Refine Search

New Search

Results: 3

(searched for: doi:10.1186/s12862-020-01732-2)
Save to Scifeed
Page of 1
Articles per Page
by
Show export options
  Select all
, , Tyler N. Starr, Roberta Marzi, Alexandra C. Walls, Fabrizia Zatta, John E. Bowen, , , Zhaoqian Wang, et al.
Published: 8 April 2021
Abstract:
The recent emergence of SARS-CoV-2 variants of concern (VOC) and the recurrent spillovers of coronaviruses in the human population highlight the need for broadly neutralizing antibodies that are not affected by the ongoing antigenic drift and that can prevent or treat future zoonotic infections. Here, we describe a human monoclonal antibody (mAb), designated S2×259, recognizing a highly conserved cryptic receptor-binding domain (RBD) epitope and cross-reacting with spikes from all sarbecovirus clades. S2×259 broadly neutralizes spike-mediated entry of SARS-CoV-2 including the B.1.1.7, B.1.351, P.1 and B.1.427/B.1.429 VOC, as well as a wide spectrum of human and zoonotic sarbecoviruses through inhibition of ACE2 binding to the RBD. Furthermore, deep-mutational scanning and in vitro escape selection experiments demonstrate that S2×259 possesses a remarkably high barrier to the emergence of resistance mutants. We show that prophylactic administration of S2×259 protects Syrian hamsters against challenges with the prototypic SARS-CoV-2 and the B.1.351 variant, suggesting this mAb is a promising candidate for the prevention and treatment of emergent VOC and zoonotic infections. Our data unveil a key antigenic site targeted by broadly-neutralizing antibodies and will guide the design of pan-sarbecovirus vaccines.
Ruibang Luo, Agnès Delaunay‐Moisan, Kenneth Timmis,
Published: 26 March 2021
by Wiley
Environmental Microbiology, Volume 23, pp 2339-2363; doi:10.1111/1462-2920.15487

Abstract:
The global propagation of SARS‐CoV‐2 and the detection of a large number of variants, some of which have replaced the original clade to become dominant, underscores the fact that the virus is actively exploring its evolutionary space. The longer high levels of viral multiplication occur – permitted by high levels of transmission –, the more the virus can adapt to the human host and find ways tosuccess. The third wave of the COVID‐19 pandemic is starting in different parts of the world, emphasizing that transmission containment measures that are being imposed are not adequate. Part of the consideration in determining containment measures is the rationale that vaccination will soon stop transmission and allow a return to normality. However, vaccines themselves represent a selection pressure for evolution of vaccine‐resistant variants, so the coupling of a policy of permitting high levels of transmission/virus multiplication during vaccine roll‐out with the expectation that vaccines will deal with the pandemic, is unrealistic. In the absence of effective antivirals, it is not improbable that SARS‐CoV‐2 infection prophylaxis will involve an annual vaccination campaign against “dominant” viral variants, similar to influenza prophylaxis. Living with COVID‐19 will be an issue of SARS‐CoV‐2 variants and evolution. It is therefore crucial to understand how SARS‐CoV‐2 evolves and what constrains its evolution, in order to anticipate the variants that will emerge. Thus far, the focus has been on the receptor‐binding spike protein, but the virus is complex, encoding 26 proteins which interact with a large number of host factors, so the possibilities for evolution are manifold and not predictable a priori. However, if we are to mount the best defence against COVID‐19, we must mount it against the variants, and to do this, we must have knowledge about the evolutionary possibilities of the virus. In addition to the generic cellular interactions of the virus, there are extensive polymorphisms in humans (e.g. Lewis, HLA, etc.), some distributed within most or all populations, some restricted to specific ethnic populations, and these variations pose additional opportunities for/constraints on viral evolution. We now have the wherewithal – viral genome sequencing, protein structure determination/modelling, protein interaction analysis – to functionally characterise viral variants, but access to comprehensive genome data is extremely uneven. Yet, to develop an understanding of the impacts of such evolution on transmission and disease, we must link it to transmission (viral epidemiology) and disease data (patient clinical data), and the population granularities of these. In this editorial, we explore key facets of viral biology and the influence of relevant aspects of human polymorphisms, human behaviour, geography and climate and, based on this, derive a series of recommendations to monitor viral evolution and predict the types of variants that are likely to arise.
International Journal of Environmental Research and Public Health, Volume 18; doi:10.3390/ijerph18052461

Abstract:
The COVID-19 pandemic has spread widely around the world. Many mathematical models have been proposed to investigate the inflection point (IP) and the spread pattern of COVID-19. However, no researchers have applied social network analysis (SNA) to cluster their characteristics. We aimed to illustrate the use of SNA to identify the spread clusters of COVID-19. Cumulative numbers of infected cases (CNICs) in countries/regions were downloaded from GitHub. The CNIC patterns were extracted from SNA based on CNICs between countries/regions. The item response model (IRT) was applied to create a general predictive model for each country/region. The IP days were obtained from the IRT model. The location parameters in continents, China, and the United States were compared. The results showed that (1) three clusters (255, n = 51, 130, and 74 in patterns from Eastern Asia and Europe to America) were separated using SNA, (2) China had a shorter mean IP and smaller mean location parameter than other counterparts, and (3) an online dashboard was used to display the clusters along with IP days for each country/region. Spatiotemporal spread patterns can be clustered using SNA and correlation coefficients (CCs). A dashboard with spread clusters and IP days is recommended to epidemiologists and researchers and is not limited to the COVID-19 pandemic.
Page of 1
Articles per Page
by
Show export options
  Select all
Back to Top Top