Project description:Here; we have described and tested a microarray based-method for the screening of dengue virus (DENV) serotypes. This DNA microarray assay is specific and sensitive and can detect dual infections with two dengue virus serotypes and single-serotype infections. Other methodologies may underestimate samples containing more than one serotype. This technology can be used to discriminate between the four DENV serotypes. Single-stranded DNA targets were covalently attached to glass slides and hybridised with specific labelled probes. DENV isolates and dengue samples were used to evaluate microarray performance. Our results demonstrate that the probes hybridized specifically to DENV serotypes; with no detection of unspecific signals. This finding provides evidence that specific probes can effectively identify single and double infections in DENV samples. Background Dengue is a mosquito-borne viral infection causing a major public health problem globally. Dengue virus (DENV) is the causative agent of dengue fever (DF) and dengue hemorrhagic fever (DHF) and includes four distinct serotypes (DENV-1, DENV-2, DENV-3, and DENV-4). DENV-2 and DENV-3 have been associated with severe dengue disease, consequently, laboratory testing for DENV is needed to confirm the diagnosis of DENV infection, serotype and to differentiate dengue from other febrile tropical illnesses. In addition, surveillance of mosquitoes infected with DENV is needed to monitor the infection rates within vector mosquito populations harboring specific serotype to provide an early warning sign to predict epidemics. Results In this work we have applied microarray analysis to simultaneously determine the serotype of multiple RNA samples from human or mosquitoes. The proposed microarray method can be used for i) rapid and reliable dengue diagnosis; ii) serotyping and iii) surveillance of mosquitoes infected with dengue. These microarrays were useful to confirm the presence of DENV-2 in 94 serum samples, DENV-3 in three samples from Juchitan, Oaxaca and one case from Juchitan, Oaxaca contained DENV-2 and -3. Moreover by using these microarrays we also determined DENV in pools of gravid females mosquitoes collected in several sites of nineteen Mexican states in 2005. Mosquito pools from 31 cities in the states of Yucatan, Campeche, Tabasco, Chiapas, Veracruz, Oaxaca, Guerrero, Tamaulipas and Colima were infected with DENV-2, six cities in Yucatán, Tabasco, Morelos, Tamaulipas, Colima, and Nayarit with DENV-1, three from Tabasco, Veracruz and Oaxaca with DENV 3 and two with two serotypes simultaneously (Ciudad Mante with DENV-1 and DENV-2, and Tavela with DENV-2 and DENV-3). Conclusion Here we show the success of applying microarrays assay to provide a consistently robust qualitative detection of dengue serotypes (DENV-1, DENV-2, DENV-3 and DENV-4) in serum samples from patients or in pools of gravid female mosquitoes collected in the field of nineteen Mexican states. Interestingly, we did not detect any mosquito or serum sample containing DENV-4.

Project description:Background: We report the detailed development of biomarkers to predict the clinical outcome under dengue infection. Transcriptional signatures from purified peripheral blood mononuclear cells were derived from whole-genome gene-expression microarray data and validated by quantitative PCR and tested in independent samples. Methodology/Principal Findings: The study was performed on patients of a well-characterized dengue cohort from Recife, Brazil. The samples analyzed were collected prospectively from acute febrile dengue patients who evolved with different degrees of disease severity, classic dengue fever or dengue hemorrhagic fever (DHF) and compared with similar samples from other non-dengue febrile illnesses. The DHF samples were collected 2-3 days before the presentation of the plasma leakage symptoms. Differentially-expressed genes were selected by univariate statistical tests as well as multivariate classification techniques. The results showed that at early stages of dengue infection, the genes involved in effector mechanisms of innate immune response presented a weaker activation on patients who later developed hemorrhagic fever, whereas the genes involved in apoptosis were expressed in higher levels. Conclusions/Significance: Some of the gene expression signatures displayed estimated accuracy rates of more than 95%, indicating that expression profiling with these signatures may provide a useful means of DHF prognosis at early stages of infection The samples correspond to blood samples from 26 patients from a cohort in Brazil, divided into three classes, DHF, DF, ND, as follows: 18 were confirmed dengue 3, genotype III cases, among which 10 were diagnosed as dengue hemorrhagic fever (DHF) and 8 as classical dengue fever (DF), and 8 control samples (ND) from febrile patients confirmed to be not infected with dengue. None of the DHF patients presented vasculopathy signs and symptoms at the time the samples used in the functional genomic characterization were collected. At the time of collection the patients referred approximately 5 days of disease and the absence of fever was reported two to three days after enrollment. The samples from the DF, DHF and ND patients were matched to avoid significant differences regarding patient age, gender, dengue infection history and days of symptoms among the groups.

Project description:This pilot study, aimed to profile the host transcriptome as a potential strategy for identifying specific biomarkers for dengue prediction and detection. High-throughput RNA-sequencing (RNA-seq) was employed to generate host transcriptome profiles in 16 dengue patients and 10 healthy controls. Differentially expressed genes (DEGs) were identified in patients with severe dengue and those with dengue with warning signs compared to healthy individuals. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to elucidate the functions of upregulated and downregulated genes. Compared to healthy controls, 6466 genes were significantly differentially expressed (P < 0.05) in the dengue with warning signs group and 3082 genes in the severe dengue group, with over half being upregulated. The major KEGG pathways implicated included transport and catabolism (14.4%-16.3%), signal transduction (6.6%-7.3%), global and overview maps (6.7%-7.1%), viral diseases (4.6%-4.8%), and the immune system (4.4%-4.6%). Several genes exhibited consistent and significant upregulation across all dengue patients, regardless of severity: Interferon alpha inducible protein 27 (IFI27), Potassium Channel Tetramerisation Domain Containing 14 (KCTD14), Syndecan 1 (SDC1), DCC netrin 1 receptor (DCC), Ubiquitin C-terminal hydrolase L1 (UCHL1), Marginal zone B and B1 cell specific protein (MZB1), Nestin (NES), C-C motif chemokine ligand 2 (CCL2), TNF receptor superfamily member 17 (TNFSF17), and TNF receptor superfamily member 13B (TNFRSF13B). Further analysis revealed potential biomarkers for severe dengue prediction, including TNF superfamily member 15 (TNFSF15), Plasminogen Activator Inhibitor-2 (SERPINB2), motif chemokine ligand 7 (CCL7), aconitate decarboxylase 1 (ACOD1), Metallothionein 1G (MT1G) and Myosin Light Chain Kinase (MYLK2), which were expressed 3.5 times, 2.9 times, 2.3 times, 2.1 times, 1.7 times, and 1.4 times greater, respectively, than dengue patients exhibiting warning signs. The identification of these host biomarkers through RNA-sequencing holds promising implications and potential to augment existing dengue detection algorithms, contributing significantly to improved diagnostic and prognostic capabilities.

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Gene expression analysis in Dengue virus infection

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