Detection of all four dengue serotypes in Aedes aegypti female mosquitoes collected in a rural area in Colombia

The Aedes aegypti vector for dengue virus (DENV) has been reported in urban and periurban areas. The information about DENV circulation in mosquitoes in Colombian rural areas is limited, so we aimed to evaluate the presence of DENV in Ae. aegypti females caught in rural locations of two Colombian municipalities, Anapoima and La Mesa. Mosquitoes from 497 rural households in 44 different rural settlements were collected. Pools of about 20 Ae. aegypti females were processed for DENV serotype detection. DENV in mosquitoes was detected in 74% of the analysed settlements with a pool positivity rate of 62%. The estimated individual mosquito infection rate was 4.12% and the minimum infection rate was 33.3/1,000 mosquitoes. All four serotypes were detected; the most frequent being DENV-2 (50%) and DENV-1 (35%). Two-three serotypes were detected simultaneously in separate pools. This is the first report on the co-occurrence of natural DENV infection of mosquitoes in Colombian rural areas. The findings are important for understanding dengue transmission and planning control strategies. A potential latent virus reservoir in rural areas could spill over to urban areas during population movements. Detecting DENV in wild-caught adult mosquitoes should be included in the development of dengue epidemic forecasting models.

Pathway analysis for identification of potential biomarkers in severe cutaneous drug hypersensitivity reactions

Purpose: To construct a cluster model or a gene signature for Stevens-Johnson syndrome (SJS) using pathways analysis in order to identify some potential biomarkers that may be used for early detection of SJS and epidermal necrolysis (TEN) manifestations. Methods: Gene expression profiles of GSE12829 were downloaded from Gene Expression Omnibus database. A total of 193 differentially expressed genes (DEGs) were obtained. We applied these genes to geneMANIA database, to remove ambiguous and duplicated genes, and after that, characterized the gene expression profiles using geneMANIA, DAVID, REACTOME, STRING and GENECODIS which are online software and databases. Results: Out of 193 genes, only 91 were used (after removing the ambiguous and duplicated genes) for topological analysis. It was found by geneMANIA database search that majority of these genes were coexpressed yielding 84.63 % co-expression. It was found that ten genes were in Physical interactions comprising almost 14.33 %. There were < 1 % pathway and genetic interactions with values of 0.97 and 0.06 %, respectively. Final analyses revealed that there are two clusters of gene interactions and 13 genes were shown to be in evident relationship of interaction with regards to hypersensitivity. Conclusion: Analysis of differential gene expressions by topological and database approaches in the current study reveals 2 gene network clusters. These genes are CD3G, CD3E, CD3D, TK1, TOP2A, CDK1, CDKN3, CCNB1, and CCNF. There are 9 key protein interactions in hypersensitivity reactions and may serve as biomarkers for SJS and TEN. Pathways related gene clusters has been identified and a genetic model to predict SJS and TEN early incidence using these biomarker genes has been developed.