Optimized Workflow for Multiplexed Phosphorylation Analysis of TMT-Labeled Peptides Using High-Field Asymmetric Waveform Ion Mobility Spectrometry

Phosphorylation is a post-translational modification with a vital role in cellular signaling. Isobaric labeling-based strategies, such as tandem mass tags (TMT), can measure the relative phosphorylation states of peptides in a multiplexed format. However, the low stoichiometry of protein phosphorylation constrains the depth of phosphopeptide analysis by mass spectrometry. As such, robust and sensitive workflows are required. Here we evaluate and optimize high-Field Asymmetric waveform Ion Mobility Spectrometry (FAIMS) coupled to Orbitrap Tribrid mass spectrometers for the analysis of TMT-labeled phosphopeptides. We determined that using FAIMS-MS3 with three compensation voltages (CV) in a single method (e.g., CV = −40/–60/–80 V) maximizes phosphopeptide coverage while minimizing inter-CV overlap. Furthermore, consecutive analyses using MSA-CID (multistage activation collision-induced dissociation) and HCD (higher-energy collisional dissociation) fragmentation at the MS2 stage increases the depth of phosphorylation analysis. The methodology and results outlined herein provide a template for tailoring optimized FAIMS-based methods

Optimized Workflow for Multiplexed Phosphorylation Analysis of TMT-Labeled Peptides Using High-Field Asymmetric Waveform Ion Mobility Spectrometry

Phosphorylation is a post-translational modification with a vital role in cellular signaling. Isobaric labeling-based strategies, such as tandem mass tags (TMT), can measure the relative phosphorylation states of peptides in a multiplexed format. However, the low stoichiometry of protein phosphorylation constrains the depth of phosphopeptide analysis by mass spectrometry. As such, robust and sensitive workflows are required. Here we evaluate and optimize high-Field Asymmetric waveform Ion Mobility Spectrometry (FAIMS) coupled to Orbitrap Tribrid mass spectrometers for the analysis of TMT-labeled phosphopeptides. We determined that using FAIMS-MS3 with three compensation voltages (CV) in a single method (e.g., CV = −40/–60/–80 V) maximizes phosphopeptide coverage while minimizing inter-CV overlap. Furthermore, consecutive analyses using MSA-CID (multistage activation collision-induced dissociation) and HCD (higher-energy collisional dissociation) fragmentation at the MS2 stage increases the depth of phosphorylation analysis. The methodology and results outlined herein provide a template for tailoring optimized FAIMS-based methods

Conditional Fragment Ion Probabilities Improve Database Searching for Nonmonoisotopic Precursors

Stochastic, intensity-based precursor isolation can result in isotopically enriched fragment ions. This problem is exacerbated for large peptides and stable isotope labeling experiments using deuterium or 15N. For stable isotope labeling experiments, incomplete and ubiquitous labeling strategies result in the isolation of peptide ions composed of many distinct structural isomers. Unfortunately, existing proteomics search algorithms do not account for this variability in isotopic incorporation, and thus often yield poor peptide and protein identification rates. We sought to resolve this shortcoming by deriving the expected isotopic distributions of each fragment ion and incorporating them into the theoretical mass spectra used for peptide-spectrum-matching. We adapted the Comet search platform to integrate a modified spectral prediction algorithm we term Conditional fragment Ion Distribution Search (CIDS). Comet-CIDS uses a traditional database searching strategy, but for each candidate peptide we compute the isotopic distribution of each fragment to better match the observed m/z distributions. Evaluating previously generated D2O and 15N labeled data sets, we found that Comet-CIDS identified more confident peptide spectral matches and higher protein sequence coverage compared to traditional theoretical spectra generation, with the magnitude of improvement largely determined by the amount of labeling in the sample

Large-Scale and Targeted Quantitative Cross-Linking MS Using Isotope-Labeled Protein Interaction Reporter (PIR) Cross-Linkers

Quantitative measurement of chemically cross-linked proteins is crucial to reveal dynamic information about protein structures and protein–protein interactions and how these are differentially regulated during stress, aging, drug treatment, and most perturbations. Previously, we demonstrated how quantitative in vivo cross-linking (CL) with stable isotope labeling of amino acids in cell culture (SILAC) enables both heritable and dynamic changes in cells to be visualized. In this work, we demonstrate the technical feasibility of proteome-scale quantitative in vivo CL–MS using isotope-labeled protein interaction reporter (PIR) cross-linkers and E. coli as a model system. This isotope-labeled cross-linkers approach, combined with Real-time Analysis of Cross-linked peptide Technology (ReACT) previously developed in our lab, enables the quantification of 941 nonredundant cross-linked peptide pairs from a total of 1213 fully identified peptide pairs in two biological replicate samples through comparison of MS1 peak intensity of the light and heavy cross-linked peptide pairs. For targeted relative quantification of cross-linked peptide pairs, we further developed a PRM-based assay to accurately probe specific site interaction changes in a complex background. The methodology described in this work provides reliable tools for both large-scale and targeted quantitative CL–MS that is useful for any sample where SILAC labeling may not be practical

Large-Scale and Targeted Quantitative Cross-Linking MS Using Isotope-Labeled Protein Interaction Reporter (PIR) Cross-Linkers

Quantitative measurement of chemically cross-linked proteins is crucial to reveal dynamic information about protein structures and protein–protein interactions and how these are differentially regulated during stress, aging, drug treatment, and most perturbations. Previously, we demonstrated how quantitative in vivo cross-linking (CL) with stable isotope labeling of amino acids in cell culture (SILAC) enables both heritable and dynamic changes in cells to be visualized. In this work, we demonstrate the technical feasibility of proteome-scale quantitative in vivo CL–MS using isotope-labeled protein interaction reporter (PIR) cross-linkers and <i>E. coli</i> as a model system. This isotope-labeled cross-linkers approach, combined with Real-time Analysis of Cross-linked peptide Technology (ReACT) previously developed in our lab, enables the quantification of 941 nonredundant cross-linked peptide pairs from a total of 1213 fully identified peptide pairs in two biological replicate samples through comparison of MS¹ peak intensity of the light and heavy cross-linked peptide pairs. For targeted relative quantification of cross-linked peptide pairs, we further developed a PRM-based assay to accurately probe specific site interaction changes in a complex background. The methodology described in this work provides reliable tools for both large-scale and targeted quantitative CL–MS that is useful for any sample where SILAC labeling may not be practical

Parallel Notched Gas-Phase Enrichment for Improved Proteome Identification and Quantification with Fast Spectral Acquisition Rates

Gas-phase fractionation enables better quantitative accuracy, improves signal-to-noise ratios, and increases sensitivity in proteomic analyses. However, traditional gas-phase enrichment, which relies upon a large continuous bin, results in suboptimal enrichment, as most chromatographic separations are not 100% orthogonal relative to the first MS dimension (MS1 m/z). As such, ions with similar m/z values tend to elute at the same retention time, which prevents the partitioning of narrow precursor m/z distributions into a few large continuous gas-phase enrichment bins. To overcome this issue, we developed and tested the use of notched isolation waveforms, which simultaneously isolate multiple discrete m/z windows in parallel (e.g., 650–700 m/z and 800–850 m/z). By comparison to a canonical gas-phase fractionation method, notched waveforms do not require bin optimization via in silico digestion or wasteful sample injections to isolate multiple precursor windows. Importantly, the collection of all m/z bins simultaneously using the isolation waveform does not suffer from the sensitivity and duty cycle pitfalls inherent to sequential collection of multiple m/z bins. Applying a notched injection waveform provided consistent enrichment of precursor ions, which resulted in improved proteome depth with greater coverage of low-abundance proteins. Finally, using a reductive dimethyl labeling approach, we show that notched isolation waveforms increase the number of quantified peptides with improved accuracy and precision across a wider dynamic range

In Vivo Cross-Linking MS Reveals Conservation in OmpA Linkage to Different Classes of β‑Lactamase Enzymes

Molecular interactions between two different classes of β-lactamase enzymes and outer membrane protein A (OmpA) were studied by in vivo chemical cross-linking of a multi-drug-resistant strain of Acinetobacter baumannii AB5075. Class A β-lactamase blaGES-11 and Class D β-lactamase Oxa23, responsible for hydrolysis of different types of β-lactam antibiotics, were found to be cross-linked to similar lysine sites of the periplasmic domain of outer membrane protein OmpA, despite low sequence homology between the two enzymes. The findings from in vivo XL-MS suggest that the interacting surfaces between both β-lactamase enzymes and OmpA are conserved during molecular evolution, and the OmpA C-terminus domain serves an important function of anchoring different types of β-lactamase enzymes in the periplasmic space

In Vivo Cross-Linking MS Reveals Conservation in OmpA Linkage to Different Classes of β‑Lactamase Enzymes

Molecular interactions between two different classes of β-lactamase enzymes and outer membrane protein A (OmpA) were studied by in vivo chemical cross-linking of a multi-drug-resistant strain of Acinetobacter baumannii AB5075. Class A β-lactamase blaGES-11 and Class D β-lactamase Oxa23, responsible for hydrolysis of different types of β-lactam antibiotics, were found to be cross-linked to similar lysine sites of the periplasmic domain of outer membrane protein OmpA, despite low sequence homology between the two enzymes. The findings from in vivo XL-MS suggest that the interacting surfaces between both β-lactamase enzymes and OmpA are conserved during molecular evolution, and the OmpA C-terminus domain serves an important function of anchoring different types of β-lactamase enzymes in the periplasmic space

TomahaqCompanion: A Tool for the Creation and Analysis of Isobaric Label Based Multiplexed Targeted Assays

Triggered by Offset, Multiplexed, Accurate mass, High resolution, and Absolute Quantitation (TOMAHAQ) is a recently introduced targeted proteomics method that combines peptide and sample multiplexing. TOMAHAQ assays enable sensitive and accurate multiplexed quantification by implementing an intricate data collection scheme that comprises multiple MSn scans, mass inclusion lists, and data-driven filters. Consequently, manual creation of TOMAHAQ methods can be time-consuming and error prone, while the resulting TOMAHAQ data may not be compatible with common mass spectrometry analysis pipelines. To address these concerns we introduce TomahaqCompanion, an open-source desktop application that enables rapid creation of TOMAHAQ methods and analysis of TOMAHAQ data. Starting from a list of peptide sequences, a user can perform each step of TOMAHAQ assay development including (1) generation of priming run target list, (2) analysis of priming run data, (3) generation of TOMAHAQ method file, and (4) analysis and export of quantitative TOMAHAQ data. We demonstrate the flexibility of TomahaqCompanion by creating a variety of methods testing TOMAHAQ parameters (e.g., number of SPS notches, run length, etc.). Lastly, we analyze an interference sample comprising heavy yeast peptides, a standard human peptide mixture, TMT11-plex, and super heavy TMT (shTMT) isobaric labels to demonstrate ∼10–200 attomol limit of quantification within a complex background using TOMAHAQ