Mass Spectrometry-based Studies Research Articles

Advances in aqueous humor proteomics for biomarker discovery and disease mechanisms exploration: a spotlight on primary open angle glaucoma.

Altered protein levels in the aqueous humor (AH) may be a valuable source of novel biomarkers in neurodegenerative retinal disease. The proximity of this body fluid to the disease focus, and its corresponding enrichment for tissue specific proteins, renders it an excellent matrix to study underlying molecular mechanisms. Novel proteomic methods accordingly hold large potential for insight into pathologies based on the composition of the AH proteome, including primary open angle glaucoma (POAG). Recent mass spectrometry-based studies use novel approaches to tackle the challenges arising from the combination of low available sample volume and protein concentration, thereby increasing proteome coverage. But despite significant improvements in mass spectrometry (MS), a different class of proteomic technologies is poised to majorly impact the analysis of ocular biofluids. Affinity proteomic workflows, having become available commercially recently, have started to complement data obtained by MS and likely will grow into a crucial tool for ophthalmological biomarker research. This review highlights corresponding approaches in proteome analysis of aqueous humor and discusses recent findings on alterations of the AH proteome in POAG.

A resource database for protein kinase substrate sequence-preference motifs based on large-scale mass spectrometry data

BackgroundProtein phosphorylation is one of the most prevalent posttranslational modifications involved in molecular control of cellular processes, and is mediated by over 520 protein kinases in humans and other mammals. Identification of the protein kinases responsible for phosphorylation events is key to understanding signaling pathways. Unbiased phosphoproteomics experiments have generated a wealth of data that can be used to identify protein kinase targets and their preferred substrate sequences.MethodsThis study utilized prior data from mass spectrometry-based studies identifying sites of protein phosphorylation after in vitro incubation of protein mixtures with recombinant protein kinases. PTM-Logo software was used with these data to generate position-dependent Shannon information matrices and sequence motif ‘logos’. Webpages were constructed for facile access to logos for each kinase and a new stand-alone application was written in Python that uses the position-dependent Shannon information matrices to identify kinases most likely to phosphorylate a particular phosphorylation site.ResultsA database of kinase substrate target preference logos allows browsing, searching, or downloading target motif data for each protein kinase (https://esbl.nhlbi.nih.gov/Databases/Kinase_Logos/). These logos were combined with phylogenetic analysis of protein kinase catalytic sequences to reveal substrate preference patterns specific to particular groups of kinases (https://esbl.nhlbi.nih.gov/Databases/Kinase_Logos/KinaseTree.html). A stand-alone program, KinasePredictor, is provided (https://esbl.nhlbi.nih.gov/Databases/Kinase_Logos/KinasePredictor.html). It takes as input, amino-acid sequences surrounding a given phosphorylation site and generates a ranked list of protein kinases most likely to phosphorylate that site.ConclusionsThis study provides three new resources for protein kinase characterization. It provides a tool for prediction of kinase-substrate interactions, which in combination with other types of data (co-localization, etc.), can predict which kinases are likely responsible for a given phosphorylation event in a given tissue.-q3N7pjxaL8wVBVRsJ9wBTVideo

OmicsEV: a tool for comprehensive quality evaluation of omics data tables.

RNA-Seq and mass spectrometry-based studies generate omics data tables with measurements for tens of thousands of genes across all samples in a study. The success of a study relies on the quality of these data tables, which is determined by both experimental data generation and computational methods used to process raw experimental data into quantitative data tables. We present OmicsEV, an R package for the quality evaluation of omics data tables. For each data table, OmicsEV uses a series of methods to evaluate data depth, data normalization, batch effect, biological signal, platform reproducibility and multi-omics concordance, producing comprehensive visual and quantitative evaluation results that help assess the data quality of individual data tables and facilitate the identification of the optimal data processing method and parameters for the omics study under investigation. The source code and the user manual of OmicsEV are available at https://github.com/bzhanglab/OmicsEV, and the source code is released under the GPL-3 license.

Mass spectrometry for the study of adipocyte cell secretome in cardiovascular diseases.

Adipose tissue is classically considered the primary site of lipid storage, but in recent years has garnered appreciation for its broad role as an endocrine organ, capable of remotely signaling to other tissues to alter their metabolic program. The adipose tissue is now recognized as a crucial regulator of cardiovascular health, mediated by the secretion of several bioactive products, with a wide range of endocrine and paracrine effects on the cardiovascular system. Thanks to the development and improvement of high-throughput mass spectrometry, the size and components of the human secretome have been characterized. In this review, we summarized the recent advances in mass spectrometry-based studies of the cell and tissue secretome for the understanding of adipose tissue biology, which may help to decipher the complex molecular mechanisms controlling the crosstalk between the adipose tissue and the cardiovascular system, and their possible clinical translation.

Classic and 11-oxygenated androgens in serum and saliva across adulthood and the menstrual cycle - a mass spectrometry-based cross-sectional study

Classic and 11-oxygenated androgens in serum and saliva across adulthood and the menstrual cycle - a mass spectrometry-based cross-sectional study

Post-translational Modification in Muscular Dystrophies.

Muscular dystrophies are a complex group of inherited neuromuscular disorders that progressively lead to a loss of muscle fibers and mobility and muscle weakness; over time, they evolve to an increasing level of disability. Muscular dystrophies are mostly caused by genetic mutations in proteins responsible for maintaining sarcolemma structures, such as an absence or reductions of dystrophin expression, conditions which are strictly related to muscular disorders that affect most people with this disease. Along the years, with the recent advances in the understanding of muscular dystrophies, it has been shown that many changes in Post-Translational Modifications (PTMs) of muscle proteins are associated with muscular dystrophies, wherein pathogenic alterations in the modulation of these muscle proteins are directly related to the incidence of this disease. An increase in the identification of the genetic bases and molecular mechanisms involved in the most common form of muscular dystrophies, including PTMs changes, holds potential to develop new therapeutic approaches. In this chapter we will describe the most common muscular dystrophies and changes in PTM processes such as phosphorylation and glycosylation that are very important in the evolution of the disease, highlighting the lack of mass spectrometry-based (MS-based) studies of these PTMs, suggesting that the application of this technique could reveal important informations about the molecular mechanisms of muscular dystrophies.

Biomass allocation in response to accession recognition in Arabidopsis thaliana depends on nutrient availability and plant age

ABSTRACT Many organisms have evolved to identify and respond to differences in genetic relatedness between conspecifics, allowing them to select between competitive and facilitative strategies to improve fitness. Due to their sessile nature, plants frequently draw from the same pool of nutrients, and the ability to limit competition between closely related conspecifics would be advantageous. Studies with Arabidopsis thaliana have confirmed that plants can detect variations at the accession level and alter their root system architecture (RSA) in response, presumably for regulating nutrient uptake. The phenotypic impact of this accession-recognition on the RSA is influenced by nutrient availability, underscoring the importance of plant-plant recognition in their growth and fitness. Thus far, these observations have been limited to short-term studies (<21 days) of only the RSA of this model angiosperm. Here we exploit nutrient-mediated regulation of accession-recognition to observe how this plant-plant recognition phenomenon influences growth from germination to flowering in A. thaliana. Our work identifies root and shoot traits that are affected by nutrient-mediated accession recognition. By coupling phenotypic assays to mass spectrometry-based studies of primary metabolite distribution, we provide preliminary insight into the biochemical underpinnings of the changes observed during these plant-plant responses. Most notably that late-stage changes in sucrose metabolism in members of the same accession drove early flowering. This work underscores the need to evaluate accession-recognition under the context of nutrient availability and consider responses throughout the plant’s life, not simply at the earliest stages of interaction.

“Multiomics” Approaches to Understand and Treat COVID-19: Mass Spectrometry and Next-Generation Sequencing

In the race against COVID-19 for timely therapeutic developments, mass spectrometry-based high-throughput methods have been valuable. COVID-19 manifests an extremely diverse spectrum of phenotypes from asymptomatic to life-threatening, drastic elevations in immune response or cytokine storm, multiple organ failure and death. These observations warrant a detailed understanding of associated molecular mechanisms to develop therapies. In this direction, high-throughput methods that generate large datasets focusing on changes in protein interactions, lipid metabolism, transcription, and epigenetic regulation of gene expression are extremely beneficial sources of information. Hence, mass spectrometry-based methods have been employed in several studies to detect changes in interactions among host proteins, and between host and viral proteins in COVID-19 patients. The methods have also been used to characterize host and viral proteins, and analyze lipid metabolism in COVID-19 patients. Information obtained using the above methods are complemented by high-throughput analysis of transcriptomic and epigenomic changes associated with COVID-19, coupled with next-generation sequencing. Hence, this review discusses the most recent studies focusing on the methods described above. The results establish the importance of mass spectrometry-based studies towards understanding the infection process, immune imbalance, disease mechanism, and indicate the potential of the methods’ therapeutic developments and biomarker screening against COVID-19 and future outbreaks.

Determination of ghrelin and desacyl ghrelin in human plasma and urine by means of LC-MS/MS for doping controls.

The hunger hormone ghrelin (G) is classified as prohibited substance in professional sport by the World Anti-Doping Agency (WADA), due to its known growth hormone releasing properties. The endogenous bioactive peptide consists of 28 amino acids with a caprylic acid attached to serine at position 3. Within this study, it was aimed to develop methods to determine G and desacyl ghrelin (DAG) in plasma and urine by means of LC-MS/MS. Two strategies were applied with a bottom-up approach for plasma and top-down analyses for urine. Both sample preparation procedures were based on solid-phase extraction for enrichment and sample clean-up. Method validation showed good results for plasma and urine with limits of detection (LODs) for G and DAG between 30 and 50 pg/ml, recoveries between 45-50%, and imprecisions (intra- and inter-day) between 3% and 24%. Plasma analysis was also valid for quantification with accuracies determined with ~100% for G and ~106% for DAG. The minimum required performance level for doping control laboratories is set to 2ng/ml in urine, and the herein established method yielded acceptable results even at 5% of this level. As proof-of-concept, plasma levels (G and DAG) of healthy volunteers were determined and ranged between 30 and 100 pg/ml for G and 100-1200 pg/ml for DAG. In contrast to earlier reported studies using ligand binding assays for urinary G and DAG, in this mass spectrometry-based study, no endogenous urinary G and DAG were found, although the LODs should enable this.

Identification of Novel Serum Metabolic Biomarkers as Indicators in the Progression of Intravenous Leiomyomatosis: A High Performance Liquid Chromatography-Tandem Mass Spectrometry-Based Study.

BackgroundIntravenous leiomyomatosis (IVL) is a rare estrogen-dependent neoplasm. However, identifiable and reliable biomarkers are still not available for clinical application, especially for the diagnosis and prognosis of the disease.MethodsIn the present study, 30 patients with IVL and 30 healthy controls were recruited. Serum samples were isolated from these participants for further high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) analysis to study metabolomics alterations and identify differentially expressed metabolites based on orthogonal partial least-squares discriminant analysis (OPLS-DA). Subsequently, lasso regression analysis and a generalized linear regression model were applied to screen out hub metabolites associated with the progression of IVL.ResultsFirst, 16 metabolites in the positive ion mode were determined from the 240 identifiable metabolites at the superclass level, with ten metabolites upregulated in the IVL group and the remaining six metabolites downregulated. Our data further proved that four metabolites [hypoxanthine, acetylcarnitine, glycerophosphocholine, and hydrocortisone (cortisol)] were closely related to the oncogenesis of IVL. Hypoxanthine and glycerophosphocholine might function as protective factors in the development of IVL (OR = 0.19 or 0.02, respectively). Nevertheless, acetylcarnitine and hydrocortisone (cortisol), especially the former, might serve as risk indicators for the disease to promote the development or recurrence of IVL (OR = 18.16 or 2.10, respectively). The predictive accuracy of these hub metabolites was further validated by the multi-class receiver operator characteristic curve analysis (ROC) with the Scikit-learn algorithms.ConclusionFour hub metabolites were finally determined via comprehensive bioinformatics analysis, and these substances could potentially serve as novel biomarkers in predicting the prognosis or progression of IVL.

MSroi: A pre-processing tool for mass spectrometry-based studies

Mass spectrometry has become one of the methods of choice in the analytical field due to its high sensitivity and selectivity to retrieve structural information allowing the univocal identification of compounds. From a chemometric point of view, mass spectrometry generates challenging datasets because of their large size with thousands of mass-to-charge values and with a high inherent complexity associated with the multicomponent mixtures analysed. These unresolved challenges have brought about the development of various computational approaches to enable the pre-processing of these mass spectrometry datasets. Here, we present the MSroi software in an attempt to provide a one-for-all solution in the compression and pre-processing of mass spectrometry datasets. MSroi allows the analysis of a variety of mass spectrometry datasets obtained using different acquisition approaches such as direct infusion, hyphenated to a separation technique or imaging. In all these cases, MSroi produces a highly compressed data table containing the measured intensities for relevant mass to charge values at each considered retention time or pixel. This output can be used as input for the feature detection step in, for instance, the ROIMCR approach, or used independently for subsequent multivariate chemometric analysis.

Mass Spectrometric Analysis of Post-Translational Modifications on SARS-CoV-2 Viral Proteins and Its Cellular Receptor ACE2

COVID-19 has caused a huge health crisis and incalculable damage worldwide. Emerging immune escaping mutants of the virus suggests that SARS-CoV-2 may be persistent in human society like the flu virus and become a long-lasting health threat. The control of SARS-CoV-2 transmission and the development of an effective treatment are imminent. Therefore, it is imperative to find appropriate biomarkers to indicate pathological and physiological. Proteins are performers of life functions and their abundance and modification status can directly reflect the immune status. Post-translational modifications such as glycosylation and phosphorylation have a great impact on the regulation of protein functions. In the studies of SARS, Zika, and H1N1, post-translational modified proteins have shown to be reliable biomarkers. In recent years, mass spectrometry-based proteomics has made great progress due to the development of mass spectrometry technology. A review of research strategies for mass spectrometry-based biomarkers, especially in the application of protein post-translational modifications, is important for the victory of human beings fighting the Covid-19 epidemic. This review summarized the current progress of mass spectrometry-based studies on the PTM status of SARS-CoV-2 viral proteins, particularly in glycosylation and phosphorylation aspect. The challenge and prospect of the application of mass spectrometry in this particular research area were outlined. © 2021, Editorial Board of Journal of Chinese Mass Spectrometry Society. All right reserved.

A Series of Ferulic Acid Amides Reveals Unexpected Peroxiredoxin 1 Inhibitory Activity with in vivo Antidiabetic and Hypolipidemic Effects.

Insulin resistance is a major pathophysiological feature in the development of type 2 diabetes (T2DM). Ferulic acid is known for attenuating the insulin resistance and reducing the blood glucose in T2DM rats. In this work, we designed and synthesized a library of new ferulic acid amides (FAA), which could be considered as ring opening derivatives of the antidiabetic PPARγ agonists Thiazolidinediones (TZDs). However, since these compounds displayed weak PPAR transactivation capacity, we employed a proteomics approach to unravel their molecular target(s) and identified the peroxiredoxin 1 (PRDX1) as a direct binding target of FAAs. Interestingly, PRDX1, a protein with antioxidant and chaperone activity, has been implied in the development of T2DM by inducing hepatic insulin resistance. SPR, mass spectrometry-based studies, docking experiments and in vitro inhibition assay confirmed that compounds VIe and VIf bound PRDX1 and induced a dose-dependent inhibition. Furthermore, VIe and VIf significantly improved hyperglycemia and hyperlipidemia in streptozotocin-nicotinamide (STZ-NA)-induced diabetic rats as confirmed by histopathological examinations. These results provide guidance for developing the current FAAs as new potential antidiabetic agents.

Mass spectrometry-based study defines the human urine nitrolipidome

Nitrated fatty acids (NO2-FA) are an endogenous class of signaling mediators formed mainly during digestion and inflammation. The signaling actions of NO2-FA have been extensively studied, but their detection and characterization lagged. Several different nitrated fatty acid species have been reported in animals and humans, but their formation remains controversial, and a systemic approach to define the endogenous pool of NO2-FA is needed. Herein, we screened for endogenous NO2-FA in urine from healthy human volunteers as this is the main excretion route for NO2-FA and its metabolites, and it provides an excellent matrix for evaluation. Only isomers of two fatty acids, conjugated linoleic and linolenic acid were found to be nitrated. Several, previously unknown, nitrated species were identified and confirmed using high-resolution mass spectrometry, fragmentation analysis, and compared to synthetic nitrated standards, the main group corresponding to nitrated conjugated linolenic acid (NO2-CLnA). In contrast, we were unable to confirm the presence of previously reported nitrated omega-3's, oleic acid, arachidonic acid and α- and γ-linolenic acid, suggesting that their biological formation and presence in humans should be re-evaluated. Metabolite analysis of NO2-CLnA in human urine identified cysteine adducts and β-oxidation products, which were compared to the metabolic products of nitrated standards obtained using primary mouse hepatocytes. Importantly, NO2-CLnA isomers belong to two defined groups, are electrophilic, participate in Michael addition reactions and account for 39% of total urinary NO2-FA, highlighting their relative abundance and possible role in cell signaling.

Differentiating Staphylococcus infection-associated glomerulonephritis and primary IgA nephropathy: a mass spectrometry-based exploratory study

Staphylococcus infection-associated glomerulonephritis (SAGN) and primary IgA nephropathy (IgAN) are separate disease entities requiring different treatment approaches. However, overlapping histologic features may cause a diagnostic dilemma. An exploratory proteomic study to identify potential distinguishing biomarkers was performed on formalin fixed paraffin embedded kidney biopsy tissue, using mass spectrometry (HPLC–MS/MS) (n = 27) and immunohistochemistry (IHC) (n = 64), on four main diagnostic groups—SAGN, primary IgAN, acute tubular necrosis (ATN) and normal kidney (baseline transplant biopsies). Spectral counts modeled as a negative binomial distribution were used for statistical comparisons and in silico pathway analysis. Analysis of variance techniques were used to compare groups and the ROC curve to evaluate classification algorithms. The glomerular proteomes of SAGN and IgAN showed remarkable similarities, except for significantly higher levels of monocyte/macrophage proteins in SAGN—mainly lysozyme and S100A9. This finding was confirmed by IHC. In contrast, the tubulointerstitial proteomes were markedly different in IgAN and SAGN, with a lower abundance of metabolic pathway proteins and a higher abundance of extracellular matrix proteins in SAGN. The stress protein transglutaminase-2 (TGM2) was also significantly higher in SAGN. IHC of differentially-expressed glomerular and tubulointerstitial proteins can be used to help discriminate between SAGN and IgAN in ambiguous cases.

Mass Spectrometry-Based Characterization of New Spirolides from Alexandrium ostenfeldii (Dinophyceae).

Spirolides belong to a group of marine phycotoxins produced by the marine planktonic dinophyte Alexandrium ostenfeldii. Composed of an imine moiety and a spiroketal ring system within a macrocylcle, spirolides are highly diverse with toxin types that vary among different strains. This study aims to characterize the spirolides from clonal A. ostenfeldii strains collected from The Netherlands, Greenland and Norway by mass spectral techniques. The structural characterization of unknown spirolides as inferred from high-resolution mass spectrometry (HR-MS) and collision induced dissociation (CID) spectra revealed the presence of nine novel spirolides that have the pseudo-molecular ions m/z 670 (1), m/z 666 (2), m/z 696 (3), m/z 678 (4), m/z 694 (5), m/z 708 (6), m/z 720 (7), m/z 722 (8) and m/z 738 (9). Of the nine new spirolides proposed in this study, compound 1 was suggested to have a truncated side chain in lieu of the commonly observed butenolide ring in spirolides. Moreover, there is indication that compound 5 might belong to new spirolide subclasses with a trispiroketal ring configuration having a 6:5:6 trispiroketal ring system. On the other hand, the other compounds were proposed as C- and G-type SPX, respectively. Compound 7 is proposed as the first G-type SPX with a 10-hydroxylation as usually observed in C-type SPX. This mass spectrometry-based study thus demonstrates that structural variability of spirolides is larger than previously known and does not only include the presence or absence of certain functional groups but also involves the triketal ring system.

ORGANOMETALLIC GAS-PHASE ION CHEMISTRY AND CATALYSIS: INSIGHTS INTO THE USE OF METAL CATALYSTS TO PROMOTE SELECTIVITY IN THE REACTIONS OF CARBOXYLIC ACIDS AND THEIR DERIVATIVES.

Carboxylic acids are valuable organic substrates as they are widely available, easy to handle, and exhibit structural and functional variety. While they are used in many standard synthetic protocols, over the past two decades numerous studies have explored new modes of metal-mediated reactivity of carboxylic acids and their derivatives. Mass spectrometry-based studies can provide fundamental mechanistic insights into these new modes of reactivity. Here gas-phase models for the following catalytic transformations of carboxylic acids and their derivatives are reviewed: protodecarboxylation; dehydration; decarbonylation; reaction as coordinated bases in C-H bond activation; remote functionalization and decarboxylative C-C bond coupling. In each case the catalytic problem is defined, insights from gas-phase studies are highlighted, comparisons with condensed-phase systems are made and perspectives are reached. Finally, the potential role for mechanistic studies that integrate both gas- and condensed-phase studies is highlighted by recent studies on the discovery of new catalysts for the selective decomposition of formic acid and the invention of the new extrusion-insertion class of reactions for the synthesis of amides, thioamides, and amidines. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Plasma protein expression differs between colorectal cancer patients depending on primary tumor location.

Colorectal cancer (CRC) includes tumors in the right colon, left colon, and rectum, although they differ significantly from each other in aspects such as prognosis and treatment. Few previous mass spectrometry‐based studies have analyzed differences in protein expression depending on the tumor location. In this study, we have used mass spectrometry‐based proteomics to analyze plasma samples from 83 CRC patients to study if differences in plasma protein expression can be seen depending on primary tumor location (right colon, left colon, or rectum). Differences were studied between the groups both regardless of and according to tumor stage (II or III). Large differences in plasma protein expression were seen, and we found that plasma samples from patients with rectal cancer separated from samples from patients with colon cancer when analyzed by principal component analysis and hierarchical clustering. Samples from patients with cancer in the right and left colon also tended to separate from each other. Pathway analysis discovered canonical pathways involved in lipid metabolism and inflammation to be enriched. This study will help to further define CRC as distinct entities depending on tumor location, as shown by the widespread differences in plasma protein profile and dysregulated pathways.

Mitochondrial Interactome: A Focus on Antiviral Signaling Pathways.

In the last years, proteomics has represented a valuable approach to elucidate key aspects in the regulation of type I/III interferons (IFNs) and autophagy, two main processes involved in the response to viral infection, to unveil the molecular strategies that viruses have evolved to counteract these processes. Besides their main metabolic roles, mitochondria are well recognized as pivotal organelles in controlling signaling pathways essential to restrain viral infections. In particular, a major role in antiviral defense is played by mitochondrial antiviral signaling (MAVS) protein, an adaptor protein that coordinates the activation of IFN inducing pathways and autophagy at the mitochondrial level. Here, we provide an overview of how mass spectrometry-based studies of protein–protein interactions and post-translational modifications (PTMs) have fostered our understanding of the molecular mechanisms that control the mitochondria-mediated antiviral immunity.

Insulin-induced serine 22 phosphorylation of retinoid X receptor alpha is dispensable for adipogenesis in brown adipocytes

ABSTRACT Insulin action initiates a series of phosphorylation events regulating cellular differentiation, growth and metabolism. We have previously discovered, in a mass spectrometry-based phosphoproteomic study, that insulin/IGF-1 signalling induces phosphorylation of retinoid x receptor alpha (RXRα) at S22 in mouse brown pre-adipocytes. Here, we show that insulin induces the phosphorylation of RXRα at S22 in both brown precursor and mature adipocytes through a pathway involving ERK, downstream of IRS-1 and −2. We also found that RXRα S22 phosphorylation is promoted by insulin and upon re-feeding in brown adipose tissue in vivo, and that insulin-stimulated S22 phosphorylation of RXRα is dampened by diet-induced obesity. We used Rxra knockout cells re-expressing wild type (WT) or S22A non-phosphorylatable forms of RXRα to further characterize the role of S22 in brown adipocytes. Knockout of Rxra in brown pre-adipocytes resulted in decreased lipid accumulation and adipogenic gene expression during differentiation, and re-expression of RxraWT alleviated these effects. However, we observed no significant difference in cells re-expressing the RxraS22A mutant as compared with the cells re-expressing RxraWT. Furthermore, comparison of gene expression during adipogenesis in the WT and S22A re-expressing cells by RNA sequencing revealed similar transcriptomic profiles. Thus, our data propose a dispensable role for RXRα S22 phosphorylation in adipogenesis and transcription in differentiating brown pre-adipocytes.