Systematic Investigation of Cellular Response and Pleiotropic Effects in Atorvastatin-Treated Liver Cells by MS-Based Proteomics

Plasma proteomics for prediction of subclinical coronary artery calcifications in primary prevention

BACKGROUND AND AIMS

Recent developments in high-throughput proteomic technologies enable the discovery of novel biomarkers of coronary atherosclerosis. The aims of this study were to test if plasma protein subsets could detect coronary artery calcifications (CAC) in asymptomatic individuals and if they add predictive value beyond traditional risk factors.

METHODS

Using proximity extension assays, 1,342 plasma proteins were measured in 1,827 individuals from the Impaired Glucose Tolerance and Microbiota (IGTM) study and 883 individuals from the Swedish Cardiopulmonary BioImage Study (SCAPIS) aged 50-64 years without history of ischaemic heart disease and with CAC assessed by computed tomography. After data-driven feature selection, extreme gradient boosting machine learning models were trained on the IGTM cohort to predict the presence of CAC using combinations of proteins and traditional risk factors. The trained models were validated in SCAPIS.

RESULTS

The best plasma protein subset (44 proteins) predicted CAC with an area under the curve (AUC) of 0.691 in the validation cohort. However, this was not better than prediction by traditional risk factors alone (AUC = 0.710, P = .17). Adding proteins to traditional risk factors did not improve the predictions (AUC = 0.705, P = .6). Most of these 44 proteins were highly correlated with traditional risk factors.

CONCLUSIONS

A plasma protein subset that could predict the presence of subclinical CAC was identified but it did not outperform nor improve a model based on traditional risk factors. Thus, support for this targeted proteomics platform to predict subclinical CAC beyond traditional risk factors was not found.

Melphalan induces cardiotoxicity through oxidative stress in cardiomyocytes derived from human induced pluripotent stem cells

BACKGROUND

Treatment-induced cardiotoxicity is a leading noncancer-related cause of acute and late onset morbidity and mortality in cancer patients on antineoplastic drugs such as melphalan-increasing clinical case reports have documented that it could induce cardiotoxicity including severe arrhythmias and heart failure. As the mechanism by which melphalan impairs cardiac cells remains poorly understood, here, we aimed to use cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs) to investigate the cellular and molecular mechanisms of melphalan-induced cardiotoxicity.

METHODS

hiPSC-CMs were generated and treated with clinically relevant doses of melphalan. To characterize melphalan-induced cardiotoxicity, cell viability and apoptosis were quantified at various treatment durations. Ca2+ transient and contractility analyses were used to examine the alterations of hiPSC-CM function. Proteomic analysis, reactive oxygen species detection, and RNA-Sequencing were conducted to investigate underlying mechanisms.

RESULTS

Melphalan treatment of hiPSC-CMs induced oxidative stress, caused Ca2+ handling defects and dysfunctional contractility, altered global transcriptomic and proteomic profiles, and resulted in apoptosis and cell death. The antioxidant N-acetyl-L-cysteine attenuated these genomic, cellular, and functional alterations. In addition, several other signaling pathways including the p53 and transforming growth factor-β signaling pathways were also implicated in melphalan-induced cardiotoxicity according to the proteomic and transcriptomic analyses.

CONCLUSIONS

Melphalan induces cardiotoxicity through the oxidative stress pathway. This study provides a unique resource of the global transcriptomic and proteomic datasets for melphalan-induced cardiotoxicity and can potentially open up new clinical mechanism-based targets to prevent and treat melphalan-induced cardiotoxicity.

Proteomic Profiling Reveals Roles of Stress Response, Ca2+ Transient Dysregulation, and Novel Signaling Pathways in Alcohol-Induced Cardiotoxicity

BACKGROUND

Alcohol use in pregnancy increases the risk of abnormal cardiac development, and excessive alcohol consumption in adults can induce cardiomyopathy, contractile dysfunction, and arrhythmias. Understanding molecular mechanisms underlying alcohol-induced cardiac toxicity could provide guidance in the development of therapeutic strategies.

METHODS

We have performed proteomic and bioinformatic analysis to examine protein alterations globally and quantitatively in cardiomyocytes derived from human-induced pluripotent stem cells (hiPSC-CMs) treated with ethanol (EtOH). Proteins in both cell lysates and extracellular culture media were systematically quantitated.

RESULTS

Treatment with EtOH caused severe detrimental effects on hiPSC-CMs as indicated by significant cell death and deranged Ca²⁺ handling. Treatment of hiPSC-CMs with EtOH significantly affected proteins responsible for stress response (e.g., GPX1 and HSPs), ion channel-related proteins (e.g. ATP1A2), myofibril structure proteins (e.g., MYL2/3), and those involved in focal adhesion and extracellular matrix (e.g., ILK and PXN). Proteins involved in the TNF receptor-associated factor 2 signaling (e.g., CPNE1 and TNIK) were also affected by EtOH treatment.

CONCLUSIONS

The observed changes in protein expression highlight the involvement of oxidative stress and dysregulation of Ca²⁺ handling and contraction while also implicating potential novel targets in alcohol-induced cardiotoxicity. These findings facilitate further exploration of potential mechanisms, discovery of novel biomarkers, and development of targeted therapeutics against EtOH-induced cardiotoxicity.

Global and site-specific analysis of protein glycosylation in complex biological systems with Mass Spectrometry

Protein glycosylation is ubiquitous in biological systems and plays essential roles in many cellular events. Global and site-specific analysis of glycoproteins in complex biological samples can advance our understanding of glycoprotein functions and cellular activities. However, it is extraordinarily challenging because of the low abundance of many glycoproteins and the heterogeneity of glycan structures. The emergence of mass spectrometry (MS)-based proteomics has provided us an excellent opportunity to comprehensively study proteins and their modifications, including glycosylation. In this review, we first summarize major methods for glycopeptide/glycoprotein enrichment, followed by the chemical and enzymatic methods to generate a mass tag for glycosylation site identification. We next discuss the systematic and quantitative analysis of glycoprotein dynamics. Reversible protein glycosylation is dynamic, and systematic study of glycoprotein dynamics helps us gain insight into glycoprotein functions. The last part of this review focuses on the applications of MS-based proteomics to study glycoproteins in different biological systems, including yeasts, plants, mice, human cells, and clinical samples. Intact glycopeptide analysis is also included in this section. Because of the importance of glycoproteins in complex biological systems, the field of glycoproteomics will continue to grow in the next decade. Innovative and effective MS-based methods will exponentially advance glycoscience, and enable us to identify glycoproteins as effective biomarkers for disease detection and drug targets for disease treatment. © 2019 Wiley Periodicals, Inc. Mass Spec Rev 9999: XX-XX, 2019.

Mass spectrometric analysis of the N-glycoproteome in statin-treated liver cells with two lectin-independent chemical enrichment methods

Protein N-glycosylation is essential for mammalian cell survival and is well-known to be involved in many biological processes. Aberrant glycosylation is directly related to human disease including cancer and infectious diseases. Global analysis of protein N-glycosylation will allow a better understanding of protein functions and cellular activities. Mass spectrometry (MS)-based proteomics provides a unique opportunity to site-specifically characterize protein glycosylation on a large scale. Due to the complexity of biological samples, effective enrichment methods are critical prior to MS analysis. Here, we compared two lectin-independent methods to enrich glycopeptides for the global analysis of protein N-glycosylation by MS. The first boronic acid-based enrichment (BA) method benefits from the universal and reversible interactions between boronic acid and sugars; the other method utilizes metabolic labeling and click chemistry (MC) to incorporate a chemical handle into glycoproteins for future affinity enrichment. We comprehensively compared the performance of the two methods in the identification and quantification of glycoproteins in statin-treated liver cells. Based on the current results, the BA method is more universal in enriching glycopeptides, while with the MC method, cell surface glycoproteins were highly enriched, and the quantification results appear to be more dynamic because only the newly-synthesized glycoproteins were analyzed. In addition, we normalized the glycosylation site ratios by the corresponding parent protein ratios to reflect the real modification changes. In combination with MS-based proteomics, effective enrichment methods will vertically advance protein glycosylation research.

Technological advances and proteomic applications in drug discovery and target deconvolution: identification of the pleiotropic effects of statins

Proteomic-based techniques provide a powerful tool for identifying the full spectrum of protein targets of a drug, elucidating its mechanism(s) of action, and identifying biomarkers of its efficacy and safety. Herein, we outline the technological advancements in the field, and illustrate the contribution of proteomics to the definition of the pharmacological profile of statins, which represent the cornerstone of the prevention and treatment of cardiovascular diseases (CVDs). Statins act by inhibiting 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase, thus reducing cholesterol biosynthesis and consequently enhancing the clearance of low-density lipoproteins from the blood; however, HMG-CoA reductase inhibition can result in a multitude of additional effects beyond lipid lowering, known as 'pleiotropic effects'. The case of statins highlights the unique contribution of proteomics to the target profiling of a drug molecule.

Quantification of tunicamycin-induced protein expression and N-glycosylation changes in yeast

Tunicamycin is a potent protein N-glycosylation inhibitor that has frequently been used to manipulate protein glycosylation in cells. However, protein expression and glycosylation changes as a result of tunicamycin treatment are still unclear. Using yeast as a model system, we systematically investigated the cellular response to tunicamycin at the proteome and N-glycoproteome levels. By utilizing modern mass spectrometry-based proteomics, we quantified 4259 proteins, which nearly covers the entire yeast proteome. After the three-hour tunicamycin treatment, more than 5% of proteins were down-regulated by at least 2 fold, among which proteins related to several glycan metabolism and glycolysis-related pathways were highly enriched. Furthermore, several proteins in the canonical unfolded protein response pathway were up-regulated because the inhibition of protein N-glycosylation impacts protein folding and trafficking. We also comprehensively quantified protein glycosylation changes in tunicamycin-treated cells, and more than one third of quantified unique glycopeptides (168 of 465 peptides) were down-regulated. Proteins containing down-regulated glycopeptides were related to glycosylation, glycoprotein metabolic processes, carbohydrate processes, and cell wall organization according to gene ontology clustering. The current results provide the first global view of the cellular response to tunicamycin at the proteome and glycoproteome levels.

Site-Specific Quantification of Surface N-Glycoproteins in Statin-Treated Liver Cells

The frequent modification of cell-surface proteins by N-linked glycans is known to be correlated with many biological processes. Aberrant glycosylation on surface proteins is associated with different cellular statuses and disease progression. However, it is extraordinarily challenging to comprehensively and site-specifically analyze glycoproteins located only on the cell surface. Currently mass spectrometry (MS)-based proteomics provides the possibility to analyze the N-glycoproteome, but effective separation and enrichment methods are required for the analysis of surface glycoproteins prior to MS measurement. The introduction of bio-orthogonal groups into proteins accelerates research in the robust visualization, identification, and quantification of proteins. Here we have comprehensively evaluated different sugar analogs in the analysis of cell-surface N-glycoproteins by combining copper-free click chemistry and MS-based proteomics. Comparison of three sugar analogs, N-azidoacetylgalactosamine (GalNAz), N-azidoacetylglucosamine (GlcNAz), and N-azidoacetylmannosamine (ManNAz), showed that metabolic labeling with GalNAz resulted in the greatest number of glycoproteins and glycosylation sites in biological duplicate experiments. GalNAz was then employed for the quantification experiment in statin-treated HepG2 liver cells, and 280 unique N-glycosylated sites were quantified from 168 surface proteins. The quantification results demonstrated that many glycosylation sites on surface proteins were down-regulated in statin-treated cells compared to untreated cells because statin prevents the synthesis of dolichol, which is essential for the formation of dolichol-linked precursor oligosaccharides. Several glycosylation sites in proteins that participate in the Alzheimer's disease pathway were down-regulated. This method can be extensively applied for the global analysis of the cell-surface N-glycoproteome.