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1.
biorxiv; 2020.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2020.09.11.294363

ABSTRACT

Increasing age is the strongest predictor of risk of COVID-19 severity. Unregulated cytokine storm together with impaired immunometabolic response leads to highest mortality in elderly infected with SARS-CoV-2. To investigate how aging compromises defense against COVID-19, we developed a model of natural murine beta coronavirus (mCoV) infection with mouse hepatitis virus strain MHV-A59 (mCoV-A59) that recapitulated majority of clinical hallmarks of COVID-19. Aged mCoV-A59-infected mice have increased mortality and higher systemic inflammation in the heart, adipose tissue and hypothalamus, including neutrophilia and loss of {gamma}{delta} T cells in lungs. Ketogenic diet increases beta-hydroxybutyrate, expands tissue protective {gamma}{delta} T cells, deactivates the inflammasome and decreases pathogenic monocytes in lungs of infected aged mice. These data underscore the value of mCoV-A59 model to test mechanism and establishes harnessing of the ketogenic immunometabolic checkpoint as a potential treatment against COVID-19 in the elderly. Highlights - Natural MHV-A59 mouse coronavirus infection mimics COVID-19 in elderly. - Aged infected mice have systemic inflammation and inflammasome activation - Murine beta coronavirus (mCoV) infection results in loss of pulmonary {gamma}{delta} T cells. - Ketones protect aged mice from infection by reducing inflammation. eTOC BlurbElderly have the greatest risk of death from COVID-19. Here, Ryu et al report an aging mouse model of coronavirus infection that recapitulates clinical hallmarks of COVID-19 seen in elderly. The increased severity of infection in aged animals involved increased inflammasome activation and loss of {gamma}{delta} T cells that was corrected by ketogenic diet.


Subject(s)
Lung Diseases , Chemical and Drug Induced Liver Injury , Hypothalamic Neoplasms , COVID-19 , Inflammation
2.
biorxiv; 2020.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2020.09.12.294413

ABSTRACT

The coronavirus disease 2019 (COVID-19) is triggered by severe acute respiratory syndrome mediated by coronavirus 2 (SARS-CoV-2) infection and was declared by WHO as a major international public health concern. While worldwide efforts are being advanced towards vaccine development, the structural modeling of TCR-pMHC (T Cell Receptor-peptide-bound Major Histocompatibility Complex) regarding SARS-CoV-2 epitopes and the design of effective T cell vaccine based on these antigens are still unresolved. Here, we present both pMHC and TCR-pMHC interfaces to infer peptide epitopes of the SARS-CoV-2 proteins. Accordingly, significant TCR-pMHC templates (Z-value cutoff > 4) along with interatomic interactions within the SARS-CoV-2-derived hit peptides were clarified. Also, we applied the structural analysis of the hit peptides from different coronaviruses to highlight a feature of evolution in SARS-CoV-2, SARS-CoV, bat-CoV, and MERS-CoV. Peptide-protein flexible docking between each of the hit peptides and their corresponding MHC molecules were performed, and a multi-hit peptides vaccine against the S and N glycoprotein of SARS-CoV-2 was designed. Filtering pipelines including antigenicity, and also physiochemical properties of designed vaccine were then evaluated by different immunoinformatics tools. Finally, vaccine-structure modeling and immune simulation of the desired vaccine were performed aiming to create robust T cell immune responses. We anticipate that our design based on the T cell antigen epitopes and the frame of the immunoinformatics analysis could serve as valuable supports for the development of COVID-19 vaccine.


Subject(s)
COVID-19 , Severe Acute Respiratory Syndrome , Respiratory Insufficiency , Coronavirus Infections
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