Short report: Historical analysis of a near disaster: Anopheles gambiae in Brazil

Attributed to human-mediated dispersal, a species of the Anopheles gambiae complex invaded northeastern Brazil in 1930. This event is considered unique among the intercontinental introductions of disease vectors and the most serious one: ""Few threats to the future health of the Americas have equalled that inherent in the invasion of Brazil, in 1930, by Anopheles gambiae."" Because it was only in the 1960s that An. gambiae was recognized as a species complex now including seven species, the precise species identity of the Brazilian invader remains a mystery. Here we used historical DNA analysis of museum specimens, collected at the time of invasion from Brazil, and aimed at the identification of the Brazilian invader. Our results identify the arid-adapted Anopheles arabiensis as being the actual invading species. Establishing the identity of the species, in addition to being of intrinsic historical interest, can inform future threats of this sort especially in a changing environment. Furthermore, these results highlight the potential danger of human-mediated range expansions of insect disease vectors and the importance of museum collections in retrieving historical information.

Resilience of protein-protein interaction networks as determined by their large-scale topological features

The relationship between the structure and function of biological networks constitutes a fundamental issue in systems biology. Particularly, the structure of protein-protein interaction networks is related to important biological functions. In this work, we investigated how such a resilience is determined by the large scale features of the respective networks. Four species are taken into account, namely yeast Saccharomyces cerevisiae, worm Caenorhabditis elegans, fly Drosophila melanogaster and Homo sapiens. We adopted two entropy-related measurements (degree entropy and dynamic entropy) in order to quantify the overall degree of robustness of these networks. We verified that while they exhibit similar structural variations under random node removal, they differ significantly when subjected to intentional attacks (hub removal). As a matter of fact, more complex species tended to exhibit more robust networks. More specifically, we quantified how six important measurements of the networks topology (namely clustering coefficient, average degree of neighbors, average shortest path length, diameter, assortativity coefficient, and slope of the power law degree distribution) correlated with the two entropy measurements. Our results revealed that the fraction of hubs and the average neighbor degree contribute significantly for the resilience of networks. In addition, the topological analysis of the removed hubs indicated that the presence of alternative paths between the proteins connected to hubs tend to reinforce resilience. The performed analysis helps to understand how resilience is underlain in networks and can be applied to the development of protein network models.