Department of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia 24061, United States.
Department of Bioengineering, University of California, Riverside, California 92521, United States.
Anal Chem. 2024 Nov 12;96(45):18301-18310. doi: 10.1021/acs.analchem.4c05177. Epub 2024 Oct 30.
The accurate and effective determination of antimicrobial resistance is essential to limiting the spread of infectious diseases and ensuring human health. Herein, a simple, accurate, and high-throughput phage-based colorimetric sensing strategy was developed for antimicrobial susceptibility testing (AST). Taking advantage of the CRISPR/Cas9 system, the genome of the T4 phage was modularly engineered to carry lacZ-α (lacZa), a marker gene encoding the α-fragment of β-galactosidase (β-gal). T4 phages were identified by blue-white selection and then used for a biosensing application. In this strategy, the bacterial solution is exposed to the T4 phage, causing target bacteria to overexpress β-gal. Upon the addition of a colorimetric substrate, the β-gal initiates an enzymatic reaction, resulting in a solution color change from yellow to red. This sensing strategy offers a visual way to monitor bacterial growth in the presence of antibiotics, enabling the determination of bacterial antimicrobial susceptibility. As a proof of concept, our developed sensing strategy was successfully applied to identify 9 different multidrug-resistant () in urine samples with 100% specificity. Compared with conventional disk diffusion susceptibility tests, the engineered phage-based sensing strategy can shorten the detection time by at least half without losing detection sensitivity, providing an alternative high-throughput method for AST in clinical diagnosis.
准确有效地确定抗菌药物耐药性对于限制传染病的传播和确保人类健康至关重要。在此，开发了一种简单、准确、高通量的基于噬菌体的比色传感策略，用于抗菌药物敏感性测试（AST）。利用 CRISPR/Cas9 系统，对 T4 噬菌体的基因组进行了模块化工程改造，使其携带 lacZ-α（lacZa），这是一个编码β-半乳糖苷酶（β-gal）α 片段的标记基因。T4 噬菌体通过蓝白选择进行鉴定，然后用于生物传感应用。在该策略中，将细菌溶液暴露于 T4 噬菌体下，导致靶细菌过度表达β-gal。加入比色底物后，β-gal 引发酶促反应，导致溶液颜色从黄色变为红色。这种传感策略提供了一种可视化的方法来监测抗生素存在下的细菌生长，从而确定细菌对抗菌药物的敏感性。作为概念验证，我们开发的传感策略成功应用于识别尿液样本中的 9 种不同的多药耐药菌（MDR），特异性为 100%。与传统的圆盘扩散药敏试验相比，基于工程噬菌体的传感策略可以至少缩短一半的检测时间，而不会降低检测灵敏度，为临床诊断中的 AST 提供了一种替代的高通量方法。
