Ever since gene editing became feasible, researchers and health officials have sought tools that can quickly and reliably distinguish genetically modified organisms from those that are naturally occurring. Though scientists can make these determinations after careful genetic analysis, the research and national security communities have shared a longstanding unmet need for a streamlined screening tool. Following the emergence of SARS-CoV-2, the world at large became aware of this need.
Now, such tools are being built.
A suite of techniques – one lab-based platform and four computational DNA sequence analysis models – was developed and refined over the course of a six-year program funded by the United States Intelligence Advanced Research Projects Activity (IARPA). These approaches have the potential to dramatically shift current screening capabilities for detecting engineered organisms.
Susan Celniker’s team at Lawrence Berkeley National Laboratory (Berkeley Lab) was chosen to lead the testing and evaluation phase of the program, called Finding Engineering-Linked Indicators, or FELIX. She and her colleagues designed and produced increasingly challenging biological samples and assessed how well the tools made by participating academic and industry groups performed.
Read more at Berkeley National Laboratory
