Garces Suarez, Y. | bioRxiv Science

bioRxiv2018

Nanoscale organization of rotavirus replication machineries

Rotavirus genome replication and assembly take place in cytoplasmic electron dense inclusions termed viro-plasms (VPs). Previous conventional optical microscopy studies observing the intracellular distribution of rotavirus proteins and their organization in VPs have lacked molecular-scale spatial resolution, due to inherent spatial resolution constraints. In this work we employed super-resolution microscopy to reveal the nanometric-scale organization of VPs formed during rotavirus infection, and quantitatively describe the structural organization of seven viral proteins and viral dsRNA within and around the VPs. The observed viral components are spatially organized as 6 concentric layers, in which NSP5 localizes at the center of the VPs, surrounded by a layer of NSP2 and NSP4 proteins, followed by an intermediate zone comprised of the VP1, VP2, VP6 proteins and the dsRNA. In the outermost zone, we observed a ring of VP4 and finally a layer of VP7. These findings show that rotavirus VPs are highly organized organelles.

microbiology↗

bioRxiv2017

Concept and in-silico assessment of an algorithm for monitoring cytosolic fluorescent aggregates in cells.

Autophagy is an evolutionary conserved pathway, by which eukaryotic cells degrade long-living cellular proteins and intracellular organelles, to maintain a pool of available nutrients. Impaired autophagy has been associated to important pathophysiological conditions, and this is the reason why several techniques have been developed for its correct assessment and monitoring. Fluorescence microscopy is one of these tools, which relies on the detection of specific fluorescence changes of targeted GFP-based reporters in dot-like organelles in which autophagy is executed. Currently, several procedures exist to count and segment this punctate structures in the resulting fluorescence images, however, they are either based on subjective criteria, or no information is available related to them. Here we present the concept of an algorithm for a semi-automatic detection and segmentation in 2D fluorescence images of spot-like structures similar to those observed under induction of autophagy. By evaluating the algorithm on more than 20000 simulated images of cells containing a variable number of punctate structures of different sizes and different levels of applied noise, we demonstrate its high robustness of puncta detection, even on a high noise background. We further demonstrate this feature of our algorithm by testing it in experimental conditions of a high non-specific background signal. We conclude that our algorithm is a suitable tool to be tested in biologically-relevant contexts.

bioinformatics↗