Biomedical engineers at Brown University announced on July 21 the development of a fully automated workflow that simplifies and accelerates the preparation of bacterial samples for genetic sequencing. The new method, called Pathogen2Read, aims to address a critical bottleneck in the sequencing process and could allow smaller laboratories to participate more effectively in outbreak-monitoring networks run by the U.S. Food and Drug Administration and the Centers for Disease Control.
Kathryn Whitehead, a graduate student in Brown's School of Engineering who led the work, said, "Next-generation sequencing has become a staple in outbreak detection and prevention. But sample preparation involves labor-intensive manual preparation and culture isolation, which can delay real-time outbreak responses. Our laboratory has developed what is, to our knowledge, the first fully automated scientific method that bypasses these limitations."
The research describing and testing Pathogen2Read was developed with collaborators at the FDA and funding from Revvity, a biotech firm. It is published in BMC Genomics. Next-generation sequencing enables scientists to rapidly sequence entire genomes of potential pathogens within hours or days, allowing researchers to quickly identify causes of illness outbreaks or detect new mutations.
However, preparing samples for sequencing typically requires multiple steps including isolating microbes, cell lysis, DNA extraction and purification—processes that can take eight to ten hours of hands-on work plus up to sixteen hours waiting time. Mistakes may require repeating the process entirely.
Pathogen2Read uses custom software and an enzyme cocktail that allows a desktop liquid-handling machine to perform all DNA sample prep steps automatically after an operator loads raw samples onto a plate. This reduces hands-on time from nearly one day to under 45 minutes while producing sequencer-ready DNA libraries after six hours.
Whitehead said collaboration with federal agencies was key: "The reason we're so excited about this is it was developed with real-world impact in mind...being able to get their responses and their input on what they need to see has allowed us to develop a method that actually can be used." Co-author Anubhav Tripathi added, "Because you're looking for small mutations that may be involved in drug resistance...the quality of the sample preparation is critically important."
