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Automated Vibratome Sectioning of Agarose-Embedded Lung Tissue for Multiplex Fluorescence Imaging

Wang, Qi LU ; Bechet, Nicholas B. LU and Lindstedt, Sandra LU (2023) In Journal of Visualized Experiments 2023(200).
Abstract

Due to its inherent structural fragility, the lung is regarded as one of the more difficult tissues to process for microscopic readouts. To add structural support for sectioning, pieces of lung tissue are commonly embedded in paraffin or OCT compound and cut with a microtome or cryostat, respectively. A more recent technique, known as precision-cut lung slices, adds structural support to fresh lung tissue through agarose infiltration and provides a platform to maintain primary lung tissue in culture. However, due to epitope masking and tissue distortion, none of these techniques adequately lend themselves to the development of reproducible advanced light imaging readouts that would be compatible across multiple antibodies and species.... (More)

Due to its inherent structural fragility, the lung is regarded as one of the more difficult tissues to process for microscopic readouts. To add structural support for sectioning, pieces of lung tissue are commonly embedded in paraffin or OCT compound and cut with a microtome or cryostat, respectively. A more recent technique, known as precision-cut lung slices, adds structural support to fresh lung tissue through agarose infiltration and provides a platform to maintain primary lung tissue in culture. However, due to epitope masking and tissue distortion, none of these techniques adequately lend themselves to the development of reproducible advanced light imaging readouts that would be compatible across multiple antibodies and species. To this end, we have developed a tissue-processing pipeline, which utilizes agarose embedding of fixed lung tissue, coupled to automated vibratome sectioning. This facilitated the generation of lung sections from 200 µm to 70 µm thick, in mouse, pig, and human lungs, which require no antigen retrieval, and represent the least "processed" version of the native isolated tissue. Using these slices, we reveal a multiplex imaging readout capable of generating high-resolution images whose spatial protein expression can be used to quantify and better understand the mechanisms underlying lung injury and regeneration.

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author
; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Journal of Visualized Experiments
volume
2023
issue
200
article number
e65943
publisher
JoVE
external identifiers
  • pmid:37870323
  • scopus:85174706039
ISSN
1940-087X
DOI
10.3791/65943
language
English
LU publication?
yes
id
c08bc9c0-dba6-4056-94e5-ccc43c0e0301
date added to LUP
2023-12-11 14:06:54
date last changed
2024-04-24 07:34:54
@article{c08bc9c0-dba6-4056-94e5-ccc43c0e0301,
  abstract     = {{<p>Due to its inherent structural fragility, the lung is regarded as one of the more difficult tissues to process for microscopic readouts. To add structural support for sectioning, pieces of lung tissue are commonly embedded in paraffin or OCT compound and cut with a microtome or cryostat, respectively. A more recent technique, known as precision-cut lung slices, adds structural support to fresh lung tissue through agarose infiltration and provides a platform to maintain primary lung tissue in culture. However, due to epitope masking and tissue distortion, none of these techniques adequately lend themselves to the development of reproducible advanced light imaging readouts that would be compatible across multiple antibodies and species. To this end, we have developed a tissue-processing pipeline, which utilizes agarose embedding of fixed lung tissue, coupled to automated vibratome sectioning. This facilitated the generation of lung sections from 200 µm to 70 µm thick, in mouse, pig, and human lungs, which require no antigen retrieval, and represent the least "processed" version of the native isolated tissue. Using these slices, we reveal a multiplex imaging readout capable of generating high-resolution images whose spatial protein expression can be used to quantify and better understand the mechanisms underlying lung injury and regeneration.</p>}},
  author       = {{Wang, Qi and Bechet, Nicholas B. and Lindstedt, Sandra}},
  issn         = {{1940-087X}},
  language     = {{eng}},
  number       = {{200}},
  publisher    = {{JoVE}},
  series       = {{Journal of Visualized Experiments}},
  title        = {{Automated Vibratome Sectioning of Agarose-Embedded Lung Tissue for Multiplex Fluorescence Imaging}},
  url          = {{http://dx.doi.org/10.3791/65943}},
  doi          = {{10.3791/65943}},
  volume       = {{2023}},
  year         = {{2023}},
}