Institute of Mass Spectrometry, School of Material Science and Chemical Engineering, Ningbo University, Ningbo, Zhejiang, China.
Department of Intensive Care Unit, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.
Microbiol Spectr. 2023 Aug 17;11(4):e0528222. doi: 10.1128/spectrum.05282-22. Epub 2023 Jul 3.
Methicillin-resistant Staphylococcus aureus (MRSA) is a clinical threat with high morbidity and mortality. Here, we describe a new simple, rapid identification method for MRSA using oxacillin sodium salt, a cell wall synthesis inhibitor, combined with Gram staining and machine vision (MV) analysis. Gram staining classifies bacteria as positive (purple) or negative (pink) according to the cell wall structure and chemical composition. In the presence of oxacillin, the integrity of the cell wall for methicillin-susceptible S. aureus (MSSA) was destroyed immediately and appeared Gram negative. In contrast, MRSA was relatively stable and appeared Gram positive. This color change can be detected by MV. The feasibility of this method was demonstrated in 150 images of the staining results for 50 clinical S. aureus strains. Based on effective feature extraction and machine learning, the accuracies of the linear linear discriminant analysis (LDA) model and nonlinear artificial neural network (ANN) model for MRSA identification were 96.7% and 97.3%, respectively. Combined with MV analysis, this simple strategy improved the detection efficiency and significantly shortened the time needed to detect antibiotic resistance. The whole process can be completed within 1 h. Unlike the traditional antibiotic susceptibility test, overnight incubation is avoided. This new strategy could be used for other bacteria and represents a new rapid method for detection of clinical antibiotic resistance. Oxacillin sodium salt destroys the integrity of the cell wall of MSSA immediately, appearing Gram negative, whereas MRSA is relatively stable and still appears Gram positive. This color change can be detected by microscopic examination and MV analysis. This new strategy has significantly reduced the time to detect resistance. The results show that using oxacillin sodium salt combined with Gram staining and MV analysis is a new, simple and rapid method for identification of MRSA.
耐甲氧西林金黄色葡萄球菌(MRSA)是一种具有高发病率和死亡率的临床威胁。在这里,我们描述了一种使用苯唑西林钠(一种细胞壁合成抑制剂)结合革兰氏染色和机器视觉(MV)分析的新的简单、快速的 MRSA 鉴定方法。革兰氏染色根据细胞壁结构和化学成分将细菌分类为阳性(紫色)或阴性(粉色)。在苯唑西林存在的情况下,甲氧西林敏感金黄色葡萄球菌(MSSA)的细胞壁完整性立即被破坏,呈现革兰氏阴性。相比之下,MRSA 相对稳定,呈现革兰氏阳性。这种颜色变化可以通过 MV 检测到。该方法的可行性在 50 株临床金黄色葡萄球菌染色结果的 150 张图像中得到了验证。基于有效的特征提取和机器学习,线性判别分析(LDA)模型和非线性人工神经网络(ANN)模型对 MRSA 鉴定的准确率分别为 96.7%和 97.3%。结合 MV 分析,这种简单的策略提高了检测效率,显著缩短了检测抗生素耐药性所需的时间。整个过程可以在 1 小时内完成。与传统的抗生素药敏试验不同,避免了过夜孵育。这种新策略可用于其他细菌,并代表了一种新的快速临床抗生素耐药性检测方法。苯唑西林钠立即破坏 MSSA 细胞壁的完整性,呈现革兰氏阴性,而 MRSA 相对稳定,仍呈革兰氏阳性。这种颜色变化可以通过显微镜检查和 MV 分析检测到。这种新策略大大缩短了检测耐药性的时间。结果表明,使用苯唑西林钠结合革兰氏染色和 MV 分析是鉴定 MRSA 的一种新的、简单和快速的方法。