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1.	Mohanty, Tirthankar, et al. (författare) Automated Image-Based Quantification of Neutrophil Extracellular Traps Using NETQUANT 2019 Ingår i: Journal of visualized experiments : JoVE. - : MyJove Corporation. - 1940-087X. ; :153 Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)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 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.

Mohanty, Tirthankar, et al. (författare)
Automated Image-Based Quantification of Neutrophil Extracellular Traps Using NETQUANT
2019
Ingår i: Journal of visualized experiments : JoVE. - : MyJove Corporation. - 1940-087X. ; :153
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)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 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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