Habib Bashour

Oslo University Hospital

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Victor Greiff

University of Oslo

Jose Gutierrez‐Marcos

University of Warwick

Rahmad Akbar

Oslo University Hospital

Puneet Rawat

Oslo University Hospital

Maria Chernigovskaya

University of Oslo

Khang Lê Quý

Oslo University Hospital

Geir Kjetil Sandve

University of Oslo

Jan Terje Andersen

University of Oslo

Andrei Slabodkin

Oslo University Hospital

Igor Snapkov

Norwegian Institute of Public Health

Cooperative Institutions

University of Oslo

Oslo University Hospital

Hospital Del Mar

Hospital del Mar Research Institute

Universitat de Barcelona

657 Oslo

Icahn School of Medicine at Mount Sinai

Hospital Sant Joan de Déu Barcelona

Pompeu Fabra University

Barcelona Biomedical Research Park

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Publisher Correction: Adaptive immune receptor repertoire analysis

Nature Reviews Methods Primers (2024)

Vanessa Mhanna Habib Bashour Khang Lê Quý Pierre Barennes Puneet Rawat

In the version of the article initially published, there were errors in Figs.1234.In Fig. 1, in the upper box, "CDR3" initially appeared as "CDR2" and "IGLJ(10)" read "IGLV( 10)".In the lower box, "TRBD" was missing from above "CDR3".In Fig. 2a, "class-switch recombination" originally read "class switching".In Fig. 3d, the uppermost arrow, " + /-UMI" and the lower "MTPX PCR" were all missing, and the second instance of " + /-UMI" appeared as "UMI".In Fig. 4c, the AIRR 1 image was missing the TCR from the surface of one of the cells.

Immune receptor

10.1038/s43586-024-00299-2

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Individualized VDJ recombination predisposes the available Ig sequence space

Genome Research (2021)

Andrei Slabodkin Maria Chernigovskaya Ivana Mikocziova Rahmad Akbar Lonneke Scheffer

The process of recombination between variable (V), diversity (D), and joining (J) immunoglobulin (Ig) gene segments determines an individual's naive Ig repertoire and, consequently, (auto)antigen recognition. VDJ recombination follows probabilistic rules that can be modeled statistically. So far, it remains unknown whether VDJ recombination rules differ between individuals. If these rules differed, identical (auto)antigen-specific Ig sequences would be generated with individual-specific probabilities, signifying that the available Ig sequence space is individual specific. We devised a sensitivity-tested distance measure that enables inter-individual comparison of VDJ recombination models. We discovered, accounting for several sources of noise as well as allelic variation in Ig sequencing data, that not only unrelated individuals but also human monozygotic twins and even inbred mice possess statistically distinguishable immunoglobulin recombination models. This suggests that, in addition to genetic, there is also nongenetic modulation of VDJ recombination. We demonstrate that population-wide individualized VDJ recombination can result in orders of magnitude of difference in the probability to generate (auto)antigen-specific Ig sequences. Our findings have implications for immune receptor-based individualized medicine approaches relevant to vaccination, infection, and autoimmunity.

V(D)J recombination

Immunogenetics

Antibody Repertoire

10.1101/gr.275373.121

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Citations (31)

Adaptive immune receptor repertoire analysis

Nature Reviews Methods Primers (2024)

Vanessa Mhanna Habib Bashour Khang Lê Quý Pierre Barennes Puneet Rawat

Immune receptor

10.1038/s43586-023-00284-1

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Citations (11)

Individualized VDJ recombination predisposes the available Ig sequence space

bioRxiv (Cold Spring Harbor Laboratory) (2021)

Andrei Slabodkin Maria Chernigovskaya Ivana Mikocziova Rahmad Akbar Lonneke Scheffer

Abstract The process of recombination between variable (V), diversity (D), and joining (J) immunoglobulin (Ig) gene segments determines an individual’s naïve Ig repertoire, and consequently (auto)antigen recognition. VDJ recombination follows probabilistic rules that can be modeled statistically. So far, it remains unknown whether VDJ recombination rules differ between individuals. If these rules differed, identical (auto)antigen-specific Ig sequences would be generated with individual-specific probabilities, signifying that the available Ig sequence space is individual-specific. We devised a sensitivity-tested distance measure that enables inter-individual comparison of VDJ recombination models. We discovered, accounting for several sources of noise as well as allelic variation in Ig sequencing data, that not only unrelated individuals but also human monozygotic twins and even inbred mice possess statistically distinguishable immunoglobulin recombination models. This suggests that, in addition to genetic, there is also non-genetic modulation of VDJ recombination. We demonstrate that population-wide individualized VDJ recombination can result in orders of magnitude of difference in the probability to generate (auto)antigen-specific Ig sequences. Our findings have implications for immune receptor-based individualized medicine approaches relevant to vaccination, infection, and autoimmunity.

V(D)J recombination

Immunogenetics

Sequence (biology)

Antibody Repertoire

10.1101/2021.04.19.440409

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Citations (11)

Biophysical cartography of the native and human-engineered antibody landscapes quantifies the plasticity of antibody developability

Communications Biology (2024)

Habib Bashour Eva Smorodina Matteo Pariset Jahn Zhong Rahmad Akbar

Designing effective monoclonal antibody (mAb) therapeutics faces a multi-parameter optimization challenge known as "developability", which reflects an antibody's ability to progress through development stages based on its physicochemical properties. While natural antibodies may provide valuable guidance for mAb selection, we lack a comprehensive understanding of natural developability parameter (DP) plasticity (redundancy, predictability, sensitivity) and how the DP landscapes of human-engineered and natural antibodies relate to one another. These gaps hinder fundamental developability profile cartography. To chart natural and engineered DP landscapes, we computed 40 sequence- and 46 structure-based DPs of over two million native and human-engineered single-chain antibody sequences. We find lower redundancy among structure-based compared to sequence-based DPs. Sequence DP sensitivity to single amino acid substitutions varied by antibody region and DP, and structure DP values varied across the conformational ensemble of antibody structures. We show that sequence DPs are more predictable than structure-based ones across different machine-learning tasks and embeddings, indicating a constrained sequence-based design space. Human-engineered antibodies localize within the developability and sequence landscapes of natural antibodies, suggesting that human-engineered antibodies explore mere subspaces of the natural one. Our work quantifies the plasticity of antibody developability, providing a fundamental resource for multi-parameter therapeutic mAb design. Analysis of 2 million native antibodies reveals that human-engineered antibodies form subspaces of the natural developability space. This large-scale analysis allows the quantification of developability plasticity, accelerating antibody drug design.

Sequence (biology)

Protein Engineering

10.1038/s42003-024-06561-3

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Citations (6)

Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies

mAbs (2022)

Rahmad Akbar Habib Bashour Puneet Rawat Philippe A. Robert Eva Smorodina

Although the therapeutic efficacy and commercial success of monoclonal antibodies (mAbs) are tremendous, the design and discovery of new candidates remain a time and cost-intensive endeavor. In this regard, progress in the generation of data describing antigen binding and developability, computational methodology, and artificial intelligence may pave the way for a new era of in silico on-demand immunotherapeutics design and discovery. Here, we argue that the main necessary machine learning (ML) components for an in silico mAb sequence generator are: understanding of the rules of mAb-antigen binding, capacity to modularly combine mAb design parameters, and algorithms for unconstrained parameter-driven in silico mAb sequence synthesis. We review the current progress toward the realization of these necessary components and discuss the challenges that must be overcome to allow the on-demand ML-based discovery and design of fit-for-purpose mAb therapeutic candidates.

10.1080/19420862.2021.2008790

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Citations (77)

Atypical memory B cells form a pre-plasmacellular reservoir for steady-state IgD responses to common nasopharyngeal antigens

bioRxiv (Cold Spring Harbor Laboratory) (2023)

Roser Tachó‐Piñot Habib Bashour Martyna Filipska Sonia Tejedor Vaquero Leire de Campos‐Mata

Abstract The human nasopharyngeal mucosa includes organized lymphoepithelial structures continually engaged in frontline immune responses to aerodigestive antigens. Advancing our understanding of these responses might lead to the development of new strategies for the prevention and treatment of common immune disorders such as allergies. Here we identified a hitherto elusive tonsillar subset of atypical IgD class-switched IgD + IgM - memory (IgD-ME) B cells that were clonally related to IgD + IgM − germinal center (IgD-GC) B cells and IgD-secreting IgD + IgM − plasma cells (IgD-PCs) but not anergic IgD + IgM − B cells. Consistent with their pre-plasmacellular properties, IgD-ME B cells served as preferential precursors of IgD-PCs over IgD-GC B cells. IgD antibodies from IgD + IgM − cells acquired reactivity to multiple oral, airborne and commensal antigens through a mutation-dependent pathway involving both innate and adaptive signals. Thus, IgD-ME B cells may form a ready-to-use pre-plasmacellular reservoir for steady-state IgD responses likely aimed at enhancing nasopharyngeal homeostasis. One Sentence Summary Tonsillar atypical memory B cells form a ready-to-use pre-plasmacellular repertoire for IgD responses to common aerodigestive antigens.

Immunoglobulin D

B-1 cell

Memory B cell

10.1101/2023.08.29.554748

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Biophysical cartography of the native and human-engineered antibody landscapes quantifies the plasticity of antibody developability

bioRxiv (Cold Spring Harbor Laboratory) (2023)

Habib Bashour Eva Smorodina Matteo Pariset Jahn Zhong Rahmad Akbar

Abstract Designing effective monoclonal antibody (mAb) therapeutics faces a multi-parameter optimization challenge known as “developability”, which reflects an antibody’s ability to progress through development stages based on its physicochemical properties. While natural antibodies may provide valuable guidance for mAb selection, we lack a comprehensive understanding of natural developability parameter (DP) plasticity (redundancy, predictability, sensitivity) and how the DP landscapes of human-engineered and natural antibodies relate to one another. These gaps hinder fundamental developability profile cartography. To chart natural and engineered DP landscapes, we computed 40 sequence- and 46 structure-based DPs of over two million native and human-engineered single-chain antibody sequences. We found lower redundancy among structure-based compared to sequence-based DPs. Sequence DP sensitivity to single amino acid substitutions varied by antibody region and DP, and structure DP values varied across the conformational ensemble of antibody structures. Sequence DPs were more predictable than structure-based ones across different machine-learning tasks and embeddings, indicating a constrained sequence-based design space. Human-engineered antibodies were localized within the developability and sequence landscapes of natural antibodies, suggesting that human-engineered antibodies explore mere subspaces of the natural one. Our work quantifies the plasticity of antibody developability, providing a fundamental resource for multi-parameter therapeutic mAb design.

Sequence (biology)

Protein Engineering

10.1101/2023.10.26.563958

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Citations (2)