Literature DB >> 28968873

Comparison of methods for phylogenetic B-cell lineage inference using time-resolved antibody repertoire simulations (AbSim).

Alexander Yermanos1, Victor Greiff1, Nike Julia Krautler2, Ulrike Menzel1, Andreas Dounas3, Enkelejda Miho1, Annette Oxenius2, Tanja Stadler1, Sai T Reddy1.   

Abstract

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 commonly utilized phylogenetic methods with regard to their accuracy in inferring antibody evolution.
RESULTS: Here, we developed AbSim, a time-resolved antibody repertoire simulation framework, which we exploited for testing the accuracy of methods for the phylogenetic reconstruction of B-cell lineages and antibody molecular evolution. AbSim enables the (i) simulation of intermediate stages of antibody sequence evolution and (ii) the modeling of immunologically relevant parameters such as duration of repertoire evolution, and the method and frequency of mutations. First, we validated that our repertoire simulation framework recreates replicates topological similarities observed in experimental sequencing data. Second, we leveraged Absim to show that current methods fail to a certain extent to predict the true phylogenetic tree correctly. Finally, we formulated simulation-validated guidelines for antibody evolution, which in the future will enable the development of accurate phylogenetic methods.
AVAILABILITY AND IMPLEMENTATION: https://cran.r-project.org/web/packages/AbSim/index.html. CONTACT: sai.reddy@ethz.ch. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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Year:  2017        PMID: 28968873     DOI: 10.1093/bioinformatics/btx533

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  17 in total

Review 1.  Integrating high-throughput screening and sequencing for monoclonal antibody discovery and engineering.

Authors:  Cristina Parola; Daniel Neumeier; Sai T Reddy
Journal:  Immunology       Date:  2017-10-30       Impact factor: 7.397

Review 2.  How repertoire data are changing antibody science.

Authors:  Claire Marks; Charlotte M Deane
Journal:  J Biol Chem       Date:  2020-05-14       Impact factor: 5.157

3.  Adaptive Immune Receptor Repertoire (AIRR) Community Guide to Repertoire Analysis.

Authors:  Susanna Marquez; Lmar Babrak; Victor Greiff; Kenneth B Hoehn; William D Lees; Eline T Luning Prak; Enkelejda Miho; Aaron M Rosenfeld; Chaim A Schramm; Ulrik Stervbo
Journal:  Methods Mol Biol       Date:  2022

Review 4.  Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies.

Authors:  Rahmad Akbar; Habib Bashour; Puneet Rawat; Philippe A Robert; Eva Smorodina; Tudor-Stefan Cotet; Karine Flem-Karlsen; Robert Frank; Brij Bhushan Mehta; Mai Ha Vu; Talip Zengin; Jose Gutierrez-Marcos; Fridtjof Lund-Johansen; Jan Terje Andersen; Victor Greiff
Journal:  MAbs       Date:  2022 Jan-Dec       Impact factor: 5.857

5.  Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification.

Authors:  Chakravarthi Kanduri; Milena Pavlović; Lonneke Scheffer; Keshav Motwani; Maria Chernigovskaya; Victor Greiff; Geir K Sandve
Journal:  Gigascience       Date:  2022-05-25       Impact factor: 7.658

Review 6.  Progress toward improved understanding of antibody maturation.

Authors:  Sandor Vajda; Kathryn A Porter; Dima Kozakov
Journal:  Curr Opin Struct Biol       Date:  2021-02-17       Impact factor: 6.809

7.  Position-Dependent Differential Targeting of Somatic Hypermutation.

Authors:  Julian Q Zhou; Steven H Kleinstein
Journal:  J Immunol       Date:  2020-11-13       Impact factor: 5.422

Review 8.  Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires.

Authors:  Enkelejda Miho; Alexander Yermanos; Cédric R Weber; Christoph T Berger; Sai T Reddy; Victor Greiff
Journal:  Front Immunol       Date:  2018-02-21       Impact factor: 7.561

Review 9.  Immune Literacy: Reading, Writing, and Editing Adaptive Immunity.

Authors:  Lucia Csepregi; Roy A Ehling; Bastian Wagner; Sai T Reddy
Journal:  iScience       Date:  2020-09-01

10.  Benchmarking Tree and Ancestral Sequence Inference for B Cell Receptor Sequences.

Authors:  Kristian Davidsen; Frederick A Matsen
Journal:  Front Immunol       Date:  2018-10-31       Impact factor: 7.561

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