NETosis was identified as a distinct mode of cell death in neutrophils more than a decade ago. Dysregulation of NETosis has been implicated in the etiology of human pathologies such as preeclampsia, sickle cell disease, systemic lupus erythematosus, multiple sclerosis, rheumatoid arthritis, sepsis, cystic fibrosis, lupus nephritis, and coagulopathies that include cancer-associated thrombosis. The literature consistently cites the lack of a standardized methodology for quantitation of NETosis as an impediment to basic and translational research. Thus, the premise is that there is a compelling, unmet need for a standardized, quantitative and automated method for the measurement of NETosis to accelerate neutrophil and inflammation-based research and facilitate the discovery and development of therapeutic compounds. The scope of this STTR project is to develop a high-throughput image analysis and quantitation method by using high content imaging and the revolutionary technology of convolutional neural networks (CNN) for the identification and quantitation of NETosis in human neutrophils. The target readout is based on the primary morphological difference between NETotic and non-NETotic nuclei--the decondensation of chromatin. This image-based quantitative method will be observer-independent and will enable robust and rapid evaluation of a large number of samples that would exceed any attempts at manual assessment. In Phase I we will complete the following Specific Aims:
Aim 1 : Optimize and standardize the high- throughput platform for quantitation of NETosis in adherent human neutrophils. This includes standard assay optimization procedures, training the CNN to identify and quantitate NETotic neutrophil, and demonstrating that the CNN reliably distinguishes between necrosis and NETosis, whose phenotypes appear similar to the human eye.
Aim 2 : Validate the NETosis assay biochemically and clinically. This includes concentration-response assays with NETosis agonists, assessment of NETosis inhibitors, and evaluation of the NETotic status of Sickle Cell Disease patient samples (a disease in which aberrant NETosis has been implicated). The expected outcome of this Phase I effort is to demonstrate proof-of-concept for this automated high- throughput NETosis assay. Further, we expect to provide insight into the utility of the assay for assessment of inhibitors of NETosis as therapeutic agents. Upon completion of our Phase I aims, our Phase II program will focus on further optimizing and validating this NETosis assay and preparing it for commercialization.
Aberrant NETosis has been implicated in the etiology of several inflammatory and autoimmune diseases. The lack of a standardized, quantitative and automated method for the measurement of NETosis is impeding basic and translational research. We have developed a high-throughput assay using convolutional neural networks to quantify NETosis in human neutrophils. This assay will accelerate neutrophil and inflammation-based research and facilitate the discovery and development of compounds with therapeutic potential.
