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Cui, Hong

Publications and source records attributed to Cui, Hong.

A multi-specific, multi-affinity antibody platform neutralizes sarbecoviruses and confers protection against SARS-CoV-2 in vivo

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), has been responsible for a global pandemic. Monoclonal antibodies (mAbs) have been used as antiviral therapeutics; however, these therapeutics have been limited in efficacy by viral sequence variability in emerging variants of concern (VOCs) and in deployment by the need for high doses. In this study, we leveraged the multi-specific, multi-affinity antibody (Multabody, MB) platform, derived from the human apoferritin protomer, to enable the multimerization of antibody fragments. MBs were shown to be highly potent, neutralizing SARS-CoV-2 at lower concentrations than their corresponding mAb counterparts. In mice infected with SARS-CoV-2, a tri-specific MB targeting three regions within the SARS-CoV-2 receptor binding domain was protective at a 30-fold lower dose than a cocktail of the corresponding mAbs. Furthermore, we showed in vitro that mono-specific MBs potently neutralize SARS-CoV-2 VOCs by leveraging augmented avidity, even when corresponding mAbs lose their ability to neutralize potently, and that tri-specific MBs expanded the neutralization breadth beyond SARS-CoV-2 to other sarbecoviruses. Our work demonstrates how avidity and multi-specificity combined can be leveraged to confer protection and resilience against viral diversity that exceeds that of traditional monoclonal antibody therapies.

60 APPLIED LIFE SCIENCES↗

Internet of Samples

Abstract Material samples are indispensable data sources in many natural science, social science, and humanity disciplines. More and more researchers recognize that samples collected in one discipline can be of great value for another. This has motivated organizations that manage a large number of samples to make their holdings accessible to the world. Currently, multiple projects are working to connect natural history and other samples managed by individual institutions or individuals into a universe of samples that follow FAIR principles. This poster reports the progress of the US NSF‐funded iSamples project, in the context of other efforts initiated by US DOE, DiSCCo, BCoN, and GBIF. By October 2021, we will also be able to present an iSamples prototype. We encourage individual organizations that hold material samples to get to know these projects and help shape these projects to realize the goal of a global linked sample cloud that connects all material samples and is accessible to all.

Richard, Stephen M.↗