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一种基于线性规划的策略,用于在自动化DNA组装中节省移液器吸头。

A linear programming-based strategy to save pipette tips in automated DNA assembly.

作者信息

Sechkar Kirill, Tuza Zoltan A, Stan Guy-Bart

机构信息

Department of Bioengineering, Imperial College London, London SW7 2AZ, UK.

出版信息

Synth Biol (Oxf). 2022 Apr 11;7(1):ysac004. doi: 10.1093/synbio/ysac004. eCollection 2022.

Abstract

Laboratory automation and mathematical optimization are key to improving the efficiency of synthetic biology research. While there are algorithms optimizing the construct designs and synthesis strategies for DNA assembly, the optimization of how DNA assembly reaction mixes are prepared remains largely unexplored. Here, we focus on reducing the pipette tip consumption of a liquid-handling robot as it delivers DNA parts across a multi-well plate where several constructs are being assembled in parallel. We propose a linear programming formulation of this problem based on the capacitated vehicle routing problem, as well as an algorithm which applies a linear programming solver to our formulation, hence providing a strategy to prepare a given set of DNA assembly mixes using fewer pipette tips. The algorithm performed well in randomly generated and real-life scenarios concerning several modular DNA assembly standards, proving to be capable of reducing the pipette tip consumption by up to [Formula: see text] in large-scale cases. Combining automatic process optimization and robotic liquid handling, our strategy promises to greatly improve the efficiency of DNA assembly, either used alone or combined with other algorithmic DNA assembly optimization methods. Graphical Abstract.

摘要

实验室自动化和数学优化是提高合成生物学研究效率的关键。虽然有算法可优化DNA组装的构建体设计和合成策略,但DNA组装反应混合物的制备方式的优化在很大程度上仍未得到探索。在这里,我们专注于减少液体处理机器人在多微孔板中输送DNA片段时的移液器吸头消耗,在该多微孔板中多个构建体正在并行组装。我们基于容量车辆路径问题提出了这个问题的线性规划公式,以及一种将线性规划求解器应用于我们公式的算法,从而提供了一种使用更少移液器吸头来制备给定的一组DNA组装混合物的策略。该算法在涉及几种模块化DNA组装标准的随机生成和实际场景中表现良好,证明在大规模情况下能够将移液器吸头消耗减少多达[公式:见正文]。结合自动过程优化和机器人液体处理,我们的策略有望大大提高DNA组装的效率,无论是单独使用还是与其他算法DNA组装优化方法结合使用。图形摘要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1836/9074407/1625207076a4/ysac004f1.jpg

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