Greiff, Victor

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Greiff, Victor

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2015 - 20194
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Enddatum: 2019 × Dateien dazu vorhanden?: Nein ×

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    Publikation
    Augmenting adaptive immunity. Progress and challenges in the quantitative engineering and analysis of adaptive immune receptor repertoires
    (Royal Society of Chemistry, 2019) Brown, Alex J.; Snapkov, Igor; Akbar, Rahmad; Pavlović, Milena; Miho, Enkelejda; Sandve, Geir K.; Greiff, Victor [in: Molecular Systems Design & Engineering]
    The adaptive immune system is a natural diagnostic sensor and therapeutic. It recognizes threats earlier than clinical symptoms manifest and neutralizes antigens with exquisite specificity. Recognition specificity and broad reactivity are enabled via adaptive B- and T-cell receptors: the immune receptor repertoire. The human immune system, however, is not omnipotent. Our natural defense system sometimes loses the battle to parasites and microbes and even turns against us in the case of cancer and (autoimmune) inflammatory disease. A long-standing dream of immunoengineers has been, therefore, to mechanistically understand how the immune system “sees”, “reacts” and “remembers” (auto)antigens. Only very recently, experimental and computational methods have achieved sufficient quantitative resolution to start querying and engineering adaptive immunity with high precision. Specifically, these innovations have been applied with the greatest fervency and success in immunotherapy, autoimmunity and vaccine design. The work here highlights advances, challenges and future directions of quantitative approaches which seek to advance the fundamental understanding of immunological phenomena, and reverse engineer the immune system to produce auspicious biopharmaceutical drugs and immunodiagnostics. Our review shows how the merger of fundamental immunology, computational immunology and (digital) biotechnology advances both immunological knowledge and immunoengineering methodologies.
    01A - Beitrag in wissenschaftlicher Zeitschrift
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    Publikation
    Learning the high-dimensional immunogenomic features that predict public and private antibody repertoires
    (American Association of Immunologists, 15.10.2017) Greiff, Victor; Weber, Cédric R.; Palme, Johannes; Bodenhofer, Ulrich; Miho, Enkelejda; Menzel, Ulrike; Reddy, Sai T. [in: Journal of Immunology]
    Recent studies have revealed that immune repertoires contain a substantial fraction of public clones, which may be defined as Ab or TCR clonal sequences shared across individuals. It has remained unclear whether public clones possess predictable sequence features that differentiate them from private clones, which are believed to be generated largely stochastically. This knowledge gap represents a lack of insight into the shaping of immune repertoire diversity. Leveraging a machine learning approach capable of capturing the high-dimensional compositional information of each clonal sequence (defined by CDR3), we detected predictive public clone and private clone–specific immunogenomic differences concentrated in CDR3’s N1–D–N2 region, which allowed the prediction of public and private status with 80% accuracy in humans and mice. Our results unexpectedly demonstrate that public, as well as private, clones possess predictable high-dimensional immunogenomic features. Our support vector machine model could be trained effectively on large published datasets (3 million clonal sequences) and was sufficiently robust for public clone prediction across individuals and studies prepared with different library preparation and high-throughput sequencing protocols. In summary, we have uncovered the existence of high-dimensional immunogenomic rules that shape immune repertoire diversity in a predictable fashion. Our approach may pave the way for the construction of a comprehensive atlas of public mouse and human immune repertoires with potential applications in rational vaccine design and immunotherapeutics.
    01A - Beitrag in wissenschaftlicher Zeitschrift
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    Publikation
    Comparison of methods for phylogenetic B-cell lineage inference using time-resolved antibody repertoire simulations (AbSim)
    (Oxford University Press, 31.08.2017) Yermanos, Alexander; Greiff, Victor; Krautler, Nike Julia; Menzel, Ulrike; Dounas, Andreas; Miho, Enkelejda; Oxenius, Annette; Stadler, Tanja; Reddy, Sai T.; Kelso, Janet [in: Bioinformatics]
    Motivation: The evolution of antibody repertoires represents a hallmark feature of adaptive B-cell immunity. Recent advancements in high-throughput sequencing have dramatically increased the resolution to which we can measure the molecular diversity of antibody repertoires, thereby offering for the first time the possibility to capture the antigen-driven evolution of B cells. However, there does not exist a repertoire simulation framework yet that enables the comparison of com monly utilized phylogenetic methods with regard to their accuracy in inferring antibody evolution.
    01A - Beitrag in wissenschaftlicher Zeitschrift
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    Publikation
    Bioinformatic and statistical analysis of adaptive immune repertoires
    (Cell Press, 10/2015) Greiff, Victor; Miho, Enkelejda; Menzel, Ulrike; Reddy, Sai T. [in: Trends in Immunology]
    High-throughput sequencing (HTS) of immune repertoires has enabled the quantitative analysis of adaptive immune responses and offers the potential to revolutionize research in lymphocyte biology, vaccine profiling, and mono clonal antibody engineering. Advances in sequencing technology coupled to an exponential decline in sequencing costs have fueled the recent over whelming interest in immune repertoire sequencing. This, in turn, has sparked the development of numerous methods for bioinformatic and statistics-driven interpretation and visualization of immune repertoires. Here, we review the current literature on bioinformatic and statistical analysis of immune reper toire HTS data and discuss underlying assumptions, applicability, and scope. We further highlight important directions for future research, which could propel immune repertoire HTS to becoming a standard method for measuring adaptive immune responses.
    01A - Beitrag in wissenschaftlicher Zeitschrift