Biology subjects

Purcell, A. W.

Publications and source records attributed to Purcell, A. W..

At least 19 recordsLinked to original sources

bioRxiv2026

Unconventional presentation of an immunodominant HLA-DR15-restricted nephritogenic proteinase 3 epitope implicated in vasculitis

Proteinase 3 (PR3) anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis is associated with HLA-DR15, implicating HLA-DR15-restricted CD4 T cell autoimmunity in the disease. However, the PR3 epitopes presented by HLA-DR15 and the autoreactive CD4 T cell responses they elicit are undefined. Using humanized hPR3.DR15+ mice, we identified PR3216-231 as an immunodominant human PR3-derived CD4 T cell epitope presented by HLA-DR15. Immunopeptidomic profiling confirmed the natural processing and HLA-DR15-restricted presentation of PR3216-231. Structural analyses of HLA-DR15-PR3216-231 complexes revealed an unconventional mode of HLA class II antigen presentation, in which a 10 amino acid peptide core occupies the 9 amino acid binding groove, causing a central kink in the bound peptide. PR3216-231-specific CD4 T cells from both hPR3.DR15+ mice and patients with PR3-ANCA-associated vasculitis exhibited convergent T cell receptor features, and patients with active vasculitis displayed a clonally expanded, PR3216-231-specific CD4 TCR repertoire. Immunization of hPR3.DR15 mice with PR3216-231 induced cell-mediated glomerulonephritis characterized by increased renal infiltration of CD4 T cells and macrophages together with segmental glomerular necrosis. These findings identify a nephritogenic PR3-derived CD4 T cell epitope presented by HLA-DR15 in ANCA-associated vasculitis and define a new extended core binding pattern, broadening our understanding of HLA class II peptide presentation.

immunology↗

bioRxiv2026

Identification of HLA-A33-restricted CD8+ T cell epitopes from avian influenza A/H5N1

The rapid evolution of avian influenza A/H5N1, including the recent U.S. clade 2.3.4.4b outbreak, highlights its pandemic potential and the urgent need for durable, broadly protective vaccines. Given the capacity of CD8+ T cells to mediate cross-strain immunity, we investigated whether geographically distinct HLA-A33 allotypes, HLA-A*33:01 in East/Southeast Asia and HLA-A*33:03 in South Asia, differentially shape the influenza immunopeptidome and influence antiviral immunity. Antigen-presenting cells overexpressing HLA-A*33:01 or HLA-A*33:03 were transfected with single A/H5N1 antigens or infected with A/X-31 (H3N2) as a control comparison representing current seasonal influenza virus. We identified novel ligands restricted to HLA-A*33:01 (57 from A/H5N1; 55 from A/X-31) and HLA-A*33:03 (29 from A/H5N1; 45 from A/X-31). Although fewer peptides were recovered for HLA-A*33:03, a larger proportion of A/X-31-derived peptides were predicted as high-affinity binders (74%) compared with HLA-A*33:01 (61%), indicating qualitative differences in antigen presentation. To determine immunogenicity, peripheral blood lymphocytes from HLA-A*33:03-positive, A/H5N1-naive donors were stimulated with four conserved peptides: PB2GTF, PB2KTY, NPSVQ and PB1MTK. All elicited robust CD8 T cell activation despite the absence of prior A/H5N1 exposure, demonstrating cross-recognition by memory T cells primed against seasonal influenza. These findings define HLA-A33-restricted influenza epitopes and reveal allotype-specific presentation features that shape CD8+ T cell immunity. Conserved, immunogenic peptides identified here represent promising candidates for rational design of broadly cross-reactive vaccines to protect HLA-A33-expressing populations against severe A/H5N1 disease. Data are available via ProteomeXchange with identifier PXD078870. Author SummaryAvian influenza A/H5N1 continues to pose a significant pandemic threat because of its ability to infect humans and its potential to acquire sustained human-to-human transmissibility. While current influenza vaccines primarily target rapidly evolving viral surface proteins, CD8+ T cells can recognize more conserved internal viral proteins and may provide broader protection against diverse influenza strains. In this study, we investigated how two common HLA-A33 variants, which are prevalent in South, East, and Southeast Asian populations, present influenza-derived peptides to CD8+ T cells. We identified novel influenza peptides presented by HLA-A*33:01 and HLA-A*33:03. Importantly, several conserved A/H5N1-derived peptides were recognized by memory CD8+ T cells from healthy individuals with no prior exposure to A/H5N1, suggesting that previous infection with seasonal influenza viruses can generate cross-reactive immune responses. Our findings expand the current repository of influenza T cell targets and provide new insights into antiviral immunity in HLA-A33-expressing populations. The conserved and immunogenic peptides identified in this study may help guide the development of broadly protective influenza vaccines and contribute to future pandemic preparedness efforts.

immunology↗

bioRxiv2026

Generative design of antigen-specific T-cell receptor sequences with a conditional diffusion model

T cell receptor (TCR)-based immunotherapy holds immense potential for treating cancers, autoimmunity, and infectious diseases, where antigen-specific TCR recognition is crucial for adaptive immune responses. Engineering or de novo generation of the complementarity-determining region 3 (CDR3) loops of TCRs using artificial intelligence offers a powerful alternative to designing antigen-specific TCRs rather than laborious experimental screening. However, current in silico approaches are constrained by weak conditional guidance, limited flexibility, and a lack of rigorous functional validation. To address these limitations, we introduce TCRDiff, a generative diffusion framework for designing antigen-specific TCRs conditioned on peptide-MHC (pMHC) targets and germline-encoded TCR variable genes. By leveraging pre-trained knowledge from massive T-cell repertoires and TCR-pMHC recognition data, TCRDiff generates CDR3{beta} sequences that closely resemble native-binding TCRs via a denoising diffusion process. Furthermore, incorporating interface geometry features generated TCR-pMHC complexes with superior structural plausibility than models relying solely on sequence-based diffusion or structure-based modeling. As a proof of concept, we deployed TCRDiff in a systematic pipeline to design candidate TCRs against a clinically validated cancer antigen. In vitro activation assays validated that TCRDiff-generated TCRs efficiently recognize the MAGE-A3 epitope with minimal off-target reactivity. Thus, TCRDiff establishes a powerful, validated computational paradigm to accelerate the development of TCR-based immunotherapies.

bioinformatics↗

bioRxiv2026

Temporal expression of liver-stage malaria antigens shapes vaccine efficacy

Vaccine-induced cytotoxic T cells can prevent malaria by killing parasite-infected hepatocytes during the liver stage. While several antigenic targets have been identified, little consideration has been given to their temporal expression. Here, we identified SERA1 of Plasmodium berghei as a late liver-stage target in rodent malaria and further showed that the classic vaccine antigen thrombospondin-related adhesion protein (TRAP) is only an early target. While vaccination with either antigen alone was modestly protective, combining these antigens enabled killing over the entire liver-stage, greatly improving efficacy. Given the relatively long liver-stage in human malaria, our findings imply TRAP-dependent vaccines likely utilize only a small proportion of the available liver-stage to eradicate parasites. Our findings further indicate that considerations of temporal coverage when selecting vaccine antigens will improve efficacy. One-Sentence SummaryTemporally defining presentation of liver-stage antigens informs rational combinations that maximize malaria vaccine efficacy.

immunology↗

bioRxiv2026

Immunopeptidomics reveals peptide antigens preferentially presented in psoriasis lesional skin of HLA-C*06:02 carriers

BackgroundHuman leukocyte antigen (HLA)-C*06:02 is a major genetic risk factor for psoriasis and understanding the HLA-C*06:02-presented peptide antigen repertoire (immunopeptidome) in the skin of patients is crucial for identifying autoantigens. Yet, no skin immunopeptidome data from patients stratified by their HLA-C*06:02 status exists. ObjectiveWe analysed biopsies from lesional and non-lesional skin of patients with psoriasis vulgaris (n=12), guttate psoriasis (n=8), or from skin of healthy controls (n=16). MethodsHLA class I and class II peptide complexes were isolated by serial immunoprecipitation and HLA-bound peptides identified by liquid chromatography-tandem mass spectrometry. HLA-C*06:02 genotyping was performed by polymerase chain reaction. ResultsOver 99,000 non-redundant peptide ligands were identified across all samples. Substantially more HLA class I and class II peptides were detected in lesional psoriatic skin compared to matched non-lesional and healthy skin. Three peptides predicted to bind HLA-C*06:02, including MRASSFLIV from the known psoriasis marker peptidase inhibitor 3 (PI3), were identified in all lesions of HLA-C*06:02-positive patients but were rarely detected or absent in HLA-C*06:02-negative patient lesional skin and not detected at all in unaffected skin. Keratinocyte differentiation-associated protein (KRTDAP) was a notable source of lesion-specific HLA class II ligands contributing three out of six peptides detected in more than half of the lesional samples. ConclusionActive psoriatic lesions display an altered and expanded immunopeptidome compared to unaffected skin. We have identified numerous unreported, lesion-specific HLA-bound peptides and their source proteins. These findings offer insights into the pathobiology of psoriasis and provide a resource for future functional studies. CAPSULE SUMMARYA selection of immunopeptides is presented exclusively in lesional skin of HLA-C*06:02+ patients with psoriasis that may represent antigenic drivers of disease.

immunology↗

bioRxiv2025

The antigen presenting molecule MR1 binds riboflavin catabolites

Major histocompatibility-complex (MHC) class I-related (MR1) protein presents vitamin B based antigens to Mucosal-Associated Invariant T (MAIT) cells. While microbial riboflavin precursors are well documented MR1 ligands, it is unclear whether host-generated riboflavin catabolites influence MR1-mediated immunity. Here, we report that riboflavin catabolites, including 10-formylmethylflavin (FMF), lumichrome, lumiflavin and alloxazine bind to MR1 with moderate affinity, while riboflavin itself binds weakly. In contrast to the microbial riboflavin antigens which increase MR1 cell surface expression, the riboflavin catabolites moderately reduced cell surface levels of MR1 by stabilizing and retaining MR1 in the endoplasmic reticulum (ER). The riboflavin catabolites appeared to bind to the intracellular MR1 and inhibit MR1 exit from the ER. These riboflavin catabolites also weakly competed with Vit B based Ags for MR1 binding, thereby inhibiting MAIT cell activation. The crystal structures of MR1 complexed with riboflavin, FMF, lumichrome and lumiflavin, show binding of these three-ringed ligands in the A-pocket of MR1. The crystal structure of MR1-lumichrome revealed that lumichrome formed a covalent "flavin bond" with MR1-Lys43 differing from the typical Schiff-base bond of MR1-Lys43-Ag complexes. Collectively, we identified three ring isoalloxazines that can bind MR1 and downregulate cell surface expression levels, suggesting a potential role in dampening MAIT cell immunity.

biochemistry↗

bioRxiv2025

A transgenic mouse allows to capture the HLA-C*06:02 immunopeptidome in a model of psoriasis

Psoriasis vulgaris is a T cell-mediated autoimmune skin condition affecting around one in fifty people worldwide. Whilst advanced immunomodulatory therapeutic options have become available in recent years, ongoing disease suppression is still required with no curative treatment available to date. The human leukocyte antigen class I allele HLA-C*06:02 is the main genetic risk determinant of psoriasis. Its function is to present peptide antigens to CD8+ T cells and natural killer cells which in turn elicit and perpetuate the immune response, yet little is known about ligands presented by HLA-C*06:02. To gain an understanding which HLA-C*06:02-restricted peptides are presented by epidermal cell populations and might be initiators of the autoimmune response in psoriasis, we have conducted an in depth immunopeptidomics analysis of HLA-C*06:02+ keratinocyte and melanocyte cell lines. Furthermore, we introduce a HLA-C*06:02 transgenic mouse which, in conjunction with the imiquimod model of psoriasis, allowed us to assess the ex vivo immunopeptidome of HLA-C*06:02 in psoriasiform skin. Overall, we detected 20,812 high confidence HLA-C*06:02 bound peptide ligands. Thus, we present a comprehensive coverage HLA-C in vitro immunopeptidomics dataset and the first HLA-C*06:02 ex vivo dataset of psoriasis-relevant peptide antigens that may inform the development of antigen-specific, novel curative therapeutic approaches in psoriasis.

immunology↗

bioRxiv2024

A quantitative approach to poxvirus infection reveals general correlates of antigen presentation and immunogenicity for viral CD8+ T cell epitopes

CD8+ T cells are essential effectors in antiviral immunity that kill infected cells displaying viral peptide epitopes on MHC class I. The pathways underpinning antigen presentation on MHC I are well known but we lack a general understanding of the quantitative and kinetic relationships between source proteins and presented epitopes, and how these relate to immunogenicity. We used quantitative mass spectrometry to interrogate infection with vaccinia virus, the MPOX vaccine, measuring amounts of >40 viral epitopes and their source proteins multiple times after infection in four cell types. This revealed that up to 90% of the epitopes were presented as fast as their source proteins were made and that protein amounts failed to correlate with epitope levels. Further, a significant correlation between epitope levels and immunogenicity required presentation to be quantified ex vivo, with each step away from a matched infection route and natural presenting cell eroding the association.

immunology↗

bioRxiv2024

Epitope-anchored contrastive transfer learning for paired CD8+ T cell receptor-antigen recognition

Understanding the mechanisms of T-cell antigen recognition that underpin adaptive immune responses is critical for the development of vaccines, immunotherapies, and treatments against autoimmune diseases. Despite extensive research efforts, the accurate identification of T cell receptor (TCR)-antigen binding pairs remains a significant challenge due to the vast diversity and cross-reactivity of TCRs. Here, we propose a deep-learning framework termed Epitope-anchored Contrastive Transfer Learning (EPACT) tailored to paired human CD8+ TCRs from single-cell sequencing data. Harnessing the pre-trained representations and the contrastive co-embedding space, EPACT demonstrates state-of-the-art model generalizability in predicting TCR binding specificity for unseen epitopes and distinct TCR repertoires, offering potential values for practical outcomes in real-world scenarios. The contrastive learning paradigm achieves highly precise predictions for immunodominant epitopes and facilitates interpretable analysis of epitope-specific T cells. The TCR binding strength predicted by EPACT aligns well with the surge in spike-specific immune responses targeting SARS-CoV-2 epitopes after vaccination. We further fine-tune EPACT on TCR-epitope structural data to decipher the residue-level interactions involved in T-cell antigen recognition. EPACT not only exhibits superior capabilities in quantifying inter-chain distance matrices and identifying contact residue pairs but also corroborates the presence of molecular mimicry across multiple tumor-associated antigens. Together, EPACT can serve as a useful AI approach with significant potential in practical applications and contribute toward the development of TCR-based diagnostics and immunotherapies.

bioinformatics↗

bioRxiv2024

A Simple and Rapid Protocol for the Isolation of Murine Bone Marrow Suitable for the Differentiation of Dendritic Cells

The generation of bone marrow-derived dendritic cells is a widely used approach in immunological research to study antigen processing and presentation as well as T cell activation responses. However, the initial step of isolating the bone marrow can be time-consuming, especially when larger numbers of precursor cells are required. Here, we assessed whether an accelerated bone marrow isolation method using centrifugation is suitable for the differentiation of FMS-like tyrosine kinase 3 ligand-driven dendritic cells. Compared to the conventional flushing method, the centrifugation-based isolation method resulted in a similar bone marrow cell yield on day 0, increased cell numbers by day 8, similar proportions of dendritic cell subsets, and consequently a higher number of type 1 conventional dendritic cells (cDC1) from the culture. Although the primary purpose of the method optimization was to improve experimental efficiency and increase the output of cDC1s, the protocol is also compatible with the differentiation of other dendritic cell subsets such as cDC2 and plasmacytoid dendritic cells, with an improved output cell count and a consistent phenotype.

immunology↗

bioRxiv2023

Conserved allomorphs of MR1 drive specificity of MR1-restricted TCRs

Major histocompatibility complex class-1-related protein (MR1), unlike human leukocyte antigen (HLA) class-1, has until recently been reported to be monomorphic. Tumor cell-specific MR1 restricted T cell receptors (TCRs) have been described, offering potential therapeutic application for cancer treatment. We show that human T cells expressing a TCR derived from an MR1-restricted T cell clone, termed MC.7.G5 (7G5.TCRT), retain MR1-directed cytotoxicity. However, activity is not pan-cancer, as initially reported with the clone MC.7.G5. Recognition is restricted by an allelic variant of MR1 (MR1*04) which is present at approximately 1% of the population at the heterozygote level. The 7G5 TCR is not cancer specific, as 7G5.TCRT and 7G5.TCRT-like TCRs react to both cancer and healthy cells expressing MR1*04 alleles. These data demonstrate that healthy individuals can harbor T cells reactive to an MR1 variant displaying self-ligands expressed in cancer and benign tissues. Targeting MR1 in cancer will require identification of cancer-specific presented ligands, and careful confirmation of cancer specificity of TCRs. MR1*04 may behave as an alloantigen warranting further study.

cancer biology↗

bioRxiv2023

Endogenous viral elements constitute a complementary source of antigens for personalized cancer immunotherapy

Personalized cancer vaccines (PCVs) largely leverage neoantigens arising from somatic mutations limiting their application to patients with relatively high tumor mutational burden (TMB). This underscores the need for alternative antigens to design PCVs for low TMB cancers. To this end, we substantiate endogenous retroviral elements (EVEs) as tumor antigens through large-scale genomic analyses of healthy tissues and solid cancers. These analyses revealed that the breadth of EVE expression in tumors stratify checkpoint inhibitor treated melanoma patients into groups with differential overall and progression-free survival. To enable the design of PCVs containing EVE-derived epitopes with therapeutic potential, we developed a computational pipeline, ObsERV. We show that EVE-derived peptides are presented as epitopes on tumors and can be predicted by ObsERV. Preclinical testing of ObsERV demonstrates induction of sustained poly-functional CD4+ and CD8+ T-cell responses as well as long-term tumor protection. As such, EVEs may facilitate and improve PCVs especially for low-TMB patients.

cancer biology↗

bioRxiv2022

TCR_Explore: a novel webtool for T cell receptor repertoire analysis

T cells expressing either alpha-beta or gamma-delta T cell receptors (TCR) are critical sentinels of the adaptive immune system, with receptor diversity being essential for protective immunity against a broad array of pathogens and agents. Programs available to profile TCR clonotypic signatures can be limiting for users with no coding expertise. Current analytical pipelines can be inefficient due to manual processing steps, open to data transcription errors and have multiple analytical tools with unique inputs that require coding expertise. Here we present a bespoke webtool designed for users irrespective of coding expertise, coined TCR_Explore, incorporating automated quality control steps that generates a single output file for creation of flexible and publication ready figures. TCR_Explore will elevate a users capacity to undertake in-depth TCR repertoire analysis of both new and pre-existing datasets for identification of T cell clonotypes associated with health and disease. The web application is located at https://tcr-explore.erc.monash.edu for users to interactively explore TCR repertoire datasets. Key PointsO_LIBespoke program for non-specialists in computerised methodologies for deep exploration of TCR repertoire analysis C_LIO_LIAutomated QC and analysis pipelines for Sanger based TCR sequencing coupled with immunophenotyping, with the capacity for integration of other sequencing platform outputs C_LIO_LIAutomated summary processes to aid data visualisation and generation of publication-ready graphical displays C_LI

bioinformatics↗

bioRxiv2021

Defective proinsulin handling modulates the MHC I bound peptidome and activates the inflammasome in β-cells

BackgroundHow immune-tolerance is lost to pancreatic {beta}-cell peptides triggering autoimmune type 1 diabetes is enigmatic. We have shown that loss of the proinsulin ER chaperone glucose-regulated protein (GRP) 94 leads to mishandling of proinsulin, ER stress and activation of the inducible proteasome. We hypothesize that inadequate ER proinsulin folding capacity relative to biosynthetic need may lead to an altered {beta}-cell MHC-I bound peptidome and inflammasome activation, sensitizing {beta}-cells to immune attack. MethodsWe used INS-1E cells with or without GRP94 knockout (KO), or in the presence or absence of GRP94 inhibitor PU-WS13 (GRP94i, 20{micro}M), or exposed to proinflammatory cytokines interleukin (IL)-1{beta} or IFN{gamma} (15 pg/ml and 10 ng/ml, respectively) for 24 hours. RT1.A (rat MHC I) expression was evaluated using flow cytometry. The total RT1.A-bound peptidome analysis was performed on cell lysates fractionated by reverse phase high performance liquid chromatography (RP-HPLC) followed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). NALP1, nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor alpha (I{kappa}B), and (pro) IL-1{beta} expression and secretion were investigated by Western blotting. ResultsGRP94 KO increased RT1.A expression in {beta}-cells as did cytokine exposure compared to relevant controls. Immunopeptidome analysis showed increased RT1.A-bound peptide repertoire in GRP94 KO/i cells as well as in the cells exposed to cytokines. The GRP94 KO/cytokine exposure groups showed partial overlap in their peptide repertoire. Notably, proinsulin-derived peptides diversity increased among the total RT1.A peptidome in GRP94 KO/i along with cytokines exposure. NALP1 expression was upregulated in GRP94 deficient cells along with decreased I{kappa}B content while proIL-1{beta} cellular levels declined, coupled with an increased secretion of mature IL-1{beta}. Our results suggest that limiting {beta}-cell proinsulin chaperoning enhances RT1.A expression, alters the MHC-I peptidome including proinsulin peptides and activates inflammatory pathways, suggesting that stress impeding proinsulin handling may sensitize {beta}-cells to immune-attack.

molecular biology↗

bioRxiv2021

Towards a systematic characterization of protein complex function: a natural language processing and machine-learning framework

It is a general assumption of molecular biology that the ensemble of expressed molecules, their activities and interactions determine biological processes, cellular states and phenotypes. Quantitative abundance of transcripts, proteins and metabolites are now routinely measured with considerable depth via an array of "OMICS" technologies, and recently a number of methods have also been introduced for the parallel analysis of the abundance, subunit composition and cell state specific changes of protein complexes. In comparison to the measurement of the molecular entities in a cell, the determination of their function remains experimentally challenging and labor-intensive. This holds particularly true for determining the function of protein complexes, which constitute the core functional assemblies of the cell. Therefore, the tremendous progress in multi-layer molecular profiling has been slow to translate into increased functional understanding of biological processes, cellular states and phenotypes. In this study we describe PCfun, a computational framework for the systematic annotation of protein complex function using Gene Ontology (GO) terms. This work is built upon the use of word embedding-- natural language text embedded into continuous vector space that preserves semantic relationships-- generated from the machine reading of 1 million open access PubMed Central articles. PCfun leverages the embedding for rapid annotation of protein complex function by integrating two approaches: (1) an unsupervised approach that obtains the nearest neighbor (NN) GO term word vectors for a protein complex query vector, and (2) a supervised approach using Random Forest (RF) models trained specifically for recovering the GO terms of protein complex queries described in the CORUM protein complex database. PCfun consolidates both approaches by performing the statistical test for the enrichment of the top NN GO terms within the child terms of the predicted GO terms by RF models. Thus, PCfun amalgamates information learned from the gold-standard protein-complex database, CORUM, with the unbiased predictions obtained directly from the word embedding, thereby enabling PCfun to identify the potential functions of putative protein complexes. The documentation and examples of the PCfun package are available at https://github.com/sharmavaruns/PCfun. We anticipate that PCfun will serve as a useful tool and novel paradigm for the large-scale characterization of protein complex function.

bioinformatics↗

bioRxiv2020

The self-peptide repertoire plays a critical role in transplant tolerance induction

While direct allorecognition underpins both solid organ allograft rejection and tolerance induction, the specific molecular targets of most directly-alloreactive CD8+ T cells have not been defined. In this study, we used a combination of genetically-engineered MHC class I (MHC I) constructs, mice with a hepatocyte-specific mutation in the class I antigen-presentation pathway and immunopeptidomic analysis to provide definitive evidence for the contribution of the peptide cargo of allogeneic MHC I molecules to transplant tolerance induction. We established a systematic approach for the discovery of directly-recognised pMHC epitopes, and identified 17 strongly immunogenic H-2Kb-associated peptides recognised by CD8+ T cells from B10.BR (H-2k) mice, 13 of which were also recognised by BALB/c (H-2d) mice. As few as five different tetramers used together were able to identify a high proportion of alloreactive T cells within a polyclonal population, suggesting that there are immunodominant allogeneic MHC-peptide complexes that can account for a large component of the alloresponse.

immunology↗

bioRxiv2020

Immunopeptidomics for Dummies: Detailed Experimental Protocols and Rapid, User-Friendly Visualization of MHC I and II Ligand Datasets with MhcVizPipe

Immunopeptidomics refers to the science of investigating the composition and dynamics of peptides presented by major histocompatibility complex (MHC) class I and class II molecules using mass spectrometry (MS). Here, we aim to provide a technical report to any non-expert in the field wishing to establish and/or optimize an immunopeptidomic workflow with relatively limited computational knowledge and resources. To this end, we thoroughly describe step-by-step instructions to isolate MHC class I and II-associated peptides from various biological sources, including mouse and human biospecimens. Most notably, we created MhcVizPipe (MVP) (https://github.com/CaronLab/MhcVizPipe), a new and easy-to-use open-source software tool to rapidly assess the quality and the specific enrichment of immunopeptidomic datasets upon the establishment of new workflows. In fact, MVP enables intuitive visualization of multiple immunopeptidomic datasets upon testing sample preparation protocols and new antibodies for the isolation of MHC class I and II peptides. In addition, MVP enables the identification of unexpected binding motifs and facilitates the analysis of non-canonical MHC peptides. We anticipate that the experimental and bioinformatic resources provided herein will represent a great starting point for any non-expert and will therefore foster the accessibility and expansion of the field to ultimately boost its maturity and impact.

bioinformatics↗

bioRxiv2020

Passage of transmissible cancers in the Tasmanian devil is due to a dominant, shared peptide motif and a limited repertoire of MHC-I allotypes

Transmissible cancers are spread via the passage of malignant cells. The survival of the Tasmanian devil, the largest marsupial carnivore, is threatened by two independent transmissible cancers, devil facial tumour (DFT) 1 and devil facial tumour 2 (DFT2). To aid the development of a peptide vaccine and to interrogate how histocompatibility barriers can be overcome, we analysed the peptides bound to Major Histocompatibility Complex class I molecules from the Tasmanian devil and its transmissible tumours. Comparison of the peptidomes from DFT1+IFNγ, DFT2 and host fibroblast cells demonstrates a shared motif, despite differences in MHC-I allotypes between the cell lines. Importantly, DFT1+IFNγ and DFT2 share the presentation of peptides derived from neural proteins, reflecting a common cellular origin that should be exploited for vaccine design. These results suggest that some polymorphisms between tumours and host are ‘hidden’ by a common peptide motif, providing the potential for permissive passage of infectious cells.Competing Interest StatementThe authors have declared no competing interest.View Full Text

immunology↗