| Autor: |
Xixian Wang, Lihui Ren, Zhidian Diao, Yuehui He, Jiaping Zhang, Min Liu, Yuandong Li, Lijun Sun, Rongze Chen, Yuetong Ji, Jian Xu, Bo Ma |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Advanced Science, Vol 10, Iss 16, Pp n/a-n/a (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2198-3844 |
| DOI: |
10.1002/advs.202207497 |
| Popis: |
Abstract A full‐spectrum spontaneous single‐cell Raman spectrum (fs‐SCRS) captures the metabolic phenome for a given cellular state of the cell in a label‐free, landscape‐like manner. Herein a positive dielectrophoresis induced deterministic lateral displacement‐based Raman flow cytometry (pDEP‐DLD‐RFC) is established. This robust flow cytometry platform utilizes a periodical positive dielectrophoresis induced deterministic lateral displacement (pDEP‐DLD) force that is exerted to focus and trap fast‐moving single cells in a wide channel, which enables efficient fs‐SCRS acquisition and extended stable running time. It automatically produces deeply sampled, heterogeneity‐resolved, and highly reproducible ramanomes for isogenic cell populations of yeast, microalgae, bacteria, and human cancers, which support biosynthetic process dissection, antimicrobial susceptibility profiling, and cell‐type classification. Moreover, when coupled with intra‐ramanome correlation analysis, it reveals state‐ and cell‐type‐specific metabolic heterogeneity and metabolite‐conversion networks. The throughput of ≈30–2700 events min−1 for profiling both nonresonance and resonance marker bands in a fs‐SCRS, plus the >5 h stable running time, represent the highest performance among reported spontaneous Raman flow cytometry (RFC) systems. Therefore, pDEP‐DLD‐RFC is a valuable new tool for label‐free, noninvasive, and high‐throughput profiling of single‐cell metabolic phenomes. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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