An Isotope‐Labeled Single‐Cell Raman Spectroscopy Approach for Tracking the Physiological Evolution Trajectory of Bacteria toward Antibiotic Resistance

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 D2O‐labeled Raman spectroscopy, advanced multivariate analy...

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Veröffentlicht in:Angewandte Chemie 2023-03, Vol.135 (14), p.n/a
Hauptverfasser: Yang, Kai, Xu, Fei, Zhu, Longji, Li, Hongzhe, Sun, Qian, Yan, Aixin, Ren, Bin, Zhu, Yong‐Guan, Cui, Li
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Sprache:eng
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Zusammenfassung: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 D2O‐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. A single‐cell approach integrating D2O‐labeled Raman spectroscopy, advanced multivariate analysis and genotypic profiling was developed to in situ track the highly heterogeneous and dynamic physiological evolution trajectory of bacteria toward antibiotic resistance. The physiological diversification of single cells into four subpopulations preceding resistance from an isogeneic population was sensitively captured and their dynamic shift was tracked.
ISSN:0044-8249
1521-3757
DOI:10.1002/ange.202217412