Nicholas M. Riley

Phosphoproteomics in the Age of Rapid and Deep Proteome Profiling

Profiling Nicholas M. Riley†,‡ and Joshua J. Coon*,†,‡,§ †Genome Center of Wisconsin, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States ‡Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States ■ CONTENTS Sampling the Phosphoproteome 74 Generating Phosphopeptides 75 Enrichment Strategies 75 Chromatographic Separations 77 Mass Spectrometry Instrumentation 78 Data Acquisition Strategies 79 Balancing Throughput and Depth 79 Quantifying the Phosphoproteome 81 Stable Isotope Labeling 81 Label-Free Strategies 83 Confident Phosphosite Assignment 84 Tandem MS Approaches 84 Post-Acquisition Processing and Informatics 85 Biological Insights via Phosphoproteomics 87 PTM Cross-Talk 88 Phosphorylation beyond Serine, Threonine, and Tyrosine 88 Looking Forward 89 Author Information 89 Corresponding Author 89 Notes 89 Biographies 89 Acknowledgments 89 References 89

Coupling Capillary Zone Electrophoresis with Electron Transfer Dissociation and Activated Ion Electron Transfer Dissociation for Top-Down Proteomics

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.

Activated Ion Electron Transfer Dissociation for Improved Fragmentation of Intact Proteins.

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.

The Negative Mode Proteome with Activated Ion Negative Electron Transfer Dissociation (AI-NETD)

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.

Neutron-encoded mass signatures for quantitative top-down proteomics.

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 13C615N2-lysine or 2H8-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 MS2-based quantitation using ETD.

Enhanced Dissociation of Intact Proteins with High Capacity Electron Transfer Dissociation.

AbstractElectron 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. Graphical Abstractᅟ

A Calibration Routine for Efficient ETD in Large-Scale Proteomics

AbstractElectron 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 Abstractᅟ

Genome Sequence and Analysis of a Stress-Tolerant, Wild-Derived Strain of Saccharomyces cerevisiae Used in Biofuels Research

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.

Proteomics Moves into the Fast Lane

Three studies demonstrate the potential of state-of-the-art mass spectrometry-based proteomics for rapid, deep characterization of proteomes.

Phosphoproteomics with Activated Ion Electron Transfer Dissociation

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.