Biology subjects

Snyder, M. P.

Publications and source records attributed to Snyder, M. P..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Accelerated Hematopoietic Stem Cell Aging in Space

Stem cell aging is accelerated by macroenvironmental and microenvironmental stressors, including inflammation. Previously, the NASA Twins study revealed inflammatory cytokine upregulation, chromosomal alterations, and telomere changes suggestive of accelerated aging in low-Earth orbit (LEO). To investigate the effects of spaceflight on human hematopoietic stem and progenitor cell (HSPC) aging, the NASA-supported Integrated Space Stem Cell Orbital Research team performed four independent 30- to 45-day NASA missions with matched flight and ground HSPC nanobioreactors in automated CubeLabs. These experiments revealed loss of HSPC dormancy, reduced self-renewal capacity, mitochondrial DNA amplification, APOBEC3-induced C-to-T mutagenesis, reduced ADAR1p150 expression, and alterations in the expression of repetitive elements. These molecular changes are indicative of accelerated HSPC aging and pre-leukemia stem cell generation in space and may be predictable and preventable.

cancer biology↗

bioRxiv2024

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease

To understand dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune and clinical markers of microbiomes from four body sites in 86 participants over six years. We found that microbiome stability and individuality are body-site-specific and heavily influenced by the host. The stool and oral microbiome were more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. Also, we identified individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlated across body sites, suggesting systemic coordination influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals showed altered microbial stability and associations between microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease. Study HighlightsO_LIThe stability of the human microbiome varies among individuals and body sites. C_LIO_LIHighly individualized microbial genera are more stable over time. C_LIO_LIAt each of the four body sites, systematic interactions between the environment, the host and bacteria can be detected. C_LIO_LIIndividuals with insulin resistance have lower microbiome stability, a more diversified skin microbiome, and significantly altered host-microbiome interactions. C_LI

microbiology↗

bioRxiv2024

A Multiomics, Spatiotemporal, and Single Cell Atlas for Mapping Cell-Type-Specific Dysregulation at the Maternal-Fetal Interface

The placenta, the first organ to functionally mature, undergoes disordered development in many pregnancy complications. Molecular investigations have been hampered by the extreme cellular heterogeneity of the placenta, and this complexity is further exaggerated at the maternal-fetal interface where maternal and fetal cells co-mingle. We generated the paired single nucleus epigenomes and transcriptome for each of [~]200,000 cells at the human maternal-fetal interface from early pregnancy to term. These data identified cell-type-specific transcriptional regulatory programs and uncovered key transcription factors driving the lineage differentiation of placental cytotrophoblasts. Integrating spatial single cell proteomics profiling, we localized the observed cell types in situ, and characterized the dynamic stages and distinct features of endothelial cells of maternal spiral arteries remodeled by extravillous cytotrophoblasts. Integrative analyses of the single cell data across gestation enabled fine-mapping of the developmental trajectories of cytotrophoblasts and decidual stromal cells, and defining the signature molecular profiles of known and novel cell (sub)types. To demonstrate clinical value, we integrated the reference single cell data with large-scale population genomes from pregnancy complications and identified the most vulnerable maternal and fetal cell types in preeclampsia, preterm birth, and miscarriage. This study presents the most comprehensive placental and decidual single cell resource across gestation to date, reveals new insights into the drivers of normal human placentation, and uncovers the cellular basis of dysfunction associated with common pregnancy complications.

genomics↗

bioRxiv2024

Short-chain fatty acids propionate and butyrate control growth and differentiation linked to cellular metabolism

The short-chain fatty acids (SCFA) propionate and butyrate have beneficial health effects, are produced in large amounts by microbial metabolism and have been identified as unique acyl lysine histone marks. In order to better understand the function of these modifications we used ChIP-seq to map the genome-wide location of four short-chain acyl histone marks H3K18pr, H3K18bu, H4K12pr and H4K12bu in treated and untreated colorectal cancer (CRC) and normal cells, as well as in mouse intestines in vivo. We correlate these marks with open chromatin regions along with gene expression to access the function of the target regions. Our data demonstrate that propionate and butyrate bind and act as promoters of genes involved in growth, differentiation as well as ion transport. We propose a mechanism involving direct modification of specific genomic regions, by SCFA resulting in increased chromatin accessibility, and in case of butyrate, opposing effects on the proliferation of normal versus CRC cells.

genetics↗

bioRxiv2023

Mapping ovarian cancer spatial organization uncovers immune evasion drivers at the genetic, cellular, and tissue level

Immune exclusion and evasion are central barriers to the success of immunotherapies and cell therapies in solid tumors. Here we applied single cell spatial and perturbational transcriptomics alongside clinical, histological, and genomic profiling to elucidate immune exclusion and evasion in high-grade serous tubo-ovarian cancer (HGSC). Using high-plex spatial transcriptomics we profiled more than 1.3 million cells from 95 tumors and 60 patients, revealing generalizable principles in HGSC tumor tissue organization. Our data demonstrates that effector T cells resist stroma-mediated trapping and sequestration. However, upon infiltration into the tumor, T cells, as well as Natural Killer (NK) cells, preferentially co-localize only with a subset of malignant cells that manifest a distinct transcriptional cell state. The latter consists of dozens of co-regulated genes and is repressed under various copy number alterations. Performing CRISPR Perturb-seq screens in ovarian cancer cells, we identified functionally diverse genetic perturbations - including knockout of the insulin sensing repressor PTPN1 and the epigenetic regulator ACTR8 - that de-repress the proposed immunogenic malignant cell state identified in patients and indeed sensitize ovarian cancer cells to T cell and NK cell cytotoxicity. Taken together, our study uncovered a profound connection between somatic genetic aberrations, malignant cell transcriptional dysregulation, and immune evasion at the cellular and tissue level, allowing us to identify targets that reprogram malignant cell states as an avenue to unleash anti-tumor immune responses.

cancer biology↗

bioRxiv2023

Integrative Multi-omic Profiling of Two Human Decedents Receiving Pig Heart Xenografts Reveals Strong Perturbations in Early Immune-Cell and Cellular Metabolism Responses.

BackgroundRecent advances in xenotransplantation in living and decedent humans using pig xenografts have laid promising groundwork towards future emergency use and first in human trials. Major obstacles remain though, including a lack of knowledge of the genetic incompatibilities between pig donors and human recipients which may led to harmful immune responses against the xenograft or dysregulation of normal physiology. In 2022 two pig heart xenografts were transplanted into two brain-dead human decedents with a minimized immunosuppression regime, primarily to evaluate onset of hyper-acute antibody mediated rejection and sustained xenograft function over 3 days. MethodsWe performed multi-omic profiling to assess the dynamic interactions between the pig and human genomes in the first two pig heart-xenografts transplants into human decedents. To assess global and specific biological changes that may correlate with immune-related outcomes and xenograft function, we generated transcriptomic, lipidomic, proteomic and metabolomics datasets, across blood and tissue samples collected every 6 hours over the 3-day procedures. ResultsSingle-cell datasets in the 3-day pig xenograft-decedent models show dynamic immune activation processes. We observe specific scRNA-seq, snRNA-seq and geospatial transcriptomic changes of early immune-activation leading to pronounced downstream T-cell activity and hallmarks of early antibody mediated rejection (AbMR) and/or ischemia reperfusion injury (IRI) in the first xenograft recipient. Using longitudinal multiomic integrative analyses from blood in addition to antigen presentation pathway enrichment, we also observe in the first xeno-heart recipient significant cellular metabolism and liver damage pathway changes that correlate with profound physiological dysfunction whereas, these signals are not present in the other xenograft recipient. ConclusionsSingle-cell and multiomics approaches reveal fundamental insights into early molecular immune responses indicative of IRI and/or early AbMR in the first human decedent, which was not evident in the conventional histological evaluations.

systems biology↗

bioRxiv2023

The ENCODE4 long-read RNA-seq collection reveals distinct classes of transcript structure diversity

The majority of mammalian genes encode multiple transcript isoforms that result from differential promoter use, changes in exonic splicing, and alternative 3 end choice. Detecting and quantifying transcript isoforms across tissues, cell types, and species has been extremely challenging because transcripts are much longer than the short reads normally used for RNA-seq. By contrast, long-read RNA-seq (LR-RNA-seq) gives the complete structure of most transcripts. We sequenced 264 LR-RNA-seq PacBio libraries totaling over 1 billion circular consensus reads (CCS) for 81 unique human and mouse samples. We detect at least one full-length transcript from 87.7% of annotated human protein coding genes and a total of 200,000 full-length transcripts, 40% of which have novel exon junction chains. To capture and compute on the three sources of transcript structure diversity, we introduce a gene and transcript annotation framework that uses triplets representing the transcript start site, exon junction chain, and transcript end site of each transcript. Using triplets in a simplex representation demonstrates how promoter selection, splice pattern, and 3 processing are deployed across human tissues, with nearly half of multitranscript protein coding genes showing a clear bias toward one of the three diversity mechanisms. Evaluated across samples, the predominantly expressed transcript changes for 74% of protein coding genes. In evolution, the human and mouse transcriptomes are globally similar in types of transcript structure diversity, yet among individual orthologous gene pairs, more than half (57.8%) show substantial differences in mechanism of diversification in matching tissues. This initial large-scale survey of human and mouse long-read transcriptomes provides a foundation for further analyses of alternative transcript usage, and is complemented by short-read and microRNA data on the same samples and by epigenome data elsewhere in the ENCODE4 collection.

genomics↗

bioRxiv2022

Organism-wide secretome mapping uncovers pathways of tissue crosstalk in exercise

There has been growing interest in identifying blood-borne factors that mediate tissue crosstalk and function as molecular effectors of physical activity. Although past studies have focused on an individual molecule or cell type, the organism-wide secretome response to physical activity has not been evaluated. Here, we use a cell type-specific proteomic approach to generate a 21-cell type, 10-tissue map of exercise-regulated secretomes in mice. Our dataset identifies >200 exercise-regulated cell type-secreted protein pairs, the majority of which have not been previously reported. Pdgfra-cre-labeled secretomes were the most responsive to exercise training. Elevated lactate levels can directly regulate protein secretion. Lastly, we establish an anti-obesity and anti-diabetic role for a proteoform of an intracellular carboxylesterase whose secretion from the liver is induced by exercise training. Together, our data uncover the dynamic remodeling of cell and tissue crosstalk by physical activity.

systems biology↗

bioRxiv2022

Global loss of fine-scale chromatin architecture and rebalancing of gene expression during early colorectal cancer development

Although 3D genome architecture can be essential for gene regulation, the biological implications of long-range chromatin interactions in disease remain elusive. In this study, we traced the early evolution and malignant transformation of colorectal cancer by generating high-resolution chromatin conformation maps of 33 colon samples spanning different stages of early neoplastic growth from polyps of Familial Adenomatous Polyposis (FAP) patients. Our analysis reveals a substantial progressive loss of genome-wide cis-regulatory connectivity at early stages of malignancy, which correlates with a non-linear effect on gene regulation. Genes with high promoter-enhancer (P-E) connectivity in unaffected mucosa are not correlated with elevated baseline expression, but instead tend to be up-regulated at advanced stages. Inhibition of highly connected promoters preferentially represses gene expression in colorectal cancer cells relative to normal colonic epithelial cells. Our results suggest a two-phase model whereby neoplastic transformation reduces P-E connectivity from a redundant state to a rate-limiting one for transcriptional levels. Overall, our study illuminates the intricate interplay between 3D genome architecture and gene regulation during early colorectal cancer progression, and provides valuable insights for potential therapeutic interventions targeting the connectivity of cis-regulatory elements.

genomics↗

bioRxiv2022

A genome-wide atlas of recurrent repeat expansions in human cancer

Expansion of a single repetitive DNA sequence, termed a tandem repeat (TR), is known to cause more than 50 diseases. However, repeat expansions are often not explored beyond neurological and neurodegenerative disorders. In some cancers, mutations accumulate in short tracts of TRs (STRs), a phenomenon termed microsatellite instability (MSI); however larger repeat expansions have not been systematically analyzed in cancer. Here, we identified TR expansions in 2,622 cancer genomes, spanning 29 cancer types. In 7 cancer types, we found 160 recurrent repeat expansions (rREs); most of these (155/160) were subtype specific. We found that rREs were non-uniformly distributed in the genome with an enrichment near candidate cis-regulatory elements, suggesting a role in gene regulation. One rRE located near a regulatory element in the first intron of UGT2B7 was detected in 34% of renal cell carcinoma samples and was validated by long-read DNA sequencing. Moreover, targeting cells harboring this rRE with a rationally designed, sequence-specific DNA binder led to a dose-dependent decrease in cell proliferation. Overall, our results demonstrate that rREs are an important but unexplored source of genetic variation in human cancers, and we provide a comprehensive catalog for further study.

genomics↗

bioRxiv2022

Lipidomic profiling reveals age-dependent changes in complex plasma membrane lipids that regulate neural stem cell aging

The aging brain exhibits a decline in the regenerative populations of neural stem cells (NSCs), which may underlie age-associated defects in sensory and cognitive functions1-6. While mechanisms that restore old NSC function have started to be identified7-23, the role of lipids - especially complex lipids - in NSC aging remains largely unclear. Using lipidomic profiling by mass spectrometry, we identify age-related lipidomic signatures in young and old quiescent NSCs in vitro and in vivo. These analyses reveal drastic changes in several complex membrane lipid classes, including phospholipids and sphingolipids in old NSCs. Moreover, poly-unsaturated fatty acids (PUFAs) strikingly increase across complex lipid classes in quiescent NSCs during aging. Age-related changes in complex lipid levels and side chain composition are largely occurring in plasma membrane lipids, as revealed by lipidomic profiling of isolated plasma membrane vesicles. Experimentally, we find that aging is accompanied by modifications in plasma membrane biophysical properties, with a decrease in plasma membrane order in old quiescent NSCs in vitro and in vivo. To determine the functional role of plasma membrane lipids in aging NSCs, we performed genetic and supplementation studies. Knockout of Mboat2, which encodes a phospholipid acyltransferase, exacerbates age-related lipidomic changes in old quiescent NSCs and impedes their ability to activate. As Mboat2 expression declines with age, Mboat2 deficiency may drive NSC decline during aging. Interestingly, supplementation of plasma membrane lipids derived from young NSCs boosts the ability of old quiescent NSCs to activate. Our work could lead to lipid-based strategies for restoring the regenerative potential of NSCs in old individuals, which has important implications for countering brain decline during aging.

molecular biology↗

bioRxiv2022

The ENCODE Imputation Challenge: A critical assessment of methods for cross-cell type imputation of epigenomic profiles

Functional genomics experiments are invaluable for understanding mechanisms of gene regulation. However, comprehensively performing all such experiments, even across a fixed set of sample and assay types, is often infeasible in practice. A promising alternative to performing experiments exhaustively is to, instead, perform a core set of experiments and subsequently use machine learning methods to impute the remaining experiments. However, questions remain as to the quality of the imputations, the best approaches for performing imputations, and even what performance measures meaningfully evaluate performance of such models. In this work, we address these questions by comprehensively analyzing imputations from 23 imputation models submitted to the ENCODE Imputation Challenge. We find that measuring the quality of imputations is significantly more challenging than reported in the literature, and is confounded by three factors: major distributional shifts that arise because of differences in data collection and processing over time, the amount of available data per cell type, and redundancy among performance measures. Our systematic analyses suggest several steps that are necessary, but also simple, for fairly evaluating the performance of such models, as well as promising directions for more robust research in this area.

bioinformatics↗

bioRxiv2021

High Resolution Single Cell Maps Reveals Distinct Cell Organization and Function Across Different Regions of the Human Intestine

The colon is a complex organ that promotes digestion, extracts nutrients, participates in immune surveillance, maintains critical symbiotic relationships with microbiota, and affects overall health. To better understand its organization, functions, and its regulation at a single cell level, we performed CODEX multiplexed imaging, as well as single nuclear RNA and open chromatin assays across eight different intestinal sites of four donors. Through systematic analyses we find cell compositions differ dramatically across regions of the intestine, demonstrate the complexity of epithelial subtypes, and find that the same cell types are organized into distinct neighborhoods and communities highlighting distinct immunological niches present in the intestine. We also map gene regulatory differences in these cells suggestive of a regulatory differentiation cascade, and associate intestinal disease heritability with specific cell types. These results describe the complexity of the cell composition, regulation, and organization for this organ, and serve as an important reference map for understanding human biology and disease.

genomics↗

bioRxiv2021

Robust and generalizable segmentation of human functional tissue units

The Human BioMolecular Atlas Program aims to compile a reference atlas for the healthy human adult body at the cellular level. Functional tissue units (FTU, e.g., renal glomeruli and colonic crypts) are of pathobiological significance and relevant for modeling and understanding disease progression. Yet, annotation of FTUs is time consuming and expensive when done manually and existing algorithms achieve low accuracy and do not generalize well. This paper compares the five winning algorithms from the "Hacking the Kidney" Kaggle competition to which more than a thousand teams from sixty countries contributed. We compare the accuracy and performance of the algorithms on a large-scale renal glomerulus Periodic acid-Schiff stain dataset and their generalizability to a colonic crypts hematoxylin and eosin stain dataset. Results help to characterize how the number of FTUs per unit area differs in relationship to their position in kidney and colon with respect to age, sex, body mass index (BMI), and other clinical data and are relevant for advancing pathology, anatomy, and surgery.

bioinformatics↗

bioRxiv2021

Evolution of diapause in the African turquoise killifish by remodeling ancient gene regulatory landscape

Suspended animation states such as hibernation or diapause allow organisms to survive extreme environments. But the mechanisms underlying the evolution of these extreme survival states are unknown. The African turquoise killifish has evolved diapause as a form of suspended development to survive the complete drought that occurs every year in its habitat. Here we show that many gene duplicates - paralogs - exhibit specialized expression in diapause versus normal development in the African turquoise killifish. Surprisingly, paralogs with specialized expression in diapause are evolutionarily very ancient, and they are also present even in vertebrates that do not exhibit diapause. Profiling the chromatin accessibility landscape among different fish species reveals an evolutionarily recent increase in chromatin accessibility at these very ancient paralogs, suggesting rewiring of their regulatory landscape. The increase in chromatin accessibility in the African turquoise killifish is linked to the presence of new binding sites for transcription factors (e.g., FOXO, REST, and PPAR), due to both de novo mutations and transposable element insertion. Interestingly, accessible chromatin regions in diapause are enriched for lipid metabolism genes. By performing lipidomics in different fish species, we uncover a specific lipid profile in African turquoise killifish embryos in diapause. Notably, select very long-chain fatty acids are high in diapause, suggesting they may be used for long-term survival in this state. Together, our multi-omic analysis indicates that diapause is driven by regulatory innovation of very ancient gene programs that are critical for survival. Our work also suggests a mechanism for how complex adaptations evolve in nature and offers strategies by which a suspended animation program could be reactivated in other species for long-term preservation.

genomics↗

bioRxiv2021

Gut microbiota analyses of Saudi populations for type 2 diabetes-related phenotypes reveals significant association

Large-scale gut microbiome sequencing has revealed key links between microbiome dysfunction and metabolic diseases such as T2D. To date, these efforts have largely focused on Western populations, with few studies assessing T2D microbiota associations in Middle Eastern communities where T2D prevalence is now over 20%. We analyzed the composition of stool 16S rRNA from 461 T2D and 119 non-T2Dparticipants from the Eastern Province of Saudi Arabia. We quantified the abundance of microbial communities to examine any significant differences between subpopulations of samples based on diabetes status and glucose level. We observed overall positive enrichment within diabetics compared to healthy individuals and amongst diabetic participants; those with high glucose levels exhibited slightly more positive enrichment compared to those at lower risk of fasting hyperglycemia. In particular, the genus Firmicutes was upregulated in diabetic participants compared to non-diabetic participants, and T2D was associated with an elevated Firmicutes/Bacteroidetes ratio, consistent with previous findings. Based on diabetes status and glucose levels of Saudi participants, relatively stable differences in stool composition were perceived by differential abundance and alpha diversity measures. Author summaryThe rates of Type 2 diabetes (T2D) in Saudi Arabia have risen dramatically in the last several decades due to socio-economic changes resulting in changes in dietary and sedentary lifestyles. This emergence has grown more rapidly and affects larger proportions of the population with estimates of T2D prevalence impacting 25% of the population. There is a paucity of microbiome data from Middle Eastern populations, and previous studies have been conducted on small sample sizes. Here we report on the first-ever characterization of gut microbiota T2D versus non-T2D and largest microbiome study ever conducted in a Middle Eastern country. The datasets from this study are important to create a regional reference T2D-microbiome catalogue which will propel the understanding of regional gut flora which are associated with T2D development. Based on T2D status and quantified glucose levels of Middle Eastern participants, relatively stable differences in stool composition were observed by differential abundance and alpha diversity measures. Comparing overlapping and varying patterns in gut microbiota with other studies is critical to assessing novel treatment options in light of a rapidly growing T2D health epidemic.

microbiology↗

bioRxiv2021

Abnormal Differentiation and Proliferation of Coronary Arterial Endothelium in Hypoplastic Left Heart Syndrome

Hypoplastic left heart syndrome (HLHS) is a severe form of single ventricle congenital heart disease characterized by the underdevelopment of the left ventricle. Early serial postmortem examinations revealed high rate of coronary artery abnormalities in HLHS fetal hearts, such as thickened wall, kinking arteries and ventriculo-coronary arterial connection. However, it is unclear if there is an intrinsic defect in the HLHS coronary vessels and what the underlying molecular mechanism is. Here, we profiled both human fetal heart with an underdeveloped left ventricle (ULV) and ECs differentiated from induced pluripotent stem cells (iPSCs) derived from HLHS patients at single cell resolution. CD144+/NPR3-vascular ECs were selected and further classified as venous, arterial and late arterial subclusters. To study the arterial EC phenotype, we specifically generated iPSC-arterial ECs (AECs, CD34+CDH5+CXCR4+NT5E-/low) derived from three HLHS patients and three age-matched healthy controls. Gene ontology analysis revealed that ULV late arterial EC subcluster showed specific defects in endothelial development, proliferation, and Notch signaling compared to control. Consistently, HLHS iPSCs exhibited impaired AEC differentiation shown as the reduced CXCR4+NT5E-/low AEC progenitor population. Mature HLHS iPSC-AECs also exhibited increased G0/G1 cell cycle arrest with decreased expression of cell cycle related genes (e.g., Ki67, CCND1/2). Additionally, NOTCH targeted genes (e.g., DLL4, HEY1, GJA5) were found suppressed in both ULV AECs and HLHS iPSC-AECs compared to control. We also found the HLHS de novo mutation gene KMT2D directly regulated the transcription of NOTCH targeted genes participating in arterial differentiation and cell proliferation, contributing to the HLHS AEC dysfunctionalities. Intriguingly, the treatment of NOTCH ligand JAG1 improved cell proliferation of HLHS AECs and upregulated G1/S transition genes downstream of NOTCH pathway. In summary, our results revealed that KMT2D directly regulated transcription activity of NOTCH signaling, contributing to the poor differentiation and low proliferation of HLHS coronary AECs.

developmental biology↗

bioRxiv2021

Precision neoantigen discovery using large-scale immunopeptidomes and composite modeling of MHC peptide presentation

Major histocompatibility complex (MHC)-bound peptides that originate from tumor-specific genetic alterations, known as neoantigens, are an important class of anti-cancer therapeutic targets. Accurately predicting peptide presentation by MHC complexes is a key aspect of discovering therapeutically relevant neoantigens. Technological improvements in mass-spectrometry-based immunopeptidomics and advanced modeling techniques have vastly improved MHC presentation prediction over the past two decades. However, improvement in the sensitivity and specificity of prediction algorithms is needed for clinical applications such as the development of personalized cancer vaccines, the discovery of biomarkers for response to checkpoint blockade and the quantification of autoimmune risk in gene therapies. Toward this end, we generated allele-specific immunopeptidomics data using 25 mono-allelic cell lines and created Systematic HLA Epitope Ranking Pan Algorithm (SHERPA), a pan-allelic MHC-peptide algorithm for predicting MHC-peptide binding and presentation. In contrast to previously published large-scale mono-allelic data, we used an HLA-null K562 parental cell line and a stable transfection of HLA alleles to better emulate native presentation. Our dataset includes five previously unprofiled alleles that expand MHC binding pocket diversity in the training data and extend allelic coverage in underprofiled populations. To improve generalizability, SHERPA systematically integrates 128 mono-allelic and 384 multi-allelic samples with publicly available immunoproteomics data and binding assay data. Using this dataset, we developed two features that empirically estimate the propensities of genes and specific regions within gene bodies to engender immunopeptides to represent antigen processing. Using a composite model constructed with gradient boosting decision trees, multiallelic deconvolution and 2.15 million peptides encompassing 167 alleles, we achieved a 1.44 fold improvement of positive predictive value compared to existing tools when evaluated on independent mono-allelic datasets and a 1.15 fold improvement when evaluating on tumor samples. With a high degree of accuracy, SHERPA has the potential to enable precision neoantigen discovery for future clinical applications.

bioinformatics↗