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Titze VM, Caixeiro S, Dinh VS, König M, Rübsam M, Pathak N, Schumacher AL, Germer M, Kukat C, Niessen CM, Schubert M, Gather MC. Hyperspectral confocal imaging for high-throughput readout and analysis of bio-integrated microlasers. Nat Protoc 2024; 19:928-959. [PMID: 38238582 DOI: 10.1038/s41596-023-00924-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 10/03/2023] [Indexed: 03/10/2024]
Abstract
Integrating micro- and nanolasers into live cells, tissue cultures and small animals is an emerging and rapidly evolving technique that offers noninvasive interrogation and labeling with unprecedented information density. The bright and distinct spectra of such lasers make this approach particularly attractive for high-throughput applications requiring single-cell specificity, such as multiplexed cell tracking and intracellular biosensing. The implementation of these applications requires high-resolution, high-speed spectral readout and advanced analysis routines, which leads to unique technical challenges. Here, we present a modular approach consisting of two separate procedures. The first procedure instructs users on how to efficiently integrate different types of lasers into living cells, and the second procedure presents a workflow for obtaining intracellular lasing spectra with high spectral resolution and up to 125-kHz readout rate and starts from the construction of a custom hyperspectral confocal microscope. We provide guidance on running hyperspectral imaging routines for various experimental designs and recommend specific workflows for processing the resulting large data sets along with an open-source Python library of functions covering the analysis pipeline. We illustrate three applications including the rapid, large-volume mapping of absolute refractive index by using polystyrene microbead lasers, the intracellular sensing of cardiac contractility with polystyrene microbead lasers and long-term cell tracking by using semiconductor nanodisk lasers. Our sample preparation and imaging procedures require 2 days, and setting up the hyperspectral confocal microscope for microlaser characterization requires <2 weeks to complete for users with limited experience in optical and software engineering.
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Affiliation(s)
- Vera M Titze
- Centre of Biophotonics, School of Physics and Astronomy, University of St Andrews, St Andrews, UK.
- Humboldt Centre for Nano- and Biophotonics, University of Cologne, Cologne, Germany.
| | - Soraya Caixeiro
- Humboldt Centre for Nano- and Biophotonics, University of Cologne, Cologne, Germany
| | - Vinh San Dinh
- Centre of Biophotonics, School of Physics and Astronomy, University of St Andrews, St Andrews, UK
- Graduate Program in Applied Physics, Northwestern University, Evanston, Illinois, USA
| | - Matthias König
- Humboldt Centre for Nano- and Biophotonics, University of Cologne, Cologne, Germany
| | - Matthias Rübsam
- Department of Cell Biology of the Skin, University Hospital Cologne, University of Cologne, Cologne, Germany
- Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Disease (CECAD), University of Cologne, Cologne, Germany
| | - Nachiket Pathak
- Humboldt Centre for Nano- and Biophotonics, University of Cologne, Cologne, Germany
| | - Anna-Lena Schumacher
- FACS & Imaging Core Facility, Max Planck Institute for Biology of Ageing, Cologne, Germany
| | - Maximilian Germer
- FACS & Imaging Core Facility, Max Planck Institute for Biology of Ageing, Cologne, Germany
| | - Christian Kukat
- FACS & Imaging Core Facility, Max Planck Institute for Biology of Ageing, Cologne, Germany
| | - Carien M Niessen
- Department of Cell Biology of the Skin, University Hospital Cologne, University of Cologne, Cologne, Germany
- Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Disease (CECAD), University of Cologne, Cologne, Germany
| | - Marcel Schubert
- Centre of Biophotonics, School of Physics and Astronomy, University of St Andrews, St Andrews, UK.
- Humboldt Centre for Nano- and Biophotonics, University of Cologne, Cologne, Germany.
| | - Malte C Gather
- Centre of Biophotonics, School of Physics and Astronomy, University of St Andrews, St Andrews, UK.
- Humboldt Centre for Nano- and Biophotonics, University of Cologne, Cologne, Germany.
- Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Disease (CECAD), University of Cologne, Cologne, Germany.
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Caixeiro S, Wijesinghe P, Dholakia K, Gather MC. Snapshot hyperspectral imaging of intracellular lasers. OPTICS EXPRESS 2023; 31:33175-33190. [PMID: 37859103 DOI: 10.1364/oe.498022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 08/18/2023] [Indexed: 10/21/2023]
Abstract
Intracellular lasers are emerging as powerful biosensors for multiplexed tracking and precision sensing of cells and their microenvironment. This sensing capacity is enabled by quantifying their narrow-linewidth emission spectra, which is presently challenging to do at high speeds. In this work, we demonstrate rapid snapshot hyperspectral imaging of intracellular lasers. Using integral field mapping with a microlens array and a diffraction grating, we obtain images of the spatial and spectral intensity distribution from a single camera acquisition. We demonstrate widefield hyperspectral imaging over a 3 × 3 mm2 field of view and volumetric imaging over 250 × 250 × 800 µm3 (XYZ) volumes with a lateral (XY) resolution of 5 µm, axial (Z) resolution of 10 µm, and a spectral resolution of less than 0.8 nm. We evaluate the performance and outline the challenges and strengths of snapshot methods in the context of characterizing the emission from intracellular lasers. This method offers new opportunities for a diverse range of applications, including high-throughput and long-term biosensing with intracellular lasers.
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Dannenberg PH, Kang J, Martino N, Kashiparekh A, Forward S, Wu J, Liapis AC, Wang J, Yun SH. Laser particle activated cell sorting in microfluidics. LAB ON A CHIP 2022; 22:2343-2351. [PMID: 35621381 PMCID: PMC9195882 DOI: 10.1039/d2lc00235c] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Accepted: 04/22/2022] [Indexed: 05/30/2023]
Abstract
Laser particles providing bright, spectrally narrowband emission renders them suitable for use as cellular barcodes. Here, we demonstrate a microfluidic platform integrated with a high-speed spectrometer, capable of reading the emission from laser particles in fluidic channels and routing cells based on their optical barcodes. The sub-nanometer spectral emission of each laser particle enables us to distinguish individual cells labeled with hundreds of different laser colors in the near infrared. Furthermore, cells tagged with laser particles are sorted based on their spectral barcodes at a kilohertz rate by using a real-time field programmable gate array and 2-way electric field switch. We demonstrate several different flavors of sorting, including isolation of barcoded cells, and cells tagged with a specific laser color. We term this novel sorting technique laser particle activated cell sorting (LACS). This flow reading and sorting technology adds to the arsenal of single-cell analysis tools using laser particles.
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Affiliation(s)
- Paul H Dannenberg
- Wellman Center for Photomedicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA.
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Jisoo Kang
- Wellman Center for Photomedicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Nicola Martino
- Wellman Center for Photomedicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA.
| | - Anokhi Kashiparekh
- Wellman Center for Photomedicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Sarah Forward
- Wellman Center for Photomedicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Jiamin Wu
- Wellman Center for Photomedicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Automation, Tsinghua University, Beijing, China
| | - Andreas C Liapis
- Wellman Center for Photomedicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA.
| | - Jie Wang
- Wellman Center for Photomedicine, Massachusetts General Hospital, Boston, MA 02114, USA
- College of Artificial Intelligence, Nanjing Agricultural University, Nanjing, Jiangsu 210031, China
| | - Seok-Hyun Yun
- Wellman Center for Photomedicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA.
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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