Analysis of an Ebola virus disease survivor whose host and viral markers were predictive of death indicates the effectiveness of medical countermeasures and supportive care.

BACKGROUND: Ebola virus disease (EVD) is an often-fatal infection where the effectiveness of medical countermeasures is uncertain. During the West African outbreak (2013-2016), several patients were treated with different types of anti-viral therapies including monoclonal antibody-based cocktails that had the potential to neutralise Ebola virus (EBOV). However, at the time, the efficacy of these therapies was uncertain. Given the scale of the outbreak, several clinical phenotypes came to the forefront including the ability of the same virus to cause recrudescence in the same patient-perhaps through persisting in immune privileged sites. Several key questions remained including establishing if monoclonal antibody therapy was effective in humans with severe EVD, whether virus escape mutants were selected during treatment, and what is the potential mechanism(s) of persistence. This was made possible through longitudinal samples taken from a UK patient with EVD. METHODS: Several different sample types, plasma and cerebrospinal fluid, were collected and sequenced using Illumina-based RNAseq. Sequence reads were mapped both to EBOV and the human genome and differential gene expression analysis used to identify changes in the abundance of gene transcripts as infection progressed. Digital Cell Quantitation analysis was used to predict the immune phenotype in samples derived from blood. RESULTS: The findings were compared to equivalent data from West African patients. The study found that both virus and host markers were predictive of a fatal outcome. This suggested that the extensive supportive care, and most likely the application of the medical countermeasure ZMab (a monoclonal antibody cocktail), contributed to survival of the UK patient. The switch from progression to a 'fatal' outcome to a 'survival' outcome could be seen in both the viral and host markers. The UK patient also suffered a recrudescence infection 10 months after the initial infection. Analysis of the sequencing data indicated that the virus entered a period of reduced or minimal replication, rather than other potential mechanisms of persistence-such as defective interfering genomes. CONCLUSIONS: The data showed that comprehensive supportive care and the application of medical countermeasures are worth pursuing despite an initial unfavourable prognosis

Deep Sequencing of RNA from Blood and Oral Swab Samples Reveals the Presence of Nucleic Acid from a Number of Pathogens in Patients with Acute Ebola Virus Disease and Is Consistent with Bacterial Translocation across the Gut.

In this study, samples from the 2013-2016 West African Ebola virus outbreak from patients in Guinea with Ebola virus disease (EVD) were analyzed to discover and classify what other pathogens were present. Throat swabs were taken from deceased EVD patients, and peripheral blood samples were analyzed that had been taken from patients when they presented at the treatment center with acute illness. High-throughput RNA sequencing (RNA-seq) and bioinformatics were used to identify the potential microorganisms. This approach confirmed Ebola virus (EBOV) in all samples from patients diagnosed as acute positive for the virus by quantitative reverse transcription-PCR in deployed field laboratories. Nucleic acid mapping to Plasmodium was also used on the patient samples, confirming results obtained with an antigen-based rapid diagnostic test (RDT) conducted in the field laboratories. The data suggested that a high Plasmodium load, as determined by sequence read depth, was associated with mortality and influenced the host response, whereas a lower parasite load did not appear to affect outcome. The identifications of selected bacteria from throat swabs via RNA-seq were confirmed by culture. The data indicated that the potential pathogens identified in the blood samples were associated with translocation from the gut, suggesting the presence of bacteremia, which transcriptome data suggested may induce or aggravate the acute-phase response observed during EVD. Transcripts mapping to different viruses were also identified, including those indicative of lytic infections. The development of high-resolution analysis of samples from patients with EVD will help inform care pathways and the most appropriate general antimicrobial therapy to be used in a resource-poor setting. IMPORTANCE Our results highlight the identification of an array of pathogens in the blood of patients with Ebola virus disease (EVD). This has not been done before, and the data have important implications for the treatment of patients with EVD, particularly considering antibiotic stewardship. We show that EVD patients who were also infected with Plasmodium, particularly at higher loads, had more adverse outcomes than patients with lower levels of Plasmodium. However, the presence of Plasmodium did not influence the innate immune response, and it is likely that the presence of EBOV dominated this response. Several viruses other than EBOV were identified, and bacteria associated with sepsis were also identified. These findings were indicative of bacterial translocation across the gut during the acute phase of EVD

Zika virus infection preferentially counterbalances human peripheral monocyte and/or NK cell activity

Zika virus (ZIKV) has reemerged in the population and caused unprecedented global outbreaks. Here, the transcriptomic consequences of ZIKV infection were studied systematically first in human peripheral blood CD14+ monocytes and monocyte-derived macrophages with high-density RNA sequencing. Analyses of the ZIKV genome revealed that the virus underwent genetic diversification, and differential mRNA abundance was found in host cells during infection. Notably, there was a significant change in the cellular response, with cross talk between monocytes and natural killer (NK) cells as one of the highly identified pathways. Immunophenotyping of peripheral blood from ZIKV-infected patients further confirmed the activation of NK cells during acute infection. ZIKV infection in peripheral blood cells isolated from healthy donors led to the induction of gamma interferon (IFN-γ) and CD107a—two key markers of NK cell function. Depletion of CD14+ monocytes from peripheral blood resulted in a reduction of these markers and reduced priming of NK cells during infection. This was complemented by the immunoproteomic changes observed. Mechanistically, ZIKV infection preferentially counterbalances monocyte and/or NK cell activity, with implications for targeted cytokine immunotherapies

Persistence and clearance of Ebola virus RNA from seminal fluid of Ebola virus disease survivors: a longitudinal analysis and modelling study

Background By January, 2016, all known transmission chains of the Ebola virus disease (EVD) outbreak in west Africa had been stopped. However, there is concern about persistence of Ebola virus in the reproductive tract of men who have survived EVD. We aimed to use biostatistical modelling to describe the dynamics of Ebola virus RNA load in seminal fl uid, including clearance parameters. Methods In this longitudinal study, we recruited men who had been discharged from three Ebola treatment units in Guinea between January and July, 2015. Participants provided samples of seminal fl uid at follow-up every 3–6 weeks, which we tested for Ebola virus RNA using quantitative real-time RT-PCR. Representative specimens from eight participants were then inoculated into immunodefi cient mice to test for infectivity. We used a linear mixed-eff ect model to analyse the dynamics of virus persistence in seminal fl uid over time. Findings We enrolled 26 participants and tested 130 seminal fl uid specimens; median follow up was 197 days (IQR 187–209 days) after enrolment, which corresponded to 255 days (228–287) after disease onset. Ebola virus RNA was detected in 86 semen specimens from 19 (73%) participants. Median duration of Ebola virus RNA detection was 158 days after onset (73–181; maximum 407 days at end of follow-up). Mathematical modelling of the quantitative time-series data showed a mean clearance rate of Ebola virus RNA from seminal fl uid of –0·58 log units per month, although the clearance kinetic varied greatly between participants. Using our biostatistical model, we predict that 50% and 90% of male survivors clear Ebola virus RNA from seminal fl uid at 115 days (90% prediction interval 72–160) and 294 days (212–399) after disease onset, respectively. We also predicted that the number of men positive for Ebola virus RNA in aff ected countries would decrease from about 50 in January 2016, to fewer than 1 person by July, 2016. Infectious virus was detected in 15 of 26 (58%) specimens tested in mice. Interpretation Time to clearance of Ebola virus RNA from seminal fl uid varies greatly between individuals and could be more than 13 months. Our predictions will assist in decision-making about surveillance and preventive measures in EVD outbreaks

Persistence and clearance of Ebola virus RNA from seminal fluid of Ebola virus disease survivors: a longitudinal analysis and modelling study.

BACKGROUND: By January, 2016, all known transmission chains of the Ebola virus disease (EVD) outbreak in west Africa had been stopped. However, there is concern about persistence of Ebola virus in the reproductive tract of men who have survived EVD. We aimed to use biostatistical modelling to describe the dynamics of Ebola virus RNA load in seminal fluid, including clearance parameters. METHODS: In this longitudinal study, we recruited men who had been discharged from three Ebola treatment units in Guinea between January and July, 2015. Participants provided samples of seminal fluid at follow-up every 3-6 weeks, which we tested for Ebola virus RNA using quantitative real-time RT-PCR. Representative specimens from eight participants were then inoculated into immunodeficient mice to test for infectivity. We used a linear mixed-effect model to analyse the dynamics of virus persistence in seminal fluid over time. FINDINGS: We enrolled 26 participants and tested 130 seminal fluid specimens; median follow up was 197 days (IQR 187-209 days) after enrolment, which corresponded to 255 days (228-287) after disease onset. Ebola virus RNA was detected in 86 semen specimens from 19 (73%) participants. Median duration of Ebola virus RNA detection was 158 days after onset (73-181; maximum 407 days at end of follow-up). Mathematical modelling of the quantitative time-series data showed a mean clearance rate of Ebola virus RNA from seminal fluid of -0·58 log units per month, although the clearance kinetic varied greatly between participants. Using our biostatistical model, we predict that 50% and 90% of male survivors clear Ebola virus RNA from seminal fluid at 115 days (90% prediction interval 72-160) and 294 days (212-399) after disease onset, respectively. We also predicted that the number of men positive for Ebola virus RNA in affected countries would decrease from about 50 in January 2016, to fewer than 1 person by July, 2016. Infectious virus was detected in 15 of 26 (58%) specimens tested in mice. INTERPRETATION: Time to clearance of Ebola virus RNA from seminal fluid varies greatly between individuals and could be more than 13 months. Our predictions will assist in decision-making about surveillance and preventive measures in EVD outbreaks. FUNDING: This study was funded by European Union's Horizon 2020 research and innovation programme, Directorate-General for International Cooperation and Development of the European Commission, Institut national de la santé et de la recherche médicale (INSERM), German Research Foundation (DFG), and Innovative Medicines Initiative 2 Joint Undertaking

Temporal and spatial analysis of the 2014-2015 Ebola virus outbreak in West Africa

West Africa is currently witnessing the most extensive Ebola virus (EBOV) outbreak so far recorded. Until now, there have been 27,013 reported cases and 11,134 deaths. The origin of the virus is thought to have been a zoonotic transmission from a bat to a two-year-old boy in December 2013 (ref. 2). From this index case the virus was spread by human-to-human contact throughout Guinea, Sierra Leone and Liberia. However, the origin of the particular virus in each country and time of transmission is not known and currently relies on epidemiological analysis, which may be unreliable owing to the difficulties of obtaining patient information. Here we trace the genetic evolution of EBOV in the current outbreak that has resulted in multiple lineages. Deep sequencing of 179 patient samples processed by the European Mobile Laboratory, the first diagnostics unit to be deployed to the epicentre of the outbreak in Guinea, reveals an epidemiological and evolutionary history of the epidemic from March 2014 to January 2015. Analysis of EBOV genome evolution has also benefited from a similar sequencing effort of patient samples from Sierra Leone. Our results confirm that the EBOV from Guinea moved into Sierra Leone, most likely in April or early May. The viruses of the Guinea/Sierra Leone lineage mixed around June/July 2014. Viral sequences covering August, September and October 2014 indicate that this lineage evolved independently within Guinea. These data can be used in conjunction with epidemiological information to test retrospectively the effectiveness of control measures, and provides an unprecedented window into the evolution of an ongoing viral haemorrhagic fever outbreak.status: publishe