Department of Electrical Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, United States.
Department of Biomedical Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, United States.
ACS Sens. 2022 Mar 25;7(3):900-911. doi: 10.1021/acssensors.2c00024. Epub 2022 Mar 3.
Clustered regularly interspaced short palindromic repeats (CRISPR)-based nucleic acid-sensing systems have grown rapidly in the past few years. Nevertheless, an objective approach to benchmark the performances of different CRISPR sensing systems is lacking due to the heterogeneous experimental setup. Here, we developed a quantitative CRISPR sensing figure of merit (FOM) to compare different CRISPR methods and explore performance improvement strategies. The CRISPR sensing FOM is defined as the product of the limit of detection (LOD) and the associated CRISPR reaction time (). A smaller FOM means that the method can detect smaller target quantities faster. We found that there is a tradeoff between the LOD of the assay and the required reaction time. With the proposed CRISPR sensing FOM, we evaluated five strategies to improve the CRISPR-based sensing: preamplification, enzymes of higher catalytic efficiency, multiple crRNAs, digitalization, and sensitive readout systems. We benchmarked the FOM performances of 57 existing studies and found that the effectiveness of these strategies on improving the FOM is consistent with the model prediction. In particular, we found that digitalization is the most promising amplification-free method for achieving comparable FOM performances (∼1 fM·min) as those using preamplification. The findings here would have broad implications for further optimization of the CRISPR-based sensing.
近年来,基于成簇规律间隔短回文重复序列(CRISPR)的核酸传感系统发展迅速。然而,由于实验设置的异质性,缺乏一种客观的方法来对不同的 CRISPR 传感系统的性能进行基准测试。在这里,我们开发了一种定量的 CRISPR 传感优值(FOM)来比较不同的 CRISPR 方法,并探索性能改进策略。CRISPR 传感 FOM 定义为检测限(LOD)和相关 CRISPR 反应时间()的乘积。较小的 FOM 意味着该方法可以更快地检测到较小的目标数量。我们发现检测限和所需反应时间之间存在权衡。使用提出的 CRISPR 传感 FOM,我们评估了五种提高基于 CRISPR 的传感的策略:预扩增、催化效率更高的酶、多个 crRNA、数字化和灵敏的读出系统。我们对 57 项现有研究的 FOM 性能进行了基准测试,发现这些策略对提高 FOM 的有效性与模型预测一致。特别是,我们发现数字化是最有前途的无扩增方法,可以实现与使用预扩增相当的 FOM 性能(∼1 fM·min)。这里的发现将对进一步优化基于 CRISPR 的传感具有广泛的意义。