MS-based Techniques Research Articles

Recent Advances in Mass Spectrometry-based Protein Interactome Studies

The foundation of all biological processes is the network of diverse and dynamic protein interactions with other molecules in cells known as the interactome. Understanding the interactome is crucial for elucidating molecular mechanisms but has been a longstanding challenge. Recent developments in mass spectrometry (MS)-based techniques, including affinity purification, proximity labeling, cross-linking, and co-fractionation mass spectrometry (MS), have significantly enhanced our abilities to study the interactome. They do so by identifying and quantifying protein interactions, yielding profound insights into protein organizations and functions. This review summarizes recent advances in MS-based interactomics, focusing on the development of techniques that capture protein-protein, protein-metabolite, and protein-nucleic acid interactions. Additionally, we discuss how integrated MS-based approaches have been applied to diverse biological samples, focusing on significant discoveries that have leveraged our understanding of cellular functions. Finally, we highlight state-of-the-art bioinformatic approaches for predictions of interactome and complex modeling, as well as strategies for combining experimental interactome data with computation methods, thereby enhancing the ability of MS-based techniques to identify protein interactomes. Indeed, advances in MS technologies and their integrations with computational biology provide new directions and avenues for interactome research, leveraging new insights into mechanisms that govern the molecular architecture of living cells and, thereby, our comprehension of biological processes.

Exploring the protein signature of endometrial cancer: A comprehensive review through diverse samples and mass spectrometry-based proteomics

Endometrial cancer (EC) is increasing incidence among women, and it constitutes a health problem for women globally. An important aspect of EC management involves the use of protein biomarkers for early detection and monitoring. Protein biomarkers allow the identification of high-risk patients, the detection of the disease in its early stages, and the assessment of treatment responses. Mass spectrometry (MS)-based proteomics offers robust analytical techniques and a comprehensive understanding of proteins. Proteomics methods allow scientists to investigate both the quantities and functions of proteins. Thus, it provides valuable insights into how proteins are altered under different conditions. This review summarizes recent advances in MS-based proteomic biomarker discovery for EC, focusing on different sample types and MS-based techniques used in clinical studies. The review emphasized in detail the most commonly used key sources such as blood, urine, vaginal fluids and tissue. Furthermore, MS-based proteomics techniques such as untargeted, targeted, sequential window acquisition of all theoretical mass spectra (SWATH-MS) and mass spectrometry imaging used in the discovery and validation/validation phases were evaluated. This review highlights the importance of biomarker discovery and clinical translation to improve diagnostic and therapeutic outcomes in EC. It aims to provide a comprehensive overview of MS-based proteomics in EC, guiding future research and clinical applications.

Peptide Biomarkers - An Emerging Diagnostic Tool and Current Applicable Assay.

In the past few decades, impressive progress achieved in technology development and improvementhasaccelerated the application of peptides as diagnostic biomarkers for various diseases. We outline the advantages of peptides as good diagnostic targets, since they serve as molecular surrogates of enzyme activities, much more specific biomarkers than proteins, and also play vital roles in many biological processes. On the basis of an extensive literature survey, peptide markers with high specificity and sensitivity that are currently applied in clinical tests, as well as recently identified, are summarized for the following four major categories of diseases: neurodegenerative disease, heart failure, infectious disease, and cancer. In addition, we summarize a few prevalent techniques used in peptide biomarker discovery and analysis, such as immunoassays, nanopore-based and nanoparticle-based peptide detection, and also MS-based peptide analysis techniques, and their pros and cons. Currently, there are plenty of analytical technologies available to achieve fast, sensitive and reliable peptide analyses, benefiting from the developments of hardware and instrumentation, as well as data analysis software and databases. Thus, with peptides emerging as sensitive, specific and reliable biomarkers for early detection of diseases, therapeutic monitoring, clinical treatment decisions and disease prognosis, the medical need for peptide biomarkers will increase strongly in the future.

Fatty Acid Synthase as Interacting Anticancer Target of the Terpenoid Myrianthic Acid Disclosed by MS-Based Proteomics Approaches.

This research focuses on the target deconvolution of the natural compound myrianthic acid, a triterpenoid characterized by an ursane skeleton isolated from the roots of Myrianthus arboreus and from Oenothera maritima Nutt. (Onagraceae), using MS-based chemical proteomic techniques. Application of drug affinity responsive target stability (DARTS) and targeted-limited proteolysis coupled to mass spectrometry (t-LiP-MS) led to the identification of the enzyme fatty acid synthase (FAS) as an interesting macromolecular counterpart of myrianthic acid. This result, confirmed by comparison with the natural ursolic acid, was thoroughly investigated and validated in silico by molecular docking, which gave a precise picture of the interactions in the MA/FAS complex. Moreover, biological assays showcased the inhibitory activity of myrianthic acid against the FAS enzyme, most likely related to its antiproliferative activity towards tumor cells. Given the significance of FAS in specific pathologies, especially cancer, the myrianthic acid structural moieties could serve as a promising reference point to start the potential development of innovative approaches in therapy.

Metabolome classification of olive by-products from different oil presses providing insights into its potential health benefits and valorization as analyzed via multiplex MS-based techniques coupled to chemometrics.

The Olive (Olea europaea L.) is one of the most popular edible oil-producing fruits, consumed worldwide for its myriad nutritional and health benefits. Olive oil production generates huge quantities of by-products from the fruit, which are considered environmental hazards. Recently, more and more efforts have been made to valorize olive by-products as a source of low-cost, value-added food applications. The main objective of this study was to globally assess the metabolome of olive fruit by-products, including olive mill wastewater, olive pomace, and olive seeds from fruits from two areas, Siwa and Anshas, Egypt. Gas chromatography-mass spectrometry (GC-MS) and ultra-high-performance liquid chromatography with mass spectrometry (UPLC-MS) were used for profiling primary and secondary metabolites in olive by-products. Also, multivariate data analyses were used to assess variations between olive by-product samples. A total of 103 primary metabolites and 105 secondary metabolites were identified by GC-MS and UPLC-MS, respectively. Fatty acids amounted to a major class in the olive by-products at 53-91%, with oleic acid dominating, especially in the pomace of Siwa. Mill wastewater was discriminated from other by-products by the presence of phenolics mainly tyrosol, hydroxyl tyrosol, and α-tocopherol as analyzed by UPLC-MS indicating their potential antioxidant activity. Pomace and seeds were rich in fatty acids/esters and hydroxy fatty acids and not readily distinguishable from each other. The current work discusses the metabolome profile of olive waste products for valorization purposes. Pomace and seeds were enriched in fatty acids/esters, though not readily distinguishable from each other.

M-nitrobenzyl alcohol supercharging reagent enhances the chromatographic separation and the charging of disulfide bond linked and His-tag peptides

The linkages of disulfide bond (DSB) play important roles in protein stability and activity. Mass spectrometry-based (MS-based) techniques become accepted tools for DSB analysis in the recent decade. In the bottom-up approach, after enzyme digestion, the neighbouring amino acids of cysteines have great impacts on the physicochemical properties of resulting disulfide bond peptides, determining their retention behaviour on liquid chromatography (LC) and their MS ionization efficiency. In this study, the addition of supercharging reagent in LC mobile phase was used to examine the impact of supercharging reagent on the charge states of disulfide-bond peptides. The results showed that 0.1 % m-nitrobenzyl alcohol (m-NBA) in LC mobile phase increased the sensitivity and charge states of DSB peptides from our model protein, equine Interleukin-5 (eIL5), as well as the resolution of reversed-phase chromatography. Notably, also the sensitivity of C-terminal peptide with His-tag significantly improved. Our findings highlight the effectiveness of employing m-NBA as a supercharging reagent when investigating disulfide-linked peptides and the C-terminal peptide with a His-tag through nano-liquid chromatography mass spectrometry.

Recent Developments in Machine Learning for Mass Spectrometry.

Statistical analysis and modeling of mass spectrometry (MS) data have a long and rich history with several modern MS-based applications using statistical and chemometric methods. Recently, machine learning (ML) has experienced a renaissance due to advents in computational hardware and the development of new algorithms for artificial neural networks (ANN) and deep learning architectures. Moreover, recent successes of new ANN and deep learning architectures in several areas of science, engineering, and society have further strengthened the ML field. Importantly, modern ML methods and architectures have enabled new approaches for tasks related to MS that are now widely adopted in several popular MS-based subdisciplines, such as mass spectrometry imaging and proteomics. Herein, we aim to provide an introductory summary of the practical aspects of ML methodology relevant to MS. Additionally, we seek to provide an up-to-date review of the most recent developments in ML integration with MS-based techniques while also providing critical insights into the future direction of the field.

Labeling of Mucin-Type O-Glycans for Quantification Using Liquid Chromatography and Fluorescence Detection.

O-glycosylation is a common post-translational modification that is essential for the defensive properties of mucus barriers. Incomplete and altered O-glycosylation is often linked to severe diseases, such as cancer, cystic fibrosis, and chronic obstructive pulmonary disease. Originating from a nontemplate-driven biosynthesis, mucin-type O-glycan structures are very complex. They are often present as heterogeneous mixtures containing multiple isomers. Therefore, the analysis of complex O-glycan mixtures usually requires hyphenation of orthogonal techniques such as liquid chromatography (LC), ion mobility spectrometry, and mass spectrometry (MS). However, MS-based techniques are mainly qualitative. Moreover, LC separation of O-glycans often lacks reproducibility and requires sophisticated data treatment and analysis. Here we present a mucin-type O-glycomics analysis workflow that utilizes hydrophilic interaction liquid chromatography for separation and fluorescence labeling for detection and quantification. In combination with mass spectrometry, a detailed analysis on the relative abundance of specific mucin-type O-glycan compositions and features, such as fucose, sialic acids, and sulfates, is performed. Furthermore, the average number of monosaccharide units of O-glycans in different samples was determined. To demonstrate universal applicability, the method was tested on mucins from different tissue types and mammals, such as bovine submaxillary mucins, porcine gastric mucins, and human milk mucins. To account for day-to-day retention time shifts in O-glycan separations and increase the comparability between different instruments and laboratories, we included fluorescently labeled dextran ladders in our workflow. In addition, we set up a library of glucose unit values for all identified O-glycans, which can be used to simplify the identification process of glycans in future analyses.

Lipidomics insight on differences between human MFGM and dietary-derived lipids.

Milk fat globule membrane (MFGM) contains lipids, which are essential for promoting infant brain development and improving cognition. In this study, the lipid differences between human MFGM and four dietary lipid sources (cow MFGM, soybean, krill, and yolk) were compared using the UHPLC-Q-Exactive MS-based lipidomics techniques. A total of 45 lipid classes and 5048 lipid species were detected. The analysis of phospholipid classes revealed that the lipid composition of human MFGM and cow MFGM was more similar than the other dietary-derived lipids. Additionally, the human MFGM lipid species were compared with cow MFGM, soybean, krill, and yolk, and 401, 416, 494, and 444 significantly different lipids were identified, respectively. Through lipid metabolic pathway analysis, differential lipids were mainly involved in the glycerophospholipid metabolic pathway. Overall, these results will provide a rationale for the future addition of lipids to infant formula to more closely approximate human MFGM lipid profiles.

Mass spectrometry-based approaches to assess the botanical authenticity of dietary supplements.

Dietary supplements are legally considered foods despite frequently including medicinal plants as ingredients. Currently, the consumption of herbal dietary supplements, also known as plant food supplements (PFS), is increasing worldwide and some raw botanicals, highly demanded due to their popularity, extensive use, and/or well-established pharmacological effects, have been attaining high prices in the international markets. Therefore, botanical adulteration for profit increase can occur along the whole PFS industry chain, from raw botanicals to plant extracts, until final PFS. Besides the substitution of high-value species, unintentional mislabeling can happen in morphologically similar species. Both cases represent a health risk for consumers, prompting the development of numerous works to access botanical adulterations in PFS. Among different approaches proposed for this purpose, mass spectrometry (MS)-based techniques have often been reported as the most promising, particularly when hyphenated with chromatographic techniques. Thus, this review aims at describing an overview of the developments in this field, focusing on the applications of MS-based techniques to targeted and untargeted analysis to detect botanical adulterations in plant materials, extracts, and PFS.

An insight into spray paints for street art: Chemical characterization of two yellow varnishes by spectroscopic and MS-based spectrometric techniques

In recent decades, modern murals and graffiti have become valuable artistic expressions that deserve attention for their dissemination and conservation. The chemical composition of spray paints with improved technical performance reflects the assortment of materials used in these artworks. Understanding the spray formulations is important in preventing deterioration of street art. In this study, two yellow varnishes were investigated by attenuated total reflectance Fourier-transform infrared (ATR-FTIR) and X-ray photoelectron spectroscopies (XPS), laser desorption ionization (LDI) and matrix-assisted (MA) LDI mass spectrometry (MS). ATR-FTIR allowed us to distinguish the occurrence of acrylic and styrene-acrylic resins as the main binders with some additional components, while XPS shed light on the recognition of some silicone-based additives, which aggregate at the most superficial varnish layers. Several established experimental conditions of MALDI-MS including matrix, salt dopant and extraction solvent, revealed the use of polyethylene glycol as an additive, while direct LDI-MS/MS analysis proved to be very useful in characterizing the yellow (PY74) and orange (PO36) pigments. Some insight into the minor components of the spray paints, such as surfactant, humectant and silicone-based levelling or anti-cratering agents, which were not easily obtained through conventional approaches, was also gained.

Progress of Mass Spectrometry-Based Lipidomics in the Dairy Field.

Lipids play important biological roles, such as providing essential fatty acids and signaling. The wide variety and structural diversity of lipids, and the limited technical means to study them, have seriously hampered the resolution of the mechanisms of action of lipids. With advances in mass spectrometry (MS) and bioinformatic technologies, large amounts of lipids have been detected and analyzed quickly using MS-based lipidomic techniques. Milk lipids, as complex structural metabolites, play a crucial role in human health. In this review, the lipidomic techniques and their applications to dairy products, including compositional analysis, quality identification, authenticity identification, and origin identification, are discussed, with the aim of providing technical support for the development of dairy products.

Mass spectrometry-based proteomic strategy for ecchymotic skin examination in forensic pathology

Mass spectrometry (MS)-based proteomics has recently attracted the attention from forensic pathologists. This work is the first report of the development of a shotgun bottom-up proteomic approach based on rapid protein extraction and nano-liquid chromatography/high-resolution mass spectrometry applied to full-thickness human skin for the differential analysis of normal and ecchymotic tissues to identify new biomarkers for bruise characterization and dating. We identified around 2000 proteins from each pooled extract. The method showed excellent precision on independent replicates, with Pearson correlation coefficients always higher than 95%. Glycophorin A, a known biomarker of vital wounds from immunochemical studies, was identified only in ecchymotic tissues, as confirmed by Western blotting analysis. This finding suggests that this protein can be used as a MS-detectable biomarker of wound vitality. By focusing on skin samples from individuals with known wound dating, besides Glycophorin A, other proteins differentially expressed in ecchymotic samples and dependant on wound age were identified, although further analysis on larger datasets are needed to validate these findings. This study paves the way for an in-depth investigation of the potential of MS-based techniques for wound examination in forensic pathology, overcoming the limitations of immunochemical assays.

Proteomics-Based Identification of Dysregulated Proteins and Biomarker Discovery in Invasive Ductal Carcinoma, the Most Common Breast Cancer Subtype.

Invasive ductal carcinoma (IDC) is the most common histological subtype of malignant breast cancer (BC), and accounts for 70-80% of all invasive BCs. IDC demonstrates great heterogeneity in clinical and histopathological characteristics, prognoses, treatment strategies, gene expressions, and proteomic profiles. Significant proteomic determinants of the progression from intraductal pre-invasive malignant lesions of the breast, which characterize a ductal carcinoma in situ (DCIS), to IDC, are still poorly identified, validated, and clinically applied. In the era of "6P" medicine, it remains a great challenge to determine which patients should be over-treated versus which need to be actively monitored without aggressive treatment. The major difficulties for designating DCIS to IDC progression may be solved by understanding the integrated genomic, transcriptomic, and proteomic bases of invasion. In this review, we showed that multiple proteomics-based techniques, such as LC-MS/MS, MALDI-ToF MS, SELDI-ToF-MS, MALDI-ToF/ToF MS, MALDI-MSI or MasSpec Pen, applied to in-tissue, off-tissue, BC cell lines and liquid biopsies, improve the diagnosis of IDC, as well as its prognosis and treatment monitoring. Classic proteomics strategies that allow the identification of dysregulated protein expressions, biological processes, and interrelated pathway analyses based on aberrant protein-protein interaction (PPI) networks have been improved to perform non-invasive/minimally invasive biomarker detection of early-stage IDC. Thus, in modern surgical oncology, highly sensitive, rapid, and accurate MS-based detection has been coupled with "proteome point sampling" methods that allow for proteomic profiling by in vivo "proteome point characterization", or by minimal tissue removal, for ex vivo accurate differentiation and delimitation of IDC. For the detection of low-molecular-weight proteins and protein fragments in bodily fluids, LC-MS/MS and MALDI-MS techniques may be coupled to enrich and capture methods which allow for the identification of early-stage IDC protein biomarkers that were previously invisible for MS-based techniques. Moreover, the detection and characterization of protein isoforms, including posttranslational modifications of proteins (PTMs), is also essential to emphasize specific molecular mechanisms, and to assure the early-stage detection of IDC of the breast.

Data-independent acquisition boosts quantitative metaproteomics for deep characterization of gut microbiota

Metaproteomics can provide valuable insights into the functions of human gut microbiota (GM), but is challenging due to the extreme complexity and heterogeneity of GM. Data-independent acquisition (DIA) mass spectrometry (MS) has been an emerging quantitative technique in conventional proteomics, but is still at the early stage of development in the field of metaproteomics. Herein, we applied library-free DIA (directDIA)-based metaproteomics and compared the directDIA with other MS-based quantification techniques for metaproteomics on simulated microbial communities and feces samples spiked with bacteria with known ratios, demonstrating the superior performance of directDIA by a comprehensive consideration of proteome coverage in identification as well as accuracy and precision in quantification. We characterized human GM in two cohorts of clinical fecal samples of pancreatic cancer (PC) and mild cognitive impairment (MCI). About 70,000 microbial proteins were quantified in each cohort and annotated to profile the taxonomic and functional characteristics of GM in different diseases. Our work demonstrated the utility of directDIA in quantitative metaproteomics for investigating intestinal microbiota and its related disease pathogenesis.

Probing the structures of G protein-coupled receptors with mass spectrometry-based techniques

G protein-coupled receptors (GPCRs) are key molecules to regulate numerous physiological processes in the human body, and represent one of the largest protein families as targets for drug development for various human diseases. Understanding the structural basis for GPCR activation, signaling and regulatory mechanisms lays the foundation for structure-based drug design. Compared to X-ray crystallography and cryo-electron microscopy which mainly present static snapshots of protein structures, mass spectrometry (MS)-based structural analysis is able to yield complementary information on the conformational ensemble and dynamics of protein machineries and their interactions with ligands or other proteins. Analysis of GPCR structures with multiple MS-based techniques have facilitated the characterization of structural architecture and conformational dynamics of GPCR proteins complexed with specific ligands and/or downstream signaling partners. In this review, we introduce four MS techniques (chemical cross-linking MS, hydrogen/deuterium exchange MS, native MS and fast photochemical oxidation of proteins MS) and illustrate how they are implemented to probe the structures of GPCR proteins and signaling complexes.

Recent Advances in Mass Spectrometry-Based Structural Elucidation Techniques.

Mass spectrometry (MS) has become the central technique that is extensively used for the analysis of molecular structures of unknown compounds in the gas phase. It manipulates the molecules by converting them into ions using various ionization sources. With high-resolution MS, accurate molecular weights (MW) of the intact molecular ions can be measured so that they can be assigned a molecular formula with high confidence. Furthermore, the application of tandem MS has enabled detailed structural characterization by breaking the intact molecular ions and protonated or deprotonated molecules into key fragment ions. This approach is not only used for the structural elucidation of small molecules (MW < 2000 Da), but also crucial biopolymers such as proteins and polypeptides; therefore, MS has been extensively used in multiomics studies for revealing the structures and functions of important biomolecules and their interactions with each other. The high sensitivity of MS has enabled the analysis of low-level analytes in complex matrices. It is also a versatile technique that can be coupled with separation techniques, including chromatography and ion mobility, and many other analytical instruments such as NMR. In this review, we aim to focus on the technical advances of MS-based structural elucidation methods over the past five years, and provide an overview of their applications in complex mixture analysis. We hope this review can be of interest for a wide range of audiences who may not have extensive experience in MS-based techniques.

Mass Spectrometry-Based Nontargeted and Targeted Analytical Approaches in Fingerprinting and Metabolomics of Food and Agricultural Research.

Mass spectrometry (MS)-based techniques have been extensively applied in food and agricultural research. This review aims to address the advances and applications of MS-based analytical strategies in nontargeted and targeted analysis and summarizes the recent publications of MS-based techniques, including flow injection MS fingerprinting, chromatography-tandem MS metabolomics, direct analysis using ambient mass spectrometry, as well as development in MS data deconvolution software packages and databases for metabolomic studies. Various nontargeted and targeted approaches are employed in marker compounds identification, material adulteration detection, and the analysis of specific classes of secondary metabolites. In the newly emerged applications, the recent advances in computer tools for the fast deconvolution of MS data in targeted secondary metabolite analysis are highlighted.

Identification of Epigallocatechin-3-Gallate (EGCG) from Green Tea Using Mass Spectrometry

In an era where humanity is reinstating its lost hope and expectation on natural products, green tea occupies quite a position for what it has proven to be, in its endeavors for human welfare and health. Epigallocatechin-3-gallate (EGCG) is the key to the vast biological activities of green tea. Green tea is no longer in the backdrop; it has emerged as the most viral, trending bioactive molecule when it comes to health benefits for human beings. This review focuses on the use of various analytical techniques for the analysis of EGCG. That which has been achieved so far, in terms of in vitro, pure component analysis, as well as those spikes in biological fluids and those in vivo in animal and human samples, was surveyed and presented. The use of MS-based techniques for the analysis of EGCG is elaborately reviewed and the need for improvising the applications is explained. The review emphasizes that there is plenty of room to explore matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) applications in this subject area.

Mass spectrometry in food authentication and origin traceability.

Food authentication and origin traceability are popular research topics, especially as concerns about food quality continue to increase. Mass spectrometry (MS) plays an indispensable role in food authentication and origin traceability. In this review, the applications of MS in food authentication and origin traceability by analyzing the main components and chemical fingerprints or profiles are summarized. In addition, the characteristic markers for food authentication are also reviewed, and the advantages and disadvantages of MS-based techniques for food authentication, as well as the current trends and challenges, are discussed. The fingerprinting and profiling methods, in combination with multivariate statistical analysis, are more suitable for the authentication of high-value foods, while characteristic marker-based methods are more suitable for adulteration detection. Several new techniques have been introduced to the field, such as proton transfer reaction mass spectrometry, ambient ionization mass spectrometry (AIMS), and ion mobility mass spectrometry, for the determination of food adulteration due to their fast and convenient analysis. As an important trend, the miniaturization of MS offers advantages, such as small and portable instrumentation and fast and nondestructive analysis. Moreover, many applications in food authentication are using AIMS, which can help food authentication in food inspection/field analysis. This review provides a reference and guide for food authentication and traceability based on MS.