• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

培养的人肺上皮细胞(A549)的光谱研究:活细胞与死细胞

Spectroscopic study of human lung epithelial cells (A549) in culture: living cells versus dead cells.

作者信息

Notingher I, Verrier S, Haque S, Polak J M, Hench L L

机构信息

Imperial College of Science, Technology and Medicine, Department of Materials, South Kensington Campus, London SW7 2BP, United Kingdom.

出版信息

Biopolymers. 2003;72(4):230-40. doi: 10.1002/bip.10378.

DOI:10.1002/bip.10378
PMID:12833477
Abstract

The noninvasive analysis of living cells grown on 3-dimensional scaffold materials is a key point in tissue engineering. In this work we show the capability of Raman spectroscopy for use as a noninvasive method to distinguish cells at different stages of the cell cycle and living cells from dead cells. The spectral differences between cells in different stages of the cell cycle are characterized mainly by variations in DNA vibrations at 782, 788, and 1095 cm(-1). The Raman spectrum of dead human lung derived (A549 line) cells indicates the breakdown of both phosphodiester bonds and DNA bases. The most sensitive peak for identifying dead cells is the 788 cm(-1) peak corresponding to DNA Obond;Pbond;O backbone stretching. The magnitude of this peak is reduced by 80% in the spectrum of dead cells. Changes in protein peaks suggest significant conformational changes; for example, the magnitude of the 1231 cm(-1) peak assigned to random coils is reduced by 63% for dead cells. The sharp peak of phenylalanine at 1005 cm(-1) drops to half, indicating a decrease of stable proteins associated with cell death. The differences in the 1190-1385 cm(-1) spectral region also suggest a decrease in the amount of nucleic acids and proteins. Using curve fitting, we quantify these spectral differences that can be used as markers of cell death.

摘要

对生长在三维支架材料上的活细胞进行无创分析是组织工程中的一个关键点。在这项工作中,我们展示了拉曼光谱作为一种无创方法区分细胞周期不同阶段的细胞以及活细胞与死细胞的能力。细胞周期不同阶段的细胞之间的光谱差异主要由782、788和1095 cm⁻¹处DNA振动的变化来表征。人源肺(A549系)死细胞的拉曼光谱表明磷酸二酯键和DNA碱基均发生了断裂。用于识别死细胞的最敏感峰是对应于DNA O键;P键;O主链拉伸的788 cm⁻¹峰。在死细胞光谱中,该峰的强度降低了80%。蛋白质峰的变化表明存在显著的构象变化;例如,归属于无规卷曲的1231 cm⁻¹峰的强度在死细胞中降低了63%。苯丙氨酸在1005 cm⁻¹处的尖锐峰降至一半,表明与细胞死亡相关的稳定蛋白质减少。1190 - 1385 cm⁻¹光谱区域的差异也表明核酸和蛋白质的量减少。通过曲线拟合,我们对这些可作为细胞死亡标志物的光谱差异进行了量化。

相似文献

1
Spectroscopic study of human lung epithelial cells (A549) in culture: living cells versus dead cells.培养的人肺上皮细胞(A549)的光谱研究:活细胞与死细胞
Biopolymers. 2003;72(4):230-40. doi: 10.1002/bip.10378.
2
In situ monitoring of cell death using Raman microspectroscopy.利用拉曼光谱显微镜对细胞死亡进行原位监测。
Biopolymers. 2004;74(1-2):157-62. doi: 10.1002/bip.20063.
3
New detection system for toxic agents based on continuous spectroscopic monitoring of living cells.基于对活细胞进行连续光谱监测的新型毒剂检测系统。
Biosens Bioelectron. 2004 Nov 1;20(4):780-9. doi: 10.1016/j.bios.2004.04.008.
4
IR spectroscopic characteristics of cell cycle and cell death probed by synchrotron radiation based Fourier transform IR spectromicroscopy.基于同步辐射的傅里叶变换红外光谱显微镜探测细胞周期和细胞死亡的红外光谱特征。
Biopolymers. 2000;57(6):329-35. doi: 10.1002/1097-0282(2000)57:6<329::AID-BIP20>3.0.CO;2-2.
5
Cell (A549)-particle (Jasada Bhasma) interactions using Raman spectroscopy.利用拉曼光谱法研究细胞(A549)与颗粒(贾萨达·巴斯马)的相互作用。
Biopolymers. 2008 Jun;89(6):555-64. doi: 10.1002/bip.20947.
6
Characterization of human breast epithelial cells by confocal Raman microspectroscopy.利用共聚焦拉曼显微光谱对人乳腺上皮细胞进行表征
Cancer Detect Prev. 2006;30(6):515-22. doi: 10.1016/j.cdp.2006.10.007. Epub 2006 Nov 20.
7
Non-invasive analysis of cell cycle dynamics in single living cells with Raman micro-spectroscopy.利用拉曼显微光谱对单个活细胞的细胞周期动力学进行无创分析。
J Cell Biochem. 2008 Jul 1;104(4):1427-38. doi: 10.1002/jcb.21720.
8
Variability in Raman spectra of single human tumor cells cultured in vitro: correlation with cell cycle and culture confluency.体外培养的单个人类肿瘤细胞的喇曼光谱变化:与细胞周期和培养密度的相关性。
Appl Spectrosc. 2010 Aug;64(8):871-87. doi: 10.1366/000370210792080966.
9
Three dimensional collagen gels as a cell culture matrix for the study of live cells by Raman spectroscopy.三维胶原凝胶作为一种细胞培养基质,用于通过拉曼光谱研究活细胞。
Analyst. 2010 Jul;135(7):1697-703. doi: 10.1039/c0an00060d. Epub 2010 Apr 30.
10
Raman spectroscopy of single human tumour cells exposed to ionizing radiation in vitro.体外放射暴露后人肿瘤细胞的拉曼光谱研究。
Phys Med Biol. 2011 Jan 7;56(1):19-38. doi: 10.1088/0031-9155/56/1/002. Epub 2010 Nov 30.

引用本文的文献

1
SERS-assisted characterization of cell biomass from biofilm-forming strains using chemometric tools.使用化学计量学工具通过表面增强拉曼光谱辅助表征生物膜形成菌株的细胞生物量。
RSC Adv. 2025 Feb 10;15(6):4581-4592. doi: 10.1039/d4ra06267a. eCollection 2025 Feb 6.
2
Unveiling the Molecular Secrets: A Comprehensive Review of Raman Spectroscopy in Biological Research.揭开分子奥秘:生物研究中拉曼光谱的全面综述
ACS Omega. 2024 Dec 3;9(51):50049-50063. doi: 10.1021/acsomega.4c00591. eCollection 2024 Dec 24.
3
Sensing the Future-Frontiers in Biosensors: Exploring Classifications, Principles, and Recent Advances.
感知未来——生物传感器前沿:探索分类、原理及最新进展
ACS Omega. 2024 Dec 6;9(50):48918-48987. doi: 10.1021/acsomega.4c07991. eCollection 2024 Dec 17.
4
Machine Learning-Assisted SERS Reveals the Biochemical Signature of Enhanced Protein Secretion from Surface-Modified Magnetic Nanoparticles.机器学习辅助的表面增强拉曼光谱揭示了表面修饰磁性纳米颗粒增强蛋白质分泌的生化特征。
ACS Appl Mater Interfaces. 2024 Dec 25;16(51):70392-70406. doi: 10.1021/acsami.4c18591. Epub 2024 Dec 11.
5
Raman spectroscopy reveals oxidative stress-induced metabolic vulnerabilities in early-stage AR-negative prostate-cancer versus normal-prostate cell lines.拉曼光谱揭示了 AR 阴性前列腺癌与正常前列腺细胞系早期氧化应激诱导的代谢脆弱性。
Sci Rep. 2024 Oct 25;14(1):25388. doi: 10.1038/s41598-024-70338-1.
6
Plasma-derived extracellular vesicles (EVs) as biomarkers of sepsis in burn patients via label-free Raman spectroscopy.基于无标记拉曼光谱的血浆衍生细胞外囊泡(EVs)作为烧伤患者脓毒症的生物标志物。
J Extracell Vesicles. 2024 Sep;13(9):e12506. doi: 10.1002/jev2.12506.
7
Non-invasive detection of regulatory T cells with Raman spectroscopy.利用拉曼光谱无创检测调节性 T 细胞。
Sci Rep. 2024 Jun 18;14(1):14025. doi: 10.1038/s41598-024-64536-0.
8
Plasma-derived Extracellular Vesicles (EVs) as Biomarkers of Sepsis in Burn Patients via Label-free Raman Spectroscopy.通过无标记拉曼光谱法检测烧伤患者血浆来源的细胞外囊泡作为脓毒症生物标志物
bioRxiv. 2024 May 15:2024.05.14.593634. doi: 10.1101/2024.05.14.593634.
9
Raman Fingerprints of SARS-CoV-2 Omicron Subvariants: Molecular Roots of Virological Characteristics and Evolutionary Directions.SARS-CoV-2 奥密克戎亚型的拉曼指纹:病毒学特征和进化方向的分子根源。
ACS Infect Dis. 2023 Nov 10;9(11):2226-2251. doi: 10.1021/acsinfecdis.3c00312. Epub 2023 Oct 18.
10
Understanding radiation response and cell cycle variation in brain tumour cells using Raman spectroscopy.使用拉曼光谱技术了解脑肿瘤细胞的辐射反应和细胞周期变化。
Analyst. 2023 May 30;148(11):2594-2608. doi: 10.1039/d3an00121k.