Development of cell differentiation in the transition to multicellularity: a dynamical modeling approach

Abstract

Multicellularity has emerged and continues to emerge in a variety of lineages and under diverse environmental conditions. In order to attain individuality and integration, multicellular organisms must exhibit spatial cell differentiation, which in turn allows cell aggregates to robustly generate traits and behaviors at the multicellular level. Nevertheless, the mechanisms that may lead to the development of cellular differentiation and patterning in emerging multicellular organisms remain unclear. We briefly review two conceptual frameworks that have addressed this issue: the cooperation-defection framework and the dynamical patterning modules (DPMs) framework. Then, situating ourselves in the DPM formalism first put forward by S. A. Newman and collaborators, we state a hypothesis for cell differentiation and arrangement in cellular masses of emerging multicellular organisms. Our hypothesis is based on the role of the generic cell-to-cell communication and adhesion patterning mechanisms, which are two fundamental mechanisms for the evolution of multicellularity, and whose molecules seem to be well-conserved in extant multicellular organisms and their unicellular relatives. We review some fundamental ideas underlying this hypothesis and contrast them with empirical and theoretical evidence currently available. Next, we use a mathematical model to illustrate how the mechanisms and assumptions considered in the hypothesis we postulate may render stereotypical arrangements of differentiated cells in an emerging cellular aggregate and may contribute to the variation and recreation of multicellular phenotypes. Finally, we discuss the potential implications of our approach and compare them to those entailed by the cooperation-defection framework in the study of cell differentiation in the transition to multicellularity.

Cell‐fate determination in Myxococcus xanthus development: Network dynamics and novel predictions

“…Moreover, dynamic models provide a tool for identifying common properties and particularities in the developmental processes in different systems. In particular, they can provide clues about generic aspects of cell-fate determination in the transition to multicellularity (Arias Del Angel et al, 2016; Duran-Nebreda, Montañez, Bonforti, & Solé, 2016;Furusawa & Kaneko, 2002;Mora Van Cauwelaert, Del Angel, Antonio, Benítez, & Azpeitia, 2015). Implementation of dynamic models for the study of cellular differentiation has been mostly limited to eukaryotic model organisms developing through a zygotic or "staying-together" mechanism (Albert & Othmer, 2003;Benítez et al, 2008;Jaeger & Reinitz, 2012).…”

Games of multicellularity

“…These include increase in genetic complexity, cell differentiation, cell adhesion and cell-to-cell communication (Rokas, 2008). Division of labor, efficient dispersal, improved metabolic efficiency, and limiting interaction with non-cooperative individuals have been suggested as advantageous traits offered by multicellularity (Michod and Roze, 2001;Michod, 2007;Bonner, 1998;Pfeiffer et al, 2001;Pfeiffer and Bonhoeffer, 2003;Kirk, 2005;Mora Van Cauwelaert et al, 2015)(see also Grosberg and Strathmann (2007) and references therein. )…”

BioCAE: A New Strategy of Complex Biological Systems for Biofabrication of Tissues and Organs

“…Multi-scale models are usually based on the continuum modeling and/or MAS approaches which can be decomposed into N single-scale mathematical models and several physical processes. Various works have already been done which apply many multi-scale methods in several biological systems [14,[17][18][19][20][21][22][36][37][38][39][40][41][42][43][44][45][46][47][48][49]: a good review is proposed in Table 1.…”

“…These diverse levels coupling intra and interscale interactions make a biological system extremely complex, requiring advanced mathematical and computational models for the integration of the different scales [15,16]. There is a range of multi-scale modelling methods that could potentially be employed in systems biology [17][18][19][20][21][22] and consequently in the biofabrication of tissues and organs. Then, in the next section, we will describe some multi-scale approaches and/or software which may be part of the BioCAE and that are playing or will play important roles in multi-scale problems in systems biology and tissues biofabricated, thereby preventing a large amount of trial and error experiments in laboratories.…”

“…Modelling and simulation of diffusion process in tissue spheroids CFD [14] Agent-based virtual tissue simulations CC3D [17] Cell compressibility, motility and contact inhibition on the growth of tumor cell clusters CC3D [18] Multiscale modeling of the early CD8 T cell immune response in lymph nodes CC3D [19] Multi-scale knowledge on cardiac development CC3D [20] The cell behavior ontology CC3D [21] Cell differentiation in the transition to multicellularity CC3D [22] Dynamics of cell aggregates fusion CC3D [36] A multi-cell model of tumor evolution CC3D [37] Virtual tissues MAS [38] Disruption of blood vessel development CC3D [39] Tumor growth and angiogenesis CC3D [40] Agent-oriented in silico liver (ILS) MAS [41] Model of thrombus development MAS (TS) [42] Three-dimensional multi-scale tumor model MAS [43] A multi-scale model of dendritic cell education and trafficking in the lung CM [44] Multi-scale model of follicular development CM [45] Multi-scale in silico leukocytes model MAS [46] Multi-scale model of organogenesis CM [47] Limitations of spheroids under inappropriate conditions FE [48] Finite lower levels occur at multiple time scales influencing the behavior of the organ. Multi-scale models are usually based on the continuum modeling and/or MAS approaches which can be decomposed into N single-scale mathematical models and several physical processes.…”