Combinatorial metabolic pathway assembly approaches and toolkits for modular assembly
| Autor: | Marko Storch, Matthew C. Haines, Rosanna E. B. Young, Paul S. Freemont |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0106 biological sciences
Computer science Chassis Interoperability Bioengineering 01 natural sciences Applied Microbiology and Biotechnology Modularity 03 medical and health sciences Synthetic biology 010608 biotechnology DNA assembly 1003 Industrial Biotechnology Pathway tuning 030304 developmental biology 0303 health sciences Cell-Free System business.industry DNA Modular design Automation Biosynthetic Pathways Living systems Metabolic pathway Metabolic Engineering Systems engineering Synthetic Biology business Engineering design process Metabolic Networks and Pathways Cloning Biotechnology |
| Zdroj: | Metabolic Engineering. 63:81-101 |
| ISSN: | 1096-7176 |
| DOI: | 10.1016/j.ymben.2020.12.001 |
| Popis: | Synthetic Biology is a rapidly growing interdisciplinary field that is primarily built upon foundational advances in molecular biology combined with engineering design principles such as modularity and interoperability. The field considers living systems as programmable at the genetic level and has been defined by the development of new platform technologies and methodological advances. A key concept driving the field is the Design-Build-Test-Learn cycle which provides a systematic framework for building new biological systems. One major application area for synthetic biology is biosynthetic pathway engineering that requires the modular assembly of different genetic regulatory elements and biosynthetic enzymes. In this review we provide an overview of modular DNA assembly and describe and compare the plethora of in vitro and in vivo assembly methods for combinatorial pathway engineering. Considerations for part design and methods for enzyme balancing are also presented, and we briefly discuss alternatives to intracellular pathway assembly including microbial consortia and cell-free systems for biosynthesis. Finally, we describe computational tools and automation for pathway design and assembly and argue that a deeper understanding of the many different variables of genetic design, pathway regulation and cellular metabolism will allow more predictive pathway design and engineering. |
| Databáze: | OpenAIRE |
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