Dataset Information

Influenza Virus-Specific Human Antibody Repertoire Studies.

ABSTRACT: The diversity of Ag-specific adaptive receptors on the surface of B cells and in the population of secreted Abs is enormous, but increasingly, we are acquiring the technical capability to interrogate Ab repertoires in great detail. These Ab technologies have been especially pointed at understanding the complex issues of immunity to infection and disease caused by influenza virus, one of the most common and vexing medical problems in man. Influenza immunity is particularly interesting as a model system because the antigenic diversity of influenza strains and proteins is high and constantly evolving. Discovery of canonical features in the subset of the influenza repertoire response that is broadly reactive for diverse influenza strains has spurred the recent optimism for creating universal influenza vaccines. Using new technologies for sequencing Ab repertoires at great depth is helping us to understand the central features of influenza immunity.

SUBMITTER: Crowe JE

PROVIDER: S-EPMC6327975 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Publications

Influenza Virus-Specific Human Antibody Repertoire Studies.

Crowe James E JE

Journal of immunology (Baltimore, Md. : 1950) 20190101 2

The diversity of Ag-specific adaptive receptors on the surface of B cells and in the population of secreted Abs is enormous, but increasingly, we are acquiring the technical capability to interrogate Ab repertoires in great detail. These Ab technologies have been especially pointed at understanding the complex issues of immunity to infection and disease caused by influenza virus, one of the most common and vexing medical problems in man. Influenza immunity is particularly interesting as a model ...[more]

PMID: 30617118

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Project description: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.ImportanceAs 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.

Project description:BackgroundVaccines dramatically affect an individual's adaptive immune system and thus provide an excellent means to study human immunity. Upon vaccination, the B cells that express antibodies (Abs) that happen to bind the vaccine are stimulated to proliferate and undergo mutagenesis at their Ab locus. This process may alter the composition of B cell lineages within an individual, which are known collectively as the antibody repertoire (AbR). Antibodies are also highly expressed in whole blood, potentially enabling RNA sequencing (RNA-seq) technologies to query this diversity. Less is known about the diversity of AbR responses across individuals to a given vaccine and if individuals tend to yield a similar response to the same antigenic stimulus.MethodsHere we implement a bioinformatic pipeline that extracts the AbR information from a time-series RNA-seq dataset of five patients who were administered a seasonal trivalent influenza vaccine (TIV). We harness the detailed time-series nature of this dataset and use methods based in functional data analysis (FDA) to identify the Abs that respond to the vaccine. We then design and implement rigorous statistical tests in order to ask whether or not these patients exhibit a convergent AbR response to the same TIV.ResultsWe find that high-resolution time-series data can be used to help identify the Abs that respond to an antigenic stimulus and that this response can exhibit a convergent nature across patients inoculated with the same vaccine. However, correlations in AbR diversity among individuals prior to inoculation can confound inference of a convergent signal unless it is taken into account.ConclusionsWe developed a framework to identify the elements of an AbR that respond to an antigen. This information could be used to understand the diversity of different immune responses in different individuals, as well as to gauge the effectiveness of the immune response to a given stimulus within an individual. We also present a framework for testing a convergent hypothesis between AbRs; a hypothesis that is more difficult to test than previously appreciated. Our discovery of a convergent signal suggests that similar epitopes do select for antibodies with similar sequence characteristics.

Dataset Information

Influenza Virus-Specific Human Antibody Repertoire Studies.

Publications

Influenza Virus-Specific Human Antibody Repertoire Studies.

Similar Datasets

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