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Viruses
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Medical Advances in Viral Hemorrhagic Fever Research
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Medical Advances in Viral Hemorrhagic Fever Research

A special issue of Viruses (ISSN 1999-4915). This special issue belongs to the section "Animal Viruses".

Deadline for manuscript submissions: closed (31 July 2019) | Viewed by 76691

Special Issue Editors

Dr. Ian Crozier

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Guest Editor
NIH/NIAID Integrated Research Facility at Fort Detrick (IRF-Frederick), supported by Clinical Monitoring Research Program, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, MD 21702, USA
Interests: emerging infectious diseases; viral hemorrhagic fevers; mechanisms of immune privilege and viral persistence; filoviruses; arenaviruses
Dr. Jens H. Kuhn

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Guest Editor
NIH/NIAID Integrated Research Facility at Fort Detrick (IRF-Frederick), B-8200 Research Plaza, Fort Detrick, Frederick, MD 21702, USA
Interests: arenaviruses; biodefense; bioengagement; BSL-4; filoviruses; henipaviruses; Kyasanur Forest disease virus; nairoviruses; phleboviruses; Omsk hemorrhagic fever virus; simian hemorrhagic fever virus
Special Issues, Collections and Topics in MDPI journals
Dr. Sheli R. Radoshitzky

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Guest Editor
United States Army Medical Research Institute of Infectious Diseases (USAMRIID), 1425 Porter Street, Fort Detrick, Frederick, MD 21702, USA
Interests: molecular virology; emerging infectious diseases; viral hemorrhagic fevers; arenaviruses; filoviruses; alphaviruses

Special Issue Information

Dear Colleagues,

Recent large outbreaks of Ebola and Marburg virus disease (Eastern and Western Africa), Lassa fever (Western Africa), Crimean Congo hemorrhagic fever (Africa, Eastern Europe, Western Asia) and severe fever with thrombocytopenia syndrome (China, Japan, South Korea) have afforded higher-resolution views at human clinical diseases historically referred to as “viral hemorrhagic Fevers.” In addition to updating our understanding of the spectrum and severity of acute disease syndromes, recent encounters have renewed interest in, e.g., the role of pathogen–agnostic care in addition to virus-specific countermeasures, clinical sequelae after infection, and viral persistence potentially associated with inflammatory syndromes or risk of transmission and outbreak re-ignition. Although there are no FDA-approved medical countermeasures against these viral agents, increased funding, interest, and novel technologies have accelerated research and understanding of many medical aspects of these and other, more neglected (e.g., Alkhurma, Chapare, Guanarito, Kyasanur Forest disease, Lujo, Omsk hemorrhagic fever, Sabiá viruses), viral hemorrhagic fever-causing pathogens. New clinical data and at-bedside approached, advanced genomics and proteomics tools, CRISPR-Cas9 screens, and novel off-label or IND-level vaccine and therapeutics platforms have all contributed (or have the potential) to expand our knowledge of disease course, pathogenesis, and molecular epidemiology, as well as to the development of better diagnostics and medical countermeasures. The present Special Issue covers a wide range of topics focusing on human clinical disease related to such “Medical Advances in Viral Hemorrhagic Fever Research".

Dr. Ian Crozier
Dr. Jens H. Kuhn
Dr. Sheli R. Radoshitzky
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Viruses is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • arenaviruses
  • filoviruses
  • flaviviruses
  • bunyaviruses
  • clinical presentation
  • epidemiology/outbreak response
  • pathology/pathogenesis
  • medical countermeasures
  • diagnostics

Published Papers (18 papers)

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15 pages, 2016 KiB  
Article
Establishing Healthcare Worker Performance and Safety in Providing Critical Care for Patients in a Simulated Ebola Treatment Unit: Non-Randomized Pilot Study
by Peter Kiiza, Sarah I. Mullin, Koren Teo, Len Goodman, Adic Perez, Ruxandra Pinto, Kelly Thompson, Dominique Piquette, Trevor Hall, Elhadj I. Bah, Michael Christian, Jan J. Hajek, Raymond Kao, François Lamontagne, John C. Marshall, Sharmistha Mishra, Srinivas Murthy, Abel Vanderschuren, Robert A. Fowler and Neill K. J. Adhikari
Viruses 2021, 13(11), 2205; https://doi.org/10.3390/v13112205 - 2 Nov 2021
Cited by 1 | Viewed by 2424
Abstract
Improving the provision of supportive care for patients with Ebola is an important quality improvement initiative. We designed a simulated Ebola Treatment Unit (ETU) to assess performance and safety of healthcare workers (HCWs) performing tasks wearing personal protective equipment (PPE) in hot (35 [...] Read more.
Improving the provision of supportive care for patients with Ebola is an important quality improvement initiative. We designed a simulated Ebola Treatment Unit (ETU) to assess performance and safety of healthcare workers (HCWs) performing tasks wearing personal protective equipment (PPE) in hot (35 °C, 60% relative humidity) or thermo-neutral (20 °C, 20% relative humidity) conditions. In this pilot phase to determine the feasibility of study procedures, HCWs in PPE were non-randomly allocated to hot or thermo-neutral conditions to perform peripheral intravenous (PIV) and midline catheter (MLC) insertion and endotracheal intubation (ETI) on mannequins. Eighteen HCWs (13 physicians, 4 nurses, 1 nurse practitioner; 2 with prior ETU experience; 10 in hot conditions) spent 69 (10) (mean (SD)) minutes in the simulated ETU. Mean (SD) task completion times were 16 (6) min for PIV insertion; 33 (5) min for MLC insertion; and 16 (8) min for ETI. Satisfactory task completion was numerically higher for physicians vs. nurses. Participants’ blood pressure was similar, but heart rate was higher (p = 0.0005) post-simulation vs. baseline. Participants had a median (range) of 2.0 (0.0–10.0) minor PPE breaches, 2.0 (0.0–6.0) near-miss incidents, and 2.0 (0.0–6.0) health symptoms and concerns. There were eight health-assessment triggers in five participants, of whom four were in hot conditions. We terminated the simulation of two participants in hot conditions due to thermal discomfort. In summary, study tasks were suitable for physician participants, but they require redesign to match nurses’ expertise for the subsequent randomized phase of the study. One-quarter of participants had a health-assessment trigger. This research model may be useful in future training and research regarding clinical care for patients with highly infectious pathogens in austere settings. Full article
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
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Figure 1

Figure 1
<p>Layout of the simulated Ebola Treatment Unit (ETU). The red zone was divided into the suspect ward (2 beds for suspected Ebola Virus Disease (EVD) patients) and the confirmed ward (1 bed for a confirmed EVD patient), delineated by red and yellow marking tape on the floor. Participants moved unidirectionally from the green zone to red zone, and from the suspected ward (with 2 patients requiring PIV and MLC) to the confirmed ward (with 1 patient requiring ETI) within the red zone. The supply stations in the red zone contained extra supplies for the 3 tasks; additional clean supplies were stored in a green zone supply station. The climate-controlled chamber had only 1 door; in an actual ETU, the entrance to the green zone and the exit from the red zone would be separated. PIV, peripheral IV; MLC, midline catheter; ETI, endotracheal intubation.</p> Full article ">Figure 2
<p>Participant in personal protective equipment (PPE) inserting peripheral intravenous catheter (top left) and midline catheter (bottom left) and performing endotracheal intubation (right).</p> Full article ">Figure 3
<p>Boxplots showing median percentage (1st and 3rd quartiles) of completed tasks for each procedure for all participants (<span class="html-italic">n</span> = 18, left pane), nurses (<span class="html-italic">n</span> = 5, middle panel), and physicians (<span class="html-italic">n</span> = 13, right panel). ETI and doffing had <span class="html-italic">n</span> = 17 (overall) and <span class="html-italic">n</span> = 12 (physicians). PIV, peripheral IV; MLC, midline catheter; ETI, endotracheal intubation.</p> Full article ">Figure 4
<p>Comparison of the mean percentages of completed tasks between the hot (<span class="html-italic">n</span> = 10, red bars) and thermo-neutral (<span class="html-italic">n</span> = 8, blue bars) conditions. Data are missing for one participant for ETI and doffing (hot condition). Differences were non-significant for donning (<span class="html-italic">p</span> = 0.14), midline catheter (MLC) insertion (<span class="html-italic">p</span> = 0.46), endotracheal intubation (ETI) (<span class="html-italic">p</span> = 0.60), and doffing (<span class="html-italic">p</span> = 0.19) and significant for peripheral IV (PIV) insertion (<span class="html-italic">p</span> = 0.015).</p> Full article ">Figure 5
<p>Changes in medians of systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) in both hot (solid lines) and thermo-neutral (dotted lines) conditions at seven time points throughout the simulation. Tasks included peripheral intravenous catheter insertion (PIV), midline catheter insertion (MLC), and endotracheal intubation (ETI). The only significant difference in vital signs between hot and thermo-neutral conditions was for HR during endotracheal intubation, denoted by the star (<span class="html-italic">p</span> = 0.029).</p> Full article ">
8 pages, 1548 KiB  
Article
Modeling Challenges of Ebola Virus–Host Dynamics during Infection and Treatment
by Daniel S. Chertow, Louis Shekhtman, Yoav Lurie, Richard T. Davey, Theo Heller and Harel Dahari
Viruses 2020, 12(1), 106; https://doi.org/10.3390/v12010106 - 16 Jan 2020
Cited by 6 | Viewed by 3571
Abstract
Mathematical modeling of Ebola virus (EBOV)–host dynamics during infection and treatment in vivo is in its infancy due to few studies with frequent viral kinetic data, lack of approved antiviral therapies, and limited insight into the timing of EBOV infection of cells and [...] Read more.
Mathematical modeling of Ebola virus (EBOV)–host dynamics during infection and treatment in vivo is in its infancy due to few studies with frequent viral kinetic data, lack of approved antiviral therapies, and limited insight into the timing of EBOV infection of cells and tissues throughout the body. Current in-host mathematical models simplify EBOV infection by assuming a single homogeneous compartment of infection. In particular, a recent modeling study assumed the liver as the largest solid organ targeted by EBOV infection and predicted that nearly all cells become refractory to infection within seven days of initial infection without antiviral treatment. We compared our observations of EBOV kinetics in multiple anatomic compartments and hepatocellular injury in a critically ill patient with Ebola virus disease (EVD) with this model’s predictions. We also explored the model’s predictions, with and without antiviral therapy, by recapitulating the model using published inputs and assumptions. Our findings highlight the challenges of modeling EBOV–host dynamics and therapeutic efficacy and emphasize the need for iterative interdisciplinary efforts to refine mathematical models that might advance understanding of EVD pathogenesis and treatment. Full article
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
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Figure 1

Figure 1
<p>Ebola virus RNA levels by compartment during acute and convalescent illness. We measured viral RNA extracted from multiple sample types by EZ-1 quantitative reverse-transcription polymerase chain reaction assay as previously described [<a href="#B6-viruses-12-00106" class="html-bibr">6</a>]. Previously published serum and semen data are included for comparison [<a href="#B5-viruses-12-00106" class="html-bibr">5</a>,<a href="#B6-viruses-12-00106" class="html-bibr">6</a>].</p> Full article ">Figure 2
<p>Aspartate and alanine aminotransferase (AST/ALT) ratio kinetics during acute Ebola virus (<span class="html-italic">n</span> = 1) [<a href="#B5-viruses-12-00106" class="html-bibr">5</a>], or acute hepatitis C virus (<span class="html-italic">n</span> = 28) [<a href="#B8-viruses-12-00106" class="html-bibr">8</a>,<a href="#B9-viruses-12-00106" class="html-bibr">9</a>] infections. Pink shaded region represents first and third AST/ALT ratio quartiles.</p> Full article ">Figure 3
<p>Estimated Ebola virus–host dynamics with and without antiviral treatment. Using parameter values presented in Figure 3 and Table 1 in Madelain et al. [<a href="#B4-viruses-12-00106" class="html-bibr">4</a>], we plot the values of target cells (T), viral load (V), refractory cells (R), productive infected cells (I2), and EBOV specific T cells (E2) with (<b>a</b>,<b>b</b>) zero antiviral efficacy (ε = 0), (<b>c</b>,<b>d</b>) with 50% efficacy (ε = 0.5), and (<b>e</b>,<b>f</b>) with 90% antiviral efficacy (ε = 0.9). Estimates over 50 days are shown in (<b>a</b>,<b>c</b>,<b>e</b>) and a zoom of the first 21 days are shown in (<b>b</b>,<b>d</b>,<b>f</b>). Gray shaded areas indicate duration of antiviral treatment.</p> Full article ">Figure 4
<p>Estimated Ebola virus–host dynamics with antiviral treatment for different periods. In (<b>a</b>) and (<b>b</b>) we again use the parameter values presented in Figure 3 and Table 1 [<a href="#B4-viruses-12-00106" class="html-bibr">4</a>], and plot the values of target cells (T), viral load (V), refractory cells (R), productive infected cells (I2), and EBOV specific T cells (E2). In (<b>a</b>) we show this for treatment ε = 0.9 beginning at day 0 and continuing through day 50, while in (<b>b</b>) we show for treatment beginning at day 7 and continuing through day 50 (gray shaded areas indicate duration of antiviral treatment). In (<b>c</b>,<b>d</b>) we compare the viral load for the case of starting treatment at day 5 and continuing through day 50 for (<b>c</b>) ε = 0.9 and (<b>d</b>) ε = 0.5.</p> Full article ">
29 pages, 5880 KiB  
Article
Characterization of Ebola Virus Disease (EVD) in Rhesus Monkeys for Development of EVD Therapeutics
by Travis Warren, Elizabeth Zumbrun, Jessica M. Weidner, Laura Gomba, Franco Rossi, Roy Bannister, Jacqueline Tarrant, Matthew Reed, Eric Lee, Jo Lynne Raymond, Jay Wells, Joshua Shamblin, Kelly Wetzel, Ginger Donnelly, Sean Van Tongeren, Nicole Lackemeyer, Jesse Steffens, Adrienne Kimmel, Carly Garvey, Holly Bloomfield, Christiana Blair, Bali Singh, Sina Bavari, Tomas Cihlar and Danielle Porteradd Show full author list remove Hide full author list
Viruses 2020, 12(1), 92; https://doi.org/10.3390/v12010092 - 13 Jan 2020
Cited by 16 | Viewed by 4084
Abstract
Recent Ebola virus (EBOV) outbreaks in West Africa and the Democratic Republic of the Congo have highlighted the urgent need for approval of medical countermeasures for treatment and prevention of EBOV disease (EVD). Until recently, when successes were achieved in characterizing the efficacy [...] Read more.
Recent Ebola virus (EBOV) outbreaks in West Africa and the Democratic Republic of the Congo have highlighted the urgent need for approval of medical countermeasures for treatment and prevention of EBOV disease (EVD). Until recently, when successes were achieved in characterizing the efficacy of multiple experimental EVD therapeutics in humans, the only feasible way to obtain data regarding potential clinical benefits of candidate therapeutics was by conducting well-controlled animal studies. Nonclinical studies are likely to continue to be important tools for screening and development of new candidates with improved pharmacological properties. Here, we describe a natural history study to characterize the time course and order of progression of the disease manifestations of EVD in rhesus monkeys. In 12 rhesus monkeys exposed by the intramuscular route to 1000 plaque-forming units of EBOV, multiple endpoints were monitored for 28 days following exposure. The disease progressed rapidly with mortality events occurring 7–10 days after exposure. Key disease manifestations observed consistently across the infected animals included, but were not limited to, viremia, fever, systemic inflammation, coagulopathy, lymphocytolysis, renal tubular necrosis with mineralization, and hepatocellular degeneration and necrosis. Full article
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Kaplan–Meier plot of survival of EBOV-exposed and mock-exposed rhesus macaques.</p> Full article ">Figure 2
<p>Daily maximum responsiveness scores.</p> Full article ">Figure 3
<p>Group mean and individual animal plasma viral RNA: (<b>A</b>) group mean ± SD of plasma viral RNA versus time; and (<b>B</b>) plasma viral RNA concentration in individual EBOV-exposed animals versus time. LOD, limit of detection, Ct = 38.07; LLOQ, lower limit of quantitation = 4.903 log<sub>10</sub> ge/mL. For display and analyses, EBOV RNA values below the LOD were imputed as 3.000 log<sub>10</sub> ge/mL; values above the LOD but below the LLOQ were imputed as 4.903 log<sub>10</sub> ge/mL. Statistical analyses were not performed.</p> Full article ">Figure 4
<p>Telemetry-based body temperature changes in mock- vs. EBOV-exposed animals. (<b>A</b>) Group mean of daily maximum change from baseline body temperature. Error bars represent SD. X-axis has been truncated to highlight responses occurring from the time of mock or virus exposure events through the acute disease phase. No statistical analyses were performed. Representative mock-exposed animal absolute body temperature (<b>B</b>) and change from baseline (running 30-min average) (<b>C</b>). Representative EBOV-exposed animal absolute body temperature (<b>D</b>) and change from baseline (running 30-min average) (<b>E</b>). (<b>C</b>,<b>E</b>) Values −3 SD (<span style="color:#00FF00">♦</span>) or +3 SD (<span style="color:#FF0000">♦</span>) from baseline are statistically significant; values &lt; 3 SD (<span style="color:#0000FF">♦</span>) are not significant.</p> Full article ">Figure 5
<p>Group means of 12-h light period activity (movement in cage). Twelve-hour light period activity monitoring by telemetry occurred from 06:00 to 18:00. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.001. <span class="html-italic">p</span>-values are indicated for comparison of change-from-baseline values in mock- vs. EBOV-exposed animals on the indicated study day.</p> Full article ">Figure 6
<p>Exposure to IM EBOV in rhesus macaques produces clinical pathology alterations indicative of systemic inflammatory responses. Group mean ± SD of: C-reactive protein (<b>A</b>); fibrinogen (<b>B</b>); albumin (<b>C</b>); neutrophils (<b>D</b>); and monocytes (<b>E</b>). X-axes are truncated to highlight responses occurring from the first sampling point through the acute disease phase. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.001. <span class="html-italic">p</span>-values are indicated for comparison of change-from-baseline values in mock- vs. EBOV-exposed animals on the indicated study day. C-reactive protein values &lt; LLOQ (LLOQ = 5 mg/L) were assigned a value of 4 mg/L for display and analysis.</p> Full article ">Figure 7
<p>Exposure to IM EBOV in rhesus macaques produces clinical pathology and histological alterations indicative of coagulopathy, including disseminated intravascular coagulopathy. Group means ± SD of: platelets (<b>A</b>); prothrombin time (<b>B</b>); activated partial thromboplastin time (<b>C</b>); d-dimer (<b>D</b>); and antithrombin (<b>E</b>). X-axes are truncated to highlight responses occurring from the first sampling point through the acute disease phase. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.001. <span class="html-italic">p</span>-values are indicated for comparison of change-from-baseline values in mock- vs. EBOV-exposed animals on the indicated study day. (<b>F)</b> Small intestine, duodenal mucosa showing numerous intravascular fibrin thrombi (FT, two representative examples noted).</p> Full article ">Figure 8
<p>Exposure to IM EBOV in rhesus macaques produces clinical pathology alterations indicative of fluid loss. Group means ± SD of: sodium (<b>A</b>); chloride (<b>B</b>); potassium (<b>C</b>); blood urea nitrogen (<b>D</b>); creatinine (<b>E</b>); and carbon dioxide (<b>F</b>). X-axes are truncated to highlight responses occurring from the first sampling point through the acute disease phase. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.001. <span class="html-italic">p</span>-values are indicated for comparison of change-from-baseline values in mock- vs. EBOV-exposed animals on the indicated study day.</p> Full article ">Figure 9
<p>Exposure to IM EBOV in rhesus macaques produces clinical pathology alterations consistent with hepatocellular damage and necrosis and other disease conditions. Group means ± SD of: aspartate aminotransferase (AST) (<b>A</b>); alanine aminotransferase (ALT) (<b>B</b>); alkaline phosphatase (ALP) (<b>C</b>); gamma glutamyl transferase (GGT) (<b>D</b>); creatine kinase (<b>E</b>); and glucose (<b>F</b>). X-axes are truncated to highlight responses occurring from the first sampling point through the acute disease phase. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.001. <span class="html-italic">p</span>-values are indicated for comparison of change-from-baseline values in mock- vs. EBOV-exposed animals on the indicated study day.</p> Full article ">Figure 10
<p>Salient microscopic findings in rhesus macaques exposed to IM EBOV. (<b>A</b>) Small intestine, duodenum: Diffuse hemorrhage expanding the mucosa and submucosa. (<b>B</b>) Spleen, white pulp: Lymphocyte depletion with lymphocytolysis (asterisk) and fibrin deposition (arrow) in the adjacent red pulp; (<b>C</b>) Kidney tubules: Necrosis of the tubular epithelium (arrows) with intratubular mineralization (asterisk). (<b>D</b>) Liver: An area containing hepatocellular degeneration (arrow heads) and necrosis (arrows).</p> Full article ">Figure 11
<p>Schematic showing generalized progression of acute EVD following exposure to IM/EBOV in rhesus macaques. The day of EBOV exposure is designated Study Day 1.</p> Full article ">Figure A1
<p>Clinical signs, viremia, and clinical pathology alterations in rhesus macaques exposed to IM EBOV. Data represent the mean for EBOV-exposed animals. Mean responsiveness score was derived from the individual animal maximum daily responsiveness score. The 12-h activity was derived from individual animal physical movements assessed via telemetry, averaged over the 12-h interval corresponding to the animal room light cycle (dark-cycle activity is not shown). For plasma viral RNA concentrations, EBOV RNA values below the LOD were imputed as 3.000 log<sub>10</sub> ge/mL; values above the LOD but below the LLOQ were imputed as 4.903 log<sub>10</sub> ge/mL. Temperature represents 30-min body temperature averages. X-axes are truncated to highlight responses occurring from the first sampling point through the acute disease phase. Error bars were omitted for clarity. The horizontal mortality bar indicates the range of timing in which animals succumbed.</p> Full article ">
17 pages, 1454 KiB  
Communication
Serum LPS Associated with Hantavirus and Dengue Disease Severity in Barbados
by Kirk Osmond Douglas, Thelma Alafia Samuels and Marquita Gittens-St. Hilaire
Viruses 2019, 11(9), 838; https://doi.org/10.3390/v11090838 - 9 Sep 2019
Cited by 7 | Viewed by 3529
Abstract
Hantavirus and dengue virus (DENV) infections are caused by RNA viruses which infect immune systems’ cells including monocytes, macrophages and dendritic cells and occur year-round in Barbados. A retrospective serological study (2008–2015) was conducted on hantavirus and dengue patient sera confirmed by IgM [...] Read more.
Hantavirus and dengue virus (DENV) infections are caused by RNA viruses which infect immune systems’ cells including monocytes, macrophages and dendritic cells and occur year-round in Barbados. A retrospective serological study (2008–2015) was conducted on hantavirus and dengue patient sera confirmed by IgM and IgG ELISA, NS1 and RT-PCR using Limulus amoebocyte lysate (LAL) kinetic turbidimetric method to determine serum endotoxin levels. Hantavirus patients were categorized into two groups, namely (a) hospitalized and (b) non-hospitalized. Dengue patients were categorized into 3 groups using 2009 WHO dengue guidelines (a) severe dengue (SD), (b) hospitalized non-severe dengue (non-SD) and (c) non-hospitalized non-SD. Statistical analyses were conducted to determine the association of endotoxin levels with hantavirus disease severity based on hospitalization and dengue disease severity. Serum endotoxin levels are associated with hantavirus disease severity and hospitalization and dengue disease severity (p < 0.01). Similar studies have found an association of serum endotoxin levels with dengue disease severity but never with hantavirus infection. Co-detection of hantavirus- and DENV-specific IgM in some patients were observed with elevated serum endotoxin levels. In addition, previous studies observed hantavirus replication in the gut of patients, gastrointestinal tract as a possible entry route of infection and evidence of microbial translocation and its impact on hantavirus disease severity. A significant correlation of serum endotoxin and hantavirus disease severity and hospitalization in hantavirus infected patients is reported for the first time ever. In addition, serum endotoxin levels correlated with dengue disease severity. This study adds further support to the role of endotoxin in both hantavirus and dengue virus infection and disease severity and its role as a possible therapeutic target for viral haemorrhagic fevers (VHFs). Full article
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
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Figure 1

Figure 1
<p>Flow chart of the investigation of serum endotoxin and hantavirus disease severity.</p> Full article ">Figure 2
<p>Investigation of serum endotoxin and dengue disease severity method flowchart.</p> Full article ">Figure 3
<p>Serum endotoxin levels of SD, hospitalised non-SD and non-hospitalised non-SD patients in Barbados.</p> Full article ">
9 pages, 446 KiB  
Article
A Methodology for Determining Which Diseases Warrant Care in a High-Level Containment Care Unit
by Theodore J. Cieslak, Jocelyn J. Herstein, Mark G. Kortepeter and Angela L. Hewlett
Viruses 2019, 11(9), 773; https://doi.org/10.3390/v11090773 - 22 Aug 2019
Cited by 6 | Viewed by 3518
Abstract
Although the concept of high-level containment care (HLCC or ‘biocontainment’), dates back to 1969, the 2014–2016 outbreak of Ebola virus disease (EVD) brought with it a renewed emphasis on the use of specialized HLCC units in the care of patients with EVD. Employment [...] Read more.
Although the concept of high-level containment care (HLCC or ‘biocontainment’), dates back to 1969, the 2014–2016 outbreak of Ebola virus disease (EVD) brought with it a renewed emphasis on the use of specialized HLCC units in the care of patients with EVD. Employment of these units in the United States and Western Europe resulted in a significant decrease in mortality compared to traditional management in field settings. Moreover, this employment appeared to significantly lessen the risk of nosocomial transmission of disease; no secondary cases occurred among healthcare workers in these units. While many now accept the wisdom of utilizing HLCC units and principles in the management of EVD (and, presumably, of other transmissible and highly hazardous viral hemorrhagic fevers, such as those caused by Marburg and Lassa viruses), no consensus exists regarding additional diseases that might warrant HLCC. We propose here a construct designed to make such determinations for existing and newly discovered diseases. The construct examines infectivity (as measured by the infectious dose needed to infect 50% of a given population (ID50)), communicability (as measured by the reproductive number (R0)), and hazard (as measured by morbidity and mortality). Diseases fulfilling all three criteria (i.e., those that are highly infectious, communicable, and highly hazardous) are considered candidates for HLCC management if they also meet a fourth criterion, namely that they lack effective and available licensed countermeasures. Full article
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
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Figure 1

Figure 1
<p>Construct used in determining diseases warranting care in a high-level containment care unit.</p> Full article ">
19 pages, 2825 KiB  
Article
Characterization of Biomarker Levels in Crimean–Congo Hemorrhagic Fever and Hantavirus Fever with Renal Syndrome
by Miša Korva, Katarina Resman Rus, Miša Pavletič, Ana Saksida, Nataša Knap, Mateja Jelovšek, Katja Strašek Smrdel, Xhevat Jakupi, Isme Humolli, Jusuf Dedushaj, Miroslav Petrovec and Tatjana Avšič-Županc
Viruses 2019, 11(8), 686; https://doi.org/10.3390/v11080686 - 26 Jul 2019
Cited by 24 | Viewed by 3696
Abstract
Hemorrhagic fever with renal syndrome (HFRS) and Crimean-Congo hemorrhagic fever (CCHF) are important viral hemorrhagic fevers (VHF), especially in the Balkan region. Infections with Dobrava or Puumala orthohantavirus and Crimean-Congo hemorrhagic fever orthonairovirus can vary from a mild, nonspecific febrile illness, to a [...] Read more.
Hemorrhagic fever with renal syndrome (HFRS) and Crimean-Congo hemorrhagic fever (CCHF) are important viral hemorrhagic fevers (VHF), especially in the Balkan region. Infections with Dobrava or Puumala orthohantavirus and Crimean-Congo hemorrhagic fever orthonairovirus can vary from a mild, nonspecific febrile illness, to a severe disease with a fatal outcome. The pathogenesis of both diseases is poorly understood, but it has been suggested that a host’s immune mechanism might influence the pathogenesis of the diseases and survival. The aim of our study is to characterize cytokine response in patients with VHF in association with the disease progression and viral load. Forty soluble mediators of the immune response, coagulation, and endothelial dysfunction were measured in acute serum samples in 100 HFRS patients and 70 CCHF patients. HFRS and CCHF patients had significantly increased levels of IL-6, IL-12p70, IP-10, INF-γ, TNF-α, GM-CSF, MCP-3, and MIP-1b in comparison to the control group. Interestingly, HFRS patients had higher concentrations of serum MIP-1α, MIP-1β, which promote activation of macrophages and NK cells. HFRS patients had increased concentrations of IFN-γ and TNF-α, while CCHF patients had significantly higher concentrations of IFN-α and IL-8. In both, CCHF and HFRS patients’ viral load significantly correlated with IP-10. Patients with fatal outcome had significantly elevated concentrations of IL-6, IFN-α2 and MIP-1α, while GRO-α, chemokine related to activation of neutrophils and basophils, was downregulated. Our study provided a comprehensive characterization of biomarkers released in the acute stages of CCHF and HFRS. Full article
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
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<p>The cytokine and chemokine concentrations with significant differences in HFRS patients (DOBV, <span class="html-italic">n</span> = 50; PUUV, <span class="html-italic">n</span> = 50) in comparison to control group (<span class="html-italic">n</span> = 30). The samples were obtained median 6 days after the onset of symptoms. The statistically significant differences are marked with * (<span class="html-italic">p</span> &lt; 0.05). ns= not statistically significant. The boxes represents medians with interquartile ranges; the whiskers depict minimum and maximum values (range). Identified outliers are not included in the figures above: IFN-γ (DOBV <span class="html-italic">n</span> = 4; PUUV <span class="html-italic">n</span> = 3), MCP-3 (DOBV <span class="html-italic">n</span> = 6; PUUV <span class="html-italic">n</span> = 5), IL-4 (DOBV <span class="html-italic">n</span> = 5; PUUV <span class="html-italic">n</span> = 5), MIP-1α (DOBV <span class="html-italic">n</span> = 3; PUUV <span class="html-italic">n</span> = 8), IL-8 (DOBV <span class="html-italic">n</span> = 7; PUUV <span class="html-italic">n</span> = 4), VEGF-A (PUUV <span class="html-italic">n</span> = 6) and Fibrinogen (DOBV <span class="html-italic">n</span> = 8; PUUV <span class="html-italic">n</span> = 2).</p> Full article ">Figure 2
<p>The cytokine and chemokine concentrations with significant differences in patients infected with DOBV (severe <span class="html-italic">n</span> = 25; mild <span class="html-italic">n</span> = 25) or PUUV (severe <span class="html-italic">n</span> = 25; mild <span class="html-italic">n</span> = 25), with regard to the disease progression and outcome. The statistically significant differences are marked with * (<span class="html-italic">p</span> &lt; 0.05). ns= not statistically significant. The boxes represents medians with interquartile ranges; the whiskers depict minimum and maximum values (range). Identified outliers are not included in the figures above: IL-6 (DOBV severe <span class="html-italic">n</span> = 4; DOBV mild <span class="html-italic">n</span> = 1; PUUV severe <span class="html-italic">n</span> = 1; PUUV mild <span class="html-italic">n</span> = 4), MCP-1 (DOBV severe <span class="html-italic">n</span> = 1; DOBV mild <span class="html-italic">n</span> = 4; PUUV severe <span class="html-italic">n</span> = 5; PUUV mild <span class="html-italic">n</span> = 4), IL-8 (DOBV severe <span class="html-italic">n</span> = 5; DOBV mild <span class="html-italic">n</span> = 3), D-dimer (PUUV mild <span class="html-italic">n</span> = 3), Fibrinogen (DOBV severe <span class="html-italic">n</span> = 5; DOBV mild <span class="html-italic">n</span> = 1; PUUV mild <span class="html-italic">n</span> = 2).</p> Full article ">Figure 3
<p>The cytokine and chemokine concentrations with significant differences in CCHF patients (<span class="html-italic">n</span> = 70) in comparison to control group (<span class="html-italic">n</span> = 30). The samples were obtained median six days after the onset of symptoms. The statistically significant differences are marked with * (<span class="html-italic">p</span> &lt; 0.05). ns= not statistically significant. The boxes represents medians with interquartile ranges; the whiskers depict minimum and maximum values (range). Identified outliers are not included in the figures above: GM-CSF (CCHF <span class="html-italic">n</span> = 5), IFN-α (CCHF <span class="html-italic">n</span> = 5), IFNγ (CCHF <span class="html-italic">n</span> = 1), GRO-α (CCHF, <span class="html-italic">n</span> = 6), IL-10 (CCHF <span class="html-italic">n</span> = 5), MCP-3 (CCHF <span class="html-italic">n</span> = 8), IL-4 (CCHF <span class="html-italic">n</span> = 8), IL-6 (CCHF <span class="html-italic">n</span> = 1), MCP-1 (CCHF <span class="html-italic">n</span> = 1), MIP-1β (CCHF <span class="html-italic">n</span> = 7), M-CSF (CCHF <span class="html-italic">n</span> = 1), VEGF-A (CCHF <span class="html-italic">n</span> = 6), TM (CCHF <span class="html-italic">n</span> = 5).</p> Full article ">Figure 4
<p>The cytokine and chemokine concentrations with significant differences in CCHF patients, with regard to the disease progression and outcome (moderate <span class="html-italic">n</span> = 24; severe <span class="html-italic">n</span> = 18; fatal <span class="html-italic">n</span> = 14). The statistically significant differences are marked with * (<span class="html-italic">p</span> &lt; 0.05). ns= not statistically significant. The boxes represents medians with interquartile ranges; the whiskers depict minimum and maximum values (range). Identified outliers are not included in the figures above: GM-CSF (moderate <span class="html-italic">n</span> = 3; severe <span class="html-italic">n</span> = 1), IFN-α (moderate <span class="html-italic">n</span> = 2; fatal <span class="html-italic">n</span> = 1), GRO-α (moderate <span class="html-italic">n</span> = 2; severe <span class="html-italic">n</span> = 3), IL-10 (moderate <span class="html-italic">n</span> = 4; fatal <span class="html-italic">n</span> = 1), IL-4 (moderate <span class="html-italic">n</span> = 3; severe <span class="html-italic">n</span> = 2), IL-6 (moderate <span class="html-italic">n</span> = 7; severe <span class="html-italic">n</span> = 3; fatal <span class="html-italic">n</span> = 1), MIP-1α (moderate <span class="html-italic">n</span> = 6; severe <span class="html-italic">n</span> = 4; fatal <span class="html-italic">n</span> = 2).</p> Full article ">Figure 5
<p>The cytokine and chemokine concentrations with significant differences between in HFRS (<span class="html-italic">n</span> = 100) and CCHF (<span class="html-italic">n</span> = 70) patients. The statistically significant differences are marked with * (<span class="html-italic">p</span> &lt; 0.05). ns= not statistically significant. The boxes represents medians with interquartile ranges; the whiskers depict minimum and maximum values (range). Identified outliers are not included in the figures above: GM-CSF (HFRS <span class="html-italic">n</span> = 8; CCHF <span class="html-italic">n</span> = 5), IFN-α2 (HFRS <span class="html-italic">n</span> = 4; CCHF <span class="html-italic">n</span> = 5), IFN-γ (HFRS <span class="html-italic">n</span> = 8; CCHF <span class="html-italic">n</span> = 1), IL-10 (HFRS <span class="html-italic">n</span> = 8; CCHF <span class="html-italic">n</span> = 5), TNF-α (HFRS <span class="html-italic">n</span> = 6; CCHF <span class="html-italic">n</span> = 3), Angiopoetin-2 (HFRS <span class="html-italic">n</span> = 9; CCHF <span class="html-italic">n</span> = 1), D-dimer (HFRS <span class="html-italic">n</span> = 1; CCHF <span class="html-italic">n</span> = 4), P-selectin (HFRS <span class="html-italic">n</span> = 4; CCHF <span class="html-italic">n</span> = 7), pCAM-1 (HFRS <span class="html-italic">n</span> = 4; CCHF <span class="html-italic">n</span> = 2), TF (HFRS <span class="html-italic">n</span> = 6; CCHF <span class="html-italic">n</span> = 8), TM (HFRS <span class="html-italic">n</span> = 2; CCHF <span class="html-italic">n</span> = 5).</p> Full article ">Figure 6
<p>Correlation between biomarker IP-10 and viral loads of HFRS patients (<b>A</b>), CCHF patients (<b>B</b>), patients infected with DOBV (<b>C</b>) and patients infected with PUUV (<b>D</b>). Nonparametric two-tailed Spearman correlation test with 95% confidence interval was used.</p> Full article ">
18 pages, 2486 KiB  
Article
Evaluation of Diagnostic Performance of Three Indirect Enzyme-Linked Immunosorbent Assays for the Detection of IgG Antibodies to Ebola Virus in Human Sera
by Janusz T. Paweska, Naazneen Moolla, Nadia Storm, Veerle Msimang, Ousman Conteh, Jacqueline Weyer and Petrus Jansen van Vuren
Viruses 2019, 11(8), 678; https://doi.org/10.3390/v11080678 - 24 Jul 2019
Cited by 3 | Viewed by 3506
Abstract
Filovirus serological diagnosis and epidemiological investigations are hampered due to the unavailability of validated immunoassays. Diagnostic performance of three indirect enzyme-linked immunosorbent assays (I-ELISA) was evaluated for the detection of IgG antibody to Ebola virus (EBOV) in human sera. One I-ELISA was based [...] Read more.
Filovirus serological diagnosis and epidemiological investigations are hampered due to the unavailability of validated immunoassays. Diagnostic performance of three indirect enzyme-linked immunosorbent assays (I-ELISA) was evaluated for the detection of IgG antibody to Ebola virus (EBOV) in human sera. One I-ELISA was based on a whole EBOV antigen (WAg) and two utilized recombinant nucleocapsid (NP) and glycoproteins (GP), respectively. Validation data sets derived from individual sera collected in South Africa (SA), representing an EBOV non-endemic country, and from sera collected during an Ebola disease (EBOD) outbreak in Sierra Leone (SL), were categorized according to the compounded results of the three I-ELISAs and real time reverse-transcription polymerase chain reaction (RT-PCR). At the cut-off values selected at 95% accuracy level by the two-graph receiver operating characteristic analysis, specificity in the SA EBOV negative serum panel (n = 273) ranged from 98.17% (GP ELISA) to 99.27% (WAg ELISA). Diagnostic specificity in the SL EBOV negative panel (n = 676) was 100% by the three ELISAs. The diagnostic sensitivity in 423 RT-PCR confirmed EBOD patients was dependent on the time when the serum was collected after onset of disease. It significantly increased 2 weeks post-onset, reaching 100% sensitivity by WAg and NP and 98.1% by GP I-ELISA. Full article
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
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<p>Distribution of percentage positivity (PP) values in South African (SA) and Sierra Leonean (SL) Ebola virus (EBOV) immunoglobulin G (IgG) negative human sera and selection of cut-off values for (<b>A</b>) the whole antigen (WAg), (<b>B</b>) nucleocapsid protein (NP) and (<b>C</b>) glycoprotein (GP) based ELISAs. Cut-off value for each assay was calculated as mean plus three standard deviations of ELISA PP (percentage positivity of internal positive control serum) values recorded by each test in 273 SA and 676 SL EVD negative sera, respectively.</p> Full article ">Figure 1 Cont.
<p>Distribution of percentage positivity (PP) values in South African (SA) and Sierra Leonean (SL) Ebola virus (EBOV) immunoglobulin G (IgG) negative human sera and selection of cut-off values for (<b>A</b>) the whole antigen (WAg), (<b>B</b>) nucleocapsid protein (NP) and (<b>C</b>) glycoprotein (GP) based ELISAs. Cut-off value for each assay was calculated as mean plus three standard deviations of ELISA PP (percentage positivity of internal positive control serum) values recorded by each test in 273 SA and 676 SL EVD negative sera, respectively.</p> Full article ">Figure 2
<p>Optimization of cut-offs for Wag (<b>A</b>), nucleocapsid (<b>B</b>) and glycoprotein (<b>C</b>) ELISAs using the two-graph receiver operating characteristic analysis (TG-ROC). The insertion point of the sensitivity (Se, smooth line) and specificity (Sp, dashed line) graphs represents a cut-off PP value (13.53, 16.44 and 26.28, respectively) at which the highest and equivalent test parameters (Se = Sp) are achieved at 95% accuracy level. Using the misclassification cost term (MCT) option of the TG-ROC, at these cut-of values, the overall misclassification costs for WAg (<b>A1</b>), NP (<b>B1</b>), and GP ELISA (<b>C1</b>) become minimal (0.0003, 0.0069, 0.0001, respectively) under assumption of 50% disease prevalence and equal costs of false-positive and false-negative results. The two MCT curves represent values based on non-parametric (dashed line) or parametric (smooth line) estimates of Se and Sp derived from data sets analyzed. Optimization of cut-off values was based on the non-parametric program option due to departure from a normal distribution of data analyzed. Cut-off values are expressed as percentage positivity (PP) of an internal positive serum control.</p> Full article ">Figure 2 Cont.
<p>Optimization of cut-offs for Wag (<b>A</b>), nucleocapsid (<b>B</b>) and glycoprotein (<b>C</b>) ELISAs using the two-graph receiver operating characteristic analysis (TG-ROC). The insertion point of the sensitivity (Se, smooth line) and specificity (Sp, dashed line) graphs represents a cut-off PP value (13.53, 16.44 and 26.28, respectively) at which the highest and equivalent test parameters (Se = Sp) are achieved at 95% accuracy level. Using the misclassification cost term (MCT) option of the TG-ROC, at these cut-of values, the overall misclassification costs for WAg (<b>A1</b>), NP (<b>B1</b>), and GP ELISA (<b>C1</b>) become minimal (0.0003, 0.0069, 0.0001, respectively) under assumption of 50% disease prevalence and equal costs of false-positive and false-negative results. The two MCT curves represent values based on non-parametric (dashed line) or parametric (smooth line) estimates of Se and Sp derived from data sets analyzed. Optimization of cut-off values was based on the non-parametric program option due to departure from a normal distribution of data analyzed. Cut-off values are expressed as percentage positivity (PP) of an internal positive serum control.</p> Full article ">Figure 3
<p>Mean IgG responses in 423 Ebola disease patients measured by a whole antigen (WAg), nucleocapsid (NP), and glycoprotein (GP) indirect ELISAs at different time post disease onset.</p> Full article ">Figure 4
<p>Dose-response kinetics of a positive EBOV IgG human serum before and after different inactivation procedures measured by a whole antigen (Wag), (<b>A</b>); nucleocapsid (NP), (<b>B</b>); and glycoprotein (GP), (<b>C</b>) indirect ELISA. <sup>1</sup> Percent positivity of internal positive control serum.</p> Full article ">Figure 4 Cont.
<p>Dose-response kinetics of a positive EBOV IgG human serum before and after different inactivation procedures measured by a whole antigen (Wag), (<b>A</b>); nucleocapsid (NP), (<b>B</b>); and glycoprotein (GP), (<b>C</b>) indirect ELISA. <sup>1</sup> Percent positivity of internal positive control serum.</p> Full article ">
11 pages, 1050 KiB  
Article
Haemostatic Changes in Five Patients Infected with Ebola Virus
by Sophie J. Smither, Lyn M. O’Brien, Lin Eastaugh, Tom Woolley, Mark Lever, Tom Fletcher, Kiran Parmar, Beverley J. Hunt, Sarah Watts and Emrys Kirkman
Viruses 2019, 11(7), 647; https://doi.org/10.3390/v11070647 - 15 Jul 2019
Cited by 26 | Viewed by 3961
Abstract
Knowledge on haemostatic changes in humans infected with Ebola virus is limited due to safety concerns and access to patient samples. Ethical approval was obtained to collect plasma samples from patients in Sierra Leone infected with Ebola virus over time and samples were [...] Read more.
Knowledge on haemostatic changes in humans infected with Ebola virus is limited due to safety concerns and access to patient samples. Ethical approval was obtained to collect plasma samples from patients in Sierra Leone infected with Ebola virus over time and samples were analysed for clotting time, fibrinogen, and D-dimer levels. Plasma from healthy volunteers was also collected by two methods to determine effect of centrifugation on test results as blood collected in Sierra Leone was not centrifuged. Collecting plasma without centrifugation only affected D-dimer values. Patients with Ebola virus disease had higher PT and APTT and D-dimer values than healthy humans with plasma collected in the same manner. Fibrinogen levels in patients with Ebola virus disease were normal or lower than values measured in healthy people. Clotting times and D-dimer levels were elevated during infection with Ebola virus but return to normal over time in patients that survived and therefore could be considered prognostic. Informative data can be obtained from plasma collected without centrifugation which could improve patient monitoring in hazardous environments. Full article
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
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<p>Effect of collection method on four haemostatic parameters. Naïve blood samples were collected from healthy UK volunteers and analysed for Prothrombin Time (PT), Activated Partial Thromboplastin Time (APTT), fibrinogen, and D-dimer amounts. Plasma was obtained by centrifugation (standard method) or by non-centrifugation where blood was left to separate over time. Non-centrifuged plasma was collected for comparison with Ebola virus-infected plasma samples collected without centrifugation. Each test was run in duplicate and both values are shown. For some centrifuged samples, multiple aliquots from the same donor were analysed on different occasions, each individual result is also shown. Mean and SEM (coloured lines and bars) are shown for each data set. Unpaired <span class="html-italic">t</span>-tests were performed to compare the results from the two collection methods.</p> Full article ">Figure 2
<p>Changes in haemostasis parameters over time in Ebola virus-infected individuals. Mean values of Prothrombin Time (PT), Activated Partial Thromboplastin Time (APTT) (top row) and fibrinogen, and D-Dimer values (bottom row) from plasma samples collected without centrifugation from five patients are shown. Each time-point was tested in at least duplicate and mean plotted. Each patient is represented by a different colour and symbol and days of sampling post-symptom onset were different for each patient. Grey shaded area indicates the range of values for each test obtained from naïve ‘normal’ human donor samples also collected without centrifugation (<a href="#viruses-11-00647-f001" class="html-fig">Figure 1</a>). Dashed line is the mean value from the un-centrifuged non-infected samples and the dotted line is the value of the un-centrifuged mean + 3 standard deviations (for fibrinogen—3 standard deviations also shown with a second dotted line). If data distribution is approximately normal, then 99.7 % lies within three standard deviations. One PT result and several D-dimer results were out of range and are plotted at the upper limit of the test and indicated as such for each data set.</p> Full article ">
18 pages, 4458 KiB  
Article
Autophagy Promotes Infectious Particle Production of Mopeia and Lassa Viruses
by Nicolas Baillet, Sophie Krieger, Alexandra Journeaux, Valérie Caro, Frédéric Tangy, Pierre-Olivier Vidalain and Sylvain Baize
Viruses 2019, 11(3), 293; https://doi.org/10.3390/v11030293 - 23 Mar 2019
Cited by 12 | Viewed by 4255
Abstract
Lassa virus (LASV) and Mopeia virus (MOPV) are two closely related Old-World mammarenaviruses. LASV causes severe hemorrhagic fever with high mortality in humans, whereas no case of MOPV infection has been reported. Comparing MOPV and LASV is a powerful strategy to unravel pathogenic [...] Read more.
Lassa virus (LASV) and Mopeia virus (MOPV) are two closely related Old-World mammarenaviruses. LASV causes severe hemorrhagic fever with high mortality in humans, whereas no case of MOPV infection has been reported. Comparing MOPV and LASV is a powerful strategy to unravel pathogenic mechanisms that occur during the course of pathogenic arenavirus infection. We used a yeast two-hybrid approach to identify cell partners of MOPV and LASV Z matrix protein in which two autophagy adaptors were identified, NDP52 and TAX1BP1. Autophagy has emerged as an important cellular defense mechanism against viral infections but its role during arenavirus infection has not been shown. Here, we demonstrate that autophagy is transiently induced by MOPV, but not LASV, in infected cells two days after infection. Impairment of the early steps of autophagy significantly decreased the production of MOPV and LASV infectious particles, whereas a blockade of the degradative steps impaired only MOPV infectious particle production. Our study provides insights into the role played by autophagy during MOPV and LASV infection and suggests that this process could partially explain their different pathogenicity. Full article
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
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<p>Confirmation of the interaction between MOPV and LASV Z protein and the host cell proteins NDP52 and TAX1BP1. (<b>A</b>) images of plates with “gap-repair colonies” (performed in duplicate). Clones were plated onto selective media (-L-W-H + 3AT) and left to grow for two weeks; (<b>B</b>) extracts from 293T cells cotransfected with the indicated expressing plasmids for 15 h were immunoprecipitated (IP) with FLAG magnetic beads. Exogenous eGFP-NDP52 and eGFP-TAX1BP1 were detected by Western blotting (<span class="html-italic">n</span> = 3 independent experiments). (<b>C</b>,<b>D</b>) HeLa cells were cotransfected with the indicated plasmids for 15 h and fixed for confocal microscopy. Exogenous eGFP-NDP52 and eGFP-TAX1BP1 are shown in green and the Z-mCherry viral proteins in red (<span class="html-italic">n</span> = 3 independent experiments). All images were taken on a confocal Zeiss LSM 510 with an Axioscope 63× oil immersion lens objective. Scale bar represents 30 µm.</p> Full article ">Figure 2
<p>NDP52 and TAX1BP1 are neither involved in the replication nor the release of MOPV or LASV infectious particles. (<b>A</b>) HeLa cells were transfected with the indicated siRNA 72 h before analysis of silencing efficiency by Western blotting (<span class="html-italic">n</span> = 4 independent experiments). (<b>B</b>–<b>D</b>) the same cells as in (A) were then infected with LASV or MOPV with an MOI of 0.1 for 1 h before being maintained for three days at 37 °C. Viral RNA was then extracted from the cells and supernatants for quantification by RTqPCR. Infectious particles from the supernatants were also titrated on Vero cells. The error bars represent the standard error of the means from four independent experiments. * indicates <span class="html-italic">p</span> &lt; 0.05, as determined by the Mann–Whitney test.</p> Full article ">Figure 3
<p>MOPV, but not LASV, induces transient autophagy in HeLa cells. (<b>A</b>) GFP-LC3 HeLa cells were treated for 2 h with CQ at a final concentration of 50 µM before transfection with the indicated plasmids for 15 h. Cells were then fixed and stained with a primary mouse anti-FLAG antibody and a secondary anti-mouse coupled Alexa555 antibody before observation by confocal microscopy (<span class="html-italic">n</span> = 3 independent experiments). All images were acquired using a confocal Zeiss LSM 510 microscope with an Axioscope 63× oil immersion lens objective. The scale bar represents 20 µm. (<b>B</b>) HeLa cells were mock infected or infected with LASV or MOPV at an MOI of 2. Cells were harvested at the indicated timepoints for p62 analysis by Western blotting. The graph represents the intensity of p62 over actin expression normalized to the MOCK-infected condition at d0 (not represented on the graph). The error bars represent the standard error of the means from five and four independent experiments for MOPV and LASV, respectively. *<span class="html-italic">p</span> &lt; 0.05, **<span class="html-italic">p</span> &lt; 0.01, and n.s.: non-significant, as determined by a Student’s <span class="html-italic">t</span>-test. (<b>C</b>) GFP-LC3 HeLa cells were infected with MOPV at an MOI of 2 for the indicated times and fixed for confocal microscopy analysis. The images were acquired using the same microscope as in (A) with an Axioscope 63× oil immersion lens objective. The error bars represent the standard error of the means from three independent experiments, *<span class="html-italic">p</span> &lt; 0.05, as determined by a Student’s <span class="html-italic">t</span>-test. GFP-LC3 dots were counted in 50 cells per condition.</p> Full article ">Figure 4
<p>Non-degradative steps of autophagy increase both LASV and MOPV infectious particle production. (<b>A</b>) HeLa cells were transfected with the indicated siRNA for 72 h before analysis of silencing efficiency by Western blotting (<span class="html-italic">n</span> = 4 independent experiments); (<b>B</b>–<b>D</b>) the same cells as in (A) were then infected with LASV or MOPV at an MOI of 0.1 for 1 h before being maintained for three days at 37 °C. Viral RNA was then extracted from the cells and supernatants for quantification by RTqPCR. The infectious particles from supernatants were also titrated on Vero cells. The error bars represent the standard error of the means from four independent experiments. * indicates <span class="html-italic">p</span> &lt; 0.05, as determined by the Mann–Whitney test.</p> Full article ">Figure 5
<p>Degradative steps of autophagy increase MOPV infectious particle production. (<b>A</b>) Hela cells were pretreated with 50 µM CQ for 2 h and placed on ice before infection with MOPV at an MOI of 2. Cells were then placed on ice before proceeding to heat shock (37 °C). At the indicated timepoints, attached virus was removed by trypsin treatment (TR), and viral intracellular RNA harvested for RTqPCR analysis. (<b>B</b>) HeLa cells were infected with LASV or MOPV at an MOI of 0.1 and then treated, or not, with 50 µM CQ one day after infection for two days. Cell supernatants were then harvested and titrated on Vero cells. The error bars represent the standard error of the means from four independent experiments. * indicates <span class="html-italic">p</span> &lt; 0.05, n.s.: non-significant, as determined by the Mann–Whitney test. The error bars represent the standard error of the means from four independent experiments. (<b>C</b>) The same cells as in (B) were lysed and the quantity of Z protein inside the cells has been measured by Western blotting. Representative results are shown, along with a graph representing the intensity of the Z protein bands over actin. The error bars represent the standard error of the means from four independent experiments. n.s. non-significant; *** <span class="html-italic">p</span> &lt; 0.001, as determined by Student’s <span class="html-italic">t</span>-test.</p> Full article ">
9 pages, 2566 KiB  
Article
Non-Pathogenic Mopeia Virus Induces More Robust Activation of Plasmacytoid Dendritic Cells than Lassa Virus
by Justine Schaeffer, Stéphanie Reynard, Xavier Carnec, Natalia Pietrosemoli, Marie-Agnès Dillies and Sylvain Baize
Viruses 2019, 11(3), 287; https://doi.org/10.3390/v11030287 - 21 Mar 2019
Cited by 7 | Viewed by 3442
Abstract
Lassa virus (LASV) causes a viral haemorrhagic fever in humans and is a major public health concern in West Africa. An efficient immune response to LASV appears to rely on type I interferon (IFN-I) production and T-cell activation. We evaluated the response of [...] Read more.
Lassa virus (LASV) causes a viral haemorrhagic fever in humans and is a major public health concern in West Africa. An efficient immune response to LASV appears to rely on type I interferon (IFN-I) production and T-cell activation. We evaluated the response of plasmacytoid dendritic cells (pDC) to LASV, as they are an important and early source of IFN-I. We compared the response of primary human pDCs to LASV and Mopeia virus (MOPV), which is very closely related to LASV, but non-pathogenic. We showed that pDCs are not productively infected by either MOPV or LASV, but produce IFN-I. However, the activation of pDCs was more robust in response to MOPV than LASV. In vivo, pDC activation may support the control of viral replication through IFN-I production, but also improve the induction of a global immune response. Therefore, pDC activation could play a role in the control of LASV infection. Full article
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
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<p>pDC infection by MOPV and LASV. (<b>a</b>) pDCs were infected with MOPV or LASV (MOI = 0.1) and infectious particles in the culture medium quantified. (<b>b</b>,<b>c</b>) pDCs were infected with MOPV or LASV (MOI = 0.1) for 1 h (day 0), 1 day, or 2 days. Viral RNA in the culture medium (<b>b</b>) or inside the cells (<b>c</b>) was quantified by RT-qPCR. (<b>d</b>–<b>g</b>) VeroE6 cells were infected with MOPV-Zflag or LASV-Zflag (MOI = 0.3). After 24 h, pDCs were added to the cells, or infected with MOPV-Zflag or LASV-Zflag (MOI = 0.1). 24 h later, cells were stained for phenotypic markers and the Z protein. Conditions were: infected VeroE6 ("veroE6"), VeroE6 cultured with pDCs ("coC"), and infected pDCs (“pDC”). Z-positive pDCs (<b>d</b>–<b>f</b>) and VeroE6 cells (<b>e</b>–<b>g</b>) were quantified by flow cytometry. All data are presented as the mean and standard error of mean (SEM) of three independent experiments. ANOVA on Ranks followed by pairwise comparisons (Tukey test) were performed. Differences are significant for <span class="html-italic">p</span> &lt; 0.05. When significant, <span class="html-italic">P</span> values of the ANOVA are indicated on the graph. Significant pairwise comparisons are indicated by a star (*).</p> Full article ">Figure 2
<p>IFN-I production in LASV-infected pDCs is less long-lasting than that of MOPV-infected pDCs. (<b>a</b>) pDCs were infected with MOPV (MOI = 2). Every 6 h, from 0 to 24 hpi, IFN-I mRNA was quantified by RT-qPCR. Data are presented as the fold change in the mRNA/GAPDH ratio in MOPV-infected pDCs relative to uninfected pDCs. (<b>b</b>–<b>d</b>) pDCs were cultured for 7 h or 16 h in culture medium (mock), R848 (1 µg/mL), MOPV, or LASV (MOI = 2). IFNα1 (<b>b</b>), IFNα2 (<b>c</b>) and IFNβ (<b>d</b>) mRNAs were quantified by RT-qPCR. Data shown are the means and SEM of three (<b>a</b>), four (<b>b</b>–<b>d</b> – 7 hpi), or seven (<b>b</b>–<b>d</b> – 16 hpi) independent experiments. ANOVA on Ranks followed by pairwise comparisons (Tukey test) were performed. Differences are significant for <span class="html-italic">p</span> &lt; 0.05. Significant pairwise comparisons are indicated by a star (*).</p> Full article ">Figure 3
<p>MOPV- and LASV-infected pDCs show different patterns of activation. (<b>a</b>) pDCs were cultured for 16 h with culture medium (mock), R848 (1 µg/mL), MOPV, or LASV (MOI = 2). Protein levels were quantified using the Luminex assay. Data are presented as the means and SEM of five independent experiments. Wilcoxon tests were performed, and differences are significant for <span class="html-italic">p</span> &lt; 0.05 (*) or <span class="html-italic">p</span> &lt; 0.01 (**). (<b>b</b>,<b>c</b>) pDCs were cultured for 12 h in culture medium (mock), MOPV, or LASV (MOI = 1). Cellular mRNA from three independent experiments was quantified by poly-A amplification and next-generation sequencing. (<b>b</b>) Data show the differential expression of genes in MOPV relative to LASV (MOPV/LASV) infected cells or in MOPV or LASV infected cells relative to mock (1, 2, 3, and mean). Genes shown in this figure displayed significant differences of expression (adjusted <span class="html-italic">p</span> &lt; 0.05). (<b>c</b>) MA plots for all pairwise comparison of data sets (MOPV/mock, LASV/mock and MOPV/LASV). Red dots indicate significantly different genes between the two conditions. Triangles correspond to features having a too low/high fold change to be displayed on the plot.</p> Full article ">
20 pages, 3787 KiB  
Article
Bovine Herpesvirus Type 4 (BoHV-4) Vector Delivering Nucleocapsid Protein of Crimean-Congo Hemorrhagic Fever Virus Induces Comparable Protective Immunity against Lethal Challenge in IFNα/β/γR−/− Mice Models
by Touraj Aligholipour Farzani, Katalin Földes, Alireza Hanifehnezhad, Burcu Yener Ilce, Seval Bilge Dagalp, Neda Amirzadeh Khiabani, Koray Ergünay, Feray Alkan, Taner Karaoglu, Hurrem Bodur and Aykut Ozkul
Viruses 2019, 11(3), 237; https://doi.org/10.3390/v11030237 - 9 Mar 2019
Cited by 28 | Viewed by 5688
Abstract
Crimean-Congo hemorrhagic fever virus (CCHFV) is the causative agent of a tick-borne infection with a significant mortality rate of up to 40% in endemic areas, with evidence of geographical expansion. Due to a lack of effective therapeutics and control measures, the development of [...] Read more.
Crimean-Congo hemorrhagic fever virus (CCHFV) is the causative agent of a tick-borne infection with a significant mortality rate of up to 40% in endemic areas, with evidence of geographical expansion. Due to a lack of effective therapeutics and control measures, the development of a protective CCHFV vaccine remains a crucial public health task. This paper describes, for the first time, a Bovine herpesvirus type 4 (BoHV-4)-based viral vector (BoHV4-∆TK-CCHFV-N) and its immunogenicity in BALB/c and protection potential in IFNα/β/γR−/− mice models in comparison with two routinely used vaccine platforms, namely, Adenovirus type 5 and a DNA vector (pCDNA3.1 myc/His A), expressing the same antigen. All vaccine constructs successfully elicited significantly elevated cytokine levels and specific antibody responses in immunized BALB/c and IFNα/β/γR−/− mice. However, despite highly specific antibody responses in both animal models, the antibodies produced were unable to neutralize the virus in vitro. In the challenge experiment, only the BoHV4-∆TK-CCHFV-N and Ad5-N constructs produced 100% protection against lethal doses of the CCHFV Ank-2 strain in IFNα/β/γR−/− mice. The delivery platforms could not be compared due to similar protection rates in IFNα/β/γR−/− mice. However, during the challenge experiment in the T cell and passive antibody transfer assay, BoHV4-∆TK-CCHFV-N was dominant, with a protection rate of 75% compared to others. In conclusion, vector-based CCHFV N protein expression constitutes an effective approach for vaccine development and BoHV-4 emerged as a strong alternative to previously used viral vectors. Full article
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
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<p>(<b>A</b>,<b>B</b>) Schematic figure of recombineering in SW102 bacteria to create BoHV-4 viral vector expressing nucleocapsid protein of CCHFV (BoHV4-∆TK-CCHFV-N) (<b>A</b>) and a homologous recombination in HEK293 to rescue Ad5-N (<b>B</b>). BoHV4-∆TK-CCHFV-N, Movar33/63, Ad5-N and Ad5-wt propagation in cells. (<b>C</b>) BoHV4-∆TK-CCHFV-N-infected MDBK cells on day 5 (fluorescence) post-infection (p.i). (<b>D</b>) BoHV4-∆TK-CCHFV-N-infected MDBK cells on day 5 (phase contrast) p.i. (<b>E</b>) Movar33/63-infected MDBK cells on day 5 p.i. (<b>F</b>) Uninfected-MDBK cells on day 5 p.i. (<b>G</b>) Ad5-N-infected HEK293 cells on day 5 p.i. (<b>H</b>) Ad5-wt-infected HEK293 cells on day 5 p.i. (<b>I</b>) Uninfected-HEK293 cells on day 5 (×400). All the viruses were inoculated at 1 moi in the mentioned cells.</p> Full article ">Figure 2
<p>In vitro expression of N protein. (<b>A</b>,<b>B</b>) Western blot assay (WB). (<b>A</b>) Positive bands of 52 kDa (N protein) detected in lane 1 (CCHFV Ank-2-infected SW-13 cells), lane 2 (BoHV4-∆TK-CCHFV-N-infected MDBK cells), lane 3 (Ad5-N-infected HEK293 cells), and lane 4 (pCD-N1-transfected HEK293A cells). We also included control groups of lane 5 (Movar33/63-infected MDBK cells), lane 6 (Ad5-wt-infected HEK293 cells), lane 7 (pCDNA3.1 myc/His A-transfected HEK293 cells) and lane 8 (negative control) in the experiment. (<b>B</b>) Beta-actin protein (43 kDa) was detected as the loading control of WB in all mentioned groups. (<b>C</b>–<b>H</b>) IIFA 48 h post-transfection. (<b>C</b>) pCD-N1-transfected BHK21-C13 cells (fluorescence). (<b>D</b>) pCD-N1-transfected BHK21-C13 cells (phase contrast). (<b>E</b>) pDC516-N-transfected BHK21-C13 cells (fluorescence). (<b>F</b>) pDC516-N-transfected BHK21-C13 cells (phase contrast). (<b>G</b>) Negative control cells (fluorescence). (<b>H</b>) Negative control cells (phase contrast). In IIFA and WB assays for the detection of N proteins, the primary and secondary antibodies are primary human polyclonal (1/250 dilution) and anti-human IgG-HRP secondary antibodies (1/750 dilution), respectively.</p> Full article ">Figure 3
<p>Serological Assays. Total antibody isotype responses and ELISA assays were performed in BALB/c and IFNα/β/γR−/− mice serum samples, respectively. (<b>A</b>) IgG1 response: pCD-N1-immunized BALB/c mice showed higher levels of this antibody than other N-expressing constructs. (<b>B</b>) IgG2a response: considering the respective backbones, the BoHV4-∆TK-CCHFV-N and pCD-N1 groups had more potential to stimulate IgG2a production. (<b>C</b>) IgG2b response: considering the N-expressing groups and related backbone subtraction, the BoHV4-∆TK-CCHFV-N group was dominant. (<b>D</b>) IgG3 response: the results were comparable to the IgG1 findings. (<b>E</b>) IgG2a/IgG1 ratio (BALB/c mice): all groups except normal saline demonstrated a ratio &lt;1, indicating a shift towards Th2 responses. (<b>F</b>) ELISA assay from immunized IFNα/β/γR−/− mice: all constructs expressing N protein could produce N-specific IgG antibodies after a 2-dose injection and before the challenge assay on day 28. The highest amount of specific antibodies was detected in the pCD-N1 group when the results were compared to the respective backbones. In addition, the BoHV4-∆TK-CCHFV-N- and Ad5-N-related findings are also significant. All data are shown as mean ± SD.* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001 versus respective backbones.</p> Full article ">Figure 4
<p>Cytokine responses of Ank-2 virus-stimulated (moi 10) splenocytes from immunized BALB/c mice (on day 28) after 48 and 72 h post-infection. (<b>A</b>) IFN-gamma response: as demonstrated here, the pCD-N1 group was higher than other N-expressing groups. (<b>B</b>) IL-2 response: Ad5-N was dominant. Other groups could not stimulate adequate production. (<b>C</b>) IL-4 response: the results were similar to IL-2. (<b>D</b>) IL-5 response: Ad5-N showed more potential to secrete IL-5. (<b>E</b>) IL-13 response: the results were similar to IL-2, IL-4 and IL-5. (<b>F</b>) IL-6 response: while the Ad5-N group was higher than the BoHV4-∆TK-CCHFV-N group, sufficient levels were also stimulated by this construct. (<b>G</b>) IL-10 response: both the BoHV4-∆TK-CCHFV-N and Ad5-N groups induced significant amounts compared to their respective backbone and pCD-N1. (<b>H</b>) TNF-alpha response: the results were similar to IL-10. All data are shown as mean ± SD; * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 versus respective backbones.</p> Full article ">Figure 5
<p>Cytokine responses of immunized BALB/c mice serum samples on days 0 (D0) and 28 (D28). (<b>A</b>) IFN-gamma response: the Ad5-N construct was dominant in comparison to other N-expressing ones. (<b>B</b>) IL-2 response: considering the respective backbones, the pCD-N1 construct showed increased potential to elicit this cytokine’s production. (<b>C</b>) IL-4 response: similar to IL-2 response, the pCD-N1 group showed elevated levels. IL-4 was further significant in the BoHV4-∆TK-CCHFV-N group. (<b>D</b>) IL-5 response: identical to IL-4. (<b>E</b>) IL-6 response: the BoHV4-∆TK-CCHFV-N and pCD-N1 groups showed higher levels. (<b>F</b>) IL-10 response: the BoHV4-∆TK-CCHFV-N group showed higher potential for stimulation. (<b>G</b>) IL-13 response: similar to IL-2. (<b>H</b>) TNF-alpha response: by subtracting the respective backbones, it is clear that pCD-N1 was dominant in this kind of response. All data are shown as mean ± SD; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001 versus respective backbones.</p> Full article ">Figure 6
<p>Cytokine responses in IFNα/β/γR−/− mice serum samples. (<b>A</b>) IFN-gamma response: no N-expressing constructs could stimulate adequate levels of this cytokine. (<b>B</b>) IL-2 response: the results were similar to IFN-gamma. (<b>C</b>) IL-4 response: the BoHV4-∆TK-CCHFV-N, Ad5-N and pCD-N1 groups’ responses were elevated. However, considering the respective backbone, only the BoHV4-∆TK-CCHFV-N and Ad5-N groups were significant. (<b>D</b>) IL-5 response: none of the three groups of BoHV4-∆TK-CCHFV-N, Ad5-N and pCD-N1 showed potential for IL-5 stimulation. (<b>E</b>) IL-6 response: the BoHV4-∆TK-CCHFV-N, Ad5-N and pCD-N1 groups demonstrated high levels. (<b>F</b>) TNF-alpha response: the results were similar to IL-6. All data are shown as mean ± SD; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0. versus respective backbones.</p> Full article ">Figure 7
<p>(<b>A</b>) Survival rate of immunized IFNα/β/γR−/− mice in challenge assay (1000TCID<sub>50</sub>/300 µL of Ank-2 strain): Survival rate of 100% observed in BoHV4-∆TK-CCHFV-N and Ad5-N groups. The results of pCD-N1 are also satisfactory with one death (survival rate of 75%). Control groups of Mover33/63 (death on day 5 post-challenge), Ad5-wt (death on day 6 post-challenge), pCDNA3.1 myc/His A (death on day 5 post-challenge) and normal saline (death on day 5 post-challenge) were also included in the experiment. (<b>B</b>) Percentage body weight of immunized IFNα/β/γR−/− mice after challenge experiment: despite lethal challenge, an almost stable body weight range was observed in the BoHV4-∆TK-CCHFV-N, Ad5-N and pCD-N1 groups. (<b>C</b>) Survival rates in the antibody passive (100–300 µL of serum containing 500 µg of IgG antibody) and T cell adoptive transfer (2 × 10<sup>5</sup> splenocytes) experiment in IFNα/β/γR−/− mice: 24 h after transfer of splenocytes plus serum samples of BALB/c immunized mice, IFNα/β/γR−/− mice were challenged and BoHV4-∆TK-CCHFV-N showed a higher survival rate (75%) than Ad5-N and pCD-N1 (survival rate of 50%) after 15 days. (<b>D</b>) Percentage body weights of surviving IFNα/β/γR−/− mice in the antibody passive and T cell adoptive transfer experiment: As demonstrated, all surviving groups showed a decline in body weight percentage on day 4 post-challenge but stabilized after day 8 post-challenge. All data in <a href="#viruses-11-00237-f007" class="html-fig">Figure 7</a>B,D are shown as mean ± SD.</p> Full article ">
9 pages, 1665 KiB  
Article
Priorities, Barriers, and Facilitators towards International Guidelines for the Delivery of Supportive Clinical Care during an Ebola Outbreak: A Cross-Sectional Survey
by Marie-Claude Battista, Christine Loignon, Lynda Benhadj, Elysee Nouvet, Srinivas Murthy, Robert Fowler, Neill K. J. Adhikari, Adnan Haj-Moustafa, Alex P. Salam, Adrienne K. Chan, Sharmistha Mishra, Francois Couturier, Catherine Hudon, Peter Horby, Richard Bedell, Michael Rekart, Jan Hajek and Francois Lamontagne
Viruses 2019, 11(2), 194; https://doi.org/10.3390/v11020194 - 23 Feb 2019
Cited by 7 | Viewed by 4954
Abstract
During the Ebola outbreak, mortality reduction was attributed to multiple improvements in supportive care delivered in Ebola treatment units (ETUs). We aimed to identify high-priority supportive care measures, as well as perceived barriers and facilitators to their implementation, for patients with Ebola Virus [...] Read more.
During the Ebola outbreak, mortality reduction was attributed to multiple improvements in supportive care delivered in Ebola treatment units (ETUs). We aimed to identify high-priority supportive care measures, as well as perceived barriers and facilitators to their implementation, for patients with Ebola Virus Disease (EVD). We conducted a cross-sectional survey of key stakeholders involved in the response to the 2014–2016 West African EVD outbreak. Out of 57 email invitations, 44 responses were received, and 29 respondents completed the survey. The respondents listed insufficient numbers of health workers (23/29, 79%), improper tools for the documentation of clinical data (n = 22/28, 79%), insufficient material resources (n = 22/29, 76%), and unadapted personal protective equipment (n = 20/28, 71%) as the main barriers to the provision of supportive care in ETUs. Facilitators to the provision of supportive care included team camaraderie (n in agreement = 25/28, 89%), ability to speak the local language (22/28, 79%), and having treatment protocols in place (22/28, 79%). This survey highlights a consensus across various stakeholders involved in the response to the 2014–2016 EVD outbreak on a limited number of high-priority supportive care interventions for clinical practice guidelines. Identified barriers and facilitators further inform the application of guidelines. Full article
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
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<p>Professional affiliations reported by survey respondents.</p> Full article ">Figure 2
<p>Number of active respondents by outbreak period.</p> Full article ">Figure 3
<p>Agreement with supportive care interventions proposed to be embedded within standard practices in Ebola treatment units.</p> Full article ">
19 pages, 5061 KiB  
Article
Co-Delivery Effect of CD24 on the Immunogenicity and Lethal Challenge Protection of a DNA Vector Expressing Nucleocapsid Protein of Crimean Congo Hemorrhagic Fever Virus
by Touraj Aligholipour Farzani, Alireza Hanifehnezhad, Katalin Földes, Koray Ergünay, Erkan Yilmaz, Hiba Hashim Mohamed Ali and Aykut Ozkul
Viruses 2019, 11(1), 75; https://doi.org/10.3390/v11010075 - 17 Jan 2019
Cited by 20 | Viewed by 5401
Abstract
Crimean Congo hemorrhagic fever virus (CCHFV) is the causative agent of a globally-spread tick-borne zoonotic infection, with an eminent risk of fatal human disease. The imminent public health threat posed by the disseminated virus activity and lack of an approved therapeutic make CCHFV [...] Read more.
Crimean Congo hemorrhagic fever virus (CCHFV) is the causative agent of a globally-spread tick-borne zoonotic infection, with an eminent risk of fatal human disease. The imminent public health threat posed by the disseminated virus activity and lack of an approved therapeutic make CCHFV an urgent target for vaccine development. We described the construction of a DNA vector expressing a nucleocapsid protein (N) of CCHFV (pV-N13), and investigated its potential to stimulate the cytokine and total/specific antibody responses in BALB/c and a challenge experiment in IFNAR−/− mice. Because of a lack of sufficient antibody stimulation towards the N protein, we have selected cluster of differentiation 24 (CD24) protein as a potential adjuvant, which has a proliferative effect on B and T cells. Overall, our N expressing construct, when administered solely or in combination with the pCD24 vector, elicited significant cellular and humoral responses in BALB/c, despite variations in the particular cytokines and total antibodies. However, the stimulated antibodies produced as a result of the N protein expression have shown no neutralizing ability in the virus neutralization assay. Furthermore, the challenge experiments revealed the protection potential of the N expressing construct in an IFNAR −/− mice model. The cytokine analysis in the IFNAR−/− mice showed an elevation in the IL-6 and TNF-alpha levels. In conclusion, we have shown that targeting the S segment of CCHFV can be considered for a practical way to develop a vaccine against this virus, because of its ability to induce an immune response, which leads to protection in the challenge assays in the interferon (IFN)-gamma defective mice models. Moreover, CD24 has a prominent immunologic effect when it co-delivers with a suitable foreign gene expressing vector. Full article
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
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<p>Immunization scheme.</p> Full article ">Figure 2
<p>(<b>A</b>,<b>B</b>) Propagation of Ank-2 strain of Crimean Congo hemorrhagic fever virus (CCHFV) in Scott and White No. 13 (SW-13) cells on day five (A: cell control, B: virus infected cells). Magnification ×400. (<b>C</b>) Plasmid construct used for DNA immunization in this study. In vitro homologous recombination between the empty vector and amplified nucleocapsid, flanked by 50 bp homologous arms to the EcoRI recognition sequence of the vector multiple cloning site, occurs in the presence of the Seamless Ligation Cloning Extract (SLiCE) lysate from PPY bacteria, adenosine triphosphate (ATP), 1,4-Dithiothreitol (DTT), and MgCl<sub>2</sub> at 37 °C. (<b>D</b>–<b>G</b>) N protein expression in the cells transfected by pV-N13 via indirect immunofluorescence assay (IIFA) 72 hours post DNA delivery (D: phase contrast; E: fluorescent contrast). CD24 protein expression in the cells transfected by pCD24 via IIFA after 72 h (F: phase contrast; G: fluorescent contrast). (<b>H</b>) Western blot analysis of the BHK21-C13 cells transfected with pV-N13. The expected protein (~52 kDa) was detected after 72 h (lane 1). We included pVAX-1 transfected cells (lane 2) and cell control (lane 3) in the assay.</p> Full article ">Figure 3
<p>Serological assays (<b>A</b>) IgG1 response. (<b>B</b>) IgG2a response. (<b>C</b>) IgG2b response. (<b>D</b>) IgG3 response: In all of the mentioned assays, the pV-N13 plus pCD24 and pCD24 groups are dominant. (<b>E</b>) IgM response: pV-N13, pV-N13 plus pCD24, and pCD24 groups are a stimulator of the IgM response. (<b>F</b>) Comparison of IgG1, IgG2a, and IgG2a/IgG1 ratio responses. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; and *** <span class="html-italic">p</span> &lt; 0.001 versus the pVAX-1 group. All of the data are shown as mean ± standard deviation (SD). (<b>G</b>–<b>H</b>) Detection of the N specific antibodies present in the serum samples in the Baby Hamster Kidney (BHK)-N cells (G: pV-N13 immunized mice serum samples, H: pV-N13 plus pCD24 immunized mice serum samples).</p> Full article ">Figure 3 Cont.
<p>Serological assays (<b>A</b>) IgG1 response. (<b>B</b>) IgG2a response. (<b>C</b>) IgG2b response. (<b>D</b>) IgG3 response: In all of the mentioned assays, the pV-N13 plus pCD24 and pCD24 groups are dominant. (<b>E</b>) IgM response: pV-N13, pV-N13 plus pCD24, and pCD24 groups are a stimulator of the IgM response. (<b>F</b>) Comparison of IgG1, IgG2a, and IgG2a/IgG1 ratio responses. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; and *** <span class="html-italic">p</span> &lt; 0.001 versus the pVAX-1 group. All of the data are shown as mean ± standard deviation (SD). (<b>G</b>–<b>H</b>) Detection of the N specific antibodies present in the serum samples in the Baby Hamster Kidney (BHK)-N cells (G: pV-N13 immunized mice serum samples, H: pV-N13 plus pCD24 immunized mice serum samples).</p> Full article ">Figure 4
<p>Cytokine responses in the supernatant of CCHFV stimulated splenocytes of the immunized BALB/c mice. (<b>A</b>) Interferon (IFN)-gamma response: As demonstrated here, the pV-N13 plus pCD24 group’s result is higher in comparison with the other groups. The pCD24 stimulation level is also significant. (<b>B</b>) IL-2 response: IL-2 response is predominant in the pV-N13 plus pCD24 and pCD24 groups. (<b>C</b>) IL-4 response: As shown, the pV-N13 plus pCD24 and pV-N13 immunized BALB/c mice demonstrated the highest amount. (<b>D</b>) IL-5 response: the IL-5 response is predominant in the pV-N13 plus pCD24 and pCD24 groups. (<b>E</b>) IL-6 response: pV-N13 plus pCD24 and pV-N13 groups are higher in comparison with the other groups. (<b>F</b>) IL-13 response: All of the immunized mice showed almost identical levels of IL-13 secretion. (<b>G</b>) IL-10 response: When comparing the N expressing groups to the empty vectors, the pV-N13 plus pCD24 group elicited a pronounced IL-10 response in the BALB/c mice model. Also, pCD24 has the potential to induce IL-10 responses. (<b>H</b>) TNF-alpha response: As shown, the pV-N13 plus pCD24 group stimulated the highest amount. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 versus the pVAX-1 group. The ‘ns’ in the graphs indicates non-significant data. All of the data are shown as mean ± SD.</p> Full article ">Figure 5
<p>Cytokine responses in the serum samples of the immunized BALB/c mice. (<b>A</b>) IFN-gamma response: pCD24 vector (on day 28) stimulated a prominent production of IFN-gamma. pV-N13 plus pCD24 on day 28 is by far dominant when compared with other groups. (<b>B</b>) IL-2 response: pCD24 and pV-N13 plus pCD24 possessed the highest amount. Moreover, the IL-2 level in the pV-N13 group is also adequate. (<b>C</b>) IL-4 response: IL-4 stimulation in pCD24 and pV-N13 plus pCD24 is considerable when compared with the other groups. (<b>D</b>) IL-5 response: Interestingly, the pV-N13 plus pCD24 group has potential to stimulate this cytokine in immunized mice in a higher level compared to the remaining groups. The amount of IL-5 in the pCD24 immunized mice is also significantly elevated. (<b>E</b>) IL-6 response: pCD24 and pV-N13 plus pCD24 immunized mice possessed the highest level of IL-6 in the serum samples. (<b>F</b>) IL-10 response: The results indicated the predominance of the pV-N13 plus pCD24 group. (<b>G</b>) IL-13 response: The resu lts are comparable to those of IFN-gamma. (<b>H</b>) TNF-alpha response: pV-N13 plus pCD24 construct stimulated the highest levels of TNF-alpha. * <span class="html-italic">p</span> &lt; 0.05; **<span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 versus pVAX-1 group. All of the data are shown as mean ± SD.</p> Full article ">Figure 6
<p>Cytokine responses in the serum samples of the immunized IFNAR<sup>−/−</sup> mice. (<b>A</b>) IFN-gamma response: pV-N13 and pV-N13 plus pCD24 showed relatively high levels of IFN-gamma on day 28 (before challenge). Despite pV-N13 plus pCD24, in the pV-N13 group, this cytokine was elevated on day 41 (13 days after challenge). (<b>B</b>) IL-2 response: The results of IL-2 are comparable to INF-gamma. (<b>C</b>) IL-4 response: pV-N13 and pV-N13 plus pCD24 demonstrated the potential to stimulate IL-4 before challenge on day 28 and 13 days after challenge on day 41. (<b>D</b>) IL-5 response: pV-N13 plus pCD24 is predominant compared with pV-N13. However, both groups demonstrated a decrease on day 41. (<b>E</b>) IL-6 response: pV-N13 plus pCD24 appeared more immunogenic than pV-N13 via the IL-6 levels. (<b>F</b>) TNF-alpha response: The results are comparable to IL-6 and both N expressing constructs had the potential to elicit adequate TNF-alpha responses before and after challenge. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 versus pVAX-1 group. All of the data are shown as mean ± SD.</p> Full article ">Figure 7
<p>Challenge experiment. (<b>A</b>) Challenge assay to find the suitable strain of CCHFV: Four different isolates were assayed in IFNAR<sup>−/−</sup> to identify the lethal strains. (<b>B</b>) Survival rate in the challenge assay with Ank-2 strain: the pV-N13 and pV-N13 plus pCD24 groups survived in the lethal dose challenge of the IFNAR<sup>−/−</sup> mice. (<b>C</b>) Percentage of body weight: Despite the lethal challenge, the pV-N13 and pV-N13 plus pCD24 groups showed an almost stable body weight range. All of the data are shown as mean ± SD.</p> Full article ">Figure 8
<p>Viral loads (copy/µL of 100 ng RNA) in the tissues of the challenged IFNAR<sup>−/−</sup> mice infected with 1000 TCID<sub>50</sub> of the Ank-2 strain. The virus copy numbers in the brain (A: all groups; B: all groups except the positive control), liver (C: all groups; D: all groups except the positive control), and spleen (E: all groups) are provided. The most significant virus clearance was observed in the pV-N13 and pV-N13 plus pCD24 groups. All of data are shown as mean ± SD.</p> Full article ">
15 pages, 1616 KiB  
Article
Phylodynamic Analysis of Ebola Virus Disease Transmission in Sierra Leone
by Petrus Jansen van Vuren, Jason T. Ladner, Antoinette A. Grobbelaar, Michael R. Wiley, Sean Lovett, Mushal Allam, Arshad Ismail, Chantel le Roux, Jacqueline Weyer, Naazneen Moolla, Nadia Storm, Joe Kgaladi, Mariano Sanchez-Lockhart, Ousman Conteh, Gustavo Palacios and Janusz T. Paweska
Viruses 2019, 11(1), 71; https://doi.org/10.3390/v11010071 - 16 Jan 2019
Cited by 3 | Viewed by 5309
Abstract
We generated genome sequences from 218 cases of Ebola virus disease (EVD) in Sierra Leone (SLE) during 2014–2015 to complement available datasets, particularly by including cases from a period of low sequence coverage during peak transmission of Ebola virus (EBOV) in the highly-affected [...] Read more.
We generated genome sequences from 218 cases of Ebola virus disease (EVD) in Sierra Leone (SLE) during 2014–2015 to complement available datasets, particularly by including cases from a period of low sequence coverage during peak transmission of Ebola virus (EBOV) in the highly-affected Western Area division of SLE. The combined dataset was utilized to produce phylogenetic and phylodynamic inferences, to study sink–source dynamics and virus dispersal from highly-populated transmission hotspots. We identified four districts in SLE where EBOV was introduced and transmission occurred without onward exportation to other districts. We also identified six districts that substantially contributed to the dispersal of the virus and prolonged the EVD outbreak: five of these served as major hubs, with lots of movement in and out, and one acted primarily as a source, exporting the virus to other areas of the country. Positive correlations between case numbers, inter-district transition events, and district population sizes reaffirm that population size was a driver of EBOV transmission dynamics in SLE. The data presented here confirm the role of urban hubs in virus dispersal and of a delayed laboratory response in the expansion and perpetuation of the EVD outbreak in SLE. Full article
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
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<p>Sink/source dynamics of Ebola virus disease (EVD) in Sierra Leone based on 5 BEAST runs and &gt;30,000 sampled trees. (<b>A</b>) Import/export events per district (means with error bars indicating 95 highest posterior density (HPD); mean of 225 total between district moves per tree, 95 HPD: 212–238); (<b>B</b>) heat map showing mean import events per district; (<b>C</b>) heat map showing mean import events over time per district; (<b>D</b>) heat map showing mean export events per district; and (<b>E</b>) heat map showing mean export events over time per district.</p> Full article ">Figure 2
<p>Phylogeographic BEAST reconstruction of transmission of Ebola virus in Sierra Leone. Colors of the lines correspond to the destination of the transmission event, while upward curving lines indicate eastward transmission and downward curving lines indicate westward transmission. The numbers represent the scale relative to the size of the lines.</p> Full article ">Figure 3
<p>Phylogeny based on BEAST analysis of 1062 sequences from Sierra Leone (SLE). Lineages SL3.1.1, SL3.1.2, and SL3.2.1–3.2.5 are highlighted, as indicated in the legend. A time scale below the tree shows the time from the root of the tree, in years, and corresponding calendar dates.</p> Full article ">Figure 4
<p>Distribution of lineages in Western Area Urban (WAU) over time (259 sequences).</p> Full article ">

Review

Jump to: Research, Other

12 pages, 671 KiB  
Review
The Role of Reference Materials in the Research and Development of Diagnostic Tools and Treatments for Haemorrhagic Fever Viruses
by Giada Mattiuzzo, Emma M. Bentley and Mark Page
Viruses 2019, 11(9), 781; https://doi.org/10.3390/v11090781 - 24 Aug 2019
Cited by 7 | Viewed by 3254
Abstract
Following the Ebola outbreak in Western Africa in 2013–16, a global effort has taken place for preparedness for future outbreaks. As part of this response, the development of vaccines, treatments and diagnostic tools has been accelerated, especially towards pathogens listed as likely to [...] Read more.
Following the Ebola outbreak in Western Africa in 2013–16, a global effort has taken place for preparedness for future outbreaks. As part of this response, the development of vaccines, treatments and diagnostic tools has been accelerated, especially towards pathogens listed as likely to cause an epidemic and for which there are no current treatments. Several of the priority pathogens identified by the World Health Organisation are haemorrhagic fever viruses. This review provides information on the role of reference materials as an enabling tool for the development and evaluation of assays, and ultimately vaccines and treatments. The types of standards available are described, along with how they can be applied for assay harmonisation through calibration as a relative potency to a common arbitrary unitage system (WHO International Unit). This assures that assay metrology is accurate and robust. We describe reference materials that have been or are being developed for haemorrhagic fever viruses and consider the issues surrounding their production, particularly that of biosafety where the viruses require specialised containment facilities. Finally, we advocate the use of reference materials at early stages, including research and development, as this helps produce reliable assays and can smooth the path to regulatory approval. Full article
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
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<p>Harmonisation of the potencies for Ebola RNA samples after assay calibration to WHO reference reagent. Mean laboratory estimates for an EBOV RNA incorporated into an HIV-like particle using NAAT methods targeting EBOV np, gp, or vp35 genes. (<b>a</b>) Results were reported by the participants as Log10 “detectable units”/mL, being “copies” for majority of the quantitative assays, or detection limit by Ct values. (<b>b</b>) Mean estimates of the same samples expressed as relative to the WHO reference reagent for EBOV RNA. Values are reported as Log10 WHO units/mL. Full details of the study are available in the WHO report [<a href="#B57-viruses-11-00781" class="html-bibr">57</a>].</p> Full article ">Figure 2
<p>Increased harmonisation of EBOV neutralizing antibody titres by the WHO International Standard. Geometric coefficient of variation (GCV) was calculated using the neutralizing antibody titres against EBOV as reported by the participants (50% neutralisation titre, blue bars) or after normalisation to the International Standard (1st WHO IS), and potency is expressed as International Unit (IU, orange bars). Note: CP = convalescent plasma. Arrow down = GCV:0% where the value has been assigned. Full details are available in the final report of the collaborative study [<a href="#B68-viruses-11-00781" class="html-bibr">68</a>].</p> Full article ">
19 pages, 1748 KiB  
Review
Pulmonary Involvement during the Ebola Virus Disease
by Eleonora Lalle, Mirella Biava, Emanuele Nicastri, Francesca Colavita, Antonino Di Caro, Francesco Vairo, Simone Lanini, Concetta Castilletti, Martin Langer, Alimuddin Zumla, Gary Kobinger, Maria R. Capobianchi and Giuseppe Ippolito
Viruses 2019, 11(9), 780; https://doi.org/10.3390/v11090780 - 24 Aug 2019
Cited by 6 | Viewed by 4912
Abstract
Filoviruses have become a worldwide public health concern, especially during the 2013–2016 Western Africa Ebola virus disease (EVD) outbreak—the largest outbreak, both by number of cases and geographical extension, recorded so far in medical history. EVD is associated with pathologies in several organs, [...] Read more.
Filoviruses have become a worldwide public health concern, especially during the 2013–2016 Western Africa Ebola virus disease (EVD) outbreak—the largest outbreak, both by number of cases and geographical extension, recorded so far in medical history. EVD is associated with pathologies in several organs, including the liver, kidney, and lung. During the 2013–2016 Western Africa outbreak, Ebola virus (EBOV) was detected in the lung of infected patients suggesting a role in lung pathogenesis. However, little is known about lung pathogenesis and the controversial issue of aerosol transmission in EVD. This review highlights the pulmonary involvement in EVD, with a special focus on the new data emerging from the 2013–2016 Ebola outbreak. Full article
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
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Figure 1
<p>Direct and indirect effects of viral infections of the airway epithelium. Upon entrance into the cell, viruses are recognized by the Toll-like receptor (TLR) on either cell membrane or in endosomes. TLRs activate interferon regulatory factors (IRFs) leading to IFN-α and IFN-β release via the Toll/IL-1 receptor domain-containing adaptor (TRIF). TLR3 stimulates IRF-7 and NF-κB via MyD88 activation, leading to the release of proinflammatory cytokines and the production of IFN-α, -β, and -λ, respectively. Secretion of proinflammatory cytokines and chemokines activate the immune system, through recruitment of eosinophils, neutrophils, macrophages, dendritic cells, T cells, and NK cells. Most respiratory viruses have developed strategies to escape antiviral defense, mainly by interfering with the IFN system or by affecting the epithelium barrier, with the consequence of a loss of integrity and protection. Furthermore, respiratory viruses can perturb (skewed or exaggerated) inflammatory responses and production of soluble mediators.</p> Full article ">Figure 2
<p>EBOV pulmonary disease pathogenesis. Arrows show the proposed sequence of events and inverted ‘Ts’ show the blocked mechanisms due to the consequences of viral infection.</p> Full article ">
27 pages, 735 KiB  
Review
Animal Models for Crimean-Congo Hemorrhagic Fever Human Disease
by Aura R. Garrison, Darci R. Smith and Joseph W. Golden
Viruses 2019, 11(7), 590; https://doi.org/10.3390/v11070590 - 28 Jun 2019
Cited by 53 | Viewed by 5628
Abstract
Crimean-Congo hemorrhagic fever virus (CCHFV) is an important tick-borne human pathogen endemic throughout Asia, Africa and Europe. CCHFV is also an emerging virus, with recent outbreaks in Western Europe. CCHFV can infect a large number of wild and domesticated mammalian species and some [...] Read more.
Crimean-Congo hemorrhagic fever virus (CCHFV) is an important tick-borne human pathogen endemic throughout Asia, Africa and Europe. CCHFV is also an emerging virus, with recent outbreaks in Western Europe. CCHFV can infect a large number of wild and domesticated mammalian species and some avian species, however the virus does not cause severe disease in these animals, but can produce viremia. In humans, CCHFV infection can lead to a severe, life-threating disease characterized by hemodynamic instability, hepatic injury and neurological disorders, with a worldwide lethality rate of ~20–30%. The pathogenic mechanisms of CCHF are poorly understood, largely due to the dearth of animal models. However, several important animal models have been recently described, including novel murine models and a non-human primate model. In this review, we examine the current knowledge of CCHF-mediated pathogenesis and describe how animal models are helping elucidate the molecular and cellular determinants of disease. This information should serve as a reference for those interested in CCHFV animal models and their utility for evaluation of medical countermeasures (MCMs) and in the study of pathogenesis. Full article
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
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<p>Lethal Crimean-Congo hemorrhagic fever virus (CCHFV) infection in mice treated with MAb-5A3 post-challenge. C57BL/6 mice(<span class="html-italic">n</span> = 8/group) were infected with 100 plaque forming units/mL CCHFV strain Afg09-2990 by the intraperitoneal route as described in [<a href="#B104-viruses-11-00590" class="html-bibr">104</a>] and at the indicated times post-infection (24 h, 36 h, 48 h or 72 h) were treated with MAb-5A3 (2.5 mg) which disrupts type I interferon signaling. Survival and group weights were monitored for 15 days and plotted using Prism software.</p> Full article ">

Other

Jump to: Research, Review

7 pages, 303 KiB  
Brief Report
Clinical Evaluation of QuickNaviTM-Ebola in the 2018 Outbreak of Ebola Virus Disease in the Democratic Republic of the Congo
by Sheila Makiala, Daniel Mukadi, Anja De Weggheleire, Shino Muramatsu, Daisuke Kato, Koichi Inano, Fumio Gondaira, Masahiro Kajihara, Reiko Yoshida, Katendi Changula, Aaron Mweene, Placide Mbala-Kingebeni, Jean-Jacques Muyembe-Tamfum, Justin Masumu, Steve Ahuka and Ayato Takada
Viruses 2019, 11(7), 589; https://doi.org/10.3390/v11070589 - 28 Jun 2019
Cited by 15 | Viewed by 3913
Abstract
The recent large outbreaks of Ebola virus disease (EVD) in West Africa and the Democratic Republic of the Congo (DRC) have highlighted the need for rapid diagnostic tests to control this disease. In this study, we clinically evaluated a previously developed immunochromatography-based kit, [...] Read more.
The recent large outbreaks of Ebola virus disease (EVD) in West Africa and the Democratic Republic of the Congo (DRC) have highlighted the need for rapid diagnostic tests to control this disease. In this study, we clinically evaluated a previously developed immunochromatography-based kit, QuickNaviTM-Ebola. During the 2018 outbreaks in DRC, 928 blood samples from EVD-suspected cases were tested with QuickNaviTM-Ebola and the WHO-approved GeneXpert. The sensitivity and specificity of QuickNaviTM-Ebola, estimated by comparing it to GeneXpert-confirmed cases, were 85% (68/80) and 99.8% (846/848), respectively. These results indicate the practical reliability of QuickNaviTM-Ebola for point-of-care diagnosis of EVD. Full article
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
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Figure 1
<p>(<b>a</b>) Illustration of QuickNavi<sup>TM</sup>-Ebola. A sample added to the sample window of the device migrates via capillary action. The ebolavirus NP antigens present in the sample bind to the latex-conjugated mAb on the conjugate pad. Another mAb is immobilized on a nitrocellulose membrane at the Test line position and captures the complexes of NPs and mAbs conjugated with latex. Those complexes deposit a visible blue line. (<b>b</b>) QuickNavi<sup>TM</sup>-Ebola used at a field laboratory in North-Kivu province.</p> Full article ">
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