The 2023 Program

Authors
Jonathan Palmer1,2; Victor Adebomi1,2; Jimmy Eng3 Patrick Salveson2; Ta-Yi Yu2; Stephen Rettie1,2; Gaurav Bhardwaj1,2; Miklos Guttman1

Institutions
1 University of Washington, Department of Medicinal Chemistry, 2University of Washington, Institute of Protein Design, 3University of Washington, Proteomics Resource Center

Abstract
High throughput screening (HTS) is an incredibly powerful tool for drug discovery and development. HTS has enabled researchers to test millions of linear peptides, but applications for cyclized peptides lag behind. Cyclized peptides can offer greater chemical control, metabolic stability, and passive permeability than linear peptides, but have added complexity when sequencing via mass spectrometry. Notably, this increased complexity prevents regular peptide sequencing tools from accurately identifying cyclic peptides. To address this gap, we utilized a novel combination of LC-MSn with an expanded Comet sequencing program to demonstrate that we can use HTS to identify macrocyclic peptides with binding affinity for protein targets.

Authors
James M. Fulcher,1,* Lye Meng Markillie,1 Hugh D. Mitchell, 1 Sarah M. Williams,1 Kristin M. Engbrecht,3 Ronald J. Moore,2 William B. Chrisler,2 Joshua Cantlon-Bruce,4,5 Johannes W. Bagnoli,5 Anjali Seth,5 Ljiljana Paša-Tolić,1 Ying Zhu1,6 *

Institutions
1Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States 2Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States 3Nuclear, Chemistry, and Biology Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States 4Scienion AG, Volmerstraße 7, 12489 Berlin, Germany 5Cellenion SASU, 60 Avenue Rockefeller, Bâtiment BioSerra2, 69008 Lyon, France 6Present address: Department of Microchemistry, Lipidomics and Next Generation Sequencing, Genentech, 1 DNA Way, South San Francisco, 94080, United States *Correspondence: Dr. Ying Zhu, zhu.ying@gene.com and Dr. James M. Fulcher james.fulcher@pnnl.gov

Abstract
Single-cell multiomics provides comprehensive insights into gene regulatory networks, cellular diversity, and temporal dynamics. While tools for co-profiling single-cell genomes, transcriptomes, or epigenomes are available, accessing proteomes in parallel is more challenging. We developed nanoSPLITS (nanodroplet SPlitting for Linked-multimodal Investigations of Trace Samples), an integrated platform that enables global profiling of the transcriptome and proteome from same single-cells using RNA sequencing and mass spectrometry-based proteomics, respectively. nanoSPLITS can precisely quantify over 5000 genes, 2000 proteins, and 140 phosphopeptides per single cell and identify cell-type-specific markers from these modalities. In the context of Cdk1-mediated cell cycle arrest, we demonstrate how nanoSPLITS-based single-cell multiomics can provide comprehensive molecular characterization with insights including covarying protein/gene clusters, unique phosphorylation events, and mitotic pathways.

Authors
Alex Zelter, Michael Riffle, Michael R. Hoopmann, Ellen Riddle, David Shteynberg, Daniel Jaschob, Robert L. Moritz, Michael J. MacCoss, Nina Isoherranen

Institutions
Alex Zelter, Michael Riffle, Daniel Jaschob, Michael J. MacCoss = Department of Genome Sciences, University of Washington; Ellen Riddle and Nina Isoherranen = Department of Pharmaceutics, University of Washington; Michael R. Hoopmann, David Shteynberg, Robert L. Moritz = Institute for Systems Biology, Seattle, WA.

Abstract
Drugs are often metabolized by cytochrome P450 (CYP) enzymes to reactive intermediates that form protein adducts. Adducts can inhibit protein activity, elicit immune responses, and cause life-threatening adverse drug reactions. The modification of cytochrome P450 3A4 (CYP3A4) active site cysteine Cys239 by raloxifene was previously proposed to be responsible for time-dependent inactivation (TDI) of CYP3A4. Previous work detected raloxifene adducts only at Cys239 and thus there were no other candidate sites for inhibition of CYP3A4. In the current work we demonstrate that raloxifene modifies multiple sites on CYP3A4 along with cytochrome P450 reductase and cytochrome b5, proteins also important for CYP3A4 activity. We show that raloxifene modifies multiple sites on cytochrome P450 2C9 (CYP2C9). In contrast to CYP3A4, raloxifene does not inactivate CYP2C9. We therefore hypothesize that determination of both the location and abundance of raloxifene adducts is important in understanding the effect of drug-protein adducts on enzyme activity. Here we present methods to discover and quantify drug-protein adducts by bottom-up liquid chromatography/mass spectrometry and discuss the challenges associated with these methods, which are necessarily applied to peptides with rare modifications. Low abundance modifications present challenges at all stages of the methodological pipeline that are not as impactful in the study of higher abundance targets. Such challenges are present in sample workup; discovery of modifications by database searching and assignment of error rates by post processing tools; and the quantification of drug modified peptides. To study the effect of drug-protein adducts on enzyme activity these challenges will have to be overcome.

Authors
Chris Hsu, Lilian R Heil, Philip Remes, Jesse Canterbury, Ping Yip, Christine Wu, Mariya T. Sweetwyne, Michael J. MacCoss

Institutions
University of Washington, Thermo Fisher Scientific (San Jose)

Abstract
The single-cell proteomics field aims to provide insights into complex biological changes, such as spatial or cellular heterogeneity, that would otherwise be lost in aggregated, bulk sample experiments. Quantification at the single-cell level or very low amounts of input material remains a challenge because protein loss from surface adsorption needs to be minimized during sample preparation and instrument sensitivity needs to be increased for peptide quantification. We aim to improve sample recovery by including a carrier proteome prior to adding in the low input sample, and we aim to increase instrument sensitivity by acquiring MS/MS data using a massively parallel targeted method coupled with a linear ion trap as a detector. With our method, we can quantify 2,200 peptides (or 800 proteins) from individually prepped 10ng samples with great precision and reproducibility. Our data highlights the quantitative performance of this workflow by demonstrating both technical reproducibility and linearity for low input samples.

Authors
Josh Eckels1; Sweta Jewargikar2; Wendy Innis2; Ankur Juneja1; Nicholas Shulman3; Vagisha Sharma3; Michael J. MacCoss3; Brendan X. MacLean3; and the Panorama Partners Program

Institutions
1LabKey, San Diego, CA; 2LabKey, Seattle, WA; 3University of Washington, Seattle, WA;

Abstract
Panorama is a web-based data management system for targeted mass spectrometry. It integrates closely with Skyline, a free, open source targeted mass spec analysis tool. Panorama’s system suitability tools automatically report on instrument health and identify problems. Features for multi-attribute method (MAM) analysis make characterizing antibodies across samples easy. For researchers doing proteomics, it also visualizes peptide and protein sequence data. Free cloud-based projects are available to everyone on PanoramaWeb.org. Panorama uses a relational database to store targeted mass spectrometry data, importing data from Skyline’s XML file. Tight integration between Panorama and Skyline ensures complementary and compatible feature sets. Panorama’s QC folders offer user-friendly, web-based visualizations and reporting of system suitability data, storing data from each mass spectrometer in a separate folder. AutoQC, a utility that monitors for newly acquired raw data files, automates the otherwise tedious process of adding new data. Panorama also offers a growing assortment of reporting and visualization tools, both available out-of-the-box, and for customization. Since Panorama first implemented system suitability monitoring in 2014, users have created more than 1,500 QC folders on PanoramaWeb.org. Of those, more than 300 folders have accumulated 100 or more samples worth of data and many have thousands of acquired files. Because statistical process controls are not necessarily intuitive to mass spectrometrists, Panorama has recently added new visualizations that show trailing mean and coefficient of variation values for its full set of metrics which may feel more intuitive to everyday users. They join the Levey-Jennings, moving range, and cumulative sum plots. Other improvements to all of Panorama’s system suitability plots help reduce visual clutter from a great deal of historical data. Users doing Multi-Attribute Method (MAM) analyses can utilize additional built-in reporting to monitor post-translational modifications and assess risk based on criteria such as complementarity-determining regions (CDRs) and sample metadata. Additionally, Panorama now supports visualization of cross-linked peptides to easily monitor peptides with disulfide bonds and other more complex PTMs. Finally, Panorama benefits from Skyline’s recent addition of tracking protein groups, capturing the full list of proteins to which a set of peptides may belong. Panorama’s protein/peptide sequence view now also displays intensity and confidence score data, either summarized across multiple samples or one sample at a time. As of February 2023, more than 650 labs are using Panorama projects, free of charge, to manage targeted mass spectrometry assays on http://panoramaweb.org, a server hosted by the MacCoss lab at the University of Washington. Additionally, major pharmaceutical companies and other organizations have deployed their own in-house installations of Panorama.

Authors
Yuan Feng, Benjamin P. Zercher, Matthew F. Bush*

Institutions
University of Washington, Department of Chemistry, Box 351700, Seattle, WA, 98115

Abstract
Introduction Analogous to the advantages of tandem mass spectrometry (MS) relative to single-stage MS, multidimensional ion mobility (IM) can increase the information content of IM experiments by isolating subpopulations of ions for further analysis. Electrostatic ion mobility (IM) enables the direct determination of mobilities without calibration, but using traditional implementations, increasing the number of dimensions also requires corresponding increases in applied potentials. One solution to this challenge is traveling-wave IM, which has been used to enable long separation pathlengths and multidimensional separations with relatively low potentials relative to electrostatic IM. Here, we present an alternative strategy that reduces the magnitude of potentials required for electrostatic IM by dynamically resetting the potential of ions between dimensions of IM.
Methods Ubiquitin, concanavalin A, and cytochrome c were purchased and prepared in aqueous 200 mM ammonium acetate adjusted to pH 7.0. Denatured cytochrome c samples were prepared by solvent exchanging proteins using size-exclusion spin columns that had been equilibrated with three washes of 0.1% acetic acid. These experiments were performed on a Structures for Lossless Ion Manipulations (SLIM) architecture IM instrument that uses electrostatic drift fields to separate ions. Ion trapping is enabled by biasing adjacent modules to create a potential well that we call a “junction trap”. The potentials that comprise the junction trap are modulated by applying time-dependent voltage programs. Preliminary In tandem IM experiments, ion packets were generated on the first module (1M) and separated in the first dimension of IM (1D) before the time-dependent selection of a specific charge state at 7M. Selected ions were accumulated in a junction trap for a short time (~10 ms) prior to the 2D. In potential resetting experiments, the 2D region was held at ground while ions were separated and selected in the 1D region. The selected ions were accumulated in a junction trap between the 1D and 2D at near ground potential. After accumulation, the potentials of the junction trap and the input of the 2D were raised in 5 V increments every 125 µs. The ions were then released from the junction trap into the 2D. For comparison, ions were also analyzed in tandem IM experiments that used the same drift fields, but applied using higher, static drift potentials. Ion lifetimes, as monitored by the depletion of the precursor, were the same in both experiments. The well-overlaid 2D arrival time distributions and mass spectra from each experiment suggest that potential resetting does not perturb trapped ions. We then isolated three subpopulations of 7+ cytochrome c, reset their potentials, and demonstrated that all subpopulations remain resolved in the 2D, which suggests that potential resetting of ions does not induce conformational changes that significantly change the arrival time of ions.

Authors
Mukul K. Midha, Charu Kapil, Michal Maes, David H. Baxter, Seamus R. Morrone, Timm J. Prokop, Robert L. Moritz

Institutions
Institute for Systems Biology, Seattle, WA 98109

Abstract
Introduction Nano-flow chromatography-tandem mass spectrometer (nLC-MS/MS) is a popular choice in proteome research as it provided high-sensitivity analysis with minimal sample usage, but its quantitative proteomics applications become restricted by low analytical throughput, and low robustness. To circumvent this limitation, we describe the performance of the new Vacuum Insulated Probe Heated ElectroSpray Ionization source (VIP-HESI) coupled to the Bruker timsTOF mass spectrometer and show it enhances micro-spray flow rate chromatography signals in comparison to nanospray source conditions using the CaptiveSpray (CS) and ElectroSpray Ionization (ESI) sources. In addition, using a 0.5 x 200mm and 1 × 150 mm columns, achieved excellent reproducibility of chromatographic retention time, coefficient of variation, and precision quantification using data from un-depleted mouse plasma, HeLa and K562 digest peptide samples.
Methods PepCalMix peptides with seven different concentration points to cover a range of 12.5fmol to 800fmol were measured to assess linear response using VIP-HESI source and compared to CaptiveSpray and ElectroSpray Ionization sources. Using un-depleted mouse plasma sample, different injection amounts of 0.4μg at 1μL/min with CaptiveSpray were compared to 2μg, 4μg, 10μg, 20μg, and 40μg injection amounts at 40μL/min coupled with VIP-HESI source. Lastly, we also assess the performance of VIP-HESI microflow setup in a slice-PASEF mode for analysis of low sample amounts. For dia-PASEF runs and slice-pasef, Spectronaut 16.0 and DIA-NN 1.8.2 tools respectively were used to identifications filtered with a q-value of <0.01 and MS2 ion peak areas of quantified peptides were summed to estimate the protein quantification.
Preliminary Data We determined excellent linear gain in the total protein quantity as we increased the PepCalMix concentration with the R-Squared (R²) of more than 99% and linear response enabled excellent comparison between the CS, ESI, and VIP-HESI sources. VIP-HESI source performed better than than ESI by providing 50% more PepCalMix quantities and 30% more abundances than CS after injecting thirty-two times more injection amounts. Using mouse undepleted plasma samples, DIA-MS analysis using Spectronaut software resulted in the cumulative identification of 5,795 - 8,610 precursors and 493 - 802 unique proteins at <1% protein FDR across the different injection amounts. Interestingly, injecting fifty times (20μg) more sample amounts (with 40 times more sample dilution) using VIP-HESI, outperforms CS 0.4μg measurement by identifying 3% more precursors and 12% more proteins. Next, on evaluating the reproducibility of quantitative measurements, VIP-HESI 20μg measurement, a total of 7,074 precursors were quantified by both biological replicates with a high positive correlation (r2 = 0.94). Whereas with CS 0.4μg replicate measurements, 6,387 precursors were quantified with a positive correlation (r2 = 0.89), indicating more variation was observed with nanoflow rates, compared to VIP-HESI-microflow runs. Subsequently, we observed similar median number of data points (5) measured across the elution profiles and similar base peak widths (0.16 and 0.14 minutes) in both VIP-HESI 20μg and CS 0.4μg measurements, signifying that VIP-HESI provides an optimal quantification of an identified precursor using spectronaut analysis. For slice-pasef experiment, DIA-NN tool with different HeLa sample amounts resulted in the identification of 6,592 - 49,130 precursors at <1% precursor FDR and 1,769 - 6,343 proteins at <1% protein FDR. For 10ng sample injection amounts, slice-PASEF yielded 63% more precursors and 38% more protein groups than the VIP-HESI source setup, demonstrating significant increase in the number of precursor and protein groups, especially with low injection amount measurements.
Novel Aspect VIP-HESI source with improved analytical setup capable of highly reproducible chromatography that can accurately quantify with a wider proteome coverage.

Authors
Sophie Moggridge, Ricard Rodriguez-Mias, Kyle Hess, Judit Villén

Institutions
Center for the Multiplexed Assessment of Phenotype, Department of Genome Sciences, University of Washington, Seattle, USA

Abstract
Protein variants arising from single amino acid substitutions contribute to many human diseases. These substitutions can affect protein properties such as structure, stability, activity, subcellular localization, and interactions with other biomolecules. Previous work has focused on characterizing the effects of substitutions using classic biochemical assays on individual protein variants. Here we streamline this process by coupling biochemical assays to mass spectrometry detection, enabling the characterization of many protein variants in a single experiment. We selected 13 previously characterized missense variants of PGM1, conducted protein solubility and thermal stability assays in a pooled format and compared our results to previously published data using purified variants. Our pooled mass spectrometry-based assay successfully recapitulated the results from individually assayed variants and achieved improved resolution and variant library coverage. Scaling these assays to thousands of variants will greatly enhance our understanding of how single amino acid substitutions affect protein function and will contribute to better classifying and understanding variants.

Authors
Matthew D. Berg(1), Ricard A. Rodriguez-Mias(1) and Judit Villén(1)

Institutions
(1) Department of Genome Sciences, University of Washington, Seattle, WA, USA

Abstract
While DNA sequencing has identified millions of natural genetic variants that alter protein sequence, determining the functional impact of these variants remains challenging. Traditional mutagenic approaches are not scalable for millions of variants and high-throughput approaches such as deep mutational scanning are limited to investigating one protein per experiment. Recently, our lab established MiRo – a high-throughput proteomic technology to enable functional annotation of thousands of missense mutations across entire proteomes. In this approach, stochastic errors in protein synthesis are induced to create variants across all expressed proteins within a cell. Variants are subject to biochemical selections that probe general protein properties like solubility, thermal stability, ligand binding, protein-protein interactions and posttranslational modifications. After selection, variants are quantified by mass spectrometry to determine the functional impact of each mutation on the measured property. Previously, non-canonical amino acids that are mis-incorporated in place of one of the 20 canonical amino acids were used to create protein variants. In this work, we expand the MiRo approach to determine the impact of canonical amino acid substitutions by engineering alanine tRNAs that mis-incorporate alanine at non-alanine positions. By mutating the anticodon of tRNAAla and expressing these engineered tRNAs in yeast, we achieve alanine mis-incorporation at nearly all non-alanine codons. We identify hundreds to thousands of mis-incorporation events with each tRNA variant using mass spectrometry. We then apply thermal proteome profiling to the alanine-substituted proteomes to determine the impact of individual substitutions on protein thermal stability and identify functionally important residues and protein regions. This work represents the first proteome-wide alanine scan and provides insight into various aspects of protein biology including the structural and functional context underlying mutational sensitivity.

Authors
Ellen Riddle, Alex Zelter, and Nina Isoherranen

Institutions
University of Washington, Department of Pharmaceutics (Ellen Riddle and Dr. Nina Isoherranen); University of Washington, Department of Biochemistry (Dr. Alex Zelter)

Abstract
A major concern for drug-drug interactions (DDI) includes the irreversible inhibition of cytochrome P450 enzymes (CYPs). Time dependent inhibition (TDI) may occur via adduction of CYP enzymes by reactive drug metabolites. Traditional methods to detect and identify reactive metabolites during drug development include glutathione trapping, radiolabeled compounds, or metabolite identification; none of which yield information regarding the precise proteins and amino acids that are adducted and thus cannot be used to study the impact of adduct location on TDI. We hypothesize that TDI via adduct formation is a function of the specific placement of the adduct and the adduct formation kinetics. Therefore, the goal of this project is to establish a relationship between protein inactivation and adduct formation kinetics. We tested our hypothesis using a combination of in vitro incubations and proteomic methods with CYP2C9 as a model enzyme, and two model compounds: tienilic acid, a known CYP2C9 TDI, and raloxifene, which does not inhibit CYP2C9 in a time-dependent manner. Both raloxifene and tienilic acid are known substrates of CYP2C9 that form reactive metabolites. In vitro IC50 shift experiments confirmed that tienilic acid, but not raloxifene, inhibits CYP2C9 in a time-dependent manner. Tienilic acid and raloxifene treated CYP2C9 reconstituted with P450 reductase were then analyzed using high-resolution mass spectrometry, and subsequently searched using Magnum, an open mass searching algorithm, which identified the adduct masses and the specific adducted peptides of tienilic acid and raloxifene treated CYP2C9. Two treatment specific significant modifications were identified on cysteines in CYP2C9 following CYP2C9 incubation with tienilic acid; R.YIDLLPTSLPHAVTCDIK.F was found to be modified by +329.96 Da, and R.CLVEELR.K was found to be modified by +349.94 Da. The MS1 scan of the +329.96 Da modified R.YIDLLPTSLPHAVTCDIK.F shows a clear chlorine isotope pattern from the tienilic acid derived adduct, and this is reflected in several y-ions in the MS2. Additionally, +329.96 Da adduct on R.YIDLLPTSLPHAVTCDIK.F is present in samples digested with and without reduction and alkylation, whereas the +349.94 Da adduct on R.CLVEELR.K is only present in samples digested without reduction and alkylation. Furthermore, a shift in retention time is present for all adducted peptides compared to the non-adducted counterpart. These adducts were then quantified by DIA analysis in Skyline. For raloxifene treated CYP2C9 purified protein, +471.15 Da was identified as a treatment specific significant modification and the +471.15 Da modification was found on multiple cysteine and tyrosine residues in CYP2C9, despite the lack of TDI. These findings suggest that although adducts of the inhibitors tested are found on CYP2C9, inactivation is dependent on both the localization and abundance of adducts present. Overall, a definitive characterization of the specific adducts formed is necessary to understand the functional consequences of protein adduction.

Authors
Nicholas Day, Xiaolu Li, Matthew Gaffrey, James Sanford, Tyler Sagendorf, Kwame Attah, Sue Bodine, Josh Adkins, Wei-Jun Qian, and the MoTrPAC consortium.

Institutions
Pacific Northwest National Laboratory, University of Iowa

Abstract
The Molecular Transducers of Physical Activity consortium (MoTrPAC) aims to identify the underlying molecular changes that occur in response to physical activity to understand how exercise improves health. Among these molecular changes are redox-based post-translational modification of protein Cysteine thiol groups by molecules such as reactive oxygen species (ROS). Quantitative measurement of reversible protein thiol oxidation enables a better understanding of the redox environment and helps to identify what protein thiols are susceptible to oxidative modifications. Herein, we investigate the temporal responses of thiol redox proteome in rat muscle tissue derived from an endurance exercise training study. 60 lateral gastrocnemius muscle tissue samples were collected from male or female rats assigned to sedentary (Control) or exercise (1, 2, 4, or 8 weeks) groups. The samples were processed using an integrated bottom-up global and ‘total oxidation’ redox proteomics workflow that incorporated multiplexed isobaric labeling and enrichment using a thiol affinity resin. Due to the presence of highly abundant proteins in muscle tissue, we implemented our recently developed deep redox profiling workflow to improve coverage that surpasses other recent studies. The peptides were analyzed using a Thermo Scientific Q Exactive HFX mass spectrometer and identified using MSGF Plus. Statistical analysis was performed using the PlexedPiper pipeline R package. Thiol oxidation of 17,201 Cysteine (Cys) sites were quantified, corresponding to 5242 proteins. Compared to the control group, significant changes in thiol oxidation (redox) are observed across all exercise groups for both sexes. Female rats show more dynamic changes in Cys oxidation compared to male rats during the first 4 weeks of exercise. However, by the 8th week of exercise, male rats show a marked increase in the number of significantly oxidized sites compared to male rats at earlier timepoints and female rats at all timepoints. Significantly changing Cys oxidation in male rats is predominantly associated with bioenergetic pathways. On the other hand, significantly changing Cys sites in female rats are involved in processes that control muscle function and quality. This distinction suggests that exercise training may have sex-specific effects on the physiology of skeletal muscle. Ongoing work will integrate redox changes with those observed with phosphorylation or metabolites, where data are already available from MoTrPAC.

Authors
Alex Zelter, King CB Yabut, Benjamin Zercher, Alice Martynova Michael J MacCoss, Matthew F. Bush, Nina Isoherranen

Institutions
Departments of Genome Sciences, Pharmaceutics and Chemistry, University of Washington

Abstract
4-Hydroxynonenal (4HNE) is a well-known lipid peroxidation product that modifies proteins via Michael addition (cysteine, histidine and lysine) and a Schiff base (lysines) mechanism. These covalent modifications have been proposed to contribute to the initiation and progression of multiple diseases associated with oxidative stress. However, the modifications formed by 4HNE are typically low abundance and difficult to identify and quantify from complex samples. The stoichiometry and kinetics of specific modifications formed by 4HNE are poorly understood and the quantitative relationships between modification and decreased protein function have not been defined. We used a combination of mass spectrometry techniques to determine the relationship between 4HNE mediated modifications in cellular retinoic acid binding protein 1 (CRABP1) and its function.
CRABP1 was expressed and purified from E. coli and treated with increasing concentrations of 4HNE to generate 4HNE-modified protein. 4HNE-modified CRABP1 was analyzed via intact protein mass spectrometry to determine the number of 4HNE modifications formed per CRABP1 protein and to estimate the fraction of the total CRABP1 modified by 4HNE with increasing concentrations of 4HNE. Treated and untreated CRABP1 protein was digested with trypsin and the 4HNE modified residues and the specific modification masses determined via shotgun proteomics. The relative abundance of the modifications at specific residues was quantified using DIA. Intact protein MS showed that following a one-hour incubation of CRABP1 with 10- or 25-fold molar excess of 4HNE, only 15-20% of CRABP1 was modified by 4HNE.
The major CRABP1-4HNE product contained just a single modification of 156 Da. This mass corresponds to the Michael addition of 4HNE to cysteine, histidine or lysine. To determine the specific locations of 4HNE modifications within the protein we performed tryptic digestion and bottom-up proteomics. 4HNE modifications were found in six of the 12 modifiable amino acids in CRABP1. Both histidines (H40 and H94) and two of the three cysteines (C95 and C129) were found modified by 4HNE. In addition, the peptides containing C95 and C129 were completely alkylated in untreated samples, while the presence of peptides without alkylation of C95 and C129 increased considerably when samples were treated with 4HNE. Of the seven lysines, only K38 and K92 were modified, consistent with the predicted lowest reactivity of lysine with 4HNE. Both the intact protein and bottom-up MS analysis supported 156 Da being the predominant modification by 4HNE. The only Schiff base modification (138 Da) found was at K92 but even in this residue the 156 Da modification was more abundant. This modification also resulted in a missed cleavage for that tryptic site. No significant decrease in the abundance of any of the unmodified peptides was observed, which highlights the limitations of using the depletion of unmodified peptides as a proxy for quantifying protein modifications. Taken together these data show that the relatively low abundance of 4HNE modified peptides in shotgun proteomics is due to incomplete modifications of the specific residues in the target protein and the distribution of modifications amongst different modifiable residues.

Authors
Alexis Chang, Mario Leutert, Ricard A. Rodriguez-Mias, Judit Villen

Institutions
Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States

Abstract
Phosphotyrosine (pY) enrichment is critical for expanding the fundamental and clinical understanding of cellular signaling by mass spectrometry-based proteomics. However, current pY enrichment methods exhibit a high cost per sample and limited reproducibility due to expensive affinity reagents and manual processing. We present rapid-robotic phosphotyrosine proteomics (R2-pY), which uses a magnetic particle processor and pY superbinders or antibodies. R2-pY can handle up to 96 samples in parallel, requires 2 days to go from cell lysate to mass spectrometry injections, and results in global proteomic, phosphoproteomic, and tyrosine-specific phosphoproteomic samples. We benchmark the method on HeLa cells stimulated with pervanadate and serum and report over 4000 unique pY sites from 1 mg of peptide input, strong reproducibility between replicates, and phosphopeptide enrichment efficiencies above 99%. R2-pY extends our previously reported R2-P2 proteomic and global phosphoproteomic sample preparation framework, opening the door to large-scale studies of pY signaling in concert with global proteome and phosphoproteome profiling.

Authors
Aprajita Yadav1, Alex Zelter2, Nina Isoherranen1

Institutions
1. Department of Pharmaceutics 2. Department of Genome Sciences, University of Washington, Seattle, WA

Abstract
Retinol binding protein 4 (RBP4) is a 21 kDa protein that forms a tetramer with transthyretin (TTR), a 55 kDa homotetrameric protein, and binds retinol in blood with high affinity. Multiple studies in humans have shown an association between increased serum levels of retinol binding protein (RBP4) and obesity, diabetes, insulin resistance, triglyceride levels, cardiovascular disease, and chronic kidney disease1. However, RBP4 and TTR concentrations have typically been measured by western blots, or using enzyme linked immunoassays (ELISA) kits, which have limited dynamic range, can be variable between labs or kits, and response can be altered by disease states, matrix effects or anticoagulant2,3.
LC-MS/MS based protein quantification has been developed as an alternative strategy for ELISAs and western blotting, but plasma proteomic analysis can be confounded by the complexity of the human plasma proteome, abundance of albumin and IgG, and the presence of protease inhibitors which can affect tryptic digest.
We hypothesized that LC-MS/MS quantification of RBP4 and TTR in plasma would provide an accurate, rigorous, and reproducible method to determine the absolute concentrations of RBP4 and TTR in human plasma/serum in patients with different disease states and allow quantification of RBP4-retinol and RBP4-TTR concentration ratios. A novel, quantitative mass spectrometry based analytical method was developed and validated to allow for simultaneous targeted quantification of RBP4 and TTR in human plasma.
Surrogate peptides for proteomic analysis of RBP4 and TTR were selected from in silico analysis and monitored following tryptic digest of purified protein standards and plasma samples. To address the phenomena of digestion quality, missed cleavages, ragged ends and variable modifications present, shotgun proteomics was employed to characterize purified RBP4 standards expressed from multiple cell systems and RBP4 and TTR in human plasma. This analysis showed the presence of peptides incorporating missed cleavages in addition to the expected fully cleaved peptides. Division of signal between multiple peptide species is an important consideration when developing quantitative assays. Yeast enolase was added as a process control and the effectiveness of reducing signal variability by normalizing to this process control was assessed. Multiple internal standards, FSGTWYAMAK[13C615N2] and YWGVASF[13C915N]LQK for RBP4 and GSPAINVAVHVFR[13C615N4] for TTR, were used to determine quantitative variability across peptides from the same protein. A set of plasma samples was quantified multiple times to address technical digest variability, inter-day digest variability, freeze-thaw stability, and autosampler stability. Instrument response linearity and matrix effects for different peptides was also assessed. Instrument variability was observed to range from 5.4 - 7.3% for different enolase peptides, digestion variability added 8 – 32.5% variation which was peptide dependent.
Broadly, these results highlight the benefits of robust method development to account for incomplete digestion, efficiency of digestion with a process control and selecting appropriate normalization criteria for accurate quantification. The developed assay will provide an important new tool for understanding the validity of RBP4 and TTR as disease biomarkers.
1. Blaner, W. S. Vitamin A signaling and homeostasis in obesity, diabetes, and metabolic disorders. Pharmacology and Therapeutics vol. 197 153–178 (2019). 2. Hoofnagle, A. N. & Wener, M. H. The fundamental flaws of immunoassays and potential solutions using tandem mass spectrometry. Journal of Immunological Methods vol. 347 3–11 (2009). 3. Graham, T. E., Wason, C. J., Blüher, M. & Kahn, B. B. Shortcomings in methodology complicate measurements of serum retinol binding protein (RBP4) in insulin-resistant human subjects. Diabetologia 50, 814–823 (2007).

Authors
Theresa A. Gozzo, May A. Constabel, Matthew F. Bush

Institutions
Department of Chemistry, University of Washington, Box 351700, Seattle, WA, 98115

Abstract
Introduction Monoclonal antibodies form the basis of a swiftly growing class of therapeutics. In contrast to traditional small molecule drugs, antibodies are large, flexible proteins generated from a biological source. Their heterogeneity and complexity pose challenges to study via traditional structural biology techniques; therefore, gas-phase approaches have been leveraged to characterize and differentiate them. Here, we present two approaches that can help characterize the structures of antibodies as well as distinguish similar antibodies from each other. First, we use a combination of solution conditions, charge reduction via Cation-to-Anion Proton-Transfer Reactions (CAPTR), and energy-dependent ion mobility-mass spectrometry (IM-MS) experiments to distinguish between IgG1 and IgG4. Second, we introduce online, temperature-controlled disulfide reduction with potential for rapid characterization of IgG disulfide bond connectivity.
Methods IgG1κ and IgG4κ (human myeloma) were purchased from Sigma-Aldrich. For native-like conditions, samples were exchanged into 200 mM ammonium acetate with Micro Bio-Spin 6 columns (Bio-Rad). For denaturing conditions, samples were instead exchanged into 0.1% acetic acid. All experiments were conducted on a Synapt G2 HDMS modified with a glow-discharge ionization source and a radio-frequency confining drift cell. To perform CAPTR, perfluoro-1,3-dimethylcyclohexane (PDCH, Sigma-Aldrich) was introduced as a vapor. The monoanion [PDCH–F]– was reacted with cations of IgG1 and IgG4 in the trap cell. IM arrival-time distributions were measured in helium. For online disulfide reduction, experiments were performed using a home-built programmable, temperature-controlled nanoelectrospray (ptESI) source, and MS data were collected on a Waters Cyclic IM-MS instrument. DTT was added to native-like buffer exchanged IgG samples in various concentrations, and mass spectra were collected continuously during temperature programs consisting of a ramp from 30 °C to a higher temperature (varied) and back to 30 °C.
Preliminary data ΩHe values of native-like IgG1 and IgG4 ions and their charge-reduced CAPTR products depend weakly on charge state, a trend that is consistent with results from CAPTR of other native-like protein ions. Conversely, ions generated from denaturing solution conditions and their charge-reduced products exhibit ΩHe values that depend strongly on charge state. Taken together, these results contribute to the body of work suggesting that protein ions with lower charge densities have Ω values that depend less on charge state than protein ions with higher charge densities. Pre-CAPTR activation was applied to ions from native-like solutions by increasing the sampling cone voltage in the atmospheric-pressure interface. When the Ω distributions were quantitively compared, charge-reduced CAPTR products had more distinguishable apparent Ω distributions than those of the precursor charge states at most pre-CAPTR activation voltages. Relative to collision-induced unfolding (CIU) of the precursor ions, the Ω distributions of charge-reduced products were also more distinguishable.
ptESI enabled the online disulfide reduction of IgGs, as monitored by shifts in m/z. We hypothesize that the pattern in which heavy and light chains become freed from intact IgGs will depend strongly on both disulfide bond connectivity and other aspects of thermal stability in solution, which will facilitate the differentiation of similar antibodies. This hypothesis and the integration of IM data will be the subject of ongoing investigation.

Authors
Vorauer, Clint; Fries, Bettina; Guttman, Miklos

Institutions
University of Washington, Department of Medicinal Chemistry; Stony Brook University

Abstract
Staphylococcal enterotoxin B (SEB) is a small, secreted protein that causes food poisoning-like symptoms and can be lethal at microgram amounts. SEB elicits a profound immune response via the bridging of major histocompatibility complex class II (MHCII) molecules on antigen presenting cells with T-cell receptors (TCR). Several monoclonal antibodies (mAbs) have been identified as capable of neutralizing SEB. Using structural mass spectrometry, we successfully mapped the epitopes of several neutralizing antibodies and determined allosteric effects that contribute to the efficacy of select mAbs. Having established a robust approach for tracking mAb-SEB interactions, we examined the interactions within polyclonal sera for understanding antibody responses to SEB and their resulting protective efficacy.
Hydrogen Deuterium Exchange coupled to Mass Spectrometry (HDX-MS) was used to map the epitopes of known neutralizing antibodies against SEB. To study the response of polyclonal sera against SEB, we developed an HDX-MS method that assays protein interacting with a mixture of different species. Uniquely, the technique assays the same immobilized SEB that is used to bind to species in complex serum, thus interrogating the natural, unpurified, and most biologically relevant solution.
It was determined that that sera capable of neutralizing SEB focused on select epitopes on the structure of SEB. We observed differential uptake of deuterium across the structure of SEB after exposure to neutralizing antibodies relative to a control condition, which indicated regions of preferred binding from the serum condition. Across a panel of sera, we determined that immunofocusing occurred on different epitopes depending on species. This assay presents a new way of examining protein interactions in complex solutions and provides a novel way to test vaccine efficacy.

Authors
Christine C Wu (1,*), Kristine A Tsantilas (1, **), Jea Park (1), Deanna L Plubell (1), Previn Naicker (2), Ireshyn Govender (2), Sindisiwe Buthelezi (2), Stoyan Stoychev (3), Justin Jordaan (3), Gennifer E Merrihew (1), Eric Huang (1), Edward D Parker (4), Michael Riffle (5), Andrew N Hoofnagle (6), Michael J MacCoss (1,*)

Institutions
1 - Department of Genome Sciences, University of Washington, Seattle, WA, USA 2 - CSIR, Pretoria, South Africa 3 - ReSyn Biosciences, Gauteng, South Africa 4 - Vision Core, Department of Ophthalmology, University of Washington, Seattle, WA, USA 5 - Department of Biochemistry, University of Washington, Seattle, WA, USA 6 - Department of Lab Medicine and Pathology, University of Washington, Seattle, WA, USA * Corresponding Authors ** Presenting author

Abstract
Extracellular vesicles (EVs) are membrane-bound particles that carry critical biological cargo throughout the body – including in blood. The particles circulating in plasma including EVs like microvesicles and exosomes along with apoptotic bodies represent ~1-2% of the total protein composition. Analysis of this enriched membrane particle fraction by mass spectrometry is effectively a “liquid biopsy” that significantly improves the dynamic range of the proteins measurable in plasma. We have developed a one-step enrichment strategy (Mag-Net) using strong-anion exchange magnetic microparticles (MagReSyn® SAX, ReSyn Biosciences) to capture membrane-bound particles from plasma on a Kingfisher system (Thermo). After capture, the particles can either be eluted and their composition characterized by electron microscopy or particle counting, or they may be carried through SP3 protein digestion. Peptides are collected and analyzed with a quantitative liquid chromatography mass spectrometry strategy using data independent acquisition. The Mag-Net method is robust, reproducible, hemolysis compatible, inexpensive, requires less than 100 μL plasma input, and translates across species.
In human plasma using an Orbitrap EclipseTM TribridTM (Thermo) coupled to a VanquishTM Neo UHPLC (Thermo), we regularly identify more than 4,000 proteins and 30,000 peptides. We consistently and quantitatively capture known protein markers of exosomes and microvesicles including CD9, CD40, CD61, PDCD6IP, NCAM1, CD147, and flotillin are enriched in Mag-Net preparations relative to unfractionated plasma by >70 fold. Abundant plasma proteins such as albumin, transferrin, alpha-2-macroglobulin, alpha-1-antitrypsin, ApoA1, and ApoB are depleted relative to unfractionated plasma. The size distribution of the membrane particles was 50-500 nm as measured by Nanosight particle tracking, which is within literature expectations for a mixed population of EVs. Lipid bilayers and similar sizing of the membrane particles was observed by TEM.
Despite its many positive attributes, the substantial proteome dynamic range of plasma often necessitates depletion of abundant proteins or affinity reagents to enrich specific analytes of biological interest. However, depletion and affinity reagents are often unavailable for model organisms, which are commonly utilized in geroscience studies to characterize the basic biology of aging or improve our understanding of age-related disease. Plasma EVs were isolated using Mag-Net from three vertebrates of varied genetics, environment, and lifespan: humans, laboratory mice, and companion dogs. We found that Mag-Net captures membrane-bound particles from mouse and dog plasma of similar size distributions to humans (and as expected for exosomes and microvesicles) by Nanosight particle tracking. Samples were also run on an Orbitrap ExplorisTM 480 (Thermo) coupled to an EASY-nLCTM 1200 (Thermo). Using Mag-Net in humans, mice, and dogs, respectively, we found 3445, 2593, and 1845 proteins derived from 15613, 10605, and 5795 unique peptides. This was inclusive of similar exosome and microvesicle proteins (CD9, CD61, CD44, FLOT1, FLOT2 NCAM1, and CD147), neurological/platelet-derived proteins (amyloid beta precursor protein, clusterin), and common membrane proteins (calreticulin, cadherins, integrins, tetraspanins). Abundant plasma proteins that are commonly depleted in commercial columns using affinity reagents (including but not limited to albumin, transferrin, alpha-2-macroglobulin, alpha-1-antitrypsin, APOA1, APOB, C3) were reduced to similar magnitude in mouse and dog plasma.
Single step enrichment of membrane particles using Mag-Net has the potential to drive innovation in basic and translational science by facilitating in-depth quantification of the plasma proteome in humans and model organisms. Future work will use this simple and fast method to focus on interspecies characterization of disease etiology and aging biology.

Authors
Charlie Mundorff1, Michael Watson1, Lauren Carter2, Malika Hale3, Adian Valdez2, Marion Pepper3, Neil King2, Miklos Guttman1

Institutions
1Department of Medicinal Chemistry, University of Washington, Seattle WA 98195 2Department of Biochemistry, University of Washington, Seattle WA 98195 3Department of Immunology, University of Washington, Seattle WA 98195

Abstract
Introduction 118/120: IgM antibodies comprise a subclass of immunoglobulins that are potent activators of immune function. IgMs trigger this response through interactions with the C1 complex which are upstream complement proteins. C1q is a large collagen-like protein responsible for recognizing surface-bound IgM, but the nature of this interaction is not well understood. These experiments utilize HDX-MS to uncover key interactions and dynamics during complement cascade initiation. HDX-MS is a great tool to study this complex mixture of proteins in an atypical experimental environment. We used protein-based nanoparticles as a model surface to display IgM antigens and induce the surface-bound IgM conformation and this novel approach has the potential to show HDX-MS applied to conditions beyond typical in-solution 1:1 binding interactions.
Methods 115/120: Anti-SARS-CoV-2 spike receptor binding domain IgMs were used for all experiments including two different constructs, pentameric and hexameric IgM. These constructs were first incubated with nanoparticles that displayed SARS-CoV-2 spike receptor binding domain spaced at regular intervals. Samples were prepared using standard HDX conditions and labelled for time points between 1min and 4hrs in D2O buffer. The experiment was repeated but the immobilized IgM samples were incubated with C1q prior to labelling. Samples were quenched to pH 2.5 and frozen in liquid nitrogen before analysis. All samples were thawed and digested using an in-line Nepenthesin-2 protease column with subsequent LC/MS analysis. All experiments included a set of internal exchange standards to ensure comparability between conditions.
Preliminary Data 108/300: Previous experiments our lab has done have provided insight into changes that occur in IgM when bound to a surface vs. bound in solution. Changes in the Fc domain of the IgM upon surface binding showed that there is a unique conformation to surface-bound IgM that likely accounts for the increase in complement activity from these surface-bound molecules. Initial experiments have shown that the nanoparticles used in this experiment give rise to a conformation of IgM that can activate the complement cascade. All of the proteins tracked in this experiment have been digested using a NEP-2 column and have shown sufficient sequence coverage for meaningful HDX data interpretation.
Novel Aspect 18/20: HDX-MS highlights details of the C1-IgM interaction that initiates immune activation using a complex nanoparticle antigen display system.

Authors
Nicholas M. Riley1, Jingjing Huang2, David Bergen2, Amanda E. Lee2, Rafael D. Melani2, William D. Barshop2, John E.P. Syka2, Jesse D. Canterbury2, Vlad Zabrouskov2, Graeme C. McAlister2, Christopher Mullen2

Institutions
1Department of Chemistry, University of Washington, Seattle, Washington, USA 2Thermo Fisher Scientific, San Jose, California, USA

Abstract
Recent hardware changes introduced on the Orbitrap Ascend Tribrid MS include dual ion routing multipoles (IRMs) that can be used to parallelize accumulation, dissociation, and mass analysis of three separate ion populations. Here we explore how this architecture improves N- and O-glycopeptide characterization by increasing scan acquisition speeds without sacrificing spectral quality. The balance between scan speed and MS/MS product ion signal-to-noise is especially important in glycoproteomics. Complexities of glycopeptide fragmentation necessitate large precursor ion populations, and consequently, long ion accumulation times, for quality MS/MS spectra. To compound matters further, dissociation methods like electron transfer dissociation (ETD) that benefit glycopeptide characterization come with overhead times that also slow down scan acquisition. Conversely, heterogeneity inherent to glycosylation means that any given retention time during an LC-MS/MS analysis may contain numerous glycopeptide species to target through data-dependent acquisition. Often duty cycle is sacrificed to some degree, which results in higher quality spectra of abundant species but leaves other precursor ions under-sampled. We analyze mixtures of N- and O-glycopeptides to show that 20-30% more MS/MS scans can be acquired when parallelizing three ion populations using the dual IRMs of the Orbitrap Ascend. This translates to 10-20% gains in glycopeptide identifications depending on dissociation type(s), scan acquisition schemes, and method parameters (e.g., precursor ion accumulation and reaction times). Focusing on O-glycopeptide analysis with ETD-based methods, we also explore how acquisition rates and ion-ion reaction times affect identifications and product ions generation. We show what parameters need to be considered in O-glycopeptide characterization to generate c- and z-type ions that can be used for O-glycosite localization while also maximizing scan acquisition rates to improve total site-localized O-glycopeptide identification. In all, we show how architectural changes to the Tribrid MS platform benefit glycoproteomic experiments by parallelizing scan functions to minimize overhead time and improve sensitivity.

Authors
Abhigya Mookherjee, Alesi Escobedo, Mike Guttman

Institutions
Department of Medicinal Chemistry, University of Washington, Seattle

Abstract
Modern glycoproteomics platforms have enabled in-depth characterization of complex glycoprotein samples. LC-MS/MS can reveal much about glycopeptides including the peptide sequence, location of the glycan attachment, and the glycan composition. However, the information is often insufficient for extracting details of the glycan structure including linkage and anomeric configurations. We have taken various approaches to fill in this missing information about glycan structure using a combination of approaches including multi-stage tandem MS, high resolution ion mobility, and gas-phase hydrogen/deuterium exchange. These techniques have revealed that even seemingly simple carbohydrate structures can adopt a complicated ensemble of conformational states in the gas-phase that can confound direct structural interpretation. With the aim of generating a practical approach to improve glycan characterization, we have begun to benchmark the structures and fragmentation behaviors for various protonated mono and oligosaccharide structures that are relevant to glycoconjugates. We have now generated an LC-MS3/MS4 approach that is compatible with many proteomics workflows and can fill in much of the missing glycan structural information, particularly for O-linked glycosylation.

Authors
Kristian Swearingen 1, Jimmy Eng 2, Vladimir Vigdorovich 3, Priya Gupta 3, David Shteynberg 1, Luis Mendoza 1, Ashley Vaughan 3, D Noah Sather 3, Eric Deutsch 1, Robert Moritz 1

Institutions
1. Institute for Systems Biology 2. University of Washington 3. Seattle Children's Research Institute

Abstract
Glycosylation of proteins with covalently-linked sugar moieties is a ubiquitous and essential co- and post-translational modification. Until recently, however, it was debated whether protein glycosylation occurred in Plasmodium, the single-celled eukaryotic pathogen responsible for the disease malaria. Using mass liquid chromatography-mass spectrometry (LC-MS), we discovered that conserved thrombospondin type 1 repeat (TSR) domains in the parasite can be modified with two rare glycosylations: O-linked fucose at Ser and C-linked mannose at Trp. Here, we will present the specially tailored LC-MS methodologies we have developed in order to characterize TSR glycosylation in Plasmodium, techniques that enable us to enrich, target, and measure the stoichiometry of these protein modifications in the parasite.
When subjected to the gas-phase collision-induced dissociation typical of shotgun proteomics, glycopeptides exhibit species-specific fragmentation and neutral losses that render them invisible to standard proteomic database search workflows. To overcome this obstacle, we have modified an existing mass spectrometry data search engine, Comet, to accommodate these neutral losses, enabling us to detect these PTMs through the bioinformatics workflows contained in the Trans-Proteomic Pipeline, an open-source proteomics data processing platform. We also exploit a recently developed monoclonal antibody to enrich C-mannosylated peptides, thereby enabling detection of low-abundance glycopeptides. We will show how these methods have enabled us to produce the most comprehensive survey to date of protein glycosylation in Plasmodium, revealing that the parasite exhibits both highly conserved as well as apparently novel glycobiology.

Authors
Wentao Zhu, Daniel Raftery

Institutions
Northwest Metabolomics Research Center, University of Washington, Seattle, WA 98109, United States of America

Abstract
Microplastic and pesticide are two common environmental pollutants whose adverse effects have been widely reported, but it is unclear whether they cause combined toxicity in mammals. In this study, polystyrene microplastics (5 µm, 0.012 or 0.120 mg/kg) or/and epoxiconazole (0.080 mg/kg) were administered orally to mice for 6 weeks, their toxicity to liver and kidney was assessed from changes in histopathology, tissue function, oxidative defense system and metabolic profile. In addition, mechanism of combined toxicity was explored in terms of bioaccumulation levels, intestinal barrier, gut microbiota. Results showed that combined ingestion of polystyrene (0.120 mg/kg) and epoxiconazole caused more severe tissue damage, dysfunction, oxidative stress, and metabolic disorders compared to single exposure sources. Interestingly, occurrence of combined toxicity was associated with their increased accumulation in tissues. In-depth exploration found that epoxiconazole caused intestinal barrier damage by targeting the gut microbiota, leading to massive invasion and accumulation of polystyrene, which in turn interfered with the metabolic clearance of epoxiconazole in liver. In all, findings highlighted that polystyrene and epoxiconazole could cause combined toxicity in mice through the synergistic effect of their bioaccumulation in vivo, which provided new reference for understanding the health risks of microplastics and pesticides and sheds light on the potential risk to humans of their combined ingestion.

Authors
Charlie Mundorff1, Michael Watson1, Lauren Carter2, Malika Hale3, Adian Valdez2, Marion Pepper3, Neil King2, Miklos Guttman1

Institutions
1Department of Medicinal Chemistry, University of Washington, Seattle WA 98195 2Department of Biochemistry, University of Washington, Seattle WA 98195 3Department of Immunology, University of Washington, Seattle WA 98195

Abstract
Introduction 118/120: IgM antibodies comprise a subclass of immunoglobulins that are potent activators of immune function. IgMs trigger this response through interactions with the C1 complex which are upstream complement proteins. C1q is a large collagen-like protein responsible for recognizing surface-bound IgM, but the nature of this interaction is not well understood. These experiments utilize HDX-MS to uncover key interactions and dynamics during complement cascade initiation. HDX-MS is a great tool to study this complex mixture of proteins in an atypical experimental environment. We used protein-based nanoparticles as a model surface to display IgM antigens and induce the surface-bound IgM conformation and this novel approach has the potential to show HDX-MS applied to conditions beyond typical in-solution 1:1 binding interactions.
Methods 115/120: Anti-SARS-CoV-2 spike receptor binding domain IgMs were used for all experiments including two different constructs, pentameric and hexameric IgM. These constructs were first incubated with nanoparticles that displayed SARS-CoV-2 spike receptor binding domain spaced at regular intervals. Samples were prepared using standard HDX conditions and labelled for time points between 1min and 4hrs in D2O buffer. The experiment was repeated but the immobilized IgM samples were incubated with C1q prior to labelling. Samples were quenched to pH 2.5 and frozen in liquid nitrogen before analysis. All samples were thawed and digested using an in-line Nepenthesin-2 protease column with subsequent LC/MS analysis. All experiments included a set of internal exchange standards to ensure comparability between conditions.
Preliminary Data 108/300: Previous experiments our lab has done have provided insight into changes that occur in IgM when bound to a surface vs. bound in solution. Changes in the Fc domain of the IgM upon surface binding showed that there is a unique conformation to surface-bound IgM that likely accounts for the increase in complement activity from these surface-bound molecules. Initial experiments have shown that the nanoparticles used in this experiment give rise to a conformation of IgM that can activate the complement cascade. All of the proteins tracked in this experiment have been digested using a NEP-2 column and have shown sufficient sequence coverage for meaningful HDX data interpretation.
Novel Aspect 18/20: HDX-MS highlights details of the C1-IgM interaction that initiates immune activation using a complex nanoparticle antigen display system.

Authors
Luis Mendoza, Michael Hoopmann, Eric W. Deutsch, and Robert L. Moritz

Institutions
ISB

Abstract
In tandem mass spectrometry (MS/MS), peptides are selected for fragmentation from the mixture of ions generated in the first stage of MS. While modern mass spectrometers typically report precursor m/z values with an accuracy of a few ppm, isolation windows are typically much wider and may allow other ions to be co-fragmented. In such a case, the resulting spectra can become complex and difficult to interpret, which can result in decreased specificity and accuracy.
Here we present PeptidePrisoner, a new tool in the Trans-Proteomic Pipeline (TPP) that provides users with an isolation quality score that makes use of the theoretical isotopic envelope of the precursor ion, as well as the total signal attributed to that ion in the selection window.

Authors
Nicholas Day, Xiaolu Li, Matthew Gaffrey, James Sanford, Tyler Sagendorf, Kwame Attah, Sue Bodine, Josh Adkins, Wei-Jun Qian, and the MoTrPAC consortium.

Institutions
Pacific Northwest National Laboratory, University of Iowa

Abstract
The Molecular Transducers of Physical Activity consortium (MoTrPAC) aims to identify the underlying molecular changes that occur in response to physical activity to understand how exercise improves health. Among these molecular changes are redox-based post-translational modification of protein Cysteine thiol groups by molecules such as reactive oxygen species (ROS). Quantitative measurement of reversible protein thiol oxidation enables a better understanding of the redox environment and helps to identify what protein thiols are susceptible to oxidative modifications. Herein, we investigate the temporal responses of thiol redox proteome in rat muscle tissue derived from an endurance exercise training study. 60 lateral gastrocnemius muscle tissue samples were collected from male or female rats assigned to sedentary (Control) or exercise (1, 2, 4, or 8 weeks) groups. The samples were processed using an integrated bottom-up global and ‘total oxidation’ redox proteomics workflow that incorporated multiplexed isobaric labeling and enrichment using a thiol affinity resin. Due to the presence of highly abundant proteins in muscle tissue, we implemented our recently developed deep redox profiling workflow to improve coverage that surpasses other recent studies. The peptides were analyzed using a Thermo Scientific Q Exactive HFX mass spectrometer and identified using MSGF Plus. Statistical analysis was performed using the PlexedPiper pipeline R package. Thiol oxidation of 17,201 Cysteine (Cys) sites were quantified, corresponding to 5242 proteins. Compared to the control group, significant changes in thiol oxidation (redox) are observed across all exercise groups for both sexes. Female rats show more dynamic changes in Cys oxidation compared to male rats during the first 4 weeks of exercise. However, by the 8th week of exercise, male rats show a marked increase in the number of significantly oxidized sites compared to male rats at earlier timepoints and female rats at all timepoints. Significantly changing Cys oxidation in male rats is predominantly associated with bioenergetic pathways. On the other hand, significantly changing Cys sites in female rats are involved in processes that control muscle function and quality. This distinction suggests that exercise training may have sex-specific effects on the physiology of skeletal muscle. Ongoing work will integrate redox changes with those observed with phosphorylation or metabolites, where data are already available from MoTrPAC.

Authors
David D Shteynberg1; Alex Zelter2; Nina Isoherranen2; Michael R Hoopmann1; Luis Mendoza1; Jimmy Eng2; Eric W. Deutsch1; Robert L. Moritz1

Institutions
1Institute for Systems Biology, Seattle, WA; 2University of Washington, Seattle, WA

Abstract
Introduction The Trans-Proteomic Pipeline (TPP) continues to be the gold-standard, open-source analysis suite for proteomics data, and its major component PeptideProphet was first published 21 years ago.
We describe a novel model in PeptideProphet for validating PSM data searched with many variable modifications, some of them rare and others less rare, in one search.
The Variable Modification Count (VMC) model assists PeptideProphet’s classification of PTM containing PSMs. Intuitively, such PSMs are more likely to occur among random results than among correct results.
VMC allows PeptideProphet to compute more accurate FDRs compared to the previous iterations of this model, as indicated by entrapment decoys employed during the search. This is done, while preserving rare PTM containing PSMs with strong spectral evidence.
Methods To test the feasibility of detecting rare PTMs in complex data, we performed native bioactivation of raloxifene in insect cell microsomes, generating a highly complex sample made by co-expressing native human CPY3A4, cytochrome P450 reductase and cytochrome b5 in insect cells.
We collected DDA and DIA spectral data and converted these to mzML.
The mzML data was searched with comet and the resulting pepXML file analyzed with the TPP using PeptideProphet, iProphet and PTMProphet to validate the search results at the PSM level, peptide level and PTM level, respectively.
DIA data was first processed with the TPP tool, DISCo (Data-Independent-Signal-Correlator), that extracts searchable fragment data from DIA data files and generates mzML files that can be searched by comet directly.
Preliminary Data Raloxifene metabolism produces several electrophilic species that form protein adducts of mass 471.1504 Da. We incubated raloxifene with insect cell microsomes resulting in raloxifene metabolism and protein adduct formation. We collected data on unexposed (solvent only), light (d0) raloxifene exposed, heavy (d4) raloxifene exposed and a mixture of d0/d4 raloxifene exposed samples.
Comet searches were performed on DDA data allowing for variable modifications of 471.1504 (d0 raloxifene diquinone methide metabolite) and 475.1755 (d4 raloxifene diquinone methide metabolite) on cysteine, tryptophan and tyrosine, 15.9949 on methionine (oxidation) and 57.021464 on cysteines (carbamidomethyl).
The database used for searching was composed of UniProt protein sequences of the organism Spodoptera frugiperda, plus the human P450 enzymes CYP3A4 and CYP3A5, human P450 reductase, cytochrome b5, yeast enolase, and common protein contaminants.
Two sets of independently randomized decoy sequences were appended to the target database.
Decoy sequences were generated using DeBruijn repeat-preserving randomization, using software within the TPP.
The decoy sequences were randomly interleaved in the FASTA database and used for the comet search. Search results were classified using both Percolator 3.06 and the TPP at the PSM, peptide, and modifications levels, both with and without the use of the novel modification-specific Variable Modification Count (VMC) model.
Novel Aspect Newly added modification specific VMC Model in PeptideProphet improves classification and reduces false positives rates among rare PTM containing peptides as confirmed by both independent decoys and prior knowledge of d0/d4 labeled sample types.

Authors
May A. Constabel, Christopher J. Weir, Theresa A. Gozzo, Meagan M. Gadzuk-Shea, and Matthew F. Bush

Institutions
Department of Chemistry, University of Washington

Abstract
Introduction We developed a low-thermal-mass, programmable, temperature-controlled electrospray ionization (ptESI) source capable of rapid thermal modulation of ESI samples. With ptESI, we can increase or decrease the temperature of the solution within the nanospray capillary during experiments at rates of at least 0.5 °C·s–1 with high fidelity. Combined with ion mobility (IM) mass spectrometry (MS), ptESI enables us to probe protein folding/unfolding, conformational stability, and protein aggregation. Here, we demonstrate two applications of ptESI: thermal cycling to characterize the reversibility of protein folding and online disulfide bond reduction of proteins.
Methods Protein Unfolding with Rapid Cycling: Solutions of 10 µM myoglobin were prepared in 200 mM ammonium acetate. 4-5 µL of solution was loaded into nESI capillaries (borosilicate glass pulled to 1-3 um i.d.), a capillary inserted into the small copper block of the ptESI source and sprayed. The temperature was cycled 4 times continuously between 30 to 90 °C using a sawtooth function with slopes of ±0.5 °C·s–1 while MS spectra were continuously acquired using a Waters Cyclic IM-MS system. Online Disulfide Bond Reduction: Samples containing ribonuclease A (RBA) or cytochrome c were exchanged into aqueous ammonium acetate and then diluted with a solution containing a reducing agent to a final concentration of 10 µM RBA and varied concentrations of DTT, βME, or TCEP. The protein solutions were cycled once from 30 to 80 °C at a rate of 0.5 °C·s–1. Additional RBA solutions were incubated at 37 °C for 1 hour or at room temperature for 1 hour prior to analysis.
Preliminary Data Protein Unfolding with Rapid Cycling: Myoglobin (Mb) is a heme-binding protein that has previously been reported to have reversible unfolding with heating. For samples at 30 °C, the mass spectrum is dominated by peaks assigned to +8 and +9 holo-Mb. With increasing temperature, the intensity of those peaks decreases and those for +12 to +18 apo-Mb increase. When the temperature of the sample is cooled, the original peaks are once again the most intense. That process corresponds to the first cycle. With increasing cycle number, the spectra at low temperatures exhibit increasing relative intensity for both +8 to +14 apo-Mb ions and heme (616 m/z). Therefore, the unfolding of Mb can be associated with reversible and irreversible changes in structure. Incorporation of a complementary IM dimension is underway.
Online Disulfide Bond Reduction: The addition of 5-10 mM DTT or 10 mM βME was sufficient to irreversibly reduce all four native disulfide bonds in RBA during the first 50 s of one thermal cycle. Mass spectra were continuously acquired during the cycle; a clear shift to higher m/z corresponding to the addition of 8 hydrogens was observed. The capability to perform in-source reduction can reduce experiment time by eliminating the long incubation sample preparation step. As a control, reducing agents were also added to solutions of cytochrome c, a protein with no native disulfide bonds. No changes in the neutral mass of cytochrome c were observed. Nonspecific adducts of DTT and βME were not observed; however, adducts of TCEP were observed. This is being investigated further.

Authors
James Sanford1, Tyler Sagendorf1, Gina Many1, Chelsea Hutchinson1, Marina Gritsenko1, Hugh Mitchell1, James Pino1, Laurie Goodyear2, Sue Bodine3, Paul Piehowski1, Wei-Jun Qian1, Joshua Adkins1, and The MoTrPAC Study Group

Institutions
1Pacific Northwest National Laboratory, Richland, WA 2Joslin Diabetes Center, Harvard Medical School, Boston, MA 3Oklahoma Medical Research Foundation, Oklahoma City, OK

Abstract
Though the health benefits of physical activity are widely appreciated, the molecular mechanisms affected in response to exercise are not completely understood. Through the Molecular Transducers of Physical Activity Consortium (MoTrPAC), we sought to characterize the proteomic and phosphoproteomic responses in multiple tissue types from models of acute and chronic endurance exercise in six-month-old rats. Utilizing multiplexed isobaric labeling and offline fractionation coupled with LC-MS/MS analysis, we obtained some of the deepest reported coverage of the proteome and phosphoproteome of skeletal muscle, white adipose tissue, lung, and kidney—quantifying greater than 10,000 unique proteins and 30,000 unique phosphorylation sites in most tissues. Following a single bout of treadmill running, substantial changes to the phosphoproteome were observed at early timepoints (immediate post-exercise to 1-hour post-exercise) in skeletal muscle and lung, which largely returned to baseline by 24 hours. Global protein abundance changes increased over time in all tissues, with the largest number of significant changes observed at 24 hours post-exercise in proteins related to tissue organization, stress responses, and metabolic processes. Endurance exercise training for up to 8 weeks led to robust changes in the proteome of skeletal muscle and white adipose tissue, as well as alterations in the phosphoproteome that suggest differential activity of kinases involved in systemic metabolism. In all tissues profiled, we observed strong sex differences in baseline protein abundance, with several tissues showing sexually dimorphic exercise-induced proteomic and phosphoproteomic responses. Together with additional multi-omic measurements through other MoTrPAC centers, these data provide a tremendous resource for advancing our understanding of the molecular impacts of physical activity.

Authors
Alexis Chang, Mario Leutert, Ricard A. Rodriguez-Mias, Judit Villen

Institutions
Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States

Abstract
Phosphotyrosine (pY) enrichment is critical for expanding the fundamental and clinical understanding of cellular signaling by mass spectrometry-based proteomics. However, current pY enrichment methods exhibit a high cost per sample and limited reproducibility due to expensive affinity reagents and manual processing. We present rapid-robotic phosphotyrosine proteomics (R2-pY), which uses a magnetic particle processor and pY superbinders or antibodies. R2-pY can handle up to 96 samples in parallel, requires 2 days to go from cell lysate to mass spectrometry injections, and results in global proteomic, phosphoproteomic, and tyrosine-specific phosphoproteomic samples. We benchmark the method on HeLa cells stimulated with pervanadate and serum and report over 4000 unique pY sites from 1 mg of peptide input, strong reproducibility between replicates, and phosphopeptide enrichment efficiencies above 99%. R2-pY extends our previously reported R2-P2 proteomic and global phosphoproteomic sample preparation framework, opening the door to large-scale studies of pY signaling in concert with global proteome and phosphoproteome profiling.

Authors
Alex Zelter, King CB Yabut, Benjamin Zercher, Alice Martynova Michael J MacCoss, Matthew F. Bush, Nina Isoherranen

Institutions
Departments of Genome Sciences, Pharmaceutics and Chemistry, University of Washington

Abstract
4-Hydroxynonenal (4HNE) is a well-known lipid peroxidation product that modifies proteins via Michael addition (cysteine, histidine and lysine) and a Schiff base (lysines) mechanism. These covalent modifications have been proposed to contribute to the initiation and progression of multiple diseases associated with oxidative stress. However, the modifications formed by 4HNE are typically low abundance and difficult to identify and quantify from complex samples. The stoichiometry and kinetics of specific modifications formed by 4HNE are poorly understood and the quantitative relationships between modification and decreased protein function have not been defined. We used a combination of mass spectrometry techniques to determine the relationship between 4HNE mediated modifications in cellular retinoic acid binding protein 1 (CRABP1) and its function.
CRABP1 was expressed and purified from E. coli and treated with increasing concentrations of 4HNE to generate 4HNE-modified protein. 4HNE-modified CRABP1 was analyzed via intact protein mass spectrometry to determine the number of 4HNE modifications formed per CRABP1 protein and to estimate the fraction of the total CRABP1 modified by 4HNE with increasing concentrations of 4HNE. Treated and untreated CRABP1 protein was digested with trypsin and the 4HNE modified residues and the specific modification masses determined via shotgun proteomics. The relative abundance of the modifications at specific residues was quantified using DIA. Intact protein MS showed that following a one-hour incubation of CRABP1 with 10- or 25-fold molar excess of 4HNE, only 15-20% of CRABP1 was modified by 4HNE.
The major CRABP1-4HNE product contained just a single modification of 156 Da. This mass corresponds to the Michael addition of 4HNE to cysteine, histidine or lysine. To determine the specific locations of 4HNE modifications within the protein we performed tryptic digestion and bottom-up proteomics. 4HNE modifications were found in six of the 12 modifiable amino acids in CRABP1. Both histidines (H40 and H94) and two of the three cysteines (C95 and C129) were found modified by 4HNE. In addition, the peptides containing C95 and C129 were completely alkylated in untreated samples, while the presence of peptides without alkylation of C95 and C129 increased considerably when samples were treated with 4HNE. Of the seven lysines, only K38 and K92 were modified, consistent with the predicted lowest reactivity of lysine with 4HNE. Both the intact protein and bottom-up MS analysis supported 156 Da being the predominant modification by 4HNE. The only Schiff base modification (138 Da) found was at K92 but even in this residue the 156 Da modification was more abundant. This modification also resulted in a missed cleavage for that tryptic site. No significant decrease in the abundance of any of the unmodified peptides was observed, which highlights the limitations of using the depletion of unmodified peptides as a proxy for quantifying protein modifications. Taken together these data show that the relatively low abundance of 4HNE modified peptides in shotgun proteomics is due to incomplete modifications of the specific residues in the target protein and the distribution of modifications amongst different modifiable residues.

Authors
Gilbert S Omenn1, 2, Lydie Lane3, Christopher M Overall4, Cecilia Lindskog5, Charles Pineau6, Nicolle H Packer7, Susan Weintraub8, Sandra Orchard9, Michael Roehrl10, Ed Nice11, Tiannan Guo12, Jennifer E Van Eyk13, Siqi Liu14, Nuno Bandeira15, Ruedi Aebersold16, Robert L. Moritz2, and Eric W Deutsch2

Institutions
1University of Michigan, 2Institute for Systems Biology, 3CALIPHO Group, SIB Swiss Institute of Bioinformatics, 4University of British Columbia, 5Uppsala Universitet, 6University Rennes, Biosit, 7Macquarie University, 8University of Texas Health Science Center, 9EMBL-EBI, 10Memorial Sloan Kettering Cancer Center, 11Monash University, 12Westlake University, 13Cedars Sinai, 14BGI Group, 15University of California-San Diego, 16ETH-Zurich

Abstract
Background Since 2010, the Human Proteome Project (HPP) home of the flagship initiative of global HUPO has pursued two goals: (1) To credibly identify the protein parts list and (2) To make proteomics an integral part of multi-omics studies of human health and disease methods.
Methods International collaboration, data sharing, standardized reanalysis of MS data sets by PeptideAtlas and MassIVE with HPP Guidelines for quality and assurance, plus extensive use of antibody profiling by the Human Protein Atlas.
Results According to the neXtProt release of 2023-03, protein expression has now been credibly detected (PE1) for 18,397 of the 19,778 predicted proteins coded in the human genome (93%). Of these PE1 proteins, 17,453 were detected with mass spectrometry in accordance with HPP Guidelines and 944 by a variety of non-MS methods. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced to 1381. These numbers represent experimental progress on the Human Proteome parts list across all of the chromosomes with significant re-classifications. Meanwhile, there are several categories of predicted proteins that have proven resistant to detection. Applying proteomics with a large array of biological and clinical studies ensures integration with other omics platforms as reported by the Biology and Disease-driven HPP teams.
The HPP has now launched its Grand Challenge to find the functions of every protein.
Conclusions The global proteomics community has made remarkable progress in detecting and characterizing protein expression and protein functions in pathways and networks critical to understanding human health and disease.

Authors
Alice Martynova, King C. B. Yabut, Benjamin P. Zercher, Nina Isoherranen, and Matthew F. Bush

Institutions
University of Washington, Department of Chemistry University of Washington, School of Pharmacy, Department of Pharmaceutics

Abstract
Native mass spectrometry (MS) has emerged as a powerful technique for analysis of intact proteins and protein-ligand complexes in solution. Native MS can provide unique insight into binding interactions, stoichiometry, interferences, and structural dynamics, which can all contribute to a more complete understanding of complex binding processes. In this study, we employed native MS for the analysis of fatty acids binding proteins (FABPs) and their protein-ligand complexes. FABPs are a family of small cytosolic proteins ubiquitously expressed in tissues that play a crucial role in the transport and metabolism of fatty acids and lipid-like molecules. In addition to their roles in lipid metabolism, FABPs have been implicated in various physiological processes, such as inflammation, insulin resistance, and cancer, which makes them intriguing targets for therapeutic and diagnostic purposes. Despite a well-established role in lipid metabolism, the involvement of FABPs in drug metabolism remains undercharacterized. Using native MS, we aimed to shed light on the drug binding capacity and drug metabolism-related functions of FABP1, specifically known as liver-type FABP.
Initial characterization of intact, recombinant FABP1 revealed that established methods for expressing, purifying, and delipidating this protein results in the retention of significant populations of copurifying molecules, presumably fatty acids from the expression system (E. coli). This finding has significant implications for interpretation of previous FAPB1 ligand binding assays, which may have probed competition between target ligands and copurifying molecules in additional to the binding of the target ligand to apo FABP1. To address this, we employed native MS to evaluate the effectiveness of different delipidation methods. Additionally, we observed evidence for a 60 Da modification to FABP1, which we tentatively assigned to modification of the single cysteine in the binding pocket of FABP1. We investigated the effectiveness of the reducing agent dithiothreitol (DTT) on this modification and its impact on native MS characterization.
Subsequently, we analyzed FABP-ligand complexes using diclofenac and 11-dansylaminoundecanoic acid (DAUDA). The analysis elucidated the stoichiometry and provided direct evidence for both single and double addition of DAUDA to FABP1, which has a single binding cavity. The characterization of the interactions between FABP1 and diclofenac, a widely used nonsteroidal anti-inflammatory drug (NSAID), expands our understanding of the binding interactions as a result drug metabolism. Additionally, we validated the use of DAUDA, a fluorescent probe, for fluorescence displacement assays, which proved useful for studying protein-drug complexes. Subsequently, the fluorescent displacement assay was applied to investigate various protein-drug complexes.
These findings provide valuable insights into the drug binding properties of FABP1 and its potential involvement in drug metabolism, opening avenues for further research and the development of therapeutic strategies targeting FABPs. More generally, these experiments highlight the benefits using native MS for characterizing protein-ligand interactions, including facile observation of interfering molecules and differentiation between proteins with one or two ligands bound.
Keywords: Fatty acid binding proteins, native mass spectrometry, drug metabolism, protein-drug interactions, fluorescent displacement assay.

Authors
Justin Sanders (1), Sewoong Oh (1), William Stafford Noble (1)(2)

Institutions
(1) Department of Genome Sciences, University of Washington (2) Paul G. Allen School of Computer Science and Engineering, University of Washington

Abstract
Computational algorithms for sequence database search are a cornerstone of modern shotgun proteomics experiments, enabling the identification and quantitation of peptides from tandem mass spectra. All existing mass spectrometry database search engines for proteomics use hand-designed score functions to assess the quality of a candidate peptide-spectrum match (PSM). Here, we propose to instead learn this score function directly from data. We train a deep neural network to solve the database search problem by using repository-scale, unlabeled mass spectra and a semi-supervised loss function based on the theory of target/decoy competition. We test the hypothesis that such a model, applied to spectra and peptides not used during training, will yield better statistical power than existing, hand-designed database search score functions. Here we present preliminary results on the feasibility and efficacy of our semi-supervised training objective. While our learned score function assigns peptides to more spectra with high confidence than existing methods, orthogonal validation reveals many of these additional PSMs to be implausible. We investigate a set of potential pitfalls that must be considered when training models using target/decoy analysis which may underlie the observed bias in predictions, and explore strategies to avoid or mitigate them.

Authors
Jesse B. Trejo, Kristin L.M. Boylan, Ashley J. Petersen, Joshua R. Hansen, Tao Liu, Amy P.N. Skubitz, Paul D. Piehowski

Institutions
PNNL, University of Minnesota

Abstract
The early detection of ovarian cancer is important to improve treatment outcomes for patients, but an effective screening for diagnoses has not been developed yet. With our collaborators at the University of Minnesota, we are investigating liquid-based Pap samples as a potential source for ovarian cancer biomarkers. However, proteomic analysis of these samples presents two major challenges: shed proteins are highly dilute within the fixative solution, and standard storage of this fixative has introduced the interference of polyethylene glycol (PEG) contamination. Two different processing methods have been optimized for ‘Mock’ SurePath Pap tests and ThinPrep Pap tests to tackle these challenges and are presented here. The first method consists of an acetone precipitation to remove PEG contamination followed by resolubilization in 8M Urea for a standard digestion protocol. We found that SurePath samples yielded enough protein material for discovery proteomics with Tandem Mass Tag (TMT) labeling. Furthermore, we found that adding a 70% ethanol wash after the acetone precipitation improved reliability to remove PEG contamination without negatively impacting protein yield. A downside of the acetone precipitation is the resulting loss of protein, which is a problem when working with small samples such as the ThinPrep Pap samples. Applying the above protocol resulted in protein yields below the detectable limit in a BCA assay, and the lack of a visible pellet made PEG removal unreliable. This caused inconsistent results and <500 protein identifications per sample even when we pooled multiple samples together. To address this, we applied the S-Trap Micro digestion protocol which is specifically intended for low yield samples. PEG contamination was completely removed from the samples and protein identifications from individual samples increased 3-fold. With these optimizations, we have carried out discovery proteomics studies using a cohort of patients with SurePath Pap tests to identify several putative biomarker candidates for downstream validation using targeted proteomics. Proteomic analysis of the ThinPrep cohort is currently underway and we plan to analyze larger cohorts in the future to continue the identification of biomarkers in ovarian cancer.

Authors
Bo Wen, William Stafford Noble

Institutions
Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA

Abstract
A longstanding goal in the analysis of tandem mass spectrometry data is to automatically assign a quality score to each observed MS/MS spectrum. Such a score would be useful not only for evaluating the quality of the data but also in the context of assigning peptides to spectra. However, spectrum quality prediction is still challenging due to the complexity of the spectra. In this study, we have developed a method to train a spectrum quality classier using PSMs from the MassIVE-KB dataset by leveraging a spectrum representation learned from deep learning. We demonstrate the performance of this method on a multi-species dataset.

Authors
Josh Eckels1; Sweta Jewargikar2; Wendy Innis2; Ankur Juneja1; Nicholas Shulman3; Vagisha Sharma3; Michael J. MacCoss3; Brendan X. MacLean3; and the Panorama Partners Program

Institutions
1LabKey, San Diego, CA; 2LabKey, Seattle, WA; 3University of Washington, Seattle, WA;

Abstract
Panorama is a web-based data management system for targeted mass spectrometry. It integrates closely with Skyline, a free, open source targeted mass spec analysis tool. Panorama’s system suitability tools automatically report on instrument health and identify problems. Features for multi-attribute method (MAM) analysis make characterizing antibodies across samples easy. For researchers doing proteomics, it also visualizes peptide and protein sequence data. Free cloud-based projects are available to everyone on PanoramaWeb.org. Panorama uses a relational database to store targeted mass spectrometry data, importing data from Skyline’s XML file. Tight integration between Panorama and Skyline ensures complementary and compatible feature sets. Panorama’s QC folders offer user-friendly, web-based visualizations and reporting of system suitability data, storing data from each mass spectrometer in a separate folder. AutoQC, a utility that monitors for newly acquired raw data files, automates the otherwise tedious process of adding new data. Panorama also offers a growing assortment of reporting and visualization tools, both available out-of-the-box, and for customization. Since Panorama first implemented system suitability monitoring in 2014, users have created more than 1,500 QC folders on PanoramaWeb.org. Of those, more than 300 folders have accumulated 100 or more samples worth of data and many have thousands of acquired files. Because statistical process controls are not necessarily intuitive to mass spectrometrists, Panorama has recently added new visualizations that show trailing mean and coefficient of variation values for its full set of metrics which may feel more intuitive to everyday users. They join the Levey-Jennings, moving range, and cumulative sum plots. Other improvements to all of Panorama’s system suitability plots help reduce visual clutter from a great deal of historical data. Users doing Multi-Attribute Method (MAM) analyses can utilize additional built-in reporting to monitor post-translational modifications and assess risk based on criteria such as complementarity-determining regions (CDRs) and sample metadata. Additionally, Panorama now supports visualization of cross-linked peptides to easily monitor peptides with disulfide bonds and other more complex PTMs. Finally, Panorama benefits from Skyline’s recent addition of tracking protein groups, capturing the full list of proteins to which a set of peptides may belong. Panorama’s protein/peptide sequence view now also displays intensity and confidence score data, either summarized across multiple samples or one sample at a time. As of February 2023, more than 650 labs are using Panorama projects, free of charge, to manage targeted mass spectrometry assays on http://panoramaweb.org, a server hosted by the MacCoss lab at the University of Washington. Additionally, major pharmaceutical companies and other organizations have deployed their own in-house installations of Panorama.

Authors
Yuan Feng, Benjamin P. Zercher, Matthew F. Bush*

Institutions
University of Washington, Department of Chemistry, Box 351700, Seattle, WA, 98115

Abstract
Introduction Analogous to the advantages of tandem mass spectrometry (MS) relative to single-stage MS, multidimensional ion mobility (IM) can increase the information content of IM experiments by isolating subpopulations of ions for further analysis. Electrostatic ion mobility (IM) enables the direct determination of mobilities without calibration, but using traditional implementations, increasing the number of dimensions also requires corresponding increases in applied potentials. One solution to this challenge is traveling-wave IM, which has been used to enable long separation pathlengths and multidimensional separations with relatively low potentials relative to electrostatic IM. Here, we present an alternative strategy that reduces the magnitude of potentials required for electrostatic IM by dynamically resetting the potential of ions between dimensions of IM.
Methods Ubiquitin, concanavalin A, and cytochrome c were purchased and prepared in aqueous 200 mM ammonium acetate adjusted to pH 7.0. Denatured cytochrome c samples were prepared by solvent exchanging proteins using size-exclusion spin columns that had been equilibrated with three washes of 0.1% acetic acid. These experiments were performed on a Structures for Lossless Ion Manipulations (SLIM) architecture IM instrument that uses electrostatic drift fields to separate ions. Ion trapping is enabled by biasing adjacent modules to create a potential well that we call a “junction trap”. The potentials that comprise the junction trap are modulated by applying time-dependent voltage programs. Preliminary In tandem IM experiments, ion packets were generated on the first module (1M) and separated in the first dimension of IM (1D) before the time-dependent selection of a specific charge state at 7M. Selected ions were accumulated in a junction trap for a short time (~10 ms) prior to the 2D. In potential resetting experiments, the 2D region was held at ground while ions were separated and selected in the 1D region. The selected ions were accumulated in a junction trap between the 1D and 2D at near ground potential. After accumulation, the potentials of the junction trap and the input of the 2D were raised in 5 V increments every 125 µs. The ions were then released from the junction trap into the 2D. For comparison, ions were also analyzed in tandem IM experiments that used the same drift fields, but applied using higher, static drift potentials. Ion lifetimes, as monitored by the depletion of the precursor, were the same in both experiments. The well-overlaid 2D arrival time distributions and mass spectra from each experiment suggest that potential resetting does not perturb trapped ions. We then isolated three subpopulations of 7+ cytochrome c, reset their potentials, and demonstrated that all subpopulations remain resolved in the 2D, which suggests that potential resetting of ions does not induce conformational changes that significantly change the arrival time of ions.

Authors
Lincoln Harris, William E. Fondrie, Sewoong Oh, William S. Noble

Institutions
University of Washington, Department of Genome Sciences Paul G. Allen School of Computer Science and Engineering, University of Washington Talus Biosciences

Abstract
Quantitative measurements produced by tandem mass spectrometry proteomics experiments typically contain a large proportion of missing values. This missingness hinders reproducibility, reduces statistical power, and makes it difficult to compare across samples or experiments. Although many methods exist for imputing missing values in proteomics data, in practice, the most commonly used methods are among the worst performing. Furthermore, previous benchmarking studies have focused on relatively simple measurements of error, such as the mean-squared error between the imputed and the held-out observed values. Here we evaluate the performance of a set of commonly used imputation methods using three practical, “downstream-centric” criteria, which measure the ability of imputation methods to reconstruct differentially expressed peptides, identify new quantitative peptides, and improve peptide lower limit of quantification. Our evaluation spans several experiment types and acquisition strategies, including data-dependent and data-independent acquisition. We find that imputation does not necessarily improve the ability to identify differentially expressed peptides, but that it can identify new quantitative peptides and improve peptide lower limit of quantification. We find that MissForest is generally the best performing method per our downstream-centric criteria. We also argue that existing imputation methods do not properly account for the variance of peptide quantifications and highlight the need for methods that do.

Authors
Mukul K. Midha, Charu Kapil, Michal Maes, David H. Baxter, Seamus R. Morrone, Timm J. Prokop, Robert L. Moritz

Institutions
Institute for Systems Biology, Seattle, WA 98109

Abstract
Introduction Nano-flow chromatography-tandem mass spectrometer (nLC-MS/MS) is a popular choice in proteome research as it provided high-sensitivity analysis with minimal sample usage, but its quantitative proteomics applications become restricted by low analytical throughput, and low robustness. To circumvent this limitation, we describe the performance of the new Vacuum Insulated Probe Heated ElectroSpray Ionization source (VIP-HESI) coupled to the Bruker timsTOF mass spectrometer and show it enhances micro-spray flow rate chromatography signals in comparison to nanospray source conditions using the CaptiveSpray (CS) and ElectroSpray Ionization (ESI) sources. In addition, using a 0.5 x 200mm and 1 × 150 mm columns, achieved excellent reproducibility of chromatographic retention time, coefficient of variation, and precision quantification using data from un-depleted mouse plasma, HeLa and K562 digest peptide samples.
Methods PepCalMix peptides with seven different concentration points to cover a range of 12.5fmol to 800fmol were measured to assess linear response using VIP-HESI source and compared to CaptiveSpray and ElectroSpray Ionization sources. Using un-depleted mouse plasma sample, different injection amounts of 0.4μg at 1μL/min with CaptiveSpray were compared to 2μg, 4μg, 10μg, 20μg, and 40μg injection amounts at 40μL/min coupled with VIP-HESI source. Lastly, we also assess the performance of VIP-HESI microflow setup in a slice-PASEF mode for analysis of low sample amounts. For dia-PASEF runs and slice-pasef, Spectronaut 16.0 and DIA-NN 1.8.2 tools respectively were used to identifications filtered with a q-value of <0.01 and MS2 ion peak areas of quantified peptides were summed to estimate the protein quantification.
Preliminary Data We determined excellent linear gain in the total protein quantity as we increased the PepCalMix concentration with the R-Squared (R²) of more than 99% and linear response enabled excellent comparison between the CS, ESI, and VIP-HESI sources. VIP-HESI source performed better than than ESI by providing 50% more PepCalMix quantities and 30% more abundances than CS after injecting thirty-two times more injection amounts. Using mouse undepleted plasma samples, DIA-MS analysis using Spectronaut software resulted in the cumulative identification of 5,795 - 8,610 precursors and 493 - 802 unique proteins at <1% protein FDR across the different injection amounts. Interestingly, injecting fifty times (20μg) more sample amounts (with 40 times more sample dilution) using VIP-HESI, outperforms CS 0.4μg measurement by identifying 3% more precursors and 12% more proteins. Next, on evaluating the reproducibility of quantitative measurements, VIP-HESI 20μg measurement, a total of 7,074 precursors were quantified by both biological replicates with a high positive correlation (r2 = 0.94). Whereas with CS 0.4μg replicate measurements, 6,387 precursors were quantified with a positive correlation (r2 = 0.89), indicating more variation was observed with nanoflow rates, compared to VIP-HESI-microflow runs. Subsequently, we observed similar median number of data points (5) measured across the elution profiles and similar base peak widths (0.16 and 0.14 minutes) in both VIP-HESI 20μg and CS 0.4μg measurements, signifying that VIP-HESI provides an optimal quantification of an identified precursor using spectronaut analysis. For slice-pasef experiment, DIA-NN tool with different HeLa sample amounts resulted in the identification of 6,592 - 49,130 precursors at <1% precursor FDR and 1,769 - 6,343 proteins at <1% protein FDR. For 10ng sample injection amounts, slice-PASEF yielded 63% more precursors and 38% more protein groups than the VIP-HESI source setup, demonstrating significant increase in the number of precursor and protein groups, especially with low injection amount measurements.
Novel Aspect VIP-HESI source with improved analytical setup capable of highly reproducible chromatography that can accurately quantify with a wider proteome coverage.

Authors
Gennifer Merrihew1; Jea Park1; Deanna Plubell1; Julia Robbins1; Brian Searle2; Eric Huang1; Christine Wu1; Kathleen Poston2; Thomas Montine2; Michael J. MacCoss1

Institutions
1University of Washington, Seattle, WA; 2Ohio State University, Columbus, OH; 3Stanford University, Stanford, CA

Abstract
Neurodegenerative diseases have complicated comorbidities and mixed pathologies that are difficult to diagnose. To assess biological signatures of neurodegenerative diseases, we used a systematic method to collect quantitative proteomics data from an age and sex matched, clinically defined cohort of cerebrospinal fluid (CSF) from 280 patients categorized into four groups: healthy control, Alzheimer’s disease/mild cognitive impairment, Parkinson’s disease cognitively normal and Parkinson’s disease cognitively impaired. To confidently measure the same peptide quantities from different patient samples, we developed a series of controls to assess system suitability, individual sample preparation quality, and quantitative accuracy on the batch level. These controls were tracked in real-time using Skyline, AutoQC, and PanoramaWeb.
CSF samples were resuspended in SDS lysis buffer with yeast enolase protein to assess sample digestion and then reduced and alkylated. Proteins were aggregated on MagResyn Hydroxyl beads, washed, and digested to peptides, using a Thermo KingFisher Flex. Peptides were separated using reverse-phase chromatography with a Thermo Easy nano-LC and electrosprayed into a Thermo Orbitrap Eclipse Tribrid analyzed using a 12 m/z staggered DIA isolation scheme. The data were demultiplexed to 6 m/z with Proteowizard.
EncyclopeDIA was used to detect peptides and assign peak boundaries which were then imported into Skyline. Peptide quantities were then median normalized and batch corrected. All levels of data are available via PanoramaWeb.
Lumbar CSF from 280 patients were divided into three major groups: 1) Healthy Control, 2) Alzheimer’s disease/mild cognitive impairment, and 3) Parkinson’s disease cognitively normal and impaired. Each row of half a 96-well plate contained 10 balanced and randomized CSF samples and two external controls. One external inter-batch control was a pool of 50 patients representing all 4 groups and the other external inter-experiment control was a commercially available pool of CSF. These controls were used to assess the technical precision within and between each batch prior to and following normalization and batch adjustment. The coefficient of variation calculated for all peptides in the inter-batch control improved 7.75% after normalization and batch adjustment at the peptide-level and 20.38% at the protein level. We also use internal process controls to assess sample preparation and monitor data collection. These controls were necessary, as the data collected encompassed seven batches analyzed on separate LC columns and traps over a three-month period.
Preliminary analysis of the CSF from the 280 patients yields 23,742 peptides and 2685 protein groups. The peptides found in our data represent many of the expected proteins previously shown to be associated with neurodegenerative diseases but we also find new proteins.
Our data has also revealed statistical significant positive or negative peptide correlations with known Alzheimer’s disease biomarkers amyloid-beta 42/40 and pTau181. Pairwise group comparisons using WGCNA yield gene ontologies such as carbon metabolism, apoptosis, neutrophil degranulation, focal adhesion and neurodegeneration.

Authors
Klaas J. van Wijk^, Tami Leppert+, Zhi Sun+, Alyssa Kearly*, Margaret Li+, Luis Mendoza+, Isabell Guzchenko^, Erica Debley^, Georgia Sauermann^, Pratyush Routray^, Sagunya Malhotra+, Andrew Nelson*, Qi Sun% and Eric W. Deutsch+

Institutions
^Section of Plant Biology, School of Integrative Plant Sciences (SIPS), Cornell University, Ithaca, NY 14853, USA; +Institute for Systems Biology (ISB), Seattle, Washington 98109, USA; *Boyce Thompson Institute, Ithaca, NY 14853.; %Computational Biology Service Unit, Cornell University, Ithaca, NY 14853.

Abstract
We present a new release of the Arabidopsis thaliana PeptideAtlas proteomics resource providing protein sequence coverage, matched mass spectrometry (MS) spectra, selected PTMs, and metadata. 70 million MS/MS spectra were matched to the Araport11 annotation, identifying ∼0.6 million unique peptides and 18267 proteins at the highest confidence level and 3396 lower confidence proteins, together representing 78.6% of the predicted proteome. Additional identified proteins not predicted in Araport11 should be considered for building the next Arabidopsis genome annotation. This release identified 5198 phosphorylated proteins, 668 ubiquitinated proteins, 3050 N-terminally acetylated proteins and 864 lysine-acetylated proteins and mapped their PTM sites. MS support was lacking for 21.4% (5896 proteins) of the predicted Araport11 proteome – the ‘dark’ proteome. This dark proteome is highly enriched for certain (e.g. CLE, CEP, IDA, PSY) but not other (e.g. THIONIN, CAP,) signaling peptides families, E3 ligases, TFs, and other proteins with unfavorable physicochemical properties. A machine learning model trained on RNA expression data and protein properties predicts the probability for proteins to be detected. The model aids in discovery of proteins with short-half life (e.g. SIG1,3 and ERF-VII TFs) and completing the proteome. PeptideAtlas is linked to TAIR, JBrowse, PPDB, SUBA, UniProtKB and Plant PTM Viewer.

Authors
Charles Watt, MS; Timothy Moore, PhD; Jen Liddle, PhD; Jeremy Balsbaugh, PhD

Institutions
Watt and Moore (Statistical Consulting Service - The University of Connecticut) Liddle and Balsbaugh (Proteomics and Metabolomics Facility - The University of Connecticut)

Abstract
Data-Independent Acquisition Mass Spectrometry (DIA-MS) powerfully expands scientific access to the proteome by theoretically capturing all observable peptide information from any biological sample. Numerous computer programs have been written to facilitate post-search data processing such as imputation, normalization, transformation, and statistical significance testing. However, these existing software packages are most often presented as plug-and-play workflows. This focus on simplicity speeds up a novice user but obscures alternative analysis methods behind defaults. MSstats, for example, offers a function “dataProcess” that performs transformation, normalization, and imputation of a data set in a single line of code. While efficient, this structure discourages innovation in analysis methods, since altering the workflow requires the intervention of a skilled programmer. To improve the legibility of the analysis workflow, the University of Connecticut is developing a new programming package, msDiaLogue, with a clear set of modular analysis functions that each perform a single operation on the data, e.g. imputation. By designing the program to invite novice users to dig deeper, the authors hope to empower further research into analysis methods in DIA-MS. The modular nature also allows for future incorporation of new, emerging methods as they become available, ultimately give the users more flexibility, without excessively increasing the programming burden.
As a motivating example, this work will compare different analysis results from a single DIA-MS dataset, the differences being obtained simply by switching the order of steps in the analysis.

Authors
Helisa H. Wippel 1, Panga J. Reddy 1, Zhi Sun 1, David Baxter 1, Kristian Swearingen 1, David D. Shteynberg 1, Mukul K. Midha 1, Melissa J. Caimano 2, Klemen Strle 3, Yongwook Cho i4, Agnes P. Chan 4, Nicholas J. Schork 4, Robert L. Moritz 1

Institutions
1. Institute for Systems Biology, Seattle, Washington, USA 2. Department of Medicine, UConn Health, Farmington, Connecticut, USA 3. Department of Molecular Biology and Microbiology, Tufts University School of Medicine, Boston, Massachusetts, USA 4. Translational Genomics Research Institute, Phoenix, Arizona, USA

Abstract
INTRODUCTION Lyme disease is a result from an infection by the spirochete Borrelia burgdorferi, the leading vector-borne disease in North America.
Due to the genomic and proteomic variability of different B. burgdorferi isolates, the study and further comparison of their proteome is key to understand the biology and infectivity of these spirochetes.
Mass spectrometry-based proteomics was used to assemble peptide datasets of commercial isolates MM1, B31, and the infective isolates 297 and B31-5A4, as well as other public datasets.
These datasets include information on the total proteome, secretome, and membrane proteome of the Borrelia isolates, and is publicly available as the Borrelia PeptideAtlas.
This unique resource allows the assessment of protein content of Borrelia isolates and compare detectable protein sequences.
METHODS B. Burgdorferi total proteome, high-pH-fractionated proteome, secretome, and membrane proteome fractions of isolates B31, MM1, 297, and the infective isolate, 5A4 were analyzed by LC-MS/MS and data analysis performed by the Trans-Proteomic Pipeline: data was searched by Comet against B. burgdorferi B31 database from UniProt (1,290 sequences), MM1 protein database from NCBI (1,152 sequences), and 116 common MS contaminants – with a total of 2,558 protein sequences, and additional 2,558 decoy sequences.
PeptideProphet assigned scores for PSMs, and iProphet was used to assign the score for peptides.
iProphet output was processed using the reSpect algorithm to get additional identifications of chimera spectra, and the filtered data was assessed with the MAYU software to calculate decoy-based FDRs at peptide and protein levels.
PRELIMINARY DATA Although numerous proteomic reports exist for B. burgdorferi isolates, no information is available as a searchable compendium of public data, and users have to resort to obtaining raw information files and search any, or all, of these data individually.
To expand the knowledge of the B. burgdorferi proteome, we have performed extensive proteomic analysis on B31, MM1, 297, and B31-5A4 isolates with mass spectrometry data generated from total proteome, secretome, and the membrane fractions of these isolates, and processed through the Trans-Proteomic Pipeline to generate a PeptideAtlas Borrelia build.
The PeptideAtlas repository contains information on peptides identified by mass spectrometry-based proteomics of multiple organism and systems, e.g., human, yeast, etc. (http://www.peptideatlas.org/).
Proteomic data from B. burgdorferi isolates, collected from 585 mass spectrometry runs, provides identification of 39,145 distinct peptides at a 0.043% peptide FDR, which map to 1,018 canonical proteins with FDR < 1% (79% of the total B31 proteome coverage).
The Borrelia PeptideAtlas provides a publicly accessible resource, important for the Lyme disease research community.
Our goal is to provide an expandable data source for many other B. burgdorferi isolates, including clinically relevant isolates, and under different growth conditions enabling the investigation of the dynamic proteome of this spirochete through its infection stages and their vastly different environments.
The diverse proteomic information from multiple infective isolates with credible data presented by the Borrelia PeptideAtlas can be useful to pinpoint potential protein targets which are common to infective isolates and may be key in the infection process – such as outer membrane proteins.
A list of membrane protein targets can be identified with in silico prediction of signal peptides and secondary structures of membrane proteins, out of the dense proteomic data, and be further investigated for host-pathogen protein interactomics with different technologies, e.g., chemical cross-linking of proteins and proximity labeling.
A public B. burgdorferi PeptideAtlas data repository for the Lyme disease research community.

Authors
Seamus R. Morrone, Michael R. Hoopmann, David D. Shteynberg, Ulrike Kusebauch, and Robert L. Moritz

Institutions
Institute for Systems Biology

Abstract
Phosphoproteomics is a biologically important and dynamic field, with researchers constantly seeking ways to improve phosphopeptide detection quantity and quality. Data-dependent mass spectrometry (DDA-MS) is a widely-used approach for phosphoproteomics, and high-throughput capabilities are quickly becoming the norm, allowing researchers from diverse fields access to data and instruments. With so many investigators not necessarily interested in DDA-MS per se, unfamiliarity with the instrument may lead to sub-optimal results; thus, it is important that the instrument be used to its fullest potential for detection of phosphopeptides. We show the response of phosphopeptide quantity and quality with changing parameters on an Orbitrap to demonstrate how it may lead from optimization for unenriched samples to phosphoenriched samples, and how phosphopeptide detection optimization is not necessarily a binary outcome. These investigations provide a roadmap for those unfamiliar with many of the commonly-used parameters in DDA-MS, an explanation for selecting certain values over others, and some insight into their effects on phosphopeptide analysis.

Authors
Linfeng Wu, Guannan Li, Patrick Batoon, Daniel Cuthbertson

Institutions
Agilent Technologies

Abstract
Large targeted multiplexing assays using LC/TQ systems have been increasingly used for proteome quantitation analysis, especially in the context of large cohort studies. Plasma is one of the most relevant sample types in academic and translational research. However, the complexity of this matrix and the wide dynamic range of protein concentration has often made it difficult to routinely monitor markers with accuracy and precision. In this study we used a new LC/TQ system driven by advanced electronics with onboard system intelligence architecture to evaluate gains in system sensitivity and ability to streamline method optimization. The dMRM acquisition method with a total of 2250 transitions, 204 maximum concurrent MRMs, and 650 millisecond (ms) cycle time was successfully applied. Using SIS peptides from PeptiQuant kits spiked into plasma we were able show to precision and accuracy at levels as low as 1 amol/µL over a wide 6-order dynamic range. With this complex matrix and intelligent mass spectrometer we maintained reproducible peak areas and precision over a multiday study demonstrating the suitability of this system for comprehensive protein quantification assays in complex matrix.

Authors
Günther Kahlert, Christie Hunter, Robert L. Moritz

Institutions
Sciex

Abstract
Drug target deconvolution is a centerpiece of medicinal chemistry efforts. In order to define positive target engagement and off-target engagement of proteins by novel drug development in a high-throughput manner, we developed a method that utilizes thermal shift assays in a combination with Data-independent analysis (DIA) or SWATH-MS. We coined the method Comprehensive Quantitative Thermal Shift Assays (CQTSA). CQTSA can reveal novel drug interaction patterns in deep complex proteomes, revealing protein unfolding patterns detectable with sensitive MS approaches. DIA mass spectrometry tracks ion fragment patterns in a multiplexed fashion over a wide dynamic range by collecting MS/MS spectra signals in variable isolation windows of any given ion fragment pattern in a window resulting in the detection of upwards of 10,000 proteins in a given sample. The new Sciex ZenoTOF 7600 MS with SWATH DIA harnesses the power of the Zeno Trap allowing very short LC separation runtimes as short as 10 minutes allowing acquisition of many samples in a given day. Using the Sciex ZenoTOF 7600 MS, we are able to effortlessly reveal the known protein target of methotrexate in under half a day demonstrating the usefulness of the ZenoTOF 7600 system for deconvoluting drug interaction patterns effortlessly.

Authors
Nick Morrice 1, Ihor Batruch 2 and Patrick Pribil 2 FCGlisson 3

Institutions
1 SCIEX, UK; 2 SCIEX, Canada; 3 Sciex, USA

Abstract
Zeno SWATH DIA on the ZenoTOF 7600 system combines the speed, sensitivity and quantitative reproducibility needed for robust detection and quantitation of proteins with very fast LC gradients, when combined with the selectivity and sensitivity afforded by Zeno trapping in MS/MS. Using a 5-minute microflow LC gradient (14-minute total runtime) and Zeno SWATH DIA with 56 variable-width SWATH DIA windows, approximately 5,000 protein groups were quantified with <20% CV from 200 ng of K562 and HeLa cell lysates. In addition, approximately 3,100 protein groups were quantified from yeast extracts. These results show that with this fast microflow LC chromatography and Zeno SWATH DIA method, approximately 1000 protein groups can be effectively quantified per minute of active gradient using the ZenoTOF 7600 system.

Authors
Authors: Cuong Le 1, Patrick Pribil 1 and J.C.Yves Le Blanc 1 , Paul Clemens/Fred Glisson 2

Institutions
Affiliations 1 Sciex Canada, 2 Sciex USA

Abstract
Top-down analysis is an emerging tool for intact protein characterization. Fragmentation techniques such as electron activated dissociation (EAD) and ultraviolet photodissociation (UVPD) have enabled detailed MS/MS analysis that provides high sequence coverage for small proteins (<30 kDa) . However, as protein mass increases, fragmentation efficiency typically decreases, which also reduces sequence coverage. An approach used to overcome these limitations is to rely on middle-down analysis in which the protein is first broken into smaller subunits, typically by using enzymes in solution, and each subunit is analyzed by CID and EAD to yield higher sequence coverage. Here, we propose using thermal collision induced dissociation (thermal-CID) fragmentation to generate protein subunits, followed by CID and EAD to increase protein sequence coverage.

Authors
Torri E. Rinker, Jarrett D. Egertson, Aisha Ellahi, Jamie Sherman, Maria Villancio-Wolter, Brittany Nortman, Julia Robinson, Ahana Dutta, Hunter B Boyce, James Joly, Filip Bartnicki, Christina Inman, Jacinto Villanueva, Jennifer McGinnis, Jonathan Leano, Nikola Kondov, Parag Mallick

Institutions
Nautilus Biotechnology

Abstract
The combination of single-molecule resolution together with comprehensive proteome coverage has potential to improve sensitivity and reproducibility of protein analysis. Here, we demonstrate Protein Identification by Short-epitope Mapping (PrISM), which aims to provide comprehensive proteome analysis with broad dynamic range at single-molecule sensitivity by interrogating immobilized, full-length proteins in parallel using multi-affinity probes.
PrISM uses non-traditional, multi-affinity probes with high affinity and low specificity that bind to short epitopes in multiple proteins. Sample proteins were conjugated to DNA nanoparticles and deposited on a high-density patterned flow cell at optically resolvable locations. Multi-affinity probes were applied to sample proteins over multiple cycles to generate binding patterns for each single-molecule protein, which are translated to protein identifications and quantities using a machine learning approach. Here we demonstrate how the PrISM methodology identifies individual protein molecules through iterative probing with our multi-affinity probes and present progress toward the estimation of false identification rate of these proteins using a target-decoy based statistical approach.
Combining single-molecule high-density protein nanoarrays with iterative multi-affinity probing, PrISM provides a new tool for quantitative proteomics. We demonstrate identification of proteins using PrISM with the future ability to make comprehensive measurements of intact proteins at single-molecule resolution to accelerate proteomic research.

Authors
Markus Lubeck1, Stephanie Kaspar-Schoenefeld1, Christoph Krisp1, Andreas Schmidt1, Florian Busch1, Eduardo Carrascosa1, Oliver Raether1, Gary Kruppa2, Ganesh Bala3

Institutions
1Bruker Daltonics GmbH & Co. KG, Bremen, Germany; 2Bruker S.R.O., Brno, Czech Republic 3Bruker Scientific LLC, San Jose, CA.

Abstract
Data-Independent Acquisition (DIA) is widely used for proteomics as it usually outperforms Data-Dependent Acquisition (DDA) for protein identification and quantitation, due to its higher ion usage and reproducibility, resulting from a fixed scheme of rather broad isolation windows. This advantage can be further increased by combining it with trapped ion mobility (TIMS), as the additional separation dimension reduces complexity and the sequential elution of condensed ion packages from the TIMS device allows for even more efficient ion usage (dia-PASEF). The two-dimensional mass and mobility space enables method creation with extensively different window schemes. Here, a variety of fixed-width as well as more advanced (py_diAID, slice-PASEF) window schemes were evaluated to determine optimal conditions for speed, sensitivity, and selectivity.