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Shang W, Ye A, Tong YK. Sub-Cellular Dynamic Analysis of BGC823 Cells after Treatment with the Multi-Component Drug CKI Using Raman Spectroscopy. Int J Mol Sci 2023; 24:12750. [PMID: 37628931 PMCID: PMC10454546 DOI: 10.3390/ijms241612750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 08/04/2023] [Accepted: 08/09/2023] [Indexed: 08/27/2023] Open
Abstract
Multi-component drugs (MCDs) can induce various cellular changes covering multiple levels, from molecular and subcellular structure to cell morphology. A "non-invasive" method for comprehensively detecting the dynamic changes of cellular fine structure and chemical components on the subcellular level is highly desirable for MCD studies. In this study, the subcellular dynamic processes of gastric cancer BGC823 cells after treatment with a multi-component drug, Compound Kushen Injection (CKI), were investigated using a homemade, high-resolution, confocal Raman spectroscopy (RS) device combined with bright-field imaging. The Raman spectra of the nucleus, cytoplasm and intracellular vesicles (0.4-1 μm) were collected simultaneously for each cell treated with CKI at different times and doses. The RS measurements showed that CKI decreased the DNA signatures, which the drug is known to inhibit. Meanwhile, the CKI-induced subcellular dynamic changes in the appearance of numerous intracellular vesicles and the deconstruction of cytoplasm components were observed and discussed. The results demonstrated that high-resolution subcellular micro-Raman spectroscopy has potential for detecting fine cellular dynamic variation induced by drugs and the screening of MCDs in cancer therapy.
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Affiliation(s)
- Wenhao Shang
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing 100871, China
- Biomed-X Center, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Anpei Ye
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing 100871, China
- Biomed-X Center, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Yu-Kai Tong
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing 100871, China
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2
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Cheng X, Liang H, Li Q, Wang J, Liu J, Zhang Y, Ru Y, Zhou Y. Raman spectroscopy differ leukemic cells from their healthy counterparts and screen biomarkers in acute leukemia. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2022; 281:121558. [PMID: 35843058 DOI: 10.1016/j.saa.2022.121558] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 06/20/2022] [Accepted: 06/22/2022] [Indexed: 06/15/2023]
Abstract
Precision medicine is important in the treatment of acute leukemia (AL). The target therapies of AL provide an opportunity to reduce the mortality of AL. How AL cells differ from their healthy counterparts is the basis for the development of therapies and the outcome of AL patients. Therefore, a label-free and noninvasive single-cell Raman platform was used to characterize cell molecular profiles and found potential biomarkers from three healthy people and twelve AL patients with more than 90% accuracy. We analyzed myeloblasts, abnormal promyelocytes, monoblasts and B-ALL cells respectively, compared with their healthy counterparts, which could be distinguished by their intrinsic phenotypic Raman spectra using orthogonal partial least squares discriminate analysis (OPLS-DA). Most importantly, we selected statistically significant markers of the four leukemia models. Further analysis of leukemic granulocytes, we found that a combination of the 1003, 1341 and 1579 cm-1 Raman peaks could discriminate myeloblasts and abnormal promyelocytes from normal granulocytes. The assignments of 1579 cm-1 gave us a clue to find potential important variables myeloperoxidase related with AL diagnosis. Our study demonstrates the capability of the Raman platform to characterize leukemia cells with non-invasively probing metabolites. The biomarker we identified could be extensible to other blood cells and potentially have a high impact on leukemia therapy.
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Affiliation(s)
- Xuelian Cheng
- State Key Laboratory of Experimental Hematology, Institute of Hematology and Hospital of Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China
| | - Haoyue Liang
- State Key Laboratory of Experimental Hematology, Institute of Hematology and Hospital of Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China
| | - Qing Li
- State Key Laboratory of Experimental Hematology, Institute of Hematology and Hospital of Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China
| | - Jing Wang
- Nankai University, National Demonstration Center for Experimental Chemistry Education, Tianjin 300071, China
| | - Jing Liu
- State Key Laboratory of Experimental Hematology, Institute of Hematology and Hospital of Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China
| | - Yun Zhang
- Department of Clinical Laboratory, The District People's Hospital of Zhangqiu, Jinan 250000, China
| | - Yongxin Ru
- State Key Laboratory of Experimental Hematology, Institute of Hematology and Hospital of Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China.
| | - Yuan Zhou
- State Key Laboratory of Experimental Hematology, Institute of Hematology and Hospital of Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China.
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3
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Favre-Bulle IA, Scott EK. Optical tweezers across scales in cell biology. Trends Cell Biol 2022; 32:932-946. [PMID: 35672197 PMCID: PMC9588623 DOI: 10.1016/j.tcb.2022.05.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 05/02/2022] [Accepted: 05/04/2022] [Indexed: 01/21/2023]
Abstract
Optical tweezers (OT) provide a noninvasive approach for delivering minute physical forces to targeted objects. Controlling such forces in living cells or in vitro preparations allows for the measurement and manipulation of numerous processes relevant to the form and function of cells. As such, OT have made important contributions to our understanding of the structures of proteins and nucleic acids, the interactions that occur between microscopic structures within cells, the choreography of complex processes such as mitosis, and the ways in which cells interact with each other. In this review, we highlight recent contributions made to the field of cell biology using OT and provide basic descriptions of the physics, the methods, and the equipment that made these studies possible.
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Affiliation(s)
- Itia A Favre-Bulle
- Queensland Brain Institute, The University of Queensland, 4067, Brisbane, Australia; School of Mathematics and Physics, The University of Queensland, 4067, Brisbane, Australia.
| | - Ethan K Scott
- Queensland Brain Institute, The University of Queensland, 4067, Brisbane, Australia; Department of Anatomy and Physiology, School of Biomedical Sciences, The University of Melbourne, Parkville, VIC 3010, Australia.
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4
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Lin CL, Wang SG, Tien MT, Chiang CH, Lee YC, Baldeck PL, Shin CS. A Novel Methodology for Detecting Variations in Cell Surface Antigens Using Cell-Tearing by Optical Tweezers. BIOSENSORS 2022; 12:656. [PMID: 36005053 PMCID: PMC9405593 DOI: 10.3390/bios12080656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 08/04/2022] [Accepted: 08/17/2022] [Indexed: 06/15/2023]
Abstract
The quantitative analysis of cell surface antigens has attracted increasing attention due to the antigenic variation recognition that can facilitate early diagnoses. This paper presents a novel methodology based on the optical "cell-tearing" and the especially proposed "dilution regulations" to detect variations in cell surface antigens. The cell attaches to the corresponding antibody-coated slide surface. Then, the cell-binding firmness between a single cell and the functionalized surface is assayed by optically tearing using gradually reduced laser powers incorporated with serial antibody dilutions. Groups B and B3 of red blood cells (RBCs) were selected as the experiment subject. The results indicate that a higher dilution called for lower power to tear off the cell binding. According to the proposed relative-quantitative analysis theory, antigenic variation can be intuitively estimated by comparing the maximum allowable dilution folds. The estimation result shows good consistency with the finding in the literature. This study suggests a novel methodology for examining the variation in cell surface antigens, expected to be widely capable with potential sensor applications not only in biochemistry and biophysics, but also in the micro-/nano- engineering field.
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Affiliation(s)
- Chih-Lang Lin
- Graduate Institute of Biotechnology and Biomedical Engineering, Central Taiwan University of Science and Technology, Taichung City 40601, Taiwan
- Department of Automatic Control Engineering, Feng Chia University, Taichung City 407802, Taiwan
| | - Shyang-Guang Wang
- Department of Medical Laboratory Science and Biotechnology, Central Taiwan University of Science and Technology, Taichung City 40601, Taiwan
| | - Meng-Tsung Tien
- General Education Center, Feng Chia University, Taichung City 407802, Taiwan
| | - Chung-Han Chiang
- Graduate Institute of Biotechnology and Biomedical Engineering, Central Taiwan University of Science and Technology, Taichung City 40601, Taiwan
| | - Yi-Chieh Lee
- Department of Medical Laboratory Science and Biotechnology, Central Taiwan University of Science and Technology, Taichung City 40601, Taiwan
| | - Patrice L. Baldeck
- ENSL, CNRS, Laboratoire de Chimie UMR 5182, 46 allée d’Italie, 69364 Lyon, France
| | - Chow-Shing Shin
- Department of Mechanical Engineering, National Taiwan University, Taipei City 10617, Taiwan
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5
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Zhou B, Sun L, Fang T, Li H, Zhang R, Ye A. Rapid and accurate identification of pathogenic bacteria at the single-cell level using laser tweezers Raman spectroscopy and deep learning. JOURNAL OF BIOPHOTONICS 2022; 15:e202100312. [PMID: 35150463 DOI: 10.1002/jbio.202100312] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 02/11/2022] [Accepted: 02/11/2022] [Indexed: 06/14/2023]
Abstract
We report a new method for the rapid identification of pathogenic bacterial species at the single-cell level that combines laser tweezers Raman spectroscopy (LTRS) with deep learning (DL). LTRS can accurately measure single-cell Raman spectra (scRS) without destroying and labeling cells. Based on the scRS data, DL rapidly and accurately identifies pathogenic bacteria. We measured scRS of 15 species bacteria using homemade LTRS. For each species, approximately, 160 cells from three different patients were measured, one patient's data were used as test set, and the rest after being augmented was used as training set. A residual network (ResNet) model, trained on the augmented training set, achieved an accuracy of 94.53% on the test set. Moreover, we applied gradient-weighted class activation mapping to visualize the proposed model. Finally, we demonstrated the advantages of ResNet over traditional machine-learning algorithms.
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Affiliation(s)
- Bo Zhou
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing, China
- School of Science, Beijing University of Posts and Telecommunications, Beijing, China
| | - Liying Sun
- Clinical Laboratory, Peking University First Hospital, Beijing, China
| | - Teng Fang
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing, China
| | - Haixia Li
- Clinical Laboratory, Peking University First Hospital, Beijing, China
| | - Ru Zhang
- School of Science, Beijing University of Posts and Telecommunications, Beijing, China
| | - Anpei Ye
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing, China
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6
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Ge X, Pereira FC, Mitteregger M, Berry D, Zhang M, Hausmann B, Zhang J, Schintlmeister A, Wagner M, Cheng JX. SRS-FISH: A high-throughput platform linking microbiome metabolism to identity at the single-cell level. Proc Natl Acad Sci U S A 2022; 119:e2203519119. [PMID: 35727976 PMCID: PMC9245642 DOI: 10.1073/pnas.2203519119] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 04/08/2022] [Indexed: 12/26/2022] Open
Abstract
One of the biggest challenges in microbiome research in environmental and medical samples is to better understand functional properties of microbial community members at a single-cell level. Single-cell isotope probing has become a key tool for this purpose, but the current detection methods for determination of isotope incorporation into single cells do not allow high-throughput analyses. Here, we report on the development of an imaging-based approach termed stimulated Raman scattering-two-photon fluorescence in situ hybridization (SRS-FISH) for high-throughput metabolism and identity analyses of microbial communities with single-cell resolution. SRS-FISH offers an imaging speed of 10 to 100 ms per cell, which is two to three orders of magnitude faster than achievable by state-of-the-art methods. Using this technique, we delineated metabolic responses of 30,000 individual cells to various mucosal sugars in the human gut microbiome via incorporation of deuterium from heavy water as an activity marker. Application of SRS-FISH to investigate the utilization of host-derived nutrients by two major human gut microbiome taxa revealed that response to mucosal sugars tends to be dominated by Bacteroidales, with an unexpected finding that Clostridia can outperform Bacteroidales at foraging fucose. With high sensitivity and speed, SRS-FISH will enable researchers to probe the fine-scale temporal, spatial, and individual activity patterns of microbial cells in complex communities with unprecedented detail.
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Affiliation(s)
- Xiaowei Ge
- Department of Electrical & Computer Engineering, Boston University, Boston, MA 02215
| | - Fátima C. Pereira
- Centre for Microbiology and Environmental Systems Science, Department of Microbiology and Ecosystem Science, University of Vienna, 1030 Vienna, Austria
| | - Matthias Mitteregger
- Centre for Microbiology and Environmental Systems Science, Department of Microbiology and Ecosystem Science, University of Vienna, 1030 Vienna, Austria
| | - David Berry
- Centre for Microbiology and Environmental Systems Science, Department of Microbiology and Ecosystem Science, University of Vienna, 1030 Vienna, Austria
| | - Meng Zhang
- Department of Electrical & Computer Engineering, Boston University, Boston, MA 02215
| | - Bela Hausmann
- Joint Microbiome Facility of the Medical University of Vienna and the University of Vienna, 1030 Vienna, Austria
- Department of Laboratory Medicine, Medical University of Vienna, 1090 Vienna, Austria
| | - Jing Zhang
- Department of Biomedical Engineering, Photonics Center, Boston University, Boston, MA 02215
| | - Arno Schintlmeister
- Centre for Microbiology and Environmental Systems Science, Department of Microbiology and Ecosystem Science, University of Vienna, 1030 Vienna, Austria
| | - Michael Wagner
- Centre for Microbiology and Environmental Systems Science, Department of Microbiology and Ecosystem Science, University of Vienna, 1030 Vienna, Austria
- Department of Chemistry and Bioscience, Aalborg University, 9220 Aalborg, Denmark
| | - Ji-Xin Cheng
- Department of Electrical & Computer Engineering, Boston University, Boston, MA 02215
- Department of Biomedical Engineering, Photonics Center, Boston University, Boston, MA 02215
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7
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Wang C, Hu W, Guan L, Yang X, Liang Q. Single-cell metabolite analysis on a microfluidic chip. CHINESE CHEM LETT 2022. [DOI: 10.1016/j.cclet.2021.10.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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8
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Li CY, Liu JX, Xin MK, He JW, Chen YL. A Self-Made Optical Tweezers Integrated Upconversion Luminescence Confocal Scanning Instrument Enables Stable and Noninvasive Long-Term In Situ Imaging a Single Suspension Cell Under Exceptionally Efficient Luminescent Resonance Energy Transfer Sensing. Anal Chem 2022; 94:6909-6917. [PMID: 35481762 DOI: 10.1021/acs.analchem.2c01338] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
It is necessary to explore labeling probes with worthy optical properties and a noninvasive fluorescence imaging manner for stable long-term in situ measuring a single suspension cell. In response to these goals, we herein make a breakthrough on two fronts. On one hand, a co-sensitizer-induced efficient 808 nm near-infrared light-excited luminescence-confined upconversion nanoparticle with a low thermal effect is fabricated by employing a layer-by-layer seed growing approach to develop a sandwich structure, under which the luminescence domain is vastly restricted into an extremely thin inner shell (∼ 2.77 nm) to finally bring about a high-efficiency luminescent resonance energy transfer (LRET) sensing behavior. On the other hand, a self-made optical tweezers integrated upconversion luminescence confocal scanning instrument is applied to enhance the imaging accuracy, after which the liquid viscous force is sufficiently overcome by the resulting single beam gradient force and the analyzed suspension cell is always immobilized to the focal plane to ensure a constant luminescence excitation condition. By making use of a metal ion-dependent DNAzyme and a hairpin DNA strand to design a corresponding LRET sensing system, our nanoprobe shows satisfactory assay performance for two model biomolecules (Ca2+ and TK1 messenger RNA). Following the optical trapping-assisted imaging, this exceptional measurement method is capable of effectively monitoring the intracellular target changes in different physiological states, endowing a powerful toolbox for single cell analysis.
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Affiliation(s)
- Cheng-Yu Li
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Medical College, Wuhan University of Science and Technology, Wuhan 430065, People's Republic of China
| | - Jun-Xian Liu
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Medical College, Wuhan University of Science and Technology, Wuhan 430065, People's Republic of China
| | - Meng-Kun Xin
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Medical College, Wuhan University of Science and Technology, Wuhan 430065, People's Republic of China
| | - Jing-Wei He
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Medical College, Wuhan University of Science and Technology, Wuhan 430065, People's Republic of China
| | - Ya-Ling Chen
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Medical College, Wuhan University of Science and Technology, Wuhan 430065, People's Republic of China
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9
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Ma X, Wang K, Chou KC, Li Q, Lu X. Conditional Generative Adversarial Network for Spectral Recovery to Accelerate Single-Cell Raman Spectroscopic Analysis. Anal Chem 2022; 94:577-582. [DOI: 10.1021/acs.analchem.1c04263] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Affiliation(s)
- Xiangyun Ma
- School of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia V6T 1Z1, Canada
| | - Kaidi Wang
- Department of Food Science and Agricultural Chemistry, Faculty of Agricultural and Environmental Sciences, McGill University, Montreal, Quebec H9X 3V9, Canada
| | - Keng C. Chou
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia V6T 1Z1, Canada
| | - Qifeng Li
- School of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Xiaonan Lu
- Department of Food Science and Agricultural Chemistry, Faculty of Agricultural and Environmental Sciences, McGill University, Montreal, Quebec H9X 3V9, Canada
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Zhang Q, Ye M, Wang L, Jiang D, Yao S, Lin D, Chen Y, Feng S, Yang T, Hu J. Characterization of Drug Resistance in Chronic Myeloid Leukemia Cells Based on Laser Tweezers Raman Spectroscopy. APPLIED SPECTROSCOPY 2021; 75:1296-1304. [PMID: 34076539 DOI: 10.1177/00037028211024581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Multidrug resistance is highly associated with poor prognosis of chronic myeloid leukemia. This work aims to explore whether the laser tweezers Raman spectroscopy (LTRS) could be practical in separating adriamycin-resistant chronic myeloid leukemia cells K562/adriamycin from its parental cells K562, and to explore the potential mechanisms. Detection of LTRS initially reflected the spectral differences caused by chemoresistance including bands assigned to carbohydrates, amino acid, protein, lipids, and nucleic acid. In addition, principal components analysis as well as the classification and regression trees algorithms showed that the specificity and sensitivity were above 90%. Moreover, the band data-based classification and regression tree model and receiver operating characteristic curve further determined some important bands and band intensity ratios to be reliable indexes in discriminating K562 chemoresistance status. Finally, we highlighted three metabolism pathways correlated with chemoresistance. This work demonstrates that the label-free LTRS analysis combined with multivariate statistical analyses have great potential to be a novel analytical strategy at the single-cell level for rapid evaluation of the chemoresistance status of K562 cells.
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Affiliation(s)
- Qian Zhang
- Department of Laboratory Medicine, 74551Fujian Medical University, Fuzhou, China
| | - Minlu Ye
- Department of Laboratory Medicine, 74551Fujian Medical University, Fuzhou, China
| | - Lingyan Wang
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory on Hematology, 74551Fujian Medical University Union Hospital, Fuzhou, China
| | - Dongmei Jiang
- Department of Medical Imaging Technology, 74551Fujian Medical University, Fuzhou, China
| | - Shuting Yao
- Department of Medical Imaging Technology, 74551Fujian Medical University, Fuzhou, China
| | - Donghong Lin
- Department of Laboratory Medicine, 74551Fujian Medical University, Fuzhou, China
| | - Yang Chen
- Department of Laboratory Medicine, 74551Fujian Medical University, Fuzhou, China
| | - Shangyuan Feng
- Key Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory for Photonics Technology, 12425Fujian Normal University, Fuzhou, China
| | - Ting Yang
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory on Hematology, 74551Fujian Medical University Union Hospital, Fuzhou, China
| | - Jianda Hu
- Department of Laboratory Medicine, 74551Fujian Medical University, Fuzhou, China
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory on Hematology, 74551Fujian Medical University Union Hospital, Fuzhou, China
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