Towards Engineering Biological Systems in a Broader Context

被引:24
|
作者
Venturelli, Ophelia S. [1 ,3 ]
Egbert, Robert G. [2 ]
Arkin, Adam P. [2 ,3 ]
机构
[1] Univ Calif Berkeley, Calif Inst Quantitat Biosci, 2151 Berkeley Way, Berkeley, CA 94704 USA
[2] EO Lawrence Berkeley Natl Lab, 1 Cyclotron Rd,MS 955-512L, Berkeley, CA 94720 USA
[3] Univ Calif Berkeley, Dept Bioengn, Berkeley, CA 94720 USA
关键词
synthetic biology; synthetic ecology; resource allocation; ecological stability; phenotypic diversification; RNA-POLYMERASE AVAILABILITY; EVOLUTIONARY TRADE-OFFS; ESCHERICHIA-COLI; GENE-EXPRESSION; COPY-NUMBER; INFORMATION-TRANSMISSION; BACTERIAL PERSISTENCE; ENVIRONMENTAL SIGNAL; METABOLIC PATHWAY; SYNTHETIC BIOLOGY;
D O I
10.1016/j.jmb.2015.10.025
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Significant advances have been made in synthetic biology to program information processing capabilities in cells. While these designs can function predictably in controlled laboratory environments, the reliability of these devices in complex, temporally changing environments has not yet been characterized. As human society faces global challenges in agriculture, human health and energy, synthetic biology should develop predictive design principles for biological systems operating in complex environments. Natural biological systems have evolved mechanisms to overcome innumerable and diverse environmental challenges. Evolutionary design rules should be extracted and adapted to engineer stable and predictable ecological function. We highlight examples of natural biological responses spanning the cellular, population and microbial community levels that show promise in synthetic biology contexts. We argue that synthetic circuits embedded in host organisms or designed ecologies informed by suitable measurement of biotic and abiotic environmental parameters could be used as engineering substrates to achieve target functions in complex environments. Successful implementation of these methods will broaden the context in which synthetic biological systems can be applied to solve important problems. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:928 / 944
页数:17
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