Biology subjects

Altin, J.

Publications and source records attributed to Altin, J..

4 recordsLinked to original sources

bioRxiv2026

Proteome-wide discovery of novel diagnostic antigens for coccidioidomycosis

Coccidioidomycosis, commonly called Valley Fever (VF), caused by Coccidioides spp., is an understudied fungal disease that accounts for a substantial fraction of pneumonias in endemic areas. Diagnosis remains challenging because the mainstay of diagnosis is serology, and current assays have modest sensitivity in early infection. Discovery of new antigens could improve serologic detection early in disease. Here, we use PepSeq, a DNA-programmable serology platform, to represent the complete proteome of Coccidioides within a library of 244,000 DNA-barcoded peptides. By profiling antibody reactivity at the protein and epitope levels in VF patients, naturally infected pigtail macaques, and healthy controls, we identify numerous previously-unrecognized antigens and epitopes, including some shared between humans and macaque responses. When translated into a pooled peptide ELISA, we show that a subset of identified antigens can discriminate VF cases from controls in an independent cohort with high accuracy (AUC = 0.91). These findings establish high-dimensional peptide serology as a scalable approach for fungal antigen discovery and identify new targets for improved VF diagnosis.

immunology↗

bioRxiv2025

Learned Geometry, Predicted Binding: Structurally-BasedPrediction of Peptide:MHC Binding Using AlphaFold 3 EnablesCD4 T Cell Epitope Prediction

The accurate prediction of T cell epitope peptides within proteins of interest has a wide range of applications, but is complicated by the multiple determinants of antigenicity, the polymorphism of the Major Histocompatibility Complex (MHC) locus, and the great diversity of possible peptide antigens. Leading in silico methods use a variety of statistical approaches to learn from sequences identified through both in vitro MHC binding and peptide elution studies, but their performance remains imperfect, particularly for MHC II-restricted responses. Here we present MHCIIFold-GNN, an entirely orthogonal solution to this problem that combines three new elements: (i) a highly-multiplexed peptide:MHCII binding assay, (ii) generalizable structural modeling using AlphaFold3, and (iii) transfer learning with a Graph-based Neural Network. Trained exclusively on newly-generated in vitro binders, we show that MHCIIFold-GNN enables state-of-the-art prediction of CD4 T cell epitopes presented by diverse MHC II proteins, on par with non-structural methods that rely on much larger datasets including naturally-processed ligands. Moreover, when MHCIIFold-GNN and a leading non-structural method are combined, we observe unparalleled performance on a held-out test set (11 % boost), underscoring the orthogonality of the methods. These results highlight the power of a new class of structure-informed approaches to the CD4 T cell epitope prediction problem.

bioinformatics↗

bioRxiv2024

Preclinical Proof of Concept for SNAPTM-TIL: a personalized, next-generation tumor-infiltrating lymphocyte therapy platform

Tumor-infiltrating lymphocyte (TIL) therapy, which involves extracting, expanding, and reinfusing immune cells to target cancer cells, has shown promise in melanoma treatment, but requires optimization for broader efficacy. The success of TIL therapy depends on the recognition of tumor-associated antigens, but neoantigen-reactive T-cells are often rare and exhausted in less immunogenic malignancies. Isolating T cells enriched in neoantigen reactivity prior to in vitro expansion and reinfusion may improve the response rates. To this end, our proprietary Specific Neo-Antigen Peptides (SNAP) technology platform improves the accuracy of neoantigen prediction and validation by combining advanced computational modeling and PepSeq, a high-throughput screen for the physical credentialing of putative neoantigens based on their affinity to bind patient-specific HLA class II proteins. This approach allows for the education and enrichment of TILs (SNAP-TILs) with personalized, predefined, highly immunogenic neoantigens prior to expansion. Using the SNAP platform, we consistently achieved, on average, an SNAP-TIL product comprising 96% CD3+ cells, with a mixture of 75% effector and 23% central memory cells. SNAP-TILs exhibited greater efficacy and selectivity in immune infiltration than TIL, which was expanded by the rapid expansion protocol alone using ex vivo models. SNAP-TIL was also reactive in highly and poorly immunogenic tumors, with 70% and 50% tumor growth inhibition in melanoma and pancreatic patient-derived xenograft models, respectively. This study demonstrates the novel benefit of our Personalized Neoantigen Pipeline approach, potentially providing a durable antitumor immune response for a larger proportion of cancer patients.

immunology↗

bioRxiv2022

Highly-multiplexed serology for non-human mammals

Emerging infectious diseases represent a serious and ongoing threat to humans. Most emerging viruses are maintained in stable relationships with other species of animals, and emergence within the human population results from cross-species transmission. Therefore, if we want to be prepared for the next emerging virus, we need to broadly characterize the diversity and ecology of viruses currently infecting other animals (i.e., the animal virosphere). High-throughput metagenomic sequencing has accelerated the pace of virus discovery. However, molecular assays can only detect active viral infections and only if virus is present within the sampled fluid or tissue at the time of collection. In contrast, serological assays measure long-lived antibody responses to infections, which can be detected within the blood, regardless of the infected tissues. Therefore, serological assays can provide a complementary approach to understanding the circulation of viruses, and while serological assays have historically been limited in scope, recent advancements allow 1000s to 100,000s of antigens to be assessed simultaneously using <1 l of blood (i.e., highly-multiplexed serology). Application of highly-multiplexed serology for characterization of the animal virosphere is dependent on the availability of reagents that can be used to capture or label antibodies of interest. Here, we demonstrate the potential for commercial immunoglobulin-binding proteins (protein A and protein G) to enable highly-multiplexed serology in 25 species of non-human mammals and we describe a competitive FLISA assay that can be used as an initial screen for choosing the most appropriate capture protein for a given host species. ImportanceAntibodies are generated in response to infections with viruses and other pathogens and they help protect against future exposures. Mature antibodies are long-lived, highly specific, and can bind to their protein targets with high affinity. Thus, antibodies can also provide information about an individuals history of viral exposures, which has important applications in understanding the epidemiology and etiology of disease. In recent years, there have been large advances in the available methods for broadly characterizing antibody binding profiles, but thus far, these have primarily been utilized only with human samples. Here, we demonstrate that commercial antibody-binding reagents can facilitate modern antibody assays for a wide variety of mammalian species, and we describe a cheap and fast approach for choosing the best reagent for each animal species. By studying antibody-binding profiles in captive and wild animals, we can better understand the distribution and prevalence of viruses that could spillover into humans.

immunology↗