The ongoing COVID-19 pandemic has prioritized the development of small animal models for SARS-CoV-2. Herein, we adapted a clinical isolate of SARS-CoV-2 by serial passaging in the respiratory tract of aged BALB/c mice. The resulting mouse-adapted strain at passage 6 (termed MASCp6) showed increased infectivity in mouse lung, and led to interstitial pneumonia and inflammatory responses in both young and aged mice following intranasal inoculation. Deep sequencing revealed a panel of adaptive mutations potentially associated with the increased virulence. In particular, the N501Y mutation is located at the receptor binding domain (RBD) of the spike protein. The protective efficacy of a recombinant RBD vaccine candidate was validated using this model. Thus, this mouse-adapted strain and associated challenge model should be of value in evaluating vaccines and antivirals against SARS-CoV-2.

The process of epithelial-to-mesenchymal transition (EMT) is an essential type of cellular plasticity associated with a change from epithelial cells that function as a barrier consisting of a sheet of tightly connected cells to cells with properties of mesenchyme that are not attached to their neighbors and are highly motile. This phenotypic change occurs during development and also contributes to pathological processes, such as cancer progression. The molecular mechanisms controlling the switch between the fully epithelial and fully mesenchymal phenotypes and cells that have characteristics of both (partial EMT) are controversial, and multiple theoretical models have been proposed. To test these theoretical models, we systematically measured the changes in the abundance of proteins, mRNAs, and microRNAs (miRNAs) that represent the core regulators of EMT induced by transforming growth factor-β1 (TGF-β1) in the human breast epithelial cell line MCF10A at the population and single-cell levels. We provide experimental confirmation for a model of cascading switches in phenotypes associated with TGF-β1-induced EMT of MCF10A cells that involves two double-negative feedback loops: one between the transcription factor SNAIL1 and the miR-34 family and another between the transcription factor ZEB1 and the miR-200 family. Furthermore, our data showed that whereas the transition from epithelial to partial EMT was reversible for MCF10A cells, the transition from partial EMT to mesenchymal was mostly irreversible at high concentrations of TGF-β1.

Summary Background The COVID-19 pandemic could lead to disruptions to provision of HIV services for people living with HIV and those at risk of acquiring HIV in sub-Saharan Africa, where UNAIDS estimated that more than two-thirds of the approximately 38 million people living with HIV resided in 2018. We aimed to predict the potential effects of such disruptions on HIV-related deaths and new infections in sub-Saharan Africa. Methods In this modelling study, we used five well described models of HIV epidemics (Goals, Optima HIV, HIV Synthesis, an Imperial College London model, and Epidemiological MODeling software [EMOD]) to estimate the effect of various potential disruptions to HIV prevention, testing, and treatment services on HIV-related deaths and new infections in sub-Saharan Africa lasting 6 months over 1 year from April 1, 2020. We considered scenarios in which disruptions affected 20%, 50%, and 100% of the population. Findings A 6-month interruption of supply of antiretroviral therapy (ART) drugs across 50% of the population of people living with HIV who are on treatment would be expected to lead to a 1·63 times (median across models; range 1·39–1·87) increase in HIV-related deaths over a 1-year period compared with no disruption. In sub-Saharan Africa, this increase amounts to a median excess of HIV deaths, across all model estimates, of 296 000 (range 229 023–420 000) if such a high level of disruption occurred. Interruption of ART would increase mother-to-child transmission of HIV by approximately 1·6 times. Although an interruption in the supply of ART drugs would have the largest impact of any potential disruptions, effects of poorer clinical care due to overstretched health facilities, interruptions of supply of other drugs such as co-trimoxazole, and suspension of HIV testing would all have a substantial effect on population-level mortality (up to a 1·06 times increase in HIV-related deaths over a 1-year period due to disruptions affecting 50% of the population compared with no disruption). Interruption to condom supplies and peer education would make populations more susceptible to increases in HIV incidence, although physical distancing measures could lead to reductions in risky sexual behaviour (up to 1·19 times increase in new HIV infections over a 1-year period if 50% of people are affected). Interpretation During the COVID-19 pandemic, the primary priority for governments, donors, suppliers, and communities should focus on maintaining uninterrupted supply of ART drugs for people with HIV to avoid additional HIV-related deaths. The provision of other HIV prevention measures is also important to prevent any increase in HIV incidence. Funding Bill & Melinda Gates Foundation.

No abstract

We developed a dynamic forecasting model for Zika virus (ZIKV), based on real-time online search data from Google Trends (GTs). It was designed to provide Zika virus disease (ZVD) surveillance and detection for Health Departments, and predictive numbers of infection cases, which would allow them sufficient time to implement interventions. In this study, we found a strong correlation between Zika-related GTs and the cumulative numbers of reported cases (confirmed, suspected and total cases; p<0.001). Then, we used the correlation data from Zika-related online search in GTs and ZIKV epidemics between 12 February and 20 October 2016 to construct an autoregressive integrated moving average (ARIMA) model (0, 1, 3) for the dynamic estimation of ZIKV outbreaks. The forecasting results indicated that the predicted data by ARIMA model, which used the online search data as the external regressor to enhance the forecasting model and assist the historical epidemic data in improving the quality of the predictions, are quite similar to the actual data during ZIKV epidemic early November 2016. Integer-valued autoregression provides a useful base predictive model for ZVD cases. This is enhanced by the incorporation of GTs data, confirming the prognostic utility of search query based surveillance. This accessible and flexible dynamic forecast model could be used in the monitoring of ZVD to provide advanced warning of future ZIKV outbreaks.

Middle East respiratory syndrome coronavirus (MERS-CoV) is a highly pathogenic virus with a crude mortality rate of ~35%. Previously, we established a human DPP4 transgenic (hDPP4-Tg) mouse model in which we studied complement overactivation-induced immunopathogenesis. Here, to better understand the pathogenesis of MERS-CoV, we studied the role of pyroptosis in THP-1 cells and hDPP4 Tg mice with MERS-CoV infection. We found that MERS-CoV infection induced pyroptosis and over-activation of complement in human macrophages. The hDPP4-Tg mice infected with MERS-CoV overexpressed caspase-1 in the spleen and showed high IL-1β levels in serum, suggesting that pyroptosis occurred after infection. However, when the C5a-C5aR1 axis was blocked by an anti-C5aR1 antibody (Ab), expression of caspase-1 and IL-1β fell. These data indicate that MERS-CoV infection induces overactivation of complement, which may contribute to pyroptosis and inflammation. Pyroptosis and inflammation were suppressed by inhibiting C5aR1. These results will further our understanding of the pathogenesis of MERS-CoV infection.

Epithelial ovarian cancer (EOC) is the most lethal and aggressive gynecological malignancy, and abnormal cellular metabolism significantly contributes to cancer onset and progression. Here, we report that miR-29b negatively regulates AKT2/AKT3 expression, causing HK2/PKM2 downregulation and leading to a decreased Warburg effect and slowed ovarian cancer progression. Compared to normal ovaries, ovaries with epithelial cancer exhibited lower miR-29b expression at both cellular/histological levels. Glucose consumption and lactate production experiments confirmed miR-29b's regulation of EOC metabolism. A luciferase reporter assay confirmed the direct binding of miR-29b to AKT2/AKT3 3′ UTRs. miR-29b silencing correlated with increased expression of AKT2/3, pAKT2/3, HK2, and PKM2. Pyruvic acid and NAD+/NADH levels also changed when miR-29b expression was suppressed; this effect could be blocked by specific AKT inhibitors, suggesting the miR-29b-AKT axis regulates the Warburg effect in ovarian cancer. In xenograft mouse models, miR-29b inhibited tumor formation in vivo. In vivo imaging also demonstrated that miR-29b agomir inhibited the relative uptake of 18F-FDG in the xenograft tumors, suggesting that miR-29b over-expression could negatively modulate tumor glucose metabolism in vivo. Taken together, our study suggests that miR-29b regulates the Warburg effect in EOC via AKT2/AKT3 and may provide novel options for future treatments for EOC.

Background: Transforming growth factor beta 1 (TGFβ1) can induce epithelial-mesenchymal transition (EMT) in various human cancers, but the complex mechanisms underlying this have not been fully elucidated. Inhibitor of DNA binding 1 (Id-1) has been identified as a novel marker of ovarian cancer progression. This study aims to investigate the role of Id-1 in TGFβ1-induced EMT in human ovarian cancer cells. Methods: Ovarian cancer cells expressing or not expressing Id-1 were incubated with TGFβ1. Changes in the EMT markers E-cadherin, vimentin, N-cadherin, Id-1, and miR-29b were detected using western blotting and qPCR analyses. Wound healing, transwell migration, and invasion assays were performed in cells where Id-1 was either knocked down or overexpressed. The effects of transfecting miR-29b mimics and inhibitors on Id-1 mRNA and protein expression were assessed. The interaction between miR-29b and Id-1 was confirmed using a luciferase reporter assay. Results: Id-1 expression was increased and miR-29b expression was repressed in TGFβ1-responsive ovarian cancer cells. Id-1 overexpression increases and Id-1 knockdown decreases cell migration and invasion capacities. Id-1 silencing leads to a partial blocking of TGFβ1-induced EMT. miR-29b negatively regulates Id-1 expression. Direct binding of miR-29b to the 3'UTR region of Id-1 was confirmed using a luciferase reporter assay. Conclusion: Id-1, a protein repressed by miR-29b, facilitates TGFβ1-induced EMT in human ovarian cancer cells and represents a promising therapeutic target for treating ovarian cancer.