Quantifying NETosis via Automated High Content Imaging Convolutional Neural Networks

PROJECT SUMMARY NETosis was identified as a distinct mode of cell death in neutrophils more than a decade agoDysregulation of NETosis has been implicated in the etiology of human pathologies such as preeclampsiasickle cell diseasesystemic lupus erythematosusmultiple sclerosisrheumatoid arthritissepsiscystic fibrosislupus nephritisand coagulopathies that include cancer associated thrombosisThe literature consistently cites the lack of a standardized methodology for quantitation of NETosis as an impediment to basic and translational researchThusthe premise is that there is a compellingunmet need for a standardizedquantitative and automated method for the measurement of NETosis to accelerate neutrophil and inflammation based research and facilitate the discovery and development of therapeutic compoundsThe 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 networksCNNfor the identification and quantitation of NETosis in human neutrophilsThe target readout is based on the primary morphological difference between NETotic and non NETotic nucleithe decondensation of chromatinThis 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 assessmentIn Phase I we will complete the following Specific AimsAimOptimize and standardize the highthroughput platform for quantitation of NETosis in adherent human neutrophilsThis includes standard assay optimization procedurestraining the CNN to identify and quantitate NETotic neutrophiland demonstrating that the CNN reliably distinguishes between necrosis and NETosiswhose phenotypes appear similar to the human eyeAimValidate the NETosis assay biochemically and clinicallyThis includes concentration response assays with NETosis agonistsassessment of NETosis inhibitorsand evaluation of the NETotic status of Sickle Cell Disease patient samplesa disease in which aberrant NETosis has been implicatedThe expected outcome of this Phase I effort is to demonstrate proof of concept for this automated highthroughput NETosis assayFurtherwe expect to provide insight into the utility of the assay for assessment of inhibitors of NETosis as therapeutic agentsUpon completion of our Phase I aimsour Phase II program will focus on further optimizing and validating this NETosis assay and preparing it for commercializationPROJECT NARRATIVE Aberrant NETosis has been implicated in the etiology of several inflammatory and autoimmune diseasesThe lack of a standardizedquantitative and automated method for the measurement of NETosis is impeding basic and translational researchWe have developed a high throughput assay using convolutional neural networks to quantify NETosis in human neutrophilsThis assay will accelerate neutrophil and inflammation based research and facilitate the discovery and development of compounds with therapeutic potential