Special collection of synthetic biology, aiming for quantitative control of cellular systems
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Over the past 15 years, the field of synthetic biology has seen a rapid rise in research activities and innovation, as evident by the increase of publications that quote the term “synthetic biology” from one in 2002 to ~1400 in 2016 (from PubMed). Furthermore, synthetic biology projects now involve biological parts that work at wide length-scales and synthetic cells that are created from the bottom-up. With the expansion of synthetic biology in terms of project scale and research activity, have we fulfilled the initial goals of the field? In my personal perspective, there are at least two primary goals of synthetic biology that differentiate it from other fields. First, synthetic biology will enable rational and quantitative control of biological systems that are robust to their environmental context. Second, synthetic biology will expand our ability to create and program biological systems from the bottom-up. Achieving the goals has broad impact on applications of synthetic biology in the manufacturing of therapeutic cells, production of biological commodities, disease diagnostics, and therapeutic treatment. However, assessing our overall advancement toward the goals is non-trivial. We do not use a standard metric to report functions of engineered cells, and we do not study the same model system within the same context. My own research has met similar obstacles in pursuing the goals. A meta-analysis of platereader protocols in synthetic biology reveals a lack of consistent protocols and consensus reporting of the protocols, which may affect their reproducibility [1]. In addition, my lab synthesizes artificial cells that mimic living cells from the bottom-up [2]. Despite the minimality of the artificial cells, it remains difficult to rationally control the cells in varying environmental conditions due to the lack of knowledge on how their parts interact with one another and with environmental factors. When I was asked to edit this special issue, my first thought was to assemble a group of emerging leaders in the field to address the two main goals from their own perspective. In contrast to other special issues in synthetic biology, this special issue focuses primarily on quantitative approaches in synthetic biology that aim to advance rational control of biological systems. The special issue covers four areas of synthetic biology: phage engineering, gene expression control, nonlinear dynamics of cells, and metabolic networks. Brown et al. review the role of synthetic biology in promoting phage therapy, and discuss challenges involved in expanding host range of bacteriophages, reducing side effect of phages, and modifying bacteria using engineered phages. Based on single-cell microscopy, Guan et al. quantify the degradation of phage DNA by the CRISPR/Cas system. Their results may open the door toward predictive model of phage-bacteria interactions in the future. Three papers in this special issue cover the quantitative control and assays of nucleic acids. Guo et al. review the application of DNA strand displacement reaction in DNA nanotechnology. Meng et al. present a machine learning approach that predicts expression strength of promoters. Choudhary et al. review the structural profiling of RNA, as well as current approaches and challenges in using the profiling data for prediction of RNA structure. Synthetic biological parts can also be integrated to generate nonlinear dynamics of biological systems. Sadeghpour et al. study the emergence of bistability in co-repressivemicrobial
[1] Cheemeng Tan,et al. Dynamic biomaterials: toward engineering autonomous feedback. , 2016, Current opinion in biotechnology.
[2] Cheemeng Tan,et al. Reproducibility of High-Throughput Plate-Reader Experiments in Synthetic Biology. , 2017, ACS synthetic biology.