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Automated Image-Based Quantification of Neutrophil Extracellular Traps Using NETQUANT

Mohanty, Tirthankar LU and Nordenfelt, Pontus LU orcid (2019) In Journal of visualized experiments : JoVE
Abstract

Neutrophil extracellular traps (NETs) are web-like antimicrobial structures consisting of DNA and granule derived antimicrobial proteins. Immunofluorescence microscopy and image-based quantification methods remain important tools to quantitate neutrophil extracellular trap formation. However, there are key limitations to the immunofluorescence-based methods that are currently available for quantifying NETs. Manual methods of image-based NET quantification are often subjective, prone to error and tedious for users, especially non-experienced users. Also, presently available software options for quantification are either semi-automatic or require training prior to operation. Here, we demonstrate the implementation of an automated... (More)

Neutrophil extracellular traps (NETs) are web-like antimicrobial structures consisting of DNA and granule derived antimicrobial proteins. Immunofluorescence microscopy and image-based quantification methods remain important tools to quantitate neutrophil extracellular trap formation. However, there are key limitations to the immunofluorescence-based methods that are currently available for quantifying NETs. Manual methods of image-based NET quantification are often subjective, prone to error and tedious for users, especially non-experienced users. Also, presently available software options for quantification are either semi-automatic or require training prior to operation. Here, we demonstrate the implementation of an automated immunofluorescence-based image quantification method to evaluate NET formation called NETQUANT. The software is easy to use and has a user-friendly graphical user interface (GUI). It considers biologically relevant parameters such as an increase in the surface area and DNA:NET marker protein ratio, and nuclear deformation to define NET formation. Furthermore, this tool is built as a freely available app, and allows for single-cell resolution quantification and analysis.

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author
and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Journal of visualized experiments : JoVE
issue
153
article number
e58528
publisher
JoVE
external identifiers
  • pmid:31840654
  • scopus:85076554865
ISSN
1940-087X
DOI
10.3791/58528
language
English
LU publication?
yes
id
03fd1948-042a-4f4e-93a3-ad8bbadd3aa3
date added to LUP
2019-12-22 07:08:35
date last changed
2024-03-20 03:06:59
@article{03fd1948-042a-4f4e-93a3-ad8bbadd3aa3,
  abstract     = {{<p>Neutrophil extracellular traps (NETs) are web-like antimicrobial structures consisting of DNA and granule derived antimicrobial proteins. Immunofluorescence microscopy and image-based quantification methods remain important tools to quantitate neutrophil extracellular trap formation. However, there are key limitations to the immunofluorescence-based methods that are currently available for quantifying NETs. Manual methods of image-based NET quantification are often subjective, prone to error and tedious for users, especially non-experienced users. Also, presently available software options for quantification are either semi-automatic or require training prior to operation. Here, we demonstrate the implementation of an automated immunofluorescence-based image quantification method to evaluate NET formation called NETQUANT. The software is easy to use and has a user-friendly graphical user interface (GUI). It considers biologically relevant parameters such as an increase in the surface area and DNA:NET marker protein ratio, and nuclear deformation to define NET formation. Furthermore, this tool is built as a freely available app, and allows for single-cell resolution quantification and analysis.</p>}},
  author       = {{Mohanty, Tirthankar and Nordenfelt, Pontus}},
  issn         = {{1940-087X}},
  language     = {{eng}},
  month        = {{11}},
  number       = {{153}},
  publisher    = {{JoVE}},
  series       = {{Journal of visualized experiments : JoVE}},
  title        = {{Automated Image-Based Quantification of Neutrophil Extracellular Traps Using NETQUANT}},
  url          = {{http://dx.doi.org/10.3791/58528}},
  doi          = {{10.3791/58528}},
  year         = {{2019}},
}