Biology subjects

Galson, J. D.

Publications and source records attributed to Galson, J. D..

12 recordsLinked to original sources

bioRxiv2024

A generative foundation model for antibody sequence understanding

Here we introduce FAbCon, a generative antibody-specific language model comprising 2.4 billion parameters. A commonly accepted wisdom in developing large language models is that increasing model scale will translate to higher performance on downstream tasks. Starting from a 144-million parameter setup, we show that progressively larger models achieve greater accuracy in predicting antigen binding and can also be used to design new antibodies with good predicted developability potential. FAbCon is available on huggingface.co/alchemab.

bioinformatics↗

bioRxiv2024

Enhancing Antibody Language Models with Structural Information

The central tenet of molecular biology is that a proteins amino acid sequence determines its three-dimensional structure, and thus its function. However, proteins with similar sequences do not always fold into the same shape, and vice-versa, dissimilar sequences can adopt similar folds. In this work, we explore antibodies, a class of proteins in the immune system, whose local shapes are highly unpredictable, even with small variations in their sequence. Inspired by the CLIP method [1], we propose a multimodal contrastive learning approach, contrastive sequence-structure pre-training (CSSP), which amalgamates the representations of antibody sequences and structures in a mutual latent space. Integrating structural information leads both antibody and protein language models to show better correspondence with structural similarity and improves accuracy and data efficiency in downstream binding prediction tasks. We provide an optimised CSSP-trained model, AntiBERTa2-CSSP, for non-commercial use at https://huggingface.co/alchemab.

bioinformatics↗

bioRxiv2023

Benchmarking and integrating human B-cell receptor genomic and antibody proteomic profiling

Immunoglobulins (Ig), which exist either as B-cell receptors (BCR) on the surface of B cells or as antibodies when secreted, play a key role in the recognition and response to antigenic threats. The capability to jointly characterize the BCR and antibody repertoire is crucial in understanding human adaptive immunity. From peripheral blood, bulk BCR sequencing (bulkBCR-seq) currently provides the highest sampling depth, single-cell BCR sequencing (scBCR-seq) allows for paired chain characterization, and antibody peptide sequencing by tandem mass spectrometry (Ab-seq) provides information on the composition of secreted antibodies in the serum. Although still rare, studies combining these three technologies would comprehensively capture the humoral immune response. Yet, it has not been benchmarked to what extent the datasets generated by these three technologies overlap and complement each other. To address this question, we isolated peripheral blood B cells from healthy donors and sequenced BCRs at bulk and single-cell level, in addition to utilizing publicly available sequencing data. Integrated analysis was performed on these datasets, resolved by replicates and across individuals. Simultaneously, serum antibodies were isolated, digested with multiple proteases, and analyzed with Ab-seq. Systems immunology analysis showed high concordance in repertoire features between bulk and scBCR-seq within individuals, especially when replicates were utilized. In addition, Ab-seq identified clonotype-specific peptides using both bulk and scBCR-seq library references, demonstrating the feasibility of combining scBCR-seq and Ab-seq for reconstructing paired-chain Ig sequences from the serum antibody repertoire. Collectively, our work serves as a proof-of-principle for combining bulk sequencing, single-cell sequencing, and mass spectrometry as complementary methods towards capturing humoral immunity in its entirety.

immunology↗

bioRxiv2022

Characterisation of the immune repertoire of a humanised transgenic mouse through immunophenotyping and high-throughput sequencing

Immunoglobulin loci-transgenic animals are widely used in antibody discovery and increasingly in vaccine response modelling. In this study, we phenotypically characterised B-cell populations from the Intelliselect(R) Transgenic mouse (Kymouse) demonstrating full B-cell development competence. Comparison of the naive B-cell receptor (BCR) repertoires of Kymice BCRs naive human and murine BCR repertoires revealed key differences in germline gene usage and junctional diversification. These differences result in Kymice having CDRH3 length and diversity intermediate between mice and humans. To compare the structural space explored by CDRH3s in each species repertoire, we used computational structure prediction to show that Kymouse naive BCR repertoires are more human-like than mouse-like in their predicted distribution of CDRH3 shape. Our combined sequence and structural analysis indicates that the naive Kymouse BCR repertoire is diverse with key similarities to human repertoires, while immunophenotyping confirms that selected naive B-cells are able to go through complete development.

immunology↗

bioRxiv2021

Deciphering the language of antibodies using self-supervised learning

An individuals B cell receptor (BCR) repertoire encodes information about past immune responses, and potential for future disease protection. Deciphering the information stored in BCR sequence datasets will transform our fundamental understanding of disease and enable discovery of novel diagnostics and antibody therapeutics. One of the grand challenges of BCR sequence analysis is the prediction of BCR properties from their amino acid sequence alone. Here we present an antibody-specific language model, AntiBERTa, which provides a contextualised representation of BCR sequences. Following pre-training, we show that AntiBERTa embeddings learn biologically relevant information, generalizable to a range of applications. As a case study, we demonstrate how AntiBERTa can be fine-tuned to predict paratope positions from an antibody sequence, outperforming public tools across multiple metrics. To our knowledge, AntiBERTa is the deepest protein family-specific language model, providing a rich representation of BCRs. AntiBERTa embeddings are primed for multiple downstream tasks and can improve our understanding of the language of antibodies.

bioinformatics↗

bioRxiv2021

Different B cell subpopulations show distinct patterns in their IgH repertoire metrics

BackgroundSeveral human B-cell subpopulations are recognized in the peripheral blood, which play distinct roles in the humoral immune response. These cells undergo developmental and maturational changes involving VDJ recombination, somatic hypermutation and class switch recombination, altogether shaping their immunoglobulin heavy chain (IgH) repertoire. MethodsHere, we sequenced the IgH repertoire of naive, marginal zone, switched and plasma cells from 10 healthy adults along with matched unsorted and in silico separated CD19+ bulk B cells. We used advanced bioinformatic analysis and machine learning to thoroughly examine and compare these repertoires. ResultsWe show that sorted B cell subpopulations are characterised by distinct repertoire characteristics on both the individual sequence and the repertoire level. Sorted subpopulations shared similar repertoire characteristics with their corresponding in silico separated subsets. Furthermore, certain IgH repertoire characteristics correlated with the position of the constant region on the IgH locus. ConclusionOverall, this study provides unprecedented insight over mechanisms of B cell repertoire control in peripherally circulating B cell subpopulations.

immunology↗

bioRxiv2020

Deep mining of early antibody response in COVID-19 patients yields potent neutralisers and reveals high level of convergence

Passive immunisation using monoclonal antibodies will play a vital role in the fight against COVID-19. Until now, the majority of anti-SARS-CoV-2 antibody discovery efforts have relied on screening B cells of patients in the convalescent phase. Here, we describe deep-mining of the antibody repertoires of hospitalised COVID-19 patients using a combination of phage display technology and B cell receptor (BCR) repertoire sequencing to isolate neutralising antibodies and gain insights into the early antibody response. This comprehensive discovery approach has yielded potent neutralising antibodies with distinct mechanisms of action, including the identification of a novel non-ACE2 receptor blocking antibody that is not expected to be affected by any of the major viral variants reported. The study highlighted the presence of potent neutralising antibodies with near germline sequences within both the IgG and IgM pools at early stages of infection. Furthermore, we highlight a highly convergent antibody response with the same sequences occurring both within this study group and also within the responses described in previously published anti-SARS-CoV-2 studies.

immunology↗

bioRxiv2020

A high affinity human monoclonal antibody against Pfs230 binds multiple parasite stages and blocks oocyst formation in mosquitoes

Malaria elimination requires tools that interrupt parasite transmission. Here, we characterized B cell receptor responses among Malian adults vaccinated against the first domain of the cysteine-rich 230kDa gamete surface protein Pfs2301-3 to neutralize sexual stage P. falciparum parasites and halt their further spread. We generated nine Pfs230 human monoclonal antibodies (mAbs). One mAb potently blocked transmission to mosquitoes in a complement-dependent manner and reacted strongly to gamete surface while eight mAbs showed only low or no blocking activity. This study provides a rational basis to improve malaria vaccines and develop therapeutic antibodies for malaria elimination.

immunology↗

bioRxiv2020

A computational method for immune repertoire mining that identifies novel binders from different clonotypes, demonstrated by identifying anti-Pertussis toxoid antibodies

Due to their shared genetic history, antibodies from the same clonotype often bind to the same epitope. This knowledge is used in immune repertoire mining, where known binders are used to search bulk sequencing repertoires to identify new binders. However current computational methods cannot identify epitope convergence between antibodies from different clonotypes, limiting the sequence diversity of antigen-specific antibodies which can be identified. We describe how the antibody binding site, the paratope, can be used to cluster antibodies with common antigen reactivity from different clonotypes. Our method, paratyping, uses the predicted paratope to identify these novel cross clonotype matches. We experimentally validated our predictions on a Pertussis toxoid dataset. Our results show that even the simplest abstraction of the antibody binding site, using only the length of the loops involved and predicted binding residues, is sufficient to group antigen-specific antibodies and provide additional information to conventional clonotype analysis.

bioinformatics↗

bioRxiv2020

Deep sequencing of B cell receptor repertoires from COVID-19 patients reveals strong convergent immune signatures

Deep sequencing of B cell receptor (BCR) heavy chains from a cohort of 19 COVID-19 patients from the UK reveals a stereotypical naive immune response to SARS-CoV-2 which is consistent across patients and may be a positive indicator of disease outcome. Clonal expansion of the B cell memory response is also observed and may be the result of memory bystander effects. There was a strong convergent sequence signature across patients, and we identified 777 clonotypes convergent between at least four of the COVID-19 patients, but not present in healthy controls. A subset of the convergent clonotypes were homologous to known SARS and SARS-CoV-2 spike protein neutralising antibodies. Convergence was also demonstrated across wide geographies by comparison of data sets between patients from UK, USA and China, further validating the disease association and consistency of the stereotypical immune response even at the sequence level. These convergent clonotypes provide a resource to identify potential therapeutic and prophylactic antibodies and demonstrate the potential of BCR profiling as a tool to help understand and predict positive patient responses.

immunology↗

bioRxiv2019

Maturation of naïve and antigen-experienced B-cell receptor repertoires with age

B cells play a central role in adaptive immune processes, mainly through the production of antibodies. The maturation of the B-cell system with age is poorly studied. We extensively investigated age-related alterations of naive and antigen-experienced B-cell receptor (BCR) repertoires. The most significant changes were observed in the first 10 years of life, and were characterized by altered immunoglobulin gene usage and an increased frequency of mutated antibodies structurally diverging from their germline precursors. Older age was associated with an increased usage of downstream constant region genes and fewer antibodies with self-reactive properties. As mutations accumulated with age, the frequency of germline-encoded self-reactive antibodies decreased, indicating a possible beneficial role of self-reactive B-cells in the developing immune system. Our results suggest a continuous process of change through childhood across a broad range of parameters characterizing BCR repertoires and stress the importance of using well-selected, age-appropriate controls in BCR studies.

immunology↗

bioRxiv2018

Inferring B cell specificity for vaccines using a mixture model

Vaccines have greatly reduced the burden of infectious disease, ranking in their impact on global health second only after clean water. Most vaccines confer protection by the production of antibodies with binding affinity for the antigen, which is the main effector function of B cells. This results in short term changes in the B Cell receptor (BCR) repertoire when an immune response is launched, and long term changes when immunity is conferred. Analysis of antibodies in the serum is usually used to evaluate vaccine response, however this is limited and therefore the investigation of the BCR repertoire provides far more detail for the analysis of vaccine response. Here, we introduce a novel Bayesian model to describe the observed distribution of BCR sequences and the pattern of sharing across time and between individuals, with the goal to identify vaccine-specific BCR sequences. We use data from two studies to assess the model and estimate that we can identify vaccine-specific sequences with 69% sensitivity.

genomics↗