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Ni C, Yang M, Yang S, Zhu Z, Chen Y, Jiang L, Xiang N. Three-dimensional inertial focusing based impedance cytometer enabling high-accuracy characterization of electrical properties of tumor cells. LAB ON A CHIP 2024. [PMID: 39132910 DOI: 10.1039/d4lc00523f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
The differences in the cross-sectional positions of cells in the detection area have a severe negative impact on achieving accurate characterization of the impedance spectra of cells. Herein, we proposed a three-dimensional (3D) inertial focusing based impedance cytometer integrating sheath fluid compression and inertial focusing for the high-accuracy electrical characterization and identification of tumor cells. First, we studied the effects of the particle initial position and the sheath fluid compression on particle focusing. Then, the relationship of the particle height and the signal-to-noise ratio (SNR) of the impedance signal was explored. The results showed that efficient single-line focusing of 7-20 μm particles close to the electrodes was achieved and impedance signals with a high SNR and a low coefficient of variation (CV) were obtained. Finally, the electrical properties of three types of tumor cells (A549, MDA-MB-231, and UM-UC-3 cells) were accurately characterized. Machine learning algorithms were implemented to accurately identify tumor cells based on the amplitude and phase opacities at multiple frequencies. Compared with traditional two-dimensional (2D) inertial focusing, the identification accuracy of A549, MDA-MB-231, and UM-UC-3 cells using our 3D inertial focusing increased by 57.5%, 36.4% and 36.6%, respectively. The impedance cytometer enables the detection of cells with a wide size range without causing clogging and obtains high SNR signals, improving applicability to different complex biological samples and cell identification accuracy.
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Affiliation(s)
- Chen Ni
- School of Mechanical Engineering, and, Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, Southeast University, Nanjing, 211189, China.
| | - Mingqi Yang
- School of Mechanical Engineering, and, Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, Southeast University, Nanjing, 211189, China.
| | - Shuai Yang
- School of Mechanical Engineering, and, Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, Southeast University, Nanjing, 211189, China.
| | - Zhixian Zhu
- School of Mechanical Engineering, and, Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, Southeast University, Nanjing, 211189, China.
| | - Yao Chen
- School of Mechanical Engineering, and, Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, Southeast University, Nanjing, 211189, China.
| | - Lin Jiang
- School of Mechanical Engineering, and, Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, Southeast University, Nanjing, 211189, China.
| | - Nan Xiang
- School of Mechanical Engineering, and, Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, Southeast University, Nanjing, 211189, China.
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2
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Zhu S, Zhu Z, Ni C, Zhou Z, Chen Y, Tang D, Guo K, Yang S, Liu K, Ni Z, Xiang N. Liquid Biopsy Instrument for Ultra-Fast and Label-Free Detection of Circulating Tumor Cells. RESEARCH (WASHINGTON, D.C.) 2024; 7:0431. [PMID: 39050821 PMCID: PMC11266806 DOI: 10.34133/research.0431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 06/27/2024] [Indexed: 07/27/2024]
Abstract
Rapid diagnosis and real-time monitoring are of great important in the fight against cancer. However, most available diagnostic technologies are time-consuming and labor-intensive and are commonly invasive. Here, we describe CytoExam, an automatic liquid biopsy instrument designed based on inertial microfluidics and impedance cytometry, which uses a deep learning algorithm for the analysis of circulating tumor cells (CTCs). In silico and in vitro experiments demonstrated that CytoExam could achieve label-free detection of CTCs in the peripheral blood of cancer patients within 15 min. The clinical applicability of CytoExam was also verified using peripheral blood samples from 10 healthy donors and >50 patients with breast, colorectal, or lung cancer. Significant differences in the number of collected cells and predicted CTCs were observed between the 2 groups, with variations in the dielectric properties of the collected cells from cancer patients also being observed. The ultra-fast and minimally invasive features of CytoExam may pave the way for new paths for cancer diagnosis and scientific research.
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Affiliation(s)
- Shu Zhu
- School of Mechanical Engineering, and Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments,
Southeast University, Nanjing 211189, China
- School of Electrical and Automation Engineering, and Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing,
Nanjing Normal University, Nanjing 210023, China
| | - Zhixian Zhu
- School of Mechanical Engineering, and Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments,
Southeast University, Nanjing 211189, China
| | - Chen Ni
- School of Mechanical Engineering, and Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments,
Southeast University, Nanjing 211189, China
| | - Zheng Zhou
- School of Mechanical Engineering, and Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments,
Southeast University, Nanjing 211189, China
| | - Yao Chen
- School of Mechanical Engineering, and Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments,
Southeast University, Nanjing 211189, China
| | - Dezhi Tang
- School of Mechanical Engineering, and Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments,
Southeast University, Nanjing 211189, China
| | - Kefan Guo
- School of Mechanical Engineering, and Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments,
Southeast University, Nanjing 211189, China
| | - Shuai Yang
- School of Mechanical Engineering, and Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments,
Southeast University, Nanjing 211189, China
| | - Kang Liu
- School of Mechanical Engineering, and Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments,
Southeast University, Nanjing 211189, China
| | - Zhonghua Ni
- School of Mechanical Engineering, and Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments,
Southeast University, Nanjing 211189, China
| | - Nan Xiang
- School of Mechanical Engineering, and Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments,
Southeast University, Nanjing 211189, China
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3
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Li SS, Xue CD, Li YJ, Chen XM, Zhao Y, Qin KR. Microfluidic characterization of single-cell biophysical properties and the applications in cancer diagnosis. Electrophoresis 2024; 45:1212-1232. [PMID: 37909658 DOI: 10.1002/elps.202300177] [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: 08/12/2023] [Revised: 09/25/2023] [Accepted: 10/16/2023] [Indexed: 11/03/2023]
Abstract
Single-cell biophysical properties play a crucial role in regulating cellular physiological states and functions, demonstrating significant potential in the fields of life sciences and clinical diagnostics. Therefore, over the last few decades, researchers have developed various detection tools to explore the relationship between the biophysical changes of biological cells and human diseases. With the rapid advancement of modern microfabrication technology, microfluidic devices have quickly emerged as a promising platform for single-cell analysis offering advantages including high-throughput, exceptional precision, and ease of manipulation. Consequently, this paper provides an overview of the recent advances in microfluidic analysis and detection systems for single-cell biophysical properties and their applications in the field of cancer. The working principles and latest research progress of single-cell biophysical property detection are first analyzed, highlighting the significance of electrical and mechanical properties. The development of data acquisition and processing methods for real-time, high-throughput, and practical applications are then discussed. Furthermore, the differences in biophysical properties between tumor and normal cells are outlined, illustrating the potential for utilizing single-cell biophysical properties for tumor cell identification, classification, and drug response assessment. Lastly, we summarize the limitations of existing microfluidic analysis and detection systems in single-cell biophysical properties, while also pointing out the prospects and future directions of their applications in cancer diagnosis and treatment.
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Affiliation(s)
- Shan-Shan Li
- School of Mechanical Engineering, Dalian University of Technology, Dalian, Liaoning, P. R. China
| | - Chun-Dong Xue
- School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning, P. R. China
| | - Yong-Jiang Li
- School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning, P. R. China
| | - Xiao-Ming Chen
- School of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian, Liaoning, P. R. China
| | - Yan Zhao
- Department of Stomach Surgery, Cancer Hospital of Dalian University of Technology, Liaoning Cancer Hospital and Institute, Shenyang, Liaoning, P. R. China
| | - Kai-Rong Qin
- School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning, P. R. China
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4
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Gong L, He L, Lu N, Petchakup C, Li KHH, Tay CY, Hou HW. Label-Free Single Microparticles and Cell Aggregates Sorting in Continuous Cell-Based Manufacturing. Adv Healthc Mater 2024; 13:e2304529. [PMID: 38465888 DOI: 10.1002/adhm.202304529] [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: 12/19/2023] [Revised: 03/04/2024] [Indexed: 03/12/2024]
Abstract
There is a paradigm shift in biomanufacturing toward continuous bioprocessing but cell-based manufacturing using adherent and suspension cultures, including microcarriers, hydrogel microparticles, and 3D cell aggregates, remains challenging due to the lack of efficient in-line bioprocess monitoring and cell harvesting tools. Herein, a novel label-free microfluidic platform for high throughput (≈50 particles/sec) impedance bioanalysis of biomass, cell viability, and stem cell differentiation at single particle resolution is reported. The device is integrated with a real-time piezo-actuated particle sorter based on user-defined multi-frequency impedance signatures. Biomass profiling of Cytodex-3 microcarriers seeded with adipose-derived mesenchymal stem cells (ADSCs) is first performed to sort well-seeded or confluent microcarriers for downstream culture or harvesting, respectively. Next, impedance-based isolation of microcarriers with osteogenic differentiated ADSCs is demonstrated, which is validated with a twofold increase of calcium content in sorted ADSCs. Impedance profiling of heterogenous ADSCs-encapsulated hydrogel (alginate) microparticles and 3D ADSC aggregate mixtures is also performed to sort particles with high biomass and cell viability to improve cell quality. Overall, the scalable microfluidic platform technology enables in-line sample processing from bioreactors directly and automated analysis of cell quality attributes to maximize cell yield and improve the control of cell quality in continuous cell-based manufacturing.
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Affiliation(s)
- Lingyan Gong
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, 639798, Singapore
| | - Linwei He
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, 639798, Singapore
| | - Nan Lu
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, 639798, Singapore
| | - Chayakorn Petchakup
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, 639798, Singapore
| | - King Ho Holden Li
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, 639798, Singapore
| | - Chor Yong Tay
- School of Materials Science and Engineering, Nanyang Technological University, Singapore, 639798, Singapore
- Environmental Chemistry and Materials Centre, Nanyang Environment & Water Research Institute, Singapore, 637141, Singapore
| | - Han Wei Hou
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, 639798, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
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5
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Wagner MS, Kranz M, Krenkel L, Pointner D, Foltan M, Lubnow M, Lehle K. Computer based visualization of clot structures in extracorporeal membrane oxygenation and histological clot investigations for understanding thrombosis in membrane lungs. Front Med (Lausanne) 2024; 11:1416319. [PMID: 38962744 PMCID: PMC11219572 DOI: 10.3389/fmed.2024.1416319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Accepted: 06/06/2024] [Indexed: 07/05/2024] Open
Abstract
Extracorporeal membrane oxygenation (ECMO) was established as a treatment for severe cardiac or respiratory disease. Intra-device clot formation is a common risk. This is based on complex coagulation phenomena which are not yet sufficiently understood. The objective was the development and validation of a methodology to capture the key properties of clots deposed in membrane lungs (MLs), such as clot size, distribution, burden, and composition. One end-of-therapy PLS ML was examined. Clot detection was performed using multidetector computed tomography (MDCT), microcomputed tomography (μCT), and photography of fiber mats (fiber mat imaging, FMI). Histological staining was conducted for von Willebrand factor (vWF), platelets (CD42b, CD62P), fibrin, and nucleated cells (4', 6-diamidino-2-phenylindole, DAPI). The three imaging methods showed similar clot distribution inside the ML. Independent of the imaging method, clot loading was detected predominantly in the inlet chamber of the ML. The μCT had the highest accuracy. However, it was more expensive and time consuming than MDCT or FMI. The MDCT detected the clots with low scanning time. Due to its lower resolution, it only showed clotted areas but not the exact shape of clot structures. FMI represented the simplest variant, requiring little effort and resources. FMI allowed clot localization and calculation of clot volume. Histological evaluation indicated omnipresent immunological deposits throughout the ML. Visually clot-free areas were covered with leukocytes and platelets forming platelet-leukocyte aggregates (PLAs). Cells were embedded in vWF cobwebs, while vWF fibers were negligible. In conclusion, the presented methodology allowed adequate clot identification and histological classification of possible thrombosis markers such as PLAs.
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Affiliation(s)
- Maria S. Wagner
- Department of Cardiothoracic Surgery, University Hospital Regensburg, Regensburg, Germany
| | - Michael Kranz
- Department of Biofluid Mechanics, Faculty of Mechanical Engineering, Technical University of Applied Sciences (OTH) Regensburg, Regensburg, Germany
- Regensburg Center of Biomedical Engineering, Facility of University Regensburg and Technical University of Applied Sciences (OTH) Regensburg, Regensburg, Germany
| | - Lars Krenkel
- Department of Biofluid Mechanics, Faculty of Mechanical Engineering, Technical University of Applied Sciences (OTH) Regensburg, Regensburg, Germany
- Regensburg Center of Biomedical Engineering, Facility of University Regensburg and Technical University of Applied Sciences (OTH) Regensburg, Regensburg, Germany
| | - Daniel Pointner
- Department of Biofluid Mechanics, Faculty of Mechanical Engineering, Technical University of Applied Sciences (OTH) Regensburg, Regensburg, Germany
- Regensburg Center of Biomedical Engineering, Facility of University Regensburg and Technical University of Applied Sciences (OTH) Regensburg, Regensburg, Germany
| | - Maik Foltan
- Department of Cardiothoracic Surgery, University Hospital Regensburg, Regensburg, Germany
| | - Matthias Lubnow
- Department of Internal Medicine II, University Hospital Regensburg, Regensburg, Germany
| | - Karla Lehle
- Department of Cardiothoracic Surgery, University Hospital Regensburg, Regensburg, Germany
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6
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Chapman M, Rajagopal V, Stewart A, Collins DJ. Critical review of single-cell mechanotyping approaches for biomedical applications. LAB ON A CHIP 2024; 24:3036-3063. [PMID: 38804123 DOI: 10.1039/d3lc00978e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Accurate mechanical measurements of cells has the potential to improve diagnostics, therapeutics and advance understanding of disease mechanisms, where high-resolution mechanical information can be measured by deforming individual cells. Here we evaluate recently developed techniques for measuring cell-scale stiffness properties; while many such techniques have been developed, much of the work examining single-cell stiffness is impacted by difficulties in standardization and comparability, giving rise to large variations in reported mechanical moduli. We highlight the role of underlying mechanical theories driving this variability, and note opportunities to develop novel mechanotyping devices and theoretical models that facilitate convenient and accurate mechanical characterisation. Moreover, many high-throughput approaches are confounded by factors including cell size, surface friction, natural population heterogeneity and convolution of elastic and viscous contributions to cell deformability. We nevertheless identify key approaches based on deformability cytometry as a promising direction for further development, where both high-throughput and accurate single-cell resolutions can be realized.
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Affiliation(s)
- Max Chapman
- Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia.
| | - Vijay Rajagopal
- Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia.
| | - Alastair Stewart
- ARC Centre for Personalised Therapeutics Technologies, The University of Melbourne, Parkville, VIC, Australia
- Department of Biochemistry and Pharmacology, The University of Melbourne, Parkville, VIC, Australia
| | - David J Collins
- Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia.
- Graeme Clarke Institute University of Melbourne Parkville, Victoria 3052, Australia
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7
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Zhu J, Pan S, Chai H, Zhao P, Feng Y, Cheng Z, Zhang S, Wang W. Microfluidic Impedance Cytometry Enabled One-Step Sample Preparation for Efficient Single-Cell Mass Spectrometry. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024; 20:e2310700. [PMID: 38483007 DOI: 10.1002/smll.202310700] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 03/05/2024] [Indexed: 06/27/2024]
Abstract
Single-cell mass spectrometry (MS) is significant in biochemical analysis and holds great potential in biomedical applications. Efficient sample preparation like sorting (i.e., separating target cells from the mixed population) and desalting (i.e., moving the cells off non-volatile salt solution) is urgently required in single-cell MS. However, traditional sample preparation methods suffer from complicated operation with various apparatus, or insufficient performance. Herein, a one-step sample preparation strategy by leveraging label-free impedance flow cytometry (IFC) based microfluidics is proposed. Specifically, the IFC framework to characterize and sort single-cells is adopted. Simultaneously with sorting, the target cell is transferred from the local high-salinity buffer to the MS-compatible solution. In this way, one-step sorting and desalting are achieved and the collected cells can be directly fed for MS analysis. A high sorting efficiency (>99%), cancer cell purity (≈87%), and desalting efficiency (>99%), and the whole workflow of impedance-based separation and MS analysis of normal cells (MCF-10A) and cancer cells (MDA-MB-468) are verified. As a standalone sample preparation module, the microfluidic chip is compatible with a variety of MS analysis methods, and envisioned to provide a new paradigm in efficient MS sample preparation, and further in multi-modal (i.e., electrical and metabolic) characterization of single-cells.
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Affiliation(s)
- Junwen Zhu
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, China
| | - Siyuan Pan
- Department of Chemistry, Tsinghua University, Beijing, 100084, China
| | - Huichao Chai
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, China
| | - Peng Zhao
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, China
| | - Yongxiang Feng
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, China
| | - Zhen Cheng
- Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Sichun Zhang
- Department of Chemistry, Tsinghua University, Beijing, 100084, China
| | - Wenhui Wang
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, China
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8
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Brandi C, De Ninno A, Ruggiero F, Limiti E, Abbruzzese F, Trombetta M, Rainer A, Bisegna P, Caselli F. On the compatibility of single-cell microcarriers (nanovials) with microfluidic impedance cytometry. LAB ON A CHIP 2024; 24:2883-2892. [PMID: 38717432 DOI: 10.1039/d4lc00002a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
We investigate for the first time the compatibility of nanovials with microfluidic impedance cytometry (MIC). Nanovials are suspendable crescent-shaped single-cell microcarriers that enable specific cell adhesion, the creation of compartments for undisturbed cell growth and secretion, as well as protection against wall shear stress. MIC is a label-free single-cell technique that characterizes flowing cells based on their electrical fingerprints and it is especially targeted to cells that are naturally in suspension. Combining nanovial technology with MIC is intriguing as it would represent a robust framework for the electrical analysis of single adherent cells at high throughput. Here, as a proof-of-concept, we report the MIC analysis of mesenchymal stromal cells loaded in nanovials. The electrical analysis is supported by numerical simulations and validated by means of optical analysis. We demonstrate that the electrical diameter can discriminate among free cells, empty nanovials, cell-loaded nanovials, and clusters, thus grounding the foundation for the use of nanovials in MIC. Furthermore, we investigate the potentiality of MIC to assess the electrical phenotype of cells loaded in nanovials and we draw directions for future studies.
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Affiliation(s)
- Cristian Brandi
- Department of Civil Engineering and Computer Science, University of Rome Tor Vergata, Rome, Italy.
| | - Adele De Ninno
- Italian National Research Council - Institute for Photonics and Nanotechnologies (CNR - IFN), Rome, Italy
| | - Filippo Ruggiero
- Italian National Research Council - Institute for Photonics and Nanotechnologies (CNR - IFN), Rome, Italy
| | - Emanuele Limiti
- Department of Engineering, Università Campus Bio-Medico di Roma, Via Álvaro del Portillo 21, 00128, Rome, Italy
| | - Franca Abbruzzese
- Department of Engineering, Università Campus Bio-Medico di Roma, Via Álvaro del Portillo 21, 00128, Rome, Italy
| | - Marcella Trombetta
- Department of Science and Technology for Sustainable Development and One Health, Università Campus Bio-Medico di Roma, Via Álvaro del Portillo 21, 00128, Rome, Italy
| | - Alberto Rainer
- Department of Engineering, Università Campus Bio-Medico di Roma, Via Álvaro del Portillo 21, 00128, Rome, Italy
- National Research Council - Institute of Nanotechnology (CNR-NANOTEC), c/o Campus Ecotekne, 73100 Lecce, Italy
| | - Paolo Bisegna
- Department of Civil Engineering and Computer Science, University of Rome Tor Vergata, Rome, Italy.
| | - Federica Caselli
- Department of Civil Engineering and Computer Science, University of Rome Tor Vergata, Rome, Italy.
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9
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Zhang S, Han Z, Qi H, Liu S, Liu B, Sun C, Feng Z, Sun M, Duan X. Convolutional Neural Network-Driven Impedance Flow Cytometry for Accurate Bacterial Differentiation. Anal Chem 2024; 96:4419-4429. [PMID: 38448396 DOI: 10.1021/acs.analchem.3c04421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
Impedance flow cytometry (IFC) has been demonstrated to be an efficient tool for label-free bacterial investigation to obtain the electrical properties in real time. However, the accurate differentiation of different species of bacteria by IFC technology remains a challenge owing to the insignificant differences in data. Here, we developed a convolutional neural networks (ConvNet) deep learning approach to enhance the accuracy and efficiency of the IFC toward distinguishing various species of bacteria. First, more than 1 million sets of impedance data (comprising 42 characteristic features for each set) of various groups of bacteria were trained by the ConvNet model. To improve the efficiency for data analysis, the Spearman correlation coefficient and the mean decrease accuracy of the random forest algorithm were introduced to eliminate feature interaction and extract the opacity of impedance related to the bacterial wall and membrane structure as the predominant features in bacterial differentiation. Moreover, the 25 optimized features were selected with differentiation accuracies of >96% for three groups of bacteria (bacilli, cocci, and vibrio) and >95% for two species of bacilli (Escherichia coli and Salmonella enteritidis), compared to machine learning algorithms (complex tree, linear discriminant, and K-nearest neighbor algorithms) with a maximum accuracy of 76.4%. Furthermore, bacterial differentiation was achieved on spiked samples of different species with different mixing ratios. The proposed ConvNet deep learning-assisted data analysis method of IFC exhibits advantages in analyzing a huge number of data sets with capacity for extracting predominant features within multicomponent information and will bring about progress and advances in the fields of both biosensing and data analysis.
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Affiliation(s)
- Shuaihua Zhang
- State Key Laboratory of Precision Measuring Technology & Instruments, College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Ziyu Han
- State Key Laboratory of Precision Measuring Technology & Instruments, College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Hang Qi
- State Key Laboratory of Precision Measuring Technology & Instruments, College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Siyuan Liu
- State Key Laboratory of Precision Measuring Technology & Instruments, College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Bohua Liu
- State Key Laboratory of Precision Measuring Technology & Instruments, College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Chongling Sun
- State Key Laboratory of Precision Measuring Technology & Instruments, College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Zhe Feng
- Wuqing District Center for Disease Control and Prevention, Tianjin 301700, China
| | - Meiqing Sun
- Wuqing District Center for Disease Control and Prevention, Tianjin 301700, China
| | - Xuexin Duan
- State Key Laboratory of Precision Measuring Technology & Instruments, College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
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10
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Tan H, Chen X, Huang X, Chen D, Qin X, Wang J, Chen J. Electrical micro flow cytometry with LSTM and its application in leukocyte differential. Cytometry A 2024; 105:54-61. [PMID: 37715355 DOI: 10.1002/cyto.a.24791] [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: 03/05/2023] [Revised: 07/13/2023] [Accepted: 09/04/2023] [Indexed: 09/17/2023]
Abstract
This paper developed an electrical micro flow cytometry to realize leukocyte differentials leveraging a constrictional microchannel and a deep neural network. Firstly, purified granulocytes, lymphocytes or monocytes traveled through the constrictional microchannel with a cross-sectional area marginally larger than individual cells and produced large impedance variations by blocking focused electric field lines. By optimizing key elements (e.g., normalization, learning rate, batch size and neuron number) of the recurrent neural network (RNN), electrical results of purified leukocytes were analyzed to establish a leukocyte differential system with a classification accuracy of 95.2%. Then the leukocyte mixtures were forced to travel through the same constrictional microchannel, producing mixed impedance profiles which were classified into granulocytes, lymphocytes and monocytes based on the aforementioned differential system. As to the classification results, two leukocyte mixtures from the same donor were processed, producing comparable classification results, which were 57% versus 59% of granulocytes, 37% versus 34% of lymphocytes and 6% versus 7% of monocytes. These results validated the established classification system based on the constrictional microchannel and the recurrent neural network, providing a new perspective of differentiating white blood cells by electrical flow cytometry.
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Affiliation(s)
- Huiwen Tan
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People's Republic of China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing, People's Republic of China
| | - Xiao Chen
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People's Republic of China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing, People's Republic of China
| | - Xukun Huang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People's Republic of China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, People's Republic of China
| | - Deyong Chen
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People's Republic of China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing, People's Republic of China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, People's Republic of China
| | - Xuzhen Qin
- Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, People's Republic of China
| | - Junbo Wang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People's Republic of China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing, People's Republic of China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, People's Republic of China
| | - Jian Chen
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People's Republic of China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing, People's Republic of China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, People's Republic of China
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11
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Chen Y, Jiang L, Zhang X, Ni Z, Xiang N. Viscoelastic-Sorting Integrated Deformability Cytometer for High-Throughput Sorting and High-Precision Mechanical Phenotyping of Tumor Cells. Anal Chem 2023; 95:18180-18187. [PMID: 38018866 DOI: 10.1021/acs.analchem.3c03792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2023]
Abstract
The counts and phenotypes of circulating tumor cells (CTCs) in whole blood are useful for disease monitoring and prognostic assessment of cancer. However, phenotyping CTCs in the blood is difficult due to the presence of a large number of background blood cells, especially some blood cells with features similar to those of tumor cells. Herein, we presented a viscoelastic-sorting integrated deformability cytometer (VSDC) for high-throughput label-free sorting and high-precision mechanical phenotyping of tumor cells. A sorting chip for removing large background blood cells and a detection chip for detecting multiple cellular mechanical properties were integrated into our VSDC. Our VSDC has a sorting efficiency and a purity of over 95% and over 81% for tumor cells, respectively. Furthermore, multiple mechanical parameters were used to distinguish tumor cells from white blood cells using machine learning. An accuracy of over 97% for identifying tumor cells was successfully achieved with the highest identification accuracy of 99.4% for MCF-7 cells. It is envisioned that our VSDC will open up new avenues for high-throughput and label-free single-cell analysis in various biomedical applications.
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Affiliation(s)
- Yao Chen
- School of Mechanical Engineering, Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, Southeast University, Nanjing 211189, China
| | - Lin Jiang
- School of Mechanical Engineering, Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, Southeast University, Nanjing 211189, China
| | - Xiaozhe Zhang
- School of Mechanical Engineering, Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, Southeast University, Nanjing 211189, China
| | - Zhonghua Ni
- School of Mechanical Engineering, Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, Southeast University, Nanjing 211189, China
| | - Nan Xiang
- School of Mechanical Engineering, Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, Southeast University, Nanjing 211189, China
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12
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Yang X, Liang Z, Luo Y, Yuan X, Cai Y, Yu D, Xing X. Single-cell impedance cytometry of anticancer drug-treated tumor cells exhibiting mitotic arrest state to apoptosis using low-cost silver-PDMS microelectrodes. LAB ON A CHIP 2023; 23:4848-4859. [PMID: 37860975 DOI: 10.1039/d3lc00459g] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2023]
Abstract
Chemotherapeutic drugs such as paclitaxel and vinblastine interact with microtubules and thus induce complex cell states of mitosis arrest at the G2/M phase followed by apoptosis dependent on drug exposure time and concentration. Microfluidic impedance cytometry (MIC), as a label-free and high-throughput technology for single-cell analysis, has been applied for viability assay of cancer cells post drug exposure at fixed time and dosage, yet verification of this technique for varied tumor cell states after anticancer drug treatment remains a challenge. Here we present a novel MIC device and for the first time perform impedance cytometry on carcinoma cells exhibiting progressive states of G2/M arrest followed by apoptosis related to drug concentration and exposure time, after treatments with paclitaxel and vinblastine, respectively. Our results from impedance cytometry reveal increased amplitude and negative phase shift at low frequency as well as higher opacity for HeLa cells under G2/M mitotic arrest compared to untreated cells. The cells under apoptosis, on the other hand, exhibit opposite changes in these electrical parameters. Therefore, the impedance features differentiate the HeLa cells under progressive states post anticancer drug treatment. We also demonstrate that vinblastine poses a more potent drug effect than paclitaxel especially at low concentrations. Our device is fabricated using a unique sacrificial layer-free soft lithography process as compared to the existing MIC device, which gives rise to readily aligned parallel microelectrodes made of silver-PDMS embedded in PDMS channel sidewalls with one molding step. Our results uncover the potential of the MIC device, with a fairly simple and low-cost fabrication process, for cellular state screening in anticancer drug therapy.
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Affiliation(s)
- Xinlong Yang
- College of Information Science and Technology, Beijing University of Chemical Technology, No. 15 North 3rd Ring Rd., Beijing, 100029, China.
| | - Ziheng Liang
- College of Information Science and Technology, Beijing University of Chemical Technology, No. 15 North 3rd Ring Rd., Beijing, 100029, China.
| | - Yuan Luo
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China
- Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xueyuan Yuan
- College of Information Science and Technology, Beijing University of Chemical Technology, No. 15 North 3rd Ring Rd., Beijing, 100029, China.
| | - Yao Cai
- College of Information Science and Technology, Beijing University of Chemical Technology, No. 15 North 3rd Ring Rd., Beijing, 100029, China.
| | - Duli Yu
- College of Information Science and Technology, Beijing University of Chemical Technology, No. 15 North 3rd Ring Rd., Beijing, 100029, China.
| | - Xiaoxing Xing
- College of Information Science and Technology, Beijing University of Chemical Technology, No. 15 North 3rd Ring Rd., Beijing, 100029, China.
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13
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Sun J, Huang X, Chen J, Xiang R, Ke X, Lin S, Xuan W, Liu S, Cao Z, Sun L. Recent advances in deformation-assisted microfluidic cell sorting technologies. Analyst 2023; 148:4922-4938. [PMID: 37743834 DOI: 10.1039/d3an01150j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Cell sorting is an essential prerequisite for cell research and has great value in life science and clinical studies. Among the many microfluidic cell sorting technologies, label-free methods based on the size of different cell types have been widely studied. However, the heterogeneity in size for cells of the same type and the inevitable size overlap between different types of cells would result in performance degradation in size-based sorting. To tackle such challenges, deformation-assisted technologies are receiving more attention recently. Cell deformability is an inherent biophysical marker of cells that reflects the changes in their internal structures and physiological states. It provides additional dimensional information for cell sorting besides size. Therefore, in this review, we summarize the recent advances in deformation-assisted microfluidic cell sorting technologies. According to how the deformability is characterized and the form in which the force acts, the technologies can be divided into two categories: (1) the indirect category including transit-time-based and image-based methods, and (2) the direct category including microstructure-based and hydrodynamics-based methods. Finally, the separation performance and the application scenarios of each method, the existing challenges and future outlook are discussed. Deformation-assisted microfluidic cell sorting technologies are expected to realize greater potential in the label-free analysis of cells.
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Affiliation(s)
- Jingjing Sun
- Ministry of Education Key Lab of RF Circuits and Systems, Hangzhou Dianzi University, China.
| | - Xiwei Huang
- Ministry of Education Key Lab of RF Circuits and Systems, Hangzhou Dianzi University, China.
| | - Jin Chen
- Ministry of Education Key Lab of RF Circuits and Systems, Hangzhou Dianzi University, China.
| | - Rikui Xiang
- Ministry of Education Key Lab of RF Circuits and Systems, Hangzhou Dianzi University, China.
| | - Xiang Ke
- Ministry of Education Key Lab of RF Circuits and Systems, Hangzhou Dianzi University, China.
| | - Siru Lin
- Ministry of Education Key Lab of RF Circuits and Systems, Hangzhou Dianzi University, China.
| | - Weipeng Xuan
- Ministry of Education Key Lab of RF Circuits and Systems, Hangzhou Dianzi University, China.
| | - Shan Liu
- Sichuan Provincial Key Laboratory for Human Disease Gene Study, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, China
| | - Zhen Cao
- College of Information Science and Electronic Engineering, Zhejiang University, China
| | - Lingling Sun
- Ministry of Education Key Lab of RF Circuits and Systems, Hangzhou Dianzi University, China.
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14
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Hua H, Zou S, Ma Z, Guo W, Fong CY, Khoo BL. A deformability-based biochip for precise label-free stratification of metastatic subtypes using deep learning. MICROSYSTEMS & NANOENGINEERING 2023; 9:120. [PMID: 37780810 PMCID: PMC10539402 DOI: 10.1038/s41378-023-00577-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 06/08/2023] [Accepted: 07/07/2023] [Indexed: 10/03/2023]
Abstract
Cellular deformability is a promising biomarker for evaluating the physiological state of cells in medical applications. Microfluidics has emerged as a powerful technique for measuring cellular deformability. However, existing microfluidic-based assays for measuring cellular deformability rely heavily on image analysis, which can limit their scalability for high-throughput applications. Here, we develop a parallel constriction-based microfluidic flow cytometry device and an integrated computational framework (ATMQcD). The ATMQcD framework includes automatic training set generation, multiple object tracking, segmentation, and cellular deformability quantification. The system was validated using cancer cell lines of varying metastatic potential, achieving a classification accuracy of 92.4% for invasiveness assessment and stratifying cancer cells before and after hypoxia treatment. The ATMQcD system also demonstrated excellent performance in distinguishing cancer cells from leukocytes (accuracy = 89.5%). We developed a mechanical model based on power-law rheology to quantify stiffness, which was fitted with measured data directly. The model evaluated metastatic potentials for multiple cancer types and mixed cell populations, even under real-world clinical conditions. Our study presents a highly robust and transferable computational framework for multiobject tracking and deformation measurement tasks in microfluidics. We believe that this platform has the potential to pave the way for high-throughput analysis in clinical applications, providing a powerful tool for evaluating cellular deformability and assessing the physiological state of cells.
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Affiliation(s)
- Haojun Hua
- City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, 999077 China
| | - Shangjie Zou
- City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, 999077 China
- Hong Kong Center for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, 999077 China
| | - Zhiqiang Ma
- Hong Kong Center for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, 999077 China
| | - Wang Guo
- City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, 999077 China
- Hong Kong Center for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, 999077 China
| | - Ching Yin Fong
- City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, 999077 China
| | - Bee Luan Khoo
- City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, 999077 China
- Hong Kong Center for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, 999077 China
- City University of Hong Kong Futian-Shenzhen Research Institute, Shenzhen, 518057 China
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15
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Petchakup C, Wong SO, Dalan R, Hou HW. Label-free virtual staining of neutrophil extracellular traps (NETs) in microfluidics. LAB ON A CHIP 2023; 23:3936-3944. [PMID: 37584074 DOI: 10.1039/d3lc00398a] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/17/2023]
Abstract
Neutrophils are the most abundant circulating white blood cells and one of their critical functions to eliminate pathogenic threats includes the release of extracellular DNA, also known as neutrophil extracellular traps (NETs), which is dysregulated in many diseases including cancer, type 2 diabetes mellitus and infectious diseases. Currently, conventional methods to quantify the NET formation (NETosis) rely on fluorescence antibody-based NET labelling or circulating NET-associated protein detection by ELISA, which are expensive, laborious, and time-consuming. In this work, we employed a novel "virtual staining" using deep convolutional neural networks (CNNs) to facilitate label-free quantification of NETs trapped in a micropillar array in a microfluidic device. Virtual staining is constructed to establish relations between morphological features in phase contrast images and fluorescence features in Sytox-green (DNA dye) images. We first investigated the effect of different learning rates on model training and optimized the learning rate to achieve the best model which can provide outputs close to Sytox green staining based on various reconstruction metrics (e.g., structural similarity (SSIM) and pixel-wise error (MAE, MSE)). The virtual staining of different NET concentrations was investigated which showed a linear correlation with fluorescent staining. As a proof of concept for clinical testing, the model was used to characterize purified neutrophils treated with NETosis inducers, including lipopolysaccharide (LPS), phorbol 12-myristate 13-acetate (PMA), and calcium ionophore (CaI), and successfully detected different NET profiles for different treatments. Collectively, these results demonstrated the potential of using deep learning for enhanced label-free image analysis of NETs for clinical research, drug discovery and point-of-care testing of diseases.
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Affiliation(s)
- Chayakorn Petchakup
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Blk N3, Level 2, Room 86 (N3-02c-86), 639798, Singapore.
| | - Siong Onn Wong
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Blk N3, Level 2, Room 86 (N3-02c-86), 639798, Singapore.
| | - Rinkoo Dalan
- Endocrinology Department, Tan Tock Seng Hospital, Singapore
| | - Han Wei Hou
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Blk N3, Level 2, Room 86 (N3-02c-86), 639798, Singapore.
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
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16
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Petchakup C, Chen YYC, Tay HM, Ong HB, Hon PY, De PP, Yeo TW, Li KHH, Vasoo S, Hou HW. Rapid Screening of Urinary Tract Infection Using Microfluidic Inertial-Impedance Cytometry. ACS Sens 2023; 8:3136-3145. [PMID: 37477562 DOI: 10.1021/acssensors.3c00819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/22/2023]
Abstract
Urinary tract infection (UTI) diagnosis based on urine culture for bacteriuria analysis is time-consuming and often leads to wastage of hospital resources due to false-positive UTI cases. Direct cellular phenotyping (e.g., RBCs, neutrophils, epithelial cells) of urine samples remains a technical challenge as low cell concentrations, and urine characteristics (conductivities, pH, microbes) can affect the accuracy of cell measurements. In this work, we report a microfluidic inertial-impedance cytometry technique for label-free rapid (<5 min) neutrophil sorting and impedance profiling from urine directly. Based on size-based inertial focusing effects, neutrophils are isolated, concentrated, and resuspended in saline (buffer exchange) to improve consistency in impedance-based single-cell analysis. We first observed that both urine pH and the presence of bacteria can affect neutrophil high-frequency impedance measurements possibly due to changes in nucleus morphology as neutrophils undergo NETosis and phagocytosis, respectively. As a proof-of-concept for clinical testing, we report for the first time, rapid UTI testing based on multiparametric impedance profiling of putative neutrophils (electrical size, membrane properties, and distribution) in urine samples from non-UTI (n = 20) and UTI patients (n = 20). A significant increase in cell count was observed in UTI samples, and biophysical parameters were used to develop a UTI classifier with an area under the receiver operating characteristic curve of 0.84. Overall, the developed platform facilitates rapid culture-free urine screening which can be further developed to assess disease severity in UTI and other urologic diseases based on neutrophil electrical signatures.
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Affiliation(s)
- Chayakorn Petchakup
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore
| | | | - Hui Min Tay
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore
| | - Hong Boon Ong
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore
| | - Pei Yun Hon
- National Center for Infectious Disease, Tan Tock Seng Hospital, Singapore 308442, Singapore
| | - Partha Pratim De
- Department of Laboratory Medicine, Tan Tock Seng Hospital, Singapore 308433, Singapore
| | - Tsin Wen Yeo
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore
| | - King Ho Holden Li
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore
| | - Shawn Vasoo
- National Center for Infectious Disease, Tan Tock Seng Hospital, Singapore 308442, Singapore
| | - Han Wei Hou
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore
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17
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Zhu J, Feng Y, Chai H, Liang F, Cheng Z, Wang W. Performance-enhanced clogging-free viscous sheath constriction impedance flow cytometry. LAB ON A CHIP 2023; 23:2531-2539. [PMID: 37082895 DOI: 10.1039/d3lc00178d] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
As a label-free and high-throughput single cell analysis platform, impedance flow cytometry (IFC) suffers from clogging caused by a narrow microchannel as mechanical constriction (MC). Current sheath constriction (SC) solutions lack systematic evaluation of the performance and proper guidelines for the sheath fluid. Herein, we hypothesize that the viscosity of the non-conductive liquid is the key to the performance of SC, and propose to employ non-conductive viscous sheath flow in SC to unlock the tradeoff between sensitivity and throughput, while ensuring measurement accuracy. By placing MC and SC in series in the same microfluidic chip, we established an evaluation platform to prove the hypothesis. Through modeling analysis and experiments, we confirmed the accuracy (error < 1.60% ± 4.71%) of SC w.r.t. MC, and demonstrated that viscous non-conductive PEG solution achieved an improved sensitivity (7.92×) and signal-to-noise ratio (1.42×) in impedance measurement, with the accuracy maintained and free of clogging. Viscous SC IFC also shows satisfactory ability to distinguish different types of cancer cells and different subtypes of human breast cancer cells. It is envisioned that viscous SC IFC paves the way for IFC to be really usable in practice with clogging-free, accurate, and sensitive performance.
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Affiliation(s)
- Junwen Zhu
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, P. R. China.
| | - Yongxiang Feng
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, P. R. China.
| | - Huichao Chai
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, P. R. China.
| | - Fei Liang
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, P. R. China.
| | - Zhen Cheng
- Department of Automation, Tsinghua University, Beijing, P. R. China
| | - Wenhui Wang
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, P. R. China.
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18
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Siu DMD, Lee KCM, Chung BMF, Wong JSJ, Zheng G, Tsia KK. Optofluidic imaging meets deep learning: from merging to emerging. LAB ON A CHIP 2023; 23:1011-1033. [PMID: 36601812 DOI: 10.1039/d2lc00813k] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Propelled by the striking advances in optical microscopy and deep learning (DL), the role of imaging in lab-on-a-chip has dramatically been transformed from a silo inspection tool to a quantitative "smart" engine. A suite of advanced optical microscopes now enables imaging over a range of spatial scales (from molecules to organisms) and temporal window (from microseconds to hours). On the other hand, the staggering diversity of DL algorithms has revolutionized image processing and analysis at the scale and complexity that were once inconceivable. Recognizing these exciting but overwhelming developments, we provide a timely review of their latest trends in the context of lab-on-a-chip imaging, or coined optofluidic imaging. More importantly, here we discuss the strengths and caveats of how to adopt, reinvent, and integrate these imaging techniques and DL algorithms in order to tailor different lab-on-a-chip applications. In particular, we highlight three areas where the latest advances in lab-on-a-chip imaging and DL can form unique synergisms: image formation, image analytics and intelligent image-guided autonomous lab-on-a-chip. Despite the on-going challenges, we anticipate that they will represent the next frontiers in lab-on-a-chip imaging that will spearhead new capabilities in advancing analytical chemistry research, accelerating biological discovery, and empowering new intelligent clinical applications.
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Affiliation(s)
- Dickson M D Siu
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, Hong Kong.
| | - Kelvin C M Lee
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, Hong Kong.
| | - Bob M F Chung
- Advanced Biomedical Instrumentation Centre, Hong Kong Science Park, Shatin, New Territories, Hong Kong
| | - Justin S J Wong
- Conzeb Limited, Hong Kong Science Park, Shatin, New Territories, Hong Kong
| | - Guoan Zheng
- Department of Biomedical Engineering, University of Connecticut, Storrs, CT, USA
| | - Kevin K Tsia
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, Hong Kong.
- Advanced Biomedical Instrumentation Centre, Hong Kong Science Park, Shatin, New Territories, Hong Kong
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19
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de Bruijn DS, Van de Waal DB, Helmsing NR, Olthuis W, van den Berg A. Microfluidic Impedance Cytometry for Single-Cell Particulate Inorganic Carbon:Particulate Organic Carbon Measurements of Calcifying Algae. GLOBAL CHALLENGES (HOBOKEN, NJ) 2023; 7:2200151. [PMID: 36910468 PMCID: PMC10000273 DOI: 10.1002/gch2.202200151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 11/16/2022] [Indexed: 06/18/2023]
Abstract
Calcifying algae, like coccolithophores, greatly contribute to the oceanic carbon cycle and are therefore of particular interest for ocean carbon models. They play a key role in two processes that are important for the effective CO2 flux: The organic carbon pump (photosynthesis) and the inorganic carbon pump (calcification). The relative contribution of calcification and photosynthesis can be measured in algae by the amount of particulate inorganic carbon (PIC) and particulate organic carbon (POC). A microfluidic impedance cytometer is presented, enabling non-invasive and high-throughput assessment of the calcification state of single coccolithophore cells. Gradual modification of the exoskeleton by acidification results in a strong linear fit (R 2 = 0.98) between the average electrical phase and the PIC:POC ratio of the coccolithophore Emiliania huxleyi 920/9. The effect of different CO2 treatments on the PIC:POC ratio, however, is inconclusive, indicating that there is no strong effect observed for this particular strain. Lower PIC:POC ratios in cultures that grew to higher cell densities are found, which are also recorded with the impedance-based PIC:POC sensor. The development of this new quantification tool for small volumes paves the way for high-throughput analysis while applying multi-variable environmental stressors to support projections of the future marine carbon cycle.
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Affiliation(s)
- Douwe S. de Bruijn
- BIOS Lab‐on‐a‐Chip groupMESA+ Institute for NanotechnologyMax Planck—University of Twente Center for Complex Fluid DynamicsUniversity of TwenteDrienerlolaan 5EnschedeOverijssel7522 NBThe Netherlands
| | - Dedmer B. Van de Waal
- Department of Aquatic EcologyNetherlands Institute of Ecology (NIOO‐KNAW)Droevendaalsesteeg 10Wageningen6708 PBThe Netherlands
| | - Nico R. Helmsing
- Department of Aquatic EcologyNetherlands Institute of Ecology (NIOO‐KNAW)Droevendaalsesteeg 10Wageningen6708 PBThe Netherlands
| | - Wouter Olthuis
- BIOS Lab‐on‐a‐Chip groupMESA+ Institute for NanotechnologyMax Planck—University of Twente Center for Complex Fluid DynamicsUniversity of TwenteDrienerlolaan 5EnschedeOverijssel7522 NBThe Netherlands
| | - Albert van den Berg
- BIOS Lab‐on‐a‐Chip groupMESA+ Institute for NanotechnologyMax Planck—University of Twente Center for Complex Fluid DynamicsUniversity of TwenteDrienerlolaan 5EnschedeOverijssel7522 NBThe Netherlands
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20
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Lu N, Tay HM, Petchakup C, He L, Gong L, Maw KK, Leong SY, Lok WW, Ong HB, Guo R, Li KHH, Hou HW. Label-free microfluidic cell sorting and detection for rapid blood analysis. LAB ON A CHIP 2023; 23:1226-1257. [PMID: 36655549 DOI: 10.1039/d2lc00904h] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Blood tests are considered as standard clinical procedures to screen for markers of diseases and health conditions. However, the complex cellular background (>99.9% RBCs) and biomolecular composition often pose significant technical challenges for accurate blood analysis. An emerging approach for point-of-care blood diagnostics is utilizing "label-free" microfluidic technologies that rely on intrinsic cell properties for blood fractionation and disease detection without any antibody binding. A growing body of clinical evidence has also reported that cellular dysfunction and their biophysical phenotypes are complementary to standard hematoanalyzer analysis (complete blood count) and can provide a more comprehensive health profiling. In this review, we will summarize recent advances in microfluidic label-free separation of different blood cell components including circulating tumor cells, leukocytes, platelets and nanoscale extracellular vesicles. Label-free single cell analysis of intrinsic cell morphology, spectrochemical properties, dielectric parameters and biophysical characteristics as novel blood-based biomarkers will also be presented. Next, we will highlight research efforts that combine label-free microfluidics with machine learning approaches to enhance detection sensitivity and specificity in clinical studies, as well as innovative microfluidic solutions which are capable of fully integrated and label-free blood cell sorting and analysis. Lastly, we will envisage the current challenges and future outlook of label-free microfluidics platforms for high throughput multi-dimensional blood cell analysis to identify non-traditional circulating biomarkers for clinical diagnostics.
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Affiliation(s)
- Nan Lu
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Blk N3, Level 2, Room 86 (N3-02c-86), 639798, Singapore.
- HP-NTU Digital Manufacturing Corporate Lab, Nanyang Technological University, 65 Nanyang Drive, Block N3, 637460, Singapore
| | - Hui Min Tay
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Blk N3, Level 2, Room 86 (N3-02c-86), 639798, Singapore.
| | - Chayakorn Petchakup
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Blk N3, Level 2, Room 86 (N3-02c-86), 639798, Singapore.
| | - Linwei He
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Blk N3, Level 2, Room 86 (N3-02c-86), 639798, Singapore.
| | - Lingyan Gong
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Blk N3, Level 2, Room 86 (N3-02c-86), 639798, Singapore.
| | - Kay Khine Maw
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Blk N3, Level 2, Room 86 (N3-02c-86), 639798, Singapore.
| | - Sheng Yuan Leong
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Blk N3, Level 2, Room 86 (N3-02c-86), 639798, Singapore.
| | - Wan Wei Lok
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Blk N3, Level 2, Room 86 (N3-02c-86), 639798, Singapore.
| | - Hong Boon Ong
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Blk N3, Level 2, Room 86 (N3-02c-86), 639798, Singapore.
| | - Ruya Guo
- Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing, 100083, China
| | - King Ho Holden Li
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Blk N3, Level 2, Room 86 (N3-02c-86), 639798, Singapore.
- HP-NTU Digital Manufacturing Corporate Lab, Nanyang Technological University, 65 Nanyang Drive, Block N3, 637460, Singapore
| | - Han Wei Hou
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Blk N3, Level 2, Room 86 (N3-02c-86), 639798, Singapore.
- HP-NTU Digital Manufacturing Corporate Lab, Nanyang Technological University, 65 Nanyang Drive, Block N3, 637460, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, 11 Mandalay Road, Clinical Sciences Building, 308232, Singapore
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21
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Ferguson CA, Hwang JCM, Zhang Y, Cheng X. Single-Cell Classification Based on Population Nucleus Size Combining Microwave Impedance Spectroscopy and Machine Learning. SENSORS (BASEL, SWITZERLAND) 2023; 23:1001. [PMID: 36679798 PMCID: PMC9860723 DOI: 10.3390/s23021001] [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: 12/09/2022] [Revised: 01/04/2023] [Accepted: 01/13/2023] [Indexed: 06/17/2023]
Abstract
Many recent efforts in the diagnostic field address the accessibility of cancer diagnosis. Typical histological staining methods identify cancer cells visually by a larger nucleus with more condensed chromatin. Machine learning (ML) has been incorporated into image analysis for improving this process. Recently, impedance spectrometers have been shown to generate all-inclusive lab-on-a-chip platforms to detect nucleus abnormities. In this paper, a wideband electrical sensor and data analysis paradigm that can identify nuclear changes shows the realization of a single-cell microfluidic device to detect nuclei of altered sizes. To model cells of altered nucleus, Jurkat cells were treated to enlarge or shrink their nucleus followed by broadband sensing to obtain the S-parameters of single cells. The ability to deduce important frequencies associated with nucleus size is demonstrated and used to improve classification models in both binary and multiclass scenarios, despite a heterogeneous and overlapping cell population. The important frequency features match those predicted in a double-shell circuit model published in prior work, demonstrating a coherent new analytical technique for electrical data analysis. The electrical sensing platform assisted by ML with impressive accuracy of cell classification looks forward to a label-free and flexible approach to cancer diagnosis.
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Affiliation(s)
| | - James C. M. Hwang
- Department of Materials Science and Engineering, Cornell University, Ithaca, NY 14853, USA
| | - Yu Zhang
- Department of Bioengineering, Lehigh University, Bethlehem, PA 18015, USA
| | - Xuanhong Cheng
- Department of Bioengineering, Lehigh University, Bethlehem, PA 18015, USA
- Department of Materials Science and Engineering, Lehigh University, Bethlehem, PA 18015, USA
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22
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Aubry G, Lee HJ, Lu H. Advances in Microfluidics: Technical Innovations and Applications in Diagnostics and Therapeutics. Anal Chem 2023; 95:444-467. [PMID: 36625114 DOI: 10.1021/acs.analchem.2c04562] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Affiliation(s)
- Guillaume Aubry
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Hyun Jee Lee
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Hang Lu
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.,Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
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