Towards Living Technology: Building an Artificial Cell

The emergence of cellular life is one of the major transitions in evolution. It involves the emergence of a well-defined boundary allowing metabolism and genetic information to be part of a well-defined compartment. Theoretical models and experimental data support the idea that simple protocells should be obtainable from a simple systems of coupled reactions dealing with the three previous components. The building of an artificial cell would be a fundamental breakthrough in our understanding of life, its origins and evolution, not to mention a wide array of potential medical and technological applications.

The integrated project PACE will focus on the IT potential of truly artificial cells: addressing both the technical opportunities of programmable artificial cells and an evolutionary roadmap to producing them under the control of current computers. Such artificial cells will be useful because of their distinctness from, rather than similarity to current biology. In this context, the fundamental principles of current biology might not emerge at the very beginning of life: this is the case for example of allometric scaling and stoichiometric inbalances

Understanding the origins of life requires the understanding of a few key events that define the so called major transitions in evolution. One of them is the emergence of cellular structures. Cellularization allowed the emergence of separated compartments (the protocells) able to evolve and maintain a well-defined integrity of all the components. Within the 6th European Framework initiative, we are part of an interdisciplinary group of researchers that will work with the final goal of building a very simple, nano-scale artificial protocell able to self-replicate and evolve under controlled conditions. Our Lab (the COMPLEX SYSTEMS LAB ) will participate at different levels, particularly from the theoretical perspective, modeling protocell dynamics and their possible evolution, the evolution of protocellular networks, with specific emphasis in exploring the role of noise on their behavior. We will also develop several modelling tools allowing to explore the behavior of in silico models of protocell and replicator dynamics. These cells will be much smaller and simpler than modern cells and eventually will allow to create the foundations for information processing in living nano-materials. They can be thought as nano-robots, performing at the molecular scale. They will integrate three basic, microscopic biochemical systems: a container (the lipid membrane), a construction system (the metabolism) and a genetic system involving information-bearing molecules (peptide-DNA) that encode the critical molecular processes and simultaneously participates catalytically in the metabolism. As such, these artificial cells will embody extremely simple versions of biochemical networks, weighting many orders of magnitude less than the smallest modern cells. Given the small numbers of copies intrinsic to the nanoscale involved, it is important to understand the limits imposed by small copy numbers to reliable replication, stability and computation.

Publications of the CSL within the PACE project

Programmable Artificial Cell Evolution WEB SITE

The integrated project PACE will explore the utilization of the simplest technically feasible elementary living units (artificial cells much simpler than current cells) to build evolvable complex information systems. We will create, analyse and investigate the applications of such systems that process information by self-organization starting at molecular scales. The project will also determine whether life-like properties are necessary for computational systems to be fully robust and adaptive and investigate the tension between evolvable living autonomy and programmable utilization. We will explore the collective properties of artificial cells and demonstrate that they are the right material for building nanoscale robot ecologies. The particular molecular systems we will consider will have genetically controlled catalytic reactions, self-assembly of complex supramolecular structures, and energy transduction. Experimental teams within PACE will investigate the stepwise evolution of such complex systems by machine complementation and combinatorial search using a programmable microfluidic interface. This work will provide theoretical and simulation frameworks for understanding emergent computational properties of such systems, and experimental frameworks for programming them by evolutionary exploration of chemical reactions. See the recent feature article on PACE in NEW SCIENTIST 12 February 2005: "ALIVE!" by Bob Holmes .

European Center for Living Technology

The Center will conduct a research, outreach and training program designed to equip a new generation of scientists and engineers to take advantage of programmable artificial cell evolution. The new European Center for Living Technology is to be established in Venice, supported by the European Union, the city of Venice, and the University of Venice Ca Foscari.

Researchers will be invited to the Center to collaborate on PACE and related multidisciplinary projects involving living technology. The Center will also proactively foster informed public discussion of the novel social, safety and ethical issues raised by living technology.

Applicants with appropriate educational background should have an ongoing institutional affiliation and plan to make a definite contribution to the PACE project in collaboration with one or more partners during their visit to the Center.

European Center for Living Technology WEB SITE


Richard Feynmann's visionary talk on Nanotechnology
Nanotechnology site by Ralph Merkle
USA Nanotechnology Initiative
Nanotech at the Foresight Institute
Scientific American Special issue on Nanotechnology

PACE Research Projects at the Complex Systems Lab

Vesicle self-reproduction through Turing-like Instabilities

Using dynamical instabilities inspired in Turing reaction-diffusion models, we have developed a new class of models defining a RD mechanism coupled with a flexible membrane container. Using this approach, we have been able to show that self-replicating protocells including membrane and metabolism can be obtained under physically and chemically reasonable conditions. Within this project, we have developed a software tool named OCCAM . It is a toolset developed within PACE project in order to study in silico the effects of non-uniform osmotic pressure coupled with membrane growth.  Membrane growth under non-uniform osmotic pressure could be the basis for devoloping  new active mechanisms, which control protocell division cycles. Here we present different metabolic scenarios which are able to create non-uniform osmotic pressures and the simulation tools to study the membrane shape evolution in these contexts.

Self-reproducing Synthetic Turing protocells: OCCAM

Nonlinear network replicator dynamics

A first theoretical step when looking at replicator dynamics involves considering nonlinear interactions with no explicit or implicit definition of cell membranes. Models of this type deal with generic features exhibited by replicator dynamics, which have been widely explored over the last decades. We are exploring a new class of replicator dynamics models involving as particular cases hipercyclic organization (see Hypercycles: an introduction) . Both spatial degrees of freedom and host-parasite dynamics are being analysed. By using an explicit definition of genome complexity in terms of small strings of traits, it is possible to follow the evolutionary dynamics of simple models of replicators and to explore how the presence of parasites can either destroy the organization of cycles or instead trigger the emergence of complexity. Since several possible genomes can be simultaneously present, these models actually explore a network of interacting replicators. The models will be extended from the standard deterministic behavior to explicit stochastic implementation. We will extend our results to models where compartents are allowed to be formed, so that sets of replicators can be eventually isolated from each other and new types of interactions, now at the protocellular level, can emerge.

SETH: Spatiotemporal Evolution Through Hypercubes (work in progress)

Noise and self-replicating spatial reaction-diffusion models

The most studied examples of the two types of reaction-diffusion systems are the Meinhardt system (Gierer &Meinhardt 2000) and the diffusive Gray-Scott system (Pearson 1993), respectively. Interesting enough, the replication characteristic is a particularity of the diffusive Gray-Scott model alone, which makes it the ideal model for developmental research - see more details. In such cases, cell-like localized structures grow, deform and make replica of themselves until they occupy the entire space , a theoretical result that also was confirmed experimentally (Lee, McCormick, Swinney & Pearson, 1994). This model was also a target for investigations resulting from the considerable interest of the scientific community in the implications of stochasticity in the evolution of biological and chemical systems. In particular, Lesmes et al. (2003) have carried out the first study of the noise-controlled pattern formation in the Pearson model, with emphasis on the self-replicating patterns. They found that for a specific set of parameters' values, the noise drives the system from the non-multiplicative, stripe-like pattern to the spot-multiplication one . Our results suggest the existence of an interval of optimum noise-intensity values leading to a maximum number of spots, rather than a single optimum value, as suggested by Lesmes and co-workers. Other models from the literature consider hypercycle networks modeling RNA-like polymers catalysing the replication of each other in a cyclic way (Cronhjort & Bloomberg, 1997). They obtain the formation and division of clusters or "spots" and will be also explored.

SELF-REPLICATING SPOTS: dynamics and noise

Nonlinearity in minimal protocellular networks

Abstract models of inimal cells, consisting of a collectively autocatalytic network of reactions enclosed within a membrane, are a first step in modelling simple cellular replicators. An example of them is the so called Ganti's chemoton. The chemoton differs from the minimal autopoiesis model suggested by Varela and co-workers in explicitly including a genetic subsystem. It is also rather more detailed in its analysis of the required chemical dynamics, and aims at supporting self-reproduction by growth and fission even in the minimal version. The chemoton has been presented mainly in papers and books by his creator, Tibor Ganti. Most of this work has been done in terms of formalizing the connection between the different components and how they relate each other. A few attempts to explore the real dynamical behavior have also been conducted, providing evidence for a primitive form of replicating cellular dynamics which exhibits some interesting homeostatic capabilities. We will explore the a whole family of simple chemoton-like models of replicating protocells both involving deterministic and stochastic dynamics. These models will provide useful intuition for further exploration of models with explicit membrane dynamics. Since they contain three coupled components (metabolism, membrane and information molecules) they are actually describable in terms of networks of reactions. We will study their stability, time evolution and adaptation to different external conditions.

Chemoton dynamics (tutorial site)

Evolving lattice cellular aggregates

A previous step before a realistic model of realistic protocell dynamics involves considering toy models of replicating systems forming aggregates in space. One possible approach involves considering dynamics of membrane components and water as happening on a discrete, regular lattice where each site can be occupied by a single molecule or part of it. Interactions include a simplified energy function which takes into account physical interactions through an Ising-like Hamiltonian. Molecular movements in such lattice model are allowed provided that energy is (tipically) minimized. The rules include a Boltzmann probabilistic update that explicitly takes into account the noise. Beyond the modelling of micelle formation and the presence of phase transitions as non-covalent forces are changed, we will also explore evolutionary dynamics of lipid aggregates. By using a given pool of available lipid molecules and other precursors, it is possible to model the emergence of compositional genomes and to observe the selection of whole replicating networks of interacting molecules. The model will be completed by considering in- and out-flow of particles thus mimicking microfluidic environments.


Protocell replication dynamics

Towards the modeling of more realistic protocells, consideration of more accurate physical interactions is required. Some teams within PACE will work towards realistic chemical simulation using molecular dynamics. Our own approach will be a shortcut between simple toy models and full physical implementations. Our main goal is to provide a platform that includes the basic implementation of a physically reasonable picture of micelle formation coupled with evolving dynamics. Beyond the specific properties displayed by the PACE protocell design, there is a whole range of possible scenarios of protocell assembly that could be explored using this framework. We will consider a set of minimal reaction networks coupled to membrane instability that will help understand the role of molecular fluctuations in the evolution of protocells. Using different types of molecular sets we should be able to characterize, at this level, the impact of external and internal noise on protocell evolution and relevant types of evolution towards stable, robust replicating entities. The emergence of parasites, simbiotic relations and other forms of cell-cell interaction will be also explored.

LIPID WORLD: molecular dynamics simulation of lipid aggregates

Reliable computation in protocellular networks

Together with the construction, characterization and analysis of artificial protocells, the PACE project intends to create a new research field of "Living Technology". As part of this initiative, we will contribute by exploring in depth the problem of how computation emerges in both protocells and protocell assemblies. Single protocells should evolve computations allowing them to guarantee reliable replication and eventually to become independent from external fluctuations. Additionally, collective computations might be possible among sets of cells displaying simple forms of communication. Such communication might be possible either through chemical signals or through artificial (computer) interfaces, such as those to be developped within PACE. We want to extend early studies by von Neumann, Cowan and Vinograd on reliable computation towards a rather unknown domain where global computations are performed by collectives or loosely coupled protocells on a given spatial domain. By exploring such simple models we hope to provide insight into the origins of multicellular systems and new views of looking at computation at the nanoscale.


Within the PACE framework, we have started a collaboration with the Barcelona Supercomputing Center, which hosts Marenostrum (right picture), the fifth Largest World's Supercomputer. By using the parallel computation capacities of this system, we expect to model realistic, whole-protocell simulations of self-organizing aggregates containing the three key components of life (membrane, metabolism and information).

By means of Marenostrum we'll be able to study the spectrum of parameter combinations and molecular reactions that allow the transition from non-living to living matter, and provide useful input to ongoing experiments. The large-scale simulation of living protocells also allows a deep exploration of their computational and evolutionary potential, thus providing a powerful framework for future development within the emerging field of living technology.