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- Publisher Website: 10.1002/anie.202217412
- Scopus: eid_2-s2.0-85148361899
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Article: An Isotope-Labeled Single-Cell Raman Spectroscopy Approach for Tracking the Physiological Evolution Trajectory of Bacteria toward Antibiotic Resistance
Title | An Isotope-Labeled Single-Cell Raman Spectroscopy Approach for Tracking the Physiological Evolution Trajectory of Bacteria toward Antibiotic Resistance |
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Authors | |
Keywords | Antibiotic Resistance Antibiotic Tolerance Evolution Trajectory Physiological Response Single Cell Raman Spectroscopy |
Issue Date | 2-Feb-2023 |
Publisher | Wiley |
Citation | Angewandte Chemie International Edition, 2023, v. 62, n. 14 How to Cite? |
Abstract | 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. |
Persistent Identifier | http://hdl.handle.net/10722/338637 |
ISSN | 2023 Impact Factor: 16.1 2023 SCImago Journal Rankings: 5.300 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Yang, K | - |
dc.contributor.author | Xu, F | - |
dc.contributor.author | Zhu, L | - |
dc.contributor.author | Li, H | - |
dc.contributor.author | Sun, Q | - |
dc.contributor.author | Yan, A | - |
dc.contributor.author | Ren, B | - |
dc.contributor.author | Zhu, YG | - |
dc.contributor.author | Cui, L | - |
dc.date.accessioned | 2024-03-11T10:30:22Z | - |
dc.date.available | 2024-03-11T10:30:22Z | - |
dc.date.issued | 2023-02-02 | - |
dc.identifier.citation | Angewandte Chemie International Edition, 2023, v. 62, n. 14 | - |
dc.identifier.issn | 1433-7851 | - |
dc.identifier.uri | http://hdl.handle.net/10722/338637 | - |
dc.description.abstract | 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. | - |
dc.language | eng | - |
dc.publisher | Wiley | - |
dc.relation.ispartof | Angewandte Chemie International Edition | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Antibiotic Resistance | - |
dc.subject | Antibiotic Tolerance | - |
dc.subject | Evolution Trajectory | - |
dc.subject | Physiological Response | - |
dc.subject | Single Cell Raman Spectroscopy | - |
dc.title | An Isotope-Labeled Single-Cell Raman Spectroscopy Approach for Tracking the Physiological Evolution Trajectory of Bacteria toward Antibiotic Resistance | - |
dc.type | Article | - |
dc.identifier.doi | 10.1002/anie.202217412 | - |
dc.identifier.scopus | eid_2-s2.0-85148361899 | - |
dc.identifier.volume | 62 | - |
dc.identifier.issue | 14 | - |
dc.identifier.eissn | 1521-3773 | - |
dc.identifier.isi | WOS:000935218300001 | - |
dc.identifier.issnl | 1433-7851 | - |