Quantitation of protein post-translational modifications using isobaric tandem mass tags

Understanding LC/MS-Based Metabolomics: A Detailed Reference for Natural Product Analysis

Liquid chromatography, when used in conjunction with mass spectrometry (LC/MS), is a powerful tool for conducting accurate and reproducible investigations of numerous metabolites in natural products (NPs). LC/MS has gained prominence in metabolomic research due to its high throughput, the availability of multiple ionization techniques and its ability to provide comprehensive metabolite coverage. This unique method can significantly influence various scientific domains. This review offers a comprehensive overview of the current state of LC/MS-based metabolomics in the investigation of NPs. This review provides a thorough overview of the state of the art in LC/MS-based metabolomics for the investigation of NPs. It covers the principles of LC/MS, various aspects of LC/MS-based metabolomics such as sample preparation, LC modes, method development, ionization techniques and data pre-processing. Moreover, it presents the applications of LC/MS-based metabolomics in numerous fields of NPs research such as including biomarker discovery, the agricultural research, food analysis, the study of marine NPs and microbiological research. Additionally, this review discusses the challenges and limitations of LC/MS-based metabolomics, as well as emerging trends and developments in this field.

Studying Autophagy Using a TMT-Based Quantitative Proteomics Approach

Maintenance of cellular homeostasis through regulated degradation of proteins and organelles is a defining feature of autophagy. This process itself is tightly regulated in a series of well-defined biochemical reactions governed largely by the highly conserved ATG protein family. Given its crucial role in regulating protein levels under both basal and stress conditions such as starvation and infection, genetic or pharmacological perturbation of autophagy results in massive changes in the cellular proteome and impacts nearly every biological process. Therefore, studying autophagy perturbations at a global scale assumes prime importance. In recent years, quantitative mass spectrometry (MS)-based proteomics has emerged as a powerful approach to explore biological processes through global proteome quantification analysis. Tandem mass tag (TMT)-based MS proteomics is one such robust quantitative technique that can examine relative protein abundances in multiple samples (parallel multiplexing). Investigating autophagy through TMT-based MS approach can give great insights into autophagy-regulated biological processes, protein-protein interaction networks, spatiotemporal protein dynamics, and identification of new autophagy substrates. This chapter provides a detailed protocol for studying the impact of a dysfunctional autophagy pathway on the cellular proteome and pathways in a healthy vs. disease (virus infection) condition using a 16-plex TMT-based quantitative proteomics approach. We also provide a pipeline on data processing and analysis using available web-based tools.

Quantitative Proteomics Using Isobaric Labeling: A Practical Guide

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

Quantitative Mass Spectrometry-Based Proteomics for Biomarker Development in Ovarian Cancer

Ovarian cancer is the most lethal gynecologic malignancy among women. Approximately 70–80% of patients with advanced ovarian cancer experience relapse within five years and develop platinum-resistance. The short life expectancy of patients with platinum-resistant or platinum-refractory disease underscores the need to develop new and more effective treatment strategies. Early detection is a critical step in mitigating the risk of disease progression from early to an advanced stage disease, and protein biomarkers have an integral role in this process. The best biological diagnostic tool for ovarian cancer will likely be a combination of biomarkers. Targeted proteomics methods, including mass spectrometry-based approaches, have emerged as robust methods that can address the chasm between initial biomarker discovery and the successful verification and validation of these biomarkers enabling their clinical translation due to the robust sensitivity, specificity, and reproducibility of these versatile methods. In this review, we provide background information on the fundamental principles of biomarkers and the need for improved treatment strategies in ovarian cancer. We also provide insight into the ways in which mass spectrometry-based targeted proteomics approaches can provide greatly needed solutions to many of the challenges related to ovarian cancer biomarker development.

Differential analysis of quantitative proteome and acetyl-proteome profiling between premenopausal and postmenopausal ovarian tissues

BACKGROUND

Natural menopause is always accompanied by specific signs and symptoms, suggesting physiological changes in this peoriod. However, no systematic study has assessed the changes at molecular level in the ovaries during the menopausal transition so far. This study integrated quantitative proteome and acetyl-proteome to comprehensively uncover the changes of ovarian protein and protein-acetylation profiles in this transitional period. The findings would provide novel insights into the biology of menopause and help relieve and treat the associated signs and symptoms, further improving the women's health care.

METHODS

Freshly thawed ovarian tissue samples obtained from premenopausal and postmenopausal women were assessed with Tandem Mass Tags for the quantitative analysis of the global profile and acetyl-proteomes by 2-dimensional separation and LC-MS/MS.

RESULTS

Comprehensively, 4210 types of protein, with 3551 types quantifiable were detected. 3047 acetylated sites in 1583 types of protein with 2256 quantifiable in 1248 proteins were detected. By comparing the global and acetylated proteome profiles for postmenopausal women and premenopausal women, 151 types of proteins were found upregulated and 65 were downregulated, along with 23 acetylated sites upregulated and 220 sites downregulated. For Immune response, the complement and coagulation cascades plus the citrate cycle and cellular detoxification were found to be significantly enhanced, while the extracellular structure and matrix organization, ECM-receptor interactions plus the infections were markedly suppressed. In addition, the amino acids around the acetylated sites were enriched by motif analysis, which can help us uncover amino acid sequence and search for the specific target in the subsequent study.

CONCLUSION

Global and acetylated proteome Profiles in ovary differ between the premenopausal and postmenopausal groups. These proteomic-level changes may offer some potential biological markers to identify the pathological changes in ovary and help relieve and treat the associated signs and symptoms, and ultimately improve women's health care.

Recent advances and clinical insights into the use of proteomics in the study of atherosclerosis

INTRODUCTION

The application of new proteomics methods may help to identify new diagnostic/predictive molecular markers in an attempt to improve the clinical management of atherosclerosis. Areas covered: Technological advances in proteomics have enhanced its sensitivity and multiplexing capacity, as well as the possibility of studying protein interactions and tissue structure. These advances will help us better understand the molecular mechanisms at play in atherosclerosis as a biological system. Moreover, this should help identify new predictive/diagnostic biomarkers and therapeutic targets that may facilitate effective risk stratification and early diagnosis, with the ensuing rapid implementation of treatment. This review provides a comprehensive overview of the novel methods in proteomics, including state-of-the-art techniques, novel biological samples and applications for the study of atherosclerosis. Expert commentary: Collaboration between clinicians and researchers is crucial to further validate and introduce new molecular markers to manage atherosclerosis that are identified using the most up to date proteomic approaches.

Understanding cell signaling in cancer stem cells for targeted therapy - can phosphoproteomics help to reveal the secrets?

Background

Cancer represents heterogeneous and aberrantly proliferative manifestations composed of (epi)genetically and phenotypically distinct cells with a common clonal origin. Cancer stem cells (CSC) make up a rare subpopulation with the remarkable capacity to initiate, propagate and spread a malignant disease. Furthermore, CSC show increased therapy resistance, thereby contributing to disease relapse. Elimination of CSC, therefore, is a crucial aim to design efficacious treatments for long-term survival of cancer patients. In this article, we highlight the nature of CSC and propose that phosphoproteomics based on unbiased high-performance liquid chromatography-mass spectrometry provides a powerful tool to decipher the molecular CSC programs. Detailed knowledge about the regulation of signaling processes in CSC is a prerequisite for the development of patient-tailored multi-modal treatments including the elimination of rare CSC.

Main body

Phosphorylation is a crucial post-translational modification regulating a plethora of both intra- and intercellular communication processes in normal and malignant cells. Small-molecule targeting of kinases has proven successful in the therapy, but the high rates of relapse and failure to stem malignant spread suggest that these kinase inhibitors largely spare CSC. Studying the kinetics of global phosphorylation patterns in an unbiased manner is, therefore, required to improve strategies and successful treatments within multi-modal therapeutic regimens by targeting the malignant behavior of CSC. The phosphoproteome comprises all phosphoproteins within a cell population that can be analyzed by phosphoproteomics, allowing the investigation of thousands of phosphorylation events. One major aspect is the perception of events underlying the activation and deactivation of kinases and phosphatases in oncogenic signaling pathways. Thus, not only can this tool be harnessed to better understand cellular processes such as those controlling CSC, but also applied to identify novel drug targets for targeted anti-CSC therapy.

Conclusion

State-of-the-art phosphoproteomics approaches focusing on single cell analysis have the potential to better understand oncogenic signaling in heterogeneous cell populations including rare, yet highly malignant CSC. By eliminating the influence of heterogeneity of populations, single-cell studies will reveal novel insights also into the inter- and intratumoral communication processes controlling malignant CSC and disease progression, laying the basis for improved rational combination treatments.

Targeted In-Depth Quantification of Signaling Using Label-Free Mass Spectrometry

Protein phosphorylation encodes information on the activity of kinase-driven signaling pathways that regulate cell biology. This chapter discusses an approach, named TIQUAS (targeted in-depth quantification of signaling), to quantify cell signaling comprehensively and without bias. The workflow-based on mass spectrometry (MS) and computational science-consists of targeting the analysis of phosphopeptides previously identified by shotgun liquid chromatography tandem MS (LC-MS/MS) across the samples that are being compared. TIQUAS therefore takes advantage of concepts derived from both targeted (data-independent) and data-dependent acquisition methods; phosphorylation sites are quantified in all experimental samples regardless of whether or not these phosphopeptides were identified by MS/MS in all runs. As a result, datasets are obtained containing quantitative information on several thousand phosphorylation sites in as many samples and replicates as required in the experimental design, and these rich datasets are devoid of a significant number of missing data points. This chapter discussed the biochemical, analytical, and computational procedures required to apply the approach and for obtaining a biological interpretation of the data in the context of our understanding of cell signaling regulation and kinase-substrate relationships.

Current landscape of protein glycosylation analysis and recent progress toward a novel paradigm of glycoscience research

This review covers the basics and some applications of methodologies for the analysis of glycoprotein glycans. Analytical techniques used for glycoprotein glycans, including liquid chromatography (LC), capillary electrophoresis (CE), mass spectrometry (MS), and high-throughput analytical methods based on microfluidics, were described to supply the essentials about biopharmaceutical and biomarker glycoproteins. We will also describe the MS analysis of glycoproteins and glycopeptides as well as the chemical and enzymatic releasing methods of glycans from glycoproteins and the chemical reactions used for the derivatization of glycans. We hope the techniques have accommodated most of the requests from glycoproteomics researchers.

Mass Spectrometry-Based Metabolomic and Proteomic Strategies in Organic Acidemias

Organic acidemias (OAs) are inherited metabolic disorders caused by deficiency of enzymatic activities in the catabolism of amino acids, carbohydrates, or lipids. These disorders result in the accumulation of mono-, di-, or tricarboxylic acids, generally referred to as organic acids. The OA outcomes can involve different organs and/or systems. Some OA disorders are easily managed if promptly diagnosed and treated, whereas, in others cases, such as propionate metabolism-related OAs (propionic acidemia, PA; methylmalonic acidemia, MMA), neither diet, vitamin therapy, nor liver transplantation appears to prevent multiorgan impairment. Here, we review the recent developments in dissecting molecular bases of OAs by using integration of mass spectrometry- (MS-) based metabolomic and proteomic strategies. MS-based techniques have facilitated the rapid and economical evaluation of a broad spectrum of metabolites in various body fluids, also collected in small samples, like dried blood spots. This approach has enabled the timely diagnosis of OAs, thereby facilitating early therapeutic intervention. Besides providing an overview of MS-based approaches most frequently used to study the molecular mechanisms underlying OA pathophysiology, we discuss the principal challenges of metabolomic and proteomic applications to OAs.

Introduction to Proteomics Technologies

Compared to genomics or transcriptomics, proteomics is often regarded as an "emerging technology," i.e., as not having reached the same level of maturity. While the successful implementation of proteomics workflows and technology still requires significant levels of expertise and specialization, great strides have been made to make the technology more powerful, streamlined and accessible. In 2014, two landmark studies published the first draft versions of the human proteome.We aim to provide an introduction specifically into the background of mass spectrometry (MS)-based proteomics. Within the field, mass spectrometry has emerged as a core technology. Coupled to increasingly powerful separations and data processing and bioinformatics solution, it allows the quantitative analysis of whole proteomes within a matter of days, a timescale that has made global comparative proteome studies feasible at last. We present and discuss the basic concepts behind proteomics mass spectrometry and the accompanying topic of protein and peptide separations, with a focus on the properties of datasets emerging from such studies.

Complementary PTM Profiling of Drug Response in Human Gastric Carcinoma by Immunoaffinity and IMAC Methods with Total Proteome Analysis

Gaining insight into normal cellular signaling and disease biology is a critical goal of proteomic analyses. The ability to perform these studies successfully to extract the maximum value and discovery of biologically relevant candidate biomarkers is therefore of primary importance. Many successful studies in the past have focused on total proteome analysis (changes at the protein level) combined with phosphorylation analysis by metal affinity enrichment (changes at the PTM level). Here, we use the gastric carcinoma cell line MKN-45 treated with the c-Met inhibitor SU11274 and PKC inhibitor staurosporine to investigate the most efficient and most comprehensive strategies for both total protein and PTM analysis. Under the conditions used, total protein analysis yielded few changes in response to either compound, while analysis of phosphorylation identified thousands of sites that changed differentially between the two treatments. Both metal affinity and antibody-based enrichments were used to assess phosphopeptide changes, and the data generated by the two methods was largely complementary (non-overlapping). Label-free quantitation of peptide peak abundances was used to accurately determine fold-changes between control and treated samples. Protein interaction network analysis allowed the data to be placed in a biologically relevant context, and follow-up validation of selected findings confirmed the accuracy of the proteomic data. Together, this study provides a framework for start-to-finish proteomic analysis of any experimental system under investigation to maximize the value of the proteomic study and yield the best chance for uncovering actionable target candidates.