Design and assembly of DNA molecules using multi-objective optimization

A Linear Programming-Based Strategy to Save Pipette Tips in Automated DNA Assembly

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 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$59\%$\end{document} 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

RoboMoClo: A Robotics-Assisted Modular Cloning Framework for Multiple Gene Assembly in Biofoundry

Efficient and versatile DNA assembly frameworks have had an impact on promoting synthetic biology to build complex biological systems. To accelerate system development, laboratory automation (or biofoundry) provides an opportunity to construct organisms and DNA assemblies via computer-aided design. However, a modular cloning (MoClo) system for multiple DNA assemblies limits the biofoundry workflow in terms of simplicity and feasibility by preparing the number of cloning materials such as destination vectors prior to the automation process. Herein, we propose robot-assisted MoClo (RoboMoClo) to accelerate a synthetic biology project with multiple gene expressions at the biofoundry. The architecture of the RoboMoClo framework provides a hybrid strategy of hierarchical gene assembly and iterative gene assembly, and fewer destination vectors compared with other MoClo systems. An industrial bacterium, Corynebacterium glutamicum, was used as a model host for RoboMoClo. After building a biopart library (promoter and terminator; level 0) and evaluating its features (level 1), various transcriptional directions in multiple gene assemblies (level 2) were studied using the RoboMoClo vectors. Among the constructs, the convergent construct exhibited potential transcriptional interference through the collision of RNA polymerases. To study design of experiment-guided lycopene biosynthesis in C. glutamicum (levels 1, 2, and 3), the biofoundry-assisted multiple gene assembly was demonstrated as a proof-of-concept by constructing various sub-pathway units (level 2) and pathway units (level 3) for C. glutamicum. The RoboMoClo framework provides an improved MoClo toolkit for laboratory automation in a synthetic biology application.