Biology subjects

Altin, J. A.

Publications and source records attributed to Altin, J. A..

6 recordsLinked to original sources

bioRxiv2026

General prediction of T cell receptor antigen specificity from sequence using AlphaFold 3

The Major Histocompatibility Complex (MHC):peptide:T Cell Receptor (TCR) complex is the most diverse trimolecular interface known in nature and a key trigger for adaptive immunity. TCRs are now routinely sequenced at scale, however decoding their specificity for antigens remains a bottleneck. While in silico approaches have advanced considerably, none enables prediction against "unseen" epitopes, limiting their applicability to a tiny fraction of cases. Here, we show that AlphaFold 3 (AF3) predicts the structures of MHC:peptide:TCR triads with unprecedented accuracy. By applying AF3 to >9,000 TCRs mapped to >1,000 distinct epitopes restricted by >70 MHC class I / II alleles, we identify features that distinguish cognate triads from controls. The resulting model achieves median AUCs of 0.81-0.92 on validation triads unseen by AF3 or during feature selection. Our results reveal that generalized prediction of TCR specificity from sequence is possible, with the potential to greatly accelerate the decoding of immune responses.

immunology↗

bioRxiv2026

IMMREP25: Unseen Peptides

T cell receptors (TCRs) can bind to peptides presented by MHC molecules (pMHC) as a first step to trigger a T cell response. Reliable approaches to predict TCR:pMHC binding would have broad applications in clinical diagnostics, therapeutics, and the fundamental understanding of molecular interactions. IMMREP is a community organized series of prediction contests that asks participants to predict TCR:pMHC binding on unpublished datasets. Previous iterations in 2022 and 2023 showed multiple approaches can predict TCR-pMHC binding with significant accuracy (median AUC_0.1[≥]0.7) for peptides where experimental data is available ("seen" peptides). In contrast, models did not outperform random guessing for peptides that have no such data available ("unseen" peptides). Here we report on the results of IMMREP25, which focused solely on unseen peptides in order to evaluate the cutting edge of the field. We received 126 named submissions predicting the specificity of 1,000 TCRs against twenty unseen peptides restricted by one of two MHC molecules (HLA-A*02:01 and HLA-B*40:01). The best performing methods showed a macro-AUC_0.1 of 0.60, significantly better than random, demonstrating significant advances in the field. The top performing methods incorporated structural modeling into their approach, indicating that especially for unseen peptides, a structural understanding aids in the prediction of TCR:pMHC interactions. The results from this benchmark highlight the significant challenges remaining for TCR:pMHC predictions and will inform future method development.

bioinformatics↗

bioRxiv2024

Integrated, high-dimensional analysis of CD4 T cell epitope specificities and phenotypes reveals unexpected diversity in the response to Mycobacterium tuberculosis

Immunity to Mycobacterium tuberculosis (Mtb), like many pathogens, is encoded jointly by the antigen specificities and functions of responding CD4 T cells. However, these features span a large two-dimensional possibility space - defined on one axis by the Mtb proteome, and on the other by the T cell transcriptome - that exceeds the dimensionality of existing technologies. Here we present an approach ("CRESTA") that combines highly-multiplexed DNA-barcoded epitope probes, single cell sequencing, and clonal analysis of T Cell Receptors (TCRs) to robustly detect rare antigen-specific CD4 T cells across hundreds of epitopes simultaneously and reveal their transcriptome-wide phenotypes. By comprehensively assaying known epitopes in Mtb-infected participants, we reveal polyclonal and multi-epitope responses across a spectrum of differentiation states, uncover previously-unobserved phenotypic diversity within and between epitopes, and increase the total number of known Mtb epitope-mapped TCR:{beta}s by [~]8-fold. We expect CRESTA to enable high-dimensional analyses of CD4 T cell responses in various settings, including infection, cancer, autoimmunity and allergy.

immunology↗

bioRxiv2023

Recurrent SARS-CoV-2 mutations at Spike D796 evade antibodies from pre-Omicron convalescent and vaccinated subjects

SARS-CoV-2 lineages of the Omicron variant rapidly became dominant in early 2022 and frequently cause human infections despite vaccination or prior infection with other variants. In addition to antibody-evading mutations in the Receptor Binding Domain, Omicron features amino acid mutations elsewhere in the Spike protein, however their effects generally remain ill-defined. The Spike D796Y substitution is present in all Omicron sub-variants and occurs at the same site as a mutation (D796H) selected during viral evolution in a chronically-infected patient. Here we map antibody reactivity to a linear epitope in the Spike protein overlapping position 796. We show that antibodies binding this region arise in pre-Omicron SARS-CoV-2 convalescent and vaccinated subjects, but that both D796Y and D796H abrogate their binding. These results suggest that D796Y contributes to the fitness of Omicron in hosts with pre-existing immunity to other variants of SARS-CoV-2 by evading antibodies targeting this site.

immunology↗

bioRxiv2021

A framework to identify antigen-expanded T Cell Receptor (TCR) clusters within complex repertoires

Common approaches for monitoring T cell responses are limited in their multiplexity and sensitivity. In contrast, deep sequencing of the T Cell Receptor (TCR) repertoire offers a global view whose theoretical sensitivity is limited only by the depth of available sampling. However, assignment of antigen specificities within TCR repertoires has become a bottleneck. Here, we combine antigen-driven expansion, deep TCR sequencing and a novel analysis framework to show that homologous Clusters of Expanded TCRs (CETs) can be confidently identified without cell isolation, and assigned to antigen against a background of non-specific clones. We show that clonotypes within each CET respond to the same epitope, and that protein antigens stimulate multiple CETs reactive to constituent peptides. Finally, we demonstrate the personalized assignment of antigen-specificity to rare clones within fully-diverse unexpanded repertoires. The method presented here may be used to monitor T cell responses to vaccination and immunotherapy with high fidelity.

immunology↗

bioRxiv2020

Epitope-resolved profiling of the SARS-CoV-2 antibody response identifies cross-reactivity with an endemic human CoV

A high-resolution understanding of the antibody response to SARS-CoV-2 is important for the design of effective diagnostics, vaccines and therapeutics. However, SARS-CoV-2 antibody epitopes remain largely uncharacterized, and it is unknown whether and how the response may cross-react with related viruses. Here, we use a multiplexed peptide assay ( PepSeq) to generate an epitope-resolved view of reactivity across all human coronaviruses. PepSeq accurately detects SARS-CoV-2 exposure and resolves epitopes across the Spike and Nucleocapsid proteins. Two of these represent recurrent reactivities to conserved, functionally-important sites in the Spike S2 subunit, regions that we show are also targeted for the endemic coronaviruses in pre-pandemic controls. At one of these sites, we demonstrate that the SARS-CoV-2 response strongly and recurrently cross-reacts with the endemic virus hCoV-OC43. Our analyses reveal new diagnostic and therapeutic targets, including a site at which SARS-CoV-2 may recruit common pre-existing antibodies and with the potential for broadly-neutralizing responses.

immunology↗