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The bacterial strain JCVI-syn3.0 stands as the first example of a living organism with a minimized synthetic genome, derived from the Mycoplasma mycoides genome and chemically synthesized in vitro. Here, we report the experimental evolution of a syn3.0- derived strain. Ten independent replicates were evolved for several hundred generations, leading to growth rate improvements of > 15%. Endpoint strains possessed an average of 8 mutations composed of indels and SNPs, with a pronounced C/G- > A/T transversion bias. Multiple genes were repeated mutational targets across the independent lineages, including phase variable lipoprotein activation, 5 distinct; nonsynonymous substitutions in the same membrane transporter protein, and inactivation of an uncharacterized gene. Transcriptomic analysis revealed an overall tradeoff reflected in upregulated ribosomal proteins and downregulated DNA and RNA related proteins during adaptation. This work establishes the suitability of synthetic, minimal strains for laboratory evolution, providing a means to optimize strain growth characteristics and elucidate gene functionality. 

Cell-free expression (CFE) systems are one of the main platforms for building synthetic cells. A major drawback is the orthogonality of cell-free systems across species. To generate a CFE system compatible with recently established minimal cell constructs, we attempted to optimize a Mycoplasma bacterium-based CFE system using lysates of the genome-minimized cell JCVI-syn3A (Syn3A) and its close phylogenetic relative Mycoplasma capricolum (Mcap). To produce mycoplasma-derived crude lysates, we systematically tested methods commonly used for bacteria, based on the S30 protocol of Escherichia coli. Unexpectedly, after numerous attempts to optimize lysate production methods or composition of feeding buffer, none of the Mcap or Syn3A lysates supported cell-free gene expression. Only modest levels of in vitro transcription of RNA aptamers were observed. While our experimental systems were intended to perform transcription and translation, our assays focused on RNA. Further investigations identified persistently high ribonuclease (RNase) activity in all lysates, despite removal of recognizable nucleases from the respective genomes and attempts to inhibit nuclease activities in assorted CFE preparations. An alternative method using digitonin to permeabilize the mycoplasma cell membrane produced a lysate with diminished RNase activity yet still was unable to support cell-free gene expression. We found that intact mycoplasma cells poisoned E. coli cell-free extracts by degrading ribosomal RNAs, indicating that the mycoplasma cells, even the minimal cell, have a surface-associated RNase activity. However, it is not clear which gene encodes the RNase. This work summarizes attempts to produce mycoplasma-based CFE and serves as a cautionary tale for researchers entering this field.

Graphical Abstract

 

ABSTRACT Analysis of the genes retained in the minimized Mycoplasma JCVI-Syn3A genome established that systems that repair or preempt metabolite damage are essential to life. Several genes known to have such functions were identified and experimentally validated, including 5-formyltetrahydrofolate cycloligase, coenzyme A (CoA) disulfide reductase, and certain hydrolases. Furthermore, we discovered that an enigmatic YqeK hydrolase domain fused to NadD has a novel proofreading function in NAD synthesis and could double as a MutT-like sanitizing enzyme for the nucleotide pool. Finally, we combined metabolomics and cheminformatics approaches to extend the core metabolic map of JCVI-Syn3A to include promiscuous enzymatic reactions and spontaneous side reactions. This extension revealed that several key metabolite damage control systems remain to be identified in JCVI-Syn3A, such as that for methylglyoxal. IMPORTANCE Metabolite damage and repair mechanisms are being increasingly recognized. We present here compelling genetic and biochemical evidence for the universal importance of these mechanisms by demonstrating that stripping a genome down to its barest essentials leaves metabolite damage control systems in place. Furthermore, our metabolomic and cheminformatic results point to the existence of a network of metabolite damage and damage control reactions that extends far beyond the corners of it that have been characterized so far. In sum, there can be little room left to doubt that metabolite damage and the systems that counter it are mainstream metabolic processes that cannot be separated from life itself. 

One way that researchers can test whether they understand a biological system is to see if they can accurately recreate it as a computer model. The more they learn about living things, the more the researchers can improve their models and the closer the models become to simulating the original. In this approach, it is best to start by trying to model a simple system. Biologists have previously succeeded in creating ‘minimal bacterial cells’. These synthetic cells contain fewer genes than almost all other living things and they are believed to be among the simplest possible forms of life that can grow on their own. The minimal cells can produce all the chemicals that they need to survive – in other words, they have a metabolism. Accurately recreating one of these cells in a computer is a key first step towards simulating a complete living system. Breuer et al. have developed a computer model to simulate the network of the biochemical reactions going on inside a minimal cell with just 493 genes. By altering the parameters of their model and comparing the results to experimental data, Breuer et al. explored the accuracy of their model. Overall, the model reproduces experimental results, but it is not yet perfect. The differences between the model and the experiments suggest new questions and tests that could advance our understanding of biology. In particular, Breuer et al. identified 30 genes that are essential for life in these cells but that currently have no known purpose. Continuing to develop and expand models like these to reproduce more complex living systems provides a tool to test current knowledge of biology. These models may become so advanced that they could predict how living things will respond to changing situations. This would allow scientists to test ideas sooner and make much faster progress in understanding life on Earth. Ultimately, these models could one day help to accelerate medical and industrial processes to save lives and enhance productivity.