In vitro reconstitution of protein systems─e.g., metabolic pathways, genetic circuits, or biosensors─often requires optimization to enhance their activity. Combinatorial DNA libraries that simultaneously target multiple genes allow for a holistic optimization strategy by studying the interplay between the systems' components, which may reveal DNA variants that would be hidden when testing each element in isolation. Here, we screen large populations of synthetic vesicles that express combinatorial DNA variants of a DNA self-replicator or a phospholipid synthesis pathway. We simultaneously vary the strengths of multiple RBSs or synonymously mutate the first codons of multiple genes to explore the effects of the protein translation rates directly on the functionality of the two core synthetic cell modules. We isolated high performers through DNA self-selection or functional screening by fluorescence-activated cell sorting. Long-read sequencing of the fittest variants revealed the optimal RBS strengths and base substitutions in the first codons and indicated which genes were most impactful in regulating the functionality of the protein systems. Single-mutation data were used to predict the fitness of combinatorial variants, which was compared with the experimental fitness observed. The theoretical fitness of combinatorial variants was extremely predictive for the two-gene library of the DNA replicator but less for the larger pathway library. Altogether, our approach exemplifies how combinatorial testing can be expanded from single proteins to multiprotein systems, which can in the future be extended to the evolutionary engineering of even larger genetic and metabolic networks, and eventually an entire artificial cell.

Understanding the relationships between genotype and phenotype is key to many areas of biological research and to the development of synthetic cells. We describe an image-based screening and sorting workflow that explores the phenotypes of gene-expressing vesicles within nonclonal populations and selects the desired variants. Using automated confocal microscopy and real-time, neural network–assisted image analysis, we demonstrate that liposomes can be selected for fluorescence intensity, protein localization, membrane morphology, and dynamic behaviors, and their phenotype can be linked to genetic content. This approach could substantially accelerate the evolution of cellular functions in a minimal synthetic context.

The editing of plasmids and construction of plasmid libraries is paramount to the engineering of desired functionalities in synthetic biology. Typically, plasmids with targeted mutations are produced through time- and resource-consuming DNA amplification and/or cloning steps. In this study, we establish MOSAIC, a highly efficient protocol for the editing of plasmids and generation of combinatorial plasmid libraries. This quick protocol employs the efficient single-stranded DNA annealing protein (SSAP) CspRecT to incorporate (libraries of) DNA oligos harboring the desired mutations into a target plasmid in Escherichia coli. In addition to up to 90% single-target plasmid editing efficiency, we demonstrate that MOSAIC enables the generation of a combinatorial plasmid library spanning four different target regions on a plasmid, in a single transformation. Lastly, we integrated a user-friendly validation pipeline using Nanopore sequencing reads, requiring minimal computational experience. We anticipate that MOSAIC will provide researchers with a simple, rapid and resource-effective method to edit plasmids or generate large, diverse plasmid libraries for a wide range of in vivo or in vitro applications in molecular and synthetic biology.