A novel method for high-throughput detection and quantification of neutrophil extracellular traps reveals ROS-independent NET release with immune complexes

AbstractA newly-described first-line immune defence mechanism of neutrophils is the release of neutrophil extracellular traps (NETs). Immune complexes (ICxs) induce low level NET release. As such, the in vitro quantification of NETs is challenging with current methodologies. In order to investigate the role of NET release in ICx-mediated autoimmune diseases, we developed a highly sensitive and automated method for quantification of NETs. After labelling human neutrophils with PKH26 and extracellular DNA with Sytox green, cells are fixed and automatically imaged with 3-dimensional confocal laser scanning microscopy (3D-CLSM). NET release is then quantified with digital image analysis whereby the NET amount (Sytox green area) is corrected for the number of imaged neutrophils (PKH26 area). A high sensitivity of the assay is achieved by a) significantly augmenting the area of the well imaged (11%) as compared to conventional assays (0.5%) and b) using a 3D imaging technique for optimal capture of NETs, which are topologically superimposed on neutrophils. In this assay, we confirmed low levels of NET release upon human ICx stimulation which were positive for citrullinated histones and neutrophil elastase. In contrast to PMA-induced NET release, ICx-induced NET release was unchanged when co-incubated with diphenyleneiodonium (DPI). We were able to quantify NET release upon stimulation with serum from RA and SLE patients, which was not observed with normal human serum. To our knowledge, this is the first semi-automated assay capable of sensitive detection and quantification of NET release at a low threshold by using 3D CLSM. The assay is applicable in a high-throughput manner and allows the in vitro analysis of NET release in ICx-mediated autoimmune diseases

Machine Learning to Quantitate Neutrophil NETosis

We introduce machine learning (ML) to perform classifcation and quantitation of images of nuclei from human blood neutrophils. Here we assessed the use of convolutional neural networks (CNNs) using free, open source software to accurately quantitate neutrophil NETosis, a recently discovered process involved in multiple human diseases. CNNs achieved \u3e94% in performance accuracy in diferentiating NETotic from non-NETotic cells and vastly facilitated dose-response analysis and screening of the NETotic response in neutrophils from patients. Using only features learned from nuclear morphology, CNNs can distinguish between NETosis and necrosis and between distinct NETosis signaling pathways, making them a precise tool for NETosis detection. Furthermore, by using CNNs and tools to determine object dispersion, we uncovered diferences in NETotic nuclei clustering between major NETosis pathways that is useful in understanding NETosis signaling events. Our study also shows that neutrophils from patients with sickle cell disease were unresponsive to one of two major NETosis pathways. Thus, we demonstrate the design, performance, and implementation of ML tools for rapid quantitative and qualitative cell analysis in basic science

The interaction of type 1 and 2 interferons with neutrophils in Juvenile-onset Systemic Lupus Erythematosus

The interaction of type 1 and 2 IFNs with neutrophils in JSLE Sophie Lindsay Irwin Introduction: Juvenile-onset Systemic Lupus Erythematosus (JSLE) is a multisystem autoimmune disease characterised by an increase in nuclear autoantigens and subsequent increased production in autoantibodies. Neutrophil function and apoptosis is dysregulated in JSLE, and thus neutrophils are thought to be an important factor in JSLE pathogenesis. Type 1 and 2 interferons (IFNs) have been shown to be increased in SLE and JSLE serum, and an IFN and granulocyte genetic signature within JSLE patients has indicated a potential interaction of IFNs and neutrophils within JSLE. However, specific mechanisms of IFNs on neutrophil apoptosis and function within JSLE is yet to be elucidated. Aim: To investigate the interaction of IFNs with neutrophil function, apoptosis and signalling pathways, with specific focus on how these interactions may change in an inflammatory disease such as JSLE. Methods: Neutrophils were isolated from whole blood from healthy adult volunteers and children with and without JSLE. Neutrophils were left naïve or primed with TNFα or IFNs, and subsequently stimulated with IFNs and other stimulants. Phagocytosis, apoptosis, activation states and receptor expression were analysed using flow cytometry. Intracellular signalling proteins were analysed using Western blotting. Chemotaxis was analysed using a transwell assay in the presence or absence of chemokines. NETosis was analysed using confocal microscopy and DNA quantification. Results: An in vitro model was developed to investigate the role of IFNs on a range of key neutrophil functions. IFNs were shown to have little effect on specific aspects of chemotaxis, phagocytosis and NETosis of healthy volunteer neutrophils. IFNs were shown to be anti-apoptotic towards naïve neutrophils from healthy adult volunteers but could either lose this ability or induce apoptosis when neutrophils were primed with TNFα. The anti-apoptotic effect observed was via reduced cleavage of caspase 3 but not through the stability of MCL1. Patient serum (including paediatric control) activated neutrophils from healthy adult volunteers, but this had no significant effect on neutrophil apoptosis downstream. Priming with TNFα reduced IFNAR1 expression on neutrophils from healthy adult volunteers but did not change the expression of other IFN receptor chains. There was no difference in IFN receptor chain expression on neutrophils from JSLE patients compared to paediatric controls. Following priming with TNFα, there was a reduction of STAT3 phosphorylation and an increase in STAT1 phosphorylation in neutrophils from healthy adult volunteers. Conclusion: IFNs have an important influence on neutrophil apoptosis. In primed neutrophils, lower concentrations of IFNs lose their anti-apoptotic ability and can induce apoptosis at high concentrations. This may reflect what is happening at sites of inflammation in active patients. Drug treatment may help to reduce this potentially IFN-related increase in neutrophil apoptosis in JSLE patients. Patients with inactive JSLE disease, likely due to their medication, had similar rates of apoptosis to matched controls. Activation of healthy adult neutrophils reduced the expression of IFNAR1 alone, which may contribute to the differential IFN induced phosphorylation of anti-apoptotic STAT3 and pro-apoptotic STAT1. This manipulation of the IFN signalling pathway through TNFα priming (and therefore through activation of neutrophils in inflammatory diseases) may contribute to the dual IFN effect on apoptosis, with STAT1 possibly involved in increased neutrophil apoptosis in JSLE. Inhibition of STAT1 may therefore be therapeutically beneficial in JSLE