key: cord-0841044-nvkzhkb9
authors: Miyamoto, Sho; Arashiro, Takeshi; Adachi, Yu; Moriyama, Saya; Kinoshita, Hitomi; Kanno, Takayuki; Saito, Shinji; Katano, Harutaka; Iida, Shun; Ainai, Akira; Kotaki, Ryutaro; Yamada, Souichi; Kuroda, Yudai; Yamamoto, Tsukasa; Ishijima, Keita; Park, Eun-Sil; Inoue, Yusuke; Kaku, Yoshihiro; Tobiume, Minoru; Iwata-Yoshikawa, Naoko; Shiwa-Sudo, Nozomi; Tokunaga, Kenzo; Ozono, Seiya; Hemmi, Takuya; Ueno, Akira; Kishida, Noriko; Watanabe, Shinji; Nojima, Kiyoko; Seki, Yohei; Mizukami, Takuo; Hasegawa, Hideki; Ebihara, Hideki; Ken, Maeda; Fukushi, Shuetsu; Takahashi, Yoshimasa; Suzuki, Tadaki
title: Vaccination-infection interval determines cross-neutralization potency to SARS-CoV-2 Omicron after breakthrough infection by other variants
date: 2022-03-04
journal: Med (N Y)
DOI: 10.1016/j.medj.2022.02.006
sha: fdaad09b1a897c0a04b9a9579081d542e2b4546c
doc_id: 841044
cord_uid: nvkzhkb9

Background The immune profile against SARS-CoV-2 has dramatically diversified due to a complex combination of exposure to vaccines and infection by various lineages/variants, likely generating a heterogeneity in protective immunity in a given population. To further complicate this, the Omicron variant, with numerous spike mutations, has emerged. These circumstances have created the need to assess the potential of immune evasion by the Omicron in individuals with various immune histories. Methods The neutralization susceptibility of the variants including the Omicron and their ancestor was comparably assessed using a panel of plasma/serum derived from individuals with divergent immune histories. Blood samples were collected from either mRNA vaccinees or from those who suffered from breakthrough infections by the Alpha/Delta with multiple time intervals following vaccination. Findings The Omicron was highly resistant to neutralization in fully vaccinated individuals without a history of breakthrough infections. In contrast, robust cross-neutralization against the Omicron were induced in vaccinees that experienced breakthrough infections. The time interval between vaccination and infection, rather than the variant types of infection, was significantly correlated with the magnitude and potency of Omicron-neutralizing antibodies. Conclusions Immune histories with breakthrough infections can overcome the resistance to infection by the Omicron, with the vaccination-infection interval being the key determinant of the magnitude and breadth of neutralization. The diverse exposure history in each individual warrants a tailored and cautious approach to understanding population immunity against the Omicron and future variants. Funding This study was supported by grants from the Japan Agency for Medical Research and Development (AMED).

and cross-neutralization potency against SARS-CoV-2 variants 16 . To investigate the neutralizing activity 122 against the Omicron variant using sera from individuals who had mRNA vaccine breakthrough infections 123 due to non-Omicron variants, convalescent sera (obtained 10-22 days after infection with Alpha or Delta 124 variant; Table S1 ) were examined in VSV pseudovirus-based and live-virus neutralization assays. In the 125 pseudovirus-based neutralization assay, neutralizing activity against the Delta variant was elevated 126 compared to that against the ancestral virus and was particularly pronounced in those with breakthrough 127 infection with the Delta variant (Figure 2A and 2C). In contrast, the neutralizing activity against Beta or 128

Omicron variants was markedly lower than that against the ancestral virus in the VSV pseudovirus-based 129 neutralization assay, with a 3.8-fold or 9.7-fold decrease for Beta or Omicron variants, respectively ( Figure  130 2A). In the live-virus neutralization assay, the neutralizing activity of the two isolates of the Omicron 131 variant was also reduced by approximately 10-fold compared to that against the ancestral virus ( Figure  132 2B). In contrast to the sera of mRNA vaccinees without breakthrough infections, we detected neutralizing 133 activity against the Omicron variant in most sera of individuals with breakthrough infections in both assays, 134 and there were large individual variations in the degree of reduction in neutralizing activity compared to 135 the ancestral virus. Notably, some sera from individuals with breakthrough infections showed high cross-136 neutralizing activity and neutralized the Omicron variant to a level comparable to that of the other variants. 137

In addition, the cross-neutralizing activity against the Omicron variant tended to be higher in sera from 138 individuals with the Delta breakthrough infections than that from the Alpha breakthrough infections 139 

To understand the factors contributing to the high heterogeneity of cross-neutralizing activity against 154 variants in sera from breakthrough cases, we evaluated the relationship between neutralizing activity 155 against each variant and time between vaccine completion and breakthrough infection in each case. 156

Intriguingly, in both pseudovirus-based and live-virus assays, the neutralizing activity against the ancestral 157 virus and each variant, including Omicron, increased as the time between vaccination and breakthrough 158 infection increased ( Figure 3A-3L) . Notably, the degree of correlation between neutralizing activity and 159 the vaccination-to-infection interval tended to be stronger for Beta and Omicron variants, which were 160 antigenically shifted from the ancestral virus ( Figure 3C , 3E, 3I, 3K, and 3L). These trends did not differ 161 significantly between sera after breakthrough infection with Alpha and Delta variants, except for 162 neutralizing activity against the Delta variant. The neutralizing activity against the Delta variant by the 163 sera obtained after Delta variant breakthrough infection showed a completely different trend from that of 164 J o u r n a l P r e -p r o o f other serum-virus combinations ( Figure 3D and 3J). Considering the effect of age on the cross-neutralizing 165 activity against SARS-CoV-2, we excluded elderly patients whose sera were obtained only with a short 166 interval between vaccination and breakthrough infection, and evaluated only sera obtained from patients 167 younger than 60 years. We found a positive correlation between cross-neutralization activity against 168 SARS-CoV-2 variants and the interval between vaccination and breakthrough infection, similar to the 169 results described above (Figure S1A-S1H). In addition, to evaluate the effect of the presence or absence 170 of symptoms on cross-neutralizing activity, we compared the neutralizing activity between subjects with 171 and without symptoms, but there was no significant difference in the neutralizing activity for each variant 172 between subjects with and without symptoms ( Figure S1I and S1J). To assess the quality of neutralizing activity by distinguishing the antibodies with a high neutralizing 177 potency from those with a lower potency which might be present in abundance, the neutralization potency 178 index (NPI), which represents the average of the neutralization potencies of individual antibodies 17 , was 179 estimated in the sera from individuals who had breakthrough infections. The IgG titer of antibody against 180 the RBD of the Omicron variant was greatly reduced by more than 40-fold compared to that of the ancestral 181 virus ( Figure 4A ). Notably, as the interval between vaccination and infection increased, the IgG titer of 182 antibody recognizing the RBD of the ancestral virus did not change whereas the IgG titer of antibodies 183 against the Omicron variant RBD increased, suggesting that IgG antibodies recognizing the Omicron RBD 184

were readily induced as this period extended ( Figure 4B ). The NPI against the ancestral virus, D614G, 185

Alpha, Beta, Delta, and Omicron variants was then calculated by dividing the neutralization titer to each 186 neutralizing activity determined in pseudovirus-based and live-virus assays, and the NPI calculated in both 188 assays demonstrated a significant increase in the Omicron variant compared with the ancestral virus 189 ( Figure 4C and 4D) . Furthermore, evaluation of the relationship between NPI against the Omicron variant 190 and vaccination-to-infection interval showed that, as with neutralizing activity, NPI was positively 191 correlated with vaccination-to-infection interval: the longer the interval, the higher the NPI and the higher 192 the quality of antibodies produced ( Figure 4E , 4F, and 4G). These results suggest that high-quality as their ancestral strain 19 . 227

In this study, we demonstrated that longer intervals between vaccination and breakthrough infection 228 All data reported in this paper will be shared by the lead contact upon request. 425

This study did not generate any new codes. 426

Any additional information required to reanalyze the data reported in this work paper is available from 427 the Lead Contact upon request. 428

The characteristics of the participants in this study are summarized in Table S1 . Human plasma samples 432 for the use of human subjects (Approval numbers 1178, 1275, 1316, and 1321) . 457

The SARS-CoV-2 ancestral strain WK-521 (lineage A, GISAID ID: EPI_ISL_408667), D614G strain QH- Cell Bank) were maintained in low glucose DMEM (Fujifilm) containing 10% heat-inactivated fetal 478 bovine serum (Biowest), 1 mg/mL geneticin (Thermo Fisher Scientific), and 100 U/mL 479

The VSV pseudovirus bearing SARS-CoV-2 spike proteins was generated as previously described 31 . were performed in multiple independent laboratories within NIID to confirm the findings, with 542 adjustments made using rabbit sera immunized with RBD (ancestral strain). Since sera from individuals 543 who suffered from breakthrough infections were limited in quantity, the assay was performed once. All 544 experiments using authentic viruses were performed in a biosafety level 3 laboratory at NIID, Japan. 545

Data analysis and visualization were performed using GraphPad Prism software. For statistical analysis, 549 one-way ANOVA with Dunnett's test and two-way ANOVA with Sidak's test were used to compare the 550 titers. The Pearson correlation coefficient was used to assess correlations between titers and time intervals. The table highlights the reagents, genetically modified organisms and strains, cell lines, software, instrumentation, and source data essential to reproduce results presented in the manuscript. Depending on the nature of the study, this may include standard laboratory materials (i.e., food chow for metabolism studies, support material for catalysis studies), but the table is not meant to be a comprehensive list of all materials and resources used (e.g., essential chemicals such as standard solvents, SDS, sucrose, or standard culture media do not need to be listed in the table). Items in the table must also be reported in the method details section within the context of their use. To maximize readability, the number of oligonucleotides and RNA sequences that may be listed in the table is restricted to no more than 10 each. If there are more than 10 oligonucleotides or RNA sequences to report, please provide this information as a supplementary document and reference the file (e.g., See Table S1 for XX) in the key resources table.

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• REAGENT or RESOURCE: Provide full descriptive name of the item so that it can be identified and linked with its description in the manuscript (e.g., provide version number for software, host source for antibody, strain name). In the experimental models section (applicable only to experimental life science studies), please include all models used in the paper and describe each line/strain as: model organism: name used for strain/line in paper: genotype. (i.e., Mouse: OXTR fl/fl : B6.129(SJL)-Oxtr tm1.1Wsy/J ). In the biological samples section (applicable only to experimental life science studies), please list all samples obtained from commercial sources or biological repositories. Please note that software mentioned in the methods details or data and code availability section needs to also be included in the table. See the sample tables at the end of this document for examples of how to report reagents.

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