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Agrati, C.

Publications and source records attributed to Agrati, C..

2 recordsLinked to original sources

Identification of neutralizing human monoclonal antibodies from Italian Covid-19 convalescent patients

In the absence of approved drugs or vaccines, there is a pressing need to develop tools for therapy and prevention of Covid-19. Human monoclonal antibodies have very good probability of being safe and effective tools for therapy and prevention of SARS-CoV-2 infection and disease. Here we describe the screening of PBMCs from seven people who survived Covid-19 infection to isolate human monoclonal antibodies against SARS-CoV-2. Over 1,100 memory B cells were single-cell sorted using the stabilized prefusion form of the spike protein and incubated for two weeks to allow natural production of antibodies. Supernatants from each cell were tested by ELISA for spike protein binding, and positive antibodies were further tested for neutralization of spike binding to receptor(s) on Vero E6 cells and for virus neutralization in vitro. From the 1,167 memory B specific for SARS-CoV-2, we recovered 318 B lymphocytes expressing human monoclonals recognizing the spike protein and 74 of these were able to inhibit the binding of the spike protein to the receptor. Finally, 17 mAbs were able to neutralize the virus when assessed for neutralization in vitro. Lead candidates to progress into the drug development pipeline will be selected from the panel of neutralizing antibodies identified with the procedure described in this study. One Sentence SummaryNeutralizing human monoclonal antibodies isolated from Covid-19 convalescent patients for therapeutic and prophylactic interventions.

immunology

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