Automatic determination of NET (neutrophil extracellular traps) coverage in fluorescent microscopy images

Interleukin-8 and neutrophil extracellular traps in children with lupus nephritis and vitamin C deficiency

BACKGROUND

Vitamin C is a potent scavenger of reactive oxygen species, which induce neutrophil extracellular trap (NET) formation. NETs are a major source of autoantigens and are involved in systemic lupus erythematosus (SLE) pathogenesis. We determined vitamin C status and evaluated NET formation and inflammatory cytokines in children with lupus nephritis.

METHODS

Serum vitamin C was measured in 46 patients (82.6% females, mean age 14.5 ± 0.3 years). Vitamin C levels < 0.3 mg/dL indicated vitamin C deficiency. Patients were divided into two groups according to serum vitamin C levels: normal and low (< 0.3 mg/dL). We compared NET formation and levels of SLE-related cytokines, including interleukin (IL)-8, IL-10, and tumor necrosis factor-α (TNF-α), between groups. NET formation was determined through measurement of serum citrullinated histone 3 levels and mRNA expression of peptidyl arginine deiminase-4 and assessment of the percentage of neutrophils with NETs by immunofluorescence.

RESULTS

Nine patients (19.6%) had vitamin C deficiency. Kidney pathology assessment at disease onset revealed that histological activity index and number of kidney biopsies containing crescentic glomeruli were higher in vitamin C-deficient patients, but chronicity index was not. NET formation and serum IL-8 were more prominent in vitamin C-deficient patients. Serum IL-8 levels were 12.9 ± 5.2 pg/mL in low vitamin C group and 5.2 ± 0.9 pg/mL in normal vitamin C group (p = 0.03). Serum IL-10 and TNF-α were similar between groups.

CONCLUSIONS

Our study demonstrated correlation among vitamin C deficiency, increased NET formation, and IL-8 upregulation in children with lupus nephritis. A prospective study is required to evaluate cause‒effect relationships of vitamin C status, NET formation and IL-8 expression.

Trapalyzer: a computer program for quantitative analyses in fluorescent live-imaging studies of neutrophil extracellular trap formation

Neutrophil extracellular traps (NETs), pathogen-ensnaring structures formed by neutrophils by expelling their DNA into the environment, are believed to play an important role in immunity and autoimmune diseases. In recent years, a growing attention has been put into developing software tools to quantify NETs in fluorescent microscopy images. However, current solutions require large, manually-prepared training data sets, are difficult to use for users without background in computer science, or have limited capabilities. To overcome these problems, we developed Trapalyzer, a computer program for automatic quantification of NETs. Trapalyzer analyzes fluorescent microscopy images of samples double-stained with a cell-permeable and a cell-impermeable dye, such as the popular combination of Hoechst 33342 and SYTOX™ Green. The program is designed with emphasis on software ergonomy and accompanied with step-by-step tutorials to make its use easy and intuitive. The installation and configuration of the software takes less than half an hour for an untrained user. In addition to NETs, Trapalyzer detects, classifies and counts neutrophils at different stages of NET formation, allowing for gaining a greater insight into this process. It is the first tool that makes this possible without large training data sets. At the same time, it attains a precision of classification on par with state-of-the-art machine learning algorithms. As an example application, we show how to use Trapalyzer to study NET release in a neutrophil-bacteria co-culture. Here, after configuration, Trapalyzer processed 121 images and detected and classified 16 000 ROIs in approximately three minutes on a personal computer. The software and usage tutorials are available at https://github.com/Czaki/Trapalyzer.

Comparison of NET quantification methods based on immunofluorescence microscopy: Hand-counting, semi-automated and automated evaluations

Formation of neutrophil extracellular traps was first described in 2004, showing that NETs are composed of decondensed chromatin fibers and nuclear and granule components. Free DNA is often used to quantify NETs, but to differentiate NETosis from necrotic DNA-release, immunofluorescence microscopy with NET-specific markers is required. Although evaluation by hand is time-consuming and difficult to standardize, it is still widespread. Unfortunately, no standardized method and only limited software tools are available for NET evaluation. This study provides an overview of recent techniques in use and aims to compare two published computer-based methods with hand counting. We found that the selected semi-automated quantification method and fully automated quantification via NETQUANT differed significantly from results obtained by hand and exhibited problems in detection of complex NET structures with partially illogical results. In contrast to that, trained persons were able to adapt to varying settings. Future approaches aimed at developing deep-learning algorithms for fast and reproducible quantification of NETs are needed.

Methods for the Assessment of NET Formation: From Neutrophil Biology to Translational Research

Several studies have indicated that a neutrophil extracellular trap (NET) formation, apart from its role in host defense, can contribute to or drive pathogenesis in a wide range of inflammatory and thrombotic disorders. Therefore, NETs may serve as a therapeutic target or/and a diagnostic tool. Here, we compare the most commonly used techniques for the assessment of NET formation. Furthermore, we review recent data from the literature on the application of basic laboratory tools for detecting NET release and discuss the challenges and the advantages of these strategies in NET evaluation. Taken together, we provide some important insights into the qualitative and quantitative molecular analysis of NETs in translational medicine today.

An Imaging and Computational Algorithm for Efficient Identification and Quantification of Neutrophil Extracellular Traps

Neutrophil extracellular traps (NETs) are associated with multiple disease pathologies including sepsis, asthma, rheumatoid arthritis, cancer, systemic lupus erythematosus, acute respiratory distress syndrome, and COVID-19. NETs, being a disintegrated death form, suffered inconsistency in their identification, nomenclature, and quantifications that hindered therapeutic approaches using NETs as a target. Multiple strategies including microscopy, ELISA, immunoblotting, flow cytometry, and image-stream-based methods have exhibited drawbacks such as being subjective, non-specific, error-prone, and not being high throughput, and thus demand the development of innovative and efficient approaches for their analyses. Here, we established an imaging and computational algorithm using high content screening (HCS)-cellomics platform that aid in easy, rapid, and specific detection as well as analyses of NETs. This method employed membrane-permeable and impermeable DNA dyes in situ to identify NET-forming cells. Automated algorithm-driven single-cell analysis of change in nuclear morphology, increase in nuclear area, and change in intensities provided precise detection of NET-forming cells and eliminated user bias with other cell death modalities. Further combination with Annexin V staining in situ detected specific death pathway, e.g., apoptosis, and thus, discriminated between NETs, apoptosis, and necrosis. Our approach does not utilize fixation and permeabilization steps that disturb NETs, and thus, allows the time-dependent monitoring of NETs. Together, this specific imaging-based high throughput method for NETs analyses may provide a good platform for the discovery of potential inhibitors of NET formation and/or agents to modulate neutrophil death, e.g., NETosis-apoptosis switch, as an alternative strategy to enhance the resolution of inflammation.

Convolutional Neural Networks-Based Image Analysis for the Detection and Quantification of Neutrophil Extracellular Traps

Over a decade ago, the formation of neutrophil extracellular traps (NETs) was described as a novel mechanism employed by neutrophils to tackle infections. Currently applied methods for NETs release quantification are often limited by the use of unspecific dyes and technical difficulties. Therefore, we aimed to develop a fully automatic image processing method for the detection and quantification of NETs based on live imaging with the use of DNA-staining dyes. For this purpose, we adopted a recently proposed Convolutional Neural Network (CNN) model called Mask R-CNN. The adopted model detected objects with quality comparable to manual counting—Over 90% of detected cells were classified in the same manner as in manual labelling. Furthermore, the inhibitory effect of GW 311616A (neutrophil elastase inhibitor) on NETs release, observed microscopically, was confirmed with the use of the CNN model but not by extracellular DNA release measurement. We have demonstrated that a modern CNN model outperforms a widely used quantification method based on the measurement of DNA release and can be a valuable tool to quantitate the formation process of NETs.

Extracellular Traps: An Ancient Weapon of Multiple Kingdoms

The discovery, in 2004, of extracellular traps released by neutrophils has extended our understanding of the mode of action of various innate immune cells. This fascinating discovery demonstrated the extracellular trapping and killing of various pathogens by neutrophils. During the last decade, evidence has accumulated showing that extracellular traps play a crucial role in the defence mechanisms of various cell types present in vertebrates, invertebrates, and plants. The aim of this review is to summarise the relevant literature on the evolutionary history of extracellular traps used as a weapon in various kingdoms of life.

Machine Learning to Quantitate Neutrophil NETosis

We introduce machine learning (ML) to perform classification 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 >94% in performance accuracy in differentiating 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 differences 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.

Treatment with DNases rescues hidden neutrophil elastase from aggregated NETs

The release of neutrophil extracellular traps (NETs) is one of the weapons neutrophils have in their armory. NETs consist of extracellular chromatin fibers decorated with a plethora of cytoplasmic and granular proteins, such as the antimicrobial serine protease neutrophil elastase (NE). Because the first description of NETs as beneficial to the host, reports on their double-faced role in health and disease have considerably increased recently. On one hand, NETs reportedly trap and kill bacteria and also participate in the resolution of the acute inflammation associated with infection and with tissue damage. On the other hand, numerous negative aspects of NETs contribute to the etiopathogenesis of autoimmune disorders. Employing soluble and solid fluorescent substrates, we demonstrate the interaction of NE with aggregated NETs (aggNETs), the limitation of its enzymatic activity and the containment of the enzyme from surrounding tissues. These events prevent the spread of inflammation and tissue damage. The detection of DNase 1-dependent elevation of NE activity attests the continuous presence of patrolling neutrophils forming NETs and aggNETs even under conditions physiologic conditions.

Computational Methodologies for the in vitro and in situ Quantification of Neutrophil Extracellular Traps

Neutrophil extracellular traps (NETs) are a neutrophil defensive mechanism where chromatin is expelled together with antimicrobial proteins in response to a number of stimuli. Even though beneficial in many cases, their dysfunction has been implicated in many diseases, such as rheumatoid arthritis and cancer. Accurate quantification of NETs is of utmost importance for correctly studying their role in various diseases, especially when considering them as therapeutic targets. Unfortunately, NET quantification has a number of limitations. However, recent developments in computational methodologies for quantifying NETs have vastly improved the ability to study NETs. Methods range from using ImageJ to user friendly applications and to more sophisticated machine-learning approaches. These various methods are reviewed and discussed in this review.

To NET or not to NET:current opinions and state of the science regarding the formation of neutrophil extracellular traps

Since the discovery and definition of neutrophil extracellular traps (NETs) 14 years ago, numerous characteristics and physiological functions of NETs have been uncovered. Nowadays, the field continues to expand and novel mechanisms that orchestrate formation of NETs, their previously unknown properties, and novel implications in disease continue to emerge. The abundance of available data has also led to some confusion in the NET research community due to contradictory results and divergent scientific concepts, such as pro- and anti-inflammatory roles in pathologic conditions, demarcation from other forms of cell death, or the origin of the DNA that forms the NET scaffold. Here, we present prevailing concepts and state of the science in NET-related research and elaborate on open questions and areas of dispute.

NETQUANT: Automated Quantification of Neutrophil Extracellular Traps

Neutrophil extracellular traps (NETs) that are extensive webs of DNA covered with antimicrobial proteins into the extracellular environment during infection or inflammation as a part of their defense arsenal. Image acquisition of fluorescently labeled NETs and subsequent image-based quantification is frequently used to analyze NET formation (NETosis) in response to various stimuli. However, there are important limitations in the present methods for quantification. Manual methods tend to be error-prone, tedious, and often quite subjective, whereas the software-rooted options are either semi-automatic or difficult to operate. Here, we present an automated and uncomplicated approach for quantifying NETs from fluorescence images, built as a freely available app for MATLAB^®. It is based on detection of a set of clearly defined parameters, all related to the biological manifestation of NETs and allowing for single-cell resolution quantification and analysis.

Computational detection and quantification of human and mouse neutrophil extracellular traps in flow cytometry and confocal microscopy

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. Our two in vitro methods, tested on n = 363/n =145 images respectively, achieved holdout sensitivity/specificity 0.98/0.93 and 1/0.92. Our unsupervised method for thin lung tissue sections in murine fungal pneumonia achieved sensitivity/specificity 0.99/0.98 in n = 14 images. Our supervised method for thin lung tissue classified NETs with sensitivity/specificity 0.86/0.90. We expect that our approach will be of value for researchers, and have application in infectious and inflammatory diseases.

Immunodetection of NETs in Paraffin-Embedded Tissue

The pathogenic potential of neutrophil extracellular traps (NETs) was recently described, and their detection in tissue could serve as a prognostic marker. NETs are delicate and filigree structures; hence good tissue preservation is essential for their detection. Indeed, analysis of paraffin-embedded tissue has proven superior to the study of cryo sections. Though, under favorable conditions, the presence of NETs can be detected in tissue sections stained with histological dyes, definitive identification of NETs needs the colocalization of immunofluorescent signals for both nuclear and granular (or cytoplasmic) NET components. We tested diverse antigen retrieval methods and various combinations of commercially available antibodies and present here staining protocols to detect NETs in human and murine tissue sections.

How Neutrophil Extracellular Traps Become Visible

Neutrophil extracellular traps (NETs) have been identified as a fundamental innate immune defense mechanism against different pathogens. NETs are characterized as released nuclear DNA associated with histones and granule proteins, which form an extracellular web-like structure that is able to entrap and occasionally kill certain microbes. Furthermore, NETs have been shown to contribute to several noninfectious disease conditions when released by activated neutrophils during inflammation. The identification of NETs has mainly been succeeded by various microscopy techniques, for example, immunofluorescence microscopy, transmission electron microscopy (TEM), and scanning electron microscopy (SEM). Since the last years the development and improvement of new immunofluorescence-based techniques enabled optimized visualization and quantification of NETs. On the one hand in vitro live-cell imaging led to profound new ideas about the mechanisms involved in the formation and functionality of NETs. On the other hand different intravital, in vivo, and in situ microscopy techniques led to deeper insights into the role of NET formation during health and disease. This paper presents an overview of the main used microscopy techniques to visualize NETs and describes their advantages as well as disadvantages.

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

A 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.