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IgTreeZ, A Toolkit for Immunoglobulin Gene Lineage Tree-Based Analysis, Reveals CDR3s Are Crucial for Selection Analysis
Somatic hypermutation (SHM) is an important diversification mechanism that plays a part in the creation of immune memory. Immunoglobulin (Ig) variable region gene lineage trees were used over the last four decades to model SHM and the selection mechanisms operating on B cell clones. We hereby presen...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9643157/ https://www.ncbi.nlm.nih.gov/pubmed/36389731 http://dx.doi.org/10.3389/fimmu.2022.822834 |
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author | Neuman, Hadas Arrouasse, Jessica Kedmi, Meirav Cerutti, Andrea Magri, Giuliana Mehr, Ramit |
author_facet | Neuman, Hadas Arrouasse, Jessica Kedmi, Meirav Cerutti, Andrea Magri, Giuliana Mehr, Ramit |
author_sort | Neuman, Hadas |
collection | PubMed |
description | Somatic hypermutation (SHM) is an important diversification mechanism that plays a part in the creation of immune memory. Immunoglobulin (Ig) variable region gene lineage trees were used over the last four decades to model SHM and the selection mechanisms operating on B cell clones. We hereby present IgTreeZ (Immunoglobulin Tree analyZer), a python-based tool that analyses many aspects of Ig gene lineage trees and their repertoires. Using simulations, we show that IgTreeZ can be reliably used for mutation and selection analyses. We used IgTreeZ on empirical data, found evidence for different mutation patterns in different B cell subpopulations, and gained insights into antigen-driven selection in corona virus disease 19 (COVID-19) patients. Most importantly, we show that including the CDR3 regions in selection analyses – which is only possible if these analyses are lineage tree-based – is crucial for obtaining correct results. Overall, we present a comprehensive lineage tree analysis tool that can reveal new biological insights into B cell repertoire dynamics. |
format | Online Article Text |
id | pubmed-9643157 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96431572022-11-15 IgTreeZ, A Toolkit for Immunoglobulin Gene Lineage Tree-Based Analysis, Reveals CDR3s Are Crucial for Selection Analysis Neuman, Hadas Arrouasse, Jessica Kedmi, Meirav Cerutti, Andrea Magri, Giuliana Mehr, Ramit Front Immunol Immunology Somatic hypermutation (SHM) is an important diversification mechanism that plays a part in the creation of immune memory. Immunoglobulin (Ig) variable region gene lineage trees were used over the last four decades to model SHM and the selection mechanisms operating on B cell clones. We hereby present IgTreeZ (Immunoglobulin Tree analyZer), a python-based tool that analyses many aspects of Ig gene lineage trees and their repertoires. Using simulations, we show that IgTreeZ can be reliably used for mutation and selection analyses. We used IgTreeZ on empirical data, found evidence for different mutation patterns in different B cell subpopulations, and gained insights into antigen-driven selection in corona virus disease 19 (COVID-19) patients. Most importantly, we show that including the CDR3 regions in selection analyses – which is only possible if these analyses are lineage tree-based – is crucial for obtaining correct results. Overall, we present a comprehensive lineage tree analysis tool that can reveal new biological insights into B cell repertoire dynamics. Frontiers Media S.A. 2022-10-26 /pmc/articles/PMC9643157/ /pubmed/36389731 http://dx.doi.org/10.3389/fimmu.2022.822834 Text en Copyright © 2022 Neuman, Arrouasse, Kedmi, Cerutti, Magri and Mehr https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Neuman, Hadas Arrouasse, Jessica Kedmi, Meirav Cerutti, Andrea Magri, Giuliana Mehr, Ramit IgTreeZ, A Toolkit for Immunoglobulin Gene Lineage Tree-Based Analysis, Reveals CDR3s Are Crucial for Selection Analysis |
title | IgTreeZ, A Toolkit for Immunoglobulin Gene Lineage Tree-Based Analysis, Reveals CDR3s Are Crucial for Selection Analysis |
title_full | IgTreeZ, A Toolkit for Immunoglobulin Gene Lineage Tree-Based Analysis, Reveals CDR3s Are Crucial for Selection Analysis |
title_fullStr | IgTreeZ, A Toolkit for Immunoglobulin Gene Lineage Tree-Based Analysis, Reveals CDR3s Are Crucial for Selection Analysis |
title_full_unstemmed | IgTreeZ, A Toolkit for Immunoglobulin Gene Lineage Tree-Based Analysis, Reveals CDR3s Are Crucial for Selection Analysis |
title_short | IgTreeZ, A Toolkit for Immunoglobulin Gene Lineage Tree-Based Analysis, Reveals CDR3s Are Crucial for Selection Analysis |
title_sort | igtreez, a toolkit for immunoglobulin gene lineage tree-based analysis, reveals cdr3s are crucial for selection analysis |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9643157/ https://www.ncbi.nlm.nih.gov/pubmed/36389731 http://dx.doi.org/10.3389/fimmu.2022.822834 |
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