Institut für Medizintechnik und Medizininformatik

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Thema: search.filters.subject.B-cell receptor

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  • Vorschaubild
    Publikation
    Maturation of the human B-cell receptor repertoire with age
    (Cold Spring Harbor Laboratory, 20.12.2019) Ghraichy, Marie; Galson, Jacob D.; Kovaltsuk, Aleksandr; Niederhäusern, Valentin von; Schmid, Jana Pachlopnik; Recher, Mike; Jauch, Annaïse J; Miho, Enkelejda; Kelly, Dominic F.; Deane, Charlotte M.; Trück, Johannes
    B cells play a central role in adaptive immune processes, mainly through the production of antibodies. The maturation of the B-cell system with age is poorly studied. We extensively investigated age-related alterations of naïve and antigen-experienced B-cell receptor (BCR) repertoires. The most significant changes were observed in the first 10 years of life, and were characterized by altered immunoglobulin gene usage and an increased frequency of mutated antibodies structurally diverging from their germline precursors. Older age was associated with an increased usage of downstream constant region genes and fewer antibodies with self-reactive properties. As mutations accumulated with age, the frequency of germline-encoded self-reactive antibodies decreased, indicating a possible beneficial role of self-reactive B-cells in the developing immune system. Our results suggest a continuous process of change through childhood across a broad range of parameters characterizing BCR repertoires and stress the importance of using well-selected, age-appropriate controls in BCR studies
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Adaptive immune receptor repertoire (AIRR) community guide to TR and IG gene annotation
    (Springer, 28.05.2022) Babrak, Lmar; Marquez, Susanna; Busse, Christian; Lees, William; Miho, Enkelejda; Ohlin, Mats; Rosenfeld, Aaron; Stervbo, Ulrik; Watson, Corey; Schramm, Chaim; Langerak, Anton W.
    High-throughput sequencing of adaptive immune receptor repertoires (AIRR, i.e., IG and TR) has revolutionized the ability to carry out large-scale experiments to study the adaptive immune response. Since the method was first introduced in 2009, AIRR sequencing (AIRR-Seq) has been applied to survey the immune state of individuals, identify antigen-specific or immune-state-associated signatures of immune responses, study the development of the antibody immune response, and guide the development of vaccines and antibody therapies. Recent advancements in the technology include sequencing at the single-cell level and in parallel with gene expression, which allows the introduction of multi-omics approaches to understand in detail the adaptive immune response. Analyzing AIRR-seq data can prove challenging even with high-quality sequencing, in part due to the many steps involved and the need to parameterize each step. In this chapter, we outline key factors to consider when preprocessing raw AIRR-Seq data and annotating the genetic origins of the rearranged receptors. We also highlight a number of common difficulties with common AIRR-seq data processing and provide strategies to address them.
    04A - Beitrag Sammelband
  • Vorschaubild
    Publikation
    Prospective artificial intelligence to dissect the dengue immune response and discover therapeutics
    (Frontiers, 15.06.2021) Natali, Eriberto; Babrak, Lmar; Miho, Enkelejda
    Dengue virus (DENV) poses a serious threat to global health as the causative agent of dengue fever. The virus is endemic in more than 128 countries resulting in approximately 390 million infection cases each year. Currently, there is no approved therapeutic for treatment nor a fully efficacious vaccine. The development of therapeutics is confounded and hampered by the complexity of the immune response to DENV, in particular to sequential infection with different DENV serotypes (DENV1–5). Researchers have shown that the DENV envelope (E) antigen is primarily responsible for the interaction and subsequent invasion of host cells for all serotypes and can elicit neutralizing antibodies in humans. The advent of high-throughput sequencing and the rapid advancements in computational analysis of complex data, has provided tools for the deconvolution of the DENV immune response. Several types of complex statistical analyses, machine learning models and complex visualizations can be applied to begin answering questions about the B- and T-cell immune responses to multiple infections, antibody-dependent enhancement, identification of novel therapeutics and advance vaccine research.
    01A - Beitrag in wissenschaftlicher Zeitschrift