Overcoming the detrimental O-acylation in TMTpro labeling improves the proteome depth and quantification precision

BACKGROUND

With the advent of proline-based reporter isobaric Tandem Mass Tag (TMTpro) reagents, the sample multiplexing capacity of tandem mass tags (TMTs) has been expanded, and up to 18 samples can be quantified in a multiplexed manner. Like classic TMT reagents, TMTpro reagents contain a tertiary amine group, which markedly enhances their reactivity toward hydroxyl groups and results in O-acylation of serine, threonine and tyrosine residues. This overlabeling significantly compromises proteome analysis in terms of depth and precision. In particular, the reactivity of hydroxyl-containing residues can be dramatically enhanced when coexisting with a histidine in the same peptides, leading to a severe systematic bias against the analysis of these peptides. Although some protocols using a reduced molar excess of TMT under alkaline conditions can alleviate overlabeling of histidine-free peptides to some extent, they have a limited effect on histidyl- and hydroxyl-containing peptides.

RESULTS

Here, we report a novel TMTpro labeling method that overcomes detrimental overlabeling while providing high labeling efficiency of amines. Additionally, our method is cost-effective, as it requires only half the amount of TMTpro reagents recommended by the reagent manufacturer. In a deep-scale analysis of a yeast/human two-proteome model sample, we compared our method with a typical alkaline labeling method using a reduced molar excess of TMTpro. Even at a depth of over 10,000 proteins, our method detected 23.7% more unique peptides and 8.7% more protein groups compared to the alkaline labeling method. Moreover, our method significantly improved the quantitative precision due to the reduced variability in labeling and increased protein sequence coverage. This substantially enhanced the statistical power of our method for detecting differentially abundant proteins, providing an average of 13% more yeast proteins that reached statistical significance.

SIGNIFCANCE

We presented a novel TMTpro labeling method that overcomes the detrimental O-acylation and thus significantly improves the depth and quantitative precision for proteome analysis.

Spectral library search for improved TMTpro labelled peptide assignment in human plasma proteomics

Clinical biomarker discovery is often based on the analysis of human plasma samples. However, the high dynamic range and complexity of plasma pose significant challenges to mass spectrometry-based proteomics. Current methods for improving protein identifications require laborious pre-analytical sample preparation. In this study, we developed and evaluated a TMTpro-specific spectral library for improved protein identification in human plasma proteomics. The library was constructed by LC-MS/MS analysis of highly fractionated TMTpro-tagged human plasma, human cell lysates, and relevant arterial tissues. The library was curated using several quality filters to ensure reliable peptide identifications. Our results show that spectral library searching using the TMTpro spectral library improves the identification of proteins in plasma samples compared to conventional sequence database searching. Protein identifications made by the spectral library search engine demonstrated a high degree of complementarity with the sequence database search engine, indicating the feasibility of increasing the number of protein identifications without additional pre-analytical sample preparation. The TMTpro-specific spectral library provides a resource for future plasma proteomics research and optimization of search algorithms for greater accuracy and speed in protein identifications in human plasma proteomics, and is made publicly available to the research community via ProteomeXchange with identifier PXD042546.

Adapting an Isobaric Tag-Labeled Yeast Peptide Standard to Develop Targeted Proteomics Assays

Targeted proteomics strategies present a streamlined hypothesis-driven approach to analyze specific sets of pathways or disease related proteins. goDig is a quantitative, targeted tandem mass tag (TMT)-based assay that can measure the relative abundance differences for hundreds of proteins directly from unfractionated mixtures. Specific protein groups or entire pathways of up to 200 proteins can be selected for quantitative profiling, while leveraging sample multiplexing permits the simultaneous analysis of up to 18 samples. Despite these benefits, implementing goDig is not without challenges, as it requires access to an instrument application programming interface (iAPI), an elution order and spectral library, a web-based method builder, and dedicated companion software. In addition, the absence of an example test assay may dissuade researchers from testing or implementing goDig. Here, we repurpose the TKO11 standard─which is commercially available but may also be assembled in-lab─and establish it as a de facto test assay for goDig. We build a proteome-wide goDig yeast library, quantify protein expression across several gene ontology (GO) categories, and compare these results to a fully fractionated yeast gold-standard data set. Essentially, we provide a guide detailing the goDig-based quantification of TKO11, which can also be used as a template for user-defined assays in other species.

Enhancing Proteome Coverage by Using Strong Anion-Exchange in Tandem with Basic-pH Reversed-Phase Chromatography for Sample Multiplexing-Based Proteomics

Sample multiplexing-based proteomic strategies rely on fractionation to improve proteome coverage. Tandem mass tag (TMT) experiments, for example, can currently accommodate up to 18 samples with proteins spanning several orders of magnitude, thus necessitating fractionation to achieve reasonable proteome coverage. Here, we present a simple yet effective peptide fractionation strategy that partitions a pooled TMT sample with a two-step elution using a strong anion-exchange (SAX) spin column prior to gradient-based basic pH reversed-phase (BPRP) fractionation. We highlight our strategy with a TMTpro18-plex experiment using nine diverse human cell lines in biological duplicate. We collected three data sets, one using only BPRP fractionation and two others of each SAX-partition followed by BPRP. The three data sets quantified a similar number of proteins and peptides, and the data highlight noticeable differences in the distribution of peptide charge and isoelectric point between the SAX partitions. The combined SAX partition data set contributed 10% more proteins and 20% more unique peptides that were not quantified by BPRP fractionation alone. In addition to this improved fractionation strategy, we provide an online resource of relative abundance profiles for over 11,000 proteins across the nine human cell lines, as well as two additional experiments using ovarian and pancreatic cancer cell lines.

Proteome-Wide Profiling Using Sample Multiplexing of a Human Cell Line Treated with Cannabidiol (CBD) and Tetrahydrocannabinol (THC)

Cannabis has been used historically for both medicinal and recreational purposes, with the most notable cannabinoids being cannabidiol (CBD) and tetrahydrocannabinol (THC). Although their therapeutic effects have been well studied and their recreational use is highly debated, the underlying mechanisms of their biological effects remain poorly defined. In this study, we use isobaric tag-based sample multiplexed proteome profiling to investigate protein abundance differences in the human neuroblastoma SH-SY5Y cell line treated with CBD and THC. We identified significantly regulated proteins by each treatment and performed a pathway classification and associated protein-protein interaction analysis. Our findings suggest that these treatments may lead to mitochondrial dysfunction and induce endoplasmic reticulum stress. These data can potentially be interrogated further to investigate the potential role of CBD and THC in various biological and disease contexts, providing a foundation for future studies.

Proteome-wide abundance profiling of yeast deletion strains for GET pathway members using sample multiplexing

The GET pathway is associated with post-translational delivery of tail-anchored (TA) proteins to the endoplasmic reticulum (ER) in yeast, as well as other eukaryotes. Moreover, dysfunction of the GET pathway has been associated with various pathological conditions (i.e., neurodegenerative disorders, cardiovascular ailments, and protein misfolding diseases). In this study, we used yeast deletion strains of Get complex members (specifically, Get1, Get2, Get3, Get4, and Get5) coupled with sample multiplexing-based quantitative mass spectrometry to profile protein abundance on a proteome-wide scale across the five individual deletion strains. Our dataset consists of over 4500 proteins, which corresponds to >75% of the yeast proteome. The data reveal several dozen proteins that are differentially abundant in one or more deletion strains, some of which are membrane-associated, yet the abundance of many TA proteins remained unchanged. This study provides valuable insights into the roles of these Get genes, and the potential for alternative pathways which help maintain cellular function despite the disruption of the GET pathway.

Comparative Proteomic Analysis of Two Commonly Used Laboratory Yeast Strains: W303 and BY4742

The yeast Saccharomyces cerevisiae is a powerful model system that is often used to expand our understanding of cellular processes and biological functions. Although many genetically well-characterized laboratory strains of S. cerevisiae are available, they may have different genetic backgrounds which can confound data interpretation. Here, we report a comparative whole-proteome analysis of two common laboratory yeast background strains, W303 and BY4742, in both exponential and stationary growth phases using isobaric-tag-based mass spectrometry to highlight differences in proteome complexity. We quantified over 4400 proteins, hundreds of which showed differences in abundance between strains and/or growth phases. Moreover, we used proteome-wide protein abundance to profile the mating type of the strains used in the experiment, the auxotrophic markers, and associated metabolic pathways, as well as to investigate differences in particular classes of proteins, such as the pleiotropic drug resistance (PDR) proteins. This study is a valuable resource that offers insight into mechanistic differences between two common yeast background strains and can be used as a guide to select a background that is best suited for addressing a particular biological question.

Comparison of the Proteomes and Phosphoproteomes of S. cerevisiae Cells Harvested with Different Strategies

The budding yeast Saccharomyces cerevisiae is a powerful model system that is widely used to investigate many cellular processes. The harvesting of yeast cells is the first step in almost every experimental procedure. Here, yeast cells are isolated from their growth medium, collected, and used for successive experiments or analysis. The two most common methods to harvest S. cerevisiae are centrifugation and filtration. Understanding if and how centrifugation and filtration affect yeast physiology is essential with respect to downstream data interpretation. Here, we profile and compare the proteomes and the phosphoproteomes, using isobaric label-based quantitative mass spectrometry, of three common methods used to harvest S. cerevisiae cells: low-speed centrifugation, high-speed centrifugation, and filtration. Our data suggest that, while the proteome was stable across the tested conditions, hundreds of phosphorylation events were different between centrifugation and filtration. Our analysis shows that, under our experimental conditions, filtration may cause both cell wall and osmotic stress at higher levels compared to centrifugation, implying harvesting-method-specific stresses. Thus, considering that the basal activation levels of specific stresses may differ under certain harvesting conditions is an important, but often overlooked, aspect of experimental design.

Enriching Cysteine-Containing Peptides Using a Sulfhydryl-Reactive Alkylating Reagent with a Phosphonic Acid Group and Immobilized Metal Affinity Chromatography

The reduction of disulfide bonds and their subsequent alkylation are commonplace in typical proteomics workflows. Here, we highlight a sulfhydryl-reactive alkylating reagent with a phosphonic acid group (iodoacetamido-LC-phosphonic acid, 6C-CysPAT) that facilitates the enrichment of cysteine-containing peptides for isobaric tag-based proteome abundance profiling. Specifically, we profile the proteome of the SH-SY5Y human cell line following 24 h treatments with two proteasome inhibitors (bortezomib and MG-132) in a tandem mass tag (TMT)pro9-plex experiment. We acquire three datasets─(1) Cys-peptide enriched, (2) the unbound complement, and (3) the non-depleted control─and compare the peptides and proteins quantified in each dataset, with emphasis on Cys-containing peptides. The data show that enrichment using 6C-Cys phosphonate adaptable tag (6C-CysPAT) can quantify over 38,000 Cys-containing peptides in 5 h with >90% specificity. In addition, our combined dataset provides the research community with a resource of over 9900 protein abundance profiles exhibiting the effects of two different proteasome inhibitors. Overall, the seamless incorporation of alkylation by 6C-CysPAT into a current TMT-based workflow permits the enrichment of a Cys-containing peptide subproteome. The acquisition of this "mini-Cys" dataset can be used to preview and assess the quality of a deep, fractionated dataset.

Spin column-based peptide fractionation alternatives for streamlined tandem mass tag (SL-TMT) sample processing

Fractionation is essential to achieving deep proteome coverage for sample multiplexing experiments where currently up to 18 samples can be analyzed concurrently. However, peptide fractionation (i.e., upstream of LC-MS/MS analysis) with a liquid chromatography system constrains sample processing as only a single sample can be fractionated at once. Here, we highlight the use of spin column-based methods which permit multiple multiplexed samples to be fractionated simultaneously. These methods require only a centrifuge and eliminate the need for a dedicated liquid chromatography system. We investigate peptide fractionation with strong anion exchange (SAX) and high-pH reversed phase (HPRP) spin columns, as well as a combination of both. In two separate experiments, we acquired deep proteome coverage (>8000 quantified proteins), while starting with <25 μg of protein per channel. Our datasets showcase the proteome alterations in two human cell lines resulting from treatment with inhibitors acting on the ubiquitin-proteasome system. We recommend this spin column-based peptide fractionation strategy for high-throughput screening applications or whenever a liquid chromatograph is not readily available. SIGNIFICANCE: Fractionation is a means to achieve deep proteome coverage for global proteomics analysis. Typical liquid chromatography systems may be a prohibitive expense for many laboratories. Here, we investigate prefractionation with strong anion exchange (SAX) and high-pH reversed phase (HPRP) spin columns, as well as a combination of both, as peptide fractionation methods. These spin columns have advantages over liquid chromatography systems, which include relative affordability, higher throughput capability, no carry over, and fewer potential instrument-related malfunctions. In two separate experiments, we acquired deep proteome coverage (>8000 quantified proteins), thereby showing the utility of each or a combination of both spin columns for global proteome analysis.

High-Throughput and In-Depth Proteomic Profiling of 5 μL Plasma and Serum Using TMTpro 16-Plex

High-throughput and in-depth proteomic analysis of plasma and serum samples remains challenging due to the presence of multiple high-abundance proteins. Here, we provide a detailed protocol for proteomic analysis of serum and plasma specimens using a high-abundance protein depletion kit and TMTpro 16-plex reagents. This method requires only 5 μL serum or plasma, identifying and quantifying about 1000 proteins. A batch of 16 samples can be processed in 36 h. On average, each sample consumes about 1.5 h of mass spectrometer instrument time. Overall, our method can identify proteins across six orders of magnitude with high reproducibility (CV < 20%) using a shorter instrument time and less sample volume compared to existing methods. Thus, the method is suitable to be applied to large-scale proteomic studies.

SimPLIT: Simplified Sample Preparation for Large-Scale Isobaric Tagging Proteomics

Large scale proteomic profiling of cell lines can reveal molecular signatures attributed to variable genotypes or induced perturbations, enabling proteogenomic associations and elucidation of pharmacological mechanisms of action. Although isobaric labeling has increased the throughput of proteomic analysis, the commonly used sample preparation workflows often require time-consuming steps and costly consumables, limiting their suitability for large scale studies. Here, we present a simplified and cost-effective one-pot reaction workflow in a 96-well plate format (SimPLIT) that minimizes processing steps and demonstrates improved reproducibility compared to alternative approaches. The workflow is based on a sodium deoxycholate lysis buffer and a single detergent cleanup step after peptide labeling, followed by quick off-line fractionation and MS2 analysis. We showcase the applicability of the workflow in a panel of colorectal cancer cell lines and by performing target discovery for a set of molecular glue degraders in different cell lines, in a 96-sample assay. Using this workflow, we report frequently dysregulated proteins in colorectal cancer cells and uncover cell-dependent protein degradation profiles of seven cereblon E3 ligase modulators (CRL4CRBN). Overall, SimPLIT is a robust method that can be easily implemented in any proteomics laboratory for medium-to-large scale TMT-based studies for deep profiling of cell lines.

Profiling Yeast Deletion Strains Using Sample Multiplexing and Network-Based Analyses

The yeast, Saccharomyces cerevisiae, is a widely used model system for investigating conserved biological functions and pathways. Advancements in sample multiplexing have facilitated the study of the yeast proteome, yet many yeast proteins remain uncharacterized or only partially characterized. Yeast deletion strain collections are powerful resources for yeast proteome studies, uncovering the effects of gene function, genetic interactions, and cellular stresses. As complex biological systems cannot be understood by simply analyzing the individual components, a systems approach is often required in which a protein is represented as a component of large, interacting networks. Here, we evaluate the current state of yeast proteome analysis using isobaric tag-based sample multiplexing (TMTpro16) to profile the proteomes of 75 yeast deletion strains for which we measured the abundance of nearly 5000 proteins. Using statistical approaches, we highlighted covariance and regulation subnetworks and the enrichment of gene ontology classifications for covarying and coregulated proteins. This dataset presents a resource that is amenable to further data mining to study individual deletion strains, pathways, proteins, and/or interactions thereof while serving as a template for future network-based investigations using yeast deletion strain collections.

Retention Time Prediction for TMT-Labeled Peptides in Proteomic LC-MS Experiments

We present the first detailed study of chromatographic behavior of peptides labeled with tandem mass tags (TMT and TMTpro) in 2D LC for proteomic applications. Carefully designed experimental procedures have permitted generating data sets of over 100,000 nonlabeled and TMT-labeled peptide pairs for the low pH RP in the second separation dimension and data sets of over 10,000 peptide pairs for high-pH RP, HILIC (amide and silica), and SCX separations in the first separation dimension. The average increase in peptide RPLC (0.1% formic acid) retention upon TMT labeling was found to be 3.3% acetonitrile (linear water/acetonitrile gradients), spanning a range of -4 to 10.3%. In addition to the bulk peptide properties such as length, hydrophobicity, and the number of labeled residues, we found several sequence-dependent features mostly associated with differences in N-terminal chemistry. The behavior of TMTpro-labeled peptides was found to be very similar except for a slightly higher hydrophobicity: an average retention shift of 3.7% acetonitrile. The respective versions of the sequence-specific retention calculator (SSRCalc) model have been developed to accommodate both TMT chemistries, showing identical prediction accuracy (R² ∼ 0.98) for labeled and nonlabeled peptides. Higher retention for TMT-labeled peptides was observed for high-pH RP and HILIC separations, while SCX selectivity remained virtually unchanged.

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.

A Compendium of Murine (Phospho)Peptides Encompassing Different Isobaric Labeling and Data Acquisition Strategies

Targeted mass spectrometry-based assays typically rely on previously acquired large data sets for peptide target selection. Such repositories are widely available for unlabeled peptides. However, they are less common for isobaric tagged peptides. Here we have assembled two series of six data sets originating from a mouse embryonic fibroblast cell line (NIH/3T3). One series is of peptides derived from a tryptic digest of a whole cell proteome and a second from enriched phosphopeptides. These data sets encompass three labeling approaches (unlabeled, TMT11-labeled, and TMTpro16-labeled) and two data acquisition strategies (ion trap MS2 with and without FAIMS-based gas phase separation). We identified a total of 1 509 526 peptide-spectrum matches which covered 11 482 proteins from the whole cell proteome tryptic digest, and 188 849 phosphopeptides from the phosphopeptide enrichment. The data sets were of similar depth, and while overlap across data sets was modest, protein overlap was high, thus reinforcing the comprehensiveness of these data sets. The data also supported FAIMS as a means to increase data set depth. These data sets provide a rich resource of peptides that may be used as starting points for targeted assays. Future data sets may be compiled for any genome-sequenced organism using the technologies and strategies highlighted herein. The data have been deposited in the ProteomeXchange Consortium with data set identifier PXD024298.

A Semiautomated Paramagnetic Bead-Based Platform for Isobaric Tag Sample Preparation

The development of streamlined and high-throughput sample processing workflows is important for capitalizing on emerging advances and innovations in mass spectrometry-based applications. While the adaptation of new technologies and improved methodologies is fast paced, automation of upstream sample processing often lags. Here we have developed and implemented a semiautomated paramagnetic bead-based platform for isobaric tag sample preparation. We benchmarked the robot-assisted platform by comparing the protein abundance profiles of six common parental laboratory yeast strains in triplicate TMTpro16-plex experiments against an identical set of experiments in which the samples were manually processed. Both sets of experiments quantified similar numbers of proteins and peptides with good reproducibility. Using these data, we constructed an interactive website to explore the proteome profiles of six yeast strains. We also provide the community with open-source templates for automating routine proteomics workflows on an opentrons OT-2 liquid handler. The robot-assisted platform offers a versatile and affordable option for reproducible sample processing for a wide range of protein profiling applications.

TMTpro Complementary Ion Quantification Increases Plexing and Sensitivity for Accurate Multiplexed Proteomics at the MS2 Level

Multiplexed proteomics is a powerful tool to assay cell states in health and disease, but accurate quantification of relative protein changes is impaired by interference from co-isolated peptides. Interference can be reduced by using MS3-based quantification, but this reduces sensitivity and requires specialized instrumentation. An alternative approach is quantification by complementary ions, the balancer group-peptide conjugates, which allows accurate and precise multiplexed quantification at the MS2 level and is compatible with most proteomics instruments. However, complementary ions of the popular TMT-tag form inefficiently and multiplexing is limited to five channels. Here, we evaluate and optimize complementary ion quantification for the recently released TMTpro-tag, which increases complementary ion plexing capacity to eight channels (TMTproC). Furthermore, the beneficial fragmentation properties of TMTpro increase sensitivity for TMTproC, resulting in ∼65% more proteins quantified compared to TMTpro-MS3 and ∼18% more when compared to real-time-search TMTpro-MS3 (RTS-SPS-MS3). TMTproC quantification is more accurate than TMTpro-MS2 and even superior to RTS-SPS-MS3. We provide the software for quantifying TMTproC data as an executable that is compatible with the MaxQuant analysis pipeline. Thus, TMTproC advances multiplexed proteomics data quality and widens access to accurate multiplexed proteomics beyond laboratories with MS3-capable instrumentation.

TMTpro-18plex: The Expanded and Complete Set of TMTpro Reagents for Sample Multiplexing

The development of the TMTpro-16plex series expanded the breadth of commercial isobaric tagging reagents by nearly 50% over classic TMT-11plex. In addition to the described 16plex reagents, the proline-based TMTpro molecule can accommodate two additional combinations of heavy carbon and nitrogen isotopes. Here, we introduce the final two labeling reagents, TMTpro-134C and TMTpro-135N, which permit the simultaneous global protein profiling of 18 samples with essentially no missing values. For example, six conditions with three biological replicates can now be perfectly accommodated. We showcase the 18plex reagent set by profiling the proteome and phosphoproteome of a pair of isogenic mammary epithelial cell lines under three conditions in triplicate. We compare the depth and quantitative performance of this data set with a TMTpro-16plex experiment in which two samples were omitted. Our analysis revealed similar numbers of quantified peptides and proteins, with high quantitative correlation. We interrogated further the TMTpro-18plex data set by highlighting changes in protein abundance profiles under different conditions in the isogenic cell lines. We conclude that TMTpro-18plex further expands the sample multiplexing landscape, allowing for complex and innovative experimental designs.

Temporal proteomic changes induced by nicotine in human cells: A quantitative proteomics approach

Nicotine is a prominent active compound in tobacco and many smoking cessation products. Some of the biological effects of nicotine are well documented in in vitro and in vivo systems; however, data are scarce concerning the time-dependent changes on protein and phosphorylation events in response to nicotine. Here, we profiled the proteomes of SH-SY5Y and A549 cell lines subjected to acute (15 min, 1 h and 4 h) or chronic (24 h, 48 h) nicotine exposures. We used sample multiplexing (TMTpro16) and quantified more than 9000 proteins and over 7000 phosphorylation events per cell line. Among our findings, we determined a decrease in mitochondrial protein abundance for SH-SY5Y, while we detected alterations in several immune pathways, such as the complement system, for A549 following nicotine treatment. We also explored the proposed association between smoking (specifically nicotine) and SARS-CoV2. Here, we found several host proteins known to interact with viral proteins that were affected by nicotine in a time dependent manner. This dataset can be mined further to investigate the potential role of nicotine in different biological contexts. SIGNIFICANCE: Smoking is a major public health issue that is associated with several serious chronic, yet preventable diseases, including stroke, heart disease, type 2 diabetes, cancer, and susceptibility to infection. Tobacco smoke is a complex mixture of thousands of different compounds, among which nicotine is the main addictive compound. The biological effects of nicotine have been reported in several models, however very little data are available concerning the temporal proteomic and phosphoproteomic changes in response to nicotine. Here, we provide a dataset exploring the potential role of nicotine on different biological processes over time, including implications in the study of SARS-CoV2.

Improved Proteomics-Based Drug Mechanism-of-Action Studies Using 16-Plex Isobaric Mass Tags

Multiplexed quantitative proteomics enabled complex workflows to study the mechanisms by which small molecule drugs interact with the proteome such as thermal proteome profiling (TPP) or multiplexed proteome dynamics profiling (mPDP). TPP measures changes in protein thermal stability in response to drug treatment and thus informs on direct targets and downstream regulation events, while the mPDP approach enables the discovery of regulated protein synthesis and degradation events caused by small molecules and other perturbations. The isobaric mass tags available for multiplexed proteomics have thus far limited the efficiency and sensitivity by which such experiments could be performed. Here we evaluate a recent generation of 16-plex isobaric mass tags and demonstrate the sensitive and time efficient identification of Staurosporine targets in HepG2 cell extracts by recording full thermal denaturation/aggregation profiles of vehicle and compound treated samples in a single mass spectrometry experiment. In 2D-TPP experiments, isothermal titration over seven concentrations per temperature enabled comprehensive selectivity profiling of Staurosporine with EC₅₀ values for kinase targets tightly matching to the kinobeads gold standard assay. Finally, we demonstrate time and condition-based multiplexing of dynamic SILAC labeling experiments to delineate proteome-wide effects of the molecular glue Indisulam on synthesis and degradation rates.

Automated 16-Plex Plasma Proteomics with Real-Time Search and Ion Mobility Mass Spectrometry Enables Large-Scale Profiling in Naked Mole-Rats and Mice

Performing large-scale plasma proteome profiling is challenging due to limitations imposed by lengthy preparation and instrument time. We present a fully automated multiplexed proteome profiling platform (AutoMP3) using the Hamilton Vantage liquid handling robot capable of preparing hundreds to thousands of samples. To maximize protein depth in single-shot runs, we combined 16-plex Tandem Mass Tags (TMTpro) with high-field asymmetric waveform ion mobility spectrometry (FAIMS Pro) and real-time search (RTS). We quantified over 40 proteins/min/sample, doubling the previously published rates. We applied AutoMP3 to investigate the naked mole-rat plasma proteome both as a function of the circadian cycle and in response to ultraviolet (UV) treatment. In keeping with the lack of synchronized circadian rhythms in naked mole-rats, we find few circadian patterns in plasma proteins over the course of 48 h. Furthermore, we quantify many disparate changes between mice and naked mole-rats at both 48 h and one week after UV exposure. These species differences in plasma protein temporal responses could contribute to the pronounced cancer resistance observed in naked mole-rats. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE [1] partner repository with the dataset identifier PXD022891.

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.

Temporal Proteomic Profiling of SH-SY5Y Differentiation with Retinoic Acid Using FAIMS and Real-Time Searching

The SH-SY5Y cell line is often used as a surrogate for neurons in cell-based studies. This cell line is frequently differentiated with all-trans retinoic acid (ATRA) over a 7-day period, which confers neuron-like properties to the cells. However, no analysis of proteome remodeling has followed the progress of this transition. Here, we quantitatively profiled over 9400 proteins across a 7-day treatment with retinoic acid using state-of-the-art mass spectrometry-based proteomics technologies, including FAIMS, real-time database searching, and TMTpro16 sample multiplexing. Gene ontology analysis revealed that categories with the highest increases in protein abundance were related to the plasma membrane/extracellular space. To showcase our data set, we surveyed the protein abundance profiles linked to neurofilament bundle assembly, neuron projections, and neuronal cell body formation. These proteins exhibited increases in abundance level, yet we observed multiple patterns among the queried proteins. The data presented represent a rich resource for investigating temporal protein abundance changes in SH-SY5Y cells differentiated with retinoic acid. Moreover, the sample preparation and data acquisition strategies used here can be readily applied to any analogous cell line differentiation analysis.