Generation of a single-cell B cell atlas of antibody repertoires and transcriptomes to identify signatures associated with antigen specificity

Agrafiotis, Andreas; Neumeier, Daniel; Hong, Kai‐Lin; Chowdhury, Tasnia; Ehling, Roy; Kuhn, Raphael; Sandu, Ioana; Kreiner, Victor; Cotet, Tudor-Stefan; Shlesinger, Danielle; Laslo, Daria; Anzböck, Stine; Starkie, Dale; Lightwood, Daniel; Oxenius, Annette; Yermanos, Alexander

doi:10.1016/j.isci.2023.106055

Cited by 8 publications

(3 citation statements)

References 89 publications

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“…Next, we explored whether transcriptional heterogeneity could similarly be detected for B cells present in PlatypusDB. Multiple datasets derived from murine models of infection, immunization, and autoimmune disease ( Merkenschlager et al 2021 , Yewdell et al 2021 , Neumeier et al 2022 , Shlesinger et al 2022 , Agrafiotis et al 2023 ) were integrated as previously performed with T cells ( Supplementary Fig. S1 and Supplementary Table S3 ).…”

Section: Usage and Applicationmentioning

confidence: 99%

ePlatypus: an ecosystem for computational analysis of immunogenomics data

Cotet,

Agrafiotis,

Kreiner

et al. 2023

Bioinformatics

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Motivation The maturation of systems immunology methodologies requires novel and transparent computational frameworks capable of integrating diverse data modalities in a reproducible manner. Results Here, we present the ePlatypus computational immunology ecosystem for immunogenomics data analysis, with a focus on adaptive immune repertoires and single-cell sequencing. ePlatypus is an open-source web-based platform and provides programming tutorials and an integrative database that helps elucidate signatures of B and T cell clonal selection. Furthermore, the ecosystem links novel and established bioinformatics pipelines relevant for single-cell immune repertoires and other aspects of computational immunology such as predicting ligand-receptor interactions, structural modeling, simulations, machine learning, graph theory, pseudotime, spatial transcriptomics and phylogenetics. The ePlatypus ecosystem helps extract deeper insight in computational immunology and immunogenomics and promote open science. Availability Platypus code used in this manuscript can be found at github.com/alexyermanos/Platypus. Supplementary information Supplementary data are available at Bioinformatics online.

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Section: Usage and Applicationmentioning

confidence: 99%

ePlatypus: an ecosystem for computational analysis of immunogenomics data

Cotet,

Agrafiotis,

Kreiner

et al. 2023

Bioinformatics

Self Cite

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“…A comprehensive understanding of the B cell repertoire is especially crucial towards the rational design of improved vaccines and also can provide insights into developing new diagnostic tools 22 . To date, single-cell sequencing methods have been previously adapted to perform single B cell RNA sequencing in humans and mice 23 – 27 . However, these methods typically do not translate to other important animal species, mainly due to differences in the viability and distribution of B cells, diversity of B cell markers, diversity of immunoglobulin genes and lack of large data analysis methods available to analyze the diversity of immunoglobulin transcripts from various animals.…”

Section: Introductionmentioning

confidence: 99%

Parallel single B cell transcriptomics to elucidate pig B cell repertoire

Bram,

Lindsey,

Drnevich

et al. 2024

Sci Rep

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Pork is the most widely consumed meat on the planet, placing swine health as a critical factor for both the world economy and the food industry. Infectious diseases in pigs not only threaten these sectors but also raise zoonotic concerns, as pigs can act as “mixing vessels” for several animals and human viruses and can lead to the emergence of new viruses that are capable of infecting humans. Several efforts are ongoing to develop pig vaccines, albeit with limited success. This has been largely attributed to the complex nature of pig infections and incomplete understanding of the pig immune responses. Additionally, pig has been suggested to be a good experimental model to study viral infections (e.g., human influenza). Despite the significant importance of studying pig immunology for developing infection models, zoonosis, and the crucial need to develop better swine vaccines, there is still very limited information on the response of the swine adaptive immune system to several emerging pathogens. Particularly, very little is known about the pig B cell repertoire upon infection. Understanding the B cell repertoire is especially crucial towards designing better vaccines, predicting zoonosis and can provide insights into developing new diagnostic agents. Here, we developed methods for performing parallel single pig B cell (up to 10,000 B cells) global and immunoglobulin transcriptome sequencing. We then adapted a computational pipeline previously built for human/mouse sequences, to now analyze pig sequences. This allowed us to comprehensively map the B cell repertoire and get paired antibody sequences from pigs in a single parallel sequencing experiment. We believe that these approaches will have significant implications for swine diseases, particularly in the context of swine mediated zoonosis and swine and human vaccine development.

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“…1). Identifying B cell receptors (BCRs) that respond to specific antigens is an important goal for describing the dynamics of B cell immunity following vaccination, with potential applications in vaccine development [1][2][3][4][5][6], personalized medicine [7][8][9], and antibody-derived therapeutics [10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Computational detection of antigen specific B cell receptors following immunization

Abbate,

Dupic,

Vigne

et al. 2023

Preprint

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B cell receptors (BCRs) play a crucial role in recognizing and fighting foreign antigens. High-throughput sequencing enables in-depth sampling of the BCRs repertoire after immunization. However, only a minor fraction of BCRs actively participate in any given infection. To what extent can we accurately identify antigen-specific sequences directly from BCRs repertoires? We present a computational method grounded on sequence similarity, aimed at identifying statistically significant responsive BCRs. This method leverages well-known characteristics of affinity maturation and expected diversity. We validate its effectiveness using longitudinally sampled human immune repertoire data following influenza vaccination and Sars-CoV-2 infections. We show that different lineages converge to the same responding CDR3, demonstrating convergent selection within an individual. The outcomes of this method hold promise for application in vaccine development, personalized medicine, and antibody-derived therapeutics.

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Generation of a single-cell B cell atlas of antibody repertoires and transcriptomes to identify signatures associated with antigen specificity

Cited by 8 publications

References 89 publications

ePlatypus: an ecosystem for computational analysis of immunogenomics data

ePlatypus: an ecosystem for computational analysis of immunogenomics data

Parallel single B cell transcriptomics to elucidate pig B cell repertoire

Computational detection of antigen specific B cell receptors following immunization

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