Biology subjects

Arakawa, A.

Publications and source records attributed to Arakawa, A..

3 recordsLinked to original sources

bioRxiv2021

The SARS-CoV-2 Delta variant is poised to acquire complete resistance to wild-type spike vaccines

mRNA-based vaccines provide effective protection against most common SARS-CoV-2 variants. However, identifying likely breakthrough variants is critical for future vaccine development. Here, we found that the Delta variant completely escaped from anti-N-terminal domain (NTD) neutralizing antibodies, while increasing responsiveness to anti-NTD infectivity-enhancing antibodies. Although Pfizer-BioNTech BNT162b2-immune sera neutralized the Delta variant, when four common mutations were introduced into the receptor binding domain (RBD) of the Delta variant (Delta 4+), some BNT162b2-immune sera lost neutralizing activity and enhanced the infectivity. Unique mutations in the Delta NTD were involved in the enhanced infectivity by the BNT162b2-immune sera. Sera of mice immunized by Delta spike, but not wild-type spike, consistently neutralized the Delta 4+ variant without enhancing infectivity. Given the fact that a Delta variant with three similar RBD mutations has already emerged according to the GISAID database, it is necessary to develop vaccines that protect against such complete breakthrough variants.

microbiology↗

bioRxiv2020

An infectivity-enhancing site on the SARS-CoV-2 spike protein is targeted by COVID-19 patient antibodies

SARS-CoV-2 infection causes severe symptoms in a subset of patients, suggesting the presence of certain unknown risk factors. Although antibodies against the receptor-binding domain (RBD) of the SARS-CoV-2 spike have been shown prevent SARS-CoV-2 infection, the effects of antibodies against other spike protein domains are largely unknown. Here, we screened a series of anti-spike monoclonal antibodies from COVID-19 patients, and found that some of antibodies against the N-terminal domain (NTD) dramatically enhanced the binding capacity of the spike protein to ACE2, and thus increased SARS-CoV2 infectivity. Surprisingly, mutational analysis revealed that all the infectivity-enhancing antibodies recognized a specific site on the surface of the NTD. The antibodies against this infectivity-enhancing site were detected in all samples of hospitalized COVID-19 patients in the study. However, the ratio of infectivity-enhancing antibodies to neutralizing antibodies differed among patients. Furthermore, the antibodies against the infectivity-enhancing site were detected in 3 out of 48 uninfected donors, albeit at low levels. These findings suggest that the production of antibodies against SARS-CoV-2 infectivity-enhancing site could be considered as a possible exacerbating factors for COVID-19 and that a spike protein lacking such antibody epitopes may be required for safe vaccine development, especially for individuals with pre-existing enhancing antibodies.

microbiology↗

bioRxiv2019

Tunings for leapfrog integration of Hamiltonian Monte Carlo for estimating genetic parameters

A Hamiltonian Monte Carlo algorithm is a Markov Chain Monte Carlo method that is considered more effective than the conventional Gibbs sampling method. Hamiltonian Monte Carlo is based on Hamiltonian dynamics, and it follows Hamiltons equations, which are expressed as two differential equations. In the sampling process of Hamiltonian Monte Carlo, a numerical integration method called leapfrog integration is used to approximately solve Hamiltons equations, and the integration is required to set the number of discrete time steps and the integration stepsize. These two parameters require some amount of tuning and calibration for effective sampling. In this study, we applied the Hamiltonian Monte Carlo method to animal breeding data and identified the optimal tunings of leapfrog integration for normal and inverse chi-square distributions. Then, using real pig data, we revealed the properties of the Hamiltonian Monte Carlo method with the optimal tuning by applying models including variance explained by pedigree information or genomic information. Compared with the Gibbs sampling method, the Hamiltonian Monte Carlo method had superior performance in both models. We have provided the source codes of this method written in the R language.

genetics↗