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利用生物传感器进行代谢产物生产能力的综合进化。

Synthetic Evolution of Metabolic Productivity Using Biosensors.

机构信息

Department of Chemistry and Biomolecular Sciences, Macquarie University, NSW, Australia.

Department of Chemistry and Biomolecular Sciences, Macquarie University, NSW, Australia.

出版信息

Trends Biotechnol. 2016 May;34(5):371-381. doi: 10.1016/j.tibtech.2016.02.002. Epub 2016 Mar 3.

Abstract

Synthetic biology has progressed to the point where genes that encode whole metabolic pathways and even genomes can be manufactured and brought to life. This impressive ability to synthesise and assemble DNA is not yet matched by an ability to predictively engineer biology. These difficulties exist because biological systems are often overwhelmingly complex, having evolved to facilitate growth and survival rather than specific engineering objectives such as the optimisation of biochemical production. A promising and revolutionary solution to this problem is to harness the process of evolution to create microbial strains with desired properties. The tools of systems biology can then be applied to understand the principles of biological design, bringing synthetic biology closer to becoming a predictive engineering discipline.

摘要

合成生物学已经发展到可以制造和赋予生命完整代谢途径甚至基因组的基因的地步。这种令人印象深刻的合成和组装 DNA 的能力尚未与预测性工程生物学相匹配。这些困难的存在是因为生物系统通常过于复杂,它们的进化是为了促进生长和生存,而不是特定的工程目标,如生化生产的优化。解决这个问题的一个有前途和革命性的方法是利用进化过程来创造具有所需特性的微生物菌株。然后可以应用系统生物学的工具来理解生物设计的原则,使合成生物学更接近成为一门可预测的工程学科。

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