Zhang Weifeng, Sun Hongyi, He Shipei, Chen Xun, Yao Lin, Zhou Liqun, Wang Yi, Wang Pu, Hong Weili
Institute of Medical Photonics, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China.
School of Engineering Medicine, Beihang University, Beijing, China.
Front Microbiol. 2022 Aug 24;13:874966. doi: 10.3389/fmicb.2022.874966. eCollection 2022.
Rapid identification and antimicrobial susceptibility testing (AST) of bacteria are key interventions to curb the spread and emergence of antimicrobial resistance. The current gold standard identification and AST methods provide comprehensive diagnostic information but often take 3 to 5 days. Here, a compound Raman microscopy (CRM), which integrates Raman spectroscopy and stimulated Raman scattering microscopy in one system, is presented and demonstrated for rapid identification and AST of pathogens in urine. We generated an extensive bacterial Raman spectral dataset and applied deep learning to identify common clinical bacterial pathogens. In addition, we employed stimulated Raman scattering microscopy to quantify bacterial metabolic activity to determine their antimicrobial susceptibility. For proof-of-concept, we demonstrated an integrated assay to diagnose urinary tract infection pathogens, and . Notably, the CRM system has the unique ability to provide Gram-staining classification and AST results within ~3 h directly from urine samples and shows great potential for clinical applications.
细菌的快速鉴定和抗菌药敏试验（AST）是遏制抗菌药物耐药性传播和出现的关键干预措施。当前的金标准鉴定和AST方法可提供全面的诊断信息，但通常需要3至5天。在此，我们展示了一种复合拉曼显微镜（CRM），它将拉曼光谱和受激拉曼散射显微镜集成在一个系统中，并用于尿液中病原体的快速鉴定和AST。我们生成了一个广泛的细菌拉曼光谱数据集，并应用深度学习来识别常见的临床细菌病原体。此外，我们采用受激拉曼散射显微镜来量化细菌代谢活性，以确定它们的抗菌药敏性。为了进行概念验证，我们展示了一种用于诊断尿路感染病原体的综合检测方法。值得注意的是，CRM系统具有独特的能力，可直接从尿液样本中在约3小时内提供革兰氏染色分类和AST结果，并显示出巨大的临床应用潜力。
