Infections of fungi by mycoviruses are often symptomless but sometimes also fatal as they perturb sporulation, growth, and, if applicable, virulence of the fungal host. Hypovirulence-inducing mycoviruses, therefore, represent a powerful mean to defeat fungal epidemics on crop plants. Infection with Fusarium graminearum virus China 9 (FgV-ch9), a dsRNA chrysovirus-like mycovirus, debilitates , the causal agent of Fusarium Head Blight. In search for potential symptom alleviation or aggravation factors in, we consecutively infected a custom-made mutant collection with FgV-ch9 and found a mutant with constantly elevated expression of a gene coding for a putative mRNA-binding protein that did not show any disease symptoms despite harboring high amounts of virus. Deletion of this gene, named virus response 1 (), resulted in phenotypes identical to those observed in the virus-infected wild type with respect to growth, reproduction, and virulence. Similarly, the viral structural protein coded on segment 3 (P3) caused virus-infection like symptoms when expressed in the wild-type but not in the -overexpression mutant. Gene expression analysis revealed a drastic downregulation of in the presence of virus and in mutants expressing P3. We conclude that symptom development and severity correlate with gene expression levels of This was confirmed by comparative transcriptome analysis showing a large transcriptional overlap between the virus-infected wild type, the deletion mutant and the P3-expressing mutant. Hence, represents a fundamental host factor for the expression of virus-related symptoms and helps to understand the underlying mechanism of hypovirulence. Virus infections of phytopathogenic fungi occasionally impair growth, reproduction, and virulence, a phenomenon referred to as hypovirulence. Hypovirulence-inducing mycoviruses, therefore, represent a powerful mean to defeat fungal epidemics on crop plants. However, the poor understanding of the molecular basis of hypovirulence induction limits their application. Using the devastating fungal pathogen on cereal crops, , we identified an mRNA binding protein (named virus response 1,) which is involved in symptom expression. Downregulation of in the virus-infected fungus and deletion evoke virus-infection like symptoms while constitutive expression overrules the cytopathic effects of the virus infection. Intriguingly, the presence of a specific viral structural protein is sufficient to trigger the fungal response, downregulation, and symptom development similar to virus infection. The advancements in understanding fungal infection and response may aid biological pest control approaches using mycoviruses or viral proteins to prevent future Fusarium epidemics.

Axonal degeneration (AxD) is a pathological hallmark of many neurodegenerative diseases. Deciphering the morphological patterns of AxD will help to understand the underlying mechanisms and develop effective therapies. Here, we evaluated the progression of AxD in cortical neurons using a novel microfluidic device together with a deep learning tool that we developed for the enhanced-throughput analysis of AxD on microscopic images. The trained convolutional neural network (CNN) sensitively and specifically segmented the features of AxD including axons, axonal swellings, and axonal fragments. Its performance exceeded that of the human evaluators. In an in vitro model of AxD in hemorrhagic stroke induced by the hemolysis product hemin, we detected a time-dependent degeneration of axons leading to a decrease in axon area, while axonal swelling and fragment areas increased. Axonal swellings preceded axon fragmentation, suggesting that swellings may be reliable predictors of AxD. Using a recurrent neural network (RNN), we identified four morphological patterns of AxD (granular, retraction, swelling, and transport degeneration). These findings indicate a morphological heterogeneity of AxD in hemorrhagic stroke. Our EntireAxon platform enables the systematic analysis of axons and AxD in time-lapse microscopy and unravels a so-far unknown intricacy in which AxD can occur in a disease context.

Different axonal degeneration (AxD) patterns have been described depending on the biological condition. Until now, it remains unclear whether they are restricted to one specific condition or can occur concomitantly. Here, we present a novel microfluidic device in combination with a deep learning tool, the EntireAxon, for the high-throughput analysis of AxD. We evaluated the progression of AxD in an in vitro model of hemorrhagic stroke and observed that axonal swellings preceded axon fragmentation. We further identified four distinct morphological patterns of AxD (granular, retraction, swelling, and transport degeneration) that occur concomitantly. These findings indicate a morphological heterogeneity of AxD under pathophysiologic conditions. The newly developed microfluidic device along with the EntireAxon deep learning tool enable the systematic analysis of AxD but also unravel a so far unknown intricacy in which AxD can occur in a disease context.

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