Cox Robert Sidney, Madsen Curtis, McLaughlin James Alastair, Nguyen Tramy, Roehner Nicholas, Bartley Bryan, Beal Jacob, Bissell Michael, Choi Kiri, Clancy Kevin, Grünberg Raik, Macklin Chris, Misirli Goksel, Oberortner Ernst, Pocock Matthew, Samineni Meher, Zhang Michael, Zhang Zhen, Zundel Zach, Gennari John H, Myers Chris, Sauro Herbert, Wipat Anil
Prospect Bio, Brisbane, CA, USA.
Boston University, Boston, MA, USA.
J Integr Bioinform. 2018 Apr 2;15(1):20180001. doi: 10.1515/jib-2018-0001.
Synthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems would be to improve the exchange of information about designed systems between laboratories. The synthetic biology open language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.2.0 of SBOL that builds upon version 2.1.0 published in last year's JIB special issue. In particular, SBOL 2.2.0 includes improved description and validation rules for genetic design provenance, an extension to support combinatorial genetic designs, a new class to add non-SBOL data as attachments, a new class for genetic design implementations, and a description of a methodology to describe the entire design-build-test-learn cycle within the SBOL data model.
合成生物学通过将工程原理应用于生物系统设计,建立在遗传学、分子生物学和代谢工程的技术及成果之上。该领域仍面临诸多重大挑战,包括研发周期长、失败率高和可重复性差等问题。改善这些问题的一种方法是加强实验室之间关于设计系统的信息交流。合成生物学开放语言(SBOL)已被开发为一种标准,以支持合成生物学中生物设计信息的规范和交换,满足了其他现有标准无法满足的需求。本文详细介绍了SBOL 2.2.0版本,它基于去年《合成生物学杂志》特刊中发布的2.1.0版本。特别是,SBOL 2.2.0包括了对基因设计来源的改进描述和验证规则、支持组合基因设计的扩展、用于以附件形式添加非SBOL数据的新类、基因设计实现的新类,以及在SBOL数据模型中描述整个设计-构建-测试-学习周期的方法说明。