Raytheon BBN, Cambridge, Massachusetts 02138, United States.
Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States.
ACS Synth Biol. 2024 Apr 19;13(4):1105-1115. doi: 10.1021/acssynbio.3c00398. Epub 2024 Mar 12.
Synthetic biology is creating genetically engineered organisms at an increasing rate for many potentially valuable applications, but this potential comes with the risk of misuse or accidental release. To begin to address this issue, we have developed a system called GUARDIAN that can automatically detect signatures of engineering in DNA sequencing data, and we have conducted a blinded test of this system using a curated Test and Evaluation (T&E) data set. GUARDIAN uses an ensemble approach based on the guiding principle that no single approach is likely to be able to detect engineering with perfect accuracy. Critically, ensembling enables GUARDIAN to detect sequence inserts in 13 target organisms with a high degree of specificity that requires no subject matter expert (SME) review.
合成生物学正在以越来越快的速度创造基因工程生物体,用于许多有潜在价值的应用,但这种潜力伴随着被滥用或意外释放的风险。为了开始解决这个问题,我们开发了一个名为 GUARDIAN 的系统,它可以自动检测 DNA 测序数据中的工程特征,并且我们已经使用经过精心策划的测试和评估 (T&E) 数据集对该系统进行了盲测。GUARDIAN 使用基于以下指导原则的集成方法,即没有单一方法能够以完美的准确性检测工程。至关重要的是,集成使 GUARDIAN 能够以无需主题专家 (SME) 审查的高度特异性检测 13 个目标生物中的序列插入。