Modelling the dawn of simple multicellularity : Cooperation, physics and evolutionary branching

L'aparició de la pluricel·lularitat (MC) va definir un esdeveniment evolutiu important en la història de la vida al nostre planeta. Ha tingut lloc diverses vegades dins de grups independents i diferents enfocaments han donat llum als seus orígens. Un enfocament reeixit del problema es basa en models teòrics i computacionals. En aquesta tesi abordem el problema de la MC des d'una perspectiva de sistemes complexos, prestant atenció a les característiques potencials anteriors a l'anomenada MC "simple". Suposant que no hi ha control genètic i, per tant, cap conjunt d'eines moleculars especificades, explorem el potencial generatiu de models mínims de MC encarnat que incorporen l'adhesió, la commutació fenotípica i l'estrès ambiental com a tres factors clau que impulsen l'agregació col·lectiva en conjunts cel·lulars. S'han trobat i analitzat nous tipus d'escenaris de ramificació evolutiva, mecanismes de formació de patrons i organització dels organismes mitjançant diferents aproximacions matemàtiques i de simulació.The emergence of multicellularity (MC) defined a major evolutionary event in the history of life on our planet. It took place several times within independent groups and different approaches have shed light on its origins. One successful approach to the problem is grounded in theoretical and computational models. In this thesis we approach the problem of MC from a complex systems perspective, paying attention to the potential features that predate so-called "simple" MC. Assuming no genetic control and thus no specified molecular toolkit, we explore the generative potential of minimal models of embodied MC that incorporate adhesion, phenotypic switching and environmental stress as three key factors driving collective aggregation in cellular assemblies. Novel types of evolutionary branching scenarios, spatial pattern-forming mechanisms and organismal organization have been found and are analysed using different mathematical and simulation approximations

Unicellular–multicellular evolutionary branching driven by resource limitations

Multicellular life forms have evolved many times on our planet, suggesting that this is a common evolutionary innovation. Multiple advantages have been proposed for the emergence of multicellularity (MC). In this paper, we address the problem of how the first precondition for MC, namely ‘stay together’, might have occurred under spatially limited resources exploited by a population of unicellular agents. Using a minimal model of evolved cell–cell adhesion among growing and dividing cells that exploit a localized resource with a given size, we show that a transition occurs at a critical resource size separating a phase of evolved multicellular aggregates from a phase where unicellularity (UC) is favoured. The two phases are separated by an intermediate domain where both UC and MC can be selected by evolution. This model provides a minimal approach to the early stages that were required to transition from individuality to cohesive groups of cells associated with a physical cooperative effect: when resources are present only in a localized portion of the habitat, MC is a desirable property as it helps cells to keep close to the available local nutrients.This work has been supported by the Spanish Ministry of Economy and Competitiveness, grant no. PID2019-111680GB-I00, an AGAUR FI 2018 grant and the Santa Fe Institute.Peer reviewe

Supplementary material from "Unicellular–multicellular evolutionary branching driven by resource limitations"

Multicellular life forms have evolved many times in our planet, suggesting that this is a common evolutionary innovation. Multiple advantages have been proposed for the emergence of multicellularity (MC). In this paper, we address the problem of how the first precondition for multicellularity, namely ‘stay together’ might have occurred under spatially limited resources exploited by a population of unicellular agents. Using a minimal model of evolved cell–cell adhesion among growing and dividing cells that exploit a localized resource with a given size, we show that a transition occurs at a critical resource size separating a phase of evolved multicellular aggregates from a phase where unicellularity (UC) is favoured. The two phases are separated by an intermediate domain where both UC and MC can be selected by evolution. This model provides a minimal approach to the early stages that were required to transition from individuality to cohesive groups of cells associated with a physical cooperative effect: when resources are present only in a localized portion of the habitat, MC is a desirable property as it helps cells to keep close to the available local nutrients.Supplementary images.-- Pseudocode of the modelPeer reviewe

Modeling endosymbioses : insights and hypotheses from theoretical approaches

Endosymbiotic relationships are pervasive across diverse taxa of life, offering key avenues for eco-evolutionary dynamics. Although a variety of experimental and empirical frameworks have shed light on critical aspects of endosymbiosis, theoretical frameworks (mathematical models) are especially well-suited for certain tasks. Mathematical models can integrate multiple factors to determine the net outcome of endosymbiotic relationships, identify broad patterns that connect endosymbioses with other systems, simplify biological complexity, generate hypotheses for underlying mechanisms, evaluate different hypotheses, identify constraints that limit certain biological interactions, and open new lines of inquiry. This Essay highlights the utility of mathematical models in endosymbiosis research, particularly in generating relevant hypotheses. Despite their limitations, mathematical models can be used to address known unknowns and discover unknown unknowns

Synthese analytique des convertisseurs statiques par la methode de conservation de la puissance instantanee: application a la determination des harmoniques des courants d'entree

SIGLEINIST T 72965 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Spatial self-organization in hybrid models of multicellular adhesion

Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.This work has been supported by the Botín Foundation by Banco Santander through its Santander Universities Global Division, a MINECO fellowship and by the Santa Fe Institut

Computational implementation of a tunable multicellular memory circuit for engineered eukaryotic consortia

Cells are complex machines capable of processing information by means of an entangled network of molecular interactions. A crucial component of these decision-making systems is the presence of memory and this is also a specially relevant target of engineered synthetic systems. A classic example of memory devices is a 1-bit memory element known as the flip-flop. Such system can be in principle designed using a single-cell implementation, but a direct mapping between standard circuit design and a living circuit can be cumbersome. Here we present a novel computational implementation of a 1-bit memory device using a reliable multicellular design able to behave as a set-reset flip-flop that could be implemented in yeast cells. The dynamics of the proposed synthetic circuit is investigated with a mathematical model using biologically-meaningful parameters. The circuit is shown to behave as a flip-flop in a wide range of parameter values. The repression strength for the NOT logics is shown to be crucial to obtain a good flip-flop signal. Our model also shows that the circuit can be externally tuned to achieve different memory states and dynamics, such as persistent and transient memory. We have characterized the parameter domains for robust memory storage and retrieval as well as the corresponding time response dynamics.This work was partially funded by the European Research Council Grant ERC SYNCOM 294294 (JM, RS, AB, NC), by grants of the Botin Foundation, by Banco Santander through its Santander Universities Global Division (RS, JS), and the Santa Fe Institute (RS)

A Synthetic Multicellular Memory Device

Changing environments pose a challenge to living organisms. Cells need to gather and process incoming information, adapting to changes in predictable ways. This requires in particular the presence of memory, which allows different internal states to be stored. Biological memory can be stored by switches that retain information on past and present events. Synthetic biologists have implemented a number of memory devices for biological applications, mostly in single cells. It has been shown that the use of multicellular consortia provides interesting advantages to implement biological circuits. Here we show how to build a synthetic biological memory switch using an eukaryotic consortium. We engineered yeast cells that can communicate and retain memory of changes in the extracellular environment. These cells were able to produce and secrete a pheromone and sense a different pheromone following NOT logic. When the two strains were cocultured, they behaved as a double-negative-feedback motif with memory. In addition, we showed that memory can be effectively changed by the use of external inputs. Further optimization of these modules and addition of other cells could lead to new multicellular circuits that exhibit memory over a broad range of biological inputs.A.U. is a recipient of a La Caixa Fellowship. This work was supported by ERC Advanced Grant 294294 from the EU Seventh Framework Programme (SYNCOM) to R.S. and F.P., the Santa Fe Institute and AGAUR to R.S., and funding from the La Caixa Foundation in collaboration with the Centre per a la Innovació de la Diabetis Infantil Sant Joan de Déu (CIDI). The laboratories of F.P. and R.S. are also supported by Fundación Botín and by Banco Santander through its Santander Universities Global Division. The laboratory of F.P. and E.d.N. is supported by grants from the Spanish Government (BFU2015-64437-P and FEDER to F.P.; BFU2014-52333-P and FEDER to E.d.N.) and the Catalan Government (2014 SGR 599). E.d.N. and F.P. are recipients of an ICREA Acadèmia (Generalitat de Catalunya).Peer reviewe

Spatial self-organization in hybrid models of multicellular adhesion

Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.This work has been supported by the Botín Foundation by Banco Santander through its Santander Universities Global Division, a MINECO fellowship and by the Santa Fe Institut