1
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Paiè P, Calisesi G, Candeo A, Comi A, Sala F, Ceccarelli F, De Luigi A, Veglianese P, Muhlberger K, Fokine M, Valentini G, Osellame R, Neil M, Bassi A, Bragheri F. Structured-light-sheet imaging in an integrated optofluidic platform. LAB ON A CHIP 2023; 24:34-46. [PMID: 37791882 DOI: 10.1039/d3lc00639e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Heterogeneity investigation at the single-cell level reveals morphological and phenotypic characteristics in cell populations. In clinical research, heterogeneity has important implications in the correct detection and interpretation of prognostic markers and in the analysis of patient-derived material. Among single-cell analysis, imaging flow cytometry allows combining information retrieved by single cell images with the throughput of fluidic platforms. Nevertheless, these techniques might fail in a comprehensive heterogeneity evaluation because of limited image resolution and bidimensional analysis. Light sheet fluorescence microscopy opened new ways to study in 3D the complexity of cellular functionality in samples ranging from single-cells to micro-tissues, with remarkably fast acquisition and low photo-toxicity. In addition, structured illumination microscopy has been applied to single-cell studies enhancing the resolution of imaging beyond the conventional diffraction limit. The combination of these techniques in a microfluidic environment, which permits automatic sample delivery and translation, would allow exhaustive investigation of cellular heterogeneity with high throughput image acquisition at high resolution. Here we propose an integrated optofluidic platform capable of performing structured light sheet imaging flow cytometry (SLS-IFC). The system encompasses a multicolor directional coupler equipped with a thermo-optic phase shifter, cylindrical lenses and a microfluidic network to generate and shift a patterned light sheet within a microchannel. The absence of moving parts allows a stable alignment and an automated fluorescence signal acquisition during the sample flow. The platform enables 3D imaging of an entire cell in about 1 s with a resolution enhancement capable of revealing sub-cellular features and sub-diffraction limit details.
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Affiliation(s)
- Petra Paiè
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci, 32, Milano, 20133, Italy.
- Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Piazza Leonardo da Vinci, 32, Milano, 20133, Italy.
| | - Gianmaria Calisesi
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci, 32, Milano, 20133, Italy.
| | - Alessia Candeo
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci, 32, Milano, 20133, Italy.
- Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Piazza Leonardo da Vinci, 32, Milano, 20133, Italy.
| | - Andrea Comi
- Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Piazza Leonardo da Vinci, 32, Milano, 20133, Italy.
| | - Federico Sala
- Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Piazza Leonardo da Vinci, 32, Milano, 20133, Italy.
| | - Francesco Ceccarelli
- Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Piazza Leonardo da Vinci, 32, Milano, 20133, Italy.
| | - Ada De Luigi
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, Milano, 20156, Italy
| | - Pietro Veglianese
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, Milano, 20156, Italy
| | - Korbinian Muhlberger
- Department of Applied Physics, KTH Royal Institute of Technology, Roslagstullsbacken 21, Stockholm, 11421, Sweden
| | - Michael Fokine
- Department of Applied Physics, KTH Royal Institute of Technology, Roslagstullsbacken 21, Stockholm, 11421, Sweden
| | - Gianluca Valentini
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci, 32, Milano, 20133, Italy.
- Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Piazza Leonardo da Vinci, 32, Milano, 20133, Italy.
| | - Roberto Osellame
- Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Piazza Leonardo da Vinci, 32, Milano, 20133, Italy.
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci, 32, Milano, 20133, Italy.
| | - Mark Neil
- Physics Department, Imperial College London, Prince Consort Road, London, SW7 2BB, UK
| | - Andrea Bassi
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci, 32, Milano, 20133, Italy.
- Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Piazza Leonardo da Vinci, 32, Milano, 20133, Italy.
| | - Francesca Bragheri
- Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Piazza Leonardo da Vinci, 32, Milano, 20133, Italy.
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2
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Aslan MK, Ding Y, Stavrakis S, deMello AJ. Smartphone Imaging Flow Cytometry for High-Throughput Single-Cell Analysis. Anal Chem 2023; 95:14526-14532. [PMID: 37733469 DOI: 10.1021/acs.analchem.3c03213] [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: 09/23/2023]
Abstract
We present a portable imaging flow cytometer comprising a smartphone, a small-footprint optical framework, and a PDMS-based microfluidic device. Flow cytometric analysis is performed in a sheathless manner via elasto-inertial focusing with a custom-written Android program, integrating a graphical user interface (GUI) that provides a high degree of user control over image acquisition. The proposed system offers two different operational modes. First, "post-processing" mode enables particle/cell sizing at throughputs of up to 67 000 particles/s. Alternatively, "real-time" mode allows for integrated cell/particle classification with machine learning at throughputs of 100 particles/s. To showcase the efficacy of our platform, polystyrene particles are accurately enumerated within heterogeneous populations using the post-processing mode. In real-time mode, an open-source machine learning algorithm is deployed within a custom-developed Android application to classify samples containing cells of similar size but with different morphologies. The flow cytometer can extract high-resolution bright-field images with a spatial resolution <700 nm using the developed machine learning-based algorithm, achieving classification accuracies of 97% and 93% for Jurkat and EL4 cells, respectively. Our results confirm that the smartphone imaging flow cytometer (sIFC) is capable of both enumerating single particles in flow and identifying morphological features with high resolution and minimal hardware.
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Affiliation(s)
- Mahmut Kamil Aslan
- Institute for Chemical and Bioengineering, ETH Zurich, 8093 Zürich, Switzerland
| | - Yun Ding
- Institute for Chemical and Bioengineering, ETH Zurich, 8093 Zürich, Switzerland
| | - Stavros Stavrakis
- Institute for Chemical and Bioengineering, ETH Zurich, 8093 Zürich, Switzerland
| | - Andrew J deMello
- Institute for Chemical and Bioengineering, ETH Zurich, 8093 Zürich, Switzerland
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3
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Zhu T, Nie J, Yu T, Zhu D, Huang Y, Chen Z, Gu Z, Tang J, Li D, Fei P. Large-scale high-throughput 3D culture, imaging, and analysis of cell spheroids using microchip-enhanced light-sheet microscopy. BIOMEDICAL OPTICS EXPRESS 2023; 14:1659-1669. [PMID: 37078040 PMCID: PMC10110308 DOI: 10.1364/boe.485217] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 02/24/2023] [Accepted: 03/06/2023] [Indexed: 05/03/2023]
Abstract
Light sheet microscopy combined with a microchip is an emerging tool in biomedical research that notably improves efficiency. However, microchip-enhanced light-sheet microscopy is limited by noticeable aberrations induced by the complex refractive indices in the chip. Herein, we report a droplet microchip that is specifically engineered to be capable of large-scale culture of 3D spheroids (over 600 samples per chip) and has a polymer index matched to water (difference <1%). When combined with a lab-built open-top light-sheet microscope, this microchip-enhanced microscopy technique allows 3D time-lapse imaging of the cultivated spheroids with ∼2.5-µm single-cell resolution and a high throughput of ∼120 spheroids per minute. This technique was validated by a comparative study on the proliferation and apoptosis rates of hundreds of spheroids with or without treatment with the apoptosis-inducing drug Staurosporine.
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Affiliation(s)
- Tingting Zhu
- School of Optical and Electronic Information - Wuhan National Laboratory for Optoelectronics - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Jun Nie
- Institute for Cell Analysis, Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Tingting Yu
- Britton Chance Center for Biomedical Photonics - MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - Dan Zhu
- Britton Chance Center for Biomedical Photonics - MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - Yanyi Huang
- Institute for Cell Analysis, Shenzhen Bay Laboratory, Shenzhen 518132, China
- College of Chemistry, Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China
| | - Zaozao Chen
- State Key Laboratory of Bioelectronics School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China
| | - Zhongze Gu
- State Key Laboratory of Bioelectronics School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China
| | - Jiang Tang
- School of Optical and Electronic Information - Wuhan National Laboratory for Optoelectronics - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Dongyu Li
- School of Optical and Electronic Information - Wuhan National Laboratory for Optoelectronics - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Peng Fei
- School of Optical and Electronic Information - Wuhan National Laboratory for Optoelectronics - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, Wuhan 430074, China
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4
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Gebreyesus ST, Muneer G, Huang CC, Siyal AA, Anand M, Chen YJ, Tu HL. Recent advances in microfluidics for single-cell functional proteomics. LAB ON A CHIP 2023; 23:1726-1751. [PMID: 36811978 DOI: 10.1039/d2lc01096h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Single-cell proteomics (SCP) reveals phenotypic heterogeneity by profiling individual cells, their biological states and functional outcomes upon signaling activation that can hardly be probed via other omics characterizations. This has become appealing to researchers as it enables an overall more holistic view of biological details underlying cellular processes, disease onset and progression, as well as facilitates unique biomarker identification from individual cells. Microfluidic-based strategies have become methods of choice for single-cell analysis because they allow facile assay integrations, such as cell sorting, manipulation, and content analysis. Notably, they have been serving as an enabling technology to improve the sensitivity, robustness, and reproducibility of recently developed SCP methods. Critical roles of microfluidics technologies are expected to further expand rapidly in advancing the next phase of SCP analysis to reveal more biological and clinical insights. In this review, we will capture the excitement of the recent achievements of microfluidics methods for both targeted and global SCP, including efforts to enhance the proteomic coverage, minimize sample loss, and increase multiplexity and throughput. Furthermore, we will discuss the advantages, challenges, applications, and future prospects of SCP.
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Affiliation(s)
- Sofani Tafesse Gebreyesus
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Nano Science and Technology Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan
| | - Gul Muneer
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Institute of Biochemical Sciences, National Taiwan University, Taipei 10617, Taiwan
| | | | - Asad Ali Siyal
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
| | - Mihir Anand
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Institute of Biochemical Sciences, National Taiwan University, Taipei 10617, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei 10617, Taiwan
| | - Hsiung-Lin Tu
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Nano Science and Technology Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei 10617, Taiwan
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5
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Gong Y, Zeng M, Zhu Y, Li S, Zhao W, Zhang C, Zhao T, Wang K, Yang J, Bai J. Flow Cytometry with Anti-Diffraction Light Sheet (ADLS) by Spatial Light Modulation. MICROMACHINES 2023; 14:679. [PMID: 36985086 PMCID: PMC10054044 DOI: 10.3390/mi14030679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 03/15/2023] [Accepted: 03/17/2023] [Indexed: 06/18/2023]
Abstract
Flow cytometry is a widespread and powerful technique whose resolution is determined by its capacity to accurately distinguish fluorescently positive populations from negative ones. However, most informative results are discarded while performing the measurements of conventional flow cytometry, e.g., the cell size, shape, morphology, and distribution or location of labeled exosomes within the unpurified biological samples. Herein, we propose a novel approach using an anti-diffraction light sheet with anisotroic feature to excite fluorescent tags. Constituted by an anti-diffraction Bessel-Gaussian beam array, the light sheet is 12 μm wide, 12 μm high, and has a thickness of ~0.8 μm. The intensity profile of the excited fluorescent signal can, therefore, reflect the size and allow samples in the range from O (100 nm) to 10 μm (e.g., blood cells) to be transported via hydrodynamic focusing in a microfluidic chip. The sampling rate is 500 kHz, which provides a capability of high throughput without sacrificing the spatial resolution. Consequently, the proposed anti-diffraction light sheet flow cytometry (ADLSFC) can obtain more informative results than the conventional methodologies, and is able to provide multiple characteristics (e.g., the size and distribution of fluorescent signal) helping to distinguish the target samples from the complex backgrounds.
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Affiliation(s)
- Yanyan Gong
- State Key Laboratory of Photon-Technology in Western China Energy, International Collaborative Center on Photoelectric Technology and Nano Functional Materials, Institute of Photonics & Photon Technology, Northwest University, Xi’an 710127, China
| | - Ming Zeng
- State Key Laboratory of Photon-Technology in Western China Energy, International Collaborative Center on Photoelectric Technology and Nano Functional Materials, Institute of Photonics & Photon Technology, Northwest University, Xi’an 710127, China
| | - Yueqiang Zhu
- State Key Laboratory of Photon-Technology in Western China Energy, International Collaborative Center on Photoelectric Technology and Nano Functional Materials, Institute of Photonics & Photon Technology, Northwest University, Xi’an 710127, China
| | - Shangyu Li
- State Key Laboratory of Photon-Technology in Western China Energy, International Collaborative Center on Photoelectric Technology and Nano Functional Materials, Institute of Photonics & Photon Technology, Northwest University, Xi’an 710127, China
| | - Wei Zhao
- State Key Laboratory of Photon-Technology in Western China Energy, International Collaborative Center on Photoelectric Technology and Nano Functional Materials, Institute of Photonics & Photon Technology, Northwest University, Xi’an 710127, China
| | - Ce Zhang
- State Key Laboratory of Photon-Technology in Western China Energy, International Collaborative Center on Photoelectric Technology and Nano Functional Materials, Institute of Photonics & Photon Technology, Northwest University, Xi’an 710127, China
| | - Tianyun Zhao
- School of Automation, Northwestern Polytechnical University, Xi’an 710072, China
| | - Kaige Wang
- State Key Laboratory of Photon-Technology in Western China Energy, International Collaborative Center on Photoelectric Technology and Nano Functional Materials, Institute of Photonics & Photon Technology, Northwest University, Xi’an 710127, China
| | - Jiangcun Yang
- Department of Transfusion Medicine, Shaanxi Provincial People’s Hospital, Xi’an 710068, China
| | - Jintao Bai
- State Key Laboratory of Photon-Technology in Western China Energy, International Collaborative Center on Photoelectric Technology and Nano Functional Materials, Institute of Photonics & Photon Technology, Northwest University, Xi’an 710127, China
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6
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Son J, Mandracchia B, Silva Trenkle AD, Kwong GA, Jia S. Portable light-sheet optofluidic microscopy for 3D fluorescence imaging flow cytometry. LAB ON A CHIP 2023; 23:624-630. [PMID: 36633262 PMCID: PMC9931680 DOI: 10.1039/d2lc01024k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Imaging flow cytometry (IFC) combines conventional flow cytometry with optical microscopy, allowing for high-throughput, multi-parameter screening of single-cell specimens with morphological and spatial information. However, current 3D IFC systems are limited by instrumental complexity and incompatibility with available microfluidic devices or operations. Here, we report portable light-sheet optofluidic microscopy (PLSOM) for 3D fluorescence cytometric imaging. PLSOM exploits a compact, open-top light-sheet configuration compatible with commonly adopted microfluidic chips. The system offers a subcellular resolution (2-4 μm) in all three dimensions, high throughput (∼1000 cells per s), and portability (30 cm (l) × 10 cm (w) × 26 cm (h)). We demonstrated PLSOM for 3D IFC using various phantom and cell systems. The low-cost and custom-built architecture of PLSOM permits easy adaptability and dissemination for broad 3D flow cytometric investigations.
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Affiliation(s)
- Jeonghwan Son
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA.
| | - Biagio Mandracchia
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA.
| | - Aaron D Silva Trenkle
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA.
| | - Gabriel A Kwong
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA.
- Parker H. Petit Institute of Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Shu Jia
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA.
- Parker H. Petit Institute of Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA 30332, USA
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7
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Ahmad A, Sala F, Paiè P, Candeo A, D'Annunzio S, Zippo A, Frindel C, Osellame R, Bragheri F, Bassi A, Rousseau D. On the robustness of machine learning algorithms toward microfluidic distortions for cell classification via on-chip fluorescence microscopy. LAB ON A CHIP 2022; 22:3453-3463. [PMID: 35946995 DOI: 10.1039/d2lc00482h] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Single-cell imaging and sorting are critical technologies in biology and clinical applications. The power of these technologies is increased when combined with microfluidics, fluorescence markers, and machine learning. However, this quest faces several challenges. One of these is the effect of the sample flow velocity on the classification performances. Indeed, cell flow speed affects the quality of image acquisition by increasing motion blur and decreasing the number of acquired frames per sample. We investigate how these visual distortions impact the final classification task in a real-world use-case of cancer cell screening, using a microfluidic platform in combination with light sheet fluorescence microscopy. We demonstrate, by analyzing both simulated and experimental data, that it is possible to achieve high flow speed and high accuracy in single-cell classification. We prove that it is possible to overcome the 3D slice variability of the acquired 3D volumes, by relying on their 2D sum z-projection transformation, to reach an efficient real time classification with an accuracy of 99.4% using a convolutional neural network with transfer learning from simulated data. Beyond this specific use-case, we provide a web platform to generate a synthetic dataset and to investigate the effect of flow speed on cell classification for any biological samples and a large variety of fluorescence microscopes (https://www.creatis.insa-lyon.fr/site7/en/MicroVIP).
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Affiliation(s)
- Ali Ahmad
- Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), UMR INRAE IRHS, Université d'Angers, 62 Avenue Notre Dame du Lac, 49000 Angers, France.
- Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), CNRS UMR 5220 - INSERM U1206, Université Lyon 1, Insa de Lyon, Lyon, France
| | - Federico Sala
- Department of Physics, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
- Istituto di Fotonica e Nanotecnologie, CNR, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
| | - Petra Paiè
- Istituto di Fotonica e Nanotecnologie, CNR, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
| | - Alessia Candeo
- Department of Physics, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
| | | | | | - Carole Frindel
- Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), CNRS UMR 5220 - INSERM U1206, Université Lyon 1, Insa de Lyon, Lyon, France
| | - Roberto Osellame
- Department of Physics, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
- Istituto di Fotonica e Nanotecnologie, CNR, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
| | - Francesca Bragheri
- Istituto di Fotonica e Nanotecnologie, CNR, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
| | - Andrea Bassi
- Department of Physics, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
- Istituto di Fotonica e Nanotecnologie, CNR, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
| | - David Rousseau
- Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), UMR INRAE IRHS, Université d'Angers, 62 Avenue Notre Dame du Lac, 49000 Angers, France.
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8
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Cai Y, Chen Y, Xia Y, Zheng S, Liu Z, Shi K. Single-Lens Light-Sheet Fluorescence Microscopy Based on Micro-Mirror Array. LASER & PHOTONICS REVIEWS 2022; 16:2100026. [PMID: 36389089 PMCID: PMC9648671 DOI: 10.1002/lpor.202100026] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Conventional light sheet fluorescence microscopy (LSFM) utilizes two perpendicularly arranged objective lenses for optical excitation and detection, respectively. Such a configuration often limits the use of high-numerical-aperture (NA) objectives or requires specially designed long-working-distance objectives. Here, a LSFM based on a micro-mirror array (MMA) to enable light sheet imaging with a single objective lens is reported. The planar fluorescent emission excited by the light sheet illumination is collected by the same objective, relayed onto an MMA and detected by a side-view camera. The proposed scheme makes LSFM compatible to single objective imaging system and shows promising candidacy for high spatiotemporal imaging.
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Affiliation(s)
- Yanhui Cai
- State Key Laboratory for Mesoscopic Physics, Department of Physics, Peking University, Beijing 100871, P. R. China; Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, Shanxi 030006, P. R. China; Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519000, P. R. China
| | - Yizhu Chen
- Department of Electrical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Yiqiu Xia
- Department of Biomedical Engineering, Penn State Material Research Institute, The Pennsylvania State University, University Park, PA 16802, USA
| | - Siyang Zheng
- Biomedical Engineering and Electrical & Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Zhiwen Liu
- Department of Electrical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Kebin Shi
- State Key Laboratory for Mesoscopic Physics, Department of Physics, Peking University, Beijing 100871, P. R. China; Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, Shanxi 030006, P. R. China; Peking University Yangtze Delta Institute of Optoelectronics, Nantong, Jiangsu 226010, P. R. China
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9
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Huang K, Matsumura H, Zhao Y, Herbig M, Yuan D, Mineharu Y, Harmon J, Findinier J, Yamagishi M, Ohnuki S, Nitta N, Grossman AR, Ohya Y, Mikami H, Isozaki A, Goda K. Deep imaging flow cytometry. LAB ON A CHIP 2022; 22:876-889. [PMID: 35142325 DOI: 10.1039/d1lc01043c] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Imaging flow cytometry (IFC) has become a powerful tool for diverse biomedical applications by virtue of its ability to image single cells in a high-throughput manner. However, there remains a challenge posed by the fundamental trade-off between throughput, sensitivity, and spatial resolution. Here we present deep-learning-enhanced imaging flow cytometry (dIFC) that circumvents this trade-off by implementing an image restoration algorithm on a virtual-freezing fluorescence imaging (VIFFI) flow cytometry platform, enabling higher throughput without sacrificing sensitivity and spatial resolution. A key component of dIFC is a high-resolution (HR) image generator that synthesizes "virtual" HR images from the corresponding low-resolution (LR) images acquired with a low-magnification lens (10×/0.4-NA). For IFC, a low-magnification lens is favorable because of reduced image blur of cells flowing at a higher speed, which allows higher throughput. We trained and developed the HR image generator with an architecture containing two generative adversarial networks (GANs). Furthermore, we developed dIFC as a method by combining the trained generator and IFC. We characterized dIFC using Chlamydomonas reinhardtii cell images, fluorescence in situ hybridization (FISH) images of Jurkat cells, and Saccharomyces cerevisiae (budding yeast) cell images, showing high similarities of dIFC images to images obtained with a high-magnification lens (40×/0.95-NA), at a high flow speed of 2 m s-1. We lastly employed dIFC to show enhancements in the accuracy of FISH-spot counting and neck-width measurement of budding yeast cells. These results pave the way for statistical analysis of cells with high-dimensional spatial information.
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Affiliation(s)
- Kangrui Huang
- Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan.
| | - Hiroki Matsumura
- Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan.
| | - Yaqi Zhao
- Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan.
| | - Maik Herbig
- Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan.
| | - Dan Yuan
- Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan.
| | - Yohei Mineharu
- Department of Neurosurgery, Kyoto University, Kyoto 606-8507, Japan
- Department of Artificial Intelligence in Healthcare and Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Jeffrey Harmon
- Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan.
| | - Justin Findinier
- Department of Plant Biology, The Carnegie Institution for Science, Stanford, California 94305, USA
| | - Mai Yamagishi
- Department of Biological Sciences, The University of Tokyo, Tokyo 113-0033, Japan
| | - Shinsuke Ohnuki
- Department of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8562, Japan
| | | | - Arthur R Grossman
- Department of Plant Biology, The Carnegie Institution for Science, Stanford, California 94305, USA
- Department of Biology, Stanford University, Stanford, California 94305, USA
| | - Yoshikazu Ohya
- Department of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8562, Japan
- Collaborative Research Institute for Innovative Microbiology, The University of Tokyo, Tokyo 113-8654, Japan
| | - Hideharu Mikami
- Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan.
- PRESTO, Japan Science and Technology Agency, Saitama 332-0012, Japan
| | - Akihiro Isozaki
- Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan.
| | - Keisuke Goda
- Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan.
- Department of Bioengineering, University of California, Los Angeles, California 90095, USA
- Institute of Technological Sciences, Wuhan University, Hubei 430072, China
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10
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Modular multimodal platform for classical and high throughput light sheet microscopy. Sci Rep 2022; 12:1969. [PMID: 35121789 PMCID: PMC8817037 DOI: 10.1038/s41598-022-05940-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 01/17/2022] [Indexed: 11/30/2022] Open
Abstract
Light-sheet fluorescence microscopy (LSFM) has become an important tool for biological and biomedical research. Although several illumination and detection strategies have been developed, the sample mounting still represents a cumbersome procedure as this is highly dependent on the type of sample and often this might be time consuming. This prevents the use of LSFM in other promising applications in which a fast and straightforward sample-mounting procedure and imaging are essential. These include the high-throughput research fields, e.g. in drug screenings and toxicology studies. Here we present a new imaging paradigm for LSFM, which exploits modularity to offer multimodal imaging and straightforward sample mounting strategy, enhancing the flexibility and throughput of the system. We describe its implementation in which the sample can be imaged either as in any classical configuration, as it flows through the light-sheet using a fluidic approach, or a combination of both. We also evaluate its ability to image a variety of samples, from zebrafish embryos and larvae to 3D complex cell cultures.
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11
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Tiwari A, Chaskar J, Ali A, Arivarasan VK, Chaskar AC. Role of Sensor Technology in Detection of the Breast Cancer. BIONANOSCIENCE 2022. [DOI: 10.1007/s12668-021-00921-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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12
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Schraivogel D, Kuhn TM, Rauscher B, Rodríguez-Martínez M, Paulsen M, Owsley K, Middlebrook A, Tischer C, Ramasz B, Ordoñez-Rueda D, Dees M, Cuylen-Haering S, Diebold E, Steinmetz LM. High-speed fluorescence image-enabled cell sorting. Science 2022; 375:315-320. [PMID: 35050652 DOI: 10.1126/science.abj3013] [Citation(s) in RCA: 93] [Impact Index Per Article: 46.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Fast and selective isolation of single cells with unique spatial and morphological traits remains a technical challenge. Here, we address this by establishing high-speed image-enabled cell sorting (ICS), which records multicolor fluorescence images and sorts cells based on measurements from image data at speeds up to 15,000 events per second. We show that ICS quantifies cell morphology and localization of labeled proteins and increases the resolution of cell cycle analyses by separating mitotic stages. We combine ICS with CRISPR-pooled screens to identify regulators of the nuclear factor κB (NF-κB) pathway, enabling the completion of genome-wide image-based screens in about 9 hours of run time. By assessing complex cellular phenotypes, ICS substantially expands the phenotypic space accessible to cell-sorting applications and pooled genetic screening.
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Affiliation(s)
- Daniel Schraivogel
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Terra M Kuhn
- Cell Biology and Biophysics Unit, EMBL, Heidelberg, Germany
| | - Benedikt Rauscher
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | | | - Malte Paulsen
- Flow Cytometry Core Facility, EMBL, Heidelberg, Germany
| | | | | | | | - Beáta Ramasz
- Flow Cytometry Core Facility, EMBL, Heidelberg, Germany
| | | | - Martina Dees
- Cell Biology and Biophysics Unit, EMBL, Heidelberg, Germany
| | | | | | - Lars M Steinmetz
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.,Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.,Stanford Genome Technology Center, Palo Alto, CA, USA
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13
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Light sheet based volume flow cytometry (VFC) for rapid volume reconstruction and parameter estimation on the go. Sci Rep 2022; 12:78. [PMID: 34997009 PMCID: PMC8741756 DOI: 10.1038/s41598-021-03902-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 12/06/2021] [Indexed: 11/08/2022] Open
Abstract
Optical imaging is paramount for disease diagnosis and to access its progression over time. The proposed optical flow imaging (VFC/iLIFE) is a powerful technique that adds new capabilities (3D volume visualization, organelle-level resolution, and multi-organelle screening) to the existing system. Unlike state-of-the-art point-illumination-based biomedical imaging techniques, the sheet-based VFC technique is capable of single-shot sectional visualization, high throughput interrogation, real-time parameter estimation, and instant volume reconstruction with organelle-level resolution of live specimens. The specimen flow system was realized on a multichannel (Y-type) microfluidic chip that enables visualization of organelle distribution in several cells in-parallel at a relatively high flow-rate (2000 nl/min). The calibration of VFC system requires the study of point emitters (fluorescent beads) at physiologically relevant flow-rates (500-2000 nl/min) for determining flow-induced optical aberration in the system point spread function (PSF). Subsequently, the recorded raw images and volumes were computationally deconvolved with flow-variant PSF to reconstruct the cell volume. High throughput investigation of the mitochondrial network in HeLa cancer cell was carried out at sub-cellular resolution in real-time and critical parameters (mitochondria count and size distribution, morphology, entropy, and cell strain statistics) were determined on-the-go. These parameters determine the physiological state of cells, and the changes over-time, revealing the metastatic progression of diseases. Overall, the developed VFC system enables real-time monitoring of sub-cellular organelle organization at a high-throughput with high-content capacity.
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14
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Vargas-Ordaz EJ, Gorelick S, York HM, Liu B, Halls ML, Arumugam S, Neild A, de Marco A, Cadarso VJ. Three-dimensional imaging on a chip using optofluidics light-sheet fluorescence microscopy. LAB ON A CHIP 2021; 21:2945-2954. [PMID: 34124739 DOI: 10.1039/d1lc00098e] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Volumetric, sub-micron to micron level resolution imaging is necessary to assay phenotypes or characteristics at the sub-cellular/organelle scale. However, three-dimensional fluorescence imaging of cells is typically low throughput or compromises on the achievable resolution in space and time. Here, we capitalise on the flow control capabilities of microfluidics and combine it with microoptics to integrate light-sheet based imaging directly into a microfluidic chip. Our optofluidic system flows suspended cells through a sub-micrometer thick light-sheet formed using micro-optical components that are cast directly in polydimethylsiloxane (PDMS). This design ensures accurate alignment, drift-free operation, and easy integration with conventional microfluidics, while providing sufficient spatial resolution, optical sectioning and volumetric data acquisition. We demonstrate imaging rates of 120 ms per cell at sub-μm resolution, that allow extraction of complex cellular phenotypes, exemplified by imaging of cell clusters, receptor distribution, and the analysis of endosomal size changes.
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Affiliation(s)
- Erick J Vargas-Ordaz
- Department of Mechanical and Aerospace Engineering, Monash University, Clayton, VIC 3800, Australia. and Centre to Impact Antimicrobial Resistance - Sustainable Solutions, Monash University, Clayton, 3800, Victoria, Australia
| | - Sergey Gorelick
- Department of Biochemistry and Molecular Biology, Monash University, 3800 Clayton, Victoria, Australia. and ARC Centre of Excellence in Advanced Molecular Imaging, Monash University, 3800 Clayton, Victoria, Australia
| | - Harrison M York
- ARC Centre of Excellence in Advanced Molecular Imaging, Monash University, 3800 Clayton, Victoria, Australia and European Molecular Biology Laboratory (EMBL) Australia, Monash University, 3800 Clayton, Victoria, Australia and Department of Anatomy and Developmental Biology, Monash University, 3800 Clayton, Victoria, Australia
| | - Bonan Liu
- Drug Discovery Biology Theme, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville 3052, Victoria, Australia
| | - Michelle L Halls
- Drug Discovery Biology Theme, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville 3052, Victoria, Australia
| | - Senthil Arumugam
- ARC Centre of Excellence in Advanced Molecular Imaging, Monash University, 3800 Clayton, Victoria, Australia and European Molecular Biology Laboratory (EMBL) Australia, Monash University, 3800 Clayton, Victoria, Australia and Department of Anatomy and Developmental Biology, Monash University, 3800 Clayton, Victoria, Australia
| | - Adrian Neild
- Department of Mechanical and Aerospace Engineering, Monash University, Clayton, VIC 3800, Australia.
| | - Alex de Marco
- Department of Biochemistry and Molecular Biology, Monash University, 3800 Clayton, Victoria, Australia. and ARC Centre of Excellence in Advanced Molecular Imaging, Monash University, 3800 Clayton, Victoria, Australia
| | - Victor J Cadarso
- Department of Mechanical and Aerospace Engineering, Monash University, Clayton, VIC 3800, Australia. and Centre to Impact Antimicrobial Resistance - Sustainable Solutions, Monash University, Clayton, 3800, Victoria, Australia and The Melbourne Centre for Nanofabrication, Victorian Node - Australian National Fabrication Facility, Clayton, Victoria 3800, Australia
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15
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Yordanov S, Neuhaus K, Hartmann R, Díaz-Pascual F, Vidakovic L, Singh PK, Drescher K. Single-objective high-resolution confocal light sheet fluorescence microscopy for standard biological sample geometries. BIOMEDICAL OPTICS EXPRESS 2021; 12:3372-3391. [PMID: 34221666 PMCID: PMC8221969 DOI: 10.1364/boe.420788] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 03/22/2021] [Accepted: 04/19/2021] [Indexed: 06/13/2023]
Abstract
Three-dimensional fluorescence-based imaging of living cells and organisms requires the sample to be exposed to substantial excitation illumination energy, typically causing phototoxicity and photobleaching. Light sheet fluorescence microscopy dramatically reduces phototoxicity, yet most implementations are limited to objective lenses with low numerical aperture and particular sample geometries that are built for specific biological systems. To overcome these limitations, we developed a single-objective light sheet fluorescence system for biological imaging based on axial plane optical microscopy and digital confocal slit detection, using either Bessel or Gaussian beam shapes. Compared to spinning disk confocal microscopy, this system displays similar optical resolution, but a significantly reduced photobleaching at the same signal level. This single-objective light sheet technique is built as an add-on module for standard research microscopes and the technique is compatible with high-numerical aperture oil immersion objectives and standard samples mounted on coverslips. We demonstrate the performance of this technique by imaging three-dimensional dynamic processes, including bacterial biofilm dispersal, the response of biofilms to osmotic shocks, and macrophage phagocytosis of bacterial cells.
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Affiliation(s)
- Stoyan Yordanov
- Max Planck Institute for Terrestrial Microbiology, Karl-von-Frisch-Straße 10, 35043 Marburg, Germany
- Equal contribution
| | - Konstantin Neuhaus
- Max Planck Institute for Terrestrial Microbiology, Karl-von-Frisch-Straße 10, 35043 Marburg, Germany
- Department of Physics, Philipps-Universität Marburg, Renthof 5, 35037 Marburg, Germany
- Equal contribution
| | - Raimo Hartmann
- Max Planck Institute for Terrestrial Microbiology, Karl-von-Frisch-Straße 10, 35043 Marburg, Germany
| | - Francisco Díaz-Pascual
- Max Planck Institute for Terrestrial Microbiology, Karl-von-Frisch-Straße 10, 35043 Marburg, Germany
| | - Lucia Vidakovic
- Max Planck Institute for Terrestrial Microbiology, Karl-von-Frisch-Straße 10, 35043 Marburg, Germany
| | - Praveen K. Singh
- Max Planck Institute for Terrestrial Microbiology, Karl-von-Frisch-Straße 10, 35043 Marburg, Germany
| | - Knut Drescher
- Max Planck Institute for Terrestrial Microbiology, Karl-von-Frisch-Straße 10, 35043 Marburg, Germany
- Department of Physics, Philipps-Universität Marburg, Renthof 5, 35037 Marburg, Germany
- Biozentrum, University of Basel, Spitalstrasse 41, CH-4056 Basel, Switzerland
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16
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Holzner G, Mateescu B, van Leeuwen D, Cereghetti G, Dechant R, Stavrakis S, deMello A. High-throughput multiparametric imaging flow cytometry: toward diffraction-limited sub-cellular detection and monitoring of sub-cellular processes. Cell Rep 2021; 34:108824. [PMID: 33691119 DOI: 10.1016/j.celrep.2021.108824] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 12/07/2020] [Accepted: 02/12/2021] [Indexed: 02/06/2023] Open
Abstract
We present a sheathless, microfluidic imaging flow cytometer that incorporates stroboscopic illumination for blur-free fluorescence detection at ultra-high analytical throughput. The imaging platform is capable of multiparametric fluorescence quantification and sub-cellular localization of these structures down to 500 nm with microscopy image quality. We demonstrate the efficacy of the approach through the analysis and localization of P-bodies and stress granules in yeast and human cells using fluorescence and bright-field detection at analytical throughputs in excess of 60,000 and 400,000 cells/s, respectively. Results highlight the utility of our imaging flow cytometer in directly investigating phase-separated compartments within cellular environments and screening rare events at the sub-cellular level for a range of diagnostic applications.
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Affiliation(s)
- Gregor Holzner
- Institute for Chemical & Bioengineering, ETH Zürich, Vladimir Prelog Weg 1, 8093 Zürich, Switzerland
| | - Bogdan Mateescu
- Brain Research Institute, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland
| | - Daniel van Leeuwen
- Department of Biology, ETH Zürich, Universitätstrasse 2, 8092 Zurich, Switzerland
| | - Gea Cereghetti
- Institute of Biochemistry, ETH Zürich, Otto-Stern-Weg 3, 8093 Zürich, Switzerland
| | - Reinhard Dechant
- Institute of Biochemistry, ETH Zürich, Otto-Stern-Weg 3, 8093 Zürich, Switzerland
| | - Stavros Stavrakis
- Institute for Chemical & Bioengineering, ETH Zürich, Vladimir Prelog Weg 1, 8093 Zürich, Switzerland.
| | - Andrew deMello
- Institute for Chemical & Bioengineering, ETH Zürich, Vladimir Prelog Weg 1, 8093 Zürich, Switzerland.
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17
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Memeo R, Paiè P, Sala F, Castriotta M, Guercio C, Vaccari T, Osellame R, Bassi A, Bragheri F. Automatic imaging of Drosophila embryos with light sheet fluorescence microscopy on chip. JOURNAL OF BIOPHOTONICS 2021; 14:e202000396. [PMID: 33295053 DOI: 10.1002/jbio.202000396] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 11/22/2020] [Accepted: 12/07/2020] [Indexed: 06/12/2023]
Abstract
We present a microscope on chip for automated imaging of Drosophila embryos by light sheet fluorescence microscopy. This integrated device, constituted by both optical and microfluidic components, allows the automatic acquisition of a 3D stack of images for specimens diluted in a liquid suspension. The device has been fully optimized to address the challenges related to the specimens under investigation. Indeed, the thickness and the high ellipticity of Drosophila embryos can degrade the image quality. In this regard, optical and fluidic optimization has been carried out to implement dual-sided illumination and automatic sample orientation. In addition, we highlight the dual color investigation capabilities of this device, by processing two sample populations encoding different fluorescent proteins. This work was made possible by the versatility of the used fabrication technique, femtosecond laser micromachining, which allows straightforward fabrication of both optical and fluidic components in glass substrates.
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Affiliation(s)
- Roberto Memeo
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci, Milan, Italy
- Istituto di Fotonica e Nanotecnologie (IFN)-CNR, Piazza Leonardo da Vinci, Milan, Italy
| | - Petra Paiè
- Istituto di Fotonica e Nanotecnologie (IFN)-CNR, Piazza Leonardo da Vinci, Milan, Italy
| | - Federico Sala
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci, Milan, Italy
- Istituto di Fotonica e Nanotecnologie (IFN)-CNR, Piazza Leonardo da Vinci, Milan, Italy
| | - Michele Castriotta
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci, Milan, Italy
- Istituto di Fotonica e Nanotecnologie (IFN)-CNR, Piazza Leonardo da Vinci, Milan, Italy
| | - Chiara Guercio
- Dipartimento di Bioscienze, Università degli Studi di Milano, via Celoria, Milan, Italy
| | - Thomas Vaccari
- Dipartimento di Bioscienze, Università degli Studi di Milano, via Celoria, Milan, Italy
| | - Roberto Osellame
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci, Milan, Italy
- Istituto di Fotonica e Nanotecnologie (IFN)-CNR, Piazza Leonardo da Vinci, Milan, Italy
| | - Andrea Bassi
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci, Milan, Italy
- Istituto di Fotonica e Nanotecnologie (IFN)-CNR, Piazza Leonardo da Vinci, Milan, Italy
| | - Francesca Bragheri
- Istituto di Fotonica e Nanotecnologie (IFN)-CNR, Piazza Leonardo da Vinci, Milan, Italy
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18
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Abstract
Microphysiological systems (MPS), often referred to as "organ-on-chips," are microfluidic-based in vitro models that aim to recapitulate the dynamic chemical and mechanical microenvironment of living organs. MPS promise to bridge the gap between in vitro and in vivo models and ultimately improve the translation from preclinical animal studies to clinical trials. However, despite the explosion of interest in this area in recent years, and the obvious rewards for such models that could improve R&D efficiency and reduce drug attrition in the clinic, the pharmaceutical industry has been slow to fully adopt this technology. The ability to extract robust, quantitative information from MPS at scale is a key requirement if these models are to impact drug discovery and the subsequent drug development process. Microscopy imaging remains a core technology that enables the capture of information at the single-cell level and with subcellular resolution. Furthermore, such imaging techniques can be automated, increasing throughput and enabling compound screening. In this review, we discuss a range of imaging techniques that have been applied to MPS of varying focus, such as organoids and organ-chip-type models. We outline the opportunities these technologies can bring in terms of understanding mechanistic biology, but also how they could be used in higher-throughput screens, widening the scope of their impact in drug discovery. We discuss the associated challenges of imaging these complex models and the steps required to enable full exploitation. Finally, we discuss the requirements for MPS, if they are to be applied at a scale necessary to support drug discovery projects.
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Affiliation(s)
- Samantha Peel
- Discovery Biology, Discovery Sciences, R&D, AstraZeneca, Cambridge, United Kingdom
| | - Mark Jackman
- Advanced Drug Delivery, Pharmaceutical Sciences, R&D, AstraZeneca, Cambridge, United Kingdom
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19
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Xu T, Lim YJ, Zheng Y, Jung M, Gaus K, Gardiner EE, Lee WM. Modified inverted selective plane illumination microscopy for sub-micrometer imaging resolution in polydimethylsiloxane soft lithography devices. LAB ON A CHIP 2020; 20:3960-3969. [PMID: 32940306 DOI: 10.1039/d0lc00598c] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
Moldable, transparent polydimethylsiloxane (PDMS) elastomer microdevices enable a broad range of complex studies of three-dimensional cellular networks in their microenvironment in vitro. However, the uneven distribution of refractive index change, external to PDMS devices and internally in the sample chamber, creates a significant optical path difference (OPD) that distorts the light sheet beam and so restricts diffraction limited performance. We experimentally showed that an OPD of 120 μm results in the broadening of the lateral point spread function by over 4-fold. In this paper, we demonstrate steps to adapt a commercial inverted selective plane illumination microscope (iSPIM) and remove the OPD so as to achieve sub-micrometer imaging ranging from 0.6 ± 0.04 μm to 0.91 ± 0.03 μm of a fluorescence biological sample suspended in regular saline (RI ≈1.34) enclosed in 1.2 to 2 mm thick micromolded PDMS microdevices. We have proven that the removal of the OPD from the external PDMS layer by refractive index (RI) matching with a readily accessible, inexpensive sucrose solution is critical to achieve a >3-fold imaging resolution improvement. To monitor the RI matching process, a single-mode fiber (SMF) illuminator was integrated into the iSPIM. To remove the OPD inside the PDMS channel, we used an electrically tunable lens (ETL) that par-focuses the light sheet beam with the detection objective lens and so minimised axial distortions to attain sub-micrometer imaging resolution. We termed this new light sheet imaging protocol as modified inverted selective plane illumination microscopy (m-iSPIM). Using the high spatial-temporal 3D imaging of m-iSPIM, we experimentally captured single platelet (≈2 μm) recruitment to a platelet aggregate (22.5 μm × 22.5 μm × 6 μm) under flow at a 150 μm depth within a microfluidic channel. m-iSPIM paves the way for the application of light sheet imaging to a wide range of 3D biological models in microfluidic devices which recapitulate features of the physiological microenvironment and elucidate subcellular responses.
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Affiliation(s)
- Tienan Xu
- Research School of Electrical, Energy and Materials Engineering, College of Engineering and Computer Science, The Australian National University, Canberra, ACT 2601, Australia.
| | - Yean Jin Lim
- Research School of Electrical, Energy and Materials Engineering, College of Engineering and Computer Science, The Australian National University, Canberra, ACT 2601, Australia. and ACRF Department of Cancer Biology and Therapeutics, The John Curtin School of Medical Research, The Australian National University, Canberra, ACT 2601, Australia
| | - Yujie Zheng
- Research School of Electrical, Energy and Materials Engineering, College of Engineering and Computer Science, The Australian National University, Canberra, ACT 2601, Australia.
| | - MoonSun Jung
- EMBL Australia Node in Single Molecule Science and ARC Centre of Excellence in Advanced Molecular Imaging, The University of New South Wales, Sydney, NSW 2052, Australia
| | - Katharina Gaus
- EMBL Australia Node in Single Molecule Science and ARC Centre of Excellence in Advanced Molecular Imaging, The University of New South Wales, Sydney, NSW 2052, Australia
| | - Elizabeth E Gardiner
- ACRF Department of Cancer Biology and Therapeutics, The John Curtin School of Medical Research, The Australian National University, Canberra, ACT 2601, Australia
| | - Woei Ming Lee
- Research School of Electrical, Energy and Materials Engineering, College of Engineering and Computer Science, The Australian National University, Canberra, ACT 2601, Australia. and ACRF Department of Cancer Biology and Therapeutics, The John Curtin School of Medical Research, The Australian National University, Canberra, ACT 2601, Australia and ARC Centre of Excellence in Advanced Molecular Imaging, The Australian National University, Canberra, ACT 2601, Australia
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20
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Isozaki A, Harmon J, Zhou Y, Li S, Nakagawa Y, Hayashi M, Mikami H, Lei C, Goda K. AI on a chip. LAB ON A CHIP 2020; 20:3074-3090. [PMID: 32644061 DOI: 10.1039/d0lc00521e] [Citation(s) in RCA: 60] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Artificial intelligence (AI) has dramatically changed the landscape of science, industry, defence, and medicine in the last several years. Supported by considerably enhanced computational power and cloud storage, the field of AI has shifted from mostly theoretical studies in the discipline of computer science to diverse real-life applications such as drug design, material discovery, speech recognition, self-driving cars, advertising, finance, medical imaging, and astronomical observation, where AI-produced outcomes have been proven to be comparable or even superior to the performance of human experts. In these applications, what is essentially important for the development of AI is the data needed for machine learning. Despite its prominent importance, the very first process of the AI development, namely data collection and data preparation, is typically the most laborious task and is often a limiting factor of constructing functional AI algorithms. Lab-on-a-chip technology, in particular microfluidics, is a powerful platform for both the construction and implementation of AI in a large-scale, cost-effective, high-throughput, automated, and multiplexed manner, thereby overcoming the above bottleneck. On this platform, high-throughput imaging is a critical tool as it can generate high-content information (e.g., size, shape, structure, composition, interaction) of objects on a large scale. High-throughput imaging can also be paired with sorting and DNA/RNA sequencing to conduct a massive survey of phenotype-genotype relations whose data is too complex to analyze with traditional computational tools, but is analyzable with the power of AI. In addition to its function as a data provider, lab-on-a-chip technology can also be employed to implement the developed AI for accurate identification, characterization, classification, and prediction of objects in mixed, heterogeneous, or unknown samples. In this review article, motivated by the excellent synergy between AI and lab-on-a-chip technology, we outline fundamental elements, recent advances, future challenges, and emerging opportunities of AI with lab-on-a-chip technology or "AI on a chip" for short.
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Affiliation(s)
- Akihiro Isozaki
- Department of Chemistry, University of Tokyo, Tokyo 113-0033, Japan. and Kanagawa Institute of Industrial Science and Technology, Kanagawa 213-0012, Japan
| | - Jeffrey Harmon
- Department of Chemistry, University of Tokyo, Tokyo 113-0033, Japan.
| | - Yuqi Zhou
- Department of Chemistry, University of Tokyo, Tokyo 113-0033, Japan.
| | - Shuai Li
- Department of Chemistry, University of Tokyo, Tokyo 113-0033, Japan. and The Cambridge Centre for Data-Driven Discovery, Cambridge University, Cambridge CB3 0WA, UK
| | - Yuta Nakagawa
- Department of Chemistry, University of Tokyo, Tokyo 113-0033, Japan.
| | - Mika Hayashi
- Department of Chemistry, University of Tokyo, Tokyo 113-0033, Japan.
| | - Hideharu Mikami
- Department of Chemistry, University of Tokyo, Tokyo 113-0033, Japan.
| | - Cheng Lei
- Department of Chemistry, University of Tokyo, Tokyo 113-0033, Japan. and Institute of Technological Sciences, Wuhan University, Hubei 430072, China
| | - Keisuke Goda
- Department of Chemistry, University of Tokyo, Tokyo 113-0033, Japan. and Institute of Technological Sciences, Wuhan University, Hubei 430072, China and Department of Bioengineering, University of California, Los Angeles, California 90095, USA
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21
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Sala F, Castriotta M, Paiè P, Farina A, D’Annunzio S, Zippo A, Osellame R, Bragheri F, Bassi A. High-throughput 3D imaging of single cells with light-sheet fluorescence microscopy on chip. BIOMEDICAL OPTICS EXPRESS 2020; 11:4397-4407. [PMID: 32923051 PMCID: PMC7449749 DOI: 10.1364/boe.393892] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 06/01/2020] [Accepted: 06/02/2020] [Indexed: 05/08/2023]
Abstract
Single-cell analysis techniques are fundamental to study the heterogeneity of cellular populations, which is the basis to understand several biomedical mechanisms. Light-sheet fluorescence microscopy is a powerful technique for obtaining high-resolution imaging of individual cells, but the complexity of the setup and the sample mounting procedures limit its overall throughput. In our work, we present an optofluidic microscope-on-chip with integrated microlenses for light-sheet shaping and with a fluidic microchannel that allows the automatic and continuous delivery of samples of a few tens of microns in size. The device is used to perform dual-color fluorescence analysis and 3D reconstruction of xenograft-derived mouse breast cancer cells.
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Affiliation(s)
- Federico Sala
- Department of Physics, Politecnico di
Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
- Istituto di Fotonica e Nanotecnologie, CNR,
Piazza Leonardo da Vinci 32, 20133 Milano, Italy
| | - Michele Castriotta
- Department of Physics, Politecnico di
Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
- Istituto di Fotonica e Nanotecnologie, CNR,
Piazza Leonardo da Vinci 32, 20133 Milano, Italy
| | - Petra Paiè
- Istituto di Fotonica e Nanotecnologie, CNR,
Piazza Leonardo da Vinci 32, 20133 Milano, Italy
| | - Andrea Farina
- Istituto di Fotonica e Nanotecnologie, CNR,
Piazza Leonardo da Vinci 32, 20133 Milano, Italy
| | - Sarah D’Annunzio
- Laboratory of Chromatin Biology &
Epigenetics, Center for Integrative Biology (CIBIO), University of
Trento, 38123, Trento, Italy
| | - Alessio Zippo
- Laboratory of Chromatin Biology &
Epigenetics, Center for Integrative Biology (CIBIO), University of
Trento, 38123, Trento, Italy
| | - Roberto Osellame
- Department of Physics, Politecnico di
Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
- Istituto di Fotonica e Nanotecnologie, CNR,
Piazza Leonardo da Vinci 32, 20133 Milano, Italy
| | - Francesca Bragheri
- Istituto di Fotonica e Nanotecnologie, CNR,
Piazza Leonardo da Vinci 32, 20133 Milano, Italy
| | - Andrea Bassi
- Department of Physics, Politecnico di
Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
- Istituto di Fotonica e Nanotecnologie, CNR,
Piazza Leonardo da Vinci 32, 20133 Milano, Italy
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22
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Pan Q, Pei S, Cui F, Xu S, Cao Z. Scattering of an Airy light sheet by a chiral sphere. APPLIED OPTICS 2019; 58:7151-7156. [PMID: 31503988 DOI: 10.1364/ao.58.007151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Accepted: 08/15/2019] [Indexed: 06/10/2023]
Abstract
Scattering of a 1D Airy beam light sheet by a chiral sphere is numerically studied within Mie theory and the plane-wave spectrum method. To testify to the validity of our code and method, the results of scattering intensity of a chiral sphere by an Airy beam light sheet reducing to a homogeneous isotropic sphere are compared with those in existing literature, which shows that these results are in good agreement. Influences of different parameters on differential scattering cross sections in the far field are investigated in detail, including the chiral parameters, sphere radius, and beam position. It is found in the scattering intensity of an Airy beam by a chiral sphere that the chiral sphere, which is compared with a homogeneous isotropic sphere, can decrease the scattering intensity in a region, and the scattering intensity distribution is sensitive to the x0 position of the Airy beam.
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23
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Isozaki A, Mikami H, Hiramatsu K, Sakuma S, Kasai Y, Iino T, Yamano T, Yasumoto A, Oguchi Y, Suzuki N, Shirasaki Y, Endo T, Ito T, Hiraki K, Yamada M, Matsusaka S, Hayakawa T, Fukuzawa H, Yatomi Y, Arai F, Di Carlo D, Nakagawa A, Hoshino Y, Hosokawa Y, Uemura S, Sugimura T, Ozeki Y, Nitta N, Goda K. A practical guide to intelligent image-activated cell sorting. Nat Protoc 2019; 14:2370-2415. [PMID: 31278398 DOI: 10.1038/s41596-019-0183-1] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Accepted: 04/18/2019] [Indexed: 02/08/2023]
Abstract
Intelligent image-activated cell sorting (iIACS) is a machine-intelligence technology that performs real-time intelligent image-based sorting of single cells with high throughput. iIACS extends beyond the capabilities of fluorescence-activated cell sorting (FACS) from fluorescence intensity profiles of cells to multidimensional images, thereby enabling high-content sorting of cells or cell clusters with unique spatial chemical and morphological traits. Therefore, iIACS serves as an integral part of holistic single-cell analysis by enabling direct links between population-level analysis (flow cytometry), cell-level analysis (microscopy), and gene-level analysis (sequencing). Specifically, iIACS is based on a seamless integration of high-throughput cell microscopy (e.g., multicolor fluorescence imaging, bright-field imaging), cell focusing, cell sorting, and deep learning on a hybrid software-hardware data management infrastructure, enabling real-time automated operation for data acquisition, data processing, intelligent decision making, and actuation. Here, we provide a practical guide to iIACS that describes how to design, build, characterize, and use an iIACS machine. The guide includes the consideration of several important design parameters, such as throughput, sensitivity, dynamic range, image quality, sort purity, and sort yield; the development and integration of optical, microfluidic, electrical, computational, and mechanical components; and the characterization and practical usage of the integrated system. Assuming that all components are readily available, a team of several researchers experienced in optics, electronics, digital signal processing, microfluidics, mechatronics, and flow cytometry can complete this protocol in ~3 months.
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Affiliation(s)
- Akihiro Isozaki
- Department of Chemistry, The University of Tokyo, Tokyo, Japan
| | - Hideharu Mikami
- Department of Chemistry, The University of Tokyo, Tokyo, Japan
| | | | - Shinya Sakuma
- Department of Micro-Nano Mechanical Science and Engineering, Nagoya University, Nagoya, Japan
| | - Yusuke Kasai
- Department of Micro-Nano Mechanical Science and Engineering, Nagoya University, Nagoya, Japan
| | - Takanori Iino
- Department of Electrical Engineering and Information Systems, The University of Tokyo, Tokyo, Japan
| | - Takashi Yamano
- Laboratory of Applied Molecular Microbiology, Kyoto University, Kyoto, Japan
| | - Atsushi Yasumoto
- Department of Clinical Laboratory Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yusuke Oguchi
- Department of Biological Sciences, The University of Tokyo, Tokyo, Japan
| | - Nobutake Suzuki
- Department of Biological Sciences, The University of Tokyo, Tokyo, Japan
| | | | | | - Takuro Ito
- Department of Chemistry, The University of Tokyo, Tokyo, Japan.,Japan Science and Technology Agency, Saitama, Japan
| | - Kei Hiraki
- Department of Chemistry, The University of Tokyo, Tokyo, Japan
| | - Makoto Yamada
- Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University, Kyoto, Japan
| | - Satoshi Matsusaka
- Clinical Research and Regional Innovation, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan
| | - Takeshi Hayakawa
- Department of Precision Mechanics, Chuo University, Tokyo, Japan
| | - Hideya Fukuzawa
- Laboratory of Applied Molecular Microbiology, Kyoto University, Kyoto, Japan
| | - Yutaka Yatomi
- Department of Clinical Laboratory Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Fumihito Arai
- Department of Micro-Nano Mechanical Science and Engineering, Nagoya University, Nagoya, Japan
| | - Dino Di Carlo
- Department of Chemistry, The University of Tokyo, Tokyo, Japan.,Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Mechanical Engineering, University of California, Los Angeles, Los Angeles, CA, USA.,California NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA, USA
| | - Atsuhiro Nakagawa
- Department of Neurosurgery, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Yu Hoshino
- Department of Chemical Engineering, Kyushu University, Fukuoka, Japan
| | - Yoichiroh Hosokawa
- Division of Materials Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan
| | - Sotaro Uemura
- Department of Biological Sciences, The University of Tokyo, Tokyo, Japan
| | - Takeaki Sugimura
- Department of Chemistry, The University of Tokyo, Tokyo, Japan.,Japan Science and Technology Agency, Saitama, Japan
| | - Yasuyuki Ozeki
- Department of Electrical Engineering and Information Systems, The University of Tokyo, Tokyo, Japan
| | - Nao Nitta
- Department of Chemistry, The University of Tokyo, Tokyo, Japan.,Japan Science and Technology Agency, Saitama, Japan
| | - Keisuke Goda
- Department of Chemistry, The University of Tokyo, Tokyo, Japan. .,Japan Science and Technology Agency, Saitama, Japan. .,Department of Electrical Engineering, University of California, Los Angeles, Los Angeles, CA, USA.
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24
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Yin L, Zhang Z, Liu Y, Gao Y, Gu J. Recent advances in single-cell analysis by mass spectrometry. Analyst 2019; 144:824-845. [PMID: 30334031 DOI: 10.1039/c8an01190g] [Citation(s) in RCA: 76] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Cells are the most basic structural units that play vital roles in the functioning of living organisms. Analysis of the chemical composition and content of a single cell plays a vital role in ensuring precise investigations of cellular metabolism, and is a crucial aspect of lipidomic and proteomic studies. In addition, structural knowledge provides a better understanding of cell behavior as well as the cellular and subcellular mechanisms. However, single-cell analysis can be very challenging due to the very small size of each cell as well as the large variety and extremely low concentrations of substances found in individual cells. On account of its high sensitivity and selectivity, mass spectrometry holds great promise as an effective technique for single-cell analysis. Numerous mass spectrometric techniques have been developed to elucidate the molecular profiles at the cellular level, including electrospray ionization mass spectrometry (ESI-MS), secondary ion mass spectrometry (SIMS), laser-based mass spectrometry and inductively coupled plasma mass spectrometry (ICP-MS). In this review, the recent advances in single-cell analysis by mass spectrometry are summarized. The strategies of different ionization modes to achieve single-cell analysis are classified and discussed in detail.
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Affiliation(s)
- Lei Yin
- Research Institute of Translational Medicine, The First Hospital of Jilin University, Jilin University, Dongminzhu Street, Changchun 130061, PR China.
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25
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Albert-Smet I, Marcos-Vidal A, Vaquero JJ, Desco M, Muñoz-Barrutia A, Ripoll J. Applications of Light-Sheet Microscopy in Microdevices. Front Neuroanat 2019; 13:1. [PMID: 30760983 PMCID: PMC6362405 DOI: 10.3389/fnana.2019.00001] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Accepted: 01/09/2019] [Indexed: 11/23/2022] Open
Abstract
Light-sheet fluorescence microscopy (LSFM) has been present in cell biology laboratories for quite some time, mainly as custom-made systems, with imaging applications ranging from single cells (in the micrometer scale) to small organisms (in the millimeter scale). Such microscopes distinguish themselves for having very low phototoxicity levels and high spatial and temporal resolution, properties that make them ideal for a large range of applications. These include the study of cellular dynamics, in particular cellular motion which is essential to processes such as tumor metastasis and tissue development. Experimental setups make extensive use of microdevices (bioMEMS) that provide better control over the substrate environment than traditional cell culture experiments. For example, to mimic in vivo conditions, experiment biochemical dynamics, and trap, move or count cells. Microdevices provide a higher degree of empirical complexity but, so far, most have been designed to be imaged through wide-field or confocal microscopes. Nonetheless, the properties of LSFM render it ideal for 3D characterization of active cells. When working with microdevices, confocal microscopy is more widespread than LSFM even though it suffers from higher phototoxicity and slower acquisition speeds. It is sometimes possible to illuminate with a light-sheet microdevices designed for confocal microscopes. However, these bioMEMS must be redesigned to exploit the full potential of LSFM and image more frequently on a wider scale phenomena such as motion, traction, differentiation, and diffusion of molecules. The use of microdevices for LSFM has extended beyond cell tracking studies into experiments regarding cytometry, spheroid cultures and lab-on-a-chip automation. Due to light-sheet microscopy being in its early stages, a setup of these characteristics demands some degree of optical expertise; and designing three-dimensional microdevices requires facilities, ingenuity, and experience in microfabrication. In this paper, we explore different approaches where light-sheet microscopy can achieve single-cell and subcellular resolution within microdevices, and provide a few pointers on how these experiments may be improved.
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Affiliation(s)
- Ignacio Albert-Smet
- Department of Bioengineering and Aerospace Engineering, Universidad Carlos III de Madrid, Madrid, Spain
| | - Asier Marcos-Vidal
- Department of Bioengineering and Aerospace Engineering, Universidad Carlos III de Madrid, Madrid, Spain
| | - Juan José Vaquero
- Department of Bioengineering and Aerospace Engineering, Universidad Carlos III de Madrid, Madrid, Spain
- Experimental Medicine and Surgery Unit, Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Madrid, Spain
| | - Manuel Desco
- Department of Bioengineering and Aerospace Engineering, Universidad Carlos III de Madrid, Madrid, Spain
- Experimental Medicine and Surgery Unit, Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Madrid, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain
| | - Arrate Muñoz-Barrutia
- Department of Bioengineering and Aerospace Engineering, Universidad Carlos III de Madrid, Madrid, Spain
- Experimental Medicine and Surgery Unit, Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Madrid, Spain
| | - Jorge Ripoll
- Department of Bioengineering and Aerospace Engineering, Universidad Carlos III de Madrid, Madrid, Spain
- Experimental Medicine and Surgery Unit, Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Madrid, Spain
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