Expanding the host range of hepatitis C virus through viral adaptation

Hepatitis C virus (HCV) species tropism is incompletely understood. We have previously shown that at the level of entry, human CD81 and occludin (OCLN) comprise the minimal set of human factors needed for viral uptake into murine cells. As an alternative approach to genetic humanization, species barriers can be overcome by adapting HCV to use the murine orthologues of these entry factors. We previously generated a murine tropic HCV (mtHCV or Jc1/mCD81) strain harboring three mutations within the viral envelope proteins that allowed productive entry into mouse cell lines. In this study, we aimed to characterize the ability of mtHCV to enter and infect mouse hepatocytes in vivo and in vitro Using a highly sensitive, Cre-activatable reporter, we demonstrate that mtHCV can enter mouse hepatocytes in vivo in the absence of any human cofactors. Viral entry still relied on expression of mouse CD81 and SCARB1 and was more efficient when mouse CD81 and OCLN were overexpressed. HCV entry could be significantly reduced in the presence of anti-HCV E2 specific antibodies, suggesting that uptake of mtHCV is dependent on viral glycoproteins. Despite mtHCV's ability to enter murine hepatocytes in vivo, we did not observe persistent infection, even in animals with severely blunted type I and III interferon signaling and impaired adaptive immune responses. Altogether, these results establish proof of concept that the barriers limiting HCV species tropism can be overcome by viral adaptation. However, additional viral adaptations will likely be needed to increase the robustness of a murine model system for hepatitis C. IMPORTANCE: At least 150 million individuals are chronically infected with HCV and are at risk of developing serious liver disease. Despite the advent of effective antiviral therapy, the frequency of chronic carriers has only marginally decreased. A major roadblock in developing a vaccine that would prevent transmission is the scarcity of animal models that are susceptible to HCV infection. It is poorly understood why HCV infects only humans and chimpanzees. To develop an animal model for hepatitis C, previous efforts focused on modifying the host environment of mice, for example, to render them more susceptible to HCV infection. Here, we attempted a complementary approach in which a laboratory-derived HCV variant was tested for its ability to infect mice. We demonstrate that this engineered HCV strain can enter mouse liver cells but does not replicate efficiently. Thus, additional adaptations are likely needed to construct a robust animal model for HCV

Targeting a host-cell entry factor barricades antiviral-resistant HCV variants from on-therapy breakthrough in human-liver mice

Objective: Direct-acting antivirals (DAAs) inhibit hepatitis C virus (HCV) infection by targeting viral proteins that play essential roles in the replication process. However, selection of resistance-associated variants (RAVs) during DAA therapy has been a cause of therapeutic failure. In this study, we wished to address whether such RAVs could be controlled by the co-administration of host-targeting entry inhibitors that prevent intrahepatic viral spread. Design: We investigated the effect of adding an entry inhibitor (the anti-scavenger receptor class B type I mAb1671) to a DAA monotherapy (the protease inhibitor ciluprevir) in human-liver mice chronically infected with HCV of genotype 1b. Clinically relevant non-laboratory strains were used to achieve viraemia consisting of a cloud of related viral variants (quasispecies) and the emergence of RAVs was monitored at high resolution using next-generation sequencing. Results: HCV-infected human-liver mice receiving DAA monotherapy rapidly experienced on-therapy viral breakthrough. Deep sequencing of the HCV protease domain confirmed the manifestation of drug-resistant mutants upon viral rebound. In contrast, none of the mice treated with a combination of the DAA and the entry inhibitor experienced on-therapy viral breakthrough, despite detection of RAV emergence in some animals. Conclusions: This study provides preclinical in vivo evidence that addition of an entry inhibitor to an anti-HCV DAA regimen restricts the breakthrough of DAA-resistant viruses. Our approach is an excellent strategy to prevent therapeutic failure caused by on-therapy rebound of DAA-RAVs. Inclusion of an entry inhibitor to the newest DAA combination therapies may further increase response rates, especially in difficult-to-treat patient populations

Tick-borne encephalitis virus and the immune response of the mammalian host

Tick-borne encephalitis (TBE) is caused by Tick-borne encephalitis virus (TBEV), one of the most prevalent arboviruses in Europe and in many parts of Asia. Transmission of TBEV to humans usually occurs by bite of an infected tick or rarely by ingestion of unpasteurized milk products of infected livestock. TBEV infection induces an innate and adaptive immune response, nevertheless it is able to replicate in several cell types of the immune system at the same time which probably contributes to the spread of the virus in the human host. Furthermore, TBEV can enter the central nervous system (CNS) by yet not well understood mechanisms via the blood brain barrier (BBB) or the olfactory neurons which leads to serious neurological disorders like meningitis, encephalitis or even meningoencephalitis. In this article we review the known facts and possible hypotheses of interaction of TBEV with components of the mammalian immune system and their implications for TBEV-mediated pathogenesis. (C) 2010 Elsevier Ltd. All rights reserved.German federal ministry of education and research (BMBF) [01KI0710

SPINE: A method for the rapid detection and analysis of protein-protein interactions in vivo

The detection and analysis of protein-protein interactions is one of the central tasks of proteomics in the postgenomic era. For this purpose, we present a procedure, the Strep-protein interaction experiment (SPINE) that combines the advantages of the Strep-tag protein purification system with those of reversible in vivo protein crosslinking by formaldehyde. Using two Bacillus subtilis regulator proteins, we demonstrate that this method is well suited to isolate protein complexes with high purity and virtually no background. Plasmids allowing the high-level expression of proteins carrying an N- or C-terminal Strep-tag in B. subtilis were constructed

Availability and Suitability of Digital Health Tools in Africa for Pandemic Control: Scoping Review and Cluster Analysis (Preprint)

BACKGROUND Gaining oversight into the rapidly growing number of mobile health tools for surveillance or outbreak management in Africa has become a challenge. OBJECTIVE The aim of this study is to map the functional portfolio of mobile health tools used for surveillance or outbreak management of communicable diseases in Africa. METHODS We conducted a scoping review by combining data from a systematic review of the literature and a telephone survey of experts. We applied the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines by searching for articles published between January 2010 and December 2020. In addition, we used the respondent-driven sampling method and conducted a telephone survey from October 2019 to February 2020 among representatives from national public health institutes from all African countries. We combined the findings and used a hierarchical clustering method to group the tools based on their functionalities (attributes). RESULTS We identified 30 tools from 1914 publications and 45 responses from 52% (28/54) of African countries. Approximately 13% of the tools (4/30; Surveillance Outbreak Response Management and Analysis System, Go.Data, CommCare, and District Health Information Software 2) covered 93% (14/15) of the identified attributes. Of the 30 tools, 17 (59%) tools managed health event data, 20 (67%) managed case-based data, and 28 (97%) offered a dashboard. Clustering identified 2 exceptional attributes for outbreak management, namely &lt;i&gt;contact follow-up&lt;/i&gt; (offered by 8/30, 27%, of the tools) and &lt;i&gt;transmission network visualization&lt;/i&gt; (offered by Surveillance Outbreak Response Management and Analysis System and Go.Data). CONCLUSIONS There is a large range of tools in use; however, most of them do not offer a comprehensive set of attributes, resulting in the need for public health workers having to use multiple tools in parallel. Only 13% (4/30) of the tools cover most of the attributes, including those most relevant for response to the COVID-19 pandemic, such as laboratory interface, contact follow-up, and transmission network visualization. CLINICALTRIAL </sec

Availability and Suitability of Digital Health Tools in Africa for Pandemic Control: Scoping Review and Cluster Analysis

Background Gaining oversight into the rapidly growing number of mobile health tools for surveillance or outbreak management in Africa has become a challenge. Objective The aim of this study is to map the functional portfolio of mobile health tools used for surveillance or outbreak management of communicable diseases in Africa. Methods We conducted a scoping review by combining data from a systematic review of the literature and a telephone survey of experts. We applied the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines by searching for articles published between January 2010 and December 2020. In addition, we used the respondent-driven sampling method and conducted a telephone survey from October 2019 to February 2020 among representatives from national public health institutes from all African countries. We combined the findings and used a hierarchical clustering method to group the tools based on their functionalities (attributes). Results We identified 30 tools from 1914 publications and 45 responses from 52% (28/54) of African countries. Approximately 13% of the tools (4/30; Surveillance Outbreak Response Management and Analysis System, Go.Data, CommCare, and District Health Information Software 2) covered 93% (14/15) of the identified attributes. Of the 30 tools, 17 (59%) tools managed health event data, 20 (67%) managed case-based data, and 28 (97%) offered a dashboard. Clustering identified 2 exceptional attributes for outbreak management, namely contact follow-up (offered by 8/30, 27%, of the tools) and transmission network visualization (offered by Surveillance Outbreak Response Management and Analysis System and Go.Data). Conclusions There is a large range of tools in use; however, most of them do not offer a comprehensive set of attributes, resulting in the need for public health workers having to use multiple tools in parallel. Only 13% (4/30) of the tools cover most of the attributes, including those most relevant for response to the COVID-19 pandemic, such as laboratory interface, contact follow-up, and transmission network visualization. </jats:sec

Inactivation and survival of hepatitis C virus on inanimate surfaces.

Hepatitis C virus (HCV) cross-contamination from inanimate surfaces or objects has been implicated in transmission of HCV in health-care settings and among injection drug users. We established HCV-based carrier and drug transmission assays that simulate practical conditions to study inactivation and survival of HCV on inanimate surfaces

Availability and suitability of digital health tools in Africa for pandemic control: scoping review and cluster analysis

Background:Gaining oversight into the rapidly growing number of mobile health tools for surveillance or outbreak management in Africa has become a challenge.Objective:The aim of this study is to map the functional portfolio of mobile health tools used for surveillance or outbreak management of communicable diseases in Africa.Methods:We conducted a scoping review by combining data from a systematic review of the literature and a telephone survey of experts. We applied the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines by searching for articles published between January 2010 and December 2020. In addition, we used the respondent-driven sampling method and conducted a telephone survey from October 2019 to February 2020 among representatives from national public health institutes from all African countries. We combined the findings and used a hierarchical clustering method to group the tools based on their functionalities (attributes).Results:We identified 30 tools from 1914 publications and 45 responses from 52% (28/54) of African countries. Approximately 13% of the tools (4/30; Surveillance Outbreak Response Management and Analysis System, Go.Data, CommCare, and District Health Information Software 2) covered 93% (14/15) of the identified attributes. Of the 30 tools, 17 (59%) tools managed health event data, 20 (67%) managed case-based data, and 28 (97%) offered a dashboard. Clustering identified 2 exceptional attributes for outbreak management, namely contact follow-up (offered by 8/30, 27%, of the tools) and transmission network visualization (offered by Surveillance Outbreak Response Management and Analysis System and Go.Data).Conclusions:There is a large range of tools in use; however, most of them do not offer a comprehensive set of attributes, resulting in the need for public health workers having to use multiple tools in parallel. Only 13% (4/30) of the tools cover most of the attributes, including those most relevant for response to the COVID-19 pandemic, such as laboratory interface, contact follow-up, and transmission network visualization

The Surveillance Outbreak Response Management and Analysis System (SORMAS): Digital Health Global Goods Maturity Assessment (Preprint)

BACKGROUND Digital health is a dynamic field that has been generating a large number of tools; many of these tools do not have the level of maturity required to function in a sustainable model. It is in this context that the concept of global goods maturity is gaining importance. Digital Square developed a global good maturity model (GGMM) for digital health tools, which engages the digital health community to identify areas of investment for global goods. The Surveillance Outbreak Response Management and Analysis System (SORMAS) is an open-source mobile and web application software that we developed to enable health workers to notify health departments about new cases of epidemic-prone diseases, detect outbreaks, and simultaneously manage outbreak response. OBJECTIVE The objective of this study was to evaluate the maturity of SORMAS using Digital Square’s GGMM and to describe the applicability of the GGMM on the use case of SORMAS and identify opportunities for system improvements. METHODS We evaluated SORMAS using the GGMM version 1.0 indicators to measure its development. SORMAS was scored based on all the GGMM indicator scores. We described how we used the GGMM to guide the development of SORMAS during the study period. GGMM contains 15 subindicators grouped into the following core indicators: (1) global utility, (2) community support, and (3) software maturity. RESULTS The assessment of SORMAS through the GGMM from November 2017 to October 2019 resulted in full completion of all subscores (10/30, (33%) in 2017; 21/30, (70%) in 2018; and 30/30, (100%) in 2019). SORMAS reached the full score of the GGMM for digital health software tools by accomplishing all 10 points for each of the 3 indicators on global utility, community support, and software maturity. CONCLUSIONS To our knowledge, SORMAS is the first electronic health tool for disease surveillance, and also the first outbreak response management tool, that has achieved a 100% score. Although some conceptual changes would allow for further improvements to the system, the GGMM already has a robust supportive effect on developing software toward global goods maturity. </sec