TMTpro: Design, Synthesis, and Initial Evaluation of a Proline-Based Isobaric 16-Plex Tandem Mass Tag Reagent Set

Time-resolved interactome profiling deconvolutes secretory protein quality control dynamics

Many cellular processes are governed by protein-protein interactions that require tight spatial and temporal regulation. Accordingly, it is necessary to understand the dynamics of these interactions to fully comprehend and elucidate cellular processes and pathological disease states. To map de novo protein-protein interactions with time resolution at an organelle-wide scale, we developed a quantitative mass spectrometry method, time-resolved interactome profiling (TRIP). We apply TRIP to elucidate aberrant protein interaction dynamics that lead to the protein misfolding disease congenital hypothyroidism. We deconvolute altered temporal interactions of the thyroid hormone precursor thyroglobulin with pathways implicated in hypothyroidism pathophysiology, such as Hsp70-/90-assisted folding, disulfide/redox processing, and N-glycosylation. Functional siRNA screening identified VCP and TEX264 as key protein degradation components whose inhibition selectively rescues mutant prohormone secretion. Ultimately, our results provide novel insight into the temporal coordination of protein homeostasis, and our TRIP method should find broad applications in investigating protein-folding diseases and cellular processes.

A Tutorial Review of Labeling Methods in Mass Spectrometry-Based Quantitative Proteomics

Recent advancements in mass spectrometry (MS) have revolutionized quantitative proteomics, with multiplex isotope labeling emerging as a key strategy for enhancing accuracy, precision, and throughput. This tutorial review offers a comprehensive overview of multiplex isotope labeling techniques, including precursor-based, mass defect-based, reporter ion-based, and hybrid labeling methods. It details their fundamental principles, advantages, and inherent limitations along with strategies to mitigate the limitation of ratio-distortion. This review will also cover the applications and latest progress in these labeling techniques across various domains, including cancer biomarker discovery, neuroproteomics, post-translational modification analysis, cross-linking MS, and single-cell proteomics. This Review aims to provide guidance for researchers on selecting appropriate methods for their specific goals while also highlighting the potential future directions in this rapidly evolving field.

Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry

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

Mass Spectrometry Acquisition and Fractionation Recommendations for TMT11 and TMT16 Labeled Samples

Proteome coverage and accurate protein quantification are both important for evaluating biological systems; however, compromises between quantification, coverage, and mass spectrometry (MS) resources are often necessary. Consequently, experimental parameters that impact coverage and quantification must be adjusted, depending on experimental goals. Among these parameters is offline prefractionation, which is utilized in MS-based proteomics to decrease sample complexity resulting in higher overall proteome coverage upon MS analysis. Prefractionation leads to increases in required MS analysis time, although this is often mitigated by isobaric labeling using tandem-mass tags (TMT), which allow samples to be multiplexed. Here we evaluate common prefractionation schemes, TMT variants, and MS acquisition methods and their impact on protein quantification and coverage. Furthermore, we provide recommendations for experimental design depending on the experimental goals.

Deep phosphotyrosine characterisation of primary murine T cells using broad spectrum optimisation of selective triggering

Sequencing the tyrosine phosphoproteome using MS-based proteomics is challenging due to the low abundance of tyrosine phosphorylation in cells, a challenge compounded in scarce samples like primary cells or clinical samples. The broad-spectrum optimisation of selective triggering (BOOST) method was recently developed to increase phosphotyrosine sequencing in low protein input samples by leveraging tandem mass tags (TMT), phosphotyrosine enrichment, and a phosphotyrosine-loaded carrier channel. Here, we demonstrate the viability of BOOST in T cell receptor (TCR)-stimulated primary murine T cells by benchmarking the accuracy and precision of the BOOST method and discerning significant alterations in the phosphoproteome associated with receptor stimulation. Using 1 mg of protein input (about 20 million cells) and BOOST, we identify and precisely quantify more than 2000 unique pY sites compared to about 300 unique pY sites in non-BOOST control samples. We show that although replicate variation increases when using the BOOST method, BOOST does not jeopardise quantitative precision or the ability to determine statistical significance for peptides measured in triplicate. Many pY previously uncharacterised sites on important T cell signalling proteins are quantified using BOOST, and we identify new TCR responsive pY sites observable only with BOOST. Finally, we determine that the phase-spectrum deconvolution method on Orbitrap instruments can impair pY quantitation in BOOST experiments.

6-Plex Tandem Phosphorus Tags (TPT) for Accurate Quantitative Proteomics

Isobaric chemical labeling is a widely used strategy for high-throughput quantitative proteomics based on mass spectrometry. However, commercially available reagents have high costs in applications as well as the sensitivity limitations for detection of the trace protein samples. Previously, we developed a 2-plex isobaric labeling strategy based on phosphorus chemistry for ultrasensitive proteome quantification with high accuracy. In this work, 6-plex tandem phosphorus tags (TPT) were developed with 3-fold increase in the multiplexing quantitative capacity compared to the 2-plex isobaric phosphorus reagents introduced previously. High isotope enrichment of 18O labeling was incorporated into the phosphoryl group with three exchangeable oxygen atoms by using commercially available H218O. The combinational incorporations of 18O atom in reporter ions and balance group set up the low-cost foundation for development of multiplex TPT reagents. The novel 6-plex TPT reagents could produce phosphoramidate as unique reporter ions with approximately 1 Da mass difference and thus enable 6-plex quantitative analysis in high-resolution ESI-MS/MS analysis. Using HeLa cell tryptic peptides, we concluded that 6-plex TPT reagents could facilitate large-scale accurate quantitative proteomics with very high labeling efficiency.

Global protein turnover quantification in Escherichia coli reveals cytoplasmic recycling under nitrogen limitation

Protein turnover is critical for proteostasis, but turnover quantification is challenging, and even in well-studied E. coli, proteome-wide measurements remain scarce. Here, we quantify the turnover rates of ~3200 E. coli proteins under 13 conditions by combining heavy isotope labeling with complement reporter ion quantification and find that cytoplasmic proteins are recycled when nitrogen is limited. We use knockout experiments to assign substrates to the known cytoplasmic ATP-dependent proteases. Surprisingly, none of these proteases are responsible for the observed cytoplasmic protein degradation in nitrogen limitation, suggesting that a major proteolysis pathway in E. coli remains to be discovered. Lastly, we show that protein degradation rates are generally independent of cell division rates. Thus, we present broadly applicable technology for protein turnover measurements and provide a rich resource for protein half-lives and protease substrates in E. coli, complementary to genomics data, that will allow researchers to study the control of proteostasis.

15N metabolic labeling-TMT multiplexing approach to facilitate the quantitation of glycopeptides derived from cell lines

The study of glycoproteomics presents a set of unique challenges, primarily due to the low abundance of glycopeptides and their intricate heterogeneity, which is specific to each site. Glycoproteins play a crucial role in numerous biological functions, including cell signaling, adhesion, and intercellular communication, and are increasingly recognized as vital markers in the diagnosis and study of various diseases. Consequently, a quantitative approach to glycopeptide research is essential. One effective strategy to address this need is the use of multiplex glycopeptide labeling. By harnessing the synergies of 15N metabolic labeling via the isotopic detection of amino sugars with glutamine (IDAWG) technique for glycan parts and tandem mass tag (TMT)pro labeling for peptide backbones, we have developed a method that allows for the accurate quantification and comparison of multiple samples simultaneously. The adoption of the liquid chromatography-synchronous precursor selection (LC-SPS-MS3) technique minimizes fragmentation interference, enhancing data reliability, as shown by a 97% TMT labeling efficiency. This method allows for detailed, high-throughput analysis of 32 diverse samples from 231BR cell lines, using both 14N and 15N glycopeptides at a 1:1 ratio. A key component of our methodology was the precise correction for isotope and TMTpro distortions, significantly improving quantification accuracy to less than 5% distortion. This breakthrough enhances the efficiency and accuracy of glycoproteomic studies, increasing our understanding of glycoproteins in health and disease. Its applicability to various cancer cell types sets a new standard in quantitative glycoproteomics, enabling deeper investigation into glycopeptide profiles.

Multiplexing the Identification of Microorganisms via Tandem Mass Tag Labeling Augmented by Interference Removal through a Novel Modification of the Expectation Maximization Algorithm

Having fast, accurate, and broad spectrum methods for the identification of microorganisms is of paramount importance to public health, research, and safety. Bottom-up mass spectrometer-based proteomics has emerged as an effective tool for the accurate identification of microorganisms from microbial isolates. However, one major hurdle that limits the deployment of this tool for routine clinical diagnosis, and other areas of research such as culturomics, is the instrument time required for the mass spectrometer to analyze a single sample, which can take ∼1 h per sample, when using mass spectrometers that are presently used in most institutes. To address this issue, in this study, we employed, for the first time, tandem mass tags (TMTs) in multiplex identifications of microorganisms from multiple TMT-labeled samples in one MS/MS experiment. A difficulty encountered when using TMT labeling is the presence of interference in the measured intensities of TMT reporter ions. To correct for interference, we employed in the proposed method a modified version of the expectation maximization (EM) algorithm that redistributes the signal from ion interference back to the correct TMT-labeled samples. We have evaluated the sensitivity and specificity of the proposed method using 94 MS/MS experiments (covering a broad range of protein concentration ratios across TMT-labeled channels and experimental parameters), containing a total of 1931 true positive TMT-labeled channels and 317 true negative TMT-labeled channels. The results of the evaluation show that the proposed method has an identification sensitivity of 93-97% and a specificity of 100% at the species level. Furthermore, as a proof of concept, using an in-house-generated data set composed of some of the most common urinary tract pathogens, we demonstrated that by using the proposed method the mass spectrometer time required per sample, using a 1 h LC-MS/MS run, can be reduced to 10 and 6 min when samples are labeled with TMT-6 and TMT-10, respectively. The proposed method can also be used along with Orbitrap mass spectrometers that have faster MS/MS acquisition rates, like the recently released Orbitrap Astral mass spectrometer, to further reduce the mass spectrometer time required per sample.

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.

Boosting the Sensitivity of Quantitative Single-Cell Proteomics with Infrared-Tandem Mass Tags

Single-cell proteomics is a powerful approach to precisely profile protein landscapes within individual cells toward a comprehensive understanding of proteomic functions and tissue and cellular states. The inherent challenges associated with limited starting material demand heightened analytical sensitivity. Just as advances in sample preparation maximize the amount of material that makes it from the cell to the mass spectrometer, we strive to maximize the number of ions that make it from ion source to the detector. In isobaric tagging experiments, limited reporter ion generation limits quantitative accuracy and precision. The combination of infrared photoactivation and ion parking circumvents the m/z dependence inherent in HCD, maximizing reporter generation and avoiding unintended degradation of TMT reporter molecules in infrared-tandem mass tags (IR-TMT). The method was applied to single-cell human proteomes using 18-plex TMTpro, resulting in 4-5-fold increases in reporter signal compared to conventional SPS-MS3 approaches. IR-TMT enables faster duty cycles, higher throughput, and increased peptide identification and quantification. Comparative experiments showcase 4-5-fold lower injection times for IR-TMT, providing superior sensitivity without compromising accuracy. In all, IR-TMT enhances the dynamic range of proteomic experiments and is compatible with gas-phase fractionation and real-time searching, promising increased gains in the study of cellular heterogeneity.

Proteomic Profiles of Human Arterioles Isolated From Fresh Adipose Tissue or Following Overnight Storage

Arterioles are key determinants of the total peripheral vascular resistance, which, in turn, is a key determinant of arterial blood pressure. However, the amount of protein available from one isolated human arteriole may be less than 5 μg, making proteomic analysis challenging. In addition, obtaining human arterioles requires manual dissection of unfrozen clinical specimens. This limits its feasibility, especially for powerful multicenter clinical studies in which clinical specimens need to be shipped overnight to a research laboratory for arteriole isolation. We performed a study to address low-input, test overnight tissue storage and develop a reference human arteriolar proteomic profile. In tandem mass tag proteomics, use of a booster channel consisting of human induced pluripotent stem cell-derived endothelial and vascular smooth muscle cells (1:5 ratio) increased the number of proteins detected in a human arteriole segment with a false discovery rate of <0.01 from 1051 to more than 3000. The correlation coefficient of proteomic profile was similar between replicate arterioles isolated freshly, following cold storage, or before and after the cold storage (1-way analysis of variance; P = .60). We built a human arteriolar proteomic profile consisting of 3832 proteins based on the analysis of 12 arteriole samples from 3 subjects. Of 1945 blood pressure-relevant proteins that we curated, 476 (12.5%) were detected in the arteriolar proteome, which was a significant overrepresentation (χ2 test; P < .05). These findings demonstrate that proteomic analysis is feasible with arterioles isolated from human adipose tissue following cold overnight storage and provide a reference human arteriolar proteome profile highly valuable for studies of arteriole-related traits.

Ergothioneine boosts mitochondrial respiration and exercise performance via direct activation of MPST

Ergothioneine (EGT) is a diet-derived, atypical amino acid that accumulates to high levels in human tissues. Reduced EGT levels have been linked to age-related disorders, including neurodegenerative and cardiovascular diseases, while EGT supplementation is protective in a broad range of disease and aging models in mice. Despite these promising data, the direct and physiologically relevant molecular target of EGT has remained elusive. Here we use a systematic approach to identify how mitochondria remodel their metabolome in response to exercise training. From this data, we find that EGT accumulates in muscle mitochondria upon exercise training. Proteome-wide thermal stability studies identify 3-mercaptopyruvate sulfurtransferase (MPST) as a direct molecular target of EGT; EGT binds to and activates MPST, thereby boosting mitochondrial respiration and exercise training performance in mice. Together, these data identify the first physiologically relevant EGT target and establish the EGT-MPST axis as a molecular mechanism for regulating mitochondrial function and exercise performance.

SHIFTR enables the unbiased identification of proteins bound to specific RNA regions in live cells

RNA-protein interactions determine the cellular fate of RNA and are central to regulating gene expression outcomes in health and disease. To date, no method exists that is able to identify proteins that interact with specific regions within endogenous RNAs in live cells. Here, we develop SHIFTR (Selective RNase H-mediated interactome framing for target RNA regions), an efficient and scalable approach to identify proteins bound to selected regions within endogenous RNAs using mass spectrometry. Compared to state-of-the-art techniques, SHIFTR is superior in accuracy, captures minimal background interactions and requires orders of magnitude lower input material. We establish SHIFTR workflows for targeting RNA classes of different length and abundance, including short and long non-coding RNAs, as well as mRNAs and demonstrate that SHIFTR is compatible with sequentially mapping interactomes for multiple target RNAs in a single experiment. Using SHIFTR, we comprehensively identify interactions of cis-regulatory elements located at the 5' and 3'-terminal regions of authentic SARS-CoV-2 RNAs in infected cells and accurately recover known and novel interactions linked to the function of these viral RNA elements. SHIFTR enables the systematic mapping of region-resolved RNA interactomes for any RNA in any cell type and has the potential to revolutionize our understanding of transcriptomes and their regulation.

Protocol for differential multi-omic analyses of distinct cell types in the mouse cerebral cortex

Here, we present a protocol for differential multi-omic analyses of distinct cell types in the developing mouse cerebral cortex. We describe steps for in utero electroporation, subsequent flow-cytometry-based isolation of developing mouse cortical cells, bulk RNA sequencing or quantitative liquid chromatography-tandem mass spectrometry, and bioinformatic analyses. This protocol can be applied to compare the proteomes and transcriptomes of developing mouse cortical cell populations after various manipulations (e.g., epigenetic). For complete details on the use and execution of this protocol, please refer to Meka et al. (2022).1.

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.

102-Plex Approach for Accurate and Multiplexed Proteome Quantification

Hyperplexing approaches have been aimed to meet the demand for large-scale proteomic analyses. Currently, the analysis capacity has expanded to up to 54 samples within a single experiment by utilizing different isotopic and isobaric reagent combinations. In this report, we propose a super multiplexed approach to enable the analysis of up to 102 samples in a single experiment, by the combination of our recently developed TAG-TMTpro and TAG-IBT16 labeling. We systematically investigated the identification and quantification performance of the 102-plex approach using the mixtures of E. coli and HeLa peptides. Our results revealed that all labeling series demonstrated accurate and reliable quantification performance. The combination of TAG-IBT16 and TAG-TMTpro approaches expands the multiplexing capacity to 102 plexes, providing a more multiplexed quantification method for even larger-scale proteomic analysis. Data are available via ProteomeXchange with the identifier PXD042398.

Mass Spectrometry-Based Proteogenomics: New Therapeutic Opportunities for Precision Medicine

Proteogenomics refers to the integration of comprehensive genomic, transcriptomic, and proteomic measurements from the same samples with the goal of fully understanding the regulatory processes converting genotypes to phenotypes, often with an emphasis on gaining a deeper understanding of disease processes. Although specific genetic mutations have long been known to drive the development of multiple cancers, gene mutations alone do not always predict prognosis or response to targeted therapy. The benefit of proteogenomics research is that information obtained from proteins and their corresponding pathways provides insight into therapeutic targets that can complement genomic information by providing an additional dimension regarding the underlying mechanisms and pathophysiology of tumors. This review describes the novel insights into tumor biology and drug resistance derived from proteogenomic analysis while highlighting the clinical potential of proteogenomic observations and advances in technique and analysis tools.

Phosphate starvation signaling increases mitochondrial membrane potential through respiration-independent mechanisms

Mitochondrial membrane potential directly powers many critical functions of mitochondria, including ATP production, mitochondrial protein import, and metabolite transport. Its loss is a cardinal feature of aging and mitochondrial diseases, and cells closely monitor membrane potential as an indicator of mitochondrial health. Given its central importance, it is logical that cells would modulate mitochondrial membrane potential in response to demand and environmental cues, but there has been little exploration of this question. We report that loss of the Sit4 protein phosphatase in yeast increases mitochondrial membrane potential, both by inducing the electron transport chain and the phosphate starvation response. Indeed, a similarly elevated mitochondrial membrane potential is also elicited simply by phosphate starvation or by abrogation of the Pho85-dependent phosphate sensing pathway. This enhanced membrane potential is primarily driven by an unexpected activity of the ADP/ATP carrier. We also demonstrate that this connection between phosphate limitation and enhancement of mitochondrial membrane potential is observed in primary and immortalized mammalian cells as well as in Drosophila. These data suggest that mitochondrial membrane potential is subject to environmental stimuli and intracellular signaling regulation and raise the possibility for therapeutic enhancement of mitochondrial function even in defective mitochondria.

A Fast-Tracking Sample Preparation Protocol for Proteomics of Formalin-Fixed Paraffin-Embedded Tumor Tissues

Archived tumor specimens are routinely preserved by formalin fixation and paraffin embedding. Despite the conventional wisdom that proteomics might be ineffective due to the cross-linking and pre-analytical variables, these samples have utility for both discovery and targeted proteomics. Building on this capability, proteomics approaches can be used to maximize our understanding of cancer biology and clinical relevance by studying preserved tumor tissues annotated with the patients' medical histories. Proteomics of formalin-fixed paraffin-embedded (FFPE) tissues also integrates with histological evaluation and molecular pathology strategies, so that additional collection of research biopsies or resected tumor aliquots is not needed. The acquisition of data from the same tumor sample also overcomes concerns about biological variation between samples due to intratumoral heterogeneity. However, the protein extraction and proteomics sample preparation from FFPE samples can be onerous, particularly for small (i.e., limited or precious) samples. Therefore, we provide a protocol for a recently introduced kit-based EasyPep method with benchmarking against a modified version of the well-established filter-aided sample preparation strategy using laser-capture microdissected lung adenocarcinoma tissues from a genetically engineered mouse model. This model system allows control over the tumor preparation and pre-analytical variables while also supporting the development of methods for spatial proteomics to examine intratumoral heterogeneity. Data are posted in ProteomeXchange (PXD045879).

An Automated Nanowell-Array Workflow for Quantitative Multiplexed Single-Cell Proteomics Sample Preparation at High Sensitivity

Multiplexed and label-free mass spectrometry-based approaches with single-cell resolution have attributed surprising heterogeneity to presumed homogenous cell populations. Even though specialized experimental designs and instrumentation have demonstrated remarkable advances, the efficient sample preparation of single cells still lags. Here, we introduce the proteoCHIP, a universal option for single-cell proteomics sample preparation including multiplexed labeling up to 16-plex with high sensitivity and throughput. The automated processing using a commercial system combining single-cell isolation and picoliter dispensing, the cellenONE, reduces final sample volumes to low nanoliters submerged in a hexadecane layer simultaneously eliminating error-prone manual sample handling and overcoming evaporation. The specialized proteoCHIP design allows direct injection of single cells via a standard autosampler resulting in around 1500 protein groups per TMT10-plex with reduced or eliminated need for a carrier proteome. We evaluated the effect of wider precursor isolation windows at single-cell input levels and found that using 2 Da isolation windows increased overall sensitivity without significantly impacting interference. Using the dedicated mass spectrometry acquisition strategies detailed here, we identified on average close to 2000 proteins per TMT10-plex across 170 multiplexed single cells that readily distinguished human cell types. Overall, our workflow combines highly efficient sample preparation, chromatographic and ion mobility-based filtering, rapid wide-window data-dependent acquisition analysis, and intelligent data analysis for optimal multiplexed single-cell proteomics. This versatile and automated proteoCHIP-based sample preparation approach is sufficiently sensitive to drive biological applications of single-cell proteomics and can be readily adopted by proteomics laboratories.

Efficient sugar utilization and transition from oxidative to substrate-level phosphorylation in high starch storage roots of African cassava genotypes

Cassava's storage roots represent one of the most important sources of nutritional carbohydrates worldwide. Particularly, smallholder farmers in sub-Saharan Africa depend on this crop plant, where resilient and yield-improved varieties are of vital importance to support steadily increasing populations. Aided by a growing understanding of the plant's metabolism and physiology, targeted improvement concepts already led to visible gains in recent years. To expand our knowledge and to contribute to these successes, we investigated storage roots of eight cassava genotypes with differential dry matter content from three successive field trials for their proteomic and metabolic profiles. At large, the metabolic focus in storage roots transitioned from cellular growth processes toward carbohydrate and nitrogen storage with increasing dry matter content. This is reflected in higher abundance of proteins related to nucleotide synthesis, protein turnover, and vacuolar energization in low starch genotypes, while proteins involved in sugar conversion and glycolysis were more prevalent in high dry matter genotypes. This shift in metabolic orientation was underlined by a clear transition from oxidative- to substrate-level phosphorylation in high dry matter genotypes. Our analyses highlight metabolic patterns that are consistently and quantitatively associated with high dry matter accumulation in cassava storage roots, providing fundamental understanding of cassava's metabolism as well as a data resource for targeted genetic improvement.

Reverse-ChIP Techniques for Identifying Locus-Specific Proteomes: A Key Tool in Unlocking the Cancer Regulome

A phenotypic hallmark of cancer is aberrant transcriptional regulation. Transcriptional regulation is controlled by a complicated array of molecular factors, including the presence of transcription factors, the deposition of histone post-translational modifications, and long-range DNA interactions. Determining the molecular identity and function of these various factors is necessary to understand specific aspects of cancer biology and reveal potential therapeutic targets. Regulation of the genome by specific factors is typically studied using chromatin immunoprecipitation followed by sequencing (ChIP-Seq) that identifies genome-wide binding interactions through the use of factor-specific antibodies. A long-standing goal in many laboratories has been the development of a 'reverse-ChIP' approach to identify unknown binding partners at loci of interest. A variety of strategies have been employed to enable the selective biochemical purification of sequence-defined chromatin regions, including single-copy loci, and the subsequent analytical detection of associated proteins. This review covers mass spectrometry techniques that enable quantitative proteomics before providing a survey of approaches toward the development of strategies for the purification of sequence-specific chromatin as a 'reverse-ChIP' technique. A fully realized reverse-ChIP technique holds great potential for identifying cancer-specific targets and the development of personalized therapeutic regimens.

Collision energies: Optimization strategies for bottom-up proteomics

Mass-spectrometry coupled to liquid chromatography is an indispensable tool in the field of proteomics. In the last decades, more and more complex and diverse biochemical and biomedical questions have arisen. Problems to be solved involve protein identification, quantitative analysis, screening of low abundance modifications, handling matrix effect, and concentrations differing by orders of magnitude. This led the development of more tailored protocols and problem centered proteomics workflows, including advanced choice of experimental parameters. In the most widespread bottom-up approach, the choice of collision energy in tandem mass spectrometric experiments has outstanding role. This review presents the collision energy optimization strategies in the field of proteomics which can help fully exploit the potential of MS based proteomics techniques. A systematic collection of use case studies is then presented to serve as a starting point for related further scientific work. Finally, this article discusses the issue of comparing results from different studies or obtained on different instruments, and it gives some hints on methodology transfer between laboratories based on measurement of reference species.

Label-free single cell proteomics utilizing ultrafast LC and MS instrumentation: A valuable complementary technique to multiplexing

The ability to map a proteomic fingerprint to transcriptomic data would master the understanding of how gene expression translates into actual phenotype. In contrast to nucleic acid sequencing, in vitro protein amplification is impossible and no single cell proteomic workflow has been established as gold standard yet. Advances in microfluidic sample preparation, multi-dimensional sample separation, sophisticated data acquisition strategies, and intelligent data analysis algorithms have resulted in major improvements to successfully analyze such tiny sample amounts with steadily boosted performance. However, among the broad variation of published approaches, it is commonly accepted that highest possible sensitivity, robustness, and throughput are still the most urgent needs for the field. While many labs have focused on multiplexing to achieve these goals, label-free SCP is a highly promising strategy as well whenever high dynamic range and unbiased accurate quantification are needed. We here focus on recent advances in label-free single-cell mass spectrometry workflows and try to guide our readers to choose the best method or combinations of methods for their specific applications. We further highlight which techniques are most propitious in the future and which applications but also limitations we foresee for the field.

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.

Super-Resolution Mass Spectrometry Enables Rapid, Accurate, and Highly Multiplexed Proteomics at the MS2 Level

In tandem mass spectrometry (MS2)-based multiplexed quantitative proteomics, the complement reporter ion approaches (TMTc and TMTproC) were developed to eliminate the ratio-compression problem of conventional MS2-level approaches. Resolving all high m/z complement reporter ions (∼6.32 mDa-spaced) requires mass resolution and scan speeds above the performance levels of OrbitrapTM instruments. Therefore, complement reporter ion quantification with TMT/TMTpro reagents is currently limited to 5 out of 11 (TMT) or 9 out of 18 (TMTpro) channels (∼1 Da spaced). We first demonstrate that a FusionTM LumosTM Orbitrap can resolve 6.32 mDa-spaced complement reporter ions with standard acquisition modes extended with 3 s transients. We then implemented a super-resolution mass spectrometry approach using the least-squares fitting (LSF) method for processing Orbitrap transients to achieve shotgun proteomics-compatible scan rates. The LSF performance resolves the 6.32 mDa doublets for all TMTproC channels in the standard mass range with transients as short as ∼108 ms (Orbitrap resolution setting of 50,000 at m/z 200). However, we observe a slight decrease in measurement precision compared to 1 Da spacing with the 108 ms transients. With 256 ms transients (resolution of 120,000 at m/z 200), coefficients of variation are essentially indistinguishable from 1 Da samples. We thus demonstrate the feasibility of highly multiplexed, accurate, and precise shotgun proteomics at the MS2 level.

Evaluation of a Pooling Chemoproteomics Strategy with an FDA-Approved Drug Library

Chemoproteomics is a key platform for characterizing the mode of action for compounds, especially for targeted protein degraders such as proteolysis targeting chimeras (PROTACs) and molecular glues. With deep proteome coverage, multiplexed tandem mass tag-mass spectrometry (TMT-MS) can tackle up to 18 samples in a single experiment. Here, we present a pooling strategy for further enhancing the throughput and apply the strategy to an FDA-approved drug library (95 best-in-class compounds). The TMT-MS-based pooling strategy was evaluated in the following steps. First, we demonstrated the capability of TMT-MS by analyzing more than 15 000 unique proteins (> 12 000 gene products) in HEK293 cells treated with five PROTACs (two BRD/BET degraders and three degraders for FAK, ALK, and BTK kinases). We then introduced a rationalized pooling strategy to separate structurally similar compounds in different pools and identified the proteomic response to 14 pools from the drug library. Finally, we validated the proteomic response from one pool by reprofiling the cells via treatment with individual drugs with sufficient replicates. Interestingly, numerous proteins were found to change upon drug treatment, including AMD1, ODC1, PRKX, PRKY, EXO1, AEN, and LRRC58 with 7-hydroxystaurosporine; C6orf64, HMGCR, and RRM2 with Sorafenib; SYS1 and ALAS1 with Venetoclax; and ATF3, CLK1, and CLK4 with Palbocilib. Thus, pooling chemoproteomics screening provides an efficient method for dissecting the molecular targets of compound libraries.

Spatial proteomics of vesicular trafficking: coupling mass spectrometry and imaging approaches in membrane biology

In plants, membrane compartmentalization requires vesicle trafficking for communication among distinct organelles. Membrane proteins involved in vesicle trafficking are highly dynamic and can respond rapidly to changes in the environment and to cellular signals. Capturing their localization and dynamics is thus essential for understanding the mechanisms underlying vesicular trafficking pathways. Quantitative mass spectrometry and imaging approaches allow a system-wide dissection of the vesicular proteome, the characterization of ligand-receptor pairs and the determination of secretory, endocytic, recycling and vacuolar trafficking pathways. In this review, we highlight major proteomics and imaging methods employed to determine the location, distribution and abundance of proteins within given trafficking routes. We focus in particular on methodologies for the elucidation of vesicle protein dynamics and interactions and their connections to downstream signalling outputs. Finally, we assess their biological applications in exploring different cellular and subcellular processes.

Control of protein stability by post-translational modifications

Post-translational modifications (PTMs) can occur on specific amino acids localized within regulatory domains of target proteins, which control a protein's stability. These regions, called degrons, are often controlled by PTMs, which act as signals to expedite protein degradation (PTM-activated degrons) or to forestall degradation and stabilize a protein (PTM-inactivated degrons). We summarize current knowledge of the regulation of protein stability by various PTMs. We aim to display the variety and breadth of known mechanisms of regulation as well as highlight common themes in PTM-regulated degrons to enhance potential for identifying novel drug targets where druggable targets are currently lacking.

Thermal Proteome Profiling for Drug Target Identification and Probing of Protein States

Proteins are central drivers of physiological and pathological processes in the cell. Methods evaluating protein functional states are therefore vital to fundamental research as well as drug discovery. Thermal proteome profiling (TPP) to this date constitutes the only approach that permits examining protein states in live cells, under native conditions and at a proteome-wide scale. TPP harnesses ligand/perturbation-induced changes in protein thermal stability, which are monitored by multiplexed quantitative mass spectrometry. In this chapter, we describe a modular experimental workflow for TPP experiments using live cells or crude cell extracts. We provide the tools to perform different TPP formats, i.e., temperature range experiments, TPP-TR; isothermal compound titrations, TPP-CCR; and a combination thereof, 2D-TPP.

In-Depth Blood Proteome Profiling by Extensive Fractionation and Multiplexed Quantitative Mass Spectrometry

Blood in the circulatory system carries information of physiological and pathological status of the human body, so blood proteins are often used as biomarkers for diagnosis, prognosis, and therapy. Human blood proteome can be explored by the latest technologies in mass spectrometry (MS), creating an opportunity of discovering new disease biomarkers. The extreme dynamic range of protein concentrations in blood, however, poses a challenge to detect proteins of low abundance, namely, tissue leakage proteins. Here, we describe a strategy to directly analyze undepleted blood samples by extensive liquid chromatography (LC) fractionation and 18-plex tandem-mass-tag (TMT) mass spectrometry. The proteins in blood specimens (e.g., plasma or serum) are isolated by acetone precipitation and digested into peptides. The resulting peptides are TMT-labeled, separated by basic pH reverse-phase (RP) LC into at least 40 fractions, and analyzed by acidic pH RPLC and high-resolution MS/MS, leading to the quantification of ~3000 unique proteins. Further increase of basic pH RPLC fractions and adjustment of the fraction concatenation strategy can enhance the proteomic coverage (up to ~5000 proteins). Finally, the combination of multiple batches of TMT experiments allows the profiling of hundreds of blood samples. This TMT-MS-based method provides a powerful platform for deep proteome profiling of human blood samples.

Proteomic Profiling of Host Response in the Cereal Crop Triticum aestivum to the Mycotoxin, 15-Acetyldeoxynivalenol, Produced by the Fungal Pathogen, Fusarium graminearum

Deoxynivalenol (DON) is a destructive mycotoxin produced by the fungal pathogen Fusarium graminearum in the devastating cereal disease Fusarium head blight (FHB). Host resistance to FHB has been identified within some of these crops (e.g., wheat, barley, corn); however, identification of how the host reduces the production of, and tolerates, DON to lessen the effects of the disease still requires further discovery. The field of quantitative proteomics is an effective tool for measuring and quantifying host defense responses to external factors, including the presence of pathogens and toxins. Success within this area of research has increased through recent technological developments (e.g., instrument sensitivity) and the accessibility of data analysis programs. One advancement we leverage is the ability to label peptides with isobaric mass tags to allow for sample multiplexing, reducing mass spectrometer run times, and providing accurate quantification. In this protocol, we exemplify this methodology to identify protein-level responses to DON within both FHB-resistant and FHB-susceptible Triticum aestivum cultivars using tandem mass tags for quantitative labeling combined with liquid-chromatography-MS/MS (LC-MS/MS) analysis. Furthermore, this protocol can be extrapolated for the identification of host responses under various conditions, including infection and environmental fluctuations, to elucidate changes in proteomic profiling in diverse biological contexts.

Insights into protein post-translational modification landscapes of individual human cells by trapped ion mobility time-of-flight mass spectrometry

Single cell proteomics is a powerful tool with potential for markedly enhancing understanding of cellular processes. Here we report the development and application of multiplexed single cell proteomics using trapped ion mobility time-of-flight mass spectrometry. When employing a carrier channel to improve peptide signal, this method allows over 40,000 tandem mass spectra to be acquired in 30 min. Using a KRAS^G12C model human-derived cell line, we demonstrate the quantification of over 1200 proteins per cell with high relative sequence coverage permitting the detection of multiple classes of post-translational modifications in single cells. When cells were treated with a KRAS^G12C covalent inhibitor, this approach revealed cell-to-cell variability in the impact of the drug, providing insight missed by traditional proteomics. We provide multiple resources necessary for the application of single cell proteomics to drug treatment studies including tools to reduce cell cycle linked proteomic effects from masking pharmacological phenotypes.

Advancements in automation for plasma proteomics sample preparation

Automation is necessary to increase sample processing throughput for large-scale clinical analyses. Replacement of manual pipettes with robotic liquid handler systems is especially helpful in processing blood-based samples, such as plasma and serum. These samples are very heterogenous, and protein expression can vary greatly from sample-to-sample, even for healthy controls. Detection of true biological changes requires that variation from sample preparation steps and downstream analytical detection methods, such as mass spectrometry, remains low. In this mini-review, we discuss plasma proteomics protocols and the benefits of automation towards enabling detection of low abundant proteins and providing low sample error and increased sample throughput. This discussion includes considerations for automation of major sample depletion and/or enrichment strategies for plasma toward mass spectrometry detection.

Proteome alterations during clonal isolation of established human pancreatic cancer cell lines

Clonal isolation is an integral step of numerous workflows in genome editing and cell engineering. It comprises the isolation of a single progenitor cell from a defined cell line population with subsequent expansion to obtain a monoclonal cell population. This process is associated with transient loss of cell–cell contacts and absence of a multicellular microenvironment. Previous studies have revealed transcriptomic changes upon clonal isolation with cell line specific extent. Since transcriptome alterations are only partially reflected on the proteome level, we sought to investigate the impact of clonal isolation on the cellular proteome to a depth of > 6000 proteins in three established pancreatic cancer cell lines. We show that clonal isolation does have an impact on the cellular proteome, however, with cell line specific extent, affecting different biological processes, and also depending on the isolation method. We demonstrate a different impact of clonal isolation on mesenchymal- and epithelial-derived cell lines mainly affecting cell proliferation, metabolism, cell adhesion and cellular stress. The results bear relevance to the field of genomic editing and cell engineering and highlight the need to consider the impact of clonal isolation when interpreting data stemming from experiments that include this step.

Isobaric labeling: Expanding the breadth, accuracy, depth, and diversity of sample multiplexing

Isobaric labeling has rapidly become a predominant strategy for proteome-wide abundance measurements. Coupled to mass spectrometry, sample multiplexing techniques using isobaric labeling are unparalleled for profiling proteins and posttranslational modifications across multiple samples in a single experiment. Here, I highlight aspects of isobaric labeling in the context of expanding the breadth of multiplexing, improving quantitative accuracy and proteome depth, and developing a wide range of diverse applications. I underscore two facets that enhance quantitative accuracy and reproducibility, specifically the availability of quality control standards for isobaric labeling experiments and the evolution of data acquisition methods. I also emphasize the necessity for standardized methodologies, particularly for emerging high-throughput workflows. Future developments in sample multiplexing will further strengthen the importance of isobaric labeling for comprehensive proteome profiling.

Recent advances in isobaric labeling and applications in quantitative proteomics

Mass spectrometry (MS) has emerged at the forefront of quantitative proteomic techniques. Liquid chromatography-mass spectrometry (LC-MS) can be used to determine abundances of proteins and peptides in complex biological samples. Several methods have been developed and adapted for accurate quantification based on chemical isotopic labeling. Among various chemical isotopic labeling techniques, isobaric tagging approaches rely on the analysis of peptides from MS2-based quantification rather than MS1-based quantification. In this review, we will provide an overview of several isobaric tags along with some recent developments including complementary ion tags, improvements in sensitive quantitation of analytes with lower abundance, strategies to increase multiplexing capabilities, and targeted analysis strategies. We will also discuss limitations of isobaric tags and approaches to alleviate these restrictions through bioinformatic tools and data acquisition methods. This review will highlight several applications of isobaric tags, including biomarker discovery and validation, thermal proteome profiling, cross-linking for structural investigations, single-cell analysis, top-down proteomics, along with applications to different molecules including neuropeptides, glycans, metabolites, and lipids, while providing considerations and evaluations to each application.

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.

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.

Calcium-dependent protein kinase 16 phosphorylates and activates the aquaporin PIP2;2 to regulate reversible flower opening in Gentiana scabra

Flower opening is important for successful pollination in many plant species, and some species repeatedly open and close their flowers. This is thought to be due to turgor pressure changes caused by water influx/efflux, which depends on osmotic oscillations in the cells. In some ornamental plants, water-transporting aquaporins, also known as plasma membrane intrinsic proteins (PIPs), may play an important role in flower opening. However, the molecular mechanism(s) involved in corolla movement are largely unknown. Gentian (Gentiana spp.) flowers undergo reversible movement in response to temperature and light stimuli; using gentian as a model, we showed that the Gentiana scabra aquaporins GsPIP2;2 and GsPIP2;7 regulate repeated flower opening. In particular, phosphorylation of a C-terminal serine residue of GsPIP2;2 is important for its transport activity and relates closely to the flower re-opening rate. Furthermore, GsPIP2;2 is phosphorylated and activated by the calcium (Ca2+)-dependent protein kinase GsCPK16, which is activated by elevated cytosolic Ca2+ levels in response to temperature and light stimuli. We propose that GsCPK16-dependent phosphorylation and activation of GsPIP2;2 regulate gentian flower re-opening, with stimulus-induced Ca2+ signals acting as triggers.

Current Advances in CETSA

Knowing that the drug candidate binds to its intended target is a vital part of drug discovery. Thus, several labeled and label-free methods have been developed to study target engagement. In recent years, the cellular thermal shift assay (CETSA) with its variations has been widely adapted to drug discovery workflows. Western blot–based CETSA is used primarily to validate the target binding of a molecule to its target protein whereas CETSA based on bead chemistry detection methods (CETSA HT) has been used to screen molecular libraries to find novel molecules binding to a pre-determined target. Mass spectrometry–based CETSA also known as thermal proteome profiling (TPP) has emerged as a powerful tool for target deconvolution and finding novel binding partners for old and novel molecules. With this technology, it is possible to probe thermal shifts among over 7,000 proteins from one sample and to identify the wanted target binding but also binding to unwanted off-targets known to cause adverse effects. In addition, this proteome-wide method can provide information on the biological process initiated by the ligand binding. The continued development of mass spectrometry labeling reagents, such as isobaric tandem mass tag technology (TMT) continues to increase the throughput of CETSA MS, allowing its use for structure–activity relationship (SAR) studies with a limited number of molecules. In this review, we discussed the differences between different label-free methods to study target engagement, but our focus was on CETSA and recent advances in the CETSA method.

29-Plex tandem mass tag mass spectrometry enabling accurate quantification by interference correction

Tandem mass tag (TMT) mass spectrometry is a mainstream isobaric chemical labeling strategy for profiling proteomes. Here we present a 29-plex TMT method to combine the 11-plex and 18-plex labeling strategies. The 29-plex method was examined with a pooled sample composed of 1×, 3×, and 10× Escherichia coli peptides with 100× human background peptides, which generated two E. coli datasets (TMT11 and TMT18), displaying the distorted ratios of 1.0:1.7:4.2 and 1.0:1.8:4.9, respectively. This ratio compression from the expected 1:3:10 ratios was caused by co-isolated TMT-labeled ions (i.e., noise). Interestingly, the mixture of two TMT sets produced MS/MS spectra with unique features for the noise detection: (i) in TMT11-labeled spectra, TMT18-specific reporter ions (e.g., 135N) were shown as the noise; (ii) in TMT18-labeled spectra, the TMT11/TMT18-shared reporter ions (e.g., 131C) typically exhibited higher intensities than TMT18-specific reporter ions, due to contaminated TMT11-labeled ions in these shared channels. We further estimated the noise levels contributed by both TMT11- and TMT18-labeled peptides, and corrected reporter ion intensities in every spectrum. Finally, the anticipated 1:3:10 ratios were largely restored. This strategy was also validated using another 29-plex sample with 1:5 ratios. Thus the 29-plex method expands the TMT throughput and enhances the quantitative accuracy.