Mice mutant for Ppap2c, a homolog of the germ cell migration regulator wunen, are viable and fertile

Phosphatidic acid phosphatases (PAPs) catalyze the conversion of phosphatidic acid to diacylglycerol and inorganic phosphate and have been postulated to function both in lipid biosynthesis and in cellular signal transduction. In Drosophila melanogaster, the Type 2 phosphatidic acid phosphatase protein encoded by the wunen gene, negatively regulates primordial germ cell migration. We recently described the cloning and characterization of the mouse Ppap2c gene, which encodes the Type 2 phosphatidic acid phosphatase Pap2c (Zhang et al., Genomics 63:142-144). To analyze the in vivo role of the Ppap2c gene we constructed a null mutation by gene targeting. Ppap2c(-/-) homozygous mutant mice were viable, fertile, and exhibited no obvious phenotypic defects. These data demonstrate that the Ppap2c gene is not essential for embryonic development or fertility in mice.     

Spatially distributed infection increases viral load in a computational model of SARS-CoV-2 lung infection

A key question in SARS-CoV-2 infection is why viral loads and patient outcomes vary dramatically across individuals. Because spatial-temporal dynamics of viral spread and immune response are challenging to study in vivo, we developed Spatial Immune Model of Coronavirus (SIMCoV), a scalable computational model that simulates hundreds of millions of lung cells, including respiratory epithelial cells and T cells. SIMCoV replicates viral growth dynamics observed in patients and shows how spatially dispersed infections can lead to increased viral loads. The model also shows how the timing and strength of the T cell response can affect viral persistence, oscillations, and control. By incorporating spatial interactions, SIMCoV provides a parsimonious explanation for the dramatically different viral load trajectories among patients by varying only the number of initial sites of infection and the magnitude and timing of the T cell immune response. When the branching airway structure of the lung is explicitly represented, we find that virus spreads faster than in a 2D layer of epithelial cells, but much more slowly than in an undifferentiated 3D grid or in a well-mixed differential equation model. These results illustrate how realistic, spatially explicit computational models can improve understanding of within-host dynamics of SARS-CoV-2 infection.