Improvement of Quantitative Measurements in Multiplex Proteomics Using High-Field Asymmetric Waveform Spectrometry

Enhanced Multiplexing Technology for Proteomics

The identification of thousands of proteins and their relative levels of expression has furthered understanding of biological processes and disease and stimulated new systems biology hypotheses. Quantitative proteomics workflows that rely on analytical assays such as mass spectrometry have facilitated high-throughput measurements of proteins partially due to multiplexing. Multiplexing allows proteome differences across multiple samples to be measured simultaneously, resulting in more accurate quantitation, increased statistical robustness, reduced analysis times, and lower experimental costs. The number of samples that can be multiplexed has evolved from as few as two to more than 50, with studies involving more than 10 samples being denoted as enhanced multiplexing or hyperplexing. In this review, we give an update on emerging multiplexing proteomics techniques and highlight advantages and limitations for enhanced multiplexing strategies.

Hyperplexing Approaches for up to 45-Plex Quantitative Proteomic Analysis

Isobaric labeling has emerged as an indispensable quantitative proteomic approach for its unprecedented multiplexing capacity in a single analysis. Currently, different hyperplexing approaches have been developed to meet the demand for the increasing sample size in large-scale cohort analysis. In this report, we present a tribrid hyperplexing approach by the combinatorial use of three types of isobaric reagents, a novel isobaric tag 16-plex (IBT16) reagent and the widely used tandem mass tag (TMT; TMT11) and TMTpro (TMT18) reagents. After the determination of labeling efficiency and the optimization of testing conditions, we systematically evaluated the identification and quantification performance of the three labeling reagents in both independent and combinatorial manners using the mixtures of E. coli and HeLa peptides with different ratios. Our results reveal that the three reagents are quite similar in all testing aspects despite some differences, and the combination use of the three reagents could expand the multiplexing capacity to up to 45-plex. Furthermore, we conclude the advantages of IBT16 in the combination use and the preferred combinations for different practical applications. Data are available via ProteomeXchange with identifier PXD037498.

Chemical isotope labeling for quantitative proteomics

Advancements in liquid chromatography and mass spectrometry over the last decades have led to a significant development in mass spectrometry-based proteome quantification approaches. An increasingly attractive strategy is multiplex isotope labeling, which significantly improves the accuracy, precision and throughput of quantitative proteomics in the data-dependent acquisition mode. Isotope labeling-based approaches can be classified into MS1-based and MS2-based quantification. In this review, we give an overview of approaches based on chemical isotope labeling and discuss their principles, benefits, and limitations with the goal to give insights into fundamental questions and provide a useful reference for choosing a method for quantitative proteomics. As a perspective, we discuss the current possibilities and limitations of multiplex, isotope labeling approaches for the data-independent acquisition mode, which is increasing in popularity.

Motif-Targeting Phosphoproteome Analysis of Cancer Cells for Profiling Kinase Inhibitors

We present a motif-targeting phosphoproteome analysis workflow utilizing in vitro kinase reaction to enrich a subset of peptides with specific primary sequence motifs. Phosphopeptides are enriched and dephosphorylated with alkaline phosphatase, followed by in vitro kinase reaction to phosphorylate substrate peptides with specific primary-sequence motifs. These phosphopeptides are enriched again, TMT-labeled, dephosphorylated to enhance MS-detectability, and analyzed by LC/MS/MS. We applied this approach to inhibitor-treated cancer cells, and successfully profiled the inhibitory spectra of multiple kinase inhibitors. We anticipate this approach will be applicable to target specific subsets of the phosphoproteome using the wide variety of available recombinant protein kinases.

IsobaricQuant enables cross-platform quantification, visualization, and filtering of isobarically-labeled peptides

In mass spectrometry (MS)-based quantitative proteomics, labeling with isobaric mass tags such as iTRAQ and TMT can substantially improve sample throughput and reduce peptide missing values. Nonetheless, the quantification of labeled peptides tends to suffer from reduced accuracy due to the co-isolation of co-eluting precursors of similar mass-to-charge. Acquisition approaches such as multistage MS3 or ion mobility separation address this problem, yet are difficult to audit and limited to expensive instrumentation. Here we introduce IsobaricQuant, an open-source software tool for quantification, visualization, and filtering of peptides labeled with isobaric mass tags, with specific focus on precursor interference. IsobaricQuant is compatible with MS2 and MS3 acquisition strategies, has a viewer that allows assessing interference, and provides several scores to aid the filtering of scans with compression. We demonstrate that IsobaricQuant quantifications are accurate by comparing it with commonly used software. We further show that its QC scores can successfully filter out scans with reduced quantitative accuracy at MS2 and MS3 levels, removing inaccurate peptide quantifications and decreasing protein CVs. Finally, we apply IsobaricQuant to a PISA dataset and show that QC scores improve the sensitivity of the identification of protein targets of a kinase inhibitor. IsobaricQuant is available at https://github.com/Villen-Lab/isobaricquant.

Comparative Assessment of Quantification Methods for Tumor Tissue Phosphoproteomics

With increasing sensitivity and accuracy in mass spectrometry, the tumor phosphoproteome is getting into reach. However, the selection of quantitation techniques best-suited to the biomedical question and diagnostic requirements remains a trial and error decision as no study has directly compared their performance for tumor tissue phosphoproteomics. We compared label-free quantification (LFQ), spike-in-SILAC (stable isotope labeling by amino acids in cell culture), and tandem mass tag (TMT) isobaric tandem mass tags technology for quantitative phosphosite profiling in tumor tissue. Compared to the classic SILAC method, spike-in-SILAC is not limited to cell culture analysis, making it suitable for quantitative analysis of tumor tissue samples. TMT offered the lowest accuracy and the highest precision and robustness toward different phosphosite abundances and matrices. Spike-in-SILAC offered the best compromise between these features but suffered from a low phosphosite coverage. LFQ offered the lowest precision but the highest number of identifications. Both spike-in-SILAC and LFQ presented susceptibility to matrix effects. Match between run (MBR)-based analysis enhanced the phosphosite coverage across technical replicates in LFQ and spike-in-SILAC but further reduced the precision and robustness of quantification. The choice of quantitative methodology is critical for both study design such as sample size in sample groups and quantified phosphosites and comparison of published cancer phosphoproteomes. Using ovarian cancer tissue as an example, our study builds a resource for the design and analysis of quantitative phosphoproteomic studies in cancer research and diagnostics.

Real-Time Search-Assisted Acquisition on a Tribrid Mass Spectrometer Improves Coverage in Multiplexed Single-Cell Proteomics

In the young field of single-cell proteomics (scMS), there is a great need for improved global proteome characterization, both in terms of proteins quantified per cell and quantitative performance thereof. The recently introduced real-time search (RTS) on the Orbitrap Eclipse Tribrid mass spectrometer in combination with SPS-MS3 acquisition has been shown to be beneficial for the measurement of samples that are multiplexed using isobaric tags. Multiplexed scMS requires high ion injection times and high-resolution spectra to quantify the single-cell signal; however, the carrier channel facilitates peptide identification and thus offers the opportunity for fast on-the-fly precursor filtering before committing to the time-intensive quantification scan. Here, we compared classical MS2 acquisition against RTS-SPS-MS3, both using the Orbitrap Eclipse Tribrid MS with the FAIMS Pro ion mobility interface and present a new acquisition strategy termed RETICLE (RTS enhanced quant of single cell spectra) that makes use of fast real-time searched linear ion trap scans to preselect MS1 peptide precursors for quantitative MS2 Orbitrap acquisition. We show that classical MS2 acquisition is outperformed by both RTS-SPS-MS3 through increased quantitative accuracy at similar proteome coverage, and RETICLE through higher proteome coverage, with the latter enabling the quantification of over 1000 proteins per cell at an MS2 injection time of 750 ms using a 2 h gradient.

Proximity labeling for investigating protein-protein interactions

The study of protein complexes and protein-protein interactions is of great importance due to their fundamental roles in cellular function. Proximity labeling, often coupled with mass spectrometry, has become a powerful and versatile tool for studying protein-protein interactions by enriching and identifying proteins in the vicinity of a specified protein-of-interest. Here, we describe and compare traditional approaches to investigate protein-protein interactions to current day state-of-the-art proximity labeling methods. We focus on the wide array of proximity labeling strategies and underscore studies using diverse model systems to address numerous biological questions. In addition, we highlight current advances in mass spectrometry-based technology that exhibit promise in improving the depth and breadth of the data acquired in proximity labeling experiments. In all, we show the diversity of proximity labeling strategies and emphasize the broad range of applications and biological inquiries that can be addressed using this technology.

Trapped Ion Mobility Spectrometry Reduces Spectral Complexity in Mass Spectrometry-Based Proteomics

In bottom-up mass spectrometry-based proteomics, deep proteome coverage is limited by high cofragmentation rates. Cofragmentation occurs when more than one analyte is isolated by the quadrupole and the subsequent fragmentation event produces fragment ions of heterogeneous origin. One strategy to reduce cofragmentation rates is through effective peptide separation techniques such as chromatographic separation and, the more recently popularized, ion mobility (IM) spectrometry, which separates peptides by their collisional cross section. Here, we use a computational model to investigate the capability of the trapped IM spectrometry (TIMS) device at effectively separating peptide ions and quantify the separation power of the TIMS device in the context of a parallel accumulation-serial fragmentation (PASEF) workflow. We found that TIMS separation increases the number of interference-free MS1 peptide features 9.2-fold, while decreasing the average peptide density in precursor spectra 6.5-fold. In a data-dependent acquisition PASEF workflow, IM separation increases the number of spectra without cofragmentation by a factor of 4.1 and the number of high-quality spectra 17-fold. Using a categorical model, we estimate that this observed decrease in spectral complexity results in an increased likelihood for peptide spectral matches, which may improve peptide identification rates. In the context of a data-independent acquisition workflow, the reduction in spectral complexity resulting from IM separation is estimated to be equivalent to a 4-fold decrease in the isolation window width (from 25 to 6.5 Da). Our study demonstrates that TIMS separation decreases spectral complexity by reducing cofragmentation rates, suggesting that TIMS separation may contribute toward the high identification rates observed in PASEF workflows.

Strategies for mass spectrometry-based phosphoproteomics using isobaric tagging

INTRODUCTION

Protein phosphorylation is a primary mechanism of signal transduction in cellular systems. Isobaric tagging can be used to investigate alterations in phosphorylation events in sample multiplexing experiments where quantification extends across all conditions. As such, innovations in tandem mass tag methods can facilitate the expansion of the depth and breadth of phosphoproteomic analyses.

AREAS COVERED

This review discusses the current state of tandem mass tag-centric phosphoproteomics and highlights advances in reagent chemistry, instrumentation, data acquisition, and data analysis. We stress that approaches for phosphoproteomic investigations require high-specificity enrichment, sensitive detection, and accurate phosphorylation site localization.

EXPERT OPINION

Tandem mass tag-centric phosphoproteomics will continue to be an important conduit for our understanding of signal transduction in living organisms. We anticipate that progress in phosphopeptide enrichment methodologies, enhancements in instrumentation and data acquisition technologies, and further refinements in analytical strategies will be key to the discovery of biologically relevant findings from phosphoproteomics studies.

Identification of tumor antigens with immunopeptidomics

The identification of actionable tumor antigens is indispensable for the development of several cancer immunotherapies, including T cell receptor-transduced T cells and patient-specific mRNA or peptide vaccines. Most known tumor antigens have been identified through extensive molecular characterization and are considered canonical if they derive from protein-coding regions of the genome. By eluting human leukocyte antigen-bound peptides from tumors and subjecting these to mass spectrometry analysis, the peptides can be identified by matching the resulting spectra against reference databases. Recently, mass-spectrometry-based immunopeptidomics has enabled the discovery of noncanonical antigens-antigens derived from sequences outside protein-coding regions or generated by noncanonical antigen-processing mechanisms. Coupled with transcriptomics and ribosome profiling, this method enables the identification of thousands of noncanonical peptides, of which a substantial fraction may be detected exclusively in tumors. Spectral matching against the immense noncanonical reference may generate false positives. However, sensitive mass spectrometry, analytical validation and advanced bioinformatics solutions are expected to uncover the full landscape of presented antigens and clinically relevant targets.

Quantitative Proteomics Using Isobaric Labeling: A Practical Guide

In the past decade, relative proteomic quantification using isobaric labeling technology has developed into a key tool for comparing the expression of proteins in biological samples. Although its multiplexing capacity and flexibility make this a valuable technology for addressing various biological questions, its quantitative accuracy and precision still pose significant challenges to the reliability of its quantification results. Here, we give a detailed overview of the different kinds of isobaric mass tags and the advantages and disadvantages of the isobaric labeling method. We also discuss which precautions should be taken at each step of the isobaric labeling workflow, to obtain reliable quantification results in large-scale quantitative proteomics experiments. In the last section, we discuss the broad applications of the isobaric labeling technology in biological and clinical studies, with an emphasis on thermal proteome profiling and proteogenomics.

Nanoscale Solid-Phase Isobaric Labeling for Multiplexed Quantitative Phosphoproteomics

We established a workflow for highly sensitive multiplexed quantitative phosphoproteomics using a nanoscale solid-phase tandem mass tag (TMT) labeling reactor. Phosphopeptides were first enriched by titanium oxide chromatography and then labeled with isobaric TMT reagents in a StageTip packed with hydrophobic polymer-based sorbents. We found that TMT-labeled singly phosphorylated peptides tend to flow through the titanium oxide column. Therefore, TMT labeling should be performed after the enrichment step from tryptic peptides, resulting in the need for microscale reactions with small amounts of phosphopeptides. Using an optimized protocol for tens to hundreds of nanograms of phosphopeptides, we obtained a nearly 10-fold increase in sensitivity compared to the conventional solution-based TMT protocol. We demonstrate that this nanoscale phosphoproteomics protocol works for 50 μg of HeLa proteins treated with selumetinib, and we successfully quantified the selumetinib-regulated phosphorylated sites on a proteome scale. The MS raw data files have been deposited with the ProteomeXchange Consortium via the jPOST partner repository (https://jpostdb.org) with the data set identifier PXD025536.

Evaluation and Optimization of High-Field Asymmetric Waveform Ion-Mobility Spectrometry for Multiplexed Quantitative Site-Specific N-Glycoproteomics

The heterogeneity and complexity of glycosylation hinder the depth of site-specific glycoproteomics analysis. High-field asymmetric-waveform ion-mobility spectrometry (FAIMS) has been shown to improve the scope of bottom-up proteomics. The benefits of FAIMS for quantitative N-glycoproteomics have not been investigated yet. In this work, we optimized FAIMS settings for N-glycopeptide identification, with or without the tandem mass tag (TMT) label. The optimized FAIMS approach significantly increased the identification of site-specific N-glycopeptides derived from the purified immunoglobulin M (IgM) protein or human lymphoma cells. We explored in detail the changes in FAIMS mobility caused by N-glycopeptides with different characteristics, including TMT labeling, charge state, glycan type, peptide sequence, glycan size, and precursor m/z. Importantly, FAIMS also improved multiplexed N-glycopeptide quantification, both with the standard MS2 acquisition method and with our recently developed Glyco-SPS-MS3 method. The combination of FAIMS and Glyco-SPS-MS3 methods provided the highest quantitative accuracy and precision. Our results demonstrate the advantages of FAIMS for improved mass spectrometry-based qualitative and quantitative N-glycoproteomics.

Quantitative single-cell proteomics as a tool to characterize cellular hierarchies

Large-scale single-cell analyses are of fundamental importance in order to capture biological heterogeneity within complex cell systems, but have largely been limited to RNA-based technologies. Here we present a comprehensive benchmarked experimental and computational workflow, which establishes global single-cell mass spectrometry-based proteomics as a tool for large-scale single-cell analyses. By exploiting a primary leukemia model system, we demonstrate both through pre-enrichment of cell populations and through a non-enriched unbiased approach that our workflow enables the exploration of cellular heterogeneity within this aberrant developmental hierarchy. Our approach is capable of consistently quantifying ~1000 proteins per cell across thousands of individual cells using limited instrument time. Furthermore, we develop a computational workflow (SCeptre) that effectively normalizes the data, integrates available FACS data and facilitates downstream analysis. The approach presented here lays a foundation for implementing global single-cell proteomics studies across the world.

Recent technical progress in sample preparation and liquid-phase separation-mass spectrometry for proteomic analysis of mass-limited samples

Mass spectrometry (MS)-based proteomics has enabled the identification and quantification of thousands of proteins from complex proteomes in a single experiment. However, its performance for mass-limited proteome samples (e.g., single cells and tissue samples from laser capture microdissection) is still not satisfying. The development of novel proteomic methodologies with better overall sensitivity is vital. During the last several years, substantial technical progress has been achieved for the preparation and liquid-phase separation-MS characterization of mass-limited proteome samples. In this review, we summarize recent technological progress of sample preparation, liquid chromatography (LC)-MS, capillary zone electrophoresis (CZE)-MS and MS instrumentation for bottom-up proteomics of trace biological samples, highlight some exciting applications of the novel techniques for single-cell proteomics, and provide a very brief perspective about the field at the end.

Strain-Specific Peptide (SSP) Interference Reference Sample: A Genetically Encoded Quality Control for Isobaric Tagging Strategies

Isobaric tag-based sample multiplexing strategies are extensively used for global protein abundance profiling. However, such analyses are often confounded by ratio compression resulting from the co-isolation, co-fragmentation, and co-quantification of co-eluting peptides, termed "interference." Recent analytical strategies incorporating ion mobility and real-time database searching have helped to alleviate interference, yet further assessment is needed. Here, we present the strain-specific peptide (SSP) interference reference sample, a tandem mass tag (TMT)pro-labeled quality control that leverages the genetic variation in the proteomes of eight phylogenetically divergent mouse strains. Typically, a peptide with a missense mutation has a different mass and retention time than the reference or native peptide. TMT reporter ion signal for the native peptide in strains that encode the mutant peptide suggests interference which can be quantified and assessed using the interference-free index (IFI). We introduce the SSP by investigating interference in three common data acquisition methods and by showcasing improvements in the IFI when using ion mobility-based gas-phase fractionation. In addition, we provide a user-friendly, online viewer to visualize the data and streamline the calculation of the IFI. The SSP will aid in developing and optimizing isobaric tag-based experiments.

Benchmarking Quantitative Performance in Label-Free Proteomics

Previous benchmarking studies have demonstrated the importance of instrument acquisition methodology and statistical analysis on quantitative performance in label-free proteomics. However, the effects of these parameters in combination with replicate number and false discovery rate (FDR) corrections are not known. Using a benchmarking standard, we systematically evaluated the combined impact of acquisition methodology, replicate number, statistical approach, and FDR corrections. These analyses reveal a complex interaction between these parameters that greatly impacts the quantitative fidelity of protein- and peptide-level quantification. At a high replicate number (n = 8), both data-dependent acquisition (DDA) and data-independent acquisition (DIA) methodologies yield accurate protein quantification across statistical approaches. However, at a low replicate number (n = 4), only DIA in combination with linear models for microarrays (LIMMA) and reproducibility-optimized test statistic (ROTS) produced a high level of quantitative fidelity. Quantitative accuracy at low replicates is also greatly impacted by FDR corrections, with Benjamini-Hochberg and Storey corrections yielding variable true positive rates for DDA workflows. For peptide quantification, replicate number and acquisition methodology are even more critical. A higher number of replicates in combination with DIA and LIMMA produce high quantitative fidelity, while DDA performs poorly regardless of replicate number or statistical approach. These results underscore the importance of pairing instrument acquisition methodology with the appropriate replicate number and statistical approach for optimal quantification performance.

HYpro16: A Two-Proteome Mixture to Assess Interference in Isobaric Tag-Based Sample Multiplexing Experiments

Isobaric tagging is a powerful strategy for global proteome profiling. A caveat of isobaric-tag-based quantification is "interference", which may be caused by coeluting peptides that are coisolated, cofragmented, and coanalyzed, thereby confounding quantitative accuracy. Here, we present a two-proteome standard that challenges the mass spectrometer to measure a range of protein abundance ratios in a background of potential interference. The HYpro16 standard consists of tandem mass tag (TMT) pro16-labeled human peptides at a 1:1 ratio across all channels into which is spiked TMTpro16-labeled yeast peptides in triplicate at 20:1, 10:1, 4:1, and 2:1 ratios. We showcase the HYpro16 standard by (1) altering the MS2 isolation window width and (2) examining different data acquisition methods (hrMS2, SPS-MS3, RTS-MS3). Our data illustrate that wider isolation widths moderately increase the TMT signal, the benefits of which are offset by decreased ratio accuracy. We also show that using real-time database searching (RTS)-MS3 resulted in the most accurate ratios. Additionally, the number of quantified yeast proteins using RTS-MS3 approaches that of hrMS2 when using a yeast-specific database for real-time searching. In short, this quality control standard allows for the assessment of multiple quantitative measurements within a single run, which can be compared across instruments to benchmark and track performance.

N-Terminomics for the Identification of In Vitro Substrates and Cleavage Site Specificity of the SARS-CoV-2 Main Protease

The genome of coronaviruses, including SARS‐CoV‐2, encodes for two proteases, a papain like (PL^pro) protease and the so‐called main protease (M^pro), a chymotrypsin‐like cysteine protease, also named 3CL^pro or non‐structural protein 5 (nsp5). M^pro is activated by autoproteolysis and is the main protease responsible for cutting the viral polyprotein into functional units. Aside from this, it is described that M^pro proteases are also capable of processing host proteins, including those involved in the host innate immune response. To identify substrates of the three main proteases from SARS‐CoV, SARS‐CoV‐2, and hCoV‐NL63 coronviruses, an LC‐MS based N‐terminomics in vitro analysis is performed using recombinantly expressed proteases and lung epithelial and endothelial cell lysates as substrate pools. For SARS‐CoV‐2 M^pro, 445 cleavage events from more than 300 proteins are identified, while 151 and 331 M^pro derived cleavage events are identified for SARS‐CoV and hCoV‐NL63, respectively. These data enable to better understand the cleavage site specificity of the viral proteases and will help to identify novel substrates in vivo. All data are available via ProteomeXchange with identifier PXD021406.

Isobaric Tag-Based Protein Profiling across Eight Human Cell Lines Using High-Field Asymmetric Ion Mobility Spectrometry and Real-Time Database Searching

A vast number of human cell lines are available for cell culture model-based studies, and as such the potential exists for discrepancies in findings due to cell line selection. To investigate this concept, the authors determine the relative protein abundance profiles of a panel of eight diverse, but commonly studied human cell lines. This panel includes HAP1, HEK293T, HeLa, HepG2, Jurkat, Panc1, SH-SY5Y, and SVGp12. A mass spectrometry-based proteomics workflow designed to enhance quantitative accuracy while maintaining analytical depth is used. To this end, this strategy leverages TMTpro16-based sample multiplexing, high-field asymmetric ion mobility spectrometry, and real-time database searching. The data show that the differences in the relative protein abundance profiles reflect cell line diversity. The authors also determine several hundred proteins to be highly enriched for a given cell line, and perform gene ontology and pathway analysis on these cell line-enriched proteins. An R Shiny application is designed to query protein abundance profiles and retrieve proteins with similar patterns. The workflows used herein can be applied to additional cell lines to aid cell line selection for addressing a given scientific inquiry or for improving an experimental design.

Improved Sensitivity of Ultralow Flow LC-MS-Based Proteomic Profiling of Limited Samples Using Monolithic Capillary Columns and FAIMS Technology

In this work, we pioneered a combination of ultralow flow (ULF) high-efficiency ultranarrow bore monolithic LC columns coupled to MS via a high-field asymmetric waveform ion mobility spectrometry (FAIMS) interface to evaluate the potential applicability for high sensitivity, robust, and reproducible proteomic profiling of low nanogram-level complex biological samples. As a result, ULF LC-FAIMS-MS brought unprecedented sensitivity levels and high reproducibility in bottom-up proteomic profiling. In addition, FAIMS improved the dynamic range, signal-to-noise ratios, and detection limits in ULF LC-MS-based measurements by significantly reducing chemical noise in comparison to the conventional nanoESI interface used with the same ULF LC-MS setup. Two, three, or four compensation voltages separated by at least 15 V were tested within a single LC-MS run using the FAIMS interface. The optimized ULF LC-ESI-FAIMS-MS/MS conditions resulted in identification of 2,348 ± 42 protein groups, 10,062 ± 285 peptide groups, and 15,734 ± 350 peptide-spectrum matches for 1 ng of a HeLa digest, using a 1 h gradient at the flow rate of 12 nL/min, which represents an increase by 38%, 91%, and 131% in respective identifications, as compared to the control experiment (without FAIMS). To evaluate the practical utility of the ULF LC-ESI-FAIMS-MS platform in proteomic profiling of limited samples, approximately 100, 1,000, and 10,000 U937 myeloid leukemia cells were processed, and a one-tenth of each sample was analyzed. Using the optimized conditions, we were able to reliably identify 251 ± 54, 1,135 ± 80, and 2,234 ± 25 protein groups from injected aliquots corresponding to ∼10, 100, and 1,000 processed cells.

Evaluation of the Potential Risk of Advanced Peak Determination in Distorting Isobaric Labeling-Based Single-Shot Proteome Quantitation

The recent development and implementation of the advanced peak determination (APD) algorithm with MS instrument dramatically increased the sampling of low abundance features for MS/MS fragmentation. After in-depth evaluation, it is found that with APD on, many chimeric spectra are acquired through co-fragmentation of high abundance contaminants with low abundance targets, and such co-fragmentations are largely avoided when APD is off. To evaluate whether such a co-fragmentation could significantly distort the accuracy of the isobaric-labeling based quantitation of the low abundance target, a single-shot TMT experiment is performed using a two-proteome model, whereby each TMT channel contains premixed peptides from human and a cyanobacterium with a known ratio. Unexpectedly, it is found that APD does not significantly distort TMT ratios, probably because the majority of the APD-specific chimeric spectra are not identifiable. Nevertheless, a few examples of significant distortion of TMT ratios of low abundance peptides caused by APD is found through manual inspection, and suggests that APD should be off in a single-shot TMT experiment to avoid the laborious and time-costing manual inspection.

Full-Featured, Real-Time Database Searching Platform Enables Fast and Accurate Multiplexed Quantitative Proteomics

Multiplexed quantitative analyses of complex proteomes enable deep biological insight. While a multitude of workflows have been developed for multiplexed analyses, the most quantitatively accurate method (SPS-MS3) suffers from long acquisition duty cycles. We built a new, real-time database search (RTS) platform, Orbiter, to combat the SPS-MS3 method's longer duty cycles. RTS with Orbiter eliminates SPS-MS3 scans if no peptide matches to a given spectrum. With Orbiter's online proteomic analytical pipeline, which includes RTS and false discovery rate analysis, it was possible to process a single spectrum database search in less than 10 ms. The result is a fast, functional means to identify peptide spectral matches using Comet, filter these matches, and more efficiently quantify proteins of interest. Importantly, the use of Comet for peptide spectral matching allowed for a fully featured search, including analysis of post-translational modifications, with well-known and extensively validated scoring. These data could then be used to trigger subsequent scans in an adaptive and flexible manner. In this work we tested the utility of this adaptive data acquisition platform to improve the efficiency and accuracy of multiplexed quantitative experiments. We found that RTS enabled a 2-fold increase in mass spectrometric data acquisition efficiency. Orbiter's RTS quantified more than 8000 proteins across 10 proteomes in half the time of an SPS-MS3 analysis (18 h for RTS, 36 h for SPS-MS3).

A Compact Quadrupole-Orbitrap Mass Spectrometer with FAIMS Interface Improves Proteome Coverage in Short LC Gradients

State-of-the-art proteomics-grade mass spectrometers can measure peptide precursors and their fragments with ppm mass accuracy at sequencing speeds of tens of peptides per second with attomolar sensitivity. Here we describe a compact and robust quadrupole-orbitrap mass spectrometer equipped with a front-end High Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Interface. The performance of the Orbitrap Exploris 480 mass spectrometer is evaluated in data-dependent acquisition (DDA) and data-independent acquisition (DIA) modes in combination with FAIMS. We demonstrate that different compensation voltages (CVs) for FAIMS are optimal for DDA and DIA, respectively. Combining DIA with FAIMS using single CVs, the instrument surpasses 2500 peptides identified per minute. This enables quantification of >5000 proteins with short online LC gradients delivered by the Evosep One LC system allowing acquisition of 60 samples per day. The raw sensitivity of the instrument is evaluated by analyzing 5 ng of a HeLa digest from which >1000 proteins were reproducibly identified with 5 min LC gradients using DIA-FAIMS. To demonstrate the versatility of the instrument, we recorded an organ-wide map of proteome expression across 12 rat tissues quantified by tandem mass tags and label-free quantification using DIA with FAIMS to a depth of >10,000 proteins.

Quantitative Proteomics Reveals Distinct Molecular Signatures of Different Cerebellum-Dependent Learning Paradigms

The cerebellum improves motor performance by adjusting motor gain appropriately. As de novo protein synthesis is essential for the formation and retention of memories, we hypothesized that motor learning in the opposite direction would induce a distinct pattern of protein expression in the cerebellum. We conducted quantitative proteomic profiling to compare the level of protein expression in the cerebellum at 1 and 24 h after training from mice that underwent different paradigms of cerebellum-dependent oculomotor learning from specific directional changes in motor gain. We quantified a total of 43 proteins that were significantly regulated in each of the three learning paradigms in the cerebellum at 1 and 24 h after learning. In addition, functional enrichment analysis identified protein groups that were differentially enriched or depleted in the cerebellum at 24 h after the three oculomotor learnings, suggesting that distinct biological pathways may be engaged in the formation of three oculomotor memories. Weighted correlation network analysis discovered groups of proteins significantly correlated with oculomotor memory. Finally, four proteins (Snca, Sncb, Cttn, and Stmn1) from the protein group correlated with the learning amount after oculomotor training were validated by Western blot. This study provides a comprehensive and unbiased list of proteins related to three cerebellum-dependent motor learning paradigms, suggesting the distinct nature of protein expression in the cerebellum for each learning paradigm. The proteomics data have been deposited to the ProteomeXchange Consortium with identifiers <PXD008433>.

Purification and enrichment of specific chromatin loci

Understanding how chromatin is regulated is essential to fully grasp genome biology, and establishing the locus-specific protein composition is a major step toward this goal. Here we explain why the isolation and analysis of a specific chromatin segment are technically challenging, independently of the method. We then describe the published strategies and discuss their advantages and limitations. We conclude by discussing why significant technology developments are required to unambiguously describe the composition of small single loci.

Progress and pitfalls of using isobaric mass tags for proteome profiling

Introduction: Quantitative proteomics using mass spectrometry is performed via label-free or label-based approaches. Labeling strategies rely on the incorporation of stable heavy isotopes by metabolic, enzymatic, or chemical routes. Isobaric labeling uses chemical labels of identical masses but of different fragmentation behaviors to allow the relative quantitative comparison of peptide/protein abundances between biological samples.Areas covered: We have carried out a systematic review on the use of isobaric mass tags in proteomic research since their inception in 2003. We focused on their quantitative performances, their multiplexing evolution, as well as their broad use for relative quantification of proteins in pre-clinical models and clinical studies. Current limitations, primarily linked to the quantitative ratio distortion, as well as state-of-the-art and emerging solutions to improve their quantitative readouts are discussed.Expert opinion: The isobaric mass tag technology offers a unique opportunity to compare multiple protein samples simultaneously, allowing higher sample throughput and internal relative quantification for improved trueness and precision. Large studies can be performed when shared reference samples are introduced in multiple experiments. The technology is well suited for proteome profiling in the context of proteomic discovery studies.

Removal of Interference MS/MS Spectra for Accurate Quantification in Isobaric Tag-Based Proteomics

Rapid progress in mass spectrometry (MS) has made comprehensive analyses of the proteome possible, but accurate quantification remains challenging. Isobaric tags for relative and absolute quantification (iTRAQ) is widely used as a tool to quantify proteins expressed in different cell types and various cellular conditions. The quantification precision of iTRAQ is quite high, but the accuracy dramatically decreases in the presence of interference peptides that are coeluted and coisolated with the target peptide. Here, we developed "removal of interference mixture MS/MS spectra (RiMS)" to improve the quantification accuracy of isobaric tag approaches. The presence of spectrum interference is judged by examining the overlap in the elution time of all scanned precursor ions. Removal of this interference decreased protein identification (11% loss) but improved quantification accuracy. Further, RiMS does not require any specialized equipment, such as MS³ instruments or an additional ion separation mode. Finally, we demonstrated that RiMS can be used to quantitatively compare human-induced pluripotent stem cells and human dermal fibroblasts, as it revealed differential protein expressions that reflect the biological characteristics of the cells.

Characterization and Optimization of Multiplexed Quantitative Analyses Using High-Field Asymmetric-Waveform Ion Mobility Mass Spectrometry

Multiplexed, isobaric tagging methods are powerful techniques to increase throughput, precision, and accuracy in quantitative proteomics. The dynamic range and accuracy of quantitation, however, can be limited by coisolation of tag-containing peptides that release reporter ions and conflate quantitative measurements across precursors. Methods to alleviate these effects often lead to the loss of protein and peptide identifications through online or offline filtering of interference containing spectra. To alleviate this effect, high-Field Asymmetric-waveform Ion Mobility Spectroscopy (FAIMS) has been proposed as a method to reduce precursor coisolation and improve the accuracy and dynamic range of multiplex quantitation. Here we tested the use of FAIMS to improve quantitative accuracy using previously established TMT-based interference standards (triple-knockout [TKO] and Human-Yeast Proteomics Resource [HYPER]). We observed that FAIMS robustly improved the quantitative accuracy of both high-resolution MS² (HRMS²) and synchronous precursor selection MS³ (SPS-MS³)-based methods without sacrificing protein identifications. We further optimized and characterized the main factors that enable robust use of FAIMS for multiplexed quantitation. We highlight these factors and provide method recommendations to take advantage of FAIMS technology to improve isobaric-tag-quantification moving forward.

A Novel Differential Ion Mobility Device Expands the Depth of Proteome Coverage and the Sensitivity of Multiplex Proteomic Measurements

The depth of proteomic analyses is often limited by the overwhelming proportion of confounding background ions that compromise the identification and quantification of low abundance peptides. To alleviate these limitations, we present a new high field asymmetric waveform ion mobility spectrometry (FAIMS) interface that can be coupled to the Orbitrap Tribrid mass spectrometers. The interface provides several advantages over previous generations of FAIMS devices, including ease of operation, robustness, and high ion transmission. Replicate LC-FAIMS-MS/MS analyses (n = 100) of HEK293 protein digests showed stable ion current over extended time periods with uniform peptide identification on more than 10,000 distinct peptides. For complex tryptic digest analyses, the coupling of FAIMS to LC-MS/MS enabled a 30% gain in unique peptide identification compared with non-FAIMS experiments. Improvement in sensitivity facilitated the identification of low abundance peptides, and extended the limit of detection by almost an order of magnitude. The reduction in chimeric MS/MS spectra using FAIMS also improved the precision and the number of quantifiable peptides when using isobaric labeling with tandem mass tag (TMT) 10-plex reagent. We compared quantitative proteomic measurements for LC-MS/MS analyses performed using synchronous precursor selection (SPS) and LC-FAIMS-MS/MS to profile the temporal changes in protein abundance of HEK293 cells following heat shock for periods up to 9 h. FAIMS provided 2.5-fold increase in the number of quantifiable peptides compared with non-FAIMS experiments (30,848 peptides from 2,646 proteins for FAIMS versus 12,400 peptides from 1,229 proteins with SPS). Altogether, the enhancement in ion transmission and duty cycle of the new FAIMS interface extended the depth and comprehensiveness of proteomic analyses and improved the precision of quantitative measurements.

Reproducible workflow for multiplexed deep-scale proteome and phosphoproteome analysis of tumor tissues by liquid chromatography-mass spectrometry

Here we present an optimized workflow for global proteome and phosphoproteome analysis of tissues or cell lines that uses isobaric tags (TMT (tandem mass tags)-10) for multiplexed analysis and relative quantification, and provides 3× higher throughput than iTRAQ (isobaric tags for absolute and relative quantification)-4-based methods with high intra- and inter-laboratory reproducibility. The workflow was systematically characterized and benchmarked across three independent laboratories using two distinct breast cancer subtypes from patient-derived xenograft models to enable assessment of proteome and phosphoproteome depth and quantitative reproducibility. Each plex consisted of ten samples, each being 300 μg of peptide derived from <50 mg of wet-weight tissue. Of the 10,000 proteins quantified per sample, we could distinguish 7,700 human proteins derived from tumor cells and 3100 mouse proteins derived from the surrounding stroma and blood. The maximum deviation across replicates and laboratories was <7%, and the inter-laboratory correlation for TMT ratio-based comparison of the two breast cancer subtypes was r > 0.88. The maximum deviation for the phosphoproteome coverage was <24% across laboratories, with an average of >37,000 quantified phosphosites per sample and differential quantification correlations of r > 0.72. The full procedure, including sample processing and data generation, can be completed within 10 d for ten tissue samples, and 100 samples can be analyzed in ~4 months using a single LC-MS/MS instrument. The high quality, depth, and reproducibility of the data obtained both within and across laboratories should enable new biological insights to be obtained from mass spectrometry-based proteomics analyses of cells and tissues together with proteogenomic data integration.

Gas-Phase Enrichment of Multiply Charged Peptide Ions by Differential Ion Mobility Extend the Comprehensiveness of SUMO Proteome Analyses

The small ubiquitin-like modifier (SUMO) is a member of the family of ubiquitin-like modifiers (UBLs) and is involved in important cellular processes, including DNA damage response, meiosis and cellular trafficking. The large-scale identification of SUMO peptides in a site-specific manner is challenging not only because of the low abundance and dynamic nature of this modification, but also due to the branched structure of the corresponding peptides that further complicate their identification using conventional search engines. Here, we exploited the unusual structure of SUMO peptides to facilitate their separation by high-field asymmetric waveform ion mobility spectrometry (FAIMS) and increase the coverage of SUMO proteome analysis. Upon trypsin digestion, branched peptides contain a SUMO remnant side chain and predominantly form triply protonated ions that facilitate their gas-phase separation using FAIMS. We evaluated the mobility characteristics of synthetic SUMO peptides and further demonstrated the application of FAIMS to profile the changes in protein SUMOylation of HEK293 cells following heat shock, a condition known to affect this modification. FAIMS typically provided a 10-fold improvement of detection limit of SUMO peptides, and enabled a 36% increase in SUMO proteome coverage compared to the same LC-MS/MS analyses performed without FAIMS. Graphical Abstract ᅟ.

Benchmarking common quantification strategies for large-scale phosphoproteomics

Comprehensive mass spectrometry (MS)-based proteomics is now feasible, but reproducible quantification remains challenging, especially for post-translational modifications such as phosphorylation. Here, we compare the most popular quantification techniques for global phosphoproteomics: label-free quantification (LFQ), stable isotope labeling by amino acids in cell culture (SILAC) and MS²- and MS³-measured tandem mass tags (TMT). In a mixed species comparison with fixed phosphopeptide ratios, we find LFQ and SILAC to be the most accurate techniques. MS²-based TMT yields the highest precision but lowest accuracy due to ratio compression, which MS³-based TMT can partly rescue. However, MS²-based TMT outperforms MS³-based TMT when analyzing phosphoproteome changes in the DNA damage response, since its higher precision and larger identification numbers allow detection of a greater number of significantly regulated phosphopeptides. Finally, we utilize the TMT multiplexing capabilities to develop an algorithm for determining phosphorylation site stoichiometry, showing that such applications benefit from the high accuracy of MS³-based TMT.

Quantitative phosphoproteomics has become a standard method in molecular and cell biology. Here, the authors compare performance and parameters of phosphoproteome quantification by LFQ, SILAC, and MS²-/MS³-based TMT and introduce a TMT-adapted algorithm for calculating phosphorylation site stoichiometry.