or may be triggered by environmental changes (e.g. in Dictyostelids 34 and Myxobacteria [8, 9]). Moreover, multicellular organisation may come about 35 either by aggregation of genetically distinct cells or by incomplete separation after 36 cell division [8, 10]. 37The genetic toolkit and the cellular components that allow for multicellularity 38 -including adhesion proteins -pre-date multicellular species and are found in 39 their unicellular relatives [8,[11][12][13]. Aggregates of cells can organise themselves 40 by exploiting these old components in the new multicellular context, allowing 41 them to perform novel functions (or to perform old functions in novel ways) that 42 may confer some competitive advantage over single cells. Greater complexity can 43 later evolve by coordinating the division of tasks between different cell lineages 44 of the same organism (e.g. in the soma-germline division of labour), giving rise 45 to embryonic development. Nevertheless, the properties of early multicellular 46 organisms are defined by self-organised aggregate cell dynamics, and the space of 47 possible multicellular outcomes and emergent functions resulting from such self-48 organisation seems large -even with limited differential adhesion and signalling 49 between cells. However, the evolution of emergent functions as a consequence of 50 ad...

Evolution of multicellularity by collective integration of spatial information

“…Parameter values are motivated throughout this section, and summarised in Table 1 . The custom software used for the simulations and to generate the figures is available at Colizzi and Vroomans, 2020 .…”

Towards evolutionary predictions: current promises and challenges

“…Examples of multi-scale models are: the coupling of large gene regulatory networks to tissue-level patterning, which have been used for hindcasting the order of evolutionary innovations in bilateral animals (Vroomans et al 2016), and estimating the likelihood that mutations increase morphological complexity (Hagolani et al 2021); models of genome evolution (Cuypers & Hogeweg 2012), which predict that genomically complex ancestors primarily adapted through gene loss during major radiation events (Deutekom et al 2019); and agent based models with rudimentary genomes, which predict emergent selective forces that can drive major evolutionary transitions (Colizzi et al 2020).…”

Social Conflicts in <em>Dictyostelium discoideum</em> : A Matter of Scales

“…They yielded important insights, for instance, on how cells sort within tissues (Beatrici and Brunnet, 2011;Steinberg, 2007), and in particular on differentiation in Dictyostelium (Maree and Hogeweg, 2001). Although they remain simplified representations, these models are easier to interface with cell-level observations and can provide explicit descriptions of the origin of biases in aggregate composition and in spatial distribution of cells, as well as of the evolution of collective functionality (Colizzi et al, 2020;Garcia, Doulcier, et al, 2015;Gestel and Nowak, 2016;Guttal and Couzin, 2010;Joshi et al, 2017;Staps et al, 2019). Their integration into general evolutionary frameworks is, however, less straightforward.…”