Yang Kai, Xu Fei, Zhu Longji, Li Hongzhe, Sun Qian, Yan Aixin, Ren Bin, Zhu Yong-Guan, Cui Li
Key Lab of Urban Environment and Health, Fujian Key Laboratory of Watershed Ecology, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China.
School of Biological Sciences, The University of Hong Kong, Pokfulam Road, Hong Kong, China.
Angew Chem Int Ed Engl. 2023 Mar 27;62(14):e202217412. doi: 10.1002/anie.202217412. Epub 2023 Feb 20.
Understanding evolution of antibiotic resistance is vital for containing its global spread. Yet our ability to in situ track highly heterogeneous and dynamic evolution is very limited. Here, we present a new single-cell approach integrating D O-labeled Raman spectroscopy, advanced multivariate analysis, and genotypic profiling to in situ track physiological evolution trajectory toward resistance. Physiological diversification of individual cells from isogenic population with cyclic ampicillin treatment is captured. Advanced multivariate analysis of spectral changes classifies all individual cells into four subsets of sensitive, intrinsic tolerant, evolved tolerant and resistant. Remarkably, their dynamic shifts with evolution are depicted and spectral markers of each state are identified. Genotypic analysis validates the phenotypic shift and provides insights into the underlying genetic basis. The new platform advances rapid phenotyping resistance evolution and guides evolution control.
了解抗生素耐药性的演变对于遏制其在全球的传播至关重要。然而，我们在原位追踪高度异质和动态演变的能力非常有限。在此，我们提出了一种新的单细胞方法，该方法整合了氘代拉曼光谱、先进的多变量分析和基因型分析，以原位追踪向耐药性发展的生理演变轨迹。通过对同基因群体进行循环氨苄青霉素处理，捕获了单个细胞的生理多样性。对光谱变化进行的先进多变量分析将所有单个细胞分为敏感、固有耐受、进化耐受和耐药四个亚组。值得注意的是，描绘了它们随进化的动态变化，并确定了每种状态的光谱标记。基因型分析验证了表型变化，并深入了解了潜在的遗传基础。这个新平台推动了耐药性演变的快速表型分析，并指导了进化控制。
