Cell-free protein synthesis in microcompartments towards cell-cell communication.

Liquid-liquid phase separation (LLPS) compartmentalizes biological systems into dynamic, membraneless condensates that regulate diverse cellular functions. Although protein and RNA-mediated LLPS have dominated research, DNA increasingly emerges as an active driver of phase separation rather than a passive structural scaffold. DNA-driven condensates orchestrate critical nuclear processes, from chromatin organization and transcriptional regulation to genome stability and innate immune responses. Yet LLPS principles extend beyond biology: programmable DNA nanostructures now enable synthetic droplets and hydrogels with tunable mechanical properties, opening pathways to biomaterials, diagnostics, and synthetic cells. Here we synthesize current understanding of DNA-mediated LLPS across biological and synthetic domains, emphasizing five underappreciated topics: (1) DNA's active driving role in LLPS through charge and topology; (2) reversible DNA aggregation and aggregate-to-condensate transitions, distinct from irreversible protein misfolding; (3) non-Fickian transport mechanisms including ballistic wave diffusion triggered by molecular recognition; (4) single-molecule mechanical characterization revealing state-dependent material properties; and (5) the multiscale complexity of cellular DNA condensation shaped by topological constraints and hierarchical organization. We highlight emerging single-molecule technologies, optical tweezers, and scanning probe microscopy that directly measure condensate mechanics and state transitions with unprecedented resolution. This integrated perspective bridges fundamental biophysics of natural DNA condensates with rational engineering principles for programmable synthetic systems, providing a blueprint for therapeutic and biotechnological applications.

Synthetic cells aim to emulate living systems by reconstituting essential cellular processes within lipid-bound architectures. However, their functional complexity remains constrained by a key challenge: the synthesis and correct integration of hydrophobic membrane proteins via cell-free approaches. Here, inspired by natural cells, we developed a spatially regulated translation strategy in which membrane-anchored mRNAs recruit ribosomes to drive the cotranslational insertion of membrane proteins into lipid bilayers. This design enables efficient in situ synthesis and integration of multiple transmembrane proteins within giant unilamellar vesicles, supporting selective small-molecule transport across membranes. Importantly, the method allows for precise stoichiometric control of membrane protein composition. Together, this work establishes a minimal yet versatile framework for the direct synthesis and integration of membrane proteins, advancing the construction of functional synthetic cells.

RNA regulators offer a promising path for building complex, orthogonal circuits due to their low resource demands and design flexibility. In this study, we explore their potential as signaling molecules in communication between synthetic cells. Specifically, we engineer populations of heterogenetic porous polymer cell mimics to produce, emit, and receive two types of small synthetic RNA regulators. These RNAs are required to activate reporter expression at both the levels of transcription and translation. We distribute this AND gate circuit in receiver and two types of sender cell mimics to compare the distributed logic computation to the behavior of the circuit in well-mixed, bulk cell-free expression reactions. Analyzing different densities and spatial arrangements of senders and receivers, we reveal spatiotemporal gradients in RNA signals and identify configurations that increase specific activation. With small regulatory RNAs, the engineering toolbox for communication between synthetic cells expands to include a programmable class of signaling molecules. The rapid turnover of RNA suggests applications in establishing dynamic signaling gradients in communities of synthetic cells.

BackgroundStanford type A aortic dissection (TAAD) is a fatal cardiovascular emergency with high mortality within 48 hours. Elucidating molecular mechanisms and identifying reliable biomarkers are essential for improving diagnosis and guiding targeted interventions.MethodsWe integrated four transcriptome datasets and two single-cell transcriptomic datasets using Harmony batch correction. Differentially expressed genes were identified with DESeq2. Three machine learning algorithms, LASSO, random forest, and SVM-RFE, were employed to identify hub genes, and SHAP analysis was used to quantify their individual contributions. A diagnostic system incorporating seven algorithms was constructed. Immune infiltration profiling, cell-cell communication analysis, and pseudotime trajectory analysis were performed. The proliferation and migration of vascular smooth muscle cells (VSMCs) were assessed using CCK-8 and wound healing assays.ResultsIntegration of bulk and single cell transcriptomic datasets identified three hub genes, SIX4, SCNN1B, and PCDH11X, through convergent machine learning approaches. SHAP analysis highlighted SIX4 as the predominant predictor within diagnostic models, which consistently achieved high accuracy (AUC > 0.9). Single cell profiling localized SIX4 expression to synthetic vascular smooth muscle cells, where it was linked to enhanced CXCL12–CXCR4 mediated immune interactions and remodeling of the inflammatory microenvironment. Functional assays confirmed that SIX4 overexpression promoted vascular smooth muscle cell proliferation and migration, corroborating its role in TAAD progression.ConclusionThis study uncovered SIX4, SCNN1B, and PCDH11X as critical regulators of TAAD. SIX4 was identified as a key modulator of smooth muscle cell plasticity and immune signaling dynamics. These findings deepen our understanding of TAAD pathogenesis and demonstrate the utility of SHAP-guided models in identifying and prioritizing mechanistic drivers in this complex vascular disease.

Living cells regulate biochemical reactions through compartmentalization, achieving high efficiency by precisely controlling spatial and temporal factors. Inspired by this principle, we developed multicompartmentalized artificial cells using liquid-liquid phase separation (LLPS) to regulate cascade enzymatic reactions. Glucose oxidase (GOx) and horseradish peroxidase (HRP) were separately encapsulated into PEGylated and non-PEGylated liposomes, forming enzyme-loaded nanoreactors. These nanoreactors were assembled within a PEG/dextran aqueous two-phase system, allowing controlled spatial arrangement of nanoreactors. Depending on PEGylation, liposomes localized either at the microdroplet interface or inside the lumen, creating four distinct artificial cell models in one step. Among them, the organization with GOx-loaded liposomes at the interface (Models 1 and2) exhibited the highest catalytic efficiency. This enhancement arose from improved substrate accessibility, reduced diffusion barriers, and optimized nanoreactor separation. Other models with less favorable spatial arrangements showed slower reaction rates. Our results highlight how spatial organization within artificial cells can critically influence cascade reaction performance. This modular and biomimetic strategy offers a versatile platform for designing synthetic cells, programmable biocatalysts, and functional microreactors for applications in biosensing, metabolic engineering, and therapeutics.

Abstract Active droplets, membraneless compartments driven by internal chemical reactions, are compelling models for protocells and synthetic life. A central challenge is to program their dynamic behaviors using heritable genetic information, which would grant them the capacity to evolve. Here, we create transiently active RNA droplets by integrating sites for ribozyme catalysis directly into the sequence of self‐assembling, four‐arm RNA nanostars. To enable perfusion and observe the resulting dynamics over time, we develop a method for trapping individual droplets in hydrogel cages by targeted in situ photopolymerization. This enables us to quantify the sequence‐programmable droplet dissolution and to control the degradation kinetics by choosing between fast (hammerhead) and slow (hairpin) ribozymes. Furthermore, we trigger the segregation of mixed droplet populations via the sequence‐specific cleavage of a chimeric linker RNA. The droplet‐encapsulated DNA templates code for the regrowth of new droplets, establishing the proof‐of‐principle for a minimal, genetically encoded cycle of dissolution and regrowth. By directly linking RNA sequence to droplet stability, composition, and life‐cycle dynamics, our work provides a robust platform for engineering evolvable materials and advancing the bottom‐up construction of synthetic cells.

Building synthetic versions of biological cells from the bottom up offers an unprecedented opportunity to understand the rules of life and harness cellular capabilities in biotechnology. Whereas substantial progress has been made in recapitulating elementary cell functions, we argue that accelerating the engineering of synthetic cells requires a shift in research practices. The dominant approach-rationally designing and integrating functional modules-becomes restrictive when dealing with the massively complex biochemical pathways associated with life, especially when design principles remain unclear. We advocate moving away from theoretical rational design towards a data-driven model that is centred on library generation. Inspired by a systems chemistry perspective, this strategy prioritizes the systematic creation and distribution of composition-function libraries. To enable this, experimental strategies must integrate high-throughput synthetic cell generation, automation and closed-feedback control of workflows. Broad adoption will also require greater emphasis on quantitative benchmarking, and the de-skilling of techniques, supporting effective laboratory-to-laboratory collaboration.

Biomolecular condensates with multiphasic architectures organize specific biomolecular processes in different compartments and dynamically reconfigure their structure to regulate their biological functions. Here, we employ multiphase coacervates as model condensates to illustrate pH-responsive dynamic reconfiguration of multiphase wetting interactions mediated by phase selective enrichment of fatty acids. We noted that unsaturated fatty acids such as linolenic acid (LA) can enrich within specific coacervates, via spontaneous substitution of like charged coacervate components, to drastically alter coacervate properties such as viscosity and surface tension. By selectively enriching fatty acids within the outer phase of a multiphase coacervate, the changes in coacervate properties were used to trigger the outer phase to dewet the inner phase and separate into two droplets. Dynamic switching between wetting and dewetting states of multiphase droplets was achieved by adjusting the outer phase composition via pH changes, which impacted LA's ability to substitute coacervate components. Finally, chemical signaling mediated reconfiguration of coacervate-based synthetic cells was shown using urease containing microgels, which secreted pH-based chemical signals to propagate a reconfiguration front within multiphase droplet populations. Taken together, our results highlight opportunities for the design of dynamically reconfigurable synthetic cells capable of transducing chemical signals into morphological changes and suggest that lipids enriched within condensates may be involved in regulating their morphology and function.

A virtual screen combining molecular simulations, alchemical calculations, Gaussian process regression, and Bayesian optimization discovers elastin-like polypeptides predicted to form stable bilayer vesicles for synthetic cells.

Artificial cells emulating the structure and function of living systems have attracted tremendous research attention. By integrating concepts and techniques from chemistry, materials science, and biochemistry, researchers have assembled functional building modules into advanced materials capable of exhibiting life-like behaviors. Recent advances have led to the creation of synthetic cells that mimic key characteristics of living cells. Polymer-based systems attract enormous interest due to their chemical versatility, robustness, and programmability. These attributes allow the construction of artificial cells with precise modulation of physicochemical properties, architecture and functionality. Representative polymeric artificial cells have demonstrated essential hallmarks of life, including membranization, integration of suborganelles, and formation of cytoskeletal frameworks. In this Review, we highlight recent advances in the design, assembly, and functionalization of polymer-based artificial cells, emphasizing how the intrinsic tunability and multifunctionality of polymeric materials enable the recreation and extension of life-like structures, dynamic behaviors, and biological functions.

Viral infection of living cells, exemplified by bacteriophage interaction with bacteria, is fundamental to biology and universal across living systems. Here, we establish an all-cell-free viral cycle where T7 phages infect synthetic cells, equipped with lipopolysaccharides on the outer leaflet of the lipid membrane, while encapsulating a cell-free gene expression system. We track each cycle step to demonstrate T7 phage-specific adsorption onto the liposomes, genome entry, replication, expression, and assembly of new infectious virions within the synthetic cells. We quantify key characteristics of the cycle, including the multiplicity of infection, replication efficiency, liposome size constraints, and phage rebinding dynamics. This work establishes a versatile, fully defined in vitro platform for reconstructing and investigating viral infections from individual molecular components.

Compartmentalization by organelles and the dynamic control of protein localization within these compartmentalized spaces are key mechanisms for regulating biological processes in eukaryotic cells. Here, we present a bottom-up approach for constructing cell-sized liposomes (giant unilamellar vesicles, GUVs) encapsulating an artificial organelle with chemically controlled protein localization. In this system, proteins fused to Escherichia coli dihydrofolate reductase are rapidly recruited on demand from the inner solution to the interior of a DNA-droplet-based ("nucleus"-like) organelle within GUVs upon addition of a synthetic, DNA-binding trimethoprim derivative to the external solution. By coupling this system with a sequence-specific protease, we constructed a synthetic cell platform that enables chemically induced, multistep cascade reactions─including protein relocalization, organelle-specific enzymatic activity, and product release from the organelle─that culminate in the control of synthetic-cell phenotypes, such as pore formation in the GUV membrane. This work provides a versatile platform for the bottom-up creation of eukaryotic-like synthetic cells with sophisticated and programmable functions.

Self-assembly is a fundamental property of living matter that drives the three-dimensional organization of cell collectives such as tissues and organs. Here, the co-assembly of synthetic and natural cells is leveraged to create hybrid living 3D cancer cultures. We screen a range of synthetic cell models for their ability to form augmented tumoroids with artificial but controllable micro-environments, and show that the balance of inter- and extracellular adhesion and synthetic cell surface tension are key material properties driving integrated co-assembly. We demonstrate that synthetic cells based on droplet-supported lipid bilayers can establish artificial tumor immune microenvironments (ART-TIMEs), mimicking immunogenic signals within tumoroids and eliminating the need to integrate complex living immune cells. Using the ART-TIME approach, we identify a AhR-ARNT-mediated co-signaling mechanism between PD-1 and CD2 as a driver in immune evasion of pancreatic ductal adenocarcinoma. Our study advances the field of hybrid organoid engineering, offers opportunities for the construction and modelling of artificial tumour environments, and marks a step towards the design of functional living/non-living cytomimetic materials.

Artificial membrane systems have enabled powerful studies of lipid dynamics and bilayer mechanics, yet they lack the structural complexity of living cells, where membranes are embedded within an extracellular matrix (ECM). Here, a biomimetic platform is presented that integrates fibronectin (FN) and collagen type I (COL) onto the surface of giant unilamellar vesicles (GUVs) to investigate ECM-induced modulation of membrane properties. ECM coating imparts distinct, protein-specific effects on vesicle curvature, mechanical resilience, and lipid diffusivity. FN promotes vesicle budding and membrane softening, while COL induces rugged membrane topographies and mechanical stiffening. Furthermore, ECM proteins reshape the geometry and stability of phase-separated lipid domains, mimicking curvature heterogeneity observed in cell membranes. Strikingly, vesicle budding events observed in FN-coated GUVs resemble exosome-like release, suggesting that ECM identity not only dictates membrane mechanics but may also regulate vesicle biogenesis. This system captures essential mechanobiological interactions between the ECM and the plasma membrane in the absence of transmembrane linkers. The findings provide a tunable platform for studying ECM-membrane coupling and ECM-vesicle interplay with relevance to exosome modeling, offering new directions for engineering responsive synthetic cells and advancing extracellular vesicle biology.

Abstract For cellular functions such as division and polarization, protein pattern formation driven by NTPase cycles is a central spatial control strategy. Operating far from equilibrium, no general theory links microscopic reaction networks and parameters to the pattern type and dynamics in these protein systems. Here we discover a generic mechanism giving rise to an effective interfacial tension organizing the macroscopic structure of non-equilibrium steady-state patterns. Namely, maintaining protein-density interfaces by cyclic protein attachment and detachment produces curvature-dependent protein redistribution, which straightens the interface. We develop a non-equilibrium Neumann angle law and Plateau vertex conditions for interface junctions and mesh patterns, thus introducing the concepts of ‘Turing mixtures’ and ‘Turing foams’. In contrast to liquid foams and mixtures, these non-equilibrium patterns can select an intrinsic wavelength by interrupting an equilibrium-like coarsening process. Data from in vitro experiments with the Escherichia coli Min protein system verify the vertex conditions and support the wavelength dynamics. Our study shows how interface laws with correspondence to thermodynamic relations can arise from distinct physical processes in active systems. It allows the design of specific pattern morphologies with potential applications as spatial control strategies in synthetic cells.

Microfluidics meets cell-free systems: from molecular engineering to synthetic cells.

Living cells employ dynamic networks for intercellular communication and cooperation, leading to tissue-wide activity. One emerging challenge in the field of bottom-up synthetic biology is emulating such sophisticated behaviors in liposome-based synthetic cells (SCs). Fabricating communication networks in lipid bilayer-based SCs remains a challenge, as signaling molecules must transit through two consecutive membranes to transfer information between different SCs. Here, we address this obstacle by engineering connexin channels that directly connect the lumens of adhering SC membranes. We focus on orthogonal channel-forming connexins, namely connexin 43 and connexin 32, and redesign their channel activity to be UV- and near IR-responsive, respectively. By combining engineered connexins into a single SC assembly, we demonstrate orthogonal transfer of reactive signaling molecules between SCs, giving rise to unique reaction products and network states in a wavelength-dependent manner - an important step toward synthetic communication networks.

Individual variability shapes how diseases manifest, how patients respond to therapy, and how rare phenotypes arise. Conventional experimental approaches obscure variation by averaging, which limits mechanistic insight and predictive accuracy. We present a computational framework that builds digital twins of human induced pluripotent stem cell derived cardiomyocytes from a single optimized voltage clamp experiment. The framework depends on massive synthetic datasets comprising synthetic simulated cells that span broad ionic and electrophysiological ranges. These synthetic data make it possible to control parameters precisely, explore biological variability comprehensively, and train models beyond the limits of experimental data. A neural network trained on synthetic data then inferred cell specific biophysical parameters from experimental recordings from live cells, reproducing distinct features. Our study unites computational modeling, data simulation, and learning to enable scalable, precise, individualized cardiac electrophysiology modeling and can be readily extended to any electrically active cell type.

pH is a critical parameter in biological systems, with acidic environments often serving as hallmarks of pathological conditions such as cancer, infection, and metabolic disorders. Here, we developed a pH-responsive synthetic cell capable of protein synthesis and release under acidic conditions. The system was constructed by integrating three molecular modules: a proton channel for pH sensing, a pH-responsive single-stranded DNA (ssDNA) that releases a trigger ssDNA upon acidification, and a toehold switch RNA that activates translation in response to the trigger ssDNA. During integration, we discovered that adjusting the annealing length between the pH-responsive and trigger strands was critical for enabling the acid-triggered protein synthesis. Using this strategy, we successfully demonstrated acid-responsive protein expression within synthetic cells. To further explore applications, we embedded the synthetic cells in a hydrogel to endow pH-responsive behavior to materials and coupled pH-responsive protein translation with a cell-penetrating peptide technology for selective release of proteins.