Utilizing proteomics to identify and optimize microalgae strains for high-quality dietary protein: a review

Algae-derived protein has immense potential to provide high-quality protein foods for the expanding human population. To meet its potential, a broad range of scientific tools are required to identify optimal algal strains from the hundreds of thousands available and identify ideal growing conditions for strains that produce high-quality protein with functional benefits. A research pipeline that includes proteomics can provide a deeper interpretation of microalgal composition and biochemistry in the pursuit of these goals. To date, proteomic investigations have largely focused on pathways that involve lipid production in selected microalgae species. Herein, we report the current state of microalgal proteome measurement and discuss promising approaches for the development of protein-containing food products derived from algae.

Comparative analysis of the longissimus muscle proteome of European wild boar and domestic pig in response to thermal processing

This study tries to fill the knowledge gap regarding differences in the expression of proteins in the meat of European wild boar (Sus scrofa scrofa) and domestic pig (Sus scrofa domestica), considering the impact of thermally induced degradation. We assessed relative protein changes between cooked longissimus thoracis et lumborum (LTL) muscle proteomes by using mass spectrometry, chemometric, label-free proteomic, and bioinformatic tools. Among 30 differentially abundant proteins identified MyHC-2a, ATPs-α, CK-S, ADP/ATPt1, IDH2, and MyBP-C1 were upregulated (x > 1) whereas NEB, γ-ENO and EPSF were downregulated (x < 1) in wild boar. ShinyGO and KEGG database pathway analyses revealed that these proteins are mainly involved in processes related to muscle contraction and various pathways of glucose metabolism and energy production. Protein expression changes could have been caused by the different muscle activity of wild animals in response to prolonged movement associated with foraging for food in the natural environment.

Bacterial protein acetylation: mechanisms, functions, and methods for study

Lysine acetylation is an evolutionarily conserved protein modification that changes protein functions and plays an essential role in many cellular processes, such as central metabolism, transcriptional regulation, chemotaxis, and pathogen virulence. It can alter DNA binding, enzymatic activity, protein-protein interactions, protein stability, or protein localization. In prokaryotes, lysine acetylation occurs non-enzymatically and by the action of lysine acetyltransferases (KAT). In enzymatic acetylation, KAT transfers the acetyl group from acetyl-CoA (AcCoA) to the lysine side chain. In contrast, acetyl phosphate (AcP) is the acetyl donor of chemical acetylation. Regardless of the acetylation type, the removal of acetyl groups from acetyl lysines occurs only enzymatically by lysine deacetylases (KDAC). KATs are grouped into three main superfamilies based on their catalytic domain sequences and biochemical characteristics of catalysis. Specifically, members of the GNAT are found in eukaryotes and prokaryotes and have a core structural domain architecture. These enzymes can acetylate small molecules, metabolites, peptides, and proteins. This review presents current knowledge of acetylation mechanisms and functional implications in bacterial metabolism, pathogenicity, stress response, translation, and the emerging topic of protein acetylation in the gut microbiome. Additionally, the methods used to elucidate the biological significance of acetylation in bacteria, such as relative quantification and stoichiometry quantification, and the genetic code expansion tool (CGE), are reviewed.

A Mass Spectrometry Strategy for Protein Quantification Based on the Differential Alkylation of Cysteines Using Iodoacetamide and Acrylamide

Mass spectrometry has become the most prominent yet evolving technology in quantitative proteomics. Today, a number of label-free and label-based approaches are available for the relative and absolute quantification of proteins and peptides. However, the label-based methods rely solely on the employment of stable isotopes, which are expensive and often limited in availability. Here we propose a label-based quantification strategy, where the mass difference is identified by the differential alkylation of cysteines using iodoacetamide and acrylamide. The alkylation reactions were performed under identical experimental conditions; therefore, the method can be easily integrated into standard proteomic workflows. Using high-resolution mass spectrometry, the feasibility of this approach was assessed with a set of tryptic peptides of human serum albumin. Several critical questions, such as the efficiency of labeling and the effect of the differential alkylation on the peptide retention and fragmentation, were addressed. The concentration of the quality control samples calculated against the calibration curves were within the ±20% acceptance range. It was also demonstrated that heavy labeled peptides exhibit a similar extraction recovery and matrix effect to light ones. Consequently, the approach presented here may be a viable and cost-effective alternative of stable isotope labeling strategies for the quantification of cysteine-containing proteins.

Protein constraints in genome-scale metabolic models: Data integration, parameter estimation, and prediction of metabolic phenotypes

Genome-scale metabolic models provide a valuable resource to study metabolism and cell physiology. These models are employed with approaches from the constraint-based modeling framework to predict metabolic and physiological phenotypes. The prediction performance of genome-scale metabolic models can be improved by including protein constraints. The resulting protein-constrained models consider data on turnover numbers (kcat ) and facilitate the integration of protein abundances. In this systematic review, we present and discuss the current state-of-the-art regarding the estimation of kinetic parameters used in protein-constrained models. We also highlight how data-driven and constraint-based approaches can aid the estimation of turnover numbers and their usage in improving predictions of cellular phenotypes. Finally, we identify standing challenges in protein-constrained metabolic models and provide a perspective regarding future approaches to improve the predictive performance.

A Proteomic Investigation to Discover Candidate Proteins Involved in Novel Mechanisms of 5-Fluorouracil Resistance in Colorectal Cancer

One of the main obstacles to therapeutic success in colorectal cancer (CRC) is the development of acquired resistance to treatment with drugs such as 5-fluorouracil (5-FU). Whilst some resistance mechanisms are well known, it is clear from the stasis in therapy success rate that much is still unknown. Here, a proteomics approach is taken towards identification of candidate proteins using 5-FU-resistant sublines of human CRC cell lines generated in house. Using a multiplexed stable isotope labelling with amino acids in cell culture (SILAC) strategy, 5-FU-resistant and equivalently passaged sensitive cell lines were compared to parent cell lines by growing in Heavy medium with 2D liquid chromatography and Orbitrap Fusion™ Tribrid™ Mass Spectrometry analysis. Among 3003 commonly quantified proteins, six (CD44, APP, NAGLU, CORO7, AGR2, PLSCR1) were found up-regulated, and six (VPS45, RBMS2, RIOK1, RAP1GDS1, POLR3D, CD55) down-regulated. A total of 11 of the 12 proteins have a known association with drug resistance mechanisms or role in CRC oncogenesis. Validation through immunodetection techniques confirmed high expression of CD44 and CD63, two known drug resistance mediators with elevated proteomics expression results. The information revealed by the sensitivity of this method warrants it as an important tool for elaborating the complexity of acquired drug resistance in CRC.

Absolute Quantitation of Peptides and Proteins by Coulometric Mass Spectrometry After Derivatization

Peptide/protein quantitation using mass spectrometry (MS) is advantageous due to its high sensitivity. Traditional absolute peptide quantitation methods rely on making calibration curves using peptide standards or isotope-labelled peptide standards, which are expensive and take time to synthesize. A method which can eliminate the need for using standards would be beneficial. Recently, we developed coulometric mass spectrometry (CMS) which can be used to quantify peptides that are oxidizable (e.g., those containing tyrosine or tryptophan), without using peptide standard. The method is based on electrochemical oxidation of peptides followed by MS to measure the oxidation yield. However, it cannot be directly used to quantify peptides without oxidizable residues. To extend this method for quantifying peptides/proteins in general, in this study, we adopted a derivatization strategy, in which a target peptide is first tagged with an electroactive reagent such as monocarboxymethylene blue NHS ester (MCMB-NHS ester), followed with quantitation by CMS. To illustrate the power of this method, we have analyzed peptides MG and RPPGFSPFR. The quantification error was less than 5%. Using RPPGFSPFR as an example, the quantitation sensitivity of the technique was found to be 0.25 pmol. Furthermore, we also used the strategy to quantify proteins cytochrome C and β-casein with an error of 2-26%.

PARROT: Prediction of enzyme abundances using protein-constrained metabolic models

Protein allocation determines the activity of cellular pathways and affects growth across all organisms. Therefore, different experimental and machine learning approaches have been developed to quantify and predict protein abundance and how they are allocated to different cellular functions, respectively. Yet, despite advances in protein quantification, it remains challenging to predict condition-specific allocation of enzymes in metabolic networks. Here, using protein-constrained metabolic models, we propose a family of constrained-based approaches, termed PARROT, to predict how much of each enzyme is used based on the principle of minimizing the difference between a reference and an alternative growth condition. To this end, PARROT variants model the minimization of enzyme reallocation using four different (combinations of) distance functions. We demonstrate that the PARROT variant that minimizes the Manhattan distance between the enzyme allocation of a reference and an alternative condition outperforms existing approaches based on the parsimonious distribution of fluxes or enzymes for both Escherichia coli and Saccharomyces cerevisiae. Further, we show that the combined minimization of flux and enzyme allocation adjustment leads to inconsistent predictions. Together, our findings indicate that minimization of protein allocation rather than flux redistribution is a governing principle determining steady-state pathway activity for microorganism grown in alternative growth conditions.

Proteomic response of A549 lung cancer cell line to protein-polysaccharide complex Venetin-1 isolated from earthworm coelomic fluid

Earthworms' celomic fluid has long attracted scientists' interest due to their toxic properties. It has been shown that the elimination of coelomic fluid cytotoxicity to normal human cells was crucial for the generation of the non-toxic Venetin-1 protein-polysaccharide complex, which exhibits selective activity against Candida albicans cells as well as A549 non-small cell lung cancer cells. To find the molecular mechanisms behind the anti-cancer properties of the preparation, this research investigated the proteome response of A549 cells to the presence of Venetin-1. The sequential window acquisition of all theoretical mass spectra (SWATH-MS) methodology was used for the analysis, which allows for a relative quantitative analysis to be carried out without radiolabelling. The results showed that the formulation did not induce significant proteome responses in normal BEAS-2B cells. In the case of the tumour line, 31 proteins were up regulated, and 18 proteins down regulated. Proteins with increased expression in neoplastic cells are mainly associated with the mitochondrion, membrane transport and the endoplasmic reticulum. In the case of altered proteins, Venetin-1 interferes with proteins that stabilise the structures, i.e., keratin, glycolysis/gluconeogenesis and metabolic processes.

Recent advances of small extracellular vesicle biomarkers in breast cancer diagnosis and prognosis

Current clinical tools for breast cancer (BC) diagnosis are insufficient but liquid biopsy of different bodily fluids has recently emerged as a minimally invasive strategy that provides a real-time snapshot of tumour biomarkers for early diagnosis, active surveillance of progression, and post-treatment recurrence. Extracellular vesicles (EVs) are nano-sized membranous structures 50-1000 nm in diameter that are released by cells into biological fluids. EVs contain proteins, nucleic acids, and lipids which play pivotal roles in tumourigenesis and metastasis through cell-to-cell communication. Proteins and miRNAs from small EVs (sEV), which range in size from 50-150 nm, are being investigated as a potential source for novel BC biomarkers using mass spectrometry-based proteomics and next-generation sequencing. This review covers recent developments in sEV isolation and single sEV analysis technologies and summarises the sEV protein and miRNA biomarkers identified for BC diagnosis, prognosis, and chemoresistance. The limitations of current sEV biomarker research are discussed along with future perspective applications.

Proximity-dependent biotinylation technologies for mapping RNA-protein interactions in live cells

Proximity ligation technologies are extremely powerful tools for unveiling RNA-protein interactions occurring at different stages in living cells. These approaches mainly rely on the inducible activity of enzymes (biotin ligases or peroxidases) that promiscuously biotinylate macromolecules within a 20 nm range. These enzymes can be either fused to an RNA binding protein or tethered to any RNA of interest and expressed in living cells to biotinylate the amino acids and nucleic acids of binding partners in proximity. The biotinylated molecules can then be easily affinity purified under denaturing conditions and analyzed by mass spectrometry or next generation sequencing. These approaches have been widely used in recent years, providing a potent instrument to map the molecular interactions of specific RNA-binding proteins as well as RNA transcripts occurring in mammalian cells. In addition, they permit the identification of transient interactions as well as interactions among low expressed molecules that are often missed by standard affinity purification strategies. This review will provide a brief overview of the currently available proximity ligation methods, highlighting both their strengths and shortcomings. Furthermore, it will bring further insights to the way these technologies could be further used to characterize post-transcriptional modifications that are known to regulate RNA-protein interactions.

Determination of the soybean allergen Gly m 6 and its stability in food processing using liquid chromatography-tandem mass spectrometry coupled with stable-isotope dimethyl labelling

A cost-effective method using liquid chromatography-tandem mass spectrometry (LC-MS/MS) coupled with stable-isotope dimethyl labelling was used for the determination of Gly m 6. The validation results revealed that the recoveries and precisions obtained from five spiked levels were in the ranges of 88.8-113.0% and 8.3-22.0%, respectively. The content and stability of the major soybean allergen Gly m 6 in various food processing procedures were evaluated by the quantification results of its surrogate signature peptide. The Gly m 6 content in soybean decreased by 42% after natto fermentation, and by 31% and 35% in pasteurised soymilk and sterilised soymilk, respectively, relative to the raw soymilk. Only 19% of Gly m 6 in raw soymilk was retained in the soymilk film. This study extended the feasibility of dimethyl labelling to soy-based food samples and examined the proteolysis of Gly m 6 in natto fermentation and its thermal instability.

Current Insights on the Impact of Proteomics in Respiratory Allergies

Respiratory allergies affect humans worldwide, causing extensive morbidity and mortality. They include allergic rhinitis (AR), asthma, pollen food allergy syndrome (PFAS), aspirin-exacerbated respiratory disease (AERD), and nasal polyps (NPs). The study of respiratory allergic diseases requires new technologies for early and accurate diagnosis and treatment. Omics technologies provide the tools required to investigate DNA, RNA, proteins, and other molecular determinants. These technologies include genomics, transcriptomics, proteomics, and metabolomics. However, proteomics is one of the main approaches to studying allergic disorders' pathophysiology. Proteins are used to indicate normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. In this field, the principal goal of proteomics has been to discover new proteins and use them in precision medicine. Multiple technologies have been applied to proteomics, but that most used for identifying, quantifying, and profiling proteins is mass spectrometry (MS). Over the last few years, proteomics has enabled the establishment of several proteins for diagnosing and treating respiratory allergic diseases.

Benchmarking of analysis strategies for data-independent acquisition proteomics using a large-scale dataset comprising inter-patient heterogeneity

Numerous software tools exist for data-independent acquisition (DIA) analysis of clinical samples, necessitating their comprehensive benchmarking. We present a benchmark dataset comprising real-world inter-patient heterogeneity, which we use for in-depth benchmarking of DIA data analysis workflows for clinical settings. Combining spectral libraries, DIA software, sparsity reduction, normalization, and statistical tests results in 1428 distinct data analysis workflows, which we evaluate based on their ability to correctly identify differentially abundant proteins. From our dataset, we derive bootstrap datasets of varying sample sizes and use the whole range of bootstrap datasets to robustly evaluate each workflow. We find that all DIA software suites benefit from using a gas-phase fractionated spectral library, irrespective of the library refinement used. Gas-phase fractionation-based libraries perform best against two out of three reference protein lists. Among all investigated statistical tests non-parametric permutation-based statistical tests consistently perform best.

Data independent acquisition (DIA) has been gaining momentum in clinical proteomics. Here, the authors create a benchmark dataset comprising inter-patient heterogeneity to compare popular DIA data analysis workflows for identifying differentially abundant proteins.

Recent progress of proteomic analysis on spermatogenesis

Testis, the only organ responsible for generating sperm, is by far the organ with the largest variety of proteins and tissue-specific proteins in humans. In testis, spermatogenesis is a multi-step complex process well-accepted that protein and mRNA are decoupled in certain stages of spermatogenesis. With the fast development of mass spectrometry-based proteomics, it is possible to systemically study protein abundances and modifications in testis and sperm to help us understand the molecular mechanisms of spermatogenesis. This review provides an overview of the recent progress of proteomics analysis on spermatogenesis, including protein expression and multiple PTMs, such as phosphorylation, glycosylation, ubiquitylation, and acetylation.

HNF4A-AS1-encoded small peptide promotes self-renewal and aggressiveness of neuroblastoma stem cells via eEF1A1-repressed SMAD4 transactivation

Cancer stem cells play crucial roles in tumorigenesis and aggressiveness, while regulatory mechanisms in neuroblastoma (NB), a pediatric extracranial malignancy with highest incidence, are still unknown. Herein, a small 51-amino acid peptide (sPEP1) encoded by hepatocyte nuclear factor 4 alpha antisense RNA 1 (HNF4A-AS1) was identified in tumor tissues and cells, which facilitated self-renewal and aggressiveness of NB stem cells. MiRNA-409-5p interacted with HNF4A-AS1 to facilitate sPEP1 translation via recruiting eukaryotic translation initiation factor 3 subunit G, while sPEP1 repressed serum deprivation-induced senescence and promoted sphere formation, growth, or metastasis of NB stem cells. Mechanistically, sPEP1 directly interacted with eukaryotic translation elongation factor 1 alpha 1 (eEF1A1) to facilitate its binding to SMAD family member 4 (SMAD4), resulting in repression of SMAD4 transactivation and transcriptional upregulation of stem cell genes associated with tumor progression. Rescue experiments revealed that sPEP1 exerted oncogenic roles via facilitating physical interaction between eEF1A1 and SMAD4. Notably, knockdown of sPEP1 significantly repressed the self-renewal and metastasis of NB stem cells in vivo. High sPEP1 or eEF1A1 levels in clinical NB tissues were linked to poor patients' survival. These findings suggest that HNF4A-AS1-encoded sPEP1 promotes self-renewal and aggressive features of NB stem cells by eEF1A1-repressed SMAD4 transactivation.

Exercise mediates ubiquitin signalling in human skeletal muscle

Physical activity or regular exercise provides many beneficial effects towards human health, helping prevent and ameliorate metabolic diseases. However, certain molecular mechanisms that mediate these health benefits remain poorly understood. Parker et al. provided the first global analysis of exercise‐regulated ubiquitin signalling in human skeletal muscle, revealing post‐translational modification cross‐talk. As a result of their analysis, NEDDylation is thought to promote ubiquitin signalling for the removal of damaged proteins following exercise. The proteomic dataset generated from their study is invaluable for researchers in this field to validate new mechanistic hypotheses. To further reveal molecular mechanisms regulated by exercise, future research could employ more sensitive mass spectrometry‐based workflows that increase the detection of both ubiquitylated sites and peptides and subsequently identify more exercise‐regulated ubiquitin signalling pathways.

Application of Proteomics in Pancreatic Ductal Adenocarcinoma Biomarker Investigations: A Review

Pancreatic ductal adenocarcinoma (PDAC), a highly aggressive malignancy with a poor prognosis is usually detected at the advanced stage of the disease. The only US Food and Drug Administration-approved biomarker that is available for PDAC, CA 19-9, is most useful in monitoring treatment response among PDAC patients rather than for early detection. Moreover, when CA 19-9 is solely used for diagnostic purposes, it has only a recorded sensitivity of 79% and specificity of 82% in symptomatic individuals. Therefore, there is an urgent need to identify reliable biomarkers for diagnosis (specifically for the early diagnosis), ascertain prognosis as well as to monitor treatment response and tumour recurrence of PDAC. In recent years, proteomic technologies are growing exponentially at an accelerated rate for a wide range of applications in cancer research. In this review, we discussed the current status of biomarker research for PDAC using various proteomic technologies. This review will explore the potential perspective for understanding and identifying the unique alterations in protein expressions that could prove beneficial in discovering new robust biomarkers to detect PDAC at an early stage, ascertain prognosis of patients with the disease in addition to monitoring treatment response and tumour recurrence of patients.

Recent Developments in Clinical Plasma Proteomics—Applied to Cardiovascular Research

The human plasma proteome mirrors the physiological state of the cardiovascular system, a fact that has been used to analyze plasma biomarkers in routine analysis for the diagnosis and monitoring of cardiovascular diseases for decades. These biomarkers address, however, only a very limited subset of cardiovascular diseases, such as acute myocardial infarct or acute deep vein thrombosis, and clinical plasma biomarkers for the diagnosis and stratification cardiovascular diseases that are growing in incidence, such as heart failure and abdominal aortic aneurysm, do not exist and are urgently needed. The discovery of novel biomarkers in plasma has been hindered by the complexity of the human plasma proteome that again transforms into an extreme analytical complexity when it comes to the discovery of novel plasma biomarkers. This complexity is, however, addressed by recent achievements in technologies for analyzing the human plasma proteome, thereby facilitating the possibility for novel biomarker discoveries. The aims of this article is to provide an overview of the recent achievements in technologies for proteomic analysis of the human plasma proteome and their applications in cardiovascular medicine.

Absolute Quantitation of Tryptophan-Containing Peptides and Amyloid β-Peptide Fragments by Coulometric Mass Spectrometry

Isotope-labeled internal standards are routinely used for mass spectrometry (MS)-based absolute quantitation. However, syntheses of isotope-labeled peptides are time-consuming and costly. To tackle this issue, we recently developed a coulometric mass spectrometric (CMS) approach for absolute quantitation without the use of standards, based on the electrochemical oxidation of cysteine or tyrosine-containing peptides followed by mass spectrometric measurement of the oxidation yield. To further expand the utility of this method, herein we present the CMS method for absolute quantitation of peptides based on tryptophan electrochemical oxidation. Several tryptophan-containing peptides, such as WGG, WQPPRARI, WAGGDASGE, RTRPLWVRME, and KVPRNQDWL, were successfully quantified with a quantification error ranging from -4.5 to +4.3%. Furthermore, this quantitation approach is also applicable to protein, in which protein can be digested and a surrogate peptide can be selected for quantification to reflect the amount of the parent protein, as exemplified by CMS analysis of peptide GITWK from cytochrome c. The CMS result agreed well with the traditional isotope dilution method, with only a small difference of 3.5%. In addition, CMS was used to successfully quantify amyloid beta (Aβ) peptide fragments (up to 28 amino acid residues) based on tyrosine oxidation. The validity of the CMS method for peptide and protein absolute quantitation without using isotope-labeled peptide standards would greatly facilitate proteomics research.

Complement and Coagulation Cascades are Potentially Involved in Dopaminergic Neurodegeneration in α-Synuclein-Based Mouse Models of Parkinson's Disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder that results in motor dysfunction and, eventually, cognitive impairment. α-Synuclein protein is known as a central protein to the pathophysiology of PD, but the underlying pathological mechanism still remains to be elucidated. In an effort to understand how α-synuclein underlies the pathology of PD, various PD mouse models with α-synuclein overexpression have been developed. However, systemic analysis of the brain proteome of those mouse models is lacking. In this study, we established two mouse models of PD by injecting α-synuclein preformed fibrils (PFF) or by inducing overexpression of human A53T α-synuclein to investigate common pathways in the two different types of the PD mouse models. For more accurate quantification of mouse brain proteome, the proteins were quantified using the method of stable isotope labeling with amino acids in mammals . We identified a total of 8355 proteins from the two mouse models; ∼6800 and ∼7200 proteins from α-synuclein PFF-injected mice and human A53T α-synuclein transgenic mice, respectively. Through pathway analysis of the differentially expressed proteins common to both PD mouse models, it was discovered that the complement and coagulation cascade pathways were enriched in the PD mice compared to control animals. Notably, a validation study demonstrated that complement component 3 (C3)-positive astrocytes were increased in the ventral midbrain of the intrastriatal α-synuclein PFF-injected mice and C3 secreted from astrocytes could induce the degeneration of dopaminergic neurons. This is the first study that highlights the significance of the complement and coagulation pathways in the pathogenesis of PD through proteome analyses with two sophisticated mouse models of PD.

Mass spectrometry based proteomics for developmental neurobiology in the amphibian Xenopus laevis

The South African clawed frog (Xenopus laevis), a prominent vertebrate model in cell and developmental biology, has been instrumental in studying molecular mechanisms of neural development and disease. Recently, high-resolution mass spectrometry (HRMS), a bioanalytical technology, has expanded the molecular toolbox of protein detection and characterization (proteomics). This chapter overviews the characteristics, advantages, and challenges of this biological model and technology. Discussions are offered on their combined use to aid studies on cell differentiation and development of neural tissues. Finally, the emerging integration of proteomics and other 'omic technologies is reflected on to generate new knowledge, drive and test new hypotheses, and ultimately, advance the understanding of neural development during states of health and disease.

Future perspectives on in-vitro diagnosis of drug allergy by the lymphocyte transformation test

This article aims to envisage future perspectives of the lymphocyte transformation test (LTT). We describe the select innovative techniques, which can be integrated at different stages of the LTT to potentially improve the sensitivity, specificity, or practicability of the LTT. We first focus upon the cell sorting techniques comprising immunomagnetic cell separation and flow cytometry, which can be implemented prior and after the LTT culturing step to concentrate and quantify specific immune cell types. Further, we elaborate upon three important omics techniques such as transcriptomics, proteomics, and metabolomics, which can be integrated downstream of the LTT to analyze molecular changes in specific immune cells following drug induced activation and proliferation. We also develop visions, how state of the art techniques used in other scientific fields, can be transferred and applied in the context of in-vitro detection of drug allergy.

Proteomic Approaches to Dissect Host SUMOylation during Innate Antiviral Immune Responses

SUMOylation is a highly dynamic ubiquitin-like post-translational modification that is essential for cells to respond to and resolve various genotoxic and proteotoxic stresses. Virus infections also constitute a considerable stress scenario for cells, and recent research has started to uncover the diverse roles of SUMOylation in regulating virus replication, not least by impacting antiviral defenses. Here, we review some of the key findings of this virus-host interplay, and discuss the increasingly important contribution that large-scale, unbiased, proteomic methodologies are making to discoveries in this field. We highlight the latest proteomic technologies that have been specifically developed to understand SUMOylation dynamics in response to cellular stresses, and comment on how these techniques might be best applied to dissect the biology of SUMOylation during innate immunity. Furthermore, we showcase a selection of studies that have already used SUMO proteomics to reveal novel aspects of host innate defense against viruses, such as functional cross-talk between SUMO proteins and other ubiquitin-like modifiers, viral antagonism of SUMO-modified antiviral restriction factors, and an infection-triggered SUMO-switch that releases endogenous retroelement RNAs to stimulate antiviral interferon responses. Future research in this area has the potential to provide new and diverse mechanistic insights into host immune defenses.

Transporter tandems: precise tools for normalizing active transporter in the plasma membrane

The transport efficiency (TE) describes the performance of a transport protein for a specific substrate. To compare the TE of different transporters, the number of active transporters in the plasma membrane must be monitored, as it may vary for each transporter and experiment. Available methods, like LC-MS quantification of tryptic peptides, fail to discriminate inactive intracellular transporters or, like cell-surface biotinylation followed by affinity chromatography and Western blotting, are imprecise and very laborious. We wanted to normalize active transporters by the activity of a second transporter. A transporter tandem, generated by joining two transporter cDNAs into a single open reading frame, should guarantee a 1 : 1 stoichiometry. Here we created a series of tandems with different linkers between the human ergothioneine (ET) transporter ETT (gene symbol SLC22A4) and organic cation transporter OCT2 (SLC22A2). The linker sequence strongly affected the expression strength. The stoichiometry was validated by absolute peptide quantification and untargeted peptide analysis. Compared with wild-type ETT, the normalized ET clearance of the natural variant L503F was higher (f = 1.34); G462E was completely inactive. The general usefulness of the tandem strategy was demonstrated by linking several transporters with ETT; every construct was active in both parts. Transporter tandems can be used - without membrane isolation or protein quantification - as precise tools for transporter number normalization, to identify, for example, relevant transporters for a drug. It is necessary, however, to find suitable linkers, to check the order of transporters, and to verify the absence of functional interference by saturation kinetics.

Shotgun proteomics of peach fruit reveals major metabolic pathways associated to ripening

BACKGROUND

Fruit ripening in Prunus persica melting varieties involves several physiological changes that have a direct impact on the fruit organoleptic quality and storage potential. By studying the proteomic differences between the mesocarp of mature and ripe fruit, it would be possible to highlight critical molecular processes involved in the fruit ripening.

RESULTS

To accomplish this goal, the proteome from mature and ripe fruit was assessed from the variety O'Henry through shotgun proteomics using 1D-gel (PAGE-SDS) as fractionation method followed by LC/MS-MS analysis. Data from the 131,435 spectra could be matched to 2740 proteins, using the peach genome reference v1. After data pre-treatment, 1663 proteins could be used for comparison with datasets assessed using transcriptomic approaches and for quantitative protein accumulation analysis. Close to 26% of the genes that code for the proteins assessed displayed higher expression at ripe fruit compared to other fruit developmental stages, based on published transcriptomic data. Differential accumulation analysis between mature and ripe fruit revealed that 15% of the proteins identified were modulated by the ripening process, with glycogen and isocitrate metabolism, and protein localization overrepresented in mature fruit, as well as cell wall modification in ripe fruit. Potential biomarkers for the ripening process, due to their differential accumulation and gene expression pattern, included a pectin methylesterase inhibitor, a gibbellerin 2-beta-dioxygenase, an omega-6 fatty acid desaturase, a homeobox-leucine zipper protein and an ACC oxidase. Transcription factors enriched in NAC and Myb protein domains would target preferentially the genes encoding proteins more abundant in mature and ripe fruit, respectively.

CONCLUSIONS

Shotgun proteomics is an unbiased approach to get deeper into the proteome allowing to detect differences in protein abundance between samples. This technique provided a resolution so that individual gene products could be identified. Many proteins likely involved in cell wall and sugar metabolism, aroma and color, change their abundance during the transition from mature to ripe fruit.

Proposing a minimal set of metrics and methods to predict probabilities of amyloidosis disease and onset age in individuals

Many amyloid-driven pathologies have both genetic and stochastic components where assessing risk of disease development requires a multifactorial assessment where many of the variables are poorly understood. Risk of transthyretin-mediated amyloidosis is enhanced by age and mutation of the transthyretin (TTR) gene, but amyloidosis is not directly initiated by mutated TTR proteins. Nearly all of the 150+ known mutations increase dissociation of the homotetrameric protein structure and increase the probability of an individual developing a TTR amyloid disease late in life. TTR amyloidosis is caused by dissociated monomers that are destabilized and refold into an amyloidogenic form. Therefore, monomer concentration, monomer proteolysis rate, and structural stability are key variables that may determine the rate of development of amyloidosis. Here we develop a unifying biophysical model that quantifies the relationships among these variables in plasma and suggest the probability of an individual developing a TTR amyloid disease can be estimated. This may allow quantification of risk for amyloidosis and provide the information necessary for development of methods for early diagnosis and prevention. Given the similar observation of genetic and sporadic amyloidoses for other diseases, this model and the measurements to assess risk may be applicable to more proteins than just TTR.

Mass Spectrometry Techniques: Principles and Practices for Quantitative Proteomics

In the current omics-age of research, major developments have been made in technologies that attempt to survey the entire repertoire of genes, transcripts, proteins, and metabolites present within a cell. While genomics has led to a dramatic increase in our understanding of such things as disease morphology and how organisms respond to medications, it is critical to obtain information at the proteome level since proteins carry out most of the functions within the cell. The primary tool for obtaining proteome-wide information on proteins within the cell is mass spectrometry (MS). While it has historically been associated with the protein identification, developments over the past couple of decades have made MS a robust technology for protein quantitation as well. Identifying quantitative changes in proteomes is complicated by its dynamic nature and the inability of any technique to guarantee complete coverage of every protein within a proteome sample. Fortunately, the combined development of sample preparation and MS methods have made it capable of quantitatively comparing many thousands of proteins obtained from cells and organisms.

THE PRESENT AND FUTURE OF THE MASS SPECTROMETRY-BASED INVESTIGATION OF THE EXOSOME LANDSCAPE

Exosomes are critical intercellular messengers released upon the fusion of multivesicular bodies with the cellular plasma membrane that deliver their cargo in the form of extracellular vesicles. Containing numerous nonrandomly packed functional proteins, lipids, and RNAs, exosomes are vital intercellular messengers that contribute to the physiologic processes of the healthy organism. During the post-genome era, exosome-oriented proteomics have garnered great interest. Since its establishment, mass spectrometry (MS) has been indispensable for the field of proteomics research and has advanced rapidly to interrogate biological samples at a higher resolution and sensitivity. Driven by new methodologies and more advanced instrumentation, MS-based approaches have revolutionized our understanding of protein biology. As the access to online proteomics database platforms has blossomed, experimental data processing occurs with more speed and accuracy. Here, we review recent advances in the technological progress of MS-based proteomics and several new detection strategies for MS-based proteomics research. We also summarize the use of integrated online databases for proteomics research in the era of big data. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Block Design with Common Reference Samples Enables Robust Large-Scale Label-Free Quantitative Proteome Profiling

Label-free quantitative proteomics has become an increasingly popular tool for profiling global protein abundances. However, one major limitation is the potential performance drift of the LC-MS platform over time, which, in turn, limits its utility for analyzing large-scale sample sets. To address this, we introduce an experimental and data analysis scheme based on a block design with common references within each block for enabling large-scale label-free quantification. In this scheme, a large number of samples (e.g., >100 samples) are analyzed in smaller and more manageable blocks, minimizing instrument drift and variability within individual blocks. Each designated block also contains common reference samples (e.g., controls) for normalization across all blocks. We demonstrated the robustness of this approach by profiling the proteome response of human macrophage THP-1 cells to 11 engineered nanomaterials at two different doses. A total of 116 samples were analyzed in six blocks, yielding an average coverage of 4500 proteins per sample. Following a common reference-based correction, 2537 proteins were quantified with high reproducibility without any imputation of missing values from 116 data sets. The data revealed the consistent quantification of proteins across all six blocks, as illustrated by the highly consistent abundances of house-keeping proteins in all samples and the high levels of correlation among samples from different blocks. The data also demonstrated that label-free quantification is robust and accurate enough to quantify even very subtle abundance changes as well as large fold-changes. Our streamlined workflow is easy to implement and can be readily adapted to other large cohort studies for reproducible label-free proteome quantification.

Mass Spectrometry Advances and Perspectives for the Characterization of Emerging Adoptive Cell Therapies

Adoptive cell therapy is an emerging anti-cancer modality, whereby the patient's own immune cells are engineered to express T-cell receptor (TCR) or chimeric antigen receptor (CAR). CAR-T cell therapies have advanced the furthest, with recent approvals of two treatments by the Food and Drug Administration of Kymriah (trisagenlecleucel) and Yescarta (axicabtagene ciloleucel). Recent developments in proteomic analysis by mass spectrometry (MS) make this technology uniquely suited to enable the comprehensive identification and quantification of the relevant biochemical architecture of CAR-T cell therapies and fulfill current unmet needs for CAR-T product knowledge. These advances include improved sample preparation methods, enhanced separation technologies, and extension of MS-based proteomic to single cells. Innovative technologies such as proteomic analysis of raw material quality attributes (MQA) and final product quality attributes (PQA) may provide insights that could ultimately fuel development strategies and lead to broad implementation.

Analysis of Proteasome-Generated Antigenic Peptides by Mass Spectrometry

Mass spectrometry (MS) is today one of the most important analytical techniques in biosciences. The development of electro spray ionization (ESI) as a gentle method, in which molecules are not destroyed, has revolutionized the analytic of peptides. MS is an ideal technique for detection and analysis of peptides generated by purified 20S proteasomes in in vitro experiments. This approach also provides a convenient and sensitive way to monitor the different processing characteristics of proteasome isoforms. The combination of high performance liquid chromatography (HPLC) with ESI-MS allows for the analysis of complex samples with separation in their specific constituents by LC and their subsequent detection by MS.

Absolute Quantitation of Oxidizable Peptides by Coulometric Mass Spectrometry

Quantitation methods for peptides using mass spectrometry have advanced rapidly. These methods rely on using standard and/or isotope-labeled peptides, which might be difficult or expensive to synthesize. To tackle this challenge, we present a new approach for absolute quantitation without the use of standards or calibration curves based on coulometry combined with mass spectrometry (MS). In this approach, which we call coulometric mass spectrometry (CMS), the mass spectrum of a target peptide containing one or more tyrosine residues is recorded before and after undergoing electrochemical oxidation. We record the total integrated oxidation current from the electrochemical measurement, which according to the Faraday's Law of coulometry, provides the number of moles of oxidized peptide. The ion intensity ratio of the target peptide before and after oxidation provides an excellent estimate of the fraction of the peptide that has been oxidized, from which the total amount of peptide is calculated. The striking strength of CMS is that it needs no standard peptide, but CMS does require the peptide to contain a known number of oxidizable groups. To illustrate the power of this method, we analyzed various tyrosine-containing peptides such as GGYR, DRVY, oxytocin, [Arg⁸]-vasotocin and angiotensinogen 1-14 with a quantification error ranging from - 7.5 to + 2.4%. This approach is also applicable to quantifying phosphopeptides and could be useful in proteomics research.

Proteomic Biomarkers for the Detection of Endometrial Cancer

Endometrial cancer is the leading gynaecological malignancy in the western world and its incidence is rising in tandem with the global epidemic of obesity. Early diagnosis is key to improving survival, which at 5 years is less than 20% in advanced disease and over 90% in early-stage disease. As yet, there are no validated biological markers for its early detection. Advances in high-throughput technologies and machine learning techniques now offer unique and promising perspectives for biomarker discovery, especially through the integration of genomic, transcriptomic, proteomic, metabolomic and imaging data. Because the proteome closely mirrors the dynamic state of cells, tissues and organisms, proteomics has great potential to deliver clinically relevant biomarkers for cancer diagnosis. In this review, we present the current progress in endometrial cancer diagnostic biomarker discovery using proteomics. We describe the various mass spectrometry-based approaches and highlight the challenges inherent in biomarker discovery studies. We suggest novel strategies for endometrial cancer detection exploiting biologically important protein biomarkers and set the scene for future directions in endometrial cancer biomarker research.

Quantitative Proteomics and Metabolomics Reveal Biomarkers of Disease as Potential Immunotherapy Targets and Indicators of Therapeutic Efficacy

Quantitative mass spectrometry (MS) continues to deepen our understanding of the immune system, quickly becoming the gold standard for obtaining high-throughput, quantitative data on biomolecules. The development of targeted and multiplexed assays for biomarker quantification makes MS an attractive tool both for diagnosing diseases and for quantifying the effects of immunotherapeutics. Because of its accuracy, the use of MS for identifying biomarkers of disease reduces the potential for misdiagnosis and overtreatment. Advances in workflows for sample processing have drastically reduced processing time and complexities due to sample preparation, making MS a more accessible technology. In this review, we present how recent developments in proteomics and metabolomics make MS an essential component of enhancing and monitoring the efficacy of immunotherapeutic treatments.

Fiber type diversity in skeletal muscle explored by mass spectrometry-based single fiber proteomics

Mammalian skeletal muscles are composed of a variety of muscle fibers with specialized functional properties. Slow fibers are suited for long lasting and low intensity contractile activity, while various subtypes of fast fibers are optimized to produce high force and power even with a significant fatigue. The functional specialization of muscle fibers is based on selective gene expression regulation, which provides each fiber with a specific protein complement. The recent refinement of small-scale sample preparation, combined with the development of mass spectrometers characterized by high sensitivity, sequencing speed and mass accuracy, has allowed the characterization of the proteome of single muscle fibers with an unprecedented resolution. In the last few years, the first studies on the global proteomics of individual fibers of different types have been published. In this short review we discuss the methodological advancements which have opened the way to single fiber proteomics and the discovery power of this approach. We provide examples of how specific features of single fibers can be overlooked when whole muscle or multi-fiber samples are analyzed and can only be detected when a single fiber proteome is analyzed. Thus, novel subtype-specific metabolic features, most prominently mitochondrial specialization of fiber types have been revealed by single fiber proteomics. In the same way, specific adaptive responses of single fibers to aging or loss of neural input have been detected when single fibers were individually analyzed. We conclude that the fiber type-resolved proteomes represent a powerful tool which can be applied to a variety of physiological and pathological conditions.

Dehydroascorbic acid S-Thiolation of peptides and proteins: Role of homocysteine and glutathione

Ascorbic acid (vitamin C) plays a significant role in the prevention of oxidative stress. In this process, ascorbate is oxidized to dehydroascorbate (DHA). We have investigated the impact of DHA on peptide/protein intramolecular disulfide formation as well as S-glutathionylation and S-homocysteinylation. S-glutathionylation of peptides/proteins is a reversible, potential regulatory mechanism in oxidative stress. Although the exact role of protein S-homocysteinylation is unknown, it has been proposed to be of importance in pathobiological processes such as onset of cardiovascular disease. Using an in vitro model system, we demonstrate that DHA causes disulfide bond formation within the active site of recombinant human glutaredoxin (Grx-1). DHA also facilities the formation of S-glutathionylation and S-homocysteinylation of a model peptide (AcFHACAAK) as well as Grx-1. We discuss the possible mechanisms of peptide/protein S-thiolation, which can occur either via thiol exchange or a thiohemiketal intermediate. A thiohemiketal DHA-peptide adduct was detected by mass spectrometry and its location on the peptide/protein cysteinyl thiol group was unambiguously confirmed by tandem mass spectrometry. This demonstrates that peptide/protein S-thiolation mediated by DHA is not limited to thiol exchange reactions but also takes place directly via the formation of a thiohemiketal peptide intermediate. Finally, we investigated a potential reducing role of glutathione (GSH) in the presence of S-homocysteinylated peptide/protein adducts. S-homocysteinylated AcFHACAAK, human hemoglobin α-chain and Grx-1 were incubated with GSH. Both peptide and proteins were reduced, and homocysteine replaced with GS-adducts by thiol exchange, as a function of time.

Proteomics and Leishmaniasis: Potential Clinical Applications

Leishmaniases are diseases caused by protozoan parasites of the genus Leishmania. They are endemic in 98 countries, affect around 12 million people worldwide and may present several distinct clinical forms. Unfortunately, there are only a few drugs available for treatment of leishmaniasis, which are toxic and not always effective. Different parasite species and different clinical forms require optimization of the treatment or more specific therapies, which are not available. The emergence of resistance is also a matter of concern. Besides, diagnosis can sometimes be complicated due to atypical manifestations and associations with other pathologies. In this review, proteomic data are presented and discussed in terms of their application in important issues in leishmaniasis such as parasite resistance to chemotherapy, diagnosis of active disease in patients and dogs, markers for different clinical forms, identification of virulence factors, and their potential use in vaccination. It is shown that proteomics has contributed to the discovery of potential biomarkers for prognosis, diagnosis, therapeutics, monitoring of disease progression, treatment follow-up and identification of vaccine candidates for specific diseases. However, the authors believe its capabilities have not yet been fully explored for routine clinical analysis for several reasons, which will be presented in this review.

The FUS-DDIT3 Interactome in Myxoid Liposarcoma

Myxoid liposarcoma is a malignant lipogenic tumor that develops in deep soft tissues. While local control rates are good, current chemotherapy options remain ineffective against metastatic disease. Myxoid liposarcoma is characterized by the FUS-DDIT3 fusion oncoprotein that is proposed to function as an aberrant transcription factor, but its exact mechanism of action has remained unclear. To identify the key functional interacting partners of FUS-DDIT3, this study utilized immunoprecipitation-mass spectrometry (IP-MS) to identify the FUS-DDIT3 interactome in whole cell lysates of myxoid liposarcoma cells, and results showed an enrichment of RNA processing proteins. Further quantitative MS analyses of FUS-DDIT3 complexes isolated from nuclear lysates showed that members of several chromatin regulatory complexes were present in the FUS-DDIT3 interactome, including NuRD, SWI/SNF, PRC1, PRC2, and MLL1 COMPASS-like complexes. Co-immunoprecipitation validated the associations of FUS-DDIT3 with BRG1/SMARCA4, BAF155/SMARCC1, BAF57/SMARCE1, and KDM1A. Data from this study provides candidates for functional validation as potential therapeutic targets, particularly for emerging epigenetic drugs.

Angiotensin II-Induced Oxidative Stress in Human Endothelial Cells: Modification of Cellular Molecules through Lipid Peroxidation

Angiotensin (Ang) II is a major bioactive peptide of the renin/angiotensin system and is involved in various cardiovascular functions and diseases. Ang II type 1 (AT₁) receptor mediates most of the physiological effects of Ang II. Previous studies have revealed that the lipid peroxidation products 4-oxo-2(E)-nonenal (ONE) and 4-hydroxy-2(E)-nonenal (HNE) readily modify the N-terminus and Asp¹, Arg², and His⁶ residues of Ang II, and these modifications alter the biological activities of Ang II. Ang II is known to stimulate the formation of reactive oxygen species (ROS) that mediate cardiovascular remodeling. Another major consequence of ROS-derived damage is lipid peroxidation, which generates genotoxic aldehydes such as ONE and HNE. This study demonstrated that Ang II induced lipid peroxidation-derived modifications of cellular molecules in EA.hy926 cells, a human vascular endothelial cell line. Ang P (ONE- and ROS-derived N-terminal pyruvamide Ang II) and [His⁶(HNE)]-Ang II were detected in the medium of EA.hy926 cells incubated with Ang II, and their concentrations increased dose-dependently upon the addition of ascorbic acid (AscA) and CuSO₄. Cells were then subjected to metabolic labeling using SILFAC (stable isotope labeling by fatty acids in cell culture) with [¹³C₁₈]-linoleic acid. Analysis of cellular phospholipids indicated over 90% labeling. [¹³C₉]-Thiadiazabicyclo-ONE-glutathione adduct as well as Ang P and [His⁶([¹³C₉]-HNE)]-Ang II was detected in the labeled cells upon treatment with Ang II and their concentrations increased in an Ang II dose-dependent manner. Incubation of the labeled cells with losartan, an AT₁ receptor blocker, inhibited the formation of modified Ang IIs in a dose-dependent manner. These results indicate that Ang II induces lipid peroxidation and modification of various cellular molecules and these reactions are mediated by the activation of AT₁ receptor. Therefore, lipid peroxidation could be one mechanism by which Ang II contributes to cardiovascular dysfunction.

Proteomics Approaches for Biomarker and Drug Target Discovery in ALS and FTD

Neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are increasing in prevalence but lack targeted therapeutics. Although the pathological mechanisms behind these diseases remain unclear, both ALS and FTD are characterized pathologically by aberrant protein aggregation and inclusion formation within neurons, which correlates with neurodegeneration. Notably, aggregation of several key proteins, including TAR DNA binding protein of 43 kDa (TDP-43), superoxide dismutase 1 (SOD1), and tau, have been implicated in these diseases. Proteomics methods are being increasingly applied to better understand disease-related mechanisms and to identify biomarkers of disease, using model systems as well as human samples. Proteomics-based approaches offer unbiased, high-throughput, and quantitative results with numerous applications for investigating proteins of interest. Here, we review recent advances in the understanding of ALS and FTD pathophysiology obtained using proteomics approaches, and we assess technical and experimental limitations. We compare findings from various mass spectrometry (MS) approaches including quantitative proteomics methods such as stable isotope labeling by amino acids in cell culture (SILAC) and tandem mass tagging (TMT) to approaches such as label-free quantitation (LFQ) and sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH-MS) in studies of ALS and FTD. Similarly, we describe disease-related protein-protein interaction (PPI) studies using approaches including immunoprecipitation mass spectrometry (IP-MS) and proximity-dependent biotin identification (BioID) and discuss future application of new techniques including proximity-dependent ascorbic acid peroxidase labeling (APEX), and biotinylation by antibody recognition (BAR). Furthermore, we explore the use of MS to detect post-translational modifications (PTMs), such as ubiquitination and phosphorylation, of disease-relevant proteins in ALS and FTD. We also discuss upstream technologies that enable enrichment of proteins of interest, highlighting the contributions of new techniques to isolate disease-relevant protein inclusions including flow cytometric analysis of inclusions and trafficking (FloIT). These recently developed approaches, as well as related advances yet to be applied to studies of these neurodegenerative diseases, offer numerous opportunities for discovery of potential therapeutic targets and biomarkers for ALS and FTD.

Mass spectrometry-based proteomics reveals the distinct nature of the skin proteomes of photoaged compared to intrinsically aged skin

OBJECTIVE

With increasing age, skin is subject to alterations in its organization, which impact on its function as well as having clinical consequences. Proteomics is a useful tool for non-targeted, semi-quantitative simultaneous investigation of high numbers of proteins. In the current study, we utilize proteomics to characterize and contrast age-associated differences in photoexposed and photoprotected skin, with a focus on the epidermis, dermal-epidermal junction and papillary dermis.

METHODS

Skin biopsies from buttock (photoprotected) and forearm (photoexposed) of healthy volunteers (aged 18-30 or ≥65 years) were transversely sectioned from the stratum corneum to a depth of 250 μm. Following SDS-PAGE, each sample lane was segmented prior to analysis by liquid chromatography-mass spectrometry/mass spectrometry. Pathway analysis was carried out using Ingenuity IPA.

RESULTS

Comparison of skin proteomes at buttock and forearm sites revealed differences in relative protein abundance. Ageing in skin on the photoexposed forearm resulted in 80% of the altered proteins being increased with age, in contrast to the photoprotected buttock where 74% of altered proteins with age were reduced. Functionally, age-altered proteins in the photoexposed forearm were associated with conferring structure, energy and metabolism. In the photoprotected buttock, proteins associated with gene expression, free-radical scavenging, protein synthesis and protein degradation were most frequently altered.

CONCLUSION

This study highlights the necessity of not considering photoageing as an accelerated intrinsic ageing, but as a distinct physiological process.

Mechanism of Action for HDAC Inhibitors-Insights from Omics Approaches

Histone deacetylase inhibitors (HDIs) are a class of prominent epigenetic drugs that are currently being tested in hundreds of clinical trials against a variety of diseases. A few compounds have already been approved for treating lymphoma or myeloma. HDIs bind to the zinc-containing catalytic domain of the histone deacetylase (HDACs) and they repress the deacetylase enzymatic activity. The broad therapeutic effect of HDIs with seemingly low toxicity is somewhat puzzling when considering that most HDIs lack strict specificity toward any individual HDAC and, even if they do, each individual HDAC has diverse functions under different physiology scenarios. Here, we review recent mechanistic studies using omics approaches, including epigenomics, transcriptomics, proteomics, metabolomics, and chemoproteomics, methods. These omics studies provide non-biased insights into the mechanism of action for HDIs.

Synthesis and characterization of a new MeCAT reagent containing a photocleavable linker for labeling of proteins and peptides in mass spectrometric analyses

The quantification of proteins and peptides becomes more important besides mere identification in modern life sciences. Therefore, we have developed a new reagent that adds to the known metall-coded affinity tagging strategy employed in molecular and elemental mass spectrometry containing a photocleavable linker. A synthesis route was developed that provides the new reagent in good yields. The stability of the synthesized reagents was assessed under different temperature and illumination conditions. Labeling reactions were carried out at peptide and protein level, while also the fragmentation behavior of labeled peptides was assessed. In additional experiments, the photocleavability of the new reagent was examined. Upon irradiation with ultraviolet light, the photoproducts were liberated and could be used for quantification of labeled peptides.

Application of Extracellular Vesicles Proteomics to Cardiovascular Disease: Guidelines, Data Analysis, and Future Perspectives

Extracellular vesicles (EVs) are a heterogeneous population of vesicles composed of a lipid bilayer that carry a large repertoire of molecules including proteins, lipids, and nucleic acids. In this review, some guidelines for plasma-derived EVs isolation, characterization, and proteomic analysis, and the application of the above to cardiovascular disease (CVD) studies are provided. For EVs analysis, blood samples should be collected using a 21-gauge needle, preferably in citrate tubes, and plasma stored for up to 1 year at -80°, using a single freeze-thaw cycle. For proteomic applications, differential centrifugation (including ultracentrifugation steps) is a good option for EVs isolation. EVs characterization is done by transmission electron microscopy, particle enumeration techniques (nanoparticle-tracking analysis, dynamic light scattering), and flow cytometry. Regarding the proteomics strategy, a label-free and gel-free quantitative method is a good choice due to its accuracy and because it minimizes the amount of sample required for clinical applications. Besides the above, main EVs proteomic findings in cardiovascular-related diseases are presented and analyzed in this review, paying especial attention to overlapping results between studies. The latter might offer new insights into the clinical relevance and potential of novel EVs biomarkers identified to date in the context of CVD.