The Min biochemical network regulates bacterial cell division and is a prototypical example of self-organizing molecular systems. Cell-free assays relying on purified proteins have shown that MinE and MinD self-organize into surface waves and oscillatory patterns. In the context of developing a synthetic cell from elementary biological modules, harnessing Min oscillations might allow us to implement higher-order cellular functions. To convey hereditary information, the Min system must be encoded in a DNA molecule that can be copied, transcribed, and translated. Here, the MinD and MinE proteins are synthesized de novo from their genes inside liposomes. Dynamic protein patterns and accompanying liposome shape deformation are observed. When integrated with the cytoskeletal proteins FtsA and FtsZ, the synthetic Min system is able to dynamically regulate FtsZ patterns. By enabling genetic control over Min protein self-organization and membrane remodeling, our methodology offers unique opportunities towards directed evolution of bacterial division processes in vitro.

A major challenge towards the realization of an autonomous synthetic cell resides in the encoding of a division machinery in a genetic programme. In the bacterial cell cycle, the assembly of cytoskeletal proteins into a ring defines the division site. At the onset of the formation of the Escherichia coli divisome, a proto-ring consisting of FtsZ and its membrane-recruiting proteins takes place. Here, we show that FtsA-FtsZ ring-like structures driven by cell-free gene expression can be reconstituted on planar membranes and inside liposome compartments. Such cytoskeletal structures are found to constrict the liposome, generating elongated membrane necks and budding vesicles. Additional expression of the FtsZ cross-linker protein ZapA yields more rigid FtsZ bundles that attach to the membrane but fail to produce budding spots or necks in liposomes. These results demonstrate that gene-directed protein synthesis and assembly of membrane-constricting FtsZ-rings can be combined in a liposome-based artificial cell.

DNA-guided cell-free protein synthesis using a minimal set of purified components has emerged as a versatile platform in constructive biology. The E. coli-based PURE (Protein synthesis Using Recombinant Elements) system offers the basic protein synthesis factory in a prospective minimal cell relying on extant molecules. However, it becomes urgent to improve the system's performance, and to build a mechanistic computational model that can help interpret and predict gene expression dynamics. Herein, we utilized all three commercially available PURE system variants: PURExpress, PUREfrex and PUREfrex2.0. We monitored apparent kinetics of mRNA and protein synthesis by fluorescence spectroscopy at different concentrations of DNA template. Analysis of polysome distributions by atomic force microscopy, combined with a stochastic model of translation, revealed inefficient usage of ribosomes, consistent with the idea that translation initiation is a limiting step. This preliminary dataset was used to formulate hypotheses regarding possible mechanisms impeding robust gene expression. Next, we challenged these hypotheses by devising targeted experiments aimed to alleviate the current limitations of PUREfrex. We identified depletion of key initiation factors by translationally inactive mRNA as a possible inhibitory mechanism. This adverse process could partly be remedied by targeted mRNA degradation, whereas addition of more IFs and of the hrpA RNA helicase had no substantial effects. Moreover, depletion of tRNAs as peptidyl-tRNAs can become limiting in PUREfrex (but not in PURExpress), which can be alleviated by addition of peptidyl-tRNAhydrolase (PTH). We attempted to build a new model for PURE system dynamics integrating all experimental observations. Although a satisfying global fit can be obtained in specific conditions (with PTH), a unifying system's level model is still missing.

The inherent stochasticity of molecular reactions prevents us from predicting the exact state of single-cells in a population. However, when a population grows at steady-state, the probability to observe a cell with particular combinations of properties is fixed. Here we validate and exploit existing theory on the statistics of single-cell growth in order to predict the probability of phenotypic characteristics such as cell-cycle times, volumes, accuracy of division and cell-age distributions, using real-time imaging data for Bacillus subtilis and Escherichia coli. Our results show that single-cell growth-statistics can accurately be predicted from a few basic measurements. These equations relate different phenotypic characteristics, and can therefore be used in consistency tests of experimental single-cell growth data and prediction of single-cell statistics. We also exploit these statistical relations in the development of a fast stochastic-simulation algorithm of single-cell growth and protein expression. This algorithm greatly reduces computational burden, by recovering the statistics of growing cell-populations from the simulation of only one of its lineages. Our approach is validated by comparison of simulations and experimental data. This work illustrates a methodology for the prediction, analysis and tests of consistency of single-cell growth and protein expression data from a few basic statistical principles.

The Protein synthesis Using Recombinant Elements (PURE) system enables transcription and translation of a DNA template from purified components. Therefore, the PURE system-catalyzed generation of RNAs and proteins constituting the PURE system itself represents a major challenge toward a self-replicating minimal cell. In this work, we show that all translation factors (except elongation factor Tu) and 20 aminoacyl-tRNA synthetases can be expressed in the PURE system from a single plasmid encoding 32 proteins in 30 cistrons. Cell-free synthesis of all 32 proteins is confirmed by quantitative mass spectrometry-based proteomic analysis using isotopically labeled amino acids. We find that a significant fraction of the gene products consists of proteins missing their C-terminal ends. The per-codon processivity loss that we measure lies between 1.3 × 10–3 and 13.2 × 10–3, depending on the expression conditions, the version of the PURE system, and the coding sequence. These values are 5 to 50 times higher than those measured in vivo in E. coli. With such an impaired processivity, a considerable fraction of the biosynthesis capacity of the PURE system is wasted, posing an unforeseen challenge toward the development of a self-regenerating PURE system.