Detection and discovery of viral pathogens associated with dengue-like symptoms

大规模的病毒监测研究对于监测全球出现的传染性疾病至关重要。 疾病和产量有关流行病毒种类的流行和季节性的重要信息， 新物种的可能存在。许多大型流行病学研究已经在 然而，温带国家在热带环境中没有重复，并且可能揭示病毒负担 以及由于固有的环境和社会差异导致的发病率变化。登革热病毒（DV）是一种 一种典型的新发传染病，估计每年以迅速的速度感染5000万至1亿人， 扩大了地理范围，是人类最常见的媒介传播病毒性疾病。目前 然而，现有的实验室诊断方法未能在30 - 70%的表现为 登革热的典型症状本研究的目的是双重的：使用最好的可用诊断 在发展中热带环境中描绘病毒病原体谱的技术， 并利用广泛筛查提供的数据作为平台， 发现新的或不同的人类病毒病原体。 与伊娃哈里斯合作，这项研究将使用病毒芯片（UCSF）来表征人类血清 和PBMC样本来自拟定的基于医院的研究， 在多个季节出现登革热样症状。这将使我们能够捕捉到流行，季节性 以及疑似登革热病例中所有已知病毒的双重感染率。我们还建议利用 基于几个标准对选定数量的样品进行超深度测序，包括 发现以前未表征的病原体的症状。我们将进行全基因组克隆， 对有前景的线索进行分子表征，包括开发基于PCR的快速诊断方法， 用于后续关联研究的血清学试剂。

Large-scale viral surveillance studies are critical to monitoring the global emergence of infectious disease and yield important information about the prevalence and seasonality of circulating virus species and the possible existence of novel species. Many large epidemiologic studies that have been conducted in temperate countries have not been repeated in tropical settings, however, and are likely to reveal viral burden and incidence variations due to inherent environmental and social differences. Dengue virus (DV) is an archetypal emerging infectious disease that infects an estimated 50-100 million people annually in a rapidly expanding geographic range and is the most common vector-borne viral disease of humans. Currently available lab diagnostic methods, however, fail to detect DV infection in 30-70% of patients presenting with hallmark dengue symptoms. The purpose of this study is twofold: to use the best available diagnostic technologies to delineate the spectrum of viral pathogens in a developing tropical environment with respect to dengue-like illnesses and to utilize the data provided by the extensive screening as a platform for the discovery of novel or divergent human viral pathogens. In collaboration with Eva Harris, this study will use the Virochip (UCSF) to characterize human sera and PBMC samples from Nicaraguan patients from the proposed hospital-based study presenting with dengue-like symptoms over multiple seasons. This will allow us to capture both the prevalence, seasonality and dual infection rates for all known viruses in suspected dengue cases over time. We also propose to utilize ultra-deep sequencing for a select number of samples based on several criteria including severity of symptoms for discovery of previously uncharacterized agents. We will pursue full genome cloning and molecular characterization for promising leads, including development of PCR-based rapid diagnostics and serological reagents for subsequent association studies.