Evidence map›Paper›PMID 38323813›Full record

ArticleJournal of virology2024

Extraction of the CDRH3 sequence of the mouse antibody repertoire selected upon influenza virus infection by subtraction of the background antibody repertoire.

Masashi Shingai, Sayaka Iida, Naoko Kawai, Mamiko Kawahara, Toshiki Sekiya, Marumi Ohno, Naoki Nomura, Chimuka Handabile, Tomomi Kawakita, Ryosuke Omori and 7 more

Abstract read
In one paragraph

Article in Journal of virology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Masashi Shingai *Division of Biologics Development, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan.ORCID 0000-0003-3214-4626
Sayaka Iida *Division of Bioinformatics, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan.
Naoko KawaiDivision of Collaboration and Education, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan.
Mamiko KawaharaDivision of Biologics Development, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan.
Toshiki SekiyaDivision of Biologics Development, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan.
Marumi OhnoDivision of Biologics Development, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan.ORCID 0000-0003-1086-8244
Naoki NomuraDivision of Biologics Development, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan.
Chimuka HandabileDivision of Biologics Development, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan.
Tomomi KawakitaInstitute for Vaccine Research and Development (HU-IVReD), Hokkaido University, Sapporo, Japan.
Ryosuke OmoriDivision of Bioinformatics, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan.
Junya YamagishiInternational Collaboration Unit, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan.ORCID 0000-0002-8385-5359
Kaori SanoDepartment of Pathology, National Institute of Infectious Diseases, Tokyo, Japan.
Akira AinaiDepartment of Pathology, National Institute of Infectious Diseases, Tokyo, Japan.
Tadaki SuzukiDepartment of Pathology, National Institute of Infectious Diseases, Tokyo, Japan.
Kazuo OhnishiDepartment of Immunology, National Institute of Infectious Diseases, Tokyo, Japan.
Kimihito ItoInternational Collaboration Unit, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan.ORCID 0000-0003-4986-1795
Hiroshi KidaDivision of Biologics Development, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan.ORCID 0000-0003-4876-1004

Funding

Japan Agency for Medical Research and Development (AMED) 22fk0108142Japan Agency for Medical Research and Development (AMED) 233fa827012Japan Agency for Medical Research and Development (AMED) 233fa827021Japan Agency for Medical Research and Development (AMED) 23gm1610011Japan Agency for Medical Research and Development (AMED) JP19fm0108008Japan Agency for Medical Research and Development (AMED) JP223fa627005Japan Agency for Medical Research and Development (AMED) JP23wm0125008MEXT | Japan Society for the Promotion of Science (JSPS) 17K15367MEXT | Japan Society for the Promotion of Science (JSPS) 18K07135MEXT | Japan Society for the Promotion of Science (JSPS) 21H02376MEXT | Japan Society for the Promotion of Science (JSPS) 21H03490MEXT | Japan Society for the Promotion of Science (JSPS) 22K15483MEXT | Japan Society for the Promotion of Science (JSPS) 23K15362MEXT | Japan Society for the Promotion of Science (JSPS) F01Ministry of Education, Culture, Sports, Science and Technology (MEXT) 1801
6 · The paper itself

Abstract

Historically, antibody reactivity to pathogens and vaccine antigens has been evaluated using serological measurements of antigen-specific antibodies. However, it is difficult to evaluate all antibodies that contribute to various functions in a single assay, such as the measurement of the neutralizing antibody titer. Bulk antibody repertoire analysis using next-generation sequencing is a comprehensive method for analyzing the overall antibody response; however, it is unreliable for estimating antigen-specific antibodies due to individual variation. To address this issue, we propose a method to subtract the background signal from the repertoire of data of interest. In this study, we analyzed changes in antibody diversity and inferred the heavy-chain complementarity-determining region 3 (CDRH3) sequences of antibody clones that were selected upon influenza virus infection in a mouse model using bulk repertoire analysis. A decrease in the diversity of the antibody repertoire was observed upon viral infection, along with an increase in neutralizing antibody titers. Using kernel density estimation of sequences in a high-dimensional sequence space with background signal subtraction, we identified several clusters of CDRH3 sequences induced upon influenza virus infection. Most of these repertoires were detected more frequently in infected mice than in uninfected control mice, suggesting that infection-specific antibody sequences can be extracted using this method. Such an accurate extraction of antigen- or infection-specific repertoire information will be a useful tool for vaccine evaluation in the future. IMPORTANCE: As specific interactions between antigens and cell-surface antibodies trigger the proliferation of B-cell clones, the frequency of each antibody sequence in the samples reflects the size of each clonal population. Nevertheless, it is extremely difficult to extract antigen-specific antibody sequences from the comprehensive bulk antibody sequences obtained from blood samples due to repertoire bias influenced by exposure to dietary antigens and other infectious agents. This issue can be addressed by subtracting the background noise from the post-immunization or post-infection repertoire data. In the present study, we propose a method to quantify repertoire data from comprehensive repertoire data. This method allowed subtraction of the background repertoire, resulting in more accurate extraction of expanded antibody repertoires upon influenza virus infection. This accurate extraction of antigen- or infection-specific repertoire information is a useful tool for vaccine evaluation.

Indexed as

Antibodies, ViralOrthomyxoviridaeOrthomyxoviridae InfectionsAnimalsAntibodies, NeutralizingB-LymphocytesClone CellsComplementarity Determining RegionsInfluenza VaccinesMiceAntibodies, NeutralizingAntibodies, ViralComplementarity Determining RegionsInfluenza Vaccinesantibody repertoireinfluenza virus

Identifiers

PMID38323813
PMCPMC10949447

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.