Viral Epidemics in a Cell Culture: Novel High Resolution Data and Their Interpretation by a Percolation Theory Based Model

Abstract

Because of its relevance to everyday life, the spreading of viral infections has been of central interest in a variety of scientific communities involved in fighting, preventing and theoretically interpreting epidemic processes. Recent large scale observations have resulted in major discoveries concerning the overall features of the spreading process in systems with highly mobile susceptible units, but virtually no data are available about observations of infection spreading for a very large number of immobile units. Here we present the first detailed quantitative documentation of percolation-type viral epidemics in a highly reproducible in vitro system consisting of tens of thousands of virtually motionless cells. We use a confluent astroglial monolayer in a Petri dish and induce productive infection in a limited number of cells with a genetically modified herpesvirus strain. This approach allows extreme high resolution tracking of the spatio-temporal development of the epidemic. We show that a simple model is capable of reproducing the basic features of our observations, i.e., the observed behaviour is likely to be applicable to many different kinds of systems. Statistical physics inspired approaches to our data, such as fractal dimension of the infected clusters as well as their size distribution, seem to fit into a percolation theory based interpretation. We suggest that our observations may be used to model epidemics in more complex systems, which are difficult to study in isolation.

Microglia control the spread of neurotropic virus infection via P2Y12 signalling and recruit monocytes through P2Y12-independent mechanisms

“…In cultures used for time-lapse recordings, microglial cells were seeded on top of astrocytic or neuronal cell cultures in 10000 cell/cm 2 density. Neuronal or astroglia cultures were infected with either PRV-Bartha-Dup-Green (BDG) virus or PRV-Bartha-DupLac (BDL) at a final titer of 2.5 × 10 5 PFU/ml, as described earlier [ 24 ]. The multiplicity of infection (MOI) was ~ 0,17 PFU/cell.…”

“…To study the mechanisms of microglia recruitment to sites of infection, we first established co-cultures of neurons and GFP-positive microglia from Cx3Cr1 +/GFP mice and per- of microglia with more advanced statistical approaches [24,43,44], which required co-cultures of microglia with very sparsely distributed cells. Since this was not feasible with neuronal cultures, we took advantage that astrocytes are also infected with PRV under in vitro conditions [24]. In fact, in sparse astrocyte cultures microglial cells migrated much longer distances on average to reach infected cells.…”

Differentiation-Dependent Motility-Responses of Developing Neural Progenitors to Optogenetic Stimulation

“…The centers of individual cells were tracked on consecutive frames of the time-lapse video images and the cell positions were determined using the WTrack program ( Gönci et al, 2010 ) (Supplementary Material S5 ). The x, y coordinates of individual cell positions were related to a non-moving reference point and the move of labeled cell centers were calculated from frame to frame.…”

“…Time-lapse images were opened in WTrack program ( Gönci et al, 2010 ) and 20 cells were selected in every starting image for movement tracking. As selection criteria, the tracked cells should not leave the microscopic field during the 12-h recording period.…”

Organ‐to‐Cell‐Scale Health Assessment Using Geographical Information System Approaches with Multibeam Scanning Electron Microscopy

“…Combined with geospatial approaches, this novel imaging technology opens the door for a range of network modeling applications which will enable disease epidemiology studies in populations of cells that inhabit tissues and organs. For example, to further explore the role of cellular connectivity in osteocyte survival, network analysis tools such as clustering methods can be used to identify spatial relationships between and among groups of viable and/or pyknotic cells . Network connectivity, shortest path and search algorithms can be implemented to further investigate distance‐based relationships between pairs of osteocytes and/or osteocytes and blood vessels.…”