Cyclooxygenase-2 inhibitor blocks the production of West Nile virus-induced neuroinflammatory markers in astrocytes

Inflammatory immune responses triggered initially to clear West Nile virus (WNV) infection later become detrimental and contribute to the pathological processes such as blood–brain barrier (BBB) disruption and neuronal death, thus complicating WNV-associated encephalitis (WNVE). It has been demonstrated previously that WNV infection in astrocytes results in induction of multiple matrix metalloproteinases (MMPs), which mediate BBB disruption. Cyclooxygenase (COX) enzymes and their product, prostaglandin E2 (PGE2), modulate neuroinflammation and regulate the production of multiple inflammatory molecules including MMPs. Therefore, this study determined and characterized the pathophysiological consequences of the expression of COX enzymes in human brain cortical astrocytes (HBCAs) following WNV infection. Whilst COX-1 mRNA expression did not change, WNV infection significantly induced RNA and protein expression of COX-2 in HBCAs. Similarly, PGE2 production was also enhanced significantly in infected HBCAs and was blocked in the presence of the COX-2-specific inhibitor NS-398, thus suggesting that COX-2, and not COX-1, was the source of the increased PGE2. Treatment of infected HBCAs with NS-398 attenuated the expression of MMP-1, -3 and -9 in a dose-dependent manner. Similarly, expression of interleukin-1β, -6 and -8, which were markedly elevated in infected HBCAs, exhibited a significant reduction in their levels in the presence of NS-398. These results provide direct evidence that WNV-induced COX-2/PGE2 is involved in modulating the expression of multiple neuroinflammatory mediators, thereby directly linking COX-2 with WNV disease pathogenesis. The ability of COX-2 inhibitors to modulate WNV-induced COX-2 and PGE2 signalling warrants further investigation in an animal model as a potential approach for clinical management of neuroinflammation associated with WNVE

Measuring the Evolutionary Rewiring of Biological Networks

We have accumulated a large amount of biological network data and expect even more to come. Soon, we anticipate being able to compare many different biological networks as we commonly do for molecular sequences. It has long been believed that many of these networks change, or “rewire”, at different rates. It is therefore important to develop a framework to quantify the differences between networks in a unified fashion. We developed such a formalism based on analogy to simple models of sequence evolution, and used it to conduct a systematic study of network rewiring on all the currently available biological networks. We found that, similar to sequences, biological networks show a decreased rate of change at large time divergences, because of saturation in potential substitutions. However, different types of biological networks consistently rewire at different rates. Using comparative genomics and proteomics data, we found a consistent ordering of the rewiring rates: transcription regulatory, phosphorylation regulatory, genetic interaction, miRNA regulatory, protein interaction, and metabolic pathway network, from fast to slow. This ordering was found in all comparisons we did of matched networks between organisms. To gain further intuition on network rewiring, we compared our observed rewirings with those obtained from simulation. We also investigated how readily our formalism could be mapped to other network contexts; in particular, we showed how it could be applied to analyze changes in a range of “commonplace” networks such as family trees, co-authorships and linux-kernel function dependencies