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1. Essential metabolism for a minimal cell

   https://doi.org/10.7554/eLife.36842  

   Breuer, Marian; Earnest, Tyler M; Merryman, Chuck; Wise, Kim S; Sun, Lijie; Lynott, Michaela R; Hutchison, Clyde A; Smith, Hamilton O; Lapek, John D; Gonzalez, David J; et al (January 2019, eLife)

   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. 

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2. Cell-free expressed membraneless organelles sequester RNA in synthetic cells

   https://doi.org/10.1101/2023.04.03.535479  

   Robinson, Abbey O; Lee, Jessica; Cameron, Anders; Keating, Christine D; Adamala, Katarzyna P (April 2023, bioRxiv)

   Abstract Compartments within living cells create specialized microenvironments, allowing for multiple reactions to be carried out simultaneously and efficiently. While some organelles are bound by a lipid bilayer, others are formed by liquid-liquid phase separation, such as P-granules and nucleoli. Synthetic minimal cells have been widely used to study many natural processes, including organelle formation. Here we describe a synthetic cell expressing RGG-GFP-RGG, a phase-separating protein derived from LAF-1 RGG domains, to form artificial membraneless organelles that can sequester RNA and reduce protein expression. We create complex microenvironments within synthetic cell cytoplasm and introduce a tool to modulate protein expression in synthetic cells. Engineering of compartments within synthetic cells furthers understanding of evolution and function of natural organelles, as well as it facilitates the creation of more complex and multifaceted synthetic life-like systems. 

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3. Synthetic cells in biomedical applications

   https://doi.org/10.1002/wnan.1761  

   Sato, Wakana; Zajkowski, Tomasz; Moser, Felix; Adamala, Katarzyna P. (March 2022, WIREs Nanomedicine and Nanobiotechnology)

   Abstract Synthetic cells are engineered vesicles that can mimic one or more salient features of life. These features include directed localization, sense‐and‐respond behavior, gene expression, metabolism, and high stability. In nanomedicine, many of these features are desirable capabilities of drug delivery vehicles but are difficult to engineer. In this focus article, we discuss where synthetic cells offer unique advantages over nanoparticle and living cell therapies. We review progress in the engineering of the above life‐like behaviors and how they are deployed in nanomedicine. Finally, we assess key challenges synthetic cells face before being deployed as drugs and suggest ways to overcome these challenges. This article is categorized under:Therapeutic Approaches and Drug Discovery > Emerging TechnologiesBiology‐Inspired Nanomaterials > Lipid‐Based Structures 

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4. Build-a-Cell: Engineering a Synthetic Cell Community

   https://doi.org/10.3390/life11111176  

   Frischmon, Caroline; Sorenson, Carlise; Winikoff, Michael; Adamala, Katarzyna P (November 2021, Life)

   Build-a-Cell is a global network of researchers that aims to develop synthetic living cells within the next decade. These cells will revolutionize the biotechnology industry by providing scientists and engineers with a more complete understanding of biology. Researchers can already replicate many cellular functions individually, but combining them into a single cell remains a significant challenge. This integration step will require the type of large-scale collaboration made possible by Build-a-Cell’s open, collective structure. Beyond the lab, Build-a-Cell addresses policy issues and biosecurity concerns associated with synthetic cells. The following review discusses Build-a-Cell’s history, function, and goals. 

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5. Rapid, robust plasmid verification by de novo assembly of short sequencing reads

   https://doi.org/10.1093/nar/gkaa727  

   Gallegos, Jenna E; Rogers, Mark F; Cialek, Charlotte A; Peccoud, Jean (September 2020, Nucleic Acids Research)

   null (Ed.)

   Abstract Plasmids are a foundational tool for basic and applied research across all subfields of biology. Increasingly, researchers in synthetic biology are relying on and developing massive libraries of plasmids as vectors for directed evolution, combinatorial gene circuit tests, and for CRISPR multiplexing. Verification of plasmid sequences following synthesis is a crucial quality control step that creates a bottleneck in plasmid fabrication workflows. Crucially, researchers often elect to forego the cumbersome verification step, potentially leading to reproducibility and—depending on the application—security issues. In order to facilitate plasmid verification to improve the quality and reproducibility of life science research, we developed a fast, simple, and open source pipeline for assembly and verification of plasmid sequences from Illumina reads. We demonstrate that our pipeline, which relies on de novo assembly, can also be used to detect contaminating sequences in plasmid samples. In addition to presenting our pipeline, we discuss the role for verification and quality control in the increasingly complex life science workflows ushered in by synthetic biology. 

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