Synergistic mutations in soluble guanylyl cyclase (sGC) reveal a key role for interfacial regions in the sGC activation mechanism.

Soluble guanylyl cyclase (sGC) is the main receptor for nitric oxide (NO) and a central component of the NO-cGMP pathway, critical to cardiovascular function. NO binding to the N-terminal sensor domain in sGC enhances the cyclase activity of the C-terminal catalytic domain. Our understanding of the structural elements regulating this signaling cascade is limited, hindering structure-based drug design efforts that target sGC to improve the management of cardiovascular diseases. Conformational changes are thought to propagate the NO-binding signal throughout the entire sGC heterodimer, via its coiled-coil domain, to reorient the catalytic domain into an active conformation. To identify the structural elements involved in this signal transduction cascade, here we optimized a cGMP-based luciferase assay that reports on heterologous sGC activity in Escherichia coli and identified several mutations that activate sGC. These mutations resided in the dorsal flaps, dimer interface, and GTP-binding regions of the catalytic domain. Combinations of mutations from these different elements synergized, resulting in even greater activity and indicating a complex cross-talk among these regions. Molecular dynamics simulations further revealed conformational changes underlying the functional impact of these mutations. We propose that the interfacial residues play a central role in the sGC activation mechanism by coupling the coiled-coil domain to the active site via a series of hot spots. Our results provide new mechanistic insights not only into the molecular pathway for sGC activation but also for other members of the larger nucleotidyl cyclase family.

Microglia at sites of atrophy restrict the progression of retinal degeneration via galectin-3 and Trem2.

Outer retinal degenerations, including age-related macular degeneration (AMD), are characterized by photoreceptor and retinal pigment epithelium (RPE) atrophy. In these blinding diseases, macrophages accumulate at atrophic sites, but their ontogeny and niche specialization remain poorly understood, especially in humans. We uncovered a unique profile of microglia, marked by galectin-3 upregulation, at atrophic sites in mouse models of retinal degeneration and human AMD. In disease models, conditional deletion of galectin-3 in microglia led to phagocytosis defects and consequent augmented photoreceptor death, RPE damage, and vision loss, indicating protective roles. Mechanistically, Trem2 signaling orchestrated microglial migration to atrophic sites and induced galectin-3 expression. Moreover, pharmacologic Trem2 agonization led to heightened protection but in a galectin-3-dependent manner. In elderly human subjects, we identified this highly conserved microglial population that expressed galectin-3 and Trem2. This population was significantly enriched in the macular RPE-choroid of AMD subjects. Collectively, our findings reveal a neuroprotective population of microglia and a potential therapeutic target for mitigating retinal degeneration.

Microglia at Sites of Atrophy Restrict the Progression of Retinal Degeneration via Galectin-3 and Trem2 Interactions.

Degenerative diseases of the outer retina, including age-related macular degeneration (AMD), are characterized by atrophy of photoreceptors and retinal pigment epithelium (RPE). In these blinding diseases, macrophages are known to accumulate ectopically at sites of atrophy, but their ontogeny and functional specialization within this atrophic niche remain poorly understood, especially in the human context. Here, we uncovered a transcriptionally unique profile of microglia, marked by galectin-3 upregulation, at atrophic sites in mouse models of retinal degeneration and in human AMD. Using disease models, we found that conditional deletion of galectin-3 in microglia led to defects in phagocytosis and consequent augmented photoreceptor death, RPE damage and vision loss, suggestive of a protective role. Mechanistically, Trem2 signaling orchestrated the migration of microglial cells to sites of atrophy, and there, induced galectin-3 expression. Moreover, pharmacologic Trem2 agonization led to heightened protection, but only in a galectin-3-dependent manner, further signifying the functional interdependence of these two molecules. Likewise in elderly human subjects, we identified a highly conserved population of microglia at the transcriptomic, protein and spatial levels, and this population was enriched in the macular region of postmortem AMD subjects. Collectively, our findings reveal an atrophy-associated specialization of microglia that restricts the progression of retinal degeneration in mice and further suggest that these protective microglia are conserved in AMD.

Incidence of Referable Retinal Disease in Diabetic Patients at a Primary Care Practice.

Purpose: This work tests the feasibility of remote ophthalmic imaging to identify referable retinal abnormalities and assesses the effectiveness of color fundus photography (CFP) vs optical coherence tomography (OCT) for this purpose. Methods: This prospective, nonrandomized study included 633 patients with diabetes at Duke Primary Care. Undilated patients underwent screening with CFP and OCT camera (MaestroCare, Topcon). Images were graded independently for interpretability and the presence of predetermined retinal disease. Retinal disease was classified as diabetic retinopathy (DR) referable to a retina specialist or incidental findings referable to either a retina specialist or a general ophthalmologist, depending on severity. Results: Mean (SD) age of screened patients was 66 (13) years, and 49% were women. The average glycated hemoglobin A1c level was 7.6 % (SD, 1.7%), and 30% of the patients were on insulin. The average duration of diabetes was 5.9 (SD, 7.3) years. Remote images from OCT were significantly more interpretable than CFP (98% vs 83%, respectively; P < .001). Referral rates were 9% for DR and 28% for incidental findings. Among patients with DR, OCT and CFP were helpful in 58% and 87% of cases, respectively (P < .001). Conclusions: Remote diagnosis of ophthalmic imaging at the point of service may allow for early identification of retinal disease and timely referral and treatment. Our approach showed that OCT had significantly better interpretability, while CFP was more helpful in identifying DR. These findings may be important when choosing the screening device in a specific context.

Automated Identification of Referable Retinal Pathology in Teleophthalmology Setting.

Purpose: This study aims to meet a growing need for a fully automated, learning-based interpretation tool for retinal images obtained remotely (e.g. teleophthalmology) through different imaging modalities that may include imperfect (uninterpretable) images. Methods: A retrospective study of 1148 optical coherence tomography (OCT) and color fundus photography (CFP) retinal images obtained using Topcon's Maestro care unit on 647 patients with diabetes. To identify retinal pathology, a Convolutional Neural Network (CNN) with dual-modal inputs (i.e. CFP and OCT images) was developed. We developed a novel alternate gradient descent algorithm to train the CNN, which allows for the use of uninterpretable CFP/OCT images (i.e. ungradable images that do not contain sufficient image biomarkers for the reviewer to conclude absence or presence of retinal pathology). Specifically, a 9:1 ratio to split the training and testing dataset was used for training and validating the CNN. Paired CFP/OCT inputs (obtained from a single eye of a patient) were grouped as retinal pathology negative (RPN; 924 images) in the absence of retinal pathology in both imaging modalities, or if one of the imaging modalities was uninterpretable and the other without retinal pathology. If any imaging modality exhibited referable retinal pathology, the corresponding CFP/OCT inputs were deemed retinal pathology positive (RPP; 224 images) if any imaging modality exhibited referable retinal pathology. Results: Our approach achieved 88.60% (95% confidence interval [CI] = 82.76% to 94.43%) accuracy in identifying pathology, along with the false negative rate (FNR) of 12.28% (95% CI = 6.26% to 18.31%), recall (sensitivity) of 87.72% (95% CI = 81.69% to 93.74%), specificity of 89.47% (95% CI = 83.84% to 95.11%), and area under the curve of receiver operating characteristic (AUC-ROC) was 92.74% (95% CI = 87.71% to 97.76%). Conclusions: Our model can be successfully deployed in clinical practice to facilitate automated remote retinal pathology identification. Translational Relevance: A fully automated tool for early diagnosis of retinal pathology might allow for earlier treatment and improved visual outcomes.

Automated Recognition of Retinal Pigment Epithelium Cells on Limited Training Samples Using Neural Networks.

Purpose: To develop a neural network (NN)-based approach, with limited training resources, that identifies and counts the number of retinal pigment epithelium (RPE) cells in confocal microscopy images obtained from cell culture or mice RPE/choroid flat-mounts. Methods: Training and testing dataset contained two image types: wild-type mice RPE/choroid flat-mounts and ARPE 19 cells, stained for Rhodamine-phalloidin, and imaged with confocal microscopy. After image preprocessing for denoising and contrast adjustment, scale-invariant feature transform descriptors were used for feature extraction. Training labels were derived from cells in the original training images, annotated and converted to Gaussian density maps. NNs were trained using the set of training input features, such that the obtained NN models accurately predicted corresponding Gaussian density maps and thus accurately identifies/counts the cells in any such image. Results: Training and testing datasets contained 229 images from ARPE19 and 85 images from RPE/choroid flat-mounts. Within two data sets, 30% and 10% of the images, were selected for validation. We achieved 96.48% ± 6.56% and 96.88% ± 3.68% accuracy (95% CI), on ARPE19 and RPE/choroid flat-mounts. Conclusions: We developed an NN-based approach that can accurately estimate the number of RPE cells contained in confocal images. Our method achieved high accuracy with limited training images, proved that it can be effectively used on images with unclear and curvy boundaries, and outperformed existing relevant methods by decreasing prediction error and variance. Translational Relevance: This approach allows efficient and effective characterization of RPE pathology and furthermore allows the assessment of novel therapeutics.

A homogeneous SIRPα-CD47 cell-based, ligand-binding assay: Utility for small molecule drug development in immuno-oncology.

CD47 is an immune checkpoint protein that downregulates both the innate and adaptive anti-tumor immune response via its counter receptor SIRPα. Biologics, including humanized CD47 monoclonal antibodies and decoy SIRPα receptors, that block the SIRPα-CD47 interaction, are currently being developed as cancer immunotherapy agents. However, adverse side effects and limited penetration of tumor tissue associated with their structure and large size may impede their clinical application. We recently developed a quantitative high throughput screening assay platform to identify small molecules that disrupt the binding of SIRPα and CD47 as an alternative approach to these protein-based therapeutics. Here, we report on the development and optimization of a cell-based binding assay to validate active small molecules from our biochemical screening effort. This assay has a low volume, high capacity homogenous format that relies on laser scanning cytometry (LSC) and associated techniques to enhance signal to noise measurement of cell surface binding. The LSC assay is specific, concentration dependent, and validated for the two major human SIRPα variants (V1 and V2), with results that parallel those of our biochemical data as well as published studies. We also utilized the LSC assay to confirm published studies showing that the inhibition of amino-terminal pyroglutamate formation on CD47 using the glutaminyl cyclase inhibitor SEN177 disrupts SIRPα binding. The SIRPα-CD47 interaction could be quantitatively measured in live and fixed tumor cells. Use of fixed cells reduces the burden of cell maintenance and provides stable cell standards to control for inter- and intra-assay variations. We also demonstrate the utility of the assay to characterize the activity of the first reported small molecule antagonists of the SIRPα-CD47 interaction. This assay will support the screening of thousands of compounds to identify or validate active small molecules as hits, develop structure activity relationships and assist in the optimization of hits to leads by a typical iterative medicinal chemistry campaign.

Quantitative high-throughput screening assays for the discovery and development of SIRPα-CD47 interaction inhibitors.

CD47 is an immune checkpoint molecule that downregulates key aspects of both the innate and adaptive anti-tumor immune response via its counter receptor SIRPα, and it is expressed at high levels in a wide variety of tumor types. This has led to the development of biologics that inhibit SIRPα engagement including humanized CD47 antibodies and a soluble SIRPα decoy receptor that are currently undergoing clinical trials. Unfortunately, toxicological issues, including anemia related to on-target mechanisms, are barriers to their clinical advancement. Another potential issue with large biologics that bind CD47 is perturbation of CD47 signaling through its high-affinity interaction with the matricellular protein thrombospondin-1 (TSP1). One approach to avoid these shortcomings is to identify and develop small molecule molecular probes and pretherapeutic agents that would (1) selectively target SIRPα or TSP1 interactions with CD47, (2) provide a route to optimize pharmacokinetics, reduce on-target toxicity and maximize tissue penetration, and (3) allow more flexible routes of administration. As the first step toward this goal, we report the development of an automated quantitative high-throughput screening (qHTS) assay platform capable of screening large diverse drug-like chemical libraries to discover novel small molecules that inhibit CD47-SIRPα interaction. Using time-resolved Förster resonance energy transfer (TR-FRET) and bead-based luminescent oxygen channeling assay formats (AlphaScreen), we developed biochemical assays, optimized their performance, and individually tested them in small-molecule library screening. Based on performance and low false positive rate, the LANCE TR-FRET assay was employed in a ~90,000 compound library qHTS, while the AlphaScreen oxygen channeling assay served as a cross-validation orthogonal assay for follow-up characterization. With this multi-assay strategy, we successfully eliminated compounds that interfered with the assays and identified five compounds that inhibit the CD47-SIRPα interaction; these compounds will be further characterized and later disclosed. Importantly, our results validate the large library qHTS for antagonists of CD47-SIRPα interaction and suggest broad applicability of this approach to screen chemical libraries for other protein-protein interaction modulators.