Abstract

Neutrophil extracellular traps (NETs) contribute to innate immunity as well as numerous diseases processes such as deep vein thrombosis, myocardial ischemia, and autoimmune disease. To date, most knowledge on NETs formation has been gathered via the qualitative microscopic examination of individual neutrophils in vitro, or aggregate structures in vivo. Here we describe a novel flow cytometry (FLOW)-based assay to identify and quantify NETs using antibodies against key NETs constituents, specifically DNA, modified histones, and granular enzymes. This method is applicable to both murine and human samples for the assessment of induced NETs in vitro, or detection of NETosis in vivo in blood samples. This FLOW-based method was validated by comparison with the well-established microscopy assay using two genetic mouse models previously demonstrated to show defective NETosis. It was then used on healthy human neutrophils for detection of ex vivo induced NETs and on blood samples from patients with sepsis for direct assessment of in vivo NET-forming neutrophils. This new methodology allows rapid and robust assessment of several thousand cells per sample and is independent of potential observer-bias, the two main limitations of the microscopic quantification. Using this new technology facilitates the direct detection of in vivo circulating NETs in blood samples and purification of NETting neutrophils by fluorescence-activated cell sorting (FACS) for further analysis.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.