Affiliation:
1. International Academic Center of Complex Systems Beijing Normal University Zhuhai China
2. Swarma Research Beijing China
3. Department of Philosophy Shanghai Jiao Tong University Shanghai China
4. Center for Biological Science and Technology Advanced Institute of Natural Sciences, Beijing Normal University Zhuhai China
5. Center for Statistics and Data Science Beijing Normal University Zhuhai China
Abstract
AbstractCreating a man‐made life in the laboratory is one of life science’s most intriguing yet challenging problems. Advances in synthetic biology and related theories, particularly those related to the origin of life, have laid the groundwork for further exploration and understanding in this field of artificial life or man‐made life. But there remains a wealth of quantitative mathematical models and tools that have yet to be applied to this area. In this paper, we review the two main approaches often employed in the field of man‐made life: the top‐down approach that reduces the complexity of extant and existing living systems and the bottom‐up approach that integrates well‐defined components, by introducing the theoretical basis, recent advances, and their limitations. We then argue for another possible approach, namely “bottom‐up from the origin of life”: Starting with the establishment of autocatalytic chemical reaction networks that employ physical boundaries as the initial compartments, then designing directed evolutionary systems, with the expectation that independent compartments will eventually emerge so that the system becomes free‐living. This approach is actually analogous to the process of how life originated. With this paper, we aim to stimulate the interest of synthetic biologists and experimentalists to consider a more theoretical perspective, and to promote the communication between the origin of life community and the synthetic man‐made life community.
Subject
Applied Mathematics,Computer Science Applications,Biochemistry, Genetics and Molecular Biology (miscellaneous),Modeling and Simulation