Automatic determination of NET (neutrophil extracellular traps) coverage in fluorescent microscopy images

Bioinformatics
Luis Pedro CoelhoJoão André Carriço

Abstract

Neutrophil extracellular traps (NETs) are believed to be essential in controlling several bacterial pathogens. Quantification of NETs in vitro is an important tool in studies aiming to clarify the biological and chemical factors contributing to NET production, stabilization and degradation. This estimation can be performed on the basis of fluorescent microscopy images using appropriate labelings. In this context, it is desirable to automate the analysis to eliminate both the tedious process of manual annotation and possible operator-specific biases. We propose a framework for the automated determination of NET content, based on visually annotated images which are used to train a supervised machine-learning method. We derive several methods in this framework. The best results are obtained by combining these into a single prediction. The overall Q(2) of the combined method is 93%. By having two experts label part of the image set, we were able to compare the performance of the algorithms to the human interoperator variability. We find that the two operators exhibited a very high correlation on their overall assessment of the NET coverage area in the images (R(2) is 97%), although there were consistent differences in labeling at p...Continue Reading

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Citations

Jun 14, 2016·Journal of Immunology Research·Nicole de Buhr, Maren von Köckritz-Blickwede
Jan 31, 2018·Frontiers in Immunology·Tirthankar MohantyPontus Nordenfelt
Sep 4, 2019·Journal of Leukocyte Biology·Malgorzata J PodolskaChristine Schauer
Feb 23, 2020·Biology·Ariane NeumannMaren von Köckritz-Blickwede
Dec 7, 2016·Frontiers in Immunology·Volker BrinkmannArturo Zychlinsky
Nov 16, 2019·Scientific Reports·Laila ElsherifLeslie V Parise

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