Cancer-stromal cell interactions in breast cancer brain metastases induce glycocalyx-mediated resistance to HER2-targeting therapies

Brain metastatic breast cancer is particularly lethal largely due to therapeutic resistance. Almost half of the patients with metastatic HER2-positive breast cancer develop brain metastases, representing a major clinical challenge. We previously described that cancer-associated fibroblasts are an important source of resistance in primary tumors. Here, we report that breast cancer brain metastasis stromal cell interactions in 3D cocultures induce therapeutic resistance to HER2-targeting agents, particularly to the small molecule inhibitor of HER2/EGFR neratinib. We investigated the underlying mechanisms using a synthetic Notch reporter system enabling the sorting of cancer cells that directly interact with stromal cells. We identified mucins and bulky glycoprotein synthesis as top-up-regulated genes and pathways by comparing the gene expression and chromatin profiles of stroma-contact and no-contact cancer cells before and after neratinib treatment. Glycoprotein gene signatures were also enriched in human brain metastases compared to primary tumors. We confirmed increased glycocalyx surrounding cocultures by immunofluorescence and showed that mucinase treatment increased sensitivity to neratinib by enabling a more efficient inhibition of EGFR/HER2 signaling in cancer cells. Overexpression of truncated MUC1 lacking the intracellular domain as a model of increased glycocalyx-induced resistance to neratinib both in cell culture and in experimental brain metastases in immunodeficient mice. Our results highlight the importance of glycoproteins as a resistance mechanism to HER2-targeting therapies in breast cancer brain metastases.

Design of a mucin-selective protease for targeted degradation of cancer-associated mucins

Targeted protein degradation is an emerging strategy for the elimination of classically undruggable proteins. Here, to expand the landscape of targetable substrates, we designed degraders that achieve substrate selectivity via recognition of a discrete peptide and glycan motif and achieve cell-type selectivity via antigen-driven cell-surface binding. We applied this approach to mucins, O-glycosylated proteins that drive cancer progression through biophysical and immunological mechanisms. Engineering of a bacterial mucin-selective protease yielded a variant for fusion to a cancer antigen-binding nanobody. The resulting conjugate selectively degraded mucins on cancer cells, promoted cell death in culture models of mucin-driven growth and survival, and reduced tumor growth in mouse models of breast cancer progression. This work establishes a blueprint for the development of biologics that degrade specific protein glycoforms on target cells.

Galectin-3 does not interact with RNA directly

Galectin-3, well characterized as a glycan binding protein, has been identified as a putative RNA binding protein, possibly through participation in pre-mRNA maturation through interactions with splicosomes. Given recent developments with cell surface RNA biology, the putative dual-function nature of galectin-3 evokes a possible non-classical connection between glycobiology and RNA biology. However, with limited functional evidence of a direct RNA interaction, many molecular-level observations rely on affinity reagents and lack appropriate genetic controls. Thus, evidence of a direct interaction remains elusive. We demonstrate that antibodies raised to endogenous human galectin-3 can isolate RNA-protein crosslinks, but this activity remains insensitive to LGALS3 knock-out. Proteomic characterization of anti-galectin-3 IPs revealed enrichment of galectin-3, but high abundance of hnRNPA2B1, an abundant, well-characterized RNA-binding protein with weak homology to the N-terminal domain of galectin-3, in the isolate. Genetic ablation of HNRNPA2B1, but not LGALS3, eliminates the ability of the anti-galectin-3 antibodies to isolate RNA-protein crosslinks, implying either an indirect interaction or cross-reactivity. To address this, we introduced an epitope tag to the endogenous C-terminal locus of LGALS3. Isolation of the tagged galectin-3 failed to reveal any RNA-protein crosslinks. This result suggests that the galectin-3 does not directly interact with RNA and may be misidentified as an RNA-binding protein, at least in HeLa where the putative RNA associations were first identified. We encourage further investigation of this phenomenon employ gene deletions and, when possible, endogenous epitope tags to achieve the specificity required to evaluate potential interactions.

The glycoimmune checkpoint receptor Siglec-7 interacts with T-cell ligands and regulates T-cell activation

Siglec-7 (sialic acid-binding immunoglobulin-like lectin 7) is a glycan-binding immune receptor that is emerging as a significant target of interest for cancer immunotherapy. The physiological ligands that bind Siglec-7, however, remain incompletely defined. In this study, we characterized the expression of Siglec-7 ligands on peripheral immune cell subsets and assessed whether Siglec-7 functionally regulates interactions between immune cells. We found that disialyl core 1 O-glycans are the major immune ligands for Siglec-7 and that these ligands are particularly highly expressed on naïve T-cells. Densely glycosylated sialomucins are the primary carriers of these glycans, in particular a glycoform of the cell-surface marker CD43. Biosynthesis of Siglec-7-binding glycans is dynamically controlled on different immune cell subsets through a genetic circuit involving the glycosyltransferase GCNT1. Siglec-7 blockade was found to increase activation of both primary T-cells and antigen-presenting dendritic cells in vitro, indicating that Siglec-7 binds T-cell glycans to regulate intraimmune signaling. Finally, we present evidence that Siglec-7 directly activates signaling pathways in T-cells, suggesting a new biological function for this receptor. These studies conclusively demonstrate the existence of a novel Siglec-7-mediated signaling axis that physiologically regulates T-cell activity. Going forward, our findings have significant implications for the design and implementation of therapies targeting immunoregulatory Siglec receptors.

Microglia Mediate Contact-Independent Neuronal Network Remodeling via Secreted Neuraminidase-3 Associated with Extracellular Vesicles

Neurons communicate with each other through electrochemical transmission at synapses. Microglia, the resident immune cells of the central nervous system, modulate this communication through a variety of contact-dependent and -independent means. Microglial secretion of active sialidase enzymes upon exposure to inflammatory stimuli is one unexplored mechanism of modulation. Recent work from our lab showed that treatment of neurons with bacterial sialidases disrupts neuronal network connectivity. Here, we find that activated microglia secrete neuraminidase-3 (Neu3) associated with fusogenic extracellular vesicles. Furthermore, we show that Neu3 mediates contact-independent disruption of neuronal network synchronicity through neuronal glycocalyx remodeling. We observe that NEU3 is transcriptionally upregulated upon exposure to inflammatory stimuli and that a genetic knockout of NEU3 abrogates the sialidase activity of inflammatory microglial secretions. Moreover, we demonstrate that Neu3 is associated with a subpopulation of extracellular vesicles, possibly exosomes, that are secreted by microglia upon inflammatory insult. Finally, we demonstrate that Neu3 is necessary and sufficient to both desialylate neurons and decrease neuronal network connectivity. These results implicate Neu3 in remodeling of the glycocalyx leading to aberrant network-level activity of neurons, with implications in neuroinflammatory diseases such as Parkinson's disease and Alzheimer's disease.

Comprehensive Overview of Bottom-up Proteomics using Mass Spectrometry

Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods to aid the novice and experienced researcher. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this work to serve as a basic resource for new practitioners in the field of shotgun or bottom-up proteomics.

Elucidating the cellular determinants of targeted membrane protein degradation by lysosome-targeting chimeras

Targeted protein degradation can provide advantages over inhibition approaches in the development of therapeutic strategies. Lysosome-targeting chimeras (LYTACs) harness receptors, such as the cation-independent mannose 6-phosphate receptor (CI-M6PR), to direct extracellular proteins to lysosomes. In this work, we used a genome-wide CRISPR knockout approach to identify modulators of LYTAC-mediated membrane protein degradation in human cells. We found that disrupting retromer genes improved target degradation by reducing LYTAC recycling to the plasma membrane. Neddylated cullin-3 facilitated LYTAC-complex lysosomal maturation and was a predictive marker for LYTAC efficacy. A substantial fraction of cell surface CI-M6PR remains occupied by endogenous M6P-modified glycoproteins. Thus, inhibition of M6P biosynthesis increased the internalization of LYTAC-target complexes. Our findings inform design strategies for next-generation LYTACs and elucidate aspects of cell surface receptor occupancy and trafficking.

Microglia mediate contact-independent neuronal pruning via secreted Neuraminidase-3 associated with extracellular vesicles

Neurons communicate with each other through electrochemical transmission at synapses. Microglia, the resident immune cells of the central nervous system, can prune these synapses through a variety of contact-dependent and -independent means. Microglial secretion of active sialidase enzymes upon exposure to inflammatory stimuli is one unexplored mechanism of pruning. Recent work from our lab showed that treatment of neurons with bacterial sialidases disrupts neuronal network connectivity. Here, we find that activated microglia secrete Neuraminidase-3 (Neu3) associated with fusogenic extracellular vesicles. Furthermore, we show Neu3 mediates contact-independent pruning of neurons and subsequent disruption of neuronal networks through neuronal glycocalyx remodeling. We observe that NEU3 is transcriptionally upregulated upon exposure to inflammatory stimuli, and that a genetic knock-out of NEU3 abrogates the sialidase activity of inflammatory microglial secretions. Moreover, we demonstrate that Neu3 is associated with a subpopulation of extracellular vesicles, possibly exosomes, that are secreted by microglia upon inflammatory insult. Finally, we demonstrate that Neu3 is both necessary and sufficient to both desialylate neurons and decrease neuronal network connectivity. These results implicate Neu3 in remodeling of the glycocalyx leading to aberrant network-level activity of neurons, with implications in neuroinflammatory diseases such as Parkinson's disease and Alzheimer's disease.

The microenvironment dictates glycocalyx construction and immune surveillance

Efforts to identify anti-cancer therapeutics and understand tumor-immune interactions are built with in vitro models that do not match the microenvironmental characteristics of human tissues. Using in vitro models which mimic the physical properties of healthy or cancerous tissues and a physiologically relevant culture medium, we demonstrate that the chemical and physical properties of the microenvironment regulate the composition and topology of the glycocalyx. Remarkably, we find that cancer and age-related changes in the physical properties of the microenvironment are sufficient to adjust immune surveillance via the topology of the glycocalyx, a previously unknown phenomenon observable only with a physiologically relevant culture medium.

Organism-wide, cell-type-specific secretome mapping of exercise training in mice

There is a significant interest in identifying blood-borne factors that mediate tissue crosstalk and function as molecular effectors of physical activity. Although past studies have focused on an individual molecule or cell type, the organism-wide secretome response to physical activity has not been evaluated. Here, we use a cell-type-specific proteomic approach to generate a 21-cell-type, 10-tissue map of exercise training-regulated secretomes in mice. Our dataset identifies >200 exercise training-regulated cell-type-secreted protein pairs, the majority of which have not been previously reported. Pdgfra-cre-labeled secretomes were the most responsive to exercise training. Finally, we show anti-obesity, anti-diabetic, and exercise performance-enhancing activities for proteoforms of intracellular carboxylesterases whose secretion from the liver is induced by exercise training.

Mutational screens highlight glycosylation as a modulator of colony-stimulating factor 3 receptor (CSF3R) activity

The colony-stimulating factor 3 receptor (CSF3R) controls the growth of neutrophils, the most abundant type of white blood cell. In healthy neutrophils, signaling is dependent on CSF3R binding to its ligand, CSF3. A single amino acid mutation in CSF3R, T618I, instead allows for constitutive, ligand-independent cell growth and leads to a rare type of cancer called chronic neutrophilic leukemia. However, the disease mechanism is not well understood. Here, we investigated why this threonine to isoleucine substitution is the predominant mutation in chronic neutrophilic leukemia and how it leads to uncontrolled neutrophil growth. Using protein domain mapping, we demonstrated that the single CSF3R domain containing residue 618 is sufficient for ligand-independent activity. We then applied an unbiased mutational screening strategy focused on this domain and found that activating mutations are enriched at sites normally occupied by asparagine, threonine, and serine residues-the three amino acids which are commonly glycosylated. We confirmed glycosylation at multiple CSF3R residues by mass spectrometry, including the presence of GalNAc and Gal-GalNAc glycans at WT threonine 618. Using the same approach applied to other cell surface receptors, we identified an activating mutation, S489F, in the interleukin-31 receptor alpha chain. Combined, these results suggest a role for glycosylated hotspot residues in regulating receptor signaling, mutation of which can lead to ligand-independent, uncontrolled activity and human disease.

MYC-driven synthesis of Siglec ligands is a glycoimmune checkpoint

The Siglecs (sialic acid-binding immunoglobulin-like lectins) are glycoimmune checkpoint receptors that suppress immune cell activation upon engagement of cognate sialoglycan ligands. The cellular drivers underlying Siglec ligand production on cancer cells are poorly understood. We find the MYC oncogene causally regulates Siglec ligand production to enable tumor immune evasion. A combination of glycomics and RNA-sequencing of mouse tumors revealed the MYC oncogene controls expression of the sialyltransferase St6galnac4 and induces a glycan known as disialyl-T. Using in vivo models and primary human leukemias, we find that disialyl-T functions as a "don't eat me" signal by engaging macrophage Siglec-E in mice or the human ortholog Siglec-7, thereby preventing cancer cell clearance. Combined high expression of MYC and ST6GALNAC4 identifies patients with high-risk cancers and reduced tumor myeloid infiltration. MYC therefore regulates glycosylation to enable tumor immune evasion. We conclude that disialyl-T is a glycoimmune checkpoint ligand. Thus, disialyl-T is a candidate for antibody-based checkpoint blockade, and the disialyl-T synthase ST6GALNAC4 is a potential enzyme target for small molecule-mediated immune therapy.

Deciphering O-glycoprotease substrate preferences with O-Pair Search

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.

Measuring the multifaceted roles of mucin-domain glycoproteins in cancer

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.

The human disease gene LYSET is essential for lysosomal enzyme transport and viral infection

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.

Practical Effects of Intramolecular Hydrogen Rearrangement in Electron Transfer Dissociation-Based Proteomics

Ion-ion reactions are valuable tools in mass-spectrometry-based peptide and protein sequencing. To boost the generation of sequence-informative fragment ions from low charge-density precursors, supplemental activation methods, via vibrational and photoactivation, have become widely adopted. However, long-lived radical peptide cations undergo intramolecular hydrogen atom transfer from c-type ions to z^•-type ions. Here we investigate the degree of hydrogen transfer for thousands of unique peptide cations where electron transfer dissociation (ETD) was performed and was followed by beam-type collisional activation (EThcD), resonant collisional activation (ETcaD), or concurrent infrared photoirradiation (AI-ETD). We report on the precursor charge density and the local amino acid environment surrounding bond cleavage to illustrate the effects of intramolecular hydrogen atom transfer for various precursor ions. Over 30% of fragments from EThcD spectra comprise distorted isotopic distributions, whereas over 20% of fragments from ETcaD have distorted distributions and less than 15% of fragments derived from ETD and AI-ETD reveal distorted isotopic distributions. Both ETcaD and EThcD give a relatively high degree of hydrogen migration, especially when D, G, N, S, and T residues were directly C-terminal to the cleavage site. Whereas all postactivation methods boost the number of c- and z^•-type fragment ions detected, the collision-based approaches produce higher rates of hydrogen migration, yielding fewer spectral identifications when only c- and z^•-type ions are considered. Understanding hydrogen rearrangement between c- and z^•-type ions will facilitate better spectral interpretation.

Protocol for cell type-specific labeling, enrichment, and proteomic profiling of plasma proteins in mice

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).

The CD22-IGF2R interaction is a therapeutic target for microglial lysosome dysfunction in Niemann-Pick type C

Lysosome dysfunction is a shared feature of rare lysosomal storage diseases and common age-related neurodegenerative diseases. Microglia, the brain-resident macrophages, are particularly vulnerable to lysosome dysfunction because of the phagocytic stress of clearing dying neurons, myelin, and debris. CD22 is a negative regulator of microglial homeostasis in the aging mouse brain, and soluble CD22 (sCD22) is increased in the cerebrospinal fluid of patients with Niemann-Pick type C disease (NPC). However, the role of CD22 in the human brain remains unknown. In contrast to previous findings in mice, here, we show that CD22 is expressed by oligodendrocytes in the human brain and binds to sialic acid–dependent ligands on microglia. Using unbiased genetic and proteomic screens, we identify insulin-like growth factor 2 receptor (IGF2R) as the binding partner of sCD22 on human myeloid cells. Targeted truncation of IGF2R revealed that sCD22 docks near critical mannose 6-phosphate–binding domains, where it disrupts lysosomal protein trafficking. Interfering with the sCD22-IGF2R interaction using CD22 blocking antibodies ameliorated lysosome dysfunction in human NPC1 mutant induced pluripotent stem cell–derived microglia-like cells without harming oligodendrocytes in vitro. These findings reinforce the differences between mouse and human microglia and provide a candidate microglia-directed immunotherapeutic to treat NPC.

Synthetic Siglec-9 Agonists Inhibit Neutrophil Activation Associated with COVID-19

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.

Modulation of immune cell reactivity with cis-binding Siglec agonists

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.

A Pragmatic Guide to Enrichment Strategies for Mass Spectrometry-Based Glycoproteomics

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.

Synthetic Siglec-9 Agonists Inhibit Neutrophil Activation Associated with COVID-19

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 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.
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Electron-Based Dissociation Is Needed for O-Glycopeptides Derived from OpeRATOR Proteolysis

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.

Cell type-selective secretome profiling in vivo

Secreted polypeptides are a fundamental biochemical axis of intercellular and endocrine communication. However, a global understanding of 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 increased unconventional secretion of the cytosolic enzyme BHMT. This secretome profiling strategy enables dynamic and cell-type dissection of the plasma proteome and the secreted polypeptides that mediate intercellular signaling.

O-Pair Search with MetaMorpheus for O-glycopeptide characterization

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 .

O-Pair Search with MetaMorpheus for O-glycopeptide characterization

We report O-Pair Search, a new approach to identify O-glycopeptides and localize O-glycosites. Using paired collision- and electron-based dissociation spectra, O-Pair Search identifies O-glycopeptides using 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.

Optical Fiber-Enabled Photoactivation of Peptides and Proteins

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.

Lysosome-targeting chimaeras for degradation of extracellular proteins

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 apolipoprotein E4, 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.

Top-Down Characterization of an Intact Monoclonal Antibody Using Activated Ion Electron Transfer Dissociation

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.

Optimal Dissociation Methods Differ for N- and O-Glycopeptides

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 of 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 in terms of identifications, indicating that ETD-based methods are not required for routine N-glycoproteomics even if they can generate higher quality spectra. 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.

Broad and thematic remodeling of the surfaceome and glycoproteome on isogenic cells transformed with driving proliferative oncogenes

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.

Interactive Peptide Spectral Annotator: A Versatile Web-based Tool for Proteomic Applications

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, whereas 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, whereas the source code and user guides are available at https://github.com/coongroup/IPSA for private hosting or custom implementations.

PKA and HOG signaling contribute separable roles to anaerobic xylose fermentation in yeast engineered for biofuel production

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.

Rewired cellular signaling coordinates sugar and hypoxic responses for anaerobic xylose fermentation in yeast

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.

Top-Down Characterization of Proteins with Intact Disulfide Bonds Using Activated-Ion Electron Transfer Dissociation

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.

The Value of Activated Ion Electron Transfer Dissociation for High-Throughput Top-Down Characterization of Intact Proteins

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.

Improved Precursor Characterization for Data-Dependent Mass Spectrometry

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.

Sequencing Larger Intact Proteins (30-70 kDa) with Activated Ion Electron Transfer Dissociation

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.

Negative Electron Transfer Dissociation Sequencing of Increasingly Sulfated Glycosaminoglycan Oligosaccharides on an Orbitrap Mass Spectrometer

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.

Sulfur Pentafluoride is a Preferred Reagent Cation for Negative Electron Transfer Dissociation

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.

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.

Activated Ion-Electron Transfer Dissociation Enables Comprehensive Top-Down Protein Fragmentation

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.

Implementation of Activated Ion Electron Transfer Dissociation on a Quadrupole-Orbitrap-Linear Ion Trap Hybrid Mass Spectrometer

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.

Multi-omics Evidence for Inheritance of Energy Pathways in Red Blood Cells

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.

Full-Featured Search Algorithm for Negative Electron-Transfer Dissociation

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.

Enhanced Dissociation of Intact Proteins with High Capacity Electron Transfer Dissociation

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.

Mitochondrial protein hyperacetylation in the failing heart

Myocardial fuel and energy metabolic derangements contribute to the pathogenesis of heart failure. Recent evidence implicates posttranslational mechanisms in the energy metabolic disturbances that contribute to the pathogenesis of heart failure. We hypothesized that accumulation of metabolite intermediates of fuel oxidation pathways drives posttranslational modifications of mitochondrial proteins during the development of heart failure. Myocardial acetylproteomics demonstrated extensive mitochondrial protein lysine hyperacetylation in the early stages of heart failure in well-defined mouse models and the in end-stage failing human heart. To determine the functional impact of increased mitochondrial protein acetylation, we focused on succinate dehydrogenase A (SDHA), a critical component of both the tricarboxylic acid (TCA) cycle and respiratory complex II. An acetyl-mimetic mutation targeting an SDHA lysine residue shown to be hyperacetylated in the failing human heart reduced catalytic function and reduced complex II-driven respiration. These results identify alterations in mitochondrial acetyl-CoA homeostasis as a potential driver of the development of energy metabolic derangements that contribute to heart failure.