
Nicholas M. Riley
Postdoctoral Scholar, Chemistry
Bio
My fascination with chemical instrumentation, especially mass spectrometry (MS), has remained persistent throughout my scientific career, and my postdoctoral work has sharpened my vision for MS innovations through the lens of needs within the glycoscience community. In my graduate work with Prof. Josh Coon at the University of Wisconsin-Madison, I developed MS technology for proteomic applications, with an emphasis on a tandem MS method co-invented by Prof. Coon called electron transfer dissociation (ETD). I built custom instrumentation, methodology, and software to implement supplemental activation strategies (termed activated ion-ETD, AI-ETD) to improve ETD-based fragmentation across bottom-up and top-down proteomics, and my graduate work continues to impact research and MS instrument development efforts for peptide, protein, and post-translational modification analyses. My graduate research efforts culminated in large-scale N-glycoproteome characterization with AI-ETD, which opened my eyes to the world of glycobiology – where I saw opportunity and intrigue. My postdoctoral research with Prof. Carolyn Bertozzi, known for her transformative work in chemical glycoscience, has crystallized my commitment to interdisciplinary science that uses chemical tools to explore fundamental questions in biology. Here, I have focused on two areas ripe for discovery within glycoscience, yet in need of new technology: mucin-domain glycoproteins and the secretome. I am now excited to devote my career to studying fundamental roles of glycosylation in cell surface biology through creative technology development.
Honors & Awards
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NIH K99 Pathway to Independence Award, National Institutes of Health (2022-present)
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NIH K00 Postdoctoral Fellow (Predoctoral to Postdoctoral Fellow Transition Award, F99/K00), National Institutes of Health - National Cancer Institute (2016-2022)
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National Science Foundation (NSF) Graduate Research Fellow, National Science Foundation (2014-2016)
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Rising Star in Proteomics and Metabolomics (40 under 40), Journal of Proteome Research (2021)
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Selected as ASMS Emerging Talent in Academia, American Society of Mass Spectrometry (2020)
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Young Mass Spectrometrists Keynote Lecture, International Mass Spectrometry Conference (2022)
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HUPO World Congress Travel Award, Human Proteome Organization (2022)
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ASBMB Postdoctoral Annual Meeting Award, American Society for Biochemistry and Molecular Biology (2021)
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SFG Travel Award, Society for Glycobiology (2021)
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US HUPO Postdoctoral Award Honorable Mention, US Human Proteome Organization (2021)
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SUMS Research Applications Symposium Poster Award, Stanford University Mass Spectrometry (2020)
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Keystone Symposia Scholarship, Keystone Symposia (2020)
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ASMS Postdoctoral Career Development Award, American Society for Mass Spectrometry (2019)
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Richard and Joan Hartl Award for Research Excellence in Analytical Chemistry, Department of Chemistry, University of Wisconsin-Madison (2018)
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Roger J. Carlson Memorial Award for Research Excellence, Department of Chemistry, University of Wisconsin-Madison (2017)
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FACSS Student Award, Federation of Analytical Chemistry and Spectroscopy Societies (2017)
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American Society for Mass Spectrometry Graduate Student Award, American Society for Mass Spectrometry (2015)
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Marg Northcott Student Award, Lake Louise Tandem MS Workshop (2016)
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Richard A. Schaeffer Award, American Society of Mass Spectrometry (2014)
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Outstanding Oral Presentation Award, Midwest Carbohydrate and Glycobiology Symposium (2017)
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Rising Star Recognition, Human Proteomics Symposium (2018)
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1st Place in Poster Competition, Human Proteomics Symposium (2015)
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1st Place in Poster Competition, Department of Chemistry, University of Wisconsin-Madison (2017)
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Pei Wang Graduate Fellowship, University of Wisconsin-Madison (2012)
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Louise McBee Graduate Fellowship, Alpha Lambda Delta Honors Society (2012)
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Algernon Sydney Sullivan Award (top undergraduate student), University of South Carolina (2012)
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Joseph H. Gibbons Outstanding Senior Award, Omicron Delta Kappa Honors Society (2012)
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Omicron Delta Kappa Leader of the Year, Omicron Delta Kappa Honors Society Chi Circle, University of South Carolina (2012)
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American Institute of Chemists Foundation Award, University of South Carolina (2011, 2012)
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Presidential Volunteer Service Award, Gold Level (250+ hours), Office of President Barack Obama (2011)
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Wilson-Kibler Bicentennial Leadership Award, University of South Carolina (2011)
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Phi Beta Kappa, Phi Beta Kappa Society (2010)
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Cultural Ambassadorial Scholar, Rotary International (2009-2010)
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Jo Anne J. Trow Academic Scholar, Alpha Lambda Delta Honors Society (2009)
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Magellan Undergraduate Research Grant, University of South Carolina (2008-2010)
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Robert C. Byrd Academic Scholar, US Department of Education (2007-2011)
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Robert C. McNair Scholar (full tuition scholarship awarded for academic merit), University of South Carolina (2007-2011)
Boards, Advisory Committees, Professional Organizations
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Member, American Society for Mass Spectrometry (2013 - Present)
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Member, American Chemical Society (2013 - Present)
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Member, Human Proteome Organization (HUPO) (2015 - Present)
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Member, Society for Glycobiology (2017 - Present)
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Scientific Advisor, Tegmine Therapeutics, Inc. (2020 - 2022)
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Associate Member, American Association for Cancer Research (2020 - Present)
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Member, American Society for Biochemistry and Molecular Biology (2020 - Present)
Professional Education
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Doctor of Philosophy, University of Wisconsin Madison (2018)
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Bachelor of Science, University of South Carolina (2012)
Current Research and Scholarly Interests
The glycocode, or combinatorial patterns of glycosylation that relay biological information, functions in essential roles that govern human health and myriad diseases (e.g., cancer, infectious diseases, autoimmune diseases). However, we lack a fundamental understanding of the rules that define changes in glycosylation, which hinders insight in to how the glycocode contributes to biological function at a molecular level. Our perspectives on the glycocode remain deficient because the non-templated complexity of glycosylation creates analytical challenges that have severely limited our ability to study glycoconjugates. I aim to solve these challenges. I leverage my graduate training in mass spectrometry (MS)-based proteomics and my postdoctoral work in chemical glycobiology to develop innovative bioanalytical and chemical biology technologies to investigate essential principles of glycocode regulation and dysregulation. Specifically, I am interested in using cutting-edge technologies to understand how altered cell surface phenotypes (i.e., glycocalyx status) manifest in cancer progression and drive metastasis. Through a combination of MS-based multi-omics, bioinformatics, and chemical biology, my goal is to use a systems-level approach to glycobiology to further our understanding of human health and disease and advance therapeutic glycoscience.
All Publications
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Measuring the multifaceted roles of mucin-domain glycoproteins in cancer.
Advances in cancer research
2023; 157: 83-121
Abstract
Mucin-domain glycoproteins are highly O-glycosylated cell surface and secreted proteins that serve as both biochemical and biophysical modulators. Aberrant expression and glycosylation of mucins are known hallmarks in numerous malignancies, yet mucin-domain glycoproteins remain enigmatic in the broad landscape of cancer glycobiology. Here we review the multifaceted roles of mucins in cancer through the lens of the analytical and biochemical methods used to study them. We also describe a collection of emerging tools that are specifically equipped to characterize mucin-domain glycoproteins in complex biological backgrounds. These approaches are poised to further elucidate how mucin biology can be understood and subsequently targeted for the next generation of cancer therapeutics.
View details for DOI 10.1016/bs.acr.2022.09.001
View details for PubMedID 36725114
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The 2022 Nobel prize in chemistry - sweet!
Glycobiology
2023
View details for DOI 10.1093/glycob/cwad016
View details for PubMedID 36892406
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Deciphering O-glycoprotease substrate preferences with O-Pair Search.
Molecular omics
2022
Abstract
O-Glycoproteases are an emerging class of enzymes that selectively digest glycoproteins at positions decorated with specific O-linked glycans. O-Glycoprotease substrates range from any O-glycoprotein (albeit with specific O-glycan modifications) to only glycoproteins harboring specific O-glycosylated sequence motifs, such as those found in mucin domains. Their utility for multiple glycoproteomic applications is driving the search to both discover new O-glycoproteases and to understand how structural features of characterized O-glycoproteases influence their substrate specificities. One challenge of defining O-glycoprotease specificity restraints is the need to characterize O-glycopeptides with site-specific analysis of O-glycosites. Here, we demonstrate how O-Pair Search, a recently developed O-glycopeptide-centric identification platform that enables rapid searches and confident O-glycosite localization, can be used to determine substrate specificities of various O-glycoproteases de novo from LC-MS/MS data of O-glycopeptides. Using secreted protease of C1 esterase inhibitor (StcE) from enterohemorrhagic Escherichia coli and O-endoprotease OgpA from Akkermansia mucinophila, we explore numerous settings that effect O-glycopeptide identification and show how non-specific and semi-tryptic searches of O-glycopeptide data can produce candidate cleavage motifs. These putative motifs can be further used to define new protease cleavage settings that lower search times and improve O-glycopeptide identifications. We use this platform to generate a consensus motif for the recently characterized immunomodulating metalloprotease (IMPa) from Pseudomonas aeruginosa and show that IMPa is a favorable O-glycoprotease for characterizing densely O-glycosylated mucin-domain glycoproteins.
View details for DOI 10.1039/d2mo00244b
View details for PubMedID 36373229
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Lysosomal cathepsin D mediates endogenous mucin glycodomain catabolism in mammals.
Proceedings of the National Academy of Sciences of the United States of America
2022; 119 (39): e2117105119
Abstract
Mucins are functionally implicated in a range of human pathologies, including cystic fibrosis, influenza, bacterial endocarditis, gut dysbiosis, and cancer. These observations have motivated the study of mucin biosynthesis as well as the development of strategies for inhibition of mucin glycosylation. Mammalian pathways for mucin catabolism, however, have remained underexplored. The canonical view, derived from analysis of N-glycoproteins in human lysosomal storage disorders, is that glycan degradation and proteolysis occur sequentially. Here, we challenge this view by providing genetic and biochemical evidence supporting mammalian proteolysis of heavily O-glycosylated mucin domains without prior deglycosylation. Using activity screening coupled with mass spectrometry, we ascribed mucin-degrading activity in murine liver to the lysosomal protease cathepsin D. Glycoproteomics of substrates digested with purified human liver lysosomal cathepsin D provided direct evidence for proteolysis within densely O-glycosylated domains. Finally, knockout of cathepsin D in a murine model of the human lysosomal storage disorder neuronal ceroid lipofuscinosis 10 resulted in accumulation of mucins in liver-resident macrophages. Our findings imply that mucin-degrading activity is a component of endogenous pathways for glycoprotein catabolism in mammalian tissues.
View details for DOI 10.1073/pnas.2117105119
View details for PubMedID 36122205
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The human disease gene LYSET is essential for lysosomal enzyme transport and viral infection.
Science (New York, N.Y.)
2022: eabn5648
Abstract
Lysosomes are key degradative compartments of the cell. Transport to lysosomes relies on GlcNAc-1-phosphotransferase-mediated tagging of soluble enzymes with mannose 6-phosphate (M6P). GlcNAc-1-phosphotransferase deficiency leads to the severe lysosomal storage disorder mucolipidosis II (MLII). Several viruses require lysosomal cathepsins to cleave structural proteins and thus depend on functional GlcNAc-1-phosphotransferase. Here, we used genome-scale CRISPR screens to identify Lysosomal Enzyme Trafficking factor (LYSET) as essential for infection by cathepsin-dependent viruses including SARS-CoV-2. LYSET deficiency resulted in global loss of M6P tagging and mislocalization of GlcNAc-1-phosphotransferase from the Golgi complex to lysosomes. Lyset knockout mice exhibited MLII-like phenotypes and human pathogenic LYSET alleles failed to restore lysosomal sorting defects. Thus, LYSET is required for correct functioning of the M6P trafficking machinery, and mutations in LYSET can explain the phenotype of the associated disorder.
View details for DOI 10.1126/science.abn5648
View details for PubMedID 36074821
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Glycoproteomics
NATURE REVIEWS METHODS PRIMERS
2022; 2 (1)
View details for DOI 10.1038/s43586-022-00128-4
View details for Web of Science ID 000888583200002
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Revealing the human mucinome.
Nature communications
2022; 13 (1): 3542
Abstract
Mucin domains are densely O-glycosylated modular protein domains found in various extracellular and transmembrane proteins. Mucin-domain glycoproteins play important roles in many human diseases, such as cancer and cystic fibrosis, but the scope of the mucinome remains poorly defined. Recently, we characterized a bacterial O-glycoprotease, StcE, and demonstrated that an inactive point mutant retains binding selectivity for mucin-domain glycoproteins. In this work, we leverage inactive StcE to selectively enrich and identify mucin-domain glycoproteins from complex samples like cell lysate and crude ovarian cancer patient ascites fluid. Our enrichment strategy is further aided by an algorithm to assign confidence to mucin-domain glycoprotein identifications. This mucinomics platform facilitates detection of hundreds of glycopeptides from mucin domains and highly overlapping populations of mucin-domain glycoproteins from ovarian cancer patients. Ultimately, we demonstrate our mucinomics approach can reveal key molecular signatures of cancer from in vitro and ex vivo sources.
View details for DOI 10.1038/s41467-022-31062-4
View details for PubMedID 35725833
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Structure-guided mutagenesis of a mucin-selective metalloprotease from Akkermansia muciniphila alters substrate preferences.
The Journal of biological chemistry
2022: 101917
Abstract
Akkermansia muciniphila, a mucin-degrading microbe found in the human gut, is often associated with positive health outcomes. The abundance of Akkermansia muciniphila is modulated by the presence and accessibility of nutrients, which can be derived from diet or host glycoproteins. In particular, the ability to degrade host mucins, a class of proteins carrying densely O-glycosylated domains, provides a competitive advantage in the sustained colonization of niche mucosal environments. Although Akkermansia muciniphila is known to rely on mucins as a carbon and nitrogen source, the enzymatic machinery used by this microbe to process mucins in the gut is not yet fully characterized. Here, we focus on the mucin-selective metalloprotease, Amuc_0627 (AM0627), which is known to cleave between adjacent residues carrying truncated core 1 O-glycans. We showed that this enzyme is capable of degrading purified mucin 2 (MUC2), the major protein component of mucus in the gut. An X-ray crystal structure of AM0627 (1.9 A resolution) revealed O-glycan binding residues that are conserved between structurally characterized enzymes from the same family. We further rationalized the substrate cleavage motif using molecular modeling to identify nonconserved glycan-interacting residues. We conclude that mutagenesis of these residues resulted in altered substrate preferences down to the glycan level, providing insight into the structural determinants of O-glycan recognition.
View details for DOI 10.1016/j.jbc.2022.101917
View details for PubMedID 35405095
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Targeting hypersialylation in multiple myeloma represents a novel approach to enhance NK cell-mediated tumor responses.
Blood advances
2022
Abstract
Abnormal glycosylation is a hallmark of cancer, and the hypersialylated tumour cell surface facilitates abnormal cell trafficking and drug resistance in several malignancies, including multiple myeloma (MM). Furthermore, hypersialylation has also been implicated in facilitating evasion of natural killer (NK) cell-mediated immunosurveillance, but not in MM to-date. In this study, we explore the role of hypersialylation in promoting escape from NK cells. We document strong expression of sialic acid-derived ligands for Siglec-7 (Siglec-7L) on primary MM cells and MM cell lines, highlighting the possibility of Siglec-7/Siglec-7L interactions in the tumor microenvironment. Interactomics experiments in MM cell lysates revealed PSGL-1 as the predominant Siglec-7L in MM. We show that desialylation, using both a sialidase and sialyltransferase inhibitor (SIA), strongly enhances NK cell-mediated cytotoxicity against MM cells. Furthermore, MM cell desialylation results in increased detection of CD38, a well validated target in MM. Desialylation enhanced NK cell cytotoxicity against CD38+ MM cells following treatment with the anti-CD38 monoclonal antibody Daratumumab. Additionally, we show that MM cells with low CD38 expression can be treated with all trans-retinoic acid (ATRA), SIA and Daratumumab to elicit a potent NK cell cytotoxic response. Finally, we demonstrate that Siglec-7KO potentiates NK cell cytotoxicity against Siglec-7L+ MM cells. Taken together, our work shows that desialylation of MM cells is a promising novel approach to enhance NK cell efficacy against MM, which can be combined with frontline therapies to elicit a potent anti-MM response.
View details for DOI 10.1182/bloodadvances.2021006805
View details for PubMedID 35294519
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Protocol for cell type-specific labeling, enrichment, and proteomic profiling of plasma proteins in mice.
STAR protocols
1800; 2 (4): 101014
Abstract
Secreted polypeptides represent a fundamental axis of intercellular communication. Here, we present a protocol for the cell type-specific biotinylation, enrichment, and proteomic profiling of secreted plasma proteins directly in mice. This protocol uses conditional "turn-on" adeno-associated viruses expressing an endoplasmic reticulum-targeted biotin ligase to globally biotinylate proteins of the secretory pathway in a cell type-specific manner. Biotinylated secreted proteins can be directly purified from blood plasma and analyzed by SDS-PAGE gel or shotgun proteomics. For complete information on the generation and use of this protocol, please refer to Wei et al. (2021).
View details for DOI 10.1016/j.xpro.2021.101014
View details for PubMedID 34950890
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Multi-omics analysis of spatially distinct stromal cells reveals tumor-induced O-glycosylation of the CDK4-pRB axis in fibroblasts at the invasive tumor edge.
Cancer research
2021
Abstract
The invasive leading edge represents a potential gateway for tumor metastasis. The role of fibroblasts from the tumor edge in promoting cancer invasion and metastasis has not been comprehensively elucidated. We hypothesize that crosstalk between tumor and stromal cells within the tumor microenvironment (TME) results in activation of key biological pathways depending on their position in the tumor (edge vs core). Here we highlight phenotypic differences between tumor-adjacent-fibroblasts (TAF) from the invasive edge and tumor core fibroblasts (TCF) from the tumor core, established from human lung adenocarcinomas. A multi-omics approach that includes genomics, proteomics, and O-glycoproteomics was used to characterize crosstalk between TAFs and cancer cells. These analyses showed that O-glycosylation, an essential post-translational modification resulting from sugar metabolism, alters key biological pathways including the cyclin-dependent kinase 4 and phosphorylated retinoblastoma protein (CDK4-pRB) axis in the stroma and indirectly modulates pro-invasive features of cancer cells. In summary, the O-glycoproteome represents a new consideration for important biological processes involved in tumor-stroma crosstalk and a potential avenue to improve the anti-cancer efficacy of CDK4 inhibitors.
View details for DOI 10.1158/0008-5472.CAN-21-1705
View details for PubMedID 34853070
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Synthetic Siglec-9 Agonists Inhibit Neutrophil Activation Associated with COVID-19.
ACS central science
2021; 7 (4): 650-657
Abstract
Severe cases of coronavirus disease 2019 (COVID-19), caused by infection with SARS-CoV-2, are characterized by a hyperinflammatory immune response that leads to numerous complications. Production of proinflammatory neutrophil extracellular traps (NETs) has been suggested to be a key factor in inducing a hyperinflammatory signaling cascade, allegedly causing both pulmonary tissue damage and peripheral inflammation. Accordingly, therapeutic blockage of neutrophil activation and NETosis, the cell death pathway accompanying NET formation, could limit respiratory damage and death from severe COVID-19. Here, we demonstrate that synthetic glycopolymers that activate signaling of the neutrophil checkpoint receptor Siglec-9 suppress NETosis induced by agonists of viral toll-like receptors (TLRs) and plasma from patients with severe COVID-19. Thus, Siglec-9 agonism is a promising therapeutic strategy to curb neutrophilic hyperinflammation in COVID-19.
View details for DOI 10.1021/acscentsci.0c01669
View details for PubMedID 34056095
View details for PubMedCentralID PMC8009098
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LYTACs that engage the asialoglycoprotein receptor for targeted protein degradation.
Nature chemical biology
2021
Abstract
Selective protein degradation platforms have afforded new development opportunities for therapeutics and tools for biological inquiry. The first lysosome-targeting chimeras (LYTACs) targeted extracellular and membrane proteins for degradation by bridging a target protein to the cation-independent mannose-6-phosphate receptor (CI-M6PR). Here, we developed LYTACs that engage the asialoglycoprotein receptor (ASGPR), a liver-specific lysosome-targeting receptor, to degrade extracellular proteins in a cell-type-specific manner. We conjugated binders to a triantenerrary N-acetylgalactosamine (tri-GalNAc) motif that engages ASGPR to drive the downregulation of proteins. Degradation of epidermal growth factor receptor (EGFR) by GalNAc-LYTAC attenuated EGFR signaling compared to inhibition with an antibody. Furthermore, we demonstrated that a LYTAC consisting of a 3.4-kDa peptide binder linked to a tri-GalNAc ligand degrades integrins and reduces cancer cell proliferation. Degradation with a single tri-GalNAc ligand prompted site-specific conjugation on antibody scaffolds, which improved the pharmacokinetic profile of GalNAc-LYTACs in vivo. GalNAc-LYTACs thus represent an avenue for cell-type-restricted protein degradation.
View details for DOI 10.1038/s41589-021-00770-1
View details for PubMedID 33767387
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Genome-wide CRISPR screens reveal a specific ligand for the glycan-binding immune checkpoint receptor Siglec-7.
Proceedings of the National Academy of Sciences of the United States of America
2021; 118 (5)
Abstract
Glyco-immune checkpoint receptors, molecules that inhibit immune cell activity following binding to glycosylated cell-surface antigens, are emerging as attractive targets for cancer immunotherapy. Defining biologically relevant ligands that bind and activate such receptors, however, has historically been a significant challenge. Here, we present a CRISPRi genomic screening strategy that allowed unbiased identification of the key genes required for cell-surface presentation of glycan ligands on leukemia cells that bind the glyco-immune checkpoint receptors Siglec-7 and Siglec-9. This approach revealed a selective interaction between Siglec-7 and the mucin-type glycoprotein CD43. Further work identified a specific N-terminal glycopeptide region of CD43 containing clusters of disialylated O-glycan tetrasaccharides that form specific Siglec-7 binding motifs. Knockout or blockade of CD43 in leukemia cells relieves Siglec-7-mediated inhibition of immune killing activity. This work identifies a potential target for immune checkpoint blockade therapy and represents a generalizable approach to dissection of glycan-receptor interactions in living cells.
View details for DOI 10.1073/pnas.2015024118
View details for PubMedID 33495350
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Modulation of immune cell reactivity with cis-binding Siglec agonists.
Proceedings of the National Academy of Sciences of the United States of America
2021; 118 (3)
Abstract
Inflammatory pathologies caused by phagocytes lead to numerous debilitating conditions, including chronic pain and blindness due to age-related macular degeneration. Many members of the sialic acid-binding immunoglobulin-like lectin (Siglec) family are immunoinhibitory receptors whose agonism is an attractive approach for antiinflammatory therapy. Here, we show that synthetic lipid-conjugated glycopolypeptides can insert into cell membranes and engage Siglec receptors in cis, leading to inhibitory signaling. Specifically, we construct a cis-binding agonist of Siglec-9 and show that it modulates mitogen-activated protein kinase (MAPK) signaling in reporter cell lines, immortalized macrophage and microglial cell lines, and primary human macrophages. Thus, these cis-binding agonists of Siglecs present a method for therapeutic suppression of immune cell reactivity.
View details for DOI 10.1073/pnas.2012408118
View details for PubMedID 33431669
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The CD22-IGF2R interaction is a therapeutic target for microglial lysosome dysfunction in Niemann-Pick type C.
Science translational medicine
2021; 13 (622): eabg2919
Abstract
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View details for DOI 10.1126/scitranslmed.abg2919
View details for PubMedID 34851695
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Cell type-selective secretome profiling in vivo.
Nature chemical biology
2020
Abstract
Secreted polypeptides are a fundamental axis of intercellular and endocrine communication. However, a global understanding of the composition and dynamics of cellular secretomes in intact mammalian organisms has been lacking. Here, we introduce a proximity biotinylation strategy that enables labeling, detection and enrichment of secreted polypeptides in a cell type-selective manner in mice. We generate a proteomic atlas of hepatocyte, myocyte, pericyte and myeloid cell secretomes by direct purification of biotinylated secreted proteins from blood plasma. Our secretome dataset validates known cell type-protein pairs, reveals secreted polypeptides that distinguish between cell types and identifies new cellular sources for classical plasma proteins. Lastly, we uncover a dynamic and previously undescribed nutrient-dependent reprogramming of the hepatocyte secretome characterized by the increased unconventional secretion of the cytosolic enzyme betaine-homocysteine S-methyltransferase (BHMT). This secretome profiling strategy enables dynamic and cell type-specific dissection of the plasma proteome and the secreted polypeptides that mediate intercellular signaling.
View details for DOI 10.1038/s41589-020-00698-y
View details for PubMedID 33199915
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O-Pair Search with MetaMorpheus for O-glycopeptide characterization.
Nature methods
2020
Abstract
We report O-Pair Search, an approach to identify O-glycopeptides and localize O-glycosites. Using paired collision- and electron-based dissociation spectra, O-Pair Search identifies O-glycopeptides via an ion-indexed open modification search and localizes O-glycosites using graph theory and probability-based localization. O-Pair Search reduces search times more than 2,000-fold compared to current O-glycopeptide processing software, while defining O-glycosite localization confidence levels and generating more O-glycopeptide identifications. Beyond the mucin-type O-glycopeptides discussed here, O-Pair Search also accepts user-defined glycan databases, making it compatible with many types of O-glycosylation. O-Pair Search is freely available within the open-source MetaMorpheus platform at https://github.com/smith-chem-wisc/MetaMorpheus .
View details for DOI 10.1038/s41592-020-00985-5
View details for PubMedID 33106676
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Optical Fiber-Enabled Photoactivation of Peptides and Proteins
ANALYTICAL CHEMISTRY
2020; 92 (18): 12363–70
Abstract
Photoactivation and photodissociation have long proven to be useful tools in tandem mass spectrometry, but implementation often involves cumbersome and potentially dangerous configurations. Here, we redress this problem by using a fiber-optic cable to couple an infrared (IR) laser to a mass spectrometer for robust, efficient, and safe photoactivation experiments. Transmitting 10.6 μm IR photons through a hollow-core fiber, we show that such fiber-assisted activated ion-electron transfer dissociation (AI-ETD) and IR multiphoton dissociation (IRMPD) experiments can be carried out as effectively as traditional mirror-based implementations. We report on the transmission efficiency of the hollow-core fiber for conducting photoactivation experiments and perform various intact protein and peptide analyses to illustrate the benefits of fiber-assisted AI-ETD, namely, a simplified system for irradiating the two-dimensional linear ion trap volume concurrent with ETD reactions to limit uninformative nondissociative events and thereby amplify sequence coverage. We also describe a calibration scheme for the routine analysis of IR laser alignment and power through the fiber and into the dual cell quadrupolar linear ion trap. In all, these advances allow for a more robust, straightforward, and safe instrumentation platform, permitting implementation of AI-ETD and IRMPD on commercial mass spectrometers and broadening the accessibility of these techniques.
View details for DOI 10.1021/acs.analchem.0c02087
View details for Web of Science ID 000572832900036
View details for PubMedID 32786458
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Top-Down Characterization of an Intact Monoclonal Antibody Using Activated Ion Electron Transfer Dissociation
ANALYTICAL CHEMISTRY
2020; 92 (15): 10246–51
Abstract
Monoclonal antibodies (mAbs) are important therapeutic glycoproteins, but their large size and structural complexity make them difficult to rapidly characterize. Top-down mass spectrometry (MS) has the potential to overcome challenges of other common approaches by minimizing sample preparation and preserving endogenous modifications. However, comprehensive mAb characterization requires generation of many, well-resolved fragments and remains challenging. While ETD retains modifications and cleaves disulfide bonds-making it attractive for mAb characterization-it can be less effective for precursors having high m/z values. Activated ion electron transfer dissociation (AI-ETD) uses concurrent infrared photoactivation to promote product ion generation and has proven effective in increasing sequence coverage of intact proteins. Here, we present the first application of AI-ETD to mAb sequencing. For the standard NIST mAb, we observe a high degree of complementarity between fragments generated using standard ETD with a short reaction time and AI-ETD with a long reaction time. Most importantly, AI-ETD reveals disulfide-bound regions that have been intractable, thus far, for sequencing with top-down MS. We conclude AI-ETD has the potential to rapidly and comprehensively analyze intact mAbs.
View details for DOI 10.1021/acs.analchem.0c00705
View details for Web of Science ID 000558761500011
View details for PubMedID 32608969
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Lysosome-targeting chimaeras for degradation of extracellular proteins.
Nature
2020
Abstract
The majority of therapies that target individual proteins rely on specific activity-modulating interactions with the target protein-for example, enzyme inhibition or ligand blocking. However, several major classes of therapeutically relevant proteins have unknown or inaccessible activity profiles and so cannot be targeted by such strategies. Protein-degradation platforms such as proteolysis-targeting chimaeras (PROTACs)1,2 and others (for example, dTAGs3, Trim-Away4, chaperone-mediated autophagy targeting5 and SNIPERs6) have been developed for proteins that are typically difficult to target; however, these methods involve the manipulation of intracellular protein degradation machinery and are therefore fundamentally limited to proteins that contain cytosolic domains to which ligands can bind and recruit the requisite cellular components. Extracellular and membrane-associated proteins-the products of 40% of all protein-encoding genes7-are key agents in cancer, ageing-related diseases and autoimmune disorders8, and so a general strategy to selectively degrade these proteins has the potential to improve human health. Here we establish the targeted degradation of extracellular and membrane-associated proteins using conjugates that bind both a cell-surface lysosome-shuttling receptor and the extracellular domain of a target protein. These initial lysosome-targeting chimaeras, which we term LYTACs, consist of a small molecule or antibody fused to chemically synthesized glycopeptide ligands that are agonists of the cation-independent mannose-6-phosphate receptor (CI-M6PR). We use LYTACs to develop a CRISPR interference screen that reveals the biochemical pathway for CI-M6PR-mediated cargo internalization in cell lines, and uncover the exocyst complex as a previously unidentified-but essential-component of this pathway. We demonstrate the scope of this platform through the degradation of therapeutically relevant proteins, including apolipoproteinE4, epidermal growth factor receptor, CD71 and programmed death-ligand 1. Our results establish a modular strategy for directing secreted and membrane proteins for lysosomal degradation, with broad implications for biochemical research and for therapeutics.
View details for DOI 10.1038/s41586-020-2545-9
View details for PubMedID 32728216
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Broad and thematic remodeling of the surfaceome and glycoproteome on isogenic cells transformed with driving proliferative oncogenes.
Proceedings of the National Academy of Sciences of the United States of America
2020
Abstract
The cell surface proteome, the surfaceome, is the interface for engaging the extracellular space in normal and cancer cells. Here we apply quantitative proteomics of N-linked glycoproteins to reveal how a collection of some 700 surface proteins is dramatically remodeled in an isogenic breast epithelial cell line stably expressing any of six of the most prominent proliferative oncogenes, including the receptor tyrosine kinases, EGFR and HER2, and downstream signaling partners such as KRAS, BRAF, MEK, and AKT. We find that each oncogene has somewhat different surfaceomes, but the functions of these proteins are harmonized by common biological themes including up-regulation of nutrient transporters, down-regulation of adhesion molecules and tumor suppressing phosphatases, and alteration in immune modulators. Addition of a potent MEK inhibitor that blocks MAPK signaling brings each oncogene-induced surfaceome back to a common state reflecting the strong dependence of the oncogene on the MAPK pathway to propagate signaling. Cell surface protein capture is mediated by covalent tagging of surface glycans, yet current methods do not afford sequencing of intact glycopeptides. Thus, we complement the surfaceome data with whole cell glycoproteomics enabled by a recently developed technique called activated ion electron transfer dissociation (AI-ETD). We found massive oncogene-induced changes to the glycoproteome and differential increases in complex hybrid glycans, especially for KRAS and HER2 oncogenes. Overall, these studies provide a broad systems-level view of how specific driver oncogenes remodel the surfaceome and the glycoproteome in a cell autologous fashion, and suggest possible surface targets, and combinations thereof, for drug and biomarker discovery.
View details for DOI 10.1073/pnas.1917947117
View details for PubMedID 32205440
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Electron-Based Dissociation Is Needed for O-Glycopeptides Derived from OpeRATOR Proteolysis.
Analytical chemistry
2020
Abstract
The recently described O-glycoprotease OpeRATOR presents exciting opportunities for O-glycoproteomics. This bacterial enzyme purified from Akkermansia muciniphila cleaves N-terminally to serine and threonine residues that are modified with (preferably asialylated) O-glycans. This provides orthogonal cleavage relative to canonical proteases (e.g., trypsin) for improved O-glycopeptide characterization with tandem mass spectrometry (MS/MS). O-glycopeptides with a modified N-terminal residue, such as those generated by OpeRATOR, present several potential benefits, perhaps the most notable being de facto O-glycosite localization without the need of glycan-retaining fragments in MS/MS spectra. Indeed, O-glycopeptides modified exclusively at the N-terminus would enable O-glycoproteomic methods to rely solely on collision-based fragmentation rather than electron-driven dissociation because glycan-retaining peptide fragments would not be required for localization. The caveat is that modified peptides would need to reliably contain only a single O-glycosite. Here, we use methods that combine collision- and electron-based fragmentation to characterize the number of O-glycosites that are present in O-glycopeptides derived from the OpeRATOR digestion of four known O-glycoproteins. Our data show that over 50% of O-glycopeptides in our sample generated from combined digestion using OpeRATOR and trypsin contain multiple O-glycosites, indicating that collision-based fragmentation alone is not sufficient. Electron-based dissociation methods are necessary to capture the O-glycopeptide diversity present in OpeRATOR digestions.
View details for DOI 10.1021/acs.analchem.0c02950
View details for PubMedID 33125225
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A Pragmatic Guide to Enrichment Strategies for Mass Spectrometry-Based Glycoproteomics.
Molecular & cellular proteomics : MCP
2020; 20: 100029
Abstract
Glycosylation is a prevalent, yet heterogeneous modification with a broad range of implications in molecular biology. This heterogeneity precludes enrichment strategies that can be universally beneficial for all glycan classes. Thus, choice of enrichment strategy has profound implications on experimental outcomes. Here we review common enrichment strategies used in modern mass spectrometry-based glycoproteomic experiments, including lectins and other affinity chromatographies, hydrophilic interaction chromatography and its derivatives, porous graphitic carbon, reversible and irreversible chemical coupling strategies, and chemical biology tools that often leverage bioorthogonal handles. Interest in glycoproteomics continues to surge as mass spectrometry instrumentation and software improve, so this review aims to help equip researchers with the necessary information to choose appropriate enrichment strategies that best complement these efforts.
View details for DOI 10.1074/mcp.R120.002277
View details for PubMedID 33583771
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Optimal Dissociation Methods Differ for N- and O-glycopeptides.
Journal of proteome research
2020
Abstract
Site-specific characterization of glycosylation requires intact glycopeptide analysis, and recent efforts have focused on how to best interrogate glycopeptides using tandem mass spectrometry (MS/MS). Beam-type collisional activation, i.e., higher-energy collisional dissociation (HCD), has been a valuable approach, but stepped collision energy HCD (sceHCD) and electron transfer dissociation with HCD supplemental activation (EThcD) have emerged as potentially more suitable alternatives. Both sceHCD and EThcD have been used with success in large-scale glycoproteomic experiments, but they each incur some degree of compromise. Most progress has occurred in the area N-glycoproteomics. There is growing interest in extending this progress to O-glycoproteomics, which necessitates comparisons of method performance for the two classes of glycopeptides. Here, we systematically explore the advantages and disadvantages of conventional HCD, sceHCD, ETD, and EThcD for intact glycopeptide analysis and determine their suitability for both N- and O-glycoproteomic applications. For N-glycopeptides, HCD and sceHCD generate similar numbers of identifications, although sceHCD generally provides higher quality spectra. Both significantly outperform EThcD methods, indicating that ETD-based methods are not required for routine N-glycoproteomics. Conversely, ETD-based methods, especially EThcD, are indispensable for site-specific analyses of O-glycopeptides. Our data show that O-glycopeptides cannot be robustly characterized with HCD-centric methods that are sufficient for N-glycopeptides, and glycoproteomic methods aiming to characterize O-glycopeptides must be constructed accordingly.
View details for DOI 10.1021/acs.jproteome.0c00218
View details for PubMedID 32500713
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PKA and HOG signaling contribute separable roles to anaerobic xylose fermentation in yeast engineered for biofuel production
PLOS ONE
2019; 14 (5): e0212389
Abstract
Lignocellulosic biomass offers a sustainable source for biofuel production that does not compete with food-based cropping systems. Importantly, two critical bottlenecks prevent economic adoption: many industrially relevant microorganisms cannot ferment pentose sugars prevalent in lignocellulosic medium, leaving a significant amount of carbon unutilized. Furthermore, chemical biomass pretreatment required to release fermentable sugars generates a variety of toxins, which inhibit microbial growth and metabolism, specifically limiting pentose utilization in engineered strains. Here we dissected genetic determinants of anaerobic xylose fermentation and stress tolerance in chemically pretreated corn stover biomass, called hydrolysate. We previously revealed that loss-of-function mutations in the stress-responsive MAP kinase HOG1 and negative regulator of the RAS/Protein Kinase A (PKA) pathway, IRA2, enhances anaerobic xylose fermentation. However, these mutations likely reduce cells' ability to tolerate the toxins present in lignocellulosic hydrolysate, making the strain especially vulnerable to it. We tested the contributions of Hog1 and PKA signaling via IRA2 or PKA negative regulatory subunit BCY1 to metabolism, growth, and stress tolerance in corn stover hydrolysate and laboratory medium with mixed sugars. We found mutations causing upregulated PKA activity increase growth rate and glucose consumption in various media but do not have a specific impact on xylose fermentation. In contrast, mutation of HOG1 specifically increased xylose usage. We hypothesized improving stress tolerance would enhance the rate of xylose consumption in hydrolysate. Surprisingly, increasing stress tolerance did not augment xylose fermentation in lignocellulosic medium in this strain background, suggesting other mechanisms besides cellular stress limit this strain's ability for anaerobic xylose fermentation in hydrolysate.
View details for DOI 10.1371/journal.pone.0212389
View details for Web of Science ID 000468451000003
View details for PubMedID 31112537
View details for PubMedCentralID PMC6528989
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Interactive Peptide Spectral Annotator: A Versatile Web-Based Tool for Proteomic Applications.
Molecular & cellular proteomics : MCP
2019
Abstract
Here we present IPSA, an innovative web-based spectrum annotator that visualizes and characterizes peptide tandem mass spectra. A tool for the scientific community, IPSA can visualize peptides collected using a wide variety of experimental and instrumental configurations. Annotated spectra are customizable via a selection of interactive features and can be exported as editable scalable vector graphics to aid in the production of publication-quality figures. Single spectra can be analyzed through provided web forms, while data for multiple peptide spectral matches can be uploaded using the Proteomics Standards Initiative file formats mzTab, mzIdentML, and mzML. Alternatively, peptide identifications and spectral data can be provided using generic file formats. IPSA provides supports for annotating spectra collecting using negative-mode ionization and facilitates the characterization of experimental MS/MS performance through the optional export of fragment ion statistics from one to many peptide spectral matches. This resource is made freely accessible at http://interactivepeptidespectralannotator.com, while the source code and user guides are available at https://github.com/coongroup/IPSA for private hosting or custom implementations.
View details for DOI 10.1074/mcp.TIR118.001209
View details for PubMedID 31088857
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Rewired cellular signaling coordinates sugar and hypoxic responses for anaerobic xylose fermentation in yeast.
PLoS genetics
2019; 15 (3): e1008037
Abstract
Microbes can be metabolically engineered to produce biofuels and biochemicals, but rerouting metabolic flux toward products is a major hurdle without a systems-level understanding of how cellular flux is controlled. To understand flux rerouting, we investigated a panel of Saccharomyces cerevisiae strains with progressive improvements in anaerobic fermentation of xylose, a sugar abundant in sustainable plant biomass used for biofuel production. We combined comparative transcriptomics, proteomics, and phosphoproteomics with network analysis to understand the physiology of improved anaerobic xylose fermentation. Our results show that upstream regulatory changes produce a suite of physiological effects that collectively impact the phenotype. Evolved strains show an unusual co-activation of Protein Kinase A (PKA) and Snf1, thus combining responses seen during feast on glucose and famine on non-preferred sugars. Surprisingly, these regulatory changes were required to mount the hypoxic response when cells were grown on xylose, revealing a previously unknown connection between sugar source and anaerobic response. Network analysis identified several downstream transcription factors that play a significant, but on their own minor, role in anaerobic xylose fermentation, consistent with the combinatorial effects of small-impact changes. We also discovered that different routes of PKA activation produce distinct phenotypes: deletion of the RAS/PKA inhibitor IRA2 promotes xylose growth and metabolism, whereas deletion of PKA inhibitor BCY1 decouples growth from metabolism to enable robust fermentation without division. Comparing phosphoproteomic changes across ira2Δ and bcy1Δ strains implicated regulatory changes linked to xylose-dependent growth versus metabolism. Together, our results present a picture of the metabolic logic behind anaerobic xylose flux and suggest that widespread cellular remodeling, rather than individual metabolic changes, is an important goal for metabolic engineering.
View details for DOI 10.1371/journal.pgen.1008037
View details for PubMedID 30856163
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Capturing site-specific heterogeneity with large-scale N-glycoproteome analysis.
Nature communications
2019; 10 (1): 1311
Abstract
Protein glycosylation is a highly important, yet poorly understood protein post-translational modification. Thousands of possible glycan structures and compositions create potential for tremendous site heterogeneity. A lack of suitable analytical methods for large-scale analyses of intact glycopeptides has limited our abilities both to address the degree of heterogeneity across the glycoproteome and to understand how this contributes biologically to complex systems. Here we show that N-glycoproteome site-specific microheterogeneity can be captured via large-scale glycopeptide profiling methods enabled by activated ion electron transfer dissociation (AI-ETD), ultimately characterizing 1,545 N-glycosites (>5,600 unique N-glycopeptides) from mouse brain tissue. Our data reveal that N-glycosylation profiles can differ between subcellular regions and structural domains and that N-glycosite heterogeneity manifests in several different forms, including dramatic differences in glycosites on the same protein. Moreover, we use this large-scale glycoproteomic dataset to develop several visualizations that will prove useful for analyzing intact glycopeptides in future studies.
View details for PubMedID 30899004
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Top-Down Characterization of Proteins with Intact Disulfide Bonds Using Activated-Ion Electron Transfer Dissociation
ANALYTICAL CHEMISTRY
2018; 90 (15): 8946–53
Abstract
Here we report the fragmentation of disulfide linked intact proteins using activated-ion electron transfer dissociation (AI-ETD) for top-down protein characterization. This fragmentation method is then compared to the alternative methods of beam-type collisional activation (HCD), electron transfer dissociation (ETD), and electron transfer and higher-energy collision dissociation (EThcD). We analyzed multiple precursor charge states of the protein standards bovine insulin, α-lactalbumin, lysozyme, β-lactoglobulin, and trypsin inhibitor. In all cases, we found that AI-ETD provides a boost in protein sequence coverage information and the generation of fragment ions from within regions enclosed by disulfide bonds. AI-ETD shows the largest improvement over the other techniques when analyzing highly disulfide linked and low charge density precursor ions. This substantial improvement is attributed to the concurrent irradiation of the gas phase ions while the electron-transfer reaction is taking place, mitigating nondissociative electron transfer, helping unfold the gas phase protein during the electron transfer event, and preventing disulfide bond reformation. We also show that AI-ETD is able to yield comparable sequence coverage information when disulfide bonds are left intact relative to proteins that have been reduced and alkylated. This work demonstrates that AI-ETD is an effective fragmentation method for the analysis of proteins with intact disulfide bonds, dramatically enhancing sequence ion generation and total sequence coverage compared to HCD and ETD.
View details for DOI 10.1021/acs.analchem.8b01113
View details for Web of Science ID 000441476600032
View details for PubMedID 29949341
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The Value of Activated Ion Electron Transfer Dissociation for High-Throughput Top-Down Characterization of Intact Proteins
ANALYTICAL CHEMISTRY
2018; 90 (14): 8553–60
Abstract
High-throughput top-down proteomic experiments directly identify proteoforms in complex mixtures, making high quality tandem mass spectra necessary to deeply characterize proteins with many sources of variation. Collision-based dissociation methods offer expedient data acquisition but often fail to extensively fragment proteoforms for thorough analysis. Electron-driven dissociation methods are a popular alternative approach, especially for precursor ions with high charge density. Combining infrared photoactivation concurrent with electron transfer dissociation (ETD) reactions, i.e., activated ion ETD (AI-ETD), can significantly improve ETD characterization of intact proteins, but benefits of AI-ETD have yet to be quantified in high-throughput top-down proteomics. Here, we report the first application of AI-ETD to LC-MS/MS characterization of intact proteins (<20 kDa), highlighting improved proteoform identification the method offers over higher energy-collisional dissociation (HCD), standard ETD, and ETD followed by supplemental HCD activation (EThcD). We identified 935 proteoforms from 295 proteins from human colorectal cancer cell line HCT116 using AI-ETD compared to 1014 proteoforms, 915 proteoforms, and 871 proteoforms with HCD, ETD, and EThcD, respectively. Importantly, AI-ETD outperformed each of the three other methods in MS/MS success rates and spectral quality metrics (e.g., sequence coverage achieved and proteoform characterization scores). In all, this four-method analysis offers the most extensive comparisons to date and demonstrates that AI-ETD both increases identifications over other ETD methods and improves proteoform characterization via higher sequence coverage, positioning it as a premier method for high-throughput top-down proteomics.
View details for DOI 10.1021/acs.analchem.8b01638
View details for Web of Science ID 000439397700038
View details for PubMedID 29924586
View details for PubMedCentralID PMC6050102
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Improved Precursor Characterization for Data-Dependent Mass Spectrometry
ANALYTICAL CHEMISTRY
2018; 90 (3): 2333–40
Abstract
Modern ion trap mass spectrometers are capable of collecting up to 60 tandem MS (MS/MS) scans per second, in theory providing acquisition speeds that can sample every eluting peptide precursor presented to the MS system. In practice, however, the precursor sampling capacity enabled by these ultrafast acquisition rates is often underutilized due to a host of reasons (e.g., long injection times and wide analyzer mass ranges). One often overlooked reason for this underutilization is that the instrument exhausts all the peptide features it identifies as suitable for MS/MS fragmentation. Highly abundant features can prevent annotation of lower abundance precursor ions that occupy similar mass-to-charge (m/z) space, which ultimately inhibits the acquisition of an MS/MS event. Here, we present an advanced peak determination (APD) algorithm that uses an iterative approach to annotate densely populated m/z regions to increase the number of peptides sampled during data-dependent LC-MS/MS analyses. The APD algorithm enables nearly full utilization of the sampling capacity of a quadrupole-Orbitrap-linear ion trap MS system, which yields up to a 40% increase in unique peptide identifications from whole cell HeLa lysates (approximately 53 000 in a 90 min LC-MS/MS analysis). The APD algorithm maintains improved peptide and protein identifications across several modes of proteomic data acquisition, including varying gradient lengths, different degrees of prefractionation, peptides derived from multiple proteases, and phosphoproteomic analyses. Additionally, the use of APD increases the number of peptides characterized per protein, providing improved protein quantification. In all, the APD algorithm increases the number of detectable peptide features, which maximizes utilization of the high MS/MS capacities and significantly improves sampling depth and identifications in proteomic experiments.
View details for DOI 10.1021/acs.analchem.7b04808
View details for Web of Science ID 000424730600117
View details for PubMedID 29272103
View details for PubMedCentralID PMC5803309
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The Role of Electron Transfer Dissociation in Modern Proteomics
ANALYTICAL CHEMISTRY
2018; 90 (1): 40–64
View details for DOI 10.1021/acs.analchem.7b04810
View details for Web of Science ID 000419419200004
View details for PubMedID 29172454
View details for PubMedCentralID PMC5750139
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Sequencing Larger Intact Proteins (30-70 kDa) with Activated Ion Electron Transfer Dissociation
JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY
2018; 29 (1): 140–49
Abstract
The analysis of intact proteins via mass spectrometry can offer several benefits to proteome characterization, although the majority of top-down experiments focus on proteoforms in a relatively low mass range (<30 kDa). Recent studies have focused on improving the analysis of larger intact proteins (up to ~75 kDa), but they have also highlighted several challenges to be addressed. One major hurdle is the efficient dissociation of larger protein ions, which often to do not yield extensive fragmentation via conventional tandem MS methods. Here we describe the first application of activated ion electron transfer dissociation (AI-ETD) to proteins in the 30-70 kDa range. AI-ETD leverages infrared photo-activation concurrent to ETD reactions to improve sequence-informative product ion generation. This method generates more product ions and greater sequence coverage than conventional ETD, higher-energy collisional dissociation (HCD), and ETD combined with supplemental HCD activation (EThcD). Importantly, AI-ETD provides the most thorough protein characterization for every precursor ion charge state investigated in this study, making it suitable as a universal fragmentation method in top-down experiments. Additionally, we highlight several acquisition strategies that can benefit characterization of larger proteins with AI-ETD, including combination of spectra from multiple ETD reaction times for a given precursor ion, multiple spectral acquisitions of the same precursor ion, and combination of spectra from two different dissociation methods (e.g., AI-ETD and HCD). In all, AI-ETD shows great promise as a method for dissociating larger intact protein ions as top-down proteomics continues to advance into larger mass ranges. Graphical Abstract ᅟ.
View details for DOI 10.1007/s13361-017-1808-7
View details for Web of Science ID 000423390800017
View details for PubMedID 29027149
View details for PubMedCentralID PMC5786479
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Negative Electron Transfer Dissociation Sequencing of Increasingly Sulfated Glycosaminoglycan Oligosaccharides on an Orbitrap Mass Spectrometer
JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY
2017; 28 (9): 1844–54
Abstract
The structural characterization of sulfated glycosaminoglycan (GAG) carbohydrates remains an important target for analytical chemists attributable to challenges introduced by the natural complexity of these mixtures and the defined need for molecular-level details to elucidate biological structure-function relationships. Tandem mass spectrometry has proven to be the most powerful technique for this purpose. Previously, electron detachment dissociation (EDD), in comparison to other methods of ion activation, has been shown to provide the largest number of useful cleavages for de novo sequencing of GAG oligosaccharides, but such experiments are restricted to Fourier transform ion cyclotron resonance mass spectrometers (FTICR-MS). Negative electron transfer dissociation (NETD) provides similar fragmentation results, and can be achieved on any mass spectrometry platform that is designed to accommodate ion-ion reactions. Here, we examine for the first time the effectiveness of NETD-Orbitrap mass spectrometry for the structural analysis of GAG oligosaccharides. Compounds ranging in size from tetrasaccharides to decasaccharides were dissociated by NETD, producing both glycosidic and cross-ring cleavages that enabled the location of sulfate modifications. The highly-sulfated, heparin-like synthetic GAG, ArixtraTM, was also successfully sequenced by NETD. In comparison to other efforts to sequence GAG chains without fully ionized sulfate constituents, the occurrence of sulfate loss peaks is minimized by judicious precursor ion selection. The results compare quite favorably to prior results with electron detachment dissociation (EDD). Significantly, the duty cycle of the NETD experiment is sufficiently short to make it an effective tool for on-line separations, presenting a straightforward path for selective, high-throughput analysis of GAG mixtures. Graphical Abstract ᅟ.
View details for DOI 10.1007/s13361-017-1709-9
View details for Web of Science ID 000407776200013
View details for PubMedID 28589488
View details for PubMedCentralID PMC5711533
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Sulfur Pentafluoride is a Preferred Reagent Cation for Negative Electron Transfer Dissociation
JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY
2017; 28 (7): 1324–32
Abstract
Negative mode proteome analysis offers access to unique portions of the proteome and several acidic post-translational modifications; however, traditional collision-based fragmentation methods fail to reliably provide sequence information for peptide anions. Negative electron transfer dissociation (NETD), on the other hand, can sequence precursor anions in a high-throughput manner. Similar to other ion-ion methods, NETD is most efficient with peptides of higher charge state because of the increased electrostatic interaction between reacting molecules. Here we demonstrate that NETD performance for lower charge state precursors can be improved by altering the reagent cation. Specifically, the recombination energy of the NETD reaction-largely dictated by the ionization energy (IE) of the reagent cation-can affect the extent of fragmentation. We compare the NETD reagent cations of C16H10●+ (IE = 7.9 eV) and SF5●+ (IE = 9.6 eV) on a set of standard peptides, concluding that SF5●+ yields greater sequence ion generation. Subsequent proteome-scale nLC-MS/MS experiments comparing C16H10●+ and SF5●+ further supported this outcome: analyses using SF5●+ yielded 4637 peptide spectral matches (PSMs) and 2900 unique peptides, whereas C16H10●+ produced 3563 PSMs and 2231 peptides. The substantive gain in identification power with SF5●+ was largely driven by improved identification of doubly deprotonated precursors, indicating that increased NETD recombination energy can increase product ion yield for low charge density precursors. This work demonstrates that SF5●+ is a viable, if not favorable, reagent cation for NETD, and provides improved fragmentation over the commonly used fluoranthene reagent. Graphical Abstract ᅟ.
View details for DOI 10.1007/s13361-017-1600-8
View details for Web of Science ID 000404171700011
View details for PubMedID 28349437
View details for PubMedCentralID PMC5483201
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Activated Ion-Electron Transfer Dissociation Enables Comprehensive Top-Down Protein Fragmentation
JOURNAL OF PROTEOME RESEARCH
2017; 16 (7): 2653–59
Abstract
Here we report the first demonstration of near-complete sequence coverage of intact proteins using activated ion-electron transfer dissociation (AI-ETD), a method that leverages concurrent infrared photoactivation to enhance electron-driven dissociation. AI-ETD produces mainly c/z-type product ions and provides comprehensive (77-97%) protein sequence coverage, outperforming HCD, ETD, and EThcD for all proteins investigated. AI-ETD also maintains this performance across precursor ion charge states, mitigating charge-state dependence that limits traditional approaches.
View details for DOI 10.1021/acs.jproteome.7b00249
View details for Web of Science ID 000405358500031
View details for PubMedID 28608681
View details for PubMedCentralID PMC5555583
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Implementation of Activated Ion Electron Transfer Dissociation on a Quadrupole-Orbitrap-Linear Ion Trap Hybrid Mass Spectrometer
ANALYTICAL CHEMISTRY
2017; 89 (12): 6358–66
Abstract
Using concurrent IR photoactivation during electron transfer dissociation (ETD) reactions, i.e., activated ion ETD (AI-ETD), significantly increases dissociation efficiency resulting in improved overall performance. Here we describe the first implementation of AI-ETD on a quadrupole-Orbitrap-quadrupole linear ion trap (QLT) hybrid MS system (Orbitrap Fusion Lumos) and demonstrate the substantial benefits it offers for peptide characterization. First, we show that AI-ETD can be implemented in a straightforward manner by fastening the laser and guiding optics to the instrument chassis itself, making alignment with the trapping volume of the QLT simple and robust. We then characterize the performance of AI-ETD using standard peptides in addition to a complex mixtures of tryptic peptides using LC-MS/MS, showing not only that AI-ETD can nearly double the identifications achieved with ETD alone but also that it outperforms the other available supplemental activation methods (ETcaD and EThcD). Finally, we introduce a new activation scheme called AI-ETD+ that combines AI-ETD in the high pressure cell of the QLT with a short infrared multiphoton dissociation (IRMPD) activation in the low-pressure cell. This reaction scheme introduces no addition time to the scan duty cycle but generates MS/MS spectra rich in b/y-type and c/z•-type product ions. The extensive generation of fragment ions in AI-ETD+ substantially increases peptide sequence coverage while also improving peptide identifications over all other ETD methods, making it a valuable new tool for hybrid fragmentation approaches.
View details for DOI 10.1021/acs.analchem.7b00213
View details for Web of Science ID 000404087600015
View details for PubMedID 28383247
View details for PubMedCentralID PMC5560271
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Phosphoproteomics with Activated Ion Electron Transfer Dissociation
ANALYTICAL CHEMISTRY
2017; 89 (12): 6367–76
Abstract
The ability to localize phosphosites to specific amino acid residues is crucial to translating phosphoproteomic data into biological meaningful contexts. In a companion manuscript ( Anal. Chem. 2017 , DOI: 10.1021/acs.analchem.7b00213 ), we described a new implementation of activated ion electron transfer dissociation (AI-ETD) on a quadrupole-Orbitrap-linear ion trap hybrid MS system (Orbitrap Fusion Lumos), which greatly improved peptide fragmentation and identification over ETD and other supplemental activation methods. Here we present the performance of AI-ETD for identifying and localizing sites of phosphorylation in both phosphopeptides and intact phosphoproteins. Using 90 min analyses we show that AI-ETD can identify 24,503 localized phosphopeptide spectral matches enriched from mouse brain lysates, which more than triples identifications from standard ETD experiments and outperforms ETcaD and EThcD as well. AI-ETD achieves these gains through improved quality of fragmentation and MS/MS success rates for all precursor charge states, especially for doubly protonated species. We also evaluate the degree to which phosphate neutral loss occurs from phosphopeptide product ions due to the infrared photoactivation of AI-ETD and show that modifying phosphoRS (a phosphosite localization algorithm) to include phosphate neutral losses can significantly improve localization in AI-ETD spectra. Finally, we demonstrate the utility of AI-ETD in localizing phosphosites in α-casein, an ∼23.5 kDa phosphoprotein that showed eight of nine known phosphorylation sites occupied upon intact mass analysis. AI-ETD provided the greatest sequence coverage for all five charge states investigated and was the only fragmentation method to localize all eight phosphosites for each precursor. Overall, this work highlights the analytical value AI-ETD can bring to both bottom-up and top-down phosphoproteomics.
View details for DOI 10.1021/acs.analchem.7b00212
View details for Web of Science ID 000404087600016
View details for PubMedID 28383256
View details for PubMedCentralID PMC5555596
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Multi-omics Evidence for Inheritance of Energy Pathways in Red Blood Cells
MOLECULAR & CELLULAR PROTEOMICS
2016; 15 (12): 3614–23
Abstract
Each year over 90 million units of blood are transfused worldwide. Our dependence on this blood supply mandates optimized blood management and storage. During storage, red blood cells undergo degenerative processes resulting in altered metabolic characteristics which may make blood less viable for transfusion. However, not all stored blood spoils at the same rate, a difference that has been attributed to variable rates of energy usage and metabolism in red blood cells. Specific metabolite abundances are heritable traits; however, the link between heritability of energy metabolism and red blood cell storage profiles is unclear. Herein we performed a comprehensive metabolomics and proteomics study of red blood cells from 18 mono- and di-zygotic twin pairs to measure heritability and identify correlations with ATP and other molecular indices of energy metabolism. Without using affinity-based hemoglobin depletion, our work afforded the deepest multi-omic characterization of red blood cell membranes to date (1280 membrane proteins and 330 metabolites), with 119 membrane protein and 148 metabolite concentrations found to be over 30% heritable. We demonstrate a high degree of heritability in the concentration of energy metabolism metabolites, especially glycolytic metabolites. In addition to being heritable, proteins and metabolites involved in glycolysis and redox metabolism are highly correlated, suggesting that crucial energy metabolism pathways are inherited en bloc at distinct levels. We conclude that individuals can inherit a phenotype composed of higher or lower concentrations of these proteins together. This can result in vastly different red blood cells storage profiles which may need to be considered to develop precise and individualized storage options. Beyond guiding proper blood storage, this intimate link in heritability between energy and redox metabolism pathways may someday prove useful in determining the predisposition of an individual toward metabolic diseases.
View details for DOI 10.1074/mcp.M116.062349
View details for Web of Science ID 000390346600006
View details for PubMedID 27777340
View details for PubMedCentralID PMC5141275
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Full-Featured Search Algorithm for Negative Electron-Transfer Dissociation
JOURNAL OF PROTEOME RESEARCH
2016; 15 (8): 2768–76
Abstract
Negative electron-transfer dissociation (NETD) has emerged as a premier tool for peptide anion analysis, offering access to acidic post-translational modifications and regions of the proteome that are intractable with traditional positive-mode approaches. Whole-proteome scale characterization is now possible with NETD, but proper informatic tools are needed to capitalize on advances in instrumentation. Currently only one database search algorithm (OMSSA) can process NETD data. Here we implement NETD search capabilities into the Byonic platform to improve the sensitivity of negative-mode data analyses, and we benchmark these improvements using 90 min LC-MS/MS analyses of tryptic peptides from human embryonic stem cells. With this new algorithm for searching NETD data, we improved the number of successfully identified spectra by as much as 80% and identified 8665 unique peptides, 24 639 peptide spectral matches, and 1338 proteins in activated-ion NETD analyses, more than doubling identifications from previous negative-mode characterizations of the human proteome. Furthermore, we reanalyzed our recently published large-scale, multienzyme negative-mode yeast proteome data, improving peptide and peptide spectral match identifications and considerably increasing protein sequence coverage. In all, we show that new informatics tools, in combination with recent advances in data acquisition, can significantly improve proteome characterization in negative-mode approaches.
View details for DOI 10.1021/acs.jproteome.6b00319
View details for Web of Science ID 000381235900038
View details for PubMedID 27402189
View details for PubMedCentralID PMC6128406
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Genome Sequence and Analysis of a Stress-Tolerant, Wild-Derived Strain of Saccharomyces cerevisiae Used in Biofuels Research
G3-GENES GENOMES GENETICS
2016; 6 (6): 1757–66
Abstract
The genome sequences of more than 100 strains of the yeast Saccharomyces cerevisiae have been published. Unfortunately, most of these genome assemblies contain dozens to hundreds of gaps at repetitive sequences, including transposable elements, tRNAs, and subtelomeric regions, which is where novel genes generally reside. Relatively few strains have been chosen for genome sequencing based on their biofuel production potential, leaving an additional knowledge gap. Here, we describe the nearly complete genome sequence of GLBRCY22-3 (Y22-3), a strain of S. cerevisiae derived from the stress-tolerant wild strain NRRL YB-210 and subsequently engineered for xylose metabolism. After benchmarking several genome assembly approaches, we developed a pipeline to integrate Pacific Biosciences (PacBio) and Illumina sequencing data and achieved one of the highest quality genome assemblies for any S. cerevisiae strain. Specifically, the contig N50 is 693 kbp, and the sequences of most chromosomes, the mitochondrial genome, and the 2-micron plasmid are complete. Our annotation predicts 92 genes that are not present in the reference genome of the laboratory strain S288c, over 70% of which were expressed. We predicted functions for 43 of these genes, 28 of which were previously uncharacterized and unnamed. Remarkably, many of these genes are predicted to be involved in stress tolerance and carbon metabolism and are shared with a Brazilian bioethanol production strain, even though the strains differ dramatically at most genetic loci. The Y22-3 genome sequence provides an exceptionally high-quality resource for basic and applied research in bioenergy and genetics.
View details for DOI 10.1534/g3.116.029389
View details for Web of Science ID 000377821600026
View details for PubMedID 27172212
View details for PubMedCentralID PMC4889671
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Proteomics Moves into the Fast Lane
CELL SYSTEMS
2016; 2 (3): 142–43
Abstract
Three studies demonstrate the potential of state-of-the-art mass spectrometry-based proteomics for rapid, deep characterization of proteomes.
View details for DOI 10.1016/j.cels.2016.03.002
View details for Web of Science ID 000394358800003
View details for PubMedID 27135360
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Enhanced Dissociation of Intact Proteins with High Capacity Electron Transfer Dissociation
JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY
2016; 27 (3): 520–31
Abstract
Electron transfer dissociation (ETD) is a valuable tool for protein sequence analysis, especially for the fragmentation of intact proteins. However, low product ion signal-to-noise often requires some degree of signal averaging to achieve high quality MS/MS spectra of intact proteins. Here we describe a new implementation of ETD on the newest generation of quadrupole-Orbitrap-linear ion trap Tribrid, the Orbitrap Fusion Lumos, for improved product ion signal-to-noise via ETD reactions on larger precursor populations. In this new high precursor capacity ETD implementation, precursor cations are accumulated in the center section of the high pressure cell in the dual pressure linear ion trap prior to charge-sign independent trapping, rather than precursor ion sequestration in only the back section as is done for standard ETD. This new scheme increases the charge capacity of the precursor accumulation event, enabling storage of approximately 3-fold more precursor charges. High capacity ETD boosts the number of matching fragments identified in a single MS/MS event, reducing the need for spectral averaging. These improvements in intra-scan dynamic range via reaction of larger precursor populations, which have been previously demonstrated through custom modified hardware, are now available on a commercial platform, offering considerable benefits for intact protein analysis and top down proteomics. In this work, we characterize the advantages of high precursor capacity ETD through studies with myoglobin and carbonic anhydrase.
View details for DOI 10.1007/s13361-015-1306-8
View details for Web of Science ID 000370272700016
View details for PubMedID 26589699
View details for PubMedCentralID PMC4758868
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Mitochondrial protein hyperacetylation in the failing heart
JCI INSIGHT
2016; 1 (2)
View details for DOI 10.1172/jci.insight.84897
View details for Web of Science ID 000387103700001
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Phosphoproteomics in the Age of Rapid and Deep Proteome Profiling
ANALYTICAL CHEMISTRY
2016; 88 (1): 74–94
View details for DOI 10.1021/acs.analchem.5b04123
View details for Web of Science ID 000367866100005
View details for PubMedID 26539879
View details for PubMedCentralID PMC4790442
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A Calibration Routine for Efficient ETD in Large-Scale Proteomics
JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY
2015; 26 (11): 1848–57
Abstract
Electron transfer dissociation (ETD) has been broadly adopted and is now available on a variety of commercial mass spectrometers. Unlike collisional activation techniques, optimal performance of ETD requires considerable user knowledge and input. ETD reaction duration is one key parameter that can greatly influence spectral quality and overall experiment outcome. We describe a calibration routine that determines the correct number of reagent anions necessary to reach a defined ETD reaction rate. Implementation of this automated calibration routine on two hybrid Orbitrap platforms illustrate considerable advantages, namely, increased product ion yield with concomitant reduction in scan rates netting up to 75% more unique peptide identifications in a shotgun experiment. Graphical Abstract ᅟ.
View details for DOI 10.1007/s13361-015-1183-1
View details for Web of Science ID 000362955400008
View details for PubMedID 26111518
View details for PubMedCentralID PMC5642106
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The Negative Mode Proteome with Activated Ion Negative Electron Transfer Dissociation (AI-NETD)
MOLECULAR & CELLULAR PROTEOMICS
2015; 14 (10): 2644–60
Abstract
The field of proteomics almost uniformly relies on peptide cation analysis, leading to an underrepresentation of acidic portions of proteomes, including relevant acidic posttranslational modifications. Despite the many benefits negative mode proteomics can offer, peptide anion analysis remains in its infancy due mainly to challenges with high-pH reversed-phase separations and a lack of robust fragmentation methods suitable for peptide anion characterization. Here, we report the first implementation of activated ion negative electron transfer dissociation (AI-NETD) on the chromatographic timescale, generating 7,601 unique peptide identifications from Saccharomyces cerevisiae in single-shot nLC-MS/MS analyses of tryptic peptides-a greater than 5-fold increase over previous results with NETD alone. These improvements translate to identification of 1,106 proteins, making this work the first negative mode study to identify more than 1,000 proteins in any system. We then compare the performance of AI-NETD for analysis of peptides generated by five proteases (trypsin, LysC, GluC, chymotrypsin, and AspN) for negative mode analyses, identifying as many as 5,356 peptides (1,045 proteins) with LysC and 4,213 peptides (857 proteins) with GluC in yeast-characterizing 1,359 proteins in total. Finally, we present the first deep-sequencing approach for negative mode proteomics, leveraging offline low-pH reversed-phase fractionation prior to online high-pH separations and peptide fragmentation with AI-NETD. With this platform, we identified 3,467 proteins in yeast with trypsin alone and characterized a total of 3,730 proteins using multiple proteases, or nearly 83% of the expressed yeast proteome. This work represents the most extensive negative mode proteomics study to date, establishing AI-NETD as a robust tool for large-scale peptide anion characterization and making the negative mode approach a more viable platform for future proteomic studies.
View details for DOI 10.1074/mcp.M115.049726
View details for Web of Science ID 000362186200007
View details for PubMedID 26193884
View details for PubMedCentralID PMC4597142
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Activated Ion Electron Transfer Dissociation for Improved Fragmentation of Intact Proteins
ANALYTICAL CHEMISTRY
2015; 87 (14): 7109–16
Abstract
Here we report the first implementation of activated ion electron transfer dissociation (AI-ETD) for top down protein characterization, showing that AI-ETD definitively extends the m/z range over which ETD can be effective for fragmentation of intact proteins. AI-ETD, which leverages infrared photon bombardment concurrent to the ETD reaction to mitigate nondissociative electron transfer, was performed using a novel multipurpose dissociation cell that can perform both beam-type collisional dissociation and ion-ion reactions on an ion trap-Orbitrap hybrid mass spectrometer. AI-ETD increased the number of c- and z-type product ions for all charge states over ETD alone, boosting product ion yield by nearly 4-fold for low charge density precursors. AI-ETD also outperformed HCD, generating more matching fragments for all proteins at all charge states investigated. In addition to generating more unique fragment ions, AI-ETD provided greater protein sequence coverage compared to both HCD and ETD. In all, the effectiveness of AI-ETD across the entirety of the m/z spectrum demonstrates its efficacy for robust fragmentation of intact proteins.
View details for DOI 10.1021/acs.analchem.5b00881
View details for Web of Science ID 000358555900019
View details for PubMedID 26067513
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Coupling Capillary Zone Electrophoresis with Electron Transfer Dissociation and Activated Ion Electron Transfer Dissociation for Top-Down Proteomics
ANALYTICAL CHEMISTRY
2015; 87 (10): 5422–29
Abstract
Top-down proteomics offers the potential for full protein characterization, but many challenges remain for this approach, including efficient protein separations and effective fragmentation of intact proteins. Capillary zone electrophoresis (CZE) has shown great potential for separation of intact proteins, especially for differentially modified proteoforms of the same gene product. To date, however, CZE has been used only with collision-based fragmentation methods. Here we report the first implementation of electron transfer dissociation (ETD) with online CZE separations for top-down proteomics, analyzing a mixture of four standard proteins and a complex protein mixture from the Mycobacterium marinum bacterial secretome. Using a multipurpose dissociation cell on an Orbitrap Elite system, we demonstrate that CZE is fully compatible with ETD as well as higher energy collisional dissociation (HCD), and that the two complementary fragmentation methods can be used in tandem on the electrophoretic time scale for improved protein characterization. Furthermore, we show that activated ion electron transfer dissociation (AI-ETD), a recently introduced method for enhanced ETD fragmentation, provides useful performance with CZE separations to greatly increase protein characterization. When combined with HCD, AI-ETD improved the protein sequence coverage by more than 200% for proteins from both standard and complex mixtures, highlighting the benefits electron-driven dissociation methods can add to CZE separations.
View details for DOI 10.1021/acs.analchem.5b00883
View details for Web of Science ID 000355057700056
View details for PubMedID 25893372
View details for PubMedCentralID PMC4439324
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Neutron-Encoded Mass Signatures for Quantitative Top-Down Proteomics
ANALYTICAL CHEMISTRY
2014; 86 (5): 2314–19
Abstract
The ability to acquire highly accurate quantitative data is an increasingly important part of any proteomics experiment, whether shotgun or top-down approaches are used. We recently developed a quantitation strategy for peptides based on neutron encoding, or NeuCode SILAC, which uses closely spaced heavy isotope-labeled amino acids and high-resolution mass spectrometry to provide quantitative data. We reasoned that the strategy would also be applicable to intact proteins and could enable robust, multiplexed quantitation for top-down experiments. We used yeast lysate labeled with either (13)C6(15)N2-lysine or (2)H8-lysine, isotopologues of lysine that are spaced 36 mDa apart. Proteins having such close spacing cannot be distinguished during a medium resolution scan, but upon acquiring a high-resolution scan, the two forms of the protein with each amino acid are resolved and the quantitative information revealed. An additional benefit NeuCode SILAC provides for top down is that the spacing of the isotope peaks indicates the number of lysines present in the protein, information that aids in identification. We used NeuCode SILAC to quantify several hundred isotope distributions, manually identify and quantify proteins from 1:1, 3:1, and 5:1 mixed ratios, and demonstrate MS(2)-based quantitation using ETD.
View details for DOI 10.1021/ac403579s
View details for Web of Science ID 000332494100009
View details for PubMedID 24475910
View details for PubMedCentralID PMC3983007