Kobinger, G. | Search bioRxiv

bioRxiv2021

Development and characterization of influenza M2 ectodomain and/or HA stalk-based DC-targeting vaccines for different influenza infections

A universal influenza vaccine is required for broad protection against influenza infection. Here, we revealed the efficacy of novel influenza vaccine candidates based on Ebola glycoprotein (EboGP) DC-targeting domain (E{Delta}M) fusion protein technology. We fused influenza hemagglutinin stalk (HAcs) and extracellular matrix protein (M2e) or four copies of M2e (referred to as tetra M2e (tM2e)) with E{Delta}M to generate E{Delta}M-HM2e or E{Delta}M-tM2e, respectively, and revealed that E{Delta}M facilitates DC/macrophage targeting in vitro. In a mouse study, E{Delta}M-HM2e- or E{Delta}M-tM2e-pseudotyped viral particles (PVPs) induced significantly higher titers of anti-HA and/or anti-M2e antibodies. We also developed recombinant vesicular stomatitis virus (rVSV)-E{Delta}M-HM2e and rVSV-E{Delta}M-tM2e vaccines that resulted in rapid and potent induction of HA and/or M2 antibodies in mouse sera and mucosa. Importantly, vaccination protects mice from influenza H1N1 and H3N2 challenges. Taken together, our study suggests that recombinant rVSV-E{Delta}M-HM2e and rVSV-E{Delta}M-tM2e are efficacious and protective universal vaccines against influenza.

microbiology↗

bioRxiv2020

COVID-19: Viral-host interactome analyzed by network based-approach model to study pathogenesis of SARS-CoV-2 infection.

BackgroundEpidemiological, virological and pathogenetic characteristics of SARS-CoV-2 infection are under evaluation. A better understanding of the pathophysiology associated with COVID-19 is crucial to improve treatment modalities and to develop effective prevention strategies. Transcriptomic and proteomic data on the host response against SARS-CoV-2 still have anecdotic character; currently available data from other coronavirus infections are therefore a key source of information. MethodsWe investigated selected molecular aspects of three human coronavirus (HCoV) infections, namely SARS-CoV, MERS-CoV and HCoV-229E, through a network based-approach. A functional analysis of HCoV-host interactome was carried out in order to provide a theoretic host-pathogen interaction model for HCoV infections and in order to translate the results in prediction for SARS-CoV-2 pathogenesis. The 3D model of S-glycoprotein of SARS-CoV-2 was compared to the structure of the corresponding SARS-CoV, HCoV-229E and MERS-CoV S-glycoprotein. SARS-CoV, MERS-CoV, HCoV-229E and the host interactome were inferred through published protein-protein interactions (PPI) as well as gene co-expression, triggered by HCoV S-glycoprotein in host cells. ResultsAlthough the amino acid sequences of the S-glycoprotein were found to be different between the various HCoV, the structures showed high similarity, but the best 3D structural overlap shared by SARS-CoV and SARS-CoV-2, consistent with the shared ACE2 predicted receptor. The host interactome, linked to the S-glycoprotein of SARS-CoV and MERS-CoV, mainly highlighted innate immunity pathway components, such as Toll Like receptors, cytokines and chemokines. ConclusionsIn this paper, we developed a network-based model with the aim to define molecular aspects of pathogenic phenotypes in HCoV infections. The resulting pattern may facilitate the process of structure-guided pharmaceutical and diagnostic research with the prospect to identify potential new biological targets.

bioinformatics↗