The gut microbiota represents a diverse and dynamic population of microorganisms that can influence the health of the host. Increasing evidence supports the role of the gut microbiota as a key player in the pathogenesis of neurodegenerative diseases, including Alzheimer's disease (AD). Unfortunately, the mechanisms behind the interplay between gut pathogens and AD are still elusive. It is known that bacteria‐derived outer membrane vesicles (OMVs) act as natural carriers of virulence factors that are central players in the pathogenesis of the bacteria. Helicobacter pylori ( H. pylori ) is a common gastric pathogen and H. pylori infection has been associated with an increased risk to develop AD. Here, we are the first to shed light on the role of OMVs derived from H. pylori on the brain in healthy conditions and on disease pathology in the case of AD. Our results reveal that H. pylori OMVs can cross the biological barriers, eventually reaching the brain. Once in the brain, these OMVs are taken up by astrocytes, which induce activation of glial cells and neuronal dysfunction, ultimately leading to exacerbated amyloid‐β pathology and cognitive decline. Mechanistically, we identified a critical role for the complement component 3 (C3)‐C3a receptor (C3aR) signalling in mediating the interaction between astrocytes, microglia and neurons upon the presence of gut H. pylori OMVs. Taken together, our study reveals that H. pylori has a detrimental effect on brain functionality and accelerates AD development via OMVs and C3‐C3aR signalling.
Glaucoma is a disease associated with the loss of retinal ganglion cells (RGCs), and remains one of the primary causes of blindness worldwide. Major research efforts are presently directed towards the understanding of disease pathogenesis and the development of new therapies, with the help of rodent models as an important preclinical research tool. The ultimate goal is reaching neuroprotection of the RGCs, which requires a tool to reliably quantify RGC survival. Hence, we demonstrate a novel deep learning pipeline that enables fully automated RGC quantification in the entire murine retina. This software, called RGCode (Retinal Ganglion Cell quantification based On DEep learning), provides a user-friendly interface that requires the input of RBPMS-immunostained flatmounts and returns the total RGC count, retinal area and density, together with output images showing the computed counts and isodensity maps. The counting model was trained on RBPMS-stained healthy and glaucomatous retinas, obtained from mice subjected to microbead-induced ocular hypertension and optic nerve crush injury paradigms. RGCode demonstrates excellent performance in RGC quantification as compared to manual counts. Furthermore, we convincingly show that RGCode has potential for wider application, by retraining the model with a minimal set of training data to count FluoroGold-traced RGCs.
Despite being one of the most studied eye diseases, clinical translation of glaucoma research is hampered, at least in part, by the lack of validated preclinical models and readouts. The most popular experimental glaucoma model is the murine microbead occlusion model, yet the observed mild phenotype, mixed success rate, and weak reproducibility urge for an expansion of available readout tools. For this purpose, we evaluated various measures that reflect early onset glaucomatous changes in the murine microbead occlusion model. Anterior chamber depth measurements and scotopic threshold response recordings were identified as an outstanding set of tools to assess the model’s success rate and to chart glaucomatous damage (or neuroprotection in future studies), respectively. Both are easy-to-measure, in vivo tools with a fast acquisition time and high translatability to the clinic and can be used, whenever judged beneficial, in combination with the more conventional measures in present-day glaucoma research (i.e., intraocular pressure measurements and post-mortem histological analyses). Furthermore, we highlighted the use of dendritic arbor analysis as an alternative histological readout for retinal ganglion cell density counts.
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