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Rapid diagnosis of Ebola hemorrhagic fever by reverse transcription-PCR in an outbreak setting and assessment of patient viral load as a predictor of outcome.

ABSTRACT: The largest outbreak on record of Ebola hemorrhagic fever (EHF) occurred in Uganda from August 2000 to January 2001. The outbreak was centered in the Gulu district of northern Uganda, with secondary transmission to other districts. After the initial diagnosis of Sudan ebolavirus by the National Institute for Virology in Johannesburg, South Africa, a temporary diagnostic laboratory was established within the Gulu district at St. Mary's Lacor Hospital. The laboratory used antigen capture and reverse transcription-PCR (RT-PCR) to diagnose Sudan ebolavirus infection in suspect patients. The RT-PCR and antigen-capture diagnostic assays proved very effective for detecting ebolavirus in patient serum, plasma, and whole blood. In samples collected very early in the course of infection, the RT-PCR assay could detect ebolavirus 24 to 48 h prior to detection by antigen capture. More than 1,000 blood samples were collected, with multiple samples obtained from many patients throughout the course of infection. Real-time quantitative RT-PCR was used to determine the viral load in multiple samples from patients with fatal and nonfatal cases, and these data were correlated with the disease outcome. RNA copy levels in patients who died averaged 2 log(10) higher than those in patients who survived. Using clinical material from multiple EHF patients, we sequenced the variable region of the glycoprotein. This Sudan ebolavirus strain was not derived from either the earlier Boniface (1976) or Maleo (1979) strain, but it shares a common ancestor with both. Furthermore, both sequence and epidemiologic data are consistent with the outbreak having originated from a single introduction into the human population.

SUBMITTER: Towner JS

PROVIDER: S-EPMC374287 | biostudies-literature | 2004 Apr

REPOSITORIES: biostudies-literature

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Rapid diagnosis of Ebola hemorrhagic fever by reverse transcription-PCR in an outbreak setting and assessment of patient viral load as a predictor of outcome.

Towner Jonathan S JS Rollin Pierre E PE Bausch Daniel G DG Sanchez Anthony A Crary Sharon M SM Vincent Martin M Lee William F WF Spiropoulou Christina F CF Ksiazek Thomas G TG Lukwiya Mathew M Kaducu Felix F Downing Robert R Nichol Stuart T ST

Journal of virology 20040401 8

The largest outbreak on record of Ebola hemorrhagic fever (EHF) occurred in Uganda from August 2000 to January 2001. The outbreak was centered in the Gulu district of northern Uganda, with secondary transmission to other districts. After the initial diagnosis of Sudan ebolavirus by the National Institute for Virology in Johannesburg, South Africa, a temporary diagnostic laboratory was established within the Gulu district at St. Mary's Lacor Hospital. The laboratory used antigen capture and rever ...[more]

PMID: 15047846

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Project description:Zaire ebolavirus (ZEBOV) is among the deadliest known human pathogens, causing severe hemorrhagic fever with high case fatality rates ranging from 70-90%. The lack of effective vaccines or treatment available for ZEBOV renders this pathogen as a significant global biodefense threat, as evidenced by the current, highly lethal outbreak of a novel ZEBOV variant in western Africa. Existing mouse models of lethal ZEBOV infection do not reproduce hallmark symptoms of Ebola hemorrhagic fever (EHF) including prolonged blood coagulation, acute hepatitis, disseminated intravascular coagulation (DIC), and death from hemorrhagic shock, thus restricting pathogenesis studies to non-human primates (NHP). This has prevented rapid evaluation of countermeasures in outbreak scenarios, and impeded a comprehensive understanding of how host responses to infection contribute to severe EHF disease. Here we demonstrate that mice from the Collaborative Cross (CC), a panel of reproducible, recombinant inbred animals that span the genetic breadth of three murine subspecies, are susceptible to a spectrum of disease phenotypes following ZEBOV infection. In contrast to C57Bl6/J mice, which develop lethal disease without symptoms of EHF, CC recombinant inbred intercrossed (CC-RIX) lines develop either complete resistance to lethal disease or severe EHF characterized by prolonged coagulation times and 100% mortality. Disease resistance and survival is not dependent on viral tropism, as both resistant and EHF-susceptible lines show similar inflammation and cytopathic effect in target organs. Transcriptomics reveal potential mechanisms for both induction of severe hemorrhage in EHF mediated by IL-6 and vascular activation, and resistance to lethal infection by induction of lymphocyte differentiation and cellular adhesion. These data demonstrate that host responses specific to unique genetic backgrounds determine susceptibility to hemorrhagic syndrome independent of virus replication. The CC represents a novel mouse model for studying EHF pathogenesis, and we anticipate that it will be applied immediately to developing and evaluating therapeutic countermeasures. Microarrays were performed on liver and spleen samples from mice collected at days 1, 3, and 5 post-infection with mouse adapted Zaire ebolavirus or from time-matched mock-infected animals.

Project description:Ebola (EBOV) virus causes severe and often lethal hemorrhagic fever in humans and nonhuman primates (NHP), and has been classified as a Category A bioweapon agent. There are currently no approved preventive vaccines or postexposure treatments for EBOV hemorrhagic fever. The mechanisms of EBOV pathogenesis are only partially understood, but the dysregulation of normal host immune responses (including destruction of lymphocytes, increases in levels of circulating proinflammatory cytokines, and development of coagulation abnormalities) is thought to play a major role. Accumulating evidence suggests that much of the observed pathology is not the direct result of virus-induced structural damage but rather is due to the release of soluble immune mediators from EBOV-infected cells. It is therefore essential to understand how the candidate therapeutic may be interrupting the disease process and/or targeting the infectious agent. Identification of effective treatment strategies may greatly benefit based on identification of molecular features of the host response to infection and treatment. In order to identify these gene signatures related to correlates of protection, we used a DNA microarray-based approach to compare the host genome-wide responses of EBOV-infected NHP responding to candidate therapeutics. With this approach, we have identified genes that appear to correlate with survival, including chemokine ligand 8 (CCL8/MCP-2), and revealed a subset of distinctly differently expressed genes that may provide possible targets for future diagnostics or therapeutics. These analyses will assist us in understanding the pathogenic mechanisms of EBOV infection as well as identify improved therapeutic strategies. Transcriptional analysis of global gene expression changes in Zaire Ebola Virus (ZEBOV)-infected rhesus macaques that were treated with either recombinant nematode anticoagulant protein c2 (rNAPc2) or recombinant human activated protein C (rhAPC). Animals were infected with 1000pfu ZEBOV, then subsequently treated with rNAPc2 or rhAPC. Four animals were left untreated for controls. Blood samples were taken at specified days post-infection and PBMCs were isolated from the samples and inactivated in TRIzol reagent. Total RNA was isolated from the samples, then linearly amplified and hybridized to a whole genome long-oligonucleotide microarray in a two color comparative format with a commercially available human reference RNA from Stratagene as a consistent control in dataset comparisons.

Dataset Information

Rapid diagnosis of Ebola hemorrhagic fever by reverse transcription-PCR in an outbreak setting and assessment of patient viral load as a predictor of outcome.

Publications

Rapid diagnosis of Ebola hemorrhagic fever by reverse transcription-PCR in an outbreak setting and assessment of patient viral load as a predictor of outcome.

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