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The hallmarks of living systems: towards creating artificial cells

N. Amy Yewdall, Alexander F. Mason, Jan C. M. van Hest

Interface Focus · 2018 · Review · CC BY

doi:10.1098/rsfs.2018.0023

Abstract

Despite the astonishing diversity and complexity of living systems, they all share five common hallmarks: compartmentalization, growth and division, information processing, energy transduction and adaptability. In this review, we give not only examples of how cells satisfy these requirements for life and the ways in which it is possible to emulate these characteristics in engineered platforms, but also the gaps that remain to be bridged. The bottom-up synthesis of life-like systems continues to be driven forward by the advent of new technologies, by the discovery of biological phenomena through their transplantation to experimentally simpler constructs and by providing insights into one of the oldest questions posed by mankind, the origin of life on Earth.

Full text

From PubMed Central, U.S. National Library of Medicine, as current on Oct 24, 2026. Paragraph numbers are ours, so an answer can point at one.

Introduction

With billions of years of evolution shaping the diverse living systems present today, we have only begun to comprehend the fascinating complexity and nuances of what makes living systems tick. Despite the huge variation among all forms of life, there are certain common characteristics that enable life to exist, and even thrive. We have defined these five characteristics as: compartmentalization, growth and division, information processing, energy transduction and adaptability (figure 1).

Advances in cellular biology have enriched our understanding of these characteristics and act as inspiration for the creation of systems that mimic life. Feynman's words of ‘what I cannot create, I do not understand’ lie at the heart of artificial cell research, especially concerning bottom-up technologies. Creating complex, multi-component systems uses convergent approaches among the different fields of biophysics, polymer engineering, protein modification, DNA nanotechnology and dynamic covalent chemistry. Here, we describe various ways in which bottom-up technology has addressed the hallmarks of living systems, and also identify the divide between what we can create and what nature can create, providing inspiration for future research.

Compartmentalization

The requirement of life to be compartmentalized is widely accepted as fact. Compartmentalization results in the concentration of reactants and chemical networks, protection of biological components from harsh external environments and the confinement of genetic material. Plasma membranes are semi-permeable and highly functional, allowing cells to interact with their environment, adopt specific shapes, display hierarchical order (organelles) and create temporary gradients to function under out-of-equilibrium conditions. Researchers have become increasingly adept at mimicking these properties using a wide range of materials, including phospholipids, block copolymers, colloids and protein–polymer hybrids. The many examples of these different types of bio-mimetic compartments have been summarized recently in several excellent reviews, and will not be described herein. Instead, this section will focus on the functional aspects of the cell membrane that remain challenging to imitate.

Membrane-active elements at compartment interfaces

The cell membrane, as traditionally described by the fluid mosaic model, is a two-dimensional fluid composed of phospholipids in which membrane proteins are randomly dispersed. In reality, membrane proteins make up a much larger mass fraction of the interface and are organized in tightly controlled ways. For example, 25% of the cross-sectional area in the plasma membrane is proteinaceous, and the ratio of protein to lipid is 76% in the inner mitochondrial membrane. Reconstitution of purified membrane proteins into synthetic compartments results in artificial cells with membranes more akin to the fluid mosaic model than nature, with relatively low protein incorporation yields, and a dearth of complexity, using only one or two proteins. In the following discussion, several solutions to this limitation will be outlined.

One possibility is to use cell-free protein synthesis for the incorporation of membrane proteins. In vitro transcription translation (IVTT) kits have revolutionized the field of synthetic biology by providing a reliable, customizable tool for the expression of proteins in entirely synthetic contexts. The cell-free expression of membrane proteins in the presence of liposomes directly facilitates their incorporation into the membrane in an active conformation. The wide applicability of this technique was demonstrated with the expression of 85 different endogenous Escherichia coli membrane proteins using IVTT in liposomes. Polymer membranes are also compatible with IVTT (figure 2), with the expression of Claudin-2, G-protein-coupled receptors and light-harvesting complex II in polymersomes. However, as both liposomes and polymersomes are static compartments, they lack waste removal or recycling machinery, setting an upper limit to the amount of protein that can be produced before the concentration of inhibitory by-products reaches toxic levels. A direct consequence of this is a limit on the number of different proteins that can be expressed in a single IVTT reaction, as the maximum concentration of active protein decreases for each additional template DNA added to the reaction. This particular issue can be circumvented by performing the IVTT reaction in a microfluidic device that enables by-product removal and reagent supplementation, albeit currently still restricted to the expression of soluble proteins due to the lack of a model membrane.

In order for an artificial cell to be able to effectively mimic the higher order behaviours observed in nature, such as energy transduction and communication, it must incorporate membrane-active elements to couple processes inside the cell to the outside world. As such, the challenges lie not only in increasing the amount and variety of functional membrane-bound entities, but also in developing a better understanding of how they interact with each other, cytosolic elements and the membrane itself.

Membrane complexity

Underlying the structural complexity of the plasma membrane is the arrangement of phospholipids within, exhibiting both lateral (liquid–liquid phase separation, or lipid rafts) and transverse (different inner and outer leaflet) organization. While, at present, engineering the energy-dependent systems responsible for maintaining this complexity is beyond our capabilities, significant advances have been made to mimic this complexity. Inducing lateral phase separation between liquid-ordered and liquid-disordered phases in model membranes has been important in the biophysical elucidation of lipid rafts; however, the mechanisms driving such behaviour in vivo remain poorly understood. So, while it is possible to create lateral phase separation, it is not appropriate to call this organization, as the structures are thermodynamically defined. Transmembrane asymmetry has also been mimicked by inducing heterogeneity in synthetic compartments. The time scale upon which heterogeneity is achieved for liposome-based systems using POPC is 5–6 h, as the small size of phospholipids enables their rapid redistribution. In contrast, polymer-based systems are metastable, and do not appear to change on measured time scales.

The organization of these elements in living cells is dynamic and adaptive, changing to suit a specific function in response to internal and external cues. Artificial cells at present are in thermodynamic equilibrium, and simply cannot mimic this behaviour, as these membrane characteristics are dictated by many regulatory pathways in a dissipative, far-from-equilibrium manner. The generation of (meta)stable complexity in membranes is nevertheless an important milestone, as it provides a set of tools to study biological processes in a controlled way.

Non-spherical morphologies

Many cells adopt non-spherical morphologies to adapt to their environment, or to perform certain functions. Almost every artificial cell model is a sphere, due to the minimization of interfacial energy. Shape transformations can be achieved using polymersomes via a number of different strategies, such as directional hydrophobic interactions and osmotic shock (figure 3). These shape changes are possible because polymer membranes are thermodynamically more stable, and ‘frozen’ in place once the transformative force is removed. It is more difficult to achieve non-spherical morphologies in liposomal systems for this very reason. Cells achieve shape differentiation by using an actin-based cytoskeletal network; this was reconstituted inside liposomes to study the effect of actin networks on membrane dynamics. In a bioinspired approach, an artificial cytoskeleton constructed from DNA origami at the inner surface of liposomes drastically increased the mechanical stability of the system. While both these examples show the effect of a subinterface network, the resulting morphologies were still spheres, thus more control is needed over the shape of the cytoskeletal mimic for shape control using this strategy. Combining lipids and polymers is another avenue only just starting to be explored, and it was recently demonstrated that the combination of lipids and polymers can result in the spontaneous formation of hybrid microtubules with phase-separated leaflets.

Cells also enter into highly controlled shape transformations during mitosis, where cell division is mediated by a network of proteins. Advances towards replicating this behaviour in artificial cells will be expanded upon in a later section.

Mimicking the cytosol

In recent years, it has become increasingly apparent that membrane-free organelles have an important role to play in many cellular processes, especially in bacteria where an open-plan structural architecture governs many internal processes. Such examples found within nature include: chromatin organization with a cell, centrosome formation during division and long-term storage of proteins and genetic material in Balbiani bodies. Their commonality is liquid–liquid phase separation resulting in a condensed phase and a dilute phase. Phase-separated liquid systems have minimum free energy, which enables the maintenance of a concentrated compartment without the constant input of energy by the cell. Complex coacervates are synthetically simple and well-defined systems that can be used to mimic biological condensed phases, as they provide a dense, charged and crowded microenvironment amenable to the investigation and reconstitution of biological processes. For example, purified FtsZ protein polymerization can be induced in these liquid–liquid phase-separated microenvironments. In addition, the IVTT processes were shown to be compatible in two different complex coacervate systems. In one case, the crowded environment improved the rate of transcription, highlighting the capabilities of coacervates to mimic and investigate the effect of crowding on macromolecular processes.

However, the membrane-free nature of complex coacervates inhibits their use in experiments that take place on extended time scales. The main driving force for condensation, electrostatic interactions, also causes complex coacervate droplets to rapidly coalesce and lose structural relevance. To overcome this, coacervates can be stabilized using phospholipids, phosphotungstate polyanionic clusters and a triblock copolymer. This polymer forms a semi-permeable interface which enables the encapsulation of functional macromolecular cargo and indefinitely stabilizes the protocells to coalescence and content mixing (figure 4). Artificial cells based on these stabilized coacervate droplets are an exciting new platform because they offer several bio-mimetic properties in one system, namely a crowded inner phase, a membrane delineating the system from the outside world and a size of the same order as single cells.

One clear difference between complex coacervates and condensed phases found in nature is the lack of regulated assembly. Cells have the ability to exquisitely control the formation and dissipation of these phases in response to internal and external cues such as fluctuations in protein concentrations, yet the formation of complex coacervates currently lacks this regulatory complexity.

Growth and division

The generation of new cells is ultimately derived from growing and replicating existing cells. For this process to occur, compartments must be able to: (i) grow, (ii) deform and finally divide, as well as (iii) regulate all of this in time and space. Within living systems, the lipid bilayer and associated proteins that enable the coordination and control of these processes are pervasive for not only cell division, but also vesicular transport, organelle division and cellular movement. Components involved in cellular growth and division can be reconstituted in vitro, which augments our understanding of their biological functions, and also inspires the synthesis of artificial cells.

Membrane synthesis and growth

The autonomous and heritable synthesis of membranes is not yet achievable for polymersome systems, so, for now, we are restricted to processes found in living systems. The easiest approach to growing membranes is the spontaneous insertion of de novo synthesized components into pre-formed vesicle membranes. Fatty acid vesicles have been heralded as possible pre-biotic compartments where growth and division are driven by the external environment. These vesicles are dynamic and can grow by the spontaneous incorporation of new fatty acid moieties into pre-existing vesicles or even by using a dipeptide catalyst to promote the recruitment of amphiphiles. Primitive homeostasis was also established using fatty acid vesicles, where inhibitory moieties were diluted with subsequent vesicle divisions to restore RNA enzyme activity.

However, for the purposes of creating self-sustaining artificial cells, compartments should be based on more stable membranes, such as those composed of phospholipids as found in most living systems. In addition to increased stability, these membranes can form in a range of pH and salt conditions compatible with most proteins; phospholipid membranes also have unique permeability properties and, most importantly, the ability to be synthesized autonomously. Autonomous membrane synthesis from amphiphilic precursors marks a crucial step towards self-sustained life-like growth. The generation of phospholipids within cells occurs via complex pathways where components and regulation vary between different cell types and organisms. Simplified pathways from purified proteins have been reconstituted in liposome systems. Alternative non-enzymatic approaches have exploited basic lipid chemistry and chemical catalysts to generate phospholipid membranes from amphiphilic precursors. However, in both approaches, the final vesicle lipid composition lacks the diversity of different phospholipids normally present on cell membranes. This has been recently addressed by incorporating purified proteins to synthesize phospholipids that were efficiently incorporated into the membrane, growing both the size and complexity of the vesicles.

For a system to support life-like growth, the process of generating more membrane precursors must be not only internally driven, but also heritable. For this, membrane synthesis and growth must be coupled to the synthesizing machinery, and these proteins must be able to regenerate from genes. Simplified systems using cell-free protein expression have been reconstituted in both liposome and coacervate systems, with limited success. The low efficiency of incorporation of newly synthesized phospholipids into the membranes resulted in a meagre increase in vesicle surface area. This disconnect between an efficient membrane growth and for these pathways to be heritable is the most obvious gap to bridge. However, this will require developments in approaches to mimic the complex cellular information-processing networks, as discussed later.

Mimicking membrane complexity with proteins such as flippases, as outlined above, as well as recreating the precise spatio-temporal regulation required to coordinate cell growth are both ongoing aspirations. Cell growth must also take into account accompanying structural features often associated with the lipid bilayer, such as cell walls or extracellular matrices, as these structures often impart shape and altered compartment permeability.

Altering membrane morphology and division

For life-like behaviour, artificial cells should possess an autonomous and heritable means to alter their membrane morphology, leading to division. Bottom-up technologies have, thus far, exploited many passive processes to generate daughter compartments in a thermodynamically driven manner. Membrane morphologies can be manipulated by altering the external environment of lipid or polymersome compartments, such as by changing salt concentrations, increasing membrane growth and using osmotic shock. Internalized RNA and altering Mg2+ ion concentrations can destabilize fatty acid membrane morphology and induce ‘division’. There are numerous examples where amphipathic helices insert into membranes, causing curvature that results in fission. In fact, protein crowding on the membrane surface was recently shown to be sufficient for spontaneous division. Regulation and spatial coordination of these passive processes will be a difficult endeavour, and, for artificial cells, internally driven processes would be more appealing.

Within living systems, processes for membrane deformation and scission are usually actively directed by proteins, and in vitro reconstitution of these systems in liposomes has not only provided insights into their mechanism of action but has also paved the way to creating out-of-equilibrium cellular organizations within artificial cells. These active mechanisms are powered by protein complexes that consume either adenosine triphosphate (ATP) or guanosine triphosphate (GTP) to generate the forces required for membrane deformation and scission. Constriction of the membrane by mechanoenzyme complexes is one mechanism by which active membrane scission occurs (figure 5), such as with the dynamin/BAR domain proteins and the endosomal sorting complexes required for transport (ESCRT). Dynamins are GTPases that bind to the external surface of lipid membranes to facilitate the formation of vesicles, and their polymerization may be assisted by BAR domain proteins. Dynamin proteins polymerize as helical structures causing the membrane to deform into tubes, and, upon GTP hydrolysis, the protein conformation changes to further constrict the membrane, which leads to fission (figure 5a). By contrast, fission of membranes orchestrated by ESCRT protein complexes occurs when these proteins form dynamic spiral structures on the internal membrane surface, the mechanism of which is still under debate (figure 5b). ESCRT complexes facilitate the fission of membranes that were previously connected by the cytoplasm, such as during cell division, and its localization is mediated via specific protein adaptors. An alternative method of scission was proposed to be driven by friction, where BAR protein complexes form organized scaffolds around the outer surface of membranes to facilitate microtubule-dependent motor proteins pulling off vesicles.

Thus far, membrane fission systems largely consist of purified proteins reconstituted in vitro. These components will eventually have to be internally produced using encapsulated IVTT systems in order for these systems to be heritable. The molecular tool box to sculpt membranes has been expanded to include DNA origami, which can be considered an orthogonal approach to heritable membrane manipulating systems.

The shape of the membrane surrounding cells is often governed by additional structures beyond their phospholipid bilayer. For instance, plant and bacterial cells have an outer cell wall composed of polysaccharides, which help control the final shape of the cells, and prevent them from osmotic shock. FtsZ proteins were shown to not only constrict the lipid membrane but also coordinate peptidoglycan synthesis in bacteria during cytokinesis. The shape of a cell often reflects its particular function, and controlling morphology is a possible means for us to dictate the function of any future artificial cell.

Spatial organization for correct division

Evidence of spatial organization can be found within all levels of biological complexity. Active processes, where energy or matter is exchanged, drive these organized states far from thermodynamic equilibrium. Spatial organization of cellular components is critical for proper cell function and division. To mimic cellular spatial organization, a simplified strategy is to target proteins to membrane surfaces using either histidine-tagged proteins to nickel-nitrilotriacetic acid (NTA) modified surfaces or by covalent targeting of molecules. Unlike processes in nature, these bottom-up technologies cannot self-regulate, but are the first steps towards creating more complex spatial organizations.

Concentration gradients within a cell and polarization ensure not only equal splitting of resources and genetic material into two daughter cells, but also the correct positioning of the protein machinery required for division. Diffusion is unreliable at equally partitioning molecules of low abundance into daughter cells. Nature's solutions involve materials actively segregated into opposite poles of rod-shaped bacteria by scaffold proteins or by evenly distributing plasmid DNA using oscillating proteins ParA/B. This phenomenon has yet to be replicated in synthetic compartments.

Establishing the middle of a cell is of crucial importance for correct division, and the bacterial Min protein system is a striking example where protein oscillations specify a statistical location within the cell. Min proteins oscillate via a reaction–diffusion mechanism on the inner surface of cell membranes, resulting in an average enrichment of MinD at the cell poles. MinD inhibits E. coli FtsZ assembly at the poles of the cell; however, the low MinD distribution at the midcell enables FtsZ to form the Z ring, thereby constricting the membrane and peptidoglycan synthesis initiates at the correct location. Patterns of oscillating Min proteins have been observed in vitro using supported lipid bilayers, as well as in confined geometries. Coupling these oscillations in synthetic compartments with the protein machinery required for membrane deformations described above is still an unmet goal in creating artificial cells capable of division.

Information processing

Information processing encompasses cellular responses to both internal and external signals. Intracellular information processing concerns the primary information carrier molecules made from nucleic acids, such as DNA and RNA, which are heritable. The replication and processing of nucleic acids is often performed by their output, which can either be proteins or segments of nucleic acids, resulting in a feedback system where output can influence the input of the system. These internal information-processing systems must also be responsive to extracellular cues. At the interface of compartments, cells are able to not only sense their surroundings and communicate, but also adapt their behaviour in response to these signals. The signals involved in this extracellular communication can extend beyond nucleic acids to include small molecules, proteins and peptides, and entire vesicles. Engineering a system where a signal triggers feedback that leads to a change in systems behaviour is vital for developing evolvable artificial cells that respond to both environmental and internal changes. The possibilities to mimic cellular information processing are broad and engineered examples exist at all levels of complexity from nucleic acids and proteins, to within protein metabolic pathways, to signal transduction and processing that occurs at the membrane.

Intracellular information processing: reconstituting transcription and translation in an artificial context

In addition to DNA, heritable information carriers in bottom-up technologies can be based on RNA and other functional polymers, such as peptide nucleic acid. These efforts reflect possible pre-biotic scenarios where alternative nucleic acid-like polymers, other than DNA, could have evolved to be the main information carrier of living systems. Through directed evolution, proteins have been developed to recognize and process these polymers, making these synthetic polymers and their protein processors a possible complementary information-processing system for future artificial cells.

For now, synthetic information-processing systems are dominated by DNA-based genetic networks that expand the engineering repertoire of living cells from all branches of life, but, when coupled with IVTT, can provide a means of regulated information processing inside artificial cells. Away from the crowded and complex environs of cellular interiors, complicated genetic circuits and logic gates can be designed to feed back and regulate information processing.

Simple protocells can be created by capturing IVTT inside synthetic compartments, of which there are numerous examples using liposomes and coacervates. These systems mostly involve the expression of single gene products, where output may not necessarily influence input. Genetic circuits with regulatory feedback networks have been created (figure 6), and some in the form of logic gates. These systems are capable of displaying more complex behaviours such as bi-stable switches, tailorable deactivation and oscillations.

An appealing feature of encapsulated IVTT systems is their allure of eventual self-regeneration, in order for these systems to be hereditary. Although there are many components that constitute IVTT systems, the in vitro transcription of ribosomes is a promising first step towards regeneration. A drawback of compartment encapsulation is their stochastic and low efficiency of incorporating all of the cell-free transcription/translation systems, which leads to variable protein production. This must be addressed either using active targeting of components into the compartments or using sorting/amplification of successfully incorporated compartments to enrich the population. Nonetheless, our ability to link phenotype to genotype is a promising means to incorporate evolution elements into future artificial cells.

Extracellular communication: signal processing through the membrane

Beyond the internal processes of individual cells, information processing also encompasses internal responses to external signals that result in altered behaviours. Semi-permeable membranes permit the diffusion of external cues into compartments, and several protocellular membranes are capable of this. Specialized membrane pores can be embedded into the compartment surface to provide additional regulation, such as the selective permeability of nutrients; to generate proton gradients; or even to generate peptide-based pores that conduct ions and bind blockers. Adaptive regulation can be incorporated in these protein-based pores through covalent modification, for example by the attachment of a peptide to OmpF protein to open and close the pore as a function of pH or redox environment. For selective information processing, however, cells use membrane receptors that trigger internal signalling cascades. Replicating these complex cascades in bottom-up protocells is yet to be achieved, but preliminary steps have been taken to embed membrane receptors into artificial surfaces.

Membrane proteins are notoriously difficult to work with, which makes bio-analogous synthetic molecules appealing alternatives that mimic information processing at compartment interfaces. For example, proton-pumping proteins can be mimicked with small molecules, using light-activated donor–acceptor triads and electron shuttles. The behaviour of ion channels can be replicated with synthetic ionophores, hydrophobic molecules that selectively bind and release specific ions. Signal transduction across a membrane resulting in a controlled release in response to a signal has also been achieved (figure 7).

Extracellular communication of protocells with living cells has also been demonstrated. Protocells that synthesized sugar were shown to communicate with live Vibrio cells, and these augmented quorum-sensing scenarios have also been replicated with E. coli. Artificial cells were also shown to translate and communicate with E. coli cells. So far, artificial cells augment the function of living systems, and this can be extended further by using synthetic compartments to capture living cells to form hybrid artificial cell systems.

Communication between two populations of artificial cells has been demonstrated for semi-permeable membrane systems, where signals diffuse and switch on internal cascades in a different protocell population. Thus far, the information-processing systems in artificial cell communication are very simple pathways, with little regulation. Mimicking other forms of life-like communication, such as cell-to-cell vesicles or cell bridges, can be a way to achieve the complexity in regulation comparable to that found in nature, but often these processes require developments in membrane deformation technologies. Again, heritable information carrier systems are key for evolvable artificial cells.

Energy transduction and metabolism

In order to fuel processes necessary for life, cells must be capable of harnessing external sources of energy, such as solar energy from the Sun, and to be able to convert this into fuel sources to drive the biochemical reactions of metabolism. The main cellular energy currencies are ATP and NADH, and also FADH2 and GTP. These energy-rich small molecules are distributed throughout the cell to power metabolic pathways or to create new biomolecules. The ability to be self-sustaining distinguishes living systems from viruses or prions. From an artificial cell perspective, the incorporation of systems that enable the transduction of chemical or light energy into a source of cellular energy in a dissipative manner is an extremely important milestone on the path to a self-sufficient, life-like system.

ATP generation

ATP homeostasis within a cell is critical for the maintenance of out-of-equilibrium states. ATP is synthesized in vivo by a transmembrane protein called FoF1 ATP synthase (ATPase). ATPase is a rotary molecular machine that couples an electromotive force across the membrane into a rotational force, which in turn catalyses the formation of ATP from adenosine diphosphate and phosphate. For synthetic ATP generation, the ATPase must be coupled to a system that generates a transmembrane proton gradient, such as proton pumps localized to membranes. ATPase has been reconstituted in liposomes along with the light-activated proton gate bacteriorhodopsin for light energy to drive ATP synthesis. Other components of the oxidative phosphorylation pathway have also been reconstituted with ATPase, such as cytochrome c oxidase or cytochrome bo3. The chemical approach is to use a synthetic proton-transporting system which, upon photoexcitation, causes photoreduction of a proton shuttle and subsequent proton translocation across the membrane, for example, using a carotenoid–porphyrin–fullerene triad coupled with quinone.

Apart from liposomes, ATP generation has also been demonstrated in more structurally robust systems, such as in hydrogel-like microspheres and polymersomes. The creation of artificial chloroplasts capable of converting light energy into ATP was achieved using cross-linked photosystem II (PSII) protein microspheres covered in a lipid membrane containing ATPase (figure 8). In addition, encapsulated ATP-producing polymersomes in a protein-based foam were able to fix carbon upon illumination to imitate photosynthesis.

There are also a number of polymersome-based examples representing the generation of electromotive force across the membrane, using bacteriorhodopsin and cytochrome c oxidase. However, these were not coupled to ATPase. While ATP is the most attractive energy-rich molecule that can be produced in an artificial cell due to its ubiquity in nature, other small molecules involved in biomolecular energy transduction such as NAD(P)H and H2O2 can also be synthesized; however, these are beyond the scope of the present article.

Metabolic pathways

The metabolism of cells comprises interconnected biochemical pathways that are responsible for the synthesis or breakdown of molecules, as well as energy homeostasis. Processes such as glycolysis, the citric acid cycle and oxidative phosphorylation all result in the production of energy-rich molecules, such as ATP and NADH, which can be used to fuel enzymes to catalyse downstream reactions. These pathways are often complex, involving many enzymes; therefore, it is worthwhile considering simplified pathways for engineering artificial cells. Simplified metabolic networks have been successfully reconstituted in synthetic compartments. These reactions often consist of the downstream pathways fuelled by energy-rich molecules. That is, they lack the energy regeneration requirement for living systems.

Within the examples of diverse living systems, evolution has satisfied the need for metabolism using orthogonal enzymes or entirely different pathways. These examples of convergent evolution can act to inspire the design of artificial cells. One such example is the completely synthetic carbon fixation pathway where 17 enzymes, from nine different organisms, were reconstituted in vitro, leading to improved fixation rates compared with in vivo pathways.

Dissipative systems

Life forms are dynamic, far-from-equilibrium systems that exhibit a constant flux of energy. This is of course accomplished by the integration of the above two capabilities, energy transduction and metabolic pathways (energy utilization), within the same compartment. The concept of dissipative self-assembly is rapidly gaining in importance in the field of supramolecular chemistry, and will likely have a significant impact on many fields including artificial cell research. While the dynamic, dissipative cellular behaviours discussed in this review are currently beyond the scope of our capabilities, there are already a number of studies demonstrating rudimentary dissipative properties that could find use in bio-mimetic applications. For example, polymer vesicles with transient membrane permeability that is dependent on the addition of a fuel could be used as adaptive organelle mimics. Transient fibres and gels fuelled by dimethylsulfate or using a redox-active gelator also bear a resemblance to actin fibres and microtubules. There is huge scope for research in this area, and the advent of more life-like artificial cell systems will surely be coupled with advances in our understanding of dissipative molecular self-assembly.

Motility as an example of adaptability

Adaptability is key for generating artificial cell systems. Motility can be considered a basic form of adaptability, as cells exhibit the ability to respond to their environment and move towards sources of energy, whether that is light (phototaxis) or chemical fuel (chemotaxis). This characteristic is useful for the survival of both unicellular and multi-cellular life, and as such is an interesting behaviour to mimic in bottom-up artificial cells because it involves the integration of two main systems: energy transduction and signal processing. In addition, motility is a property that is easy to observe on the macro-scale, and is a phenomenon that has been mimicked in both purely biological and chemical contexts. For an entity to achieve self-propulsion, it must convert a source of energy into kinetic energy. In addition, it should not do this in a stochastic manner; movement should ideally be directed towards a higher concentration of fuel in order to minimize the expenditure of energy and increase survival. This process thus involves signal sensing (determination of fuel position) and instruction (activation of motile elements to move there).

Movement generation in nature at the microorganism level can occur by several different modes, such as cilia or the bacterial flagellar rotor. The overarching principle is the requirement for asymmetry, or non-reciprocal deformations, as the viscous forces of water dominate at this scale and inertia has a negligible effect. Movement in artificial systems can, of course, be generated through external force fields, for example with magnetite nanoparticles in a magnetic field. However, with external forces at play, an entire population of particles will move as an ensemble. To achieve autonomous behaviour of individual entities, taxis must be generated at the molecule/particle level. Many strategies exist to achieve this, ranging from synthetic molecular motors to bubble evolution on asymmetric inorganic nanoparticles. An example of bubble-based propulsion are the stomatocyte-based nanomotors, where bowl-shaped structures made from polymers can encapsulate cargo, such as platinum nanoparticles or catalase, to induce motility as oxygen gas is produced and forced out of a small aperture to generate a propulsive force (figure 9). These nanomotors could be used to mobilize future artificial cells.

However, these colloidal systems are stochastic in their behaviour, and even when there is an element of chemotaxis, for example with the directed motion of catalase towards hydrogen peroxide, the process is immediate with the catalyst acting directly in a gradient of ‘fuel’. This is in contrast with nature, where the sensing systems and the movement generation systems are separated in space and time. In order to truly mimic adaptability, these two components need to be integrated in the same system, using strategies described earlier in this article to equip artificial cells with the ability to transduce information (functional membranes), compute information (DNA/protein networks) and then generate motion (natural or artificial motors) in a specific direction. Motion generation could be achieved by the coupling of the aforementioned colloidal/molecular motors with artificial cell scaffolds. For example, an inorganic Ni/Ti helical flagellum attached to the surface of liposomes results in magnetically controllable motion. Another approach would be the reconstitution of large, multi-component protein-based motors such as the flagellar motor. However, this complex is one of the largest found in nature, a 45 nm structure assembled from approximately 13 different subunits, and as such has not yet been wholly reconstituted in a model compartment. Certain components have been shown to retain activity, such as PomA/PomB, which are involved in torque generation. These processes mimic basic unicellular motility, whereas in multi-cellular systems, via internal cytoskeletal proteins, generation of polarity and extracellular matrices play a key role in membrane deformation. The amalgamation of an energy transduction system and protein components required for membrane deformation and motility has been demonstrated, where ATP synthases were reconstituted in giant unilamellar vesicles (GUVs) and used to power the fibrillation of cytoskeletal proteins, actin and microtubules. Although shape deformation was not shown for these particular GUVs, it is known that, with the right liposome dimension and flexibility, actin filaments can interact with and deform membranes. Light-activated ATP synthesis was recently demonstrated to induce actin-driven shape deformation in liposomes. These examples are promising first steps towards coordinating different hallmarks to achieve more life-like adaptability.

Motility is only one example of adaptability. Living systems demonstrate an array of adaptable behaviours, such examples range from within single cells, where internal recycling mechanisms can be activated in response to stress, to populations of cells that exhibit collective adaptive behaviour. These are all tantalizing end goals for artificial cell research.

Critical discussion

The creation of an artificial cell that satisfies all the hallmarks of life has not yet been achieved. We have made great progress in mimicking individual characteristics of life, and even combining several hallmarks into bottom-up technologies. However, many examples are in fact a rediscovery of colloidal effects in life-like contexts, and this acts as an important reminder that life indeed is based on core principles of physical chemistry. Our current efforts are thermodynamically limited, and truly life-like behaviours are attainable only with the incorporation of some form of metabolism and energy dissipation. Other key challenges in the pursuit of artificial life include controlling the spatio-temporal distribution of each nanoscale component, as well as addressing the compatibility of current artificial cell platforms to support all of the hallmarks of life. Addressing these is not trivial, and to have the best chance of success in achieving this complex goal, multiple and convergent bio-mimetic, bioinspired and bio-analogous approaches are required to one day create artificial unicellular organisms. As we become more advanced at mimicking the five hallmarks, integrating structures into living systems and moving towards evolvable life, ethical considerations must also be addressed, as the enthusiasm of scientists for this topic can also be met with societal criticism and resistance.

Although the authors acknowledge that simplified synthetic tissue systems have been created and provide a useful platform for investigating cell-to-cell communication, the challenges associated with the bottom-up synthesis of multi-cellular systems, and even higher-order assemblies such as tissues and entire organisms, have not been addressed. Truly mimicking these systems by increasing hierarchical complexity requires exquisite control over communication, extracellular structures and other physiological characteristics beyond the scope of current technology.

Creating artificial living systems requires multi-disciplinary collaboration because a convergence of diverse approaches is needed to progress. Understanding the biophysics of living biological processes is critical for engineering systems from the bottom up. In addition, top-down synthetic biology can provide insights into the essential processes for living systems that will make artificial cells work. Computer science will enable us to engineer in the face of complexity as disciplines including, but not limited to, machine learning and neural networks map the plethora of interactions required for living processes. The five hallmarks of life are a means to simplify the complex, multi-faceted problem of creating artificial life into more tenable goals. When each of these hallmarks is addressed in unison such a system can satisfy NASA's working definition of life: ‘a self-sustaining chemical system capable of Darwinian evolution’.

References 177

  1. 1.

    Mason AF, Thordarson P 2017 Polymersomes as protocellular constructs. J. Polym. Sci. Part A Polym. Chem. 55, 3817–3825. ()

    Not in our library10.1002/pola.28780

  2. 2.

    Elani Y 2016 Construction of membrane-bound artificial cells using microfluidics: a new frontier in bottom-up synthetic biology. Biochem. Soc. Trans. 44, 723–730. ()

    Not in our library10.1042/bst20160052

  3. 3.

    Brea RJ, Hardy MD, Devaraj NK 2015 Towards self-assembled hybrid artificial cells: novel bottom-up approaches to functional synthetic membranes. Chem. Eur. J. 21, 12 564–12 570. ()

    Not in our library10.1002/chem.201501229

  4. 4.

    Buddingh’ BC, van Hest JCM 2017 Artificial cells: synthetic compartments with life-like functionality and adaptivity. Acc. Chem. Res. 50, 769–777. ()

    Not in our library10.1021/acs.accounts.6b00512

  5. 5.

    Spoelstra WK, Deshpande S, Dekker C 2018 Tailoring the appearance: what will synthetic cells look like? Curr. Opin. Biotechnol. 51, 47–56. ()

    Not in our library10.1016/j.copbio.2017.11.005

  6. 6.

    Nicolson GL 2014 The fluid–mosaic model of membrane structure: still relevant to understanding the structure, function and dynamics of biological membranes after more than 40 years. Biochim. Biophys. Acta 1838, 1451–1466. ()

    Not in our library10.1016/j.bbamem.2013.10.019

  7. 7.

    Singer SJ, Nicolson GL 1972 The fluid mosaic model of the structure of cell membranes. Science 175, 720–731. ()

    Not in our library10.1126/science.175.4023.720

  8. 8.

    Dupuy AD, Engelman DM 2008 Protein area occupancy at the center of the red blood cell membrane. Proc. Natl. Acad. Sci. USA 105, 2848–2852. ()

    Not in our library10.1073/pnas.0712379105

  9. 9.

    Habel J et al. 2015 Aquaporin-based biomimetic polymeric membranes: approaches and challenges. Membranes 5, 307–351. ()

    Not in our library10.3390/membranes5030307

  10. 10.

    Althoff T, Davies KM, Schulze S, Joos F, Kühlbrandt W 2012 GRecon: a method for the lipid reconstitution of membrane proteins. Angew. Chem. Int. Ed. 51, 8343–8347. ()

    Not in our library10.1002/anie.201202094

  11. 11.

    Sachse R, Dondapati SK, Fenz SF, Schmidt T, Kubick S 2014 Membrane protein synthesis in cell-free systems: from bio-mimetic systems to bio-membranes. FEBS Lett. 588, 2774–2781. ()

    Not in our library10.1016/j.febslet.2014.06.007

  12. 12.

    Kuruma Y, Ueda T 2015 The PURE system for the cell-free synthesis of membrane proteins. Nat. Protoc. 10, 1328–1344. ()

    Not in our library10.1038/nprot.2015.082

  13. 13.

    Matthies D, Haberstock S, Joos F, Dötsch V, Vonck J, Bernhard F, Meier T 2011 Cell-free expression and assembly of ATP synthase. J. Mol. Biol. 413, 593–603. ()

    Not in our library10.1016/j.jmb.2011.08.055

  14. 14.

    Niwa T et al. 2016 Comprehensive study of liposome-assisted synthesis of membrane proteins using a reconstituted cell-free translation system. Sci. Rep. 5, 18 025 ()

    Not in our library10.1038/srep18025

  15. 15.

    May S, Andreasson-Ochsner M, Fu Z, Low YX, Tan D, de Hoog H-PM, Ritz S, Nallani M, Sinner E-K 2013 In vitro expressed GPCR inserted in polymersome membranes for ligand-binding studies. Angew. Chem. Int. Ed. 52, 749–753. ()

    Not in our library10.1002/anie.201204645

  16. 16.

    Nallani M, Andreasson-Ochsner M, Tan C-WD, Sinner E-K, Wisantoso Y, Geifman-Shochat S, Hunziker W 2011 Proteopolymersomes: in vitro production of a membrane protein in polymersome membranes. Biointerphases 6, 153–157. ()

    Not in our library10.1116/1.3644384

  17. 17.

    de Hoog H-PM, Lin JieRong EM, Banerjee S, Décaillot FM, Nallani M 2014 Conformational antibody binding to a native, cell-free expressed GPCR in block copolymer membranes. PLoS ONE 9, e110847 ()

    Not in our library10.1371/journal.pone.0110847

  18. 18.

    Zapf T, Tan C-WD, Reinelt T, Huber C, Shaohua D, Geifman-Shochat S, Paulsen H, Sinner E-K 2015 Synthesis and functional reconstitution of light-harvesting complex II into polymeric membrane architectures. Angew. Chem. Int. Ed. 54, 14 664–14 668. ()

    Not in our library10.1002/anie.201506304

  19. 19.

    Caschera F, Noireaux V 2014 Integration of biological parts toward the synthesis of a minimal cell. Curr. Opin. Chem. Biol. 22, 85–91. ()

    Not in our library10.1016/j.cbpa.2014.09.028

  20. 20.

    Karzbrun E, Tayar AM, Noireaux V, Bar-Ziv RH 2014 Programmable on-chip DNA compartments as artificial cells. Science 345, 829–832. ()

    Not in our library10.1126/science.1255550

  21. 21.

    Sezgin E, Levental I, Mayor S, Eggeling C 2017 The mystery of membrane organization: composition, regulation and roles of lipid rafts. Nat. Rev. Mol. Cell Biol. 18, 361–374. ()

    Not in our library10.1038/nrm.2017.16

  22. 22.

    Nickels JD, Smith JC, Cheng X 2015 Lateral organization, bilayer asymmetry, and inter-leaflet coupling of biological membranes. Chem. Phys. Lipids 192, 87–99. ()

    Not in our library10.1016/j.chemphyslip.2015.07.012

  23. 23.

    Simons K, Vaz WLC 2004 Model systems, lipid rafts, and cell membranes. Annu. Rev. Biophys. Biomol. Struct. 33, 269–295. ()

    Not in our library10.1146/annurev.biophys.32.110601.141803

  24. 24.

    Peyret A, Ibarboure E, Le Meins J-F, Lecommandoux S 2018 Asymmetric hybrid polymer-lipid giant vesicles as cell membrane mimics. Adv. Sci. 5, 1700453 ()

    Not in our library10.1002/advs.201700453

  25. 25.

    Kamiya K, Kawano R, Osaki T, Akiyoshi K, Takeuchi S 2016 Cell-sized asymmetric lipid vesicles facilitate the investigation of asymmetric membranes. Nat. Chem. 8, 881–889. ()

    Not in our library10.1038/nchem.2537

  26. 26.

    Konishcheva EV, Zhumaev UE, Meier WP 2017 PEO-b-PCL-b-PMOXA triblock copolymers: from synthesis to microscale polymersomes with asymmetric membrane. Macromolecules 50, 1512–1520. ()

    Not in our library10.1021/acs.macromol.6b02743

  27. 27.

    Stoenescu R, Graff A, Meier W 2004 Asymmetric ABC-triblock copolymer membranes induce a directed insertion of membrane proteins. Macromol. Biosci. 4, 930–935. ()

    Not in our library10.1002/mabi.200400065

  28. 28.

    Mason AF, Thordarson P 2016 Polymersomes with asymmetric membranes based on readily accessible di- and triblock copolymers synthesized via SET-LRP. ACS Macro Lett. 5, 1172–1175. ()

    Not in our library10.1021/acsmacrolett.6b00747

  29. 29.

    Wong CK, Mason AF, Stenzel MH, Thordarson P 2017 Formation of non-spherical polymersomes driven by hydrophobic directional aromatic perylene interactions. Nat. Commun. 8, 1240 ()

    Not in our library10.1038/s41467-017-01372-z

  30. 30.

    Abdelmohsen LKEA, Williams DS, Pille J, Ozel SG, Rikken RSM, Wilson DA, van Hest JCM 2016 Formation of well-defined, functional nanotubes via osmotically induced shape transformation of biodegradable polymersomes. J. Am. Chem. Soc. 138, 9353–9356. ()

    Not in our library10.1021/jacs.6b03984

  31. 31.

    Kim KT, Zhu J, Meeuwissen SA, Cornelissen JJLM, Pochan DJ, Nolte RJM, van Hest JCM 2010 Polymersome stomatocytes: controlled shape transformation in polymer vesicles. J. Am. Chem. Soc. 132, 12 522–12 524. ()

    Not in our library10.1021/ja104154t

  32. 32.

    Guevorkian K, Manzi J, Pontani L-L, Brochard-Wyart F, Sykes C 2015 Mechanics of biomimetic liposomes encapsulating an actin shell. Biophys. J. 109, 2471–2479. ()

    Not in our library10.1016/j.bpj.2015.10.050

  33. 33.

    Kurokawa C et al. 2017 DNA cytoskeleton for stabilizing artificial cells. Proc. Natl Acad. Sci. USA 114, 7228–7233. ()

    Not in our library10.1073/pnas.1702208114

  34. 34.

    Lim SK, Wong ASW, de Hoog H-PM, Rangamani P, Parikh AN, Nallani M, Sandin S, Liedberg B 2017 Spontaneous formation of nanometer scale tubular vesicles in aqueous mixtures of lipid and block copolymer amphiphiles. Soft Matter 13, 1107–1115. ()

    Not in our library10.1039/c6sm01753c

  35. 35.

    Shin Y, Brangwynne CP 2017 Liquid phase condensation in cell physiology and disease. Science 357, eaaf4382 ()

    Not in our library10.1126/science.aaf4382

  36. 36.

    Woodruff JB, Hyman AA, Boke E 2017 Organization and function of non-dynamic biomolecular condensates. Trends Biochem. Sci. 43, 81–94. ()

    Not in our library10.1016/j.tibs.2017.11.005

  37. 37.

    Surovtsev I, Jacobs-Wagner C 2018 Subcellular organization: a critical feature of bacterial cell replication. Cell 172, 1271–1293. ()

    Not in our library10.1016/j.cell.2018.01.014

  38. 38.

    Banani SF, Lee HO, Hyman AA, Rosen MK 2017 Biomolecular condensates: organizers of cellular biochemistry. Nat. Rev. Mol. Cell Biol. 18, 285–298. ()

    Not in our library10.1038/nrm.2017.7

  39. 39.

    Monterroso B, Zorrilla S, Sobrinos-Sanguino M, Keating CD, Rivas G 2016 Microenvironments created by liquid-liquid phase transition control the dynamic distribution of bacterial division FtsZ protein. Sci. Rep. 6, 35140 ()

    Not in our library10.1038/srep35140

  40. 40.

    Dora TT-Y, van Swaay D, DeMello A, Ross Anderson JL, Mann S 2015 In vitro gene expression within membrane-free coacervate protocells. Chem. Commun. 51, 11 429–11 432. ()

    Not in our library10.1039/c5cc04220h

  41. 41.

    Sokolova E, Spruijt E, Hansen MMK, Dubuc E, Groen J, Chokkalingam V, Piruska A, Heus HA, Huck WTS 2013 Enhanced transcription rates in membrane-free protocells formed by coacervation of cell lysate. Proc. Natl. Acad. Sci. USA 110, 11 692–11 697. ()

    Not in our library10.1073/pnas.1222321110

  42. 42.

    Dora TT-Y et al. 2014 Fatty acid membrane assembly on coacervate microdroplets as a step towards a hybrid protocell model. Nat. Chem. 6, 527–533. ()

    Not in our library10.1038/nchem.1921

  43. 43.

    Williams DS, Patil AJ, Mann S 2014 Spontaneous structuration in coacervate-based protocells by polyoxometalate-mediated membrane assembly. Small 10, 1830–1840. ()

    Not in our library10.1002/smll.201303654

  44. 44.

    Mason AF, Buddingh’ BC, Williams DS, van Hest JCM 2017 Hierarchical self-assembly of a copolymer-stabilized coacervate protocell. J. Am. Chem. Soc. 139, 17 309–17 312. ()

    Not in our library10.1021/jacs.7b10846

  45. 45.

    Renard H-F, Johannes L, Morsomme P 2018 Increasing diversity of biological membrane fission mechanisms. Trends Cell Biol. 28, 274–286. ()

    Not in our library10.1016/j.tcb.2017.12.001

  46. 46.

    Zhu Y, Yang B, Chen S, Du J 2017 Polymer vesicles: mechanism, preparation, application, and responsive behavior. Prog. Polym. Sci. 64, 1–22. ()

    Not in our library10.1016/j.progpolymsci.2015.05.001

  47. 47.

    Gebicki JM, Hicks M 1973 Ufasomes are stable particles surrounded by unsaturated fatty acid membranes. Nature 243, 232–234. ()

    Not in our library10.1038/243232a0

  48. 48.

    Hargreaves WR, Deamer DW 1978 Liposomes from ionic, single-chain amphiphiles. Biochemistry 17, 3759–3768. ()

    Not in our library10.1021/bi00611a014

  49. 49.

    Xu C, Hu S, Chen X 2016 Artificial cells: from basic science to applications. Mater. Today 19, 516–532. ()

    Not in our library10.1016/j.mattod.2016.02.020

  50. 50.

    Oberholzer T, Wick R, Luisi PL, Biebricher CK 1995 Enzymatic RNA replication in self-reproducing vesicles: an approach to a minimal cell. Biochem. Biophys. Res. Commun. 207, 250–257. ()

    Not in our library10.1006/bbrc.1995.1180

  51. 51.

    Chen IA, Salehi-Ashtiani K, Szostak JW 2005 RNA catalysis in model protocell vesicles. J. Am. Chem. Soc. 127, 13 213–13 219. ()

    Not in our library10.1021/ja051784p

  52. 52.

    Zhu TF, Szostak JW 2009 Coupled growth and division of model protocell membranes. J. Am. Chem. Soc. 131, 5705–5713. ()

    Not in our library10.1021/ja900919c

  53. 53.

    Budin I, Debnath A, Szostak JW 2012 Concentration-driven growth of model protocell membranes. J. Am. Chem. Soc. 134, 20 812–20 819. ()

    Not in our library10.1021/ja310382d

  54. 54.

    Takakura K, Yamamoto T, Kurihara K, Toyota T, Ohnuma K, Sugawara T 2014 Spontaneous transformation from micelles to vesicles associated with sequential conversions of comprising amphiphiles within assemblies. Chem. Commun. 50, 2190–2192. ()

    Not in our library10.1039/c3cc47786j

  55. 55.

    Adamala K, Szostak JW 2013 Competition between model protocells driven by an encapsulated catalyst. Nat. Chem. 5, 495–501. ()

    Not in our library10.1038/nchem.1650

  56. 56.

    Engelhart AE, Adamala KP, Szostak JW 2016 A simple physical mechanism enables homeostasis in primitive cells. Nat. Chem. 8, 448–453. ()

    Not in our library10.1038/nchem.2475

  57. 57.

    Vance JE 2015 Phospholipid synthesis and transport in mammalian cells. Traffic 16, 1–18. ()

    Not in our library10.1111/tra.12230

  58. 58.

    Sohlenkamp C, Geiger O 2016 Bacterial membrane lipids: diversity in structures and pathways. FEMS Microbiol. Rev. 40, 133–159. ()

    Not in our library10.1093/femsre/fuv008

  59. 59.

    Wick R, Luisi PL 1996 Enzyme-containing liposomes can endogenously produce membrane-constituting lipids. Chem. Biol. 3, 277–285. ()

    Not in our library10.1016/s1074-5521(96)90107-6

  60. 60.

    Schmidli PK, Schurtenberger P, Luisi PL 1991 Liposome-mediated enzymatic synthesis of phosphatidylcholine as an approach to self-replicating liposomes. J. Am. Chem. Soc. 113, 8127–8130. ()

    Not in our library10.1021/ja00021a043

  61. 61.

    Minkenberg CB, Li F, van Rijn P, Florusse L, Boekhoven J, Stuart MCA, Eelkema R, vanEsch JH 2011 Responsive vesicles from dynamic covalent surfactants. Angew. Chem. Int. Ed. 50, 3421–3424. ()

    Not in our library10.1002/anie.201007401

  62. 62.

    Brea RJ, Cole CM, Devaraj NK 2014 In situ vesicle formation by native chemical ligation. Angew. Chem. Int. Ed. 53, 14 102–14 105. ()

    Not in our library10.1002/anie.201408538

  63. 63.

    Hardy MD, Yang J, Selimkhanov J, Cole CM, Tsimring LS, Devaraj NK 2015 Self-reproducing catalyst drives repeated phospholipid synthesis and membrane growth. Proc. Natl. Acad. Sci. USA 112, 8187–8192. ()

    Not in our library10.1073/pnas.1506704112

  64. 64.

    Exterkate M, Caforio A, Stuart MCA, Driessen AJM 2018 Growing membranes in vitro by continuous phospholipid biosynthesis from free fatty acids. ACS Synth. Biol. 7, 153–165. ()

    Not in our library10.1021/acssynbio.7b00265

  65. 65.

    Kuruma Y, Stano P, Ueda T, Luisi PL 2009 A synthetic biology approach to the construction of membrane proteins in semi-synthetic minimal cells. Biochim. Biophys. Acta—Biomembr. 1788, 567–574. ()

    Not in our library10.1016/j.bbamem.2008.10.017

  66. 66.

    Scott A, Noga MJ, de Graaf P, Westerlaken I, Yildirim E, Danelon C 2016 Cell-free phospholipid biosynthesis by gene-encoded enzymes reconstituted in liposomes. PLoS ONE 11, e0163058 ()

    Not in our library10.1371/journal.pone.0163058

  67. 67.

    Pijpers IAB, Abdelmohsen LKEA, Williams DS, van Hest JCM 2017 Morphology under control: engineering biodegradable stomatocytes. ACS Macro Lett. 6, 1217–1222. ()

    Not in our library10.1021/acsmacrolett.7b00723

  68. 68.

    Kurihara K, Tamura M, Shohda K-I, Toyota T, Suzuki K, Sugawara T 2011 Self-reproduction of supramolecular giant vesicles combined with the amplification of encapsulated DNA. Nat. Chem. 3, 775–781. ()

    Not in our library10.1038/nchem.1127

  69. 69.

    Ho JCS, Rangamani P, Liedberg B, Parikh AN 2016 Mixing water, transducing energy, and shaping membranes: autonomously self-regulating giant vesicles. Langmuir 32, 2151–2163. ()

    Not in our library10.1021/acs.langmuir.5b04470

  70. 70.

    Zong W, Ma S, Zhang X, Wang X, Li Q, Han X 2017 A fissionable artificial eukaryote-like cell model. J. Am. Chem. Soc. 139, 9955–9960. ()

    Not in our library10.1021/jacs.7b04009

  71. 71.

    Campelo F, McMahon HT, Kozlov MM 2008 The hydrophobic insertion mechanism of membrane curvature generation by proteins. Biophys. J. 95, 2325–2339. ()

    Not in our library10.1529/biophysj.108.133173

  72. 72.

    Rossman JS, Jing X, Leser GP, Lamb RA 2010 Influenza virus M2 protein mediates ESCRT-independent membrane scission. Cell 142, 902–913. ()

    Not in our library10.1016/j.cell.2010.08.029

  73. 73.
  74. 74.

    Simunovic M et al. 2016 How curvature-generating proteins build scaffolds on membrane nanotubes. Proc. Natl Acad. Sci. USA 113, 11 226–11 231. ()

    Not in our library10.1073/pnas.1606943113

  75. 75.

    Snead WT, Hayden CC, Gadok AK, Zhao C, Lafer EM, Rangamani P, Stachowiak JC 2017 Membrane fission by protein crowding. Proc. Natl Acad. Sci. USA 114, E3258–E3267. ()

    Not in our library10.1073/pnas.1616199114

  76. 76.

    Colom A, Redondo-Morata L, Chiaruttini N, Roux A, Scheuring S 2017 Dynamic remodeling of the dynamin helix during membrane constriction. Proc. Natl. Acad. Sci. USA 114, 5449–5454. ()

    Not in our library10.1073/pnas.1619578114

  77. 77.
  78. 78.

    Antonny B et al. 2016 Membrane fission by dynamin: what we know and what we need to know. EMBO J. 35, 2270–2284. ()

    Not in our library10.15252/embj.201694613

  79. 79.
  80. 80.

    Mierzwa BE et al. 2017 Dynamic subunit turnover in ESCRT-III assemblies is regulated by Vps4 to mediate membrane remodelling during cytokinesis. Nat. Cell Biol. 19, 787–798. ()

    Not in our library10.1038/ncb3559

  81. 81.
  82. 82.

    Czogalla A, Franquelim HG, Schwille P 2016 DNA nanostructures on membranes as tools for synthetic biology. Biophys. J. 110, 1698–1707. ()

    Not in our library10.1016/j.bpj.2016.03.015

  83. 83.
  84. 84.

    Osawa M, Anderson DE, Erickson HP 2008 Reconstitution of contractile FtsZ rings in liposomes. Science 320, 792–794. ()

    Not in our library10.1126/science.1154520

  85. 85.
  86. 86.

    Bisson-Filho AW et al. 2017 Treadmilling by FtsZ filaments drives peptidoglycan synthesis and bacterial cell division. Science 355, 739–743. ()

    Not in our library10.1126/science.aak9973

  87. 87.

    Monteiro JM et al. 2018 Peptidoglycan synthesis drives an FtsZ-treadmilling-independent step of cytokinesis. Nature 554, 528–532. ()

    Not in our library10.1038/nature25506

  88. 88.

    Peters RJRW, Nijemeisland M, van Hest JCM 2015 Reversibly triggered protein–ligand assemblies in giant vesicles. Angew. Chemie 127, 9750–9753. ()

    Not in our library10.1002/ange.201502920

  89. 89.

    Rudd AK, Valls Cuevas JM, Devaraj NK 2015 SNAP-tag-reactive lipid anchors enable targeted and spatiotemporally controlled localization of proteins to phospholipid membranes. J. Am. Chem. Soc. 137, 4884–4887. ()

    Not in our library10.1021/jacs.5b00040

  90. 90.

    Campbell CS, Mullins RD 2007 In vivo visualization of type II plasmid segregation: bacterial actin filaments pushing plasmids. J. Cell Biol. 179, 1059–1066. ()

    Not in our library10.1083/jcb.200708206

  91. 91.

    Surovtsev I, Campos M, Jacobs-Wagner C 2016 DNA-relay mechanism is sufficient to explain ParA-dependent intracellular transport and patterning of single and multiple cargos. Proc. Natl. Acad. Sci. USA 113, E7268–E7276. ()

    Not in our library10.1073/pnas.1616118113

  92. 92.

    Loose M, Fischer-Friedrich E, Ries J, Kruse K, Schwille P 2008 Spatial regulators for bacterial cell division self-organize into surface waves in vitro. Science 320, 789–792. ()

    Not in our library10.1126/science.1154413

  93. 93.

    Vecchiarelli AG, Li M, Mizuuchi M, Mizuuchi K 2014 Differential affinities of MinD and MinE to anionic phospholipid influence Min patterning dynamics in vitro. Mol. Microbiol. 93, 453–463. ()

    Not in our library10.1111/mmi.12669

  94. 94.

    Loose M, Zieske K, Schwille P 2017 Reconstitution of protein dynamics involved in bacterial cell division. In Prokaryotic cytoskeletons: filamentous protein polymers active in the cytoplasm of bacterial and archaeal cells, pp. 419–444. Cham, Switzerland: Springer International Publishing.

    Not in our library10.1007/978-3-319-53047-5_15

  95. 95.

    Caspi Y, Dekker C 2016 Mapping out Min protein patterns in fully confined fluidic chambers. Elife 5, e19271 ()

    Not in our library10.7554/elife.19271

  96. 96.

    Martos A, Jiménez M, Rivas G, Schwille P 2012 Towards a bottom-up reconstitution of bacterial cell division. Trends Cell Biol. 22, 634–643. ()

    Not in our library10.1016/j.tcb.2012.09.003

  97. 97.

    Carlberg C, Molnár F 2016 Mechanisms of gene regulation, 2nd edn Dordrecht, The Netherlands: Springer.

    Not in our library

  98. 98.

    Hanczyc MM 2003 Experimental models of primitive cellular compartments: encapsulation, growth, and division. Science 302, 618–622. ()

    Not in our library10.1126/science.1089904

  99. 99.

    Mansy SS, Schrum JP, Krishnamurthy M, Tobé S, Treco DA, Szostak JW 2008 Template-directed synthesis of a genetic polymer in a model protocell. Nature 454, 122–125. ()

    Not in our library10.1038/nature07018

  100. 100.

    Walde P, Goto A, Monnard P-A, Wessicken M, Luisi PL 1994 Oparin's reactions revisited: enzymic synthesis of poly(adenylic acid) in micelles and self-reproducing vesicles. J. Am. Chem. Soc. 116, 7541–7547. ()

    Not in our library10.1021/ja00096a010

  101. 101.

    Rasmussen S, Chen L, Nilsson M, Abe S 2003 Bridging nonliving and living matter. Artif. Life 9, 269–316. ()

    Not in our library10.1162/106454603322392479

  102. 102.

    Houlihan G, Arangundy-Franklin S, Holliger P 2017 Exploring the chemistry of genetic information storage and propagation through polymerase engineering. Acc. Chem. Res. 50, 1079–1087. ()

    Not in our library10.1021/acs.accounts.7b00056

  103. 103.

    Wu F, Tan C 2014 The engineering of artificial cellular nanosystems using synthetic biology approaches. Wiley Interdiscip. Rev. Nanomed. Nanobiotechnol. 6, 369–383. ()

    Not in our library10.1002/wnan.1265

  104. 104.

    Jia H, Heymann M, Bernhard F, Schwille P, Kai L 2017 Cell-free protein synthesis in micro compartments: building a minimal cell from biobricks. N. Biotechnol. 39, 199–205. ()

    Not in our library10.1016/j.nbt.2017.06.014

  105. 105.

    Shimizu Y, Kanamori T, Ueda T 2005 Protein synthesis by pure translation systems. Methods 36, 299–304. ()

    Not in our library10.1016/j.ymeth.2005.04.006

  106. 106.

    Yu W, Sato K, Wakabayashi M, Nakaishi T, Ko-Mitamura EP, Shima Y, Urabe I, Yomo T 2001 Synthesis of functional protein in liposome. J. Biosci. Bioeng. 92, 590–593. ()

    Not in our library10.1016/s1389-1723(01)80322-4

  107. 107.

    Oberholzer T, Nierhaus KH, Luisi PL 1999 Protein expression in liposomes. Biochem. Biophys. Res. Commun. 261, 238–241. ()

    Not in our library10.1006/bbrc.1999.0404

  108. 108.

    Noireaux V, Libchaber A 2004 A vesicle bioreactor as a step toward an artificial cell assembly. Proc. Natl Acad. Sci. USA 101, 17 669–17 674. ()

    Not in our library10.1073/pnas.0408236101

  109. 109.

    Nomura SM, Tsumoto K, Hamada T, Akiyoshi K, Nakatani Y, Yoshikawa K 2003 Gene expression within cell-sized lipid vesicles. Chembiochem 4, 1172–1175. ()

    Not in our library10.1002/cbic.200300630

  110. 110.

    Niederholtmeyer H, Stepanova V, Maerkl SJ 2013 Implementation of cell-free biological networks at steady state. Proc. Natl Acad. Sci. USA 110, 15 985–15 990. ()

    Not in our library10.1073/pnas.1311166110

  111. 111.

    Bonnet J, Yin P, Ortiz ME, Subsoontorn P, Endy D 2013 Amplifying genetic logic gates. Science 340, 599–603. ()

    Not in our library10.1126/science.1232758

  112. 112.

    Lebar T et al. 2014 A bistable genetic switch based on designable DNA-binding domains. Nat. Commun. 5, 5007 ()

    Not in our library10.1038/ncomms6007

  113. 113.
  114. 114.

    Hasatani K, Leocmach M, Genot AJ, Estévez-Torres A, Fujii T, Rondelez Y 2013 High-throughput and long-term observation of compartmentalized biochemical oscillators. Chem. Commun. 49, 8090 ()

    Not in our library10.1039/c3cc44323j

  115. 115.

    Pogodaev AA, Wong ASY, Huck WTS 2017 Photochemical control over oscillations in chemical reaction networks. J. Am. Chem. Soc. 139, 15 296–15 299. ()

    Not in our library10.1021/jacs.7b08109

  116. 116.

    Garamella J, Marshall R, Rustad M, Noireaux V 2016 The all E. coli TX-TL Toolbox 2.0: a platform for cell-free synthetic biology. ACS Synth. Biol. 5, 344–355. ()

    Not in our library10.1021/acssynbio.5b00296

  117. 117.

    Adamala KP, Martin-Alarcon DA, Guthrie-Honea KR, Boyden ES 2016 Engineering genetic circuit interactions within and between synthetic minimal cells. Nat. Chem. 9, 1–9. ()

    Not in our library10.1038/nchem.2644

  118. 118.

    Franco E, Friedrichs E, Kim J, Jungmann R, Murray R, Winfree E, Simmel FC 2011 Timing molecular motion and production with a synthetic transcriptional clock. Proc. Natl Acad. Sci. USA 108, E784–E793. ()

    Not in our library10.1073/pnas.1100060108

  119. 119.

    Li J, Haas W, Jackson K, Kuru E, Jewett MC, Fan ZH, Gygi S, Church GM 2017 Cogenerating synthetic parts toward a self-replicating system. ACS Synth. Biol. 6, 1327–1336. ()

    Not in our library10.1021/acssynbio.6b00342

  120. 120.

    Nishimura K, Tsuru S, Suzuki H, Yomo T 2015 Stochasticity in gene expression in a cell-sized compartment. ACS Synth. Biol. 4, 566–576. ()

    Not in our library10.1021/sb500249g

  121. 121.

    van Vliet LD, Colin P-Y, Hollfelder F 2015 Bioinspired genotype–phenotype linkages: mimicking cellular compartmentalization for the engineering of functional proteins. Interface Focus 5, 20150035 ()

    Not in our library10.1098/rsfs.2015.0035

  122. 122.

    Ayub M, Bayley H 2016 Engineered transmembrane pores. Curr. Opin. Chem. Biol. 34, 117–126. ()

    Not in our library10.1016/j.cbpa.2016.08.005

  123. 123.

    Ritzmann N, Thoma J, Hirschi S, Kalbermatter D, Fotiadis D, Müller DJ 2017 Fusion domains guide the oriented insertion of light-driven proton pumps into liposomes. Biophys. J. 113, 1181–1186. ()

    Not in our library10.1016/j.bpj.2017.06.022

  124. 124.

    Mahendran KR, Niitsu A, Kong L, Thomson AR, Sessions RB, Woolfson DN, Bayley H 2016 A monodisperse transmembrane α-helical peptide barrel. Nat. Chem. 9, 411–419. ()

    Not in our library10.1038/nchem.2647

  125. 125.

    Einfalt T, Goers R, Dinu IA, Najer A, Spulber M, Onaca-Fischer O, Palivan CG 2015 Stimuli-triggered activity of nanoreactors by biomimetic engineering polymer membranes. Nano Lett. 15, 7596–7603. ()

    Not in our library10.1021/acs.nanolett.5b03386

  126. 126.

    Einfalt T et al. 2018 Biomimetic artificial organelles with in vitro and in vivo activity triggered by reduction in microenvironment. Nat. Commun. 9, 1–12. ()

    Not in our library10.1038/s41467-018-03560-x

  127. 127.

    Zorman S, Botte M, Jiang Q, Collinson I, Schaffitzel C 2015 Advances and challenges of membrane–protein complex production. Curr. Opin. Struct. Biol. 32, 123–130. ()

    Not in our library10.1016/j.sbi.2015.03.010

  128. 128.

    Steinberg-Yfrach G, Rigaud J-L, Durantini EN, Moore AL, Gust D, Moore TA 1998 Light-driven production of ATP catalysed by F0F1-ATP synthase in an artificial photosynthetic membrane. Nature 392, 479–482. ()

    Not in our library10.1038/33116

  129. 129.

    Gale PA, Davis JT, Quesada R 2017 Anion transport and supramolecular medicinal chemistry. Chem. Soc. Rev. 46, 2497–2519. ()

    Not in our library10.1039/c7cs00159b

  130. 130.

    Langton MJ, Keymeulen F, Ciaccia M, Williams NH, Hunter CA 2016 Controlled membrane translocation provides a mechanism for signal transduction and amplification. Nat. Chem. 9, 426–430. ()

    Not in our library10.1038/nchem.2678

  131. 131.

    Langton MJ, Scriven LM, Williams NH, Hunter CA 2017 Triggered release from lipid bilayer vesicles by an artificial transmembrane signal transduction system. J. Am. Chem. Soc. 139, 15 768–15 773. ()

    Not in our library10.1021/jacs.7b07747

  132. 132.

    Gardner PM, Winzer K, Davis BG 2009 Sugar synthesis in a protocellular model leads to a cell signalling response in bacteria. Nat. Chem. 1, 377–383. ()

    Not in our library10.1038/nchem.296

  133. 133.
  134. 134.

    Weitz M, Mückl A, Kapsner K, Berg R, Meyer A, Simmel FC 2014 Communication and computation by bacteria compartmentalized within microemulsion droplets. J. Am. Chem. Soc. 136, 72–75. ()

    Not in our library10.1021/ja411132w

  135. 135.

    Fernandes R, Roy V, Wu H-C, Bentley WE 2010 Engineered biological nanofactories trigger quorum sensing response in targeted bacteria. Nat. Nanotechnol. 5, 213–217. ()

    Not in our library10.1038/nnano.2009.457

  136. 136.

    Elani Y, Trantidou T, Wylie D, Dekker L, Polizzi K, Law RV, Ces O 2018 Constructing vesicle-based artificial cells with embedded living cells as organelle-like modules. Sci. Rep. 8, 4564 ()

    Not in our library10.1038/s41598-018-22263-3

  137. 137.

    Qiao Y, Li M, Booth R, Mann S 2017 Predatory behaviour in synthetic protocell communities. Nat. Chem. 9, 110–119. ()

    Not in our library10.1038/nchem.2617

  138. 138.

    Von Ballmoos C, Biner O, Nilsson T, Brzezinski P 2016 Mimicking respiratory phosphorylation using purified enzymes. Biochim. Biophys. Acta—Bioenerg. 1857, 321–331. ()

    Not in our library10.1016/j.bbabio.2015.12.007

  139. 139.

    Nilsson T, Lundin CR, Nordlund G, Ädelroth P, Von Ballmoos C, Brzezinski P 2016 Lipid-mediated protein–protein interactions modulate respiration-driven ATP synthesis. Sci. Rep. 6, 1–11. ()

    Not in our library10.1038/srep24113

  140. 140.

    Gust D, Moore TA, Moore AL 2001 Mimicking photosynthetic solar energy transduction. Acc. Chem. Res. 34, 40–48. ()

    Not in our library10.1021/ar9801301

  141. 141.

    Duan L, Qi W, Yan X, He Q, Cui Y, Wang K, Li D, Li J 2009 Proton gradients produced by glucose oxidase microcapsules containing motor F 0 F 1 -ATPase for continuous ATP biosynthesis. J. Phys. Chem. B 113, 395–399. ()

    Not in our library10.1021/jp807883e

  142. 142.

    Feng X, Jia Y, Cai P, Fei J, Li J 2016 Coassembly of photosystem II and ATPase as artificial chloroplast for light-driven ATP synthesis. ACS Nano. 10, 556–561. ()

    Not in our library10.1021/acsnano.5b05579

  143. 143.

    Choi H-J, Montemagno CD 2005 Artificial organelle: ATP synthesis from cellular mimetic polymersomes. Nano Lett. 5, 2538–2542. ()

    Not in our library10.1021/nl051896e

  144. 144.

    Wendell D, Todd J, Montemagno C 2010 Artificial photosynthesis in Ranaspumin-2 based foam. Nano Lett. 10, 3231–3236. ()

    Not in our library10.1021/nl100550k

  145. 145.

    Kuang L, Fernandes DA, O'Halloran M, Zheng W, Jiang Y, Ladizhansky V, Brown LS, Liang H 2014 ‘Frozen’ block copolymer nanomembranes with light-driven proton pumping performance. ACS Nano. 8, 537–545. ()

    Not in our library10.1021/nn4059852

  146. 146.

    Hua D, Kuang L, Liang H 2011 Self-directed reconstitution of proteorhodopsin with amphiphilic block copolymers induces the formation of hierarchically ordered proteopolymer membrane arrays. J. Am. Chem. Soc. 133, 2354–2357. ()

    Not in our library10.1021/ja109796x

  147. 147.

    Hvasanov D, Peterson JR, Thordarson P 2013 Self-assembled light-driven photosynthetic-respiratory electron transport chain hybrid proton pump. Chem. Sci. 4, 3833–3838. ()

    Not in our library10.1039/c3sc51780b

  148. 148.

    Fukuzumi S, Lee Y-M, Nam W 2018 Artificial photosynthesis for production of ATP, NAD(P)H, and hydrogen peroxide. ChemPhotoChem 2, 121–135. ()

    Not in our library10.1002/cptc.201700146

  149. 149.

    Nijemeisland M, Abdelmohsen LKEA, Huck WTS, Wilson DA, van Hest JCM 2016 A compartmentalized out-of-equilibrium enzymatic reaction network for sustained autonomous movement. ACS Cent. Sci. 2, 843–849. ()

    Not in our library10.1021/acscentsci.6b00254

  150. 150.

    Tanner P, Egli S, Balasubramanian V, Onaca O, Palivan CG, Meier W 2011 Can polymeric vesicles that confine enzymatic reactions act as simplified organelles? FEBS Lett. 585, 1699–1706. ()

    Not in our library10.1016/j.febslet.2011.05.003

  151. 151.

    Erb TJ, Jones PR, Bar-Even A 2017 Synthetic metabolism: metabolic engineering meets enzyme design. Curr. Opin. Chem. Biol. 37, 56–62. ()

    Not in our library10.1016/j.cbpa.2016.12.023

  152. 152.

    Schwander T, Schada von Borzyskowski L, Burgener S, Cortina NS, Erb TJ 2016 A synthetic pathway for the fixation of carbon dioxide in vitro. Science 354, 900–904. ()

    Not in our library10.1126/science.aah5237

  153. 153.

    Pross A 2011 Toward a general theory of evolution: extending Darwinian theory to inanimate matter. J. Syst. Chem. 2, 1–14. ()

    Not in our library10.1186/1759-2208-2-1

  154. 154.

    Lubbe AS, van Leeuwen T, Wezenberg SJ, Feringa BL 2017 Designing dynamic functional molecular systems. Tetrahedron 73, 4837–4848. ()

    Not in our library10.1016/j.tet.2017.06.049

  155. 155.

    Panettieri S, Ulijn R V 2018 Energy landscaping in supramolecular materials. Curr. Opin. Struct. Biol. 51, 9–18. ()

    Not in our library10.1016/j.sbi.2018.02.001

  156. 156.

    Grzybowski BA, Fitzner K, Paczesny J, Granick S 2017 From dynamic self-assembly to networked chemical systems. Chem. Soc. Rev. 46, 5647–5678. ()

    Not in our library10.1039/c7cs00089h

  157. 157.

    van Rossum SAP, Tena-Solsona M, van Esch JH, Eelkema R, Boekhoven J 2017 Dissipative out-of-equilibrium assembly of man-made supramolecular materials. Chem. Soc. Rev. 46, 5519–5535. ()

    Not in our library10.1039/c7cs00246g

  158. 158.

    Che H, Cao S, van Hest JCM 2018 Feedback-induced temporal control of ‘breathing’ polymersomes to create self-adaptive nanoreactors. J. Am. Chem. Soc. 140, 5356–5359. ()

    Not in our library10.1021/jacs.8b02387

  159. 159.

    Boekhoven J, Hendriksen WE, Koper GJM, Eelkema R, van Esch JH 2015 Transient assembly of active materials fueled by a chemical reaction. Science 349, 1075–1079. ()

    Not in our library10.1126/science.aac6103

  160. 160.

    Wojciechowski JP, Martin AD, Thordarson P 2018 Kinetically controlled lifetimes in redox-responsive transient supramolecular hydrogels. J. Am. Chem. Soc. 140, 2869–2874. ()

    Not in our library10.1021/jacs.7b12198

  161. 161.

    Sowa Y, Berry RM 2008 Bacterial flagellar motor. Q. Rev. Biophys. 41, 103–132. ()

    Not in our library10.1017/s0033583508004691

  162. 162.

    Purcell EME 1977 Life at low Reynolds number. Am. J. Phys. 45, 3–11. ()

    Not in our library10.1119/1.10903

  163. 163.

    Dey KK, Sen A 2017 Chemically propelled molecules and machines. J. Am. Chem. Soc. 139, 7666–7676. ()

    Not in our library10.1021/jacs.7b02347

  164. 164.

    Gao W, Wang J 2014 Synthetic micro/nanomotors in drug delivery. Nanoscale 6, 10 486–10 494. ()

    Not in our library10.1039/c4nr03124e

  165. 165.

    Kassem S, van Leeuwen T, Lubbe AS, Wilson MR, Feringa BL, Leigh DA 2017 Artificial molecular motors. Chem. Soc. Rev. 46, 2592–2621. ()

    Not in our library10.1039/c7cs00245a

  166. 166.

    Mou F, Chen C, Zhong Q, Yin Y, Ma H, Guan J 2014 Autonomous motion and temperature-controlled drug delivery of Mg/Pt-Poly(N-isopropylacrylamide) Janus micromotors driven by simulated body fluid and blood plasma. ACS Appl. Mater. Interfaces 6, 9897–9903. ()

    Not in our library10.1021/am502729y

  167. 167.

    Wilson DA, Nolte RJM, van Hest JCM 2012 Autonomous movement of platinum-loaded stomatocytes. Nat. Chem. 4, 268–274. ()

    Not in our library10.1038/nchem.1281

  168. 168.

    Dey KK, Das S, Poyton MF, Sengupta S, Butler PJ, Cremer PS, Sen A 2014 Chemotactic separation of enzymes. ACS Nano 8, 11 941–11 949. ()

    Not in our library10.1021/nn504418u

  169. 169.

    Sengupta S et al. 2014 Self-powered enzyme micropumps. Nat. Chem. 6, 415–422. ()

    Not in our library10.1038/nchem.1895

  170. 170.

    Mhanna R, Qiu F, Zhang L, Ding Y, Sugihara K, Zenobi-Wong M, Nelson BJ 2014 Artificial bacterial flagella for remote-controlled targeted single-cell drug delivery. Small 10, 1953–1957. ()

    Not in our library10.1002/smll.201303538

  171. 171.

    Sato K, Homma M 2000 Functional reconstitution of the Na-driven polar flagellar motor component of Vibrio alginolyticus. J. Biol. Chem. 275, 5718–5722. ()

    Not in our library10.1074/jbc.275.8.5718

  172. 172.

    Weiss M et al. 2018 Sequential bottom-up assembly of mechanically stabilized synthetic cells by microfluidics. Nat. Mater. 17, 89–96. ()

    Not in our library10.1038/nmat5005

  173. 173.

    Tsai F-C, Koenderink GH 2015 Shape control of lipid bilayer membranes by confined actin bundles. Soft Matter 11, 8834–8847. ()

    Not in our library10.1039/c5sm01583a

  174. 174.

    Lee KY et al. 2018 Photosynthetic artificial organelles sustain and control ATP-dependent reactions in a protocellular system. Nat. Biotechnol. 36, 530–535. ()

    Not in our library10.1038/nbt.4140

  175. 175.

    Viry E, Paggetti J, Baginska J, Mgrditchian T, Berchem G, Moussay E, Janji B 2014 Autophagy: an adaptive metabolic response to stress shaping the antitumor immunity. Biochem. Pharmacol. 92, 31–42. ()

    Not in our library10.1016/j.bcp.2014.07.006

  176. 176.

    Reid CR, Latty T 2016 Collective behaviour and swarm intelligence in slime moulds. FEMS Microbiol. Rev. 40, 798–806. ()

    Not in our library10.1093/femsre/fuw033

  177. 177.

    De Palo G, Yi D, Endres RG 2017 A critical-like collective state leads to long-range cell communication in Dictyostelium discoideum aggregation. PLoS Biol. 15, e1002602 ()

    Not in our library10.1371/journal.pbio.1002602

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