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Ao, M.

Publications and source records attributed to Ao, M..

6 recordsLinked to original sources

Discovery of post-translationally modified self-peptides that promote hypertension

Post translational modifications can enhance immunogenicity of self-proteins. In several conditions including hypertension, systemic lupus, and heart failure, isolevuglandins (IsoLGs) are formed by lipid peroxidation and covalently bond with protein lysine residues. Here we show that the murine class-I major histocompatibility complex (MHC-I) variant H-2Db uniquely presents isoLG modified peptides and developed a computational pipeline that identifies structural features for MHC-I accommodation of such peptides. We identified isoLG-adducted peptides from renal proteins including the sodium glucose transporter 2, Cadherin 16, Kelch Domain containing protein 7A and solute carrier family 23, that are recognized by CD8+ T cells in tissues of hypertensive mice, induce T cell proliferation in vitro, and prime hypertension after adoptive transfer. Finally, we find similar patterns of isoLG-adducted antigen restriction in class-I human leukocyte antigens as in murine analogues. Thus, we have used a combined computational and experimental approach to define likely antigenic peptides in hypertension.

immunology↗

Immunoproteasomal Processing of Isolevuglandin Adducts in Hypertension

O_FIG O_LINKSMALLFIG WIDTH=192 HEIGHT=200 SRC="FIGDIR/small/536054v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1fc2367org.highwire.dtl.DTLVardef@787fcforg.highwire.dtl.DTLVardef@10f09f2org.highwire.dtl.DTLVardef@561978_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG Isolevuglandins (isoLGs) are lipid aldehydes that form in the presence of reactive oxygen species (ROS) and drive immune activation. We found that isoLG-adducts are presented within the context of major histocompatibility complexes (MHC-I) by an immunoproteasome dependent mechanism. Pharmacologic inhibition of LMP7, the chymotrypsin subunit of the immunoproteasome, attenuates hypertension and tissue inflammation in the angiotensin II (Ang II) model of hypertension. Genetic loss of function of all immunoproteasome subunits or conditional deletion of LMP7 in dendritic cell (DCs) or endothelial cells (ECs) attenuated hypertension, reduced aortic T cell infiltration, and reduced isoLG-adduct MHC-I interaction. Furthermore, isoLG adducts structurally resemble double-stranded DNA and contribute to the activation of STING in ECs. These studies define a critical role of the immunoproteasome in the processing and presentation of isoLG-adducts. Moreover they define a role of LMP7 as a regulator of T cell activation and tissue infiltration in hypertension.

immunology↗

EXoO-Tn: Tag-n-Map the Tn Antigen in the Human Proteome

Tn antigen (Tn), a single N-acetylgalactosamine (GalNAc) monosaccharide attached to protein Ser/Thr residues, is found on most solid tumors yet rarely detected in adult tissues, featuring it one of the most distinctive signatures of cancers. Although it is prevalent in cancers, Tn-glycosylation sites are not entirely clear owing to the lack of suitable technology. Knowing the Tn-glycosylation sites will spur the development of new vaccines, diagnostics, and therapeutics of cancers. Here, we report a novel technology named EXoO-Tn for large-scale mapping of Tn-glycosylation sites. EXoO-Tn utilizes glycosyltransferase C1GalT1 and isotopically-labeled UDP-Gal(13C6) to tag and convert Tn to Gal(13C6)-Tn, which has a unique mass being distinguishable to other glycans. This exquisite Gal(13C6)-Tn structure is recognized by OpeRATOR that specifically cleaves N-termini of the Gal(13C6)-Tn-occupied Ser/Thr residues to yield site-containing glycopeptides. The use of EXoO-Tn mapped 947 Tn-glycosylation sites from 480 glycoproteins in Jurkat cells. Given the importance of Tn in diseases, EXoO-Tn is anticipated to have broad utility in clinical studies.

systems biology↗

OmicsOne: Associate Omics Data with Phenotypes in One-Click

The rapid advancements of high-throughput \"omics\" technologies have brought huge amount of data to process during and after experiments. Multi-omic analysis facilitates a deeper interrogation of a dataset, and discovery of interesting genes, proteins, lipids, glycans, or metabolites, or pathways related to the corresponding phenotypes in a study. Many individual software tools have been developed to analyze and visualize the data. However, integrating multiple omics data analysis strategies and approaches in a single data processing pipeline is still a challenge task. OmicsOne is a software developed in R, Python and Jupyter Notebook that can achieve statistical analysis, machine learning, and data visualization on multi- omics data by taking the advantages of integrating the useful tools from individual software packages. OmicsOne can simplify \"omics\" data analysis, and delineate molecules, or pathways associated to interested phenotypes.

bioinformatics↗

Mapping In Vivo O-Glycoproteome Using Site-specific Extraction of O-linked glycopeptides (EXoO)

Protein glycosylation is one of the most abundant post-translational modifications. However, detailed analysis of in vivo O-linked glycosylation, a major type of protein glycosylation, has been severely impeded by the scarcity of suitable methodologies. Here, we present a chemoenzymatic method for the site-specific extraction of O-linked glycopeptides (EXoO), which enabled the unambiguous mapping of over 3,000 O-linked glycosylation sites and definition of their glycans on over 1,000 proteins in human kidney tissues, T cells and serum. This large-scale localization of O-linked glycosylation sites nearly doubles the number of previously identified sites, demonstrating that EXoO is the most effective method to-date for defining the site-specific O-linked glycoproteome in different types of sample. Detailed structural analysis of the sites identified revealed conserved motifs and topological orientations facing extracellular space, the cell surface, the lumen of the ER and the Golgi. EXoO was also able to reveal significant differences in the in vivo O-linked glycoproteome of tumor and normal kidney tissues pointing to its broader use in clinical diagnostics and therapeutics.

systems biology↗

Reanalysis of global proteomic and phosphoproteomic data identified a large number of glycopeptides

Protein glycosylation plays fundamental roles in many cellular processes, and previous reports have shown dysregulation to be associated with several human diseases, including diabetes, cancer, and neurodegenerative disorders. Despite the vital role of glycosylation for proper protein function, the analysis of glycoproteins has been lagged behind to other protein modifications. In this study, we describe the re-analysis of global proteomic data from breast cancer xenograft tissues using recently developed software package GPQuest 2.0, revealing a large number of previously unidentified N-linked glycopeptides. More importantly, we found that using immobilized metal affinity chromatography (IMAC) technology for the enrichment of phosphopeptides had co-enriched a substantial number of sialoglycopeptides, allowing for a large-scale analysis of sialoglycopeptides in conjunction with the analysis of phosphopeptides. Collectively, combined MS/MS analyses of global proteomic and phosphoproteomic datasets resulted in the identification of 6,724 N-linked glycopeptides from 617 glycoproteins derived from two breast cancer xenograft tissues. Next, we utilized GPQuest for the re-analysis of global and phosphoproteomic data generated from 108 human breast cancer tissues that were previously analyzed by Clinical Proteomic Analysis Consortium (CPTAC). Reanalysis of the CPTAC dataset resulted in the identification of 2,683 glycopeptides from the global proteomic data set and 4,554 glycopeptides from phosphoproteomic data set, respectively. Together, 11,292 N-linked glycopeptides corresponding to 1,731 N-linked glycosites from 883 human glycoproteins were identified from the two data sets. This analysis revealed an extensive number of glycopeptides hidden in the global and enriched in IMAC-based phosphopeptide-enriched proteomic data, information which would have remained unknown from the original study otherwise. The reanalysis described herein can be readily applied to identify glycopeptides from already existing data sets, providing insight into many important facets of protein glycosylation in different biological, physiological, and pathological processes.

systems biology↗