Standardizing Automated DNA Assembly: Best Practices, Metrics, and Protocols Using Robots. (June 2019)

• Record Type: Journal Article
• Authors: Walsh, David I.; Pavan, Marilene; Ortiz, Luis; Wick, Scott; Bobrow, Johanna; Guido, Nicholas J.; Leinicke, Sarah; Fu, Dany; Pandit, Shreya; Qin, Lucy; Carr, Peter A.; Densmore, Douglas
• Is Part Of: SLAS technology. Volume 24:Number 3(2019)
• Page Start: 282
• Page End: 290
• Publication Date: 2019-06
• Subjects: DNA assembly -- liquid-handling robots -- metrics -- synthetic biology -- standards; Medical laboratory technology -- Periodicals; Laboratories -- Equipment and supplies -- Periodicals; Diagnosis, Laboratory -- Periodicals; 616.075
• DOI: 10.1177/2472630318825335
• Languages: English
• ISSNs: 2472-6303

Abstract

The advancement of synthetic biology requires the ability to create new DNA sequences to produce unique behaviors in biological systems. Automation is increasingly employed to carry out well-established assembly methods of DNA fragments in a multiplexed, high-throughput fashion, allowing many different configurations to be tested simultaneously. However, metrics are required to determine when automation is warranted based on factors such as assembly methodology, protocol details, and number of samples. The goal of our synthetic biology automation work is to develop and test protocols, hardware, and software to investigate and optimize DNA assembly through quantifiable metrics. We performed a parameter analysis of DNA assembly to develop a standardized, highly efficient, and reproducible MoClo protocol, suitable to be used both manually and with liquid-handling robots. We created a key DNA assembly metric (Q-metric) to characterize a given automation method's advantages over conventional manual manipulations with regard to researchers' highest-priority parameters: output, cost, and time. A software tool called Puppeteer was developed to formally capture these metrics, help define the assembly design, and provide human and robotic liquid-handling instructions. Altogether, we contribute to a growing foundation of standardizing practices, metrics, and protocols for automating DNA assembly.