Pantropic retroviral vectors integrate and express in cells of the malaria mosquito, Anopheles gambiae.

The lack of efficient mechanisms for stable genetic transformation of medically important insects, such as anopheline mosquitoes, is the single most important impediment to progress in identifying novel control strategies. Currently available techniques for foreign gene expression in insect cells in culture lack the benefit of stable inheritance conferred by integration. To overcome this problem, a new class of pantropic retroviral vectors has been developed in which the amphotropic envelope is completely replaced by the G glycoprotein of vesicular stomatitis virus. The broadened host cell range of these particles allowed successful entry, integration, and expression of heterologous genes in cultured cells of Anopheles gambiae, the principle mosquito vector responsible for the transmission of over 100 million cases of malaria each year. Mosquito cells in culture infected with a pantropic vector expressing hygromycin phosphotransferase from the Drosophila hsp70 promoter were resistant to the antibiotic hygromycin B. Integrated provirus was detected in infected mosquito cell clones grown in selective media. Thus, pantropic retroviral vectors hold promise as a transformation system for mosquitoes in vivo.

Rapid local synchronization of action potentials: toward computation with coupled integrate-and-fire neurons.

The collective behavior of interconnected spiking nerve cells is investigated. It is shown that a variety of model systems exhibit the same short-time behavior and rapidly converge to (approximately) periodic firing patterns with locally synchronized action potentials. The dynamics of one model can be described by a downhill motion on an abstract energy landscape. Since an energy landscape makes it possible to understand and program computation done by an attractor network, the results will extend our understanding of collective computation from models based on a firing-rate description to biologically more realistic systems with integrate-and-fire neurons.