Search

Gangliosides are specialized glycosphingolipids most abundant in the central nervous system. Their complex amphiphilic structure is essential to the formation of membrane lipid rafts and for molecular recognition. Dysfunction of lipid rafts and ganglioside metabolism has been linked to cancer, metabolic disorders, and neurodegenerative disorders. Changes in ganglioside concentration and diversity during the progression of disease have made them potential biomarkers for early detection and shed light on disease mechanisms. Chemical derivatization facilitates whole ion analysis of gangliosides while improving ionization, providing rich fragmentation spectra, and enabling multiplexed analysis schemes such as stable isotope labeling. In this work, we report improvement to our previously reported isobaric labeling methodology for ganglioside analysis by increasing buffer concentration and removing solid-phase extraction desalting for a more complete and quantitative reaction. Identification and quantification of gangliosides are automated through MS-DIAL with an in-house ganglioside derivatives library. We have applied the updated methodology to relative quantification of gangliosides in six mouse brain regions (cerebellum, pons/medulla, midbrain, thalamus/hypothalamus, cortex, and basal ganglia) with 2 mg tissue per sample, and region-specific distributions of 88 ganglioside molecular species are described with ceramide isomers resolved. This method is promising for application to comparative analysis of gangliosides in biological samples. [ABSTRACT FROM AUTHOR]

Protein phosphorylation is a critical post-translational modification involved in the regulation of numerous cellular processes from signal transduction to modulation of enzyme activities. Knowledge of dynamic changes of phosphorylation levels during biological processes, under various treatments or between healthy and disease models is fundamental for understanding the role of each phosphorylation event. Thereby, LC-MS/MS based technologies in combination with quantitative proteomics strategies evolved as a powerful strategy to investigate the function of individual protein phosphorylation events. State-of-the-art labeling techniques including stable isotope and isobaric labeling provide precise and accurate quantification of phosphorylation events. Here, we review the strengths and limitations of recent quantification methods and provide examples based on current studies, how quantitative phosphoproteomics can be further optimized for enhanced analytic depth, dynamic range, site localization, and data integrity. Specifically, reducing the input material demands is key to a broader implementation of quantitative phosphoproteomics, not least for clinical samples. Despite quantitative phosphoproteomics is one of the most thriving fields in the proteomics world, many challenges still have to be overcome to facilitate even deeper and more comprehensive analyses as required in the current research, especially at single cell levels and in clinical diagnostics. [ABSTRACT FROM AUTHOR]

Stable isotope chemical labeling methods have been widely used for high‐throughput mass spectrometry (MS)‐based quantitative proteomics in biological and clinical applications. However, the existing methods are far from meeting the requirements for high sensitivity detection. In the present study, a novel isobaric stable isotope N‐phosphorylation labeling (iSIPL) strategy was developed for quantitative proteome analysis. The tryptic peptides were selectively labeled with iSIPL tag to generate the novel reporter ions containing phosphoramidate P−N bond with high intensities under lower collision energies. iSIPL strategy are suitable for peptide sequencing and quantitative analysis with high sensitivity and accuracy even for samples of limited quantity. Furthermore, iSIPL coupled with affinity purification and mass spectrometry was applied to measure the dynamics of cyclin dependent kinase 9 (CDK9) interactomes during transactivation of the HIV‐1 provirus. The interaction of CDK9 with PARP13 was found to significantly decrease during Tat‐induced activation of HIV‐1 gene transcription, suggesting the effectiveness of iSIPL strategy in dynamic analysis of protein‐protein interaction in vivo. More than that, the proposed iSIPL strategy would facilitate large‐scale accurate quantitative proteomics by increasing multiplexing capability. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We present an update of the MaxQuant software for isobaric labeling data and evaluate its performance on benchmark data sets. Impurity correction factors can be applied to labels mixing C- and N-type reporter ions such as TMT Pro. Application to a single-cell multispecies mixture benchmark shows the high accuracy of the impurity-corrected results. TMT data recorded with FAIMS separation can be analyzed directly in MaxQuant without splitting the raw data into separate files per FAIMS voltage. Weighted median normalization is applied to several data sets, including large-scale human body atlas data. In the benchmark data sets, the weighted median normalization either removes or strongly reduces the batch effects between different TMT plexes and results in clustering by biology. In data sets including reference channels, we find that weighted median normalization performs as well or better when the reference channels are ignored and only the sample channel intensities are used, suggesting that the measurement of reference channels is unnecessary when using weighted median normalization in MaxQuant. We demonstrate that MaxQuant including the weighted median normalization performs well on multinotch MS3 data, as well as on phosphorylation data. MaxQuant is freely available for any purpose and can be downloaded from https://www.maxquant.org/.

The quantification of proteoforms, i.e., all molecular forms in which proteins can be present, by top-down proteomics provides essential insights into biological processes at the molecular level. Isobaric labeling-based quantification strategies are suitable for multidimensional separation strategies and allow for multiplexing of the samples. Here, we investigated cysteine-directed isobaric labeling by iodoTMT in combination with a gel- and gas-phase fractionation (GeLC-FAIMS-MS) for in-depth quantitative proteoform analysis. We optimized the acquisition workflow (i.e., the FAIMS compensation voltages, isolation windows, acquisition strategy, and fragmentation method) using a two-proteome mix to increase the number of quantified proteoforms and reduce ratio compression. Additionally, we implemented a mass feature-based quantification strategy in the widely used deconvolution algorithm FLASHDeconv, which improves and facilitates data analysis. The optimized iodoTMT GeLC-FAIMS-MS workflow was applied to quantitatively analyze the proteome of Escherichia coli grown under glucose or acetate as the sole carbon source, resulting in the identification of 726 differentially abundant proteoforms.

Studies of induced granulocytic differentiation help to reveal molecular mechanisms of cell maturation. The nuclear proteome represents a rich source of regulatory molecules, including transcription factors (TFs). It is important to have an understanding of molecular perturbations at the early stages of the differentiation processes. By applying the proteomic quantitative profiling using isobaric labeling, we found that the contents of 214, 319, 376, 426, and 391 proteins were altered at 3, 6, 9, 12, and 72 h, respectively, compared to 0 h in the HL-60 cell nuclear fraction under all-trans-retinoid acid (ATRA) treatment. From 1860 identified nuclear proteins, 231 proteins were annotated as proteins with transcription factor (TF) activity. Six TFs (RREB1, SRCAP, CCDC124, TRIM24, BRD7, and BUD31) were downregulated and three TFs EWSR1, ENO1, and FUS were upregulated at early time points (3–12 h) after ATRA treatment. Bioinformatic annotation indicates involvement of the HL-60 nuclear proteome in DNA damage recognition in the RUNX1-triggered pathway, and in the p53-regulation pathway. By applying scheduled multiple reaction monitoring using stable isotopically labeled peptide standards (MRM/SIS), we found a persistent increase in the content of the following proteins: PRAM1, CEPBP, RBPJ, and HIC1 in the HL-60 cell nuclear fraction during ATRA-induced granulocytic differentiation. In the case of STAT1, CASP3, PARP1, and PRKDC proteins, a transient increase in their content was observed at early time points (3–12 h) after the ATRA treatment. Obtained data on nuclear proteome composition and dynamics during granulocytic differentiation could be beneficial for the development of new treatment approaches for leukemias with the mutated p53 gene. [ABSTRACT FROM AUTHOR]

Protein glycosylation, covalent attachment of carbohydrates to polypeptide chains, is a highly important post-translational modification involved in many essential physiological processes. Comprehensive site-specific and quantitative analysis is crucial for revealing the diverse functions and dynamics of glycosylation. To characterize intact glycopeptides, mass spectrometry (MS)-based glycoproteomics employs versatile fragmentation methods, among which electron-transfer/higher-energy collision dissociation (EThcD) has gained great popularity. However, the inherent limitation of EThcD in fragmenting low-charge ions has prevented its widespread applications. Furthermore, there is a need to develop a high-throughput strategy for comparative glycoproteomics with a large cohort of samples. Herein, we developed isobaric N,N-dimethyl leucine-derivatized ethylenediamine (DiLeuEN) tags to increase the charge states of glycopeptides, thereby improving the fragmentation efficiency and allowing for in-depth intact glycopeptide analysis, especially for sialoglycopeptides. Moreover, the unique reporter ions of DiLeuEN-labeled glycopeptides generated in tandem MS spectra enable relative quantification of up to four samples in a single analysis, which represents a new high-throughput method for quantitative glycoproteomics. [ABSTRACT FROM AUTHOR]

Legumes are an essential source of nutrients that complement energy and protein requirements in the human diet. They also contribute to the intake of bioactive compounds such as polyphenols, whose content can vary depending on cultivars and genotypes. We conducted a comparative proteomics and metabolomics study to determine if there were significant variations in relevant nutraceutical compounds in the five genotypes of Kabuli-type chickpea grains. We performed an isobaric tandem mass tag (TMT) couple to synchronous precursor selection (SPS)-MS3 method along with a targeted and untargeted metabolomics approach based on accurate mass spectrometry. We observed an association between the overproduction of proteins involved in starch, lipid, and amino acid metabolism with gibberellin accumulation in large grains. In contrast, we visualized the over-accumulation of proteins associated with water deprivation in small grains. It was possible to visualize in small grains the over-accumulation of some phenolics such as vanillin, salicylic acid, protocatechuic acid, 4-coumaric acid, 4-hydroxybenzoic acid, vanillic acid, ferulic acid, and kaempferol 3-O-glucoside as well as the amino acid l-phenylalanine. The activated phenolic pathway was associated with the higher antioxidant capacity of small grains. Small grains consumption could be advantageous due to their nutraceutical properties. [ABSTRACT FROM AUTHOR]

Mass spectrometry (MS)-based proteomics is a powerful tool for identifying and quantifying proteins. However, chimeric spectra caused by the fragmentation of multiple precursors within the same isolation window impair the accuracy of peptide identification and isobaric mass tag-based quantification. While there have been advances in computational deconvolution of chimeric spectra and methods to further separate the peptides by ion mobility or through MSn, the use of narrower isolation windows to decrease the fraction of chimeric species remains to be fully explored. We present results obtained on a SCIEX TripleTOF instrument where the quadrupole was optimized and tuned for precursor isolation at 0.1 Da (FWHH). Using a three-proteome model (trypsin digest of protein lysates from yeast, human and E. coli) and 8-plex iTRAQ labeling to document the interference effect, we investigated the impact of co-fragmentation on spectral purity, identification accuracy and quantification accuracy. The narrow quadrupole isolation window significantly improved the spectral purity and reduced the interference of non-target precursors on quantification accuracy. The high-resolution isolation strategy also reduced the number of false identifications caused by chimeric spectra. While these improvements came at the cost of sensitivity loss, combining high-resolution isolation with other advanced techniques, including ion mobility, may result in improved accuracy in identification and quantification. Compared to standard-resolution quadrupole isolation (0.7 Da), high-resolution quadrupole isolation (0.1 Da) significantly improved the spectral purity and quantification accuracy while reducing the number of potential false identifications caused by chimeric spectra, thus showing excellent potential for further development to analyze clinical proteomics samples, for which high accuracy is essential. [Display omitted] • We optimized and tuned a SCIEX TripleTOF instrument to achieve high-resolution quadrupole isolation (0.1 Da isolation width). • An 8-plex iTRAQ labeled three-proteome model was designed to document the co-fragmentation effect. • High-resolution quadrupole significantly improved the spectral purity and quantification accuracy. • High-resolution quadrupole reduced the number of false identifications caused by chimeric spectra. [ABSTRACT FROM AUTHOR]

Crystallin proteins serve as both essential structural and as well as protective components of the ocular lens and are required for the transparency and light refraction properties of the organ. The mouse lens crystallin proteome is represented by αA-, αB-, βA1-, βA2-, βA3-, βA4-, βB1-, βB2-, βB3-, γA-, γB-, γC-, γD-, γE, γF-, γN-, and γS-crystallin proteins encoded by 16 genes. Their mutations are responsible for lens opacification and early onset cataract formation. While many cataract-causing missense and nonsense mutations are known for these proteins, including the human CRYBB3 gene, the mammalian loss-of function model of the Crybb3 gene remains to be established. Herein, we generated the first mouse model via deletion of the Crybb3 promoter that abolished expression of the βB3-crystallin. Histological analysis of lens morphology using newborn βB3-crystallin-deficient lenses revealed disrupted lens morphology with early-onset phenotypic variability. In-depth lens proteomics at four time points (newborn, 3-weeks, 6-weeks, and 3-months) showed both down- and up-regulation of various proteins, with the highest divergence from control mice observed in 3-months lenses. Apart from the βB3-crystallin, another protein Smarcc1/Baf155 was down-regulated in all four samples. In addition, downregulation of Hspe1, Pdlim1, Ast/Got, Lsm7, Ddx23, and Acad11 was found in three time points. Finally, we show that the βB3-crystallin promoter region, which contains multiple binding sites for the transcription factors AP-2α, c-Jun, c-Maf, Etv5, and Pax6 is activated by FGF2 in primary lens cell culture experiments. Together, these studies establish the mouse Crybb3 loss-of-function model and its disrupted crystallin and non-crystallin proteomes., Competing Interests: Conflict of interest The authors declare no conflict of interests.

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ∼3500 proteins at a spatial resolution of 50 μm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provides robust protein quantifications in identifying differentially abundant proteins and spatially covariable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial coexpression analysis., Competing Interests: Conflict of interest Y. Z. is an employee of Genentech Inc. and shareholder of Roche Group. A. I. N. and F. Y. receive royalties from the University of Michigan for the sale of MSFragger and IonQuant software licenses to commercial entities. All license transactions are managed by the University of Michigan Innovation Partnerships office and all proceeds are subject to university technology transfer policy. The other authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Global and phosphoproteome profiling has demonstrated great utility for the analysis of clinical specimens. One barrier to the broad clinical application of proteomic profiling is the large amount of biological material required, particularly for phosphoproteomics─currently on the order of 25 mg wet tissue weight. For hematopoietic cancers such as acute myeloid leukemia (AML), the sample requirement is ≥10 million peripheral blood mononuclear cells (PBMCs). Across large study cohorts, this requirement will exceed what is obtainable for many individual patients/time points. For this reason, we were interested in the impact of differential peptide loading across multiplex channels on proteomic data quality. To achieve this, we tested a range of channel loading amounts (approximately the material obtainable from 5E5, 1E6, 2.5E6, 5E6, and 1E7 AML patient cells) to assess proteome coverage, quantification precision, and peptide/phosphopeptide detection in experiments utilizing isobaric tandem mass tag (TMT) labeling. As expected, fewer missing values were observed in TMT channels with higher peptide loading amounts compared to lower loadings. Moreover, channels with a lower loading have greater quantitative variability than channels with higher loadings. A statistical analysis showed that decreased loading amounts result in an increase in the type I error rate. We then examined the impact of differential loading on the detection of known differences between distinct AML cell lines. Similar patterns of increased data missingness and higher quantitative variability were observed as loading was decreased resulting in fewer statistical differences; however, we found good agreement in features identified as differential, demonstrating the value of this approach. [ABSTRACT FROM AUTHOR]

Mass spectrometry-based single-cell proteomics (scMS) is experiencing rapid evolution due to the increased sensitivity of mass spectrometers as well as advances in multiplexing and sample preparation. To date, researchers have focused on two general approaches to scMS: label-free and isobaric label-based multiplexing. While label-free analysis provides straightforward sample preparation and a clear path to automation, it currently lacks the throughput necessary to practically analyze thousands of single cells. Multiplexed analysis utilizing isobaric labels requires additional sample manipulation but increases throughput such that analyzing thousands of cells is currently achievable. A key feature of multiplexed scMS experiments is a 'carrier proteome' – a sample added at 25x-500x, the single-cell sample that increases the number of proteins that can be identified in an MS analysis. Here, we review early examples of carrier proteomes in quantitative proteomics before summarizing advantages and challenges of using a carrier proteome in scMS experiments. We conclude that the addition of carrier proteomes improves depth of identification for scMS, but high levels of carrier proteomes can have adverse effects on quantitative accuracy and precision. [ABSTRACT FROM AUTHOR]

Fatty acids (FAs) are essential cellular components and play important roles in various biological processes. Importantly, FAs produced by microorganisms from renewable sugars are considered sustainable substrates for biodiesels and oleochemicals. Their complex structures and diverse functional roles in biochemical processes necessitate the development of efficient and accurate methods for their quantitative analysis. Here, we developed a novel method for relative quantification of FAs by combining 12-plex isobaric N,N - di methyl leu cine-derivatized e thyle n ediamine (DiLeuEN) labeling and microchip capillary electrophoresis-mass spectrometry (CE-MS). This method enables simultaneous quantification of 12 samples in a single MS analysis. DiLeuEN labeling introduced tertiary amine center structure into FAs, which makes them compatible with the positive mode separation of commercial microchip CE systems and further improves the sensitivity. The CE separation parameters were optimized, and the quantification accuracy was assessed using FA standards. Microchip CE-MS detection exhibited high sensitivity with a femtomole level detection limit and a total analysis time within 8 min. Finally, the applicability of our method to complex biological samples was demonstrated by analyzing FAs produced by four industrially relevant yeast strains (Saccharomyces cerevisiae , Yarrowia lipolytica YB-432 , Yarrowia lipolytica Po1f and Rhodotorula glutinis). The analysis time for each sample is less than 1 min. This work addresses the current challenges in the field by introducing a method that combines microchip-based capillary electrophoresis separation with multiplex isobaric labeling. Our method not only offers remarkable sensitivity and rapid analysis speed but also the capability to quantify fatty acids across multiple samples simultaneously, which holds significant potential for extensive application in FA quantitative studies in diverse research areas, promising an enhanced understanding of FA functions and mechanisms. [Display omitted] • Integrated 12-plex DiLeuEN isobaric labeling with CE-MS to enable rapid and precise fatty acids (FAs) relative quantification. • Enhanced the throughput of FAs quantification with notable precision and accuracy through 12-plex DiLeuEN isobaric labeling. • Achieved fast FAs separation in 8 min with fmol level detection limits via microchip CE-MS. • Successfully applied the developed method for quantitative analysis of FAs across four different yeast strains. [ABSTRACT FROM AUTHOR]

Isotope tags for relative and absolute quantification (iTRAQ) are among the most widely used proteomics quantification techniques. These tags can be rapidly coupled to the primary amines of proteins/peptides through chemical reactions under mild conditions, making this technique universally applicable to any kind of sample. However, iTRAQ reagents also partially react with the hydroxyl groups of serine, threonine and tyrosine residues, particularly when these residues coexist with a histidine residue in the same peptide. This overlabeling of peptides causes systematic biases and significantly compromises protein/peptide identification rates. In this study, we report a novel iTRAQ labeling method that overcomes the detrimental overlabeling while providing high amine labeling efficiency. The impacts of reaction temperature, reactant concentrations, reaction time, buffer compositions, and pH on iTRAQ labeling performance were investigated in-depth. In a comparison experiment between our method and the standard labeling method provided by the iTRAQ manufacturer, our method reduced the number of overlabeled peptides by 55-fold while achieving comparable amine labeling efficiency. This improvement allowed our method to eliminates the systematic bias against histidyl- and hydroxyl-containing peptides, and more importantly, enabled the identification of 23.9% more peptides and 9.8% more proteins. In addition to amines, the hydroxyl groups in serine, threonine, and tyrosine residues can also partially labeled by iTRAQ reagents, which leads to systematic biases and significantly compromises the analytical sensitivity. To address this issue, we developed a novel iTRAQ labeling method that overcomes the detrimental overlabeling while providing high labeling efficiency of amines. When benchmarking our method against the standard method provided by the reagent manufacturer, our method achieved comparable labeling efficiency but reduced the overlabeled species by 55-fold. This significant improvement eliminated the systematic biases, and more importantly, enabled the identification of 23.9% more peptides and 9.8% more proteins, demonstrating its superior performance and potential to enhance proteome quantification using iTRAQ labeling. [Display omitted] • A novel iTRAQ labeling method overcomes harmful O-acylation of hydroxyl residues. • Elimination of systematic bias against histidyl- and hydroxyl-containing peptides. • Significantly increased identification rates for overall peptides and proteins. • A practical and accessible method requiring no special reagent or added experiment step. [ABSTRACT FROM AUTHOR]

Legumes are an essential source of nutrients that complement energy and protein requirements in the human diet. They also contribute to the intake of bioactive compounds such as polyphenols, whose content can vary depending on cultivars and genotypes. We conducted a comparative proteomics and metabolomics study to determine if there were significant variations in relevant nutraceutical compounds in the five genotypes of Kabuli-type chickpea grains. We performed an isobaric tandem mass tag (TMT) couple to synchronous precursor selection (SPS)-MS3 method along with a targeted and untargeted metabolomics approach based on accurate mass spectrometry. We observed an association between the overproduction of proteins involved in starch, lipid, and amino acid metabolism with gibberellin accumulation in large grains. In contrast, we visualized the over-accumulation of proteins associated with water deprivation in small grains. It was possible to visualize in small grains the over-accumulation of some phenolics such as vanillin, salicylic acid, protocatechuic acid, 4-coumaric acid, 4-hydroxybenzoic acid, vanillic acid, ferulic acid, and kaempferol 3-O-glucoside as well as the amino acid l-phenylalanine. The activated phenolic pathway was associated with the higher antioxidant capacity of small grains. Small grains consumption could be advantageous due to their nutraceutical properties.

Labeling approaches using isobaric chemical tags (e.g. isobaric tagging for relative and absolute quantification, iTRAQ and tandem mass tag, TMT) have been widely applied for the quantification of peptides and proteins in bottom-up MS. However, until recently, successful applications of these approaches to top-down proteomics have been limited because proteins tend to precipitate and "crash" out of solution during TMT labeling of complex samples making the quantification of such samples difficult. In this study, we report a top-down TMT MS platform for confidently identifying and quantifying low molecular weight intact proteoforms in complex biological samples. To reduce the sample complexity and remove large proteins from complex samples, we developed a filter-SEC technique that combines a molecular weight cutoff filtration step with high-performance size exclusion chromatography (SEC) separation. No protein precipitation was observed in filtered samples under the intact protein-level TMT labeling conditions. The proposed top-down TMT MS platform enables high-throughput analysis of intact proteoforms, allowing for the identification and quantification of hundreds of intact proteoforms from Escherichia coli cell lysates. To our knowledge, this represents the first high-throughput TMT labeling-based, quantitative, top-down MS analysis suitable for complex biological samples. [ABSTRACT FROM AUTHOR]

Proteins undergo reversible S -acylation via a thioester linkage in vivo. S -palmitoylation, modification by C16:0 fatty acid, is a common S -acylation that mediates critical protein-membrane and protein-protein interactions. The most widely used S -acylation assays, including acyl-biotin exchange and acyl resin-assisted capture, utilize blocking of free Cys thiols, hydroxylamine-dependent cleavage of the thioester and subsequent labeling of nascent thiol. These assays generally require >500 μg of protein input material per sample and numerous reagent removal and washing steps, making them laborious and ill-suited for high throughput and low input applications. To overcome these limitations, we devised "Acyl-Trap", a suspension trap-based assay that utilizes a thiol-reactive quartz to enable buffer exchange and hydroxylamine-mediated S -acyl enrichment. We show that the method is compatible with protein-level detection of S -acylated proteins (e.g., H-Ras) as well as S -acyl site identification and quantification using "on trap" isobaric labeling and LC-MS/MS from as little as 20 μg of protein input. In mouse brain, Acyl-Trap identified 279 reported sites of S -acylation and 1298 previously unreported putative sites. Also described are conditions for long-term hydroxylamine storage, which streamline the assay. More generally, Acyl-Trap serves as a proof-of-concept for PTM-tailored suspension traps suitable for both traditional protein detection and chemoproteomic workflows.

Pathway proteomics strategies measure protein expression changes in specific cellular processes that carry out related functions. Using targeted tandem mass tags-based sample multiplexing, hundreds of proteins can be quantified across 10 or more samples simultaneously. To facilitate these highly complex experiments, we introduce a strategy that provides complete control over targeted sample multiplexing experiments, termed Tomahto, and present its implementation on the Orbitrap Tribrid mass spectrometer platform. Importantly, this software monitors via the external desktop computer to the data stream and inserts optimized MS2 and MS3 scans in real time based on an application programming interface with the mass spectrometer. Hundreds of proteins of interest from diverse biological samples can be targeted and accurately quantified in a sensitive and high-throughput fashion. It achieves sensitivity comparable to, if not better than, deep fractionation and requires minimal total sample input (~10 µg). As a proof-of-principle experiment, we selected four pathways important in metabolism- and inflammation-related processes (260 proteins/520 peptides) and measured their abundance across 90 samples (nine tissues from five old and five young mice) to explore effects of aging. Tissue-specific aging is presented here and we highlight the role of inflammation- and metabolism-related processes in white adipose tissue. We validated our approach through comparison with a global proteome survey across the tissues, work that we also provide as a general resource for the community. [ABSTRACT FROM AUTHOR]

Multiplexed proteomics using isobaric tagging allows for simultaneously comparing the proteomes of multiple samples. In this technique, digested peptides from each sample are labeled with a chemical tag prior to pooling sample for LC-MS/MS with nanoflow chromatography (NanoLC). The isobaric nature of the tag prevents deconvolution of samples until fragmentation liberates the isotopically labeled reporter ions. To ensure efficient peptide labeling, large concentrations of labeling reagents are included in the reagent kits to allow scientists to use high ratios of chemical label per peptide. The increasing speed and sensitivity of mass spectrometers has reduced the peptide concentration required for analysis, leading to most of the label or labeled sample to be discarded. In conjunction, improvements in the speed of sample loading, reliable pump pressure, and stable gradient construction of analytical flow HPLCs has continued to improve the sample delivery process to the mass spectrometer. In this study we describe a method for performing multiplexed proteomics without the use of NanoLC by using offline fractionation of labeled peptides followed by rapid “standard flow” HPLC gradient LC-MS/MS. Standard Flow Multiplexed Proteomics (SFloMPro) enables high coverage quantitative proteomics of up to 16 mammalian samples in about 24 h. In this study, we compare NanoLC and SFloMPro analysis of fractionated samples. Our results demonstrate that comparable data is obtained by injecting 20 µg of labeled peptides per fraction with SFloMPro, compared to 1 µg per fraction with NanoLC. We conclude that, for experiments where protein concentration is not strictly limited, SFloMPro is a competitive approach to traditional NanoLC workflows with improved up-time, reliability and at a lower relative cost per sample.

Objective To screen for the differential expression proteins in brain tissues of SD rat after diffuse axonal injury （DAI） by isobaric tag for relative and absolute quantification-liquid chromatograph-mass spectrometer/mass spectrometer （iTRAQ-LC-MS/MS）, and to explore potential biomarkers available for the diagnosis of DAI. Methods Animal models of DAI were established with the Marmarou method as reference, and the subjects were divided into blank control group （n=4）, sham strike group （n=4） and fatal strike group （n=4）, respectively. The proteins in rat brain tissues were detected by iTRAQ-LC-MS/MS, and bioinformatics analysis and verification were performed on the results and screened for the differential expression proteins. Results A total of 2 016 proteins were identified and quantified. The bioinformatics analysis revealed that the proteins had wide distribution and function, and participated in different biological processes. There were 16 proteins showed differential expression in fatal strike group, including one up-regulated expression protein and 15 down-regulated expression proteins. The results of iTRAQ-LC-MS/MS were confirmed by Western blotting method. Conclusion Multiple differential expression proteins in rat brain tissues after DAI can be screened by iTRAQ-LC-MS/MS. This not only indicates a research direction for exploring the pathogenesis of DAI, but also provides potential biomarkers available for the diagnosis of DAI.

Tandem mass tags (TMT) are widely used in proteomics to simultaneously quantify multiple samples in a single experiment. The tags can be easily added to the primary amines of peptides/proteins through chemical reactions. In addition to amines, TMT reagents also partially react with the hydroxyl groups of serine, threonine, and tyrosine residues under alkaline conditions, which significantly compromises the analytical sensitivity and precision. Under alkaline conditions, reducing the TMT molar excess can partially mitigate overlabeling of histidine-free peptides, but has a limited effect on peptides containing histidine and hydroxyl groups. Here, we present a method under acidic conditions to suppress overlabeling while efficiently labeling amines, using only one-fifth of the TMT amount recommended by the manufacturer. In a deep-scale analysis of a yeast/human two-proteome sample, we systematically evaluated our method against the manufacturer's method and a previously reported TMT-reduced method. Our method reduced overlabeled peptides by 9-fold and 6-fold, respectively, resulting in the substantial enhancement in peptide/protein identification rates. More importantly, the quantitative accuracy and precision were improved as overlabeling was reduced, endowing our method with greater statistical power to detect 42% and 12% more statistically significant yeast proteins compared to the standard and TMT-reduced methods, respectively. Mass spectrometric data have been deposited in the ProteomeXchange Consortium via the iProX partner repository with the data set identifier PXD047052.

GoDig, a platform for targeted pathway proteomics without the need for manual assay scheduling or synthetic standards, is a powerful, flexible, and easy-to-use method that uses tandem mass tags to increase sample throughput up to 18-fold relative to label-free methods. Though the protein-level success rates of GoDig are high, the peptide-level success rates are more limited, hampering assays of harder-to-quantify proteins and site-specific phenomena. To guide the optimization of GoDig assays as well as improvements to the GoDig platform, we created GoDigViewer, a new stand-alone software that provides detailed visualizations of GoDig runs. GoDigViewer guided the implementation of "priming runs," an acquisition mode with significantly higher success rates. In this mode, two or more chromatographic priming runs are automatically performed to improve the accuracy and precision of target elution orders, followed by analytical runs which quantify targets. Using priming runs, success rates exceeded 97% for a list of 400 peptide targets and 95% for a list of 200 targets that are usually not quantified using untargeted mass spectrometry. We used priming runs to establish a quantitative assay of 125 macroautophagy proteins that had a >95% success rate and revealed differences in macroautophagy expression profiles across four human cell lines.

Mass spectrometry (MS)-based single-cell proteomics (SCP) provides us the opportunity to unbiasedly explore biological variability within cells without the limitation of antibody availability. This field is rapidly developed with the main focuses on instrument advancement, sample preparation refinement, and signal boosting methods; however, the optimal data processing and analysis are rarely investigated which holds an arduous challenge because of the high proportion of missing values and batch effect. Here, we introduced a quantification quality control to intensify the identification of differentially expressed proteins (DEPs) by considering both within and across SCP data. Combining quantification quality control with isobaric matching between runs (IMBR) and PSM-level normalization, an additional 12% and 19% of proteins and peptides, with more than 90% of proteins/peptides containing valid values, were quantified. Clearly, quantification quality control was able to reduce quantification variations and q-values with the more apparent cell type separations. In addition, we found that PSM-level normalization performed similar to other protein-level normalizations but kept the original data profiles without the additional requirement of data manipulation. In proof of concept of our refined pipeline, six uniquely identified DEPs exhibiting varied fold-changes and playing critical roles for melanoma and monocyte functionalities were selected for validation using immunoblotting. Five out of six validated DEPs showed an identical trend with the SCP dataset, emphasizing the feasibility of combining the IMBR, cell quality control, and PSM-level normalization in SCP analysis, which is beneficial for future SCP studies., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Mass spectrometry-based stable isotope labeling provides the advantages of multiplexing capability and accurate quantification but requires tailored bioinformatics tools for data analysis. Despite the rapid advancements in analytical methodology, it is often challenging to analyze stable isotope labeling-based metabolomics data, particularly for isobaric labeling using MS/MS reporter ions for quantification. We report Metandem, a novel online software tool for isobaric labeling-based metabolomics, freely available at http://metandem.com/web/. Metandem provides a comprehensive data analysis pipeline integrating feature extraction, metabolite quantification, metabolite identification, batch processing of multiple data files, online parameter optimization for custom datasets, data normalization, and statistical analysis. Systematic evaluation of the Metandem tool was demonstrated on UPLC-MS/MS, nanoLC-MS/MS, CE-MS/MS and MALDI-MS platforms, via duplex, 4-plex, 10-plex, and 12-plex isobaric labeling experiments and the application to various biological samples. Image 1 • A novel online software tool, Metandem, was developed for isobaric labeling-based metabolomics. • Metandem provides highly accurate metabolite quantification on the MS/MS level. • Online parameter optimization, identification, and statistics can be conducted simultaneously. • Metandem was evaluated by various MS platforms and multiplex isobaric labeling experiments. [ABSTRACT FROM AUTHOR]

Analyzing the phosphoproteome at nanoscale poses a significant challenge, mainly due to the substantial sample loss from nonspecific surface adsorption during the enrichment of low stoichiometric phosphopeptides. Here, we describe a tandem tip-based phosphoproteomics sample preparation method capable of sequential sample cleanup and enrichment without the need for additional sample transfer, thereby minimizing sample loss. Integration of this method to our recently developed SOP (surfactant-assisted one-pot sample preparation) and iBASIL (improved boosting to amplify signal with isobaric labeling) approaches creates a streamlined workflow, enabling sensitive, high-throughput nanoscale phosphoproteomics measurements., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Glycans, which are ubiquitously distributed on most proteins and cell surfaces, are a class of important biomolecules playing crucial roles in various biological processes such as molecular recognition and cellular communication. Modern mass spectrometry (MS) coupled with novel chemical probe labeling strategies has greatly advanced analysis of glycans. However, the requirement of high-throughput and robust quantitative analysis still calls for the development of more advanced tools. Recently, we devised isobaric multiplex reagents for carbonyl-containing compound (SUGAR) tags for 4-plex N-glycan analysis. To further improve the throughput, we utilized the mass-defect strategy and expanded the multiplexing capacity to 12 channels without changing the chemical structure of the SUGAR tag, achieving a threefold enhancement in throughput compared with the original design and managing to perform high-throughput N-glycan analysis in a single LC - MS/MS injection. Herein, we present detailed methods for the synthesis of 12-plex SUGAR isobaric tags, the procedure to release and label the N-glycans from proteins, and the analysis by high-resolution LC-MS/MS, as well as data processing to achieve multiplexed quantitative glycomics., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Abstract Enzymatic 18O exchange, the well-established approach in comparative proteomics, has some disadvantages such as back exchange of labeled oxygen and overlapping the peak of a labeled peptide with isotopic peaks of an unlabeled one. Herein we demonstrated a simple procedure in which samples digested with a trypsin (with and without H 2 18O) were reacted with unlabeled and quadrupled 13C-labeled pyrylium salt respectively which results in formation of pyridinium cations. Thus, each isobarically labeled peptide containing zero or four 13C atoms in the mass reporter group, during tandem MS/MS forms an unique reporter ion useful for a relative quantitation. Such a sample treatment improves the signal to noise ratio, reduces overlapping of the isotopic peaks and completely eliminates the back exchange problem. Graphical abstract Image 1 Highlights • Formation of the isobaric peptides derivatives (duplex) in two samples compared. • A combination of enzymatic incorporation of 18O and reaction with 13C pyrylium salt. • The MS/MS experiment generates diagnostic ions shifted by 4 Da. • It solves the problem of overlapping of the isotopic peaks in the 18O approach. • Method eliminates the risk of back-exchange and increase of the ionization efficiency. [ABSTRACT FROM AUTHOR]

Over the past decade, chemical labeling with isobaric tandem mass tags, such as isobaric tags for relative and absolute quantification reagents (iTRAQ) and tandem mass tag (TMT) reagents, has been employed in a wide range of different clinically orientated serum and plasma proteomics studies. In this review the scope of these works is presented with attention to the areas of research, methods employed and performance limitations. These applications have covered a wide range of diseases, disorders and infections, and have implemented a variety of different preparative and mass spectrometric approaches. In contrast to earlier works, which struggled to quantify more than a few hundred proteins, increasingly these studies have provided deeper insight into the plasma proteome extending the numbers of quantified proteins to over a thousand. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is the most prevalent form of dementia, disproportionately affecting women in disease prevalence and progression. Comprehensive analysis of the serum proteome in a common AD mouse model offers potential in identifying possible AD pathology- and gender-associated biomarkers. Here, we introduce a multiplexed, nondepleted mouse serum proteome profiling via tandem mass-tag (TMTpro) labeling. The labeled sample was separated into 475 fractions using basic reversed-phase liquid chromatography (RPLC), which were categorized into low-, medium-, and high-concentration fractions for concatenation. This concentration-dependent concatenation strategy resulted in 128 fractions for acidic RPLC-tandem mass spectrometry (MS/MS) analysis, collecting ∼5 million MS/MS scans and identifying 3972 unique proteins (3413 genes) that cover a dynamic range spanning at least 6 orders of magnitude. The differential expression analysis between wild type and the commonly used AD model (5xFAD) mice exhibited minimal significant protein alterations. However, we detected 60 statistically significant (FDR < 0.05), sex-specific proteins, including complement components, serpins, carboxylesterases, major urinary proteins, cysteine-rich secretory protein 1, pregnancy-associated murine protein 1, prolactin, amyloid P component, epidermal growth factor receptor, fibrinogen-like protein 1, and hepcidin. The results suggest that our platform possesses the sensitivity and reproducibility required to detect sex-specific differentially expressed proteins in mouse serum samples.