Honors & Awards

  • ASMS Postdoctoral Career Development Award, American Society for Mass Spectrometry (2019)
  • NIH K00 Postdoctoral Fellow (Predoctoral to Postdoctoral Fellow Transition Award, F99/K00), National Institutes of Health - National Cancer Institute (2016-2022)
  • National Science Foundation (NSF) Graduate Research Fellow, National Science Foundation (2014-2016)
  • Richard and Joan Hartl Award for Research Excellence in Analytical Chemistry, Department of Chemistry, University of Wisconsin-Madison (2018)
  • Roger J. Carlson Memorial Award for Research Excellence, Department of Chemistry, University of Wisconsin-Madison (2017)
  • FACSS Student Award, Federation of Analytical Chemistry and Spectroscopy Societies (2017)
  • American Society for Mass Spectrometry Graduate Student Award, American Society for Mass Spectrometry (2015)
  • Marg Northcott Student Award, Lake Louise Tandem MS Workshop (2016)
  • Richard A. Schaeffer Award, American Society of Mass Spectrometry (2014)
  • Outstanding Oral Presentation Award, Midwest Carbohydrate and Glycobiology Symposium (2017)
  • Rising Star Recognition, Human Proteomics Symposium (2018)
  • 1st Place in Poster Competition, Human Proteomics Symposium (2015)
  • 1st Place in Poster Competition, Department of Chemistry, University of Wisconsin-Madison (2017)
  • Pei Wang Graduate Fellowship, University of Wisconsin-Madison (2012)
  • Louise McBee Graduate Fellowship, Alpha Lambda Delta Honors Society (2012)
  • Algernon Sydney Sullivan Award (top undergraduate student), University of South Carolina (2012)
  • Joseph H. Gibbons Outstanding Senior Award, Omicron Delta Kappa Honors Society (2012)
  • Omicron Delta Kappa Leader of the Year, Omicron Delta Kappa Honors Society Chi Circle, University of South Carolina (2012)
  • American Institute of Chemists Foundation Award, University of South Carolina (2011, 2012)
  • Presidential Volunteer Service Award, Gold Level (250+ hours), Office of President Barack Obama (2011)
  • Wilson-Kibler Bicentennial Leadership Award, University of South Carolina (2011)
  • Phi Beta Kappa, Phi Beta Kappa Society (2010)
  • Cultural Ambassadorial Scholar, Rotary International (2009-2010)
  • Jo Anne J. Trow Academic Scholar, Alpha Lambda Delta Honors Society (2009)
  • Magellan Undergraduate Research Grant, University of South Carolina (2008-2010)
  • Robert C. Byrd Academic Scholar, US Department of Education (2007-2011)
  • Robert C. McNair Scholar (full tuition scholarship awarded for academic merit), University of South Carolina (2007-2011)

Boards, Advisory Committees, Professional Organizations

  • Member, Society for Glycobiology (2017 - Present)
  • Member, US Human Proteome Organization (HUPO) (2015 - Present)
  • Member, American Chemical Society (2013 - Present)
  • Member, American Society for Mass Spectrometry (2013 - Present)

Professional Education

  • Doctor of Philosophy, University of Wisconsin Madison (2018)
  • Bachelor of Science, University of South Carolina (2012)

Stanford Advisors

Current Research and Scholarly Interests

In my graduate training in the Coon lab I developed new mass spectrometry instrumentation and methodology to leverage ion-ion reactions and other modes of tandem mass spectrometry for proteomic analyses. I specifically applied these technologies to large-scale characterization of intact proteins and post-translational modifications, namely glycosylation and phosphorylation.

As a postdoctoral researcher in the Bertozzi group, I am investigating new ways to study and modify cell surfaces in cancer cells to understand tumor progression. Through chemical tools to label and engineer mucin-type proteins and sialosides in the cancer glycocalyx (the collection of cell surface glycoconjugates), I aim to understand the role of glycosylation in cancer metastasis and how to develop new therapeutic strategies based on this knowledge.

All Publications

  • 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 Leung, K. K., Wilson, G. M., Kirkemo, L. L., Riley, N. M., Coon, J. J., Wells, J. A. 2020


    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

  • Optimal Dissociation Methods Differ for N- and O-glycopeptides. Journal of proteome research Riley, N. M., Malaker, S. A., Driessen, M., Bertozzi, C. R. 2020


    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

  • Enzyme toolkit for selective enrichment and analysis of mucin-domain glycoproteins Malaker, S. A., Shon, J., Pedram, K., Riley, N. M., Bertozzi, C. R. AMER SOC BIOCHEMISTRY MOLECULAR BIOLOGY INC. 2019: S42
  • PKA and HOG signaling contribute separable roles to anaerobic xylose fermentation in yeast engineered for biofuel production PLOS ONE Wagner, E. R., Myers, K. S., Riley, N. M., Coon, J. J., Gasch, A. P. 2019; 14 (5): e0212389


    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

  • Rewired cellular signaling coordinates sugar and hypoxic responses for anaerobic xylose fermentation in yeast. PLoS genetics Myers, K. S., Riley, N. M., MacGilvray, M. E., Sato, T. K., McGee, M., Heilberger, J., Coon, J. J., Gasch, A. P. 2019; 15 (3): e1008037


    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

  • Interactive Peptide Spectral Annotator: A Versatile Web-Based Tool for Proteomic Applications. Molecular & cellular proteomics : MCP Brademan, D. R., Riley, N. M., Kwiecien, N. W., Coon, J. J. 2019


    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

  • Capturing site-specific heterogeneity with large-scale N-glycoproteome analysis. Nature communications Riley, N. M., Hebert, A. S., Westphall, M. S., Coon, J. J. 2019; 10 (1): 1311


    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

  • Top-Down Characterization of Proteins with Intact Disulfide Bonds Using Activated-Ion Electron Transfer Dissociation ANALYTICAL CHEMISTRY Rush, M. P., Riley, N. M., Westphall, M. S., Coon, J. J. 2018; 90 (15): 8946–53


    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

  • The Value of Activated Ion Electron Transfer Dissociation for High-Throughput Top-Down Characterization of Intact Proteins ANALYTICAL CHEMISTRY Riley, N. M., Sikora, J. W., Seckler, H. S., Greer, J. B., Fellers, R. T., LeDuc, R. D., Westphall, M. S., Thomas, P. M., Kelleher, N. L., Coon, J. J. 2018; 90 (14): 8553–60


    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

  • Improved Precursor Characterization for Data-Dependent Mass Spectrometry ANALYTICAL CHEMISTRY Hebert, A. S., Thoeing, C., Riley, N. M., Kwiecien, N. W., Shiskova, E., Huguet, R., Cardasis, H. L., Kuehn, A., Eliuk, S., Zabrouskov, V., Westphall, M. S., McAlister, G. C., Coon, J. J. 2018; 90 (3): 2333–40


    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

  • The Role of Electron Transfer Dissociation in Modern Proteomics ANALYTICAL CHEMISTRY Riley, N. M., Coon, J. J. 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

  • Sequencing Larger Intact Proteins (30-70 kDa) with Activated Ion Electron Transfer Dissociation JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY Riley, N. M., Westphall, M. S., Coon, J. J. 2018; 29 (1): 140–49


    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

  • Negative Electron Transfer Dissociation Sequencing of Increasingly Sulfated Glycosaminoglycan Oligosaccharides on an Orbitrap Mass Spectrometer JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY Leach, F. E., Riley, N. M., Westphall, M. S., Coon, J. J., Amster, I. 2017; 28 (9): 1844–54


    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

  • Sulfur Pentafluoride is a Preferred Reagent Cation for Negative Electron Transfer Dissociation JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY Rush, M. P., Riley, N. M., Westphall, M. S., Syka, J. P., Coon, J. J. 2017; 28 (7): 1324–32


    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

  • Activated Ion-Electron Transfer Dissociation Enables Comprehensive Top-Down Protein Fragmentation JOURNAL OF PROTEOME RESEARCH Riley, N. M., Westphall, M. S., Coon, J. J. 2017; 16 (7): 2653–59


    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

  • Implementation of Activated Ion Electron Transfer Dissociation on a Quadrupole-Orbitrap-Linear Ion Trap Hybrid Mass Spectrometer ANALYTICAL CHEMISTRY Riley, N. M., Westphall, M. S., Hebert, A. S., Coon, J. J. 2017; 89 (12): 6358–66


    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

  • Phosphoproteomics with Activated Ion Electron Transfer Dissociation ANALYTICAL CHEMISTRY Riley, N. M., Hebert, A. S., Duernberger, G., Stanek, F., Mechtler, K., Westphall, M. S., Coon, J. J. 2017; 89 (12): 6367–76


    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

  • Multi-omics Evidence for Inheritance of Energy Pathways in Red Blood Cells MOLECULAR & CELLULAR PROTEOMICS Weisenhorn, E. M., van 't Erve, T. J., Riley, N. M., Hess, J. R., Raife, T. J., Coon, J. J. 2016; 15 (12): 3614–23


    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

  • Full-Featured Search Algorithm for Negative Electron-Transfer Dissociation JOURNAL OF PROTEOME RESEARCH Riley, N. M., Bern, M., Westphall, M. S., Coon, J. J. 2016; 15 (8): 2768–76


    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

  • Genome Sequence and Analysis of a Stress-Tolerant, Wild-Derived Strain of Saccharomyces cerevisiae Used in Biofuels Research G3-GENES GENOMES GENETICS McIlwain, S. J., Peris, D., Sardi, M., Moskvin, O. V., Zhan, F., Myers, K. S., Riley, N. M., Buzzell, A., Parreiras, L. S., Ong, I. M., Landick, R., Coon, J. J., Gasch, A. P., Sato, T. K., Hittinger, C. 2016; 6 (6): 1757–66


    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

  • Proteomics Moves into the Fast Lane CELL SYSTEMS Riley, N. M., Hebert, A. S., Coon, J. J. 2016; 2 (3): 142–43


    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

  • Enhanced Dissociation of Intact Proteins with High Capacity Electron Transfer Dissociation JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY Riley, N. M., Mullen, C., Weisbrod, C. R., Sharma, S., Senko, M. W., Zabrouskov, V., Westphall, M. S., Syka, J. P., Coon, J. J. 2016; 27 (3): 520–31


    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

  • Mitochondrial protein hyperacetylation in the failing heart JCI INSIGHT Horton, J. L., Martin, O. J., Lai, L., Riley, N. M., Richards, A. L., Vega, R. B., Leone, T. C., Pagliarini, D. J., Muoio, D. M., Bedi, K. C., Margulies, K. B., Coon, J. J., Kelly, D. P. 2016; 1 (2)
  • Phosphoproteomics in the Age of Rapid and Deep Proteome Profiling ANALYTICAL CHEMISTRY Riley, N. M., Coon, J. J. 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

  • A Calibration Routine for Efficient ETD in Large-Scale Proteomics JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY Rose, C. M., Rush, M. P., Riley, N. M., Merrill, A. E., Kwiecien, N. W., Holden, D. D., Mullen, C., Westphall, M. S., Coon, J. J. 2015; 26 (11): 1848–57


    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

  • The Negative Mode Proteome with Activated Ion Negative Electron Transfer Dissociation (AI-NETD) MOLECULAR & CELLULAR PROTEOMICS Riley, N. M., Rush, M. P., Rose, C. M., Richards, A. L., Kwiecien, N. W., Bailey, D. J., Hebert, A. S., Westphall, M. S., Coon, J. J. 2015; 14 (10): 2644–60


    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

  • Activated Ion Electron Transfer Dissociation for Improved Fragmentation of Intact Proteins ANALYTICAL CHEMISTRY Riley, N. M., Westphall, M. S., Coon, J. J. 2015; 87 (14): 7109–16


    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

  • Coupling Capillary Zone Electrophoresis with Electron Transfer Dissociation and Activated Ion Electron Transfer Dissociation for Top-Down Proteomics ANALYTICAL CHEMISTRY Zhao, Y., Riley, N. M., Sun, L., Hebert, A. S., Yan, X., Westphall, M. S., Rush, M. P., Zhu, G., Champion, M. M., Medie, F., Champion, P., Coon, J. J., Dovichi, N. J. 2015; 87 (10): 5422–29


    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

  • Neutron-Encoded Mass Signatures for Quantitative Top-Down Proteomics ANALYTICAL CHEMISTRY Rhoads, T. W., Rose, C. M., Bailey, D. J., Riley, N. M., Molden, R. C., Nestler, A. J., Merrill, A. E., Smith, L. M., Hebert, A. S., Westphall, M. S., Pagliarini, D. J., Garcia, B. A., Coon, J. J. 2014; 86 (5): 2314–19


    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