Midgut microbiota of the malaria mosquito vector Anopheles gambiae and interactions with Plasmodium falciparum infection.

The susceptibility of Anopheles mosquitoes to Plasmodium infections relies on complex interactions between the insect vector and the malaria parasite. A number of studies have shown that the mosquito innate immune responses play an important role in controlling the malaria infection and that the strength of parasite clearance is under genetic control, but little is known about the influence of environmental factors on the transmission success. We present here evidence that the composition of the vector gut microbiota is one of the major components that determine the outcome of mosquito infections. A. gambiae mosquitoes collected in natural breeding sites from Cameroon were experimentally challenged with a wild P. falciparum isolate, and their gut bacterial content was submitted for pyrosequencing analysis. The meta-taxogenomic approach revealed a broader richness of the midgut bacterial flora than previously described. Unexpectedly, the majority of bacterial species were found in only a small proportion of mosquitoes, and only 20 genera were shared by 80% of individuals. We show that observed differences in gut bacterial flora of adult mosquitoes is a result of breeding in distinct sites, suggesting that the native aquatic source where larvae were grown determines the composition of the midgut microbiota. Importantly, the abundance of Enterobacteriaceae in the mosquito midgut correlates significantly with the Plasmodium infection status. This striking relationship highlights the role of natural gut environment in parasite transmission. Deciphering microbe-pathogen interactions offers new perspectives to control disease transmission.

New approach for segmentation and quantification of two-dimensional gel electrophoresis images.

MOTIVATION: Detection of protein spots in two-dimensional gel electrophoresis images (2-DE) is a very complex task and current approaches addressing this problem still suffer from significant shortcomings. When quantifying a spot, most of the current software applications include a lot of background due to poor segmentation. Other software applications use a fixed window for this task, resulting in omission of part of the protein spot, or including background in the quantification. The approach presented here for the segmentation and quantification of 2-DE aims to minimize these problems. RESULTS: Five sections from different gels are used to test the performance of the presented method concerning the detection of protein spots, and three gel sections are used to test the quantification of sixty protein spots. Comparisons with a state-of-the-art commercial software and an academic state-of-the-art approach are presented. It is shown that the proposed approach for segmentation and quantification of 2-DE images can compete with the available commercial and academic software packages. AVAILABILITY: A command-line prototype may be downloaded, for non-commercial use, from http://w3.ualg.pt/~aanjos/prototypes.html.