Markowitz, M. | Search bioRxiv

bioRxiv2020

Perivascular Space Semi-Automatic Segmentation (PVSSAS): A Tool for Segmenting, Viewing and Editing Perivascular Spaces

ObjectiveIn this study, we validate and describe a user-friendly tool for PVS tracing that uses a Frangi-based detection algorithm; which will be made freely available to aid in future clinical and research applications. All PVS detected by the semi-automated method had a match with the manual dataset and 94% of the manual PVS had a match within the semi-automated dataset. MethodsWe deployed a Frangi-based filter using a pre-existing Matlab toolbox. The PVSSAS tool pre-processes the images and is optimized for maximum effectiveness in this application. A user-friendly GUI was developed to aid the speed and ease in marking large numbers of PVS across the entire brain at once. ResultsUsing a tolerance of 0.7 cm, 83% of all PVSs detected by the semi-automated method had a match with the manual dataset and 94% of the manual PVS had a match within the semi-automated dataset. As shown in figure 3, there was generally excellent agreement between the manual and semi-automated markings in any given slice. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/385336v1_fig3.gif" ALT="Figure 3"> View larger version (19K): org.highwire.dtl.DTLVardef@35f651org.highwire.dtl.DTLVardef@be6b08org.highwire.dtl.DTLVardef@164ec0aorg.highwire.dtl.DTLVardef@c48643_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 3&4C_FLOATNO Rendered 3-D view of total PVS found across all slices for one patient. C_FIG SignificanceThe primary benefit of PVSSAS will be time saved marking PVS. Clinical MRI use is likely to become more widespread in the diagnosis, treatment, and study of MS and other degenerative neurological conditions in the coming years. Tools like the one presented here will be invaluable in ensuring that the tracing and quantitative analysis of these PVS does not act as a bottle neck to treatment and further research.

neuroscience↗

bioRxiv2019

Y-RNAs Lead an Endogenous Program of RIG-I Agonism Mobilized upon RNA Virus Infection and Targeted by HIV

Pattern recognition receptors (PRRs) protect against host invasion by detecting specific molecular patterns found in pathogens and initiating an immune response. While microbial-derived PRR ligands have been extensively characterized, the contribution and relevance of endogenous ligands to PRR activation during viral infection remain overlooked. In this work, we characterize the landscape of endogenous ligands that engage RIG-I-like receptors (RLRs) upon infection by a positive-sense RNA virus, a negative-sense RNA virus or a retrovirus. We found that several endogenous RNAs transcribed by RNA polymerase 3 (Pol3) specifically engage RLRs, and in particular the family of small non-coding repeats Y-RNAs, which presents the highest affinity as RIG-I ligands. We show that this recognition is dependent on Y-RNA mimicking viral secondary structure and its 5-triphosphate extremity. Further, we found that HIV-1 infection triggers a VPR-dependent downregulation of RNA triphosphatase DUSP11 in vitro and in vivo, leading to an increase of Y-RNA 5-triphosphorylation that enables their immunogenicity. Importantly, we show that altering DUSP11 expression is sufficient to induce a type-I interferon and T cell activation transcriptional program associated with HIV-1 infection. Overall, our work uncovers the critical contribution of endogenous repeat RNAs ligands to antiviral immunity and demonstrates the role of this pathway in HIV-1 infection.

immunology↗