Differential quantification of isobaric phosphopeptides using data-independent acquisition mass spectrometry

CysQuant: Simultaneous quantification of cysteine oxidation and protein abundance using data dependent or independent acquisition mass spectrometry

Protein cysteinyl thiols are susceptible to reduction-oxidation reactions that can influence protein function. Accurate quantification of cysteine oxidation is therefore crucial for decoding protein redox regulation. Here, we present CysQuant, a novel approach for simultaneous quantification of cysteine oxidation degrees and protein abundancies. CysQuant involves light/heavy iodoacetamide isotopologues for differential labeling of reduced and reversibly oxidized cysteines analyzed by data-dependent acquisition (DDA) or data-independent acquisition mass spectrometry (DIA-MS). Using plexDIA with in silico predicted spectral libraries, we quantified an average of 18% cysteine oxidation in Arabidopsis thaliana by DIA-MS, including a subset of highly oxidized cysteines forming disulfide bridges in AlphaFold2 predicted structures. Applying CysQuant to Arabidopsis seedlings exposed to excessive light, we successfully quantified the well-established increased reduction of Calvin-Benson cycle enzymes and discovered yet uncharacterized redox-sensitive disulfides in chloroplastic enzymes. Overall, CysQuant is a highly versatile tool for assessing the cysteine modification status that can be widely applied across various mass spectrometry platforms and organisms.

Improving Phosphoproteomics Profiling Using Data-Independent Mass Spectrometry

Mass spectrometry-based profiling of the phosphoproteome is a powerful method of identifying phosphorylation events at a systems level. Most phosphoproteomics studies have used data-dependent acquisition (DDA) mass spectrometry as their method of choice. In this Perspective, we review some recent studies benchmarking DDA and DIA methods for phosphoproteomics and discuss data analysis options for DIA phosphoproteomics. In order to evaluate the impact of data-dependent and data-independent acquisition (DIA) on identification and quantification, we analyze a previously published phosphopeptide-enriched data set consisting of 10 replicates acquired by DDA and DIA each. We find that though more unique identifications are made in DDA data, phosphopeptides are identified more consistently across replicates in DIA. We further discuss the challenges of identifying chromatographically coeluting phosphopeptide isomers and investigate the impact on reproducibility of identifying high-confidence site-localized phosphopeptides in replicates.

Identification and characterization of post-translational modifications: Clinical implications

Post-translational modifications (PTMs) generate marginally modified isoforms of native peptides, proteins and lipoproteins thereby regulating protein functions, molecular interactions, and localization. With a key role in functional proteomics, post-translational modifications are recently also associated with the onsets and progressions of various diseases, such as cancer, cardiovascular, renal, and metabolic diseases. With the impact of post-translational modifications becoming increasingly clear, its reliable detection and quantification remain a major obstacle in the translation of these novel pathological markers into clinical diagnosis. While current antibody-based clinical diagnostics struggle to detect and quantify these marginal protein and lipoprotein alterations, state-of-the-art mass spectrometric, proteomic approaches provide the mass accuracy and resolving power necessary to isolate, identify and quantify novel and pathological post-translational modifications; however clinical translation of mass spectrometric applications are still facing major challenges. Here we review the status quo of the clinical translation of mass-spectrometric applications as novel diagnostic tools for the identification and quantification of post-translational modifications and focus on the emerging role of mass spectrometric methods in the clinical assessment of PTMs in disease states.

Illuminating the dark phosphoproteome

Protein phosphorylation is a major regulator of protein function and biological outcomes. This was first recognized through functional biochemical experiments, and in the past decade, major technological advances in mass spectrometry have enabled the study of protein phosphorylation on a global scale. This rapidly growing field of phosphoproteomics has revealed that more than 100,000 distinct phosphorylation events occur in human cells, which likely affect the function of every protein. Phosphoproteomics has improved the understanding of the function of even the most well-characterized protein kinases by revealing new downstream substrates and biology. However, current biochemical and bioinformatic approaches have only identified kinases for less than 5% of the phosphoproteome, and functional assignments of phosphosites are almost negligible. Notably, our understanding of the relationship between kinases and their substrates follows a power law distribution, with almost 90% of phosphorylation sites currently assigned to the top 20% of kinases. In addition, more than 150 kinases do not have a single known substrate. Despite a small group of kinases dominating biomedical research, the number of substrates assigned to a kinase does not correlate with disease relevance as determined by pathogenic human mutation prevalence and mouse model phenotypes. Improving our understanding of the substrates targeted by all kinases and functionally annotating the phosphoproteome will be broadly beneficial. Advances in phosphoproteomics technologies, combined with functional screening approaches, should make it feasible to illuminate the connectivity and functionality of the entire phosphoproteome, providing enormous opportunities for discovering new biology, therapeutic targets, and possibly diagnostics.

Proteomic Analysis of Histone Variants and Their PTMs: Strategies and Pitfalls

Epigenetic modifications contribute to the determination of cell fate and differentiation. The molecular mechanisms underlying histone variants and post-translational modifications (PTMs) have been studied in the contexts of development, differentiation, and disease. Antibody-based assays have classically been used to target PTMs, but these approaches fail to reveal combinatorial patterns of modifications. In addition, some histone variants are so similar to canonical histones that antibodies have difficulty distinguishing between these isoforms. Mass spectrometry (MS) has progressively developed as a powerful technology for the study of histone variants and their PTMs. Indeed, MS analyses highlighted exquisitely complex combinations of PTMs, suggesting “crosstalk” between them, and also revealed that PTM patterns are often variant-specific. Even though the sensitivity and acquisition speed of MS instruments have considerably increased alongside the development of computational tools for the study of multiple PTMs, it remains challenging to correctly describe the landscape of histone PTMs, and in particular to confidently assign modifications to specific amino acids. Here, we provide an inventory of MS-based strategies and of the pitfalls inherent to histone PTM and variant characterization, while stressing the complex interplay between PTMs and histone sequence variations. We will particularly illustrate the roles played by MS-based analyses in identifying and quantifying histone variants and modifications.

EpiProfile 2.0: A Computational Platform for Processing Epi-Proteomics Mass Spectrometry Data

Epigenetics has become a fundamental scientific discipline with various implications for biology and medicine. Epigenetic marks, mostly DNA methylation and histone post-translational modifications (PTMs), play important roles in chromatin structure and function. Accurate quantification of these marks is an ongoing challenge due to the variety of modifications and their wide dynamic range of abundance. Here we present EpiProfile 2.0, an extended version of our 2015 software (v1.0), for accurate quantification of histone peptides based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. EpiProfile 2.0 is now optimized for data-independent acquisition through the use of precursor and fragment extracted ion chromatography to accurately determine the chromatographic profile and to discriminate isobaric forms of peptides. The software uses an intelligent retention time prediction trained on the analyzed samples to enable accurate peak detection. EpiProfile 2.0 supports label-free and isotopic labeling, different organisms, known sequence mutations in diseases, different derivatization strategies, and unusual PTMs (such as acyl-derived modifications). In summary, EpiProfile 2.0 is a universal and accurate platform for the quantification of histone marks via LC-MS/MS. Being the first software of its kind, we anticipate that EpiProfile 2.0 will play a fundamental role in epigenetic studies relevant to biology and translational medicine. EpiProfile is freely available at https://github.com/zfyuan/EpiProfile2.0_Family .

Phosphoproteomics-Based Profiling of Kinase Activities in Cancer Cells

Cellular signaling, predominantly mediated by phosphorylation through protein kinases, is found to be deregulated in most cancers. Accordingly, protein kinases have been subject to intense investigations in cancer research, to understand their role in oncogenesis and to discover new therapeutic targets. Despite great advances, an understanding of kinase dysfunction in cancer is far from complete.A powerful tool to investigate phosphorylation is mass-spectrometry (MS)-based phosphoproteomics, which enables the identification of thousands of phosphorylated peptides in a single experiment. Since every phosphorylation event results from the activity of a protein kinase, high-coverage phosphoproteomics data should indirectly contain comprehensive information about the activity of protein kinases.In this chapter, we discuss the use of computational methods to predict kinase activity scores from MS-based phosphoproteomics data. We start with a short explanation of the fundamental features of the phosphoproteomics data acquisition process from the perspective of the computational analysis. Next, we briefly review the existing databases with experimentally verified kinase-substrate relationships and present a set of bioinformatic tools to discover novel kinase targets. We then introduce different methods to infer kinase activities from phosphoproteomics data and these kinase-substrate relationships. We illustrate their application with a detailed protocol of one of the methods, KSEA (Kinase Substrate Enrichment Analysis). This method is implemented in Python within the framework of the open-source Kinase Activity Toolbox (kinact), which is freely available at http://github.com/saezlab/kinact/ .

Quantitative Phosphoproteomic Analysis Reveals Key Mechanisms of Cellular Proliferation in Liver Cancer Cells

Understanding the mechanisms of uncontrolled proliferation in cancer cells provides valuable insights into tumor development and is benefit for discovering efficient methods in cancer treatment. In this study, we identified and quantified 2,057 phosphoproteins and 9,824 unique phosphosites in three liver cell lines with high (QGY, Hep3B) and low (L02) proliferative potentials and disclosed the wide variations in phosphorylation sites and levels among them. We found that the number of identified phosphoproteins and phosphosites in these cells were negatively correlated with their proliferative abilities. The function analysis suggested that the aberrant phosphorylation of SR proteins and activation of MAPK pathway might be two critical factors to promote cancer cell proliferation. Meanwhile, the phosphorylation status of mini-chromosome maintenance (MCM) and nuclear pore (NPC) complexes are significantly different between cell lines with high and low proliferative potentials. Furthermore, the phosphosites targeted by kinase families of CDK, STE and HIPK in the proteins coded by cancer driver genes showed distinct profiles between caner and normal cell lines. These results present key phosphorylation networks involving in abnormal proliferation of cancer cells and uncovered potential molecular markers for estimating the proliferation ability of liver cancer cells.

Targeted mass spectrometry: An emerging powerful approach to unblock the bottleneck in phosphoproteomics

Following the rapid expansion of the proteomics field, the investigation of post translational modifications (PTM) has become extremely popular changing our perspective of how proteins constantly fine tune cellular functions. Reversible protein phosphorylation plays a pivotal role in virtually all biological processes in the cell and it is one the most characterized PTM up to date. During the last decade, the development of phosphoprotein/phosphopeptide enrichment strategies and mass spectrometry (MS) technology has revolutionized the field of phosphoproteomics discovering thousands of new site-specific phosphorylations and unveiling unprecedented evidence about their modulation under distinct cellular conditions. The field has expanded so rapidly that the use of traditional methods to validate and characterize the biological role of the phosphosites is not feasible any longer. Targeted MS holds great promise for becoming the method of choice to study with high precision and sensitivity already known site-specific phosphorylation events. This review summarizes the contribution of large-scale unbiased MS analyses and highlights the need of targeted MS-based approaches for follow-up investigation. Additionally, the article illustrates the biological relevance of protein phosphorylation by providing examples of disease-related phosphorylation events and emphasizes the benefits of applying targeted MS in clinics for disease diagnosis, prognosis and drug-response evaluation.