Buildout and integration of an automated high-throughput CLIA laboratory for SARS-CoV-2 testing on a large urban campus.

In 2019, the first cases of SARS-CoV-2 were detected in Wuhan, China, and by early 2020 the first cases were identified in the United States. SARS-CoV-2 infections increased in the US causing many states to implement stay-at-home orders and additional safety precautions to mitigate potential outbreaks. As policies changed throughout the pandemic and restrictions lifted, there was an increase in demand for COVID-19 testing which was costly, difficult to obtain, or had long turn-around times. Some academic institutions, including Boston University (BU), created an on-campus COVID-19 screening protocol as part of a plan for the safe return of students, faculty, and staff to campus with the option for in-person classes. At BU, we put together an automated high-throughput clinical testing laboratory with the capacity to run 45,000 individual tests weekly by Fall of 2020, with a purpose-built clinical testing laboratory, a multiplexed reverse transcription PCR (RT-qPCR) test, robotic instrumentation, and trained staff. There were many challenges including supply chain issues for personal protective equipment and testing materials in addition to equipment that were in high demand. The BU Clinical Testing Laboratory (CTL) was operational at the start of Fall 2020 and performed over 1 million SARS-CoV-2 PCR tests during the 2020-2021 academic year.

Standardizing Automated DNA Assembly: Best Practices, Metrics, and Protocols Using Robots.

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.