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UF Health University of Florida
Computational Microscopy Imaging Laboratory Section of Quantitative Health in the Department of Medicine
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Research Overview

Computational detection and quantification of human and mouse neutrophil extracellular traps

Neutrophil extracellular traps (NETs) are extracellular defense mechanisms used by neutrophils, where chromatin is expelled together with histones and granular/cytoplasmic proteins. They have become an immunology hotspot, implicated in infections, but also in a diverse array of diseases such as systemic lupus erythematosus, diabetes, and cancer. However, the precise assessment of in vivo relevance in different disease settings has been hampered by limited tools to quantify occurrence of extracellular traps in experimental models and human samples. To expedite progress towards improved quantitative tools, we have developed computational pipelines to identify extracellular traps from an in vitro human samples visualized using the ImageStream® platform (Millipore Sigma, Darmstadt, Germany), and confocal images of an in vivo mouse disease model of aspergillus fumigatus pneumonia. We expect that our approach will be of value for researchers, and have application in infectious and inflammatory diseases.

Unsupervised pipeline to identify neutrophil extracellular traps (NETs) from immunofluorescence images of mouse lung following Aspergillus fumigatus infection.
Unsupervised pipeline to identify neutrophil extracellular traps (NETs) from immunofluorescence images of mouse lung following Aspergillus fumigatus infection.   (A) Raw image. DNA is identified by DAPI staining (blue) and primary antibodies directed against MPO (red) and histone H1 (green) were detected with AlexaFluor 568- and 488- conjugated secondary antibodies. Yellow box indicates sub-region for B–M. (B) Sub-image of A. (C) Image shown in B after top-hat filtering. (D) Visualization of the image after normalization. (E) Bradley local thresholding defines a master object mask. (F) Objects with co-localized levels of histones and myeloperoxidase both greater than one unit of intensity standard deviation in the respective channels. (G) Objects with all markers co-localized. (H) Objects where histone marker intensity is greater than DNA marker. (I) Objects where DNA marker exhibits higher intensity than histone marker. (J) Intersection of the images in F, G, and H, with pixels contained in I set to zero. (K) Reconstruction of the image shown in J underneath the image in F, followed by morphological noise removal in (L). (M) Visualization of the extracted co-localized regions (pink) over the master object regions (blue).

Selected References

B. Ginley, T. Emmons, B. Lutnick, C. Urban, B. H. Segal, and P. Sarder, “Computational detection and quantification of human and mouse neutrophil extracellular traps in flow cytometry and confocal microscopy,” Scientific Reports – Nature, vol. 7, pp. 17755:1–11, Dec. 2017.

Underline indicates corresponding author.
* indicates equal contribution.
Ω indicates Dr. Sarder’s faculty trainees.
§ indicates post doctoral associates.
† indicates Dr. Sarder’s graduate students.
‡ indicates Dr. Sarder’s undergraduate students.