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N. Hacohen

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Open access Jul 2026

Scaling measurements of peptide-HLA complex stability using user-defined libraries and mass spectrometry 2310029

Human leukocyte antigen (HLA) class I presents intracellular peptides to the immune system on the cell surface. Since this process is crucial for the recognition of cancer cells and the initiation of anti-tumor immunity, peptides presented by HLA are valuable immunotherapy targets. More stable peptide HLA (pHLA) complexes provoke superior immune responses. However, how peptide sequence motifs contribute to pHLA stability is not well understood. We developed a high-throughput assay to quantify stability of thousands of user-defined pHLA produced in E. coli. Peptide libraries and the desired HLA are produced and form pHLA complexes in E. coli. pHLA are purified and stability is evaluated by treating pHLA with a thermal gradient and recovering only the peptides which remain HLA-bound after heat treatment. Peptide depletion over the temperature range is monitored by quantitative tandem mass tag (TMT) enabled mass spectrometry. Our new E. coli-based method is reliable for assessing pHLA stability. Detected HLA-binding peptides have the expected binding motifs, and stability data strongly correlates with current gold-standard data. We are able to generate large peptide stability datasets (1,800+ peptides) in one scaled experiment — five times larger than currently available datasets. We show that peptide motifs and anchor residue combinations potentially drive pHLA stability. Additionally, peptides were included in user-defined libraries with public immunogenicity annotations. We observed that immunogenic peptides were significantly more stable than non-immunogenic peptides. We generated customizable pHLA stability datasets which show how peptide sequence motifs affect pHLA stability, and may be helpful for improving our mechanistic understanding of pHLA stability. Further, since peptide stability is related to immunogenicity, these large-scale pHLA stability datasets will be useful for improving peptide immunogenicity predictions for the development of immunotherapeutics. NIH R01CA155010, Mark Foundation for Cancer Research, Moderna Classical and Non-Classical Antigen Presenting Cells (APC)

M. Wilbrink, Luis O Correa-Medero, Emma C Duggan et al. · Journal of Immunology · 0 citations

Open access Jul 2026

Scalable single-cell isoform profiling with sequencing-by-expansion

Single-cell RNA sequencing has transformed our understanding of cellular systems, yet the reliance on short-read sequencing restricts analysis to gene-level quantification and obscures the immense biological diversity generated by alternative splicing. While long-read sequencing technologies can capture full-length RNA and resolve transcript isoforms, current platforms remain constrained by throughput and high per-base costs, rendering them impractical for modern million-cell applications. To address this critical limitation, we developed and optimized sequencing-by-expansion (SBX) chemistry for high-throughput single-cell RNA isoform profiling. Integrated within the AXELIOS 1 sequencing platform, SBX employs a unique biochemical conversion process that transforms complementary DNA into expanded surrogate high signal-to-noise polymers called Xpandomers which are sequenced via translocation through a dense nanopore array yielding over 9.5 billion reads in a two-hour run. To leverage this unique data type for long-read single-cell RNA isoform sequencing, we developed the Consensus UMI Deduplication using Longest Length (CUDLL) algorithm, which computationally consolidates variable-length raw SBX reads into single, high-fidelity consensus reads, elevating sequence accuracy to 99.83% and maximizing per transcript read length. We demonstrate that this consensus approach successfully captures the vast isoform diversity of single-cell libraries and enables the accurate measure of differential isoform expression across distinct cell types in peripheral blood mononuclear cells. Furthermore, SBX coupled with CUDLL efficiently resolves T-cell and B-cell receptor clonotypes directly from whole-transcriptome libraries without the need for VDJ-specific target enrichment. Ultimately, this work establishes SBX and the AXELIOS 1 as a transformative platform for high-scale single-cell isoform sequencing.

Christophe H. Georgescu, Ghamdan Al-Eryani, Allison Brookhart et al. · bioRxiv · 0 citations