Tandem Mass Tags Reporter Ions Research Articles

Understanding proteome quantification in an interactive learning module on Google Cloud Platform.

This manuscript describes the development of a resource module that is part of a learning platform named 'NIGMS Sandbox for Cloud-based Learning' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox at the beginning of this Supplement. This module delivers learning materials on protein quantification in an interactive format that uses appropriate cloud resources for data access and analyses. Quantitative proteomics is a rapidly growing discipline due to the cutting-edge technologies of high resolution mass spectrometry. There are many data types to consider for proteome quantification including data dependent acquisition, data independent acquisition, multiplexing with Tandem Mass Tag reporter ions, spectral counts, and more. As part of the NIH NIGMS Sandbox effort, we developed a learning module to introduce students to mass spectrometry terminology, normalization methods, statistical designs, and basics of R programming. By utilizing the Google Cloud environment, the learning module is easily accessible without the need for complex installation procedures. The proteome quantification module demonstrates the analysis using a provided TMT10plex data set using MS3 reporter ion intensity quantitative values in a Jupyter notebook with an R kernel. The learning module begins with the raw intensities, performs normalization, and differential abundance analysis using limma models, and is designed for researchers with a basic understanding of mass spectrometry and R programming language. Learners walk away with a better understanding of how to navigate Google Cloud Platform for proteomic research, and with the basics of mass spectrometry data analysis at the command line. This manuscript describes the development of a resource module that is part of a learning platform named ``NIGMS Sandbox for Cloud-based Learning'' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [1] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.

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.

Evaluating the Performance of 193 nm Ultraviolet Photodissociation for Tandem Mass Tag Labeled Peptides

Despite the successful application of tandem mass tags (TMT) for peptide quantitation, missing reporter ions in higher energy collisional dissociation (HCD) spectra remains a challenge for consistent quantitation, especially for peptides with labile post-translational modifications. Ultraviolet photodissociation (UVPD) is an alternative ion activation method shown to provide superior coverage for sequencing of peptides and intact proteins. Here, we optimized and evaluated 193 nm UVPD for the characterization of TMT-labeled model peptides, HeLa proteome, and N-glycopeptides from model proteins. UVPD yielded the same TMT reporter ions as HCD, at m/z 126–131. Additionally, UVPD produced a wide range of fragments that yielded more complete characterization of glycopeptides and less frequent missing TMT reporter ion channels, whereas HCD yielded a strong tradeoff between characterization and quantitation of TMT-labeled glycopeptides. However, the lower fragmentation efficiency of UVPD yielded fewer peptide identifications than HCD. Overall, 193 nm UVPD is a valuable tool that provides an alternative to HCD for the quantitation of large and highly modified peptides with labile PTMs. Continued development of instrumentation specific to UVPD will yield greater fragmentation efficiency and fulfil the potential of UVPD to be an all-in-one spectrum ion activation method for broad use in the field of proteomics.

Global quantitative analysis of the human brain proteome and phosphoproteome in Alzheimer\u2019s disease

Alzheimer’s disease (AD) is characterized by an early, asymptomatic phase (AsymAD) in which individuals exhibit amyloid-beta (Aβ) plaque accumulation in the absence of clinically detectable cognitive decline. Here we report an unbiased multiplex quantitative proteomic and phosphoproteomic analysis using tandem mass tag (TMT) isobaric labeling of human post-mortem cortex (n = 27) across pathology-free controls, AsymAD and symptomatic AD individuals. With off-line high-pH fractionation and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) on an Orbitrap Lumos mass spectrometer, we identified 11,378 protein groups across three TMT 11-plex batches. Immobilized metal affinity chromatography (IMAC) was used to enrich for phosphopeptides from the same TMT-labeled cases and 51,736 phosphopeptides were identified. Of these, 48,992 were quantified by TMT reporter ions representing 33,652 unique phosphosites. Two reference standards in each TMT 11-plex were included to assess intra- and inter-batch variance at the protein and peptide level. This comprehensive human brain proteome and phosphoproteome dataset will serve as a valuable resource for the identification of biochemical, cellular and signaling pathways altered during AD progression.

Abstract 559: Proteomic analysis of lung cancer cells exposed to tumor treating fields identified the dysregulation of the E2F-Rb-CDK4/6 axis rendering tumor cells susceptible to novel combination therapies that target CDK4/6 and/or E2F

Abstract TTFields is a novel non-invasive physical modality of cancer therapy now approved for recurrent and newly diagnosed glioblastoma multiforme (GBM) in combination with temozolomide, and unresectable locally advanced or metastatic malignant pleural mesothelioma (MPM) in combination with platinum based chemotherapy. Clinical trials are ongoing for other cancers, including lung, pancreatic, and ovarian cancers. TTFields are low-intensity, intermediate frequency, alternating electric fields that are applied to tumor regions and cells using non-invasive arrays. One mechanism described for TTFields induced cell death has been via the disruption of mitosis while a more recent examination suggests that TTFields causes replication stress, and down-regulates DNA repair and cell cycle checkpoint genes. However, the exact cause of the downregulation of DNA repair and cell cycle checkpoint genes has been elusive. To that end, we employed relative quantitative proteomic analysis using tandem mass tags (TMT). All samples underwent trypsin digestion and labelling with different TMT reagents. They were then combined and the mixture was analyzed on an Orbitrap Fusion mass spectrometry device. Peptide quantitation was accomplished by comparing the intensities of the TMT reporter ions. STRING DB analysis of differentially expressed proteins revealed interaction networks that included cell cycle, DNA damage repair and replication, and transcriptional and translational regulation. Upstream analysis of key genes associated with cell cycle checkpoint and DNA repair identified reduced expression of the transcriptional activators E2F1 and E2F2 and increased expression of the transcriptional repressor E2F6, suggesting that TTFields affects the CDK-RB-E2F axis. For example, the downregulation of key DNA repair genes including RAD51, BRCA1 and BRCA2 could be explained through the upregulation of the transcriptional repressors E2F4 and E2F6 (a known repressor of BRCA1). These proteins are involved in homologous recombination repair and nucleotide excision repair, but also with replication fork maintenance, replication fork collapse and overall replication stress, the latter of which likely leads to cell death. Therefore, TTFields was combined with the E2F inhibitor HLM006474 with or without the CDK4/6 inhibitor abemaciclib. TTFields in combination with either inhibitor enhanced cell killing synergistically, as compared to TTFields alone, while the triple combination was found to be highly lethal (>90% by 72 h) as measured by clonogenic assay followed by the Highest Single Agent approach to determine synergy. Taken together our results identify the CDK-RB-E2F axis as a novel druggable target that can be used in combination with TTFields for cancer therapy. Citation Format: Narasimha Kumar Karanam, Sivaramakrishna Yadavalli, Michael Story. Proteomic analysis of lung cancer cells exposed to tumor treating fields identified the dysregulation of the E2F-Rb-CDK4/6 axis rendering tumor cells susceptible to novel combination therapies that target CDK4/6 and/or E2F [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 559.

Tandem Mass Tag Approach Utilizing Pervanadate BOOST Channels Delivers Deeper Quantitative Characterization of the Tyrosine Phosphoproteome

Dynamic tyrosine phosphorylation is fundamental to a myriad of cellular processes. However, the inherently low abundance of tyrosine phosphorylation in the proteome and the inefficient enrichment of phosphotyrosine(pTyr)-containing peptides has led to poor pTyr peptide identification and quantitation, critically hindering researchers' ability to elucidate signaling pathways regulated by tyrosine phosphorylation in systems where cellular material is limited. The most popular approaches to wide-scale characterization of the tyrosine phosphoproteome use pTyr enrichment with pan-specific, anti-pTyr antibodies from a large amount of starting material. Methods that decrease the amount of starting material and increase the characterization depth of the tyrosine phosphoproteome while maintaining quantitative accuracy and precision would enable the discovery of tyrosine phosphorylation networks in rarer cell populations. To achieve these goals, the BOOST (Broad-spectrum Optimization Of Selective Triggering) method leveraging the multiplexing capability of tandem mass tags (TMT) and the use of pervanadate (PV) boost channels (cells treated with the broad-spectrum tyrosine phosphatase inhibitor PV) selectively increased the relative abundance of pTyr-containing peptides. After PV boost channels facilitated selective fragmentation of pTyr-containing peptides, TMT reporter ions delivered accurate quantitation of each peptide for the experimental samples while the quantitation from PV boost channels was ignored. This method yielded up to 6.3-fold boost in pTyr quantification depth of statistically significant data derived from contrived ratios, compared with TMT without PV boost channels or intensity-based label-free (LF) quantitation while maintaining quantitative accuracy and precision, allowing quantitation of over 2300 unique pTyr peptides from only 1 mg of T cell receptor-stimulated Jurkat T cells. The BOOST strategy can potentially be applied in analyses of other post-translational modifications where treatments that broadly elevate the levels of those modifications across the proteome are available.

Limits for Resolving Isobaric Tandem Mass Tag Reporter Ions Using Phase-Constrained Spectrum Deconvolution.

A popular method for peptide quantification relies on isobaric labeling such as tandem mass tags (TMT), which enables multiplexed proteome analyses. Quantification is achieved by reporter ions generated by fragmentation in a tandem mass spectrometer. However, with higher degrees of multiplexing, the smaller mass differences between the reporter ions increase the mass resolving power requirements. This contrasts with faster peptide sequencing capabilities enabled by lowered mass resolution on Orbitrap instruments. It is therefore important to determine the mass resolution limits for highly multiplexed quantification when maximizing proteome depth. Here, we defined the lower boundaries for resolving TMT reporter ions with 0.0063 Da mass differences using an ultra-high-field Orbitrap mass spectrometer. We found the optimal method depends on the relative ratio between closely spaced reporter ions and that 64 ms transient acquisition time provided sufficient resolving power for separating TMT reporter ions with absolute ratio changes up to 16-fold. Furthermore, a 32 ms transient processed with phase-constrained spectrum deconvolution provides >50% more identifications with >99% quantified but with a slight loss in quantification precision and accuracy. These findings should guide decisions on what Orbitrap resolution settings to use in future proteomics experiments, relying on isobaric TMT reporter ion quantification.

Spectral Library Search Improves Assignment of TMT Labeled MS/MS Spectra.

Tandem mass tag (TMT)-based liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a proven approach for large-scale multiplexed protein quantification. However, the identification of TMT-labeled peptides is compromised by the labeling during traditional sequence database searches. In this study, we aim to use a spectral library search to increase the sensitivity and specificity of peptide identification for TMT-based MS data. Compared to MS/MS spectra of unlabeled peptides, the spectra of TMT-labeled counterparts usually display intensified b ions, suggesting that TMT labeling can alter product ion patterns during MS/MS fragementation. We compiled a human TMT spectral library of 401,168 unique peptides of high quality from millions of peptide-spectrum matches in tens of profiling projects, matching to 14,048 nonredundant proteins (13,953 genes). A mouse TMT spectral library of similar size was also constructed. The libraries were subsequently appended with decoy spectra to evaluate the false discovery rate, which was validated by a simulated null TMT data set. The performance of the library search was further optimized by removing TMT reporter ions and selecting an appropriate library construction method. Finally, we searched a human TMT data set against the spectral library to demonstrate that the spectral library outperformed the sequence database. Both human and mouse TMT libraries were made publicly available to the research community.

MS3-IDQ: Utilizing MS3 Spectra beyond Quantification Yields Increased Coverage of the Phosphoproteome in Isobaric Tag Experiments.

Protein phosphorylation is critically important for many cellular processes, including progression through the cell cycle, cellular metabolism, and differentiation. Isobaric labeling, for example, tandem mass tags (TMT), in phosphoproteomics workflows enables both relative and absolute quantitation of these phosphorylation events. Traditional TMT workflows identify peptides using fragment ions at the MS2 level and quantify reporter ions at the MS3 level. However, in addition to the TMT reporter ions, MS3 spectra also include fragment ions that can be used to identify peptides. Here we describe using MS3 spectra for both phosphopeptide identification and quantification, a process that we term MS3-IDQ. To maximize quantified phosphopeptides, we optimize several instrument parameters, including the modality of mass analyzer (i.e., ion trap or Orbitrap), MS2 automatic gain control (AGC), and MS3 normalized collision energy (NCE), to achieve the best balance of identified and quantified peptides. Our optimized MS3-IDQ method included the following parameters for the MS3 scan: NCE = 37.5 and AGC target = 1.5 × 105, and scan range = 100-2000. Data from the MS3 scan were complementary to those of the MS2 scan, and the combination of these scans can increase phosphoproteome coverage by >50%, thereby yielding a greater number of quantified and accurately localized phosphopeptides.

Isobaric Labeling of Intact Gangliosides toward Multiplexed LC-MS/MS-Based Quantitative Analysis.

Gangliosides are sialic acid-containing glycosphingolipids recognized to play essential role in biological processes. Both the glycan and lipid structures influence their biological function and thus necessitate their determination as intact molecular species. To our knowledge, no multiplexed method for intact gangliosides currently exists. In this paper, we aimed to demonstrate an approach for isobaric labeling of intact gangliosides. Specifically, we carried out the rapid, chemoselective oxidation of sialic acid side chain in common ganglioside core structures using NaIO4 followed by ligation with a carbonyl-reactive isobaric tandem mass tag (TMT) reagent and subsequent RPLC-MS/MS analysis. Attachment of the isobaric label was observed to improve the ionization efficiency of complex gangliosides using electrospray ionization. Fragmentation of the resulting [M + 2H]2+ ions of TMT-labeled gangliosides provided information-rich spectra containing fragments from the glycan, lipid, and TMT reporter ions. This facile approach enabled simultaneous quantification of up to six samples as well as identification of glycan and lipid compositions in a single injection. As a proof-of-concept, using porcine brain total ganglioside extracts pooled at known ratios, we obtained overall sample-to-sample precision of <12% RSD and mean error of <10%. This showcased the great promise and feasibility of this strategy for high-throughput analysis of intact gangliosides in biological extracts.

Abstract B46: The use of quantitative proteomics to increase the knowledge about metabolic symbiosis in a tumor microenvironment

Abstract For more than a century, it is known that in a solid tumor, malignant cancer cells co-reside with stromal cells including fibroblasts and immune cells. In addition, changes in metabolic requirements of malignant cells are necessary to cover their high proliferative rate. Although it has been demonstrated that complementary metabolic functions of tumor cells and their supporting local stroma (e.g. cancer-associated fibroblasts, adipocytes) contribute to the progression of cancer, less is known about the metabolic needs of immune cells in this local tumor microenvironment. However, in the context of cancer, immune cells, including tumor-associated macrophages (TAMs) are of high interest since it is known that these cells are able to influence tumor progression by allowing the establishment of an attractive environment for tumor growth and metastasis. Studying the expression profiles of proteins involved in metabolic processes of these cells might be a good strategy to elucidate this question. In this study, we applied quantitative proteomics to study the differences in protein expression of TAMs vs. control macrophages (both bone marrow-derived and peritoneal macrophages) isolated from an in vivo murine model for non-small cell lung adenocarcinoma. In our peptide-centric two dimensional liquid chromatography (LC)- tandem mass spectrometry (MS/MS) setup where Tandem Mass Tag (TMT) labeling is applied, we were able to identify 1250 unique proteins, of which 1178 proteins were quantified with all six TMT reporter ions. Interestingly, analysis of the differentially expressed proteins indicate that several Gene Ontology terms regarding metabolic pathways including glutathione metabolic processes (p= 3.47 e-14) and pentose phosphate shunt (p= 2.29 e-8) were enriched. These data suggest that TAMs can reprogram their metabolism in order to survive to the oxidative stress existing in this kind of microenvironment. In conclusion, our results illustrate that proteome analysis is a good strategy to obtain insights in the biology of tumor-associated macrophages. Citation Format: Evelyne Maes, Mathias Wenes, Dirk Valkenborg, Inge Mertens, Hans Prenen, Massimiliano Mazzone, Geert Baggerman. The use of quantitative proteomics to increase the knowledge about metabolic symbiosis in a tumor microenvironment. [abstract]. In: Proceedings of the AACR Special Conference: Metabolism and Cancer; Jun 7-10, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(1_Suppl):Abstract nr B46.