Mapping antibody class switch mechanisms and function
Lead Research Organisation:
UNIVERSITY COLLEGE LONDON
Department Name: Structural Molecular Biology
Abstract
Antibodies are produced by a specialised immune cell (B cell) and act as important immune mediators, bridging between pathogens and effector cells to protect us from infection. Antibody molecules can also exist bound to the B cell surface where they act as receptor for detecting target molecules (antigens). Their versatility is immense, they are used to make diagnostics, research tools and therapeutics.
One part of the antibody (variable region) is responsible for binding to the antigen, the other end of the molecule is responsible for activating/mediating different functions in the immune system. Uniquely, the antibody variable region can evolve within the organism within a short timescale, in response to infection or vaccination, to improve its binding to the antigen. The constant region does not evolve, but it can be changed to one of 9 different classes or subclasses in order to change the function of the antibody in a genetic process known as Class Switch Recombination (CSR). The (sub)classes of antibody are arranged in the genome in this order: IgM-IgD-IgG3-IgG1-IgA1-IgG2-IgG4-IgE-IgA2; a B cell starts life with IgM and IgD and after activation switches to another (sub)class. Until very recently it was thought that CSR had no effect on the binding abilities of the Variable region.
Recent research in different areas (Ageing, Ebola, HIV infection, Cancer) indicates that we don't fully understand the processes that control which (sub)class will be used, the difference that CSR between subclasses makes to the outcome of an immune response or the exact molecular effects that CSR might have on the variable region binding properties. Therapeutic antibodies are a critical pharmaceutical resource, being the fastest growing class of pharmaceuticals, with thousands now in the development pipeline. Current products with regulatory approval/undergoing regulatory review are mostly IgG1 whilst none are IgA or IgE. As we understand more about the functions of these classes, we may find that the potential utility of antibodies can be increased, such as IgE in skin cancers or IgA in gut-related disorders.
In this programme we propose to harness the unique expertise of a team of bioinformaticians and immunologists to determine what factors, both outside the cell and inside the cell, control CSR. We will monitor how CSR progresses with time on a daily basis for a fortnight after challenge with the flu vaccine and we will use computer modelling of antibody structures to investigate how changing one side of the antibody molecule may affect the other. Each of these three main objectives will produce a range of results, some of which will help to understand the work in the other objectives, although would not be critical for their success. All parts of the programme require input from all the team to varying levels.
The methods we will use and develop are ground-breaking, in our preliminary data, we show pathways of class switching to different types of antibody in cell culture on a single cell basis. We will alter the conditions of these experiments, note the resulting changes and map the protein-protein and gene interactions to deduce what molecules are controlling CSR. These methods will be applicable in all cellular Bioscience disciplines and will transform cell biology research. The mapping of human CSR and the molecular modelling of antibody structure will also result in new tools for others to use, we have successfully done this before and have large global user groups in several areas. The interdisciplinary nature of our team means that we have insight into how to design tools that are user friendly and flexible, all data and tools will be made publicly available in a collective resource "BHive". We will also run our programme in such a way as to maximise the interdisciplinary familiarisation across all our teams and ensure our ECRs have a springboard into their future careers.
One part of the antibody (variable region) is responsible for binding to the antigen, the other end of the molecule is responsible for activating/mediating different functions in the immune system. Uniquely, the antibody variable region can evolve within the organism within a short timescale, in response to infection or vaccination, to improve its binding to the antigen. The constant region does not evolve, but it can be changed to one of 9 different classes or subclasses in order to change the function of the antibody in a genetic process known as Class Switch Recombination (CSR). The (sub)classes of antibody are arranged in the genome in this order: IgM-IgD-IgG3-IgG1-IgA1-IgG2-IgG4-IgE-IgA2; a B cell starts life with IgM and IgD and after activation switches to another (sub)class. Until very recently it was thought that CSR had no effect on the binding abilities of the Variable region.
Recent research in different areas (Ageing, Ebola, HIV infection, Cancer) indicates that we don't fully understand the processes that control which (sub)class will be used, the difference that CSR between subclasses makes to the outcome of an immune response or the exact molecular effects that CSR might have on the variable region binding properties. Therapeutic antibodies are a critical pharmaceutical resource, being the fastest growing class of pharmaceuticals, with thousands now in the development pipeline. Current products with regulatory approval/undergoing regulatory review are mostly IgG1 whilst none are IgA or IgE. As we understand more about the functions of these classes, we may find that the potential utility of antibodies can be increased, such as IgE in skin cancers or IgA in gut-related disorders.
In this programme we propose to harness the unique expertise of a team of bioinformaticians and immunologists to determine what factors, both outside the cell and inside the cell, control CSR. We will monitor how CSR progresses with time on a daily basis for a fortnight after challenge with the flu vaccine and we will use computer modelling of antibody structures to investigate how changing one side of the antibody molecule may affect the other. Each of these three main objectives will produce a range of results, some of which will help to understand the work in the other objectives, although would not be critical for their success. All parts of the programme require input from all the team to varying levels.
The methods we will use and develop are ground-breaking, in our preliminary data, we show pathways of class switching to different types of antibody in cell culture on a single cell basis. We will alter the conditions of these experiments, note the resulting changes and map the protein-protein and gene interactions to deduce what molecules are controlling CSR. These methods will be applicable in all cellular Bioscience disciplines and will transform cell biology research. The mapping of human CSR and the molecular modelling of antibody structure will also result in new tools for others to use, we have successfully done this before and have large global user groups in several areas. The interdisciplinary nature of our team means that we have insight into how to design tools that are user friendly and flexible, all data and tools will be made publicly available in a collective resource "BHive". We will also run our programme in such a way as to maximise the interdisciplinary familiarisation across all our teams and ensure our ECRs have a springboard into their future careers.
Technical Summary
Antibodies are a critical component of the immune system with multiple key functions. The huge range of possible specificities, coupled with the ability to change effector functions for the same specificity, makes them a unique adaptable resource - both in vivo in immune responses and in therapeutics. Effector functions are changed by switching to a different class, or subclass, of antibody in the process of Class Switch Recombination (CSR). Our understanding of CSR events and their consequences is inadequate for interpretation of recent key observations; eg failure of IgA1 responses in ageing, repertoire differences between IgG1 vs IgG2, change of CSR focus in Ebola survivors.
We have three main objectives 1) Determine endogenous and exogenous factors affecting CSR in vitro. Implementing novel methods to overcome difficulties inherent in current protocols, in an iterative process, combining B cell activation and gene silencing with single cell RNASeq. Our preliminary data shows that single cell RNASeq of ex vivo cultured B cells can distinguish different types of CSR and use pseudotime to monitor CSR progress. 2) Determine the dynamics of CSR in vivo after vaccination in different age groups. Using qualitative and quantitative repertoire analysis to track CSR at frequent (16 in 14 days) time points and model the dynamics of class switching. 3) Investigate the effect of allostery on antibody activity. Recent evidence indicates that not all antibody variable regions are resistant to allosteric effect of CSR, which has implications for the evolution/design of effective antibodies. We will measure potential allosteric effects in silico and verify outcomes in vitro.
This integrated program combines expertise in cellular/molecular immunology and bioinformatics/biophysics to achieve a better understanding of the control and relevance of class switching in the immune response and produce novel bio-analytical tools broadly applicable across many bioscience disciplines.
We have three main objectives 1) Determine endogenous and exogenous factors affecting CSR in vitro. Implementing novel methods to overcome difficulties inherent in current protocols, in an iterative process, combining B cell activation and gene silencing with single cell RNASeq. Our preliminary data shows that single cell RNASeq of ex vivo cultured B cells can distinguish different types of CSR and use pseudotime to monitor CSR progress. 2) Determine the dynamics of CSR in vivo after vaccination in different age groups. Using qualitative and quantitative repertoire analysis to track CSR at frequent (16 in 14 days) time points and model the dynamics of class switching. 3) Investigate the effect of allostery on antibody activity. Recent evidence indicates that not all antibody variable regions are resistant to allosteric effect of CSR, which has implications for the evolution/design of effective antibodies. We will measure potential allosteric effects in silico and verify outcomes in vitro.
This integrated program combines expertise in cellular/molecular immunology and bioinformatics/biophysics to achieve a better understanding of the control and relevance of class switching in the immune response and produce novel bio-analytical tools broadly applicable across many bioscience disciplines.
Planned Impact
The outputs of this collaboration will have extremely broad reach, informing the fields of Immunology (B cell development), vaccinology and immunotherapeutics. The methodological approaches and bioinformatical tools developed here will take advantage of cutting edge technologies in single cell analysis and will revolutionise biological gene silencing experiments in many other areas of biology.
Gene silencing in vitro is an immensely powerful tool, across all fields of biological sciences, to determine the function of intracellular molecules and determine their regulation and network interactions. A drawback has been that silencing methods are not 100% efficient, so any outcome of an experiment is an average of the results from cells with a varying degree of silencing. Engineered cell lines, expressing markers, can be used to monitor silencing, but there has been no widely applicable solution for research on primary cells. By integrating gene silencing with single cell transcriptomics we can determine the level of silencing per cell and correlate this with the level of the consequent effect. Thus, the combination of gene silencing and single cell technologies, with appropriate tools to facilitate analysis and interpretation, will be of immense benefit to many different researchers in a wide range of biological sciences as well as in immunology/host defence.
Antibody class switch recombination (CSR) is poorly understood in humans, yet evidence indicates that antibodies other than IgG1 play critical roles in protection against infectious disease and reducing our risk of autoimmunity and cancer. A full understanding of the human immune response to challenge, including dynamics of all B cell classes as well as serum Ig and cytokine measurement, is required if we are to design effective vaccines. It will also be important knowledge as the basis from which to design immune monitoring in clinical trials and will help us to understand the immune response in infectious diseases.
An antibody has two parts - Variable (V), with specificity for antigen, and Constant (C), encoding one of 9 classes of antibody. The prevailing paradigm is that the specificity of the V is unaffected by a change in C after class switching. Yet this may not always be the case, - changes in binding function have been seen between the same V on IgA2 versus IgG1, and different classes of antibody have different V repertoires. The latter could be due to historically different activation pathways (resulting in different C region use) selecting different V, or could be due to loss or gain of functionality upon CSR resulting in a change of representation by a particular V. Therapeutic antibodies are the fastest growing class of pharmaceuticals, with thousands now in the development pipeline. Of the products that have received regulatory approval, or are currently undergoing regulatory review, the majority are IgG1 and none are IgA or IgE. It is important to understand where V-C interactions might alter antibody function to optimise the pipeline and reduce development costs. As we understand more about the functions of different classes of antibody we may find that the potential utility of antibodies can be increased. For example, we recently showed that IgE is involved in the response to skin tumors in mice.
Stakeholders: The main beneficiaries of this basic science programme will be research academics in the life sciences and companies concerned with the use of antibodies in therapeutics/ diagnostics/ research applications. The ECRs on the programme and in the labs of the senior investigators will also increase and diversify their skills in this synergistic interdisciplinary environment. Information and tools from this program will lead to improvements in research and development which will eventually benefit public health in the way of improved vaccines and biological pharmaceuticals.
Gene silencing in vitro is an immensely powerful tool, across all fields of biological sciences, to determine the function of intracellular molecules and determine their regulation and network interactions. A drawback has been that silencing methods are not 100% efficient, so any outcome of an experiment is an average of the results from cells with a varying degree of silencing. Engineered cell lines, expressing markers, can be used to monitor silencing, but there has been no widely applicable solution for research on primary cells. By integrating gene silencing with single cell transcriptomics we can determine the level of silencing per cell and correlate this with the level of the consequent effect. Thus, the combination of gene silencing and single cell technologies, with appropriate tools to facilitate analysis and interpretation, will be of immense benefit to many different researchers in a wide range of biological sciences as well as in immunology/host defence.
Antibody class switch recombination (CSR) is poorly understood in humans, yet evidence indicates that antibodies other than IgG1 play critical roles in protection against infectious disease and reducing our risk of autoimmunity and cancer. A full understanding of the human immune response to challenge, including dynamics of all B cell classes as well as serum Ig and cytokine measurement, is required if we are to design effective vaccines. It will also be important knowledge as the basis from which to design immune monitoring in clinical trials and will help us to understand the immune response in infectious diseases.
An antibody has two parts - Variable (V), with specificity for antigen, and Constant (C), encoding one of 9 classes of antibody. The prevailing paradigm is that the specificity of the V is unaffected by a change in C after class switching. Yet this may not always be the case, - changes in binding function have been seen between the same V on IgA2 versus IgG1, and different classes of antibody have different V repertoires. The latter could be due to historically different activation pathways (resulting in different C region use) selecting different V, or could be due to loss or gain of functionality upon CSR resulting in a change of representation by a particular V. Therapeutic antibodies are the fastest growing class of pharmaceuticals, with thousands now in the development pipeline. Of the products that have received regulatory approval, or are currently undergoing regulatory review, the majority are IgG1 and none are IgA or IgE. It is important to understand where V-C interactions might alter antibody function to optimise the pipeline and reduce development costs. As we understand more about the functions of different classes of antibody we may find that the potential utility of antibodies can be increased. For example, we recently showed that IgE is involved in the response to skin tumors in mice.
Stakeholders: The main beneficiaries of this basic science programme will be research academics in the life sciences and companies concerned with the use of antibodies in therapeutics/ diagnostics/ research applications. The ECRs on the programme and in the labs of the senior investigators will also increase and diversify their skills in this synergistic interdisciplinary environment. Information and tools from this program will lead to improvements in research and development which will eventually benefit public health in the way of improved vaccines and biological pharmaceuticals.
Publications

Bradford H
(2024)
Thioredoxin is a metabolic rheostat controlling regulatory B cells
in Nature Immunology

Carmona OG
(2025)
AllohubPy: Detecting Allosteric Signals Through An Information-theoretic Approach.
in Journal of molecular biology

Crescioli S
(2023)
B cell profiles, antibody repertoire and reactivity reveal dysregulated responses with autoimmune features in melanoma.
in Nature communications



Guo D
(2024)
Modelling the assembly and flexibility of antibody structures.
in Current opinion in structural biology

Guo D
(2024)
VCAb: a web-tool for structure-guided exploration of antibodies
in Bioinformatics Advances

Hassi NK
(2023)
In Silico and In Vitro Analysis of IL36RN Alterations Reveals Critical Residues for the Function of the Interleukin-36 Receptor Complex.
in The Journal of investigative dermatology

Lebrusant-Fernandez M
(2024)
IFN-?-dependent regulation of intestinal epithelial homeostasis by NKT cells
in Cell Reports

Mallaby J
(2023)
Diversification of immunoglobulin genes by gene conversion in the domestic chicken (Gallus gallus domesticus).
in Discovery immunology
Related Projects
Project Reference | Relationship | Related To | Start | End | Award Value |
---|---|---|---|---|---|
BB/T002212/1 | 01/02/2020 | 31/10/2022 | £2,823,420 | ||
BB/T002212/2 | Transfer | BB/T002212/1 | 01/11/2022 | 31/01/2026 | £1,573,277 |
Description | We developed single-cell inference of CSR (sciCSR, pronounced as in "scissors"), a computational method that enables us to analyze single-cell RNA sequencing (scRNA-seq) data and extract CSR signals. sciCSR re-analyzes scRNA-seq alignments to distinguish sterile and productive transcripts (Fig. 1a). Because regions 5' to the constant region exons (denoted "5' C") are a hallmark of sterile transcripts1, a positive read count covering this region signifies sterile transcripts. Similarly, reads covering the antibody variable (V), diversity (D) and joining (J) segments imply productive transcripts. We reasoned that we could couple sciCSR with recent tools aimed at inferring cellular trajectories3 to resolve the temporal trajectory of CSR and the antibody response. We curated publicly available scRNA-seq datasets of B cells from vaccination studies (monitoring the development of antibody response over time) and genetically engineered systems, such as mice in which known CSR-related genes have been knocked down. To facilitate understanding of primary human responses we produced a comprehensive multi-omic data-set obtained from PBMC collected after SARS-CoV-2 vaccination in naïve adults at sequential time points. This includes integrable antigen-specific scRNA seq data with inferred B cell subtypes and paired chain BCR repertoire, bulk BCR repertoire, cell phenotype analysis and serology. Using these data, we uncovered new insights into the dynamics of class switch recombination (CSR) in B cells, challenging the existing paradigm of the early B cell vaccine response. Although a number of antibody structure databases exist, a public data resource which provides clear, consistent annotation of isotypes, species coverage of 3D antibody structures and their deep mutation profiles is currently lacking. The V and C region bearing antibody (VCAb) web tool is established with the purpose to clarify these annotations and provide an accessible and easily consultable resource to facilitate antibody engineering. VCAb currently provides data on 6,948 experimentally determined antibody structures including both V and C regions from different species. Additionally, VCAb provides annotations of species and isotypes with both V and C region numbering schemes applied, which can be interactively queried or downloaded in batch. |
Exploitation Route | The developed software can be used for the analysis of antibody repertoires and for the characterization of their single cells profiles. The methods are novel and will allow for new discoveries in the characterization of Antibody Isotypes implicated in Class-Switch recombination upon immunological challenges. |
Sectors | Healthcare Manufacturing including Industrial Biotechology Pharmaceuticals and Medical Biotechnology |
URL | https://github.com/Fraternalilab/ |
Description | ROYAL FREE LONDON NHS FOUNDATION |
Organisation | Royal Free Hospital |
Department | Department Immunology |
Country | United Kingdom |
Sector | Hospitals |
PI Contribution | Amir Gander Royal Free London NHS Foundation Trust Royal Free Hospital Collaboration SIB Vaccine study |
Collaborator Contribution | Collaboration on Vaccine study- recruitment and sample collection as part of the UKRI funded SLoLa award MACSMSAF |
Impact | Multidisciplinary: Virology, Immunology, Cpmputational Biology, Bcells Repertoire study, Data Analysis. |
Start Year | 2021 |
Description | ROYAL FREE LONDON NHS FOUNDATION |
Organisation | Royal Free Hospital |
Country | United Kingdom |
Sector | Hospitals |
PI Contribution | Amir Gander Royal Free London NHS Foundation Trust Royal Free Hospital Collaboration SIB Vaccine study |
Collaborator Contribution | Collaboration on Vaccine study- recruitment and sample collection as part of the UKRI funded SLoLa award MACSMSAF |
Impact | Multidisciplinary: Virology, Immunology, Cpmputational Biology, Bcells Repertoire study, Data Analysis. |
Start Year | 2021 |