Lipid Analysis Research Articles

Classifying patients with psoriatic arthritis according to their disease activity status using serum metabolites and machine learning

IntroductionPsoriatic arthritis (PsA) is a heterogeneous inflammatory arthritis, affecting approximately a quarter of patients with psoriasis. Accurate assessment of disease activity is difficult. There are currently no clinically validated biomarkers to stratify PsA patients based on their disease activity, which is important for improving clinical management.ObjectivesTo identify metabolites capable of classifying patients with PsA according to their disease activity.MethodsAn in-house solid-phase microextraction (SPME)—liquid chromatography-high resolution mass spectrometry (LC-HRMS) method for lipid analysis was used to analyze serum samples obtained from patients classified as having low (n = 134), moderate (n = 134) or high (n = 104) disease activity, based on psoriatic arthritis disease activity scores (PASDAS). Metabolite data were analyzed using eight machine learning methods to predict disease activity levels. Top performing methods were selected based on area under the curve (AUC) and significance.ResultsThe best model for predicting high disease activity from low disease activity achieved AUC 0.818. The best model for predicting high disease activity from moderate disease activity achieved AUC 0.74. The best model for classifying low disease activity from moderate and high disease activity achieved AUC 0.765. Compounds confirmed by MS/MS validation included metabolites from diverse compound classes such as sphingolipids, phosphatidylcholines and carboxylic acids.ConclusionSeveral lipids and other metabolites when combined in classifying models predict high disease activity from both low and moderate disease activity. Lipids of key interest included lysophosphatidylcholine and sphingomyelin. Quantitative MS assays based on selected reaction monitoring, are required to quantify the candidate biomarkers identified.

Structural determination of Rickettsia lipid A without chemical extraction confirms shorter acyl chains in later-evolving spotted fever group pathogens.

Rickettsiae are Gram-negative obligate intracellular parasites of numerous eukaryotes. Human pathogens of the transitional group (TRG), typhus group (TG), and spotted fever group (SFG) rickettsiae infect blood-feeding arthropods, have dissimilar clinical manifestations, and possess unique genomic and morphological attributes. Lacking glycolysis, rickettsiae pilfer numerous metabolites from the host cytosol to synthesize peptidoglycan and lipopolysaccharide (LPS). For LPS, O-antigen immunogenicity varies between SFG and TG pathogens; however, lipid A proinflammatory potential is unknown. We previously demonstrated that Rickettsia akari (TRG), Rickettsia typhi (TG), and Rickettsia montanensis (SFG) produce lipid A with long 2' secondary acyl chains (C16 or C18) compared to short 2' secondary acyl chains (C12) in Rickettsia rickettsii (SFG) lipid A. To further probe this structural heterogeneity and estimate a time point when shorter 2' secondary acyl chains originated, we generated lipid A structures for two additional SFG rickettsiae (Rickettsia rhipicephali and Rickettsia parkeri) utilizing fast lipid analysis technique adopted for use with tandem mass spectrometry (FLATn). FLATn allowed analysis of lipid A structure directly from host cell-purified bacteria, providing a substantial improvement over lipid A chemical extraction. FLATn-derived structures indicate SFG rickettsiae diverging after R. rhipicephali evolved shorter 2' secondary acyl chains. While 2' secondary acyl chain lengths do not distinguish Rickettsia pathogens from non-pathogens, in silico analyses of Rickettsia LpxL late acyltransferases revealed discrete active sites and hydrocarbon rulers for long versus short 2' secondary acyl chain addition. Our collective data warrant determining Rickettsia lipid A inflammatory potential and how structural heterogeneity impacts lipid A-host receptor interactions.IMPORTANCEDeforestation, urbanization, and homelessness lead to spikes in Rickettsioses. Vector-borne human pathogens of transitional group (TRG), typhus group (TG), and spotted fever group (SFG) rickettsiae differ by clinical manifestations, immunopathology, genome composition, and morphology. We previously showed that lipid A (or endotoxin), the membrane anchor of Gram-negative bacterial lipopolysaccharide (LPS), structurally differs in Rickettsia rickettsii (later-evolving SFG) relative to Rickettsia montanensis (basal SFG), Rickettsia typhi (TG), and Rickettsia akari (TRG). As lipid A structure influences recognition potential in vertebrate LPS sensors, further assessment of Rickettsia lipid A structural heterogeneity is needed. Here, we sidestepped the difficulty of ex vivo lipid A chemical extraction by utilizing fast lipid analysis technique adopted for use with tandem mass spectrometry, a new procedure for generating lipid A structures directly from host cell-purified bacteria. These data confirm that later-evolving SFG pathogens synthesize structurally distinct lipid A. Our findings impact interpreting immune responses to different Rickettsia pathogens and utilizing lipid A adjuvant or anti-inflammatory properties in vaccinology.

Comparative analysis of the skin surface lipids between acne patients and controls using UFLC method

Comparative analysis of the skin surface lipids between acne patients and controls using UFLC method

LCMS: An R package for automated semitargeted analysis in lipidomics

AbstractWhile nontargeted analysis aims to profile and report the relative distributions of a wide range of molecules from different lipid classes/subclasses, its major challenge is the annotation and identification of the molecules. Semitargeted analysis circumvents the problem by establishing a (potentially large) list of molecules to be targeted in the samples that are identified before the analysis. This approach is particularly adapted for lipid analysis to help with the automation of lipid annotation and identification. However, the manual extraction of peaks for many molecules and many samples is time consuming. Consequently, an automation of these extractions is deeply required. This paper presents a free R package for the automation of semitargeted analysis for lipid analysis. From raw files collected with LC‐MS device and a list of molecules to target (containing their class), it automatically returns Excel files containing the intensities for each targeted molecule and each sample. This package allows a fast computation of the intensities. Furthermore, it guarantees the reproducibility of the results and is freely available and user‐friendly.Practical Applications: With the help of the R package presented in this paper, the use of semitargeted lipidomics as an alternative to untargeted analysis should be investigated by more labs. Work on the comparisons between the approaches could be conducted. While untargeted methods are mostly used, they require long pretreatments and identification of molecules of interest. On the contrary, in semitargeted analysis, once the integration table and retention time are obtained, the results are fast and directly interpretable. An idea for lipidomics would be to use untargeted lipidomics to compute the integration table and retention table, then use semitargeted analysis for a fast computation of well identified molecules.

Comparison of three rapid diagnostic tests for bloodstream infections using Benefit-risk Evaluation Framework (BED-FRAME).

Rapid diagnostic tests (RDTs) for bloodstream infections have the potential to reduce time to appropriate antimicrobial therapy and improve patient outcomes. Previously, an in-house, lipid-based, matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) method, Fast Lipid Analysis Technique (FLAT MS), has shown promise as a rapid pathogen identification method. In this study, FLAT MS for direct from blood culture identification was evaluated and compared to FDA-cleared identification methods using the Benefit-risk Evaluation Framework (BED-FRAME) analysis. FLAT MS was evaluated and compared to Bruker Sepsityper and bioMérieux BioFire FilmArray BCID2 using results from a previous study. For this study, 301 positive blood cultures were collected from the University of Maryland Medical Center. The RDTs were compared by their sensitivities, time-to-results, hands-on time, and BED-FRAME analysis. The overall sensitivity of all platforms compared to culture results from monomicrobial-positive blood cultures was 88.3%. However, the three RDTs differed in their accuracy for identifying Gram-positive bacteria, Gram-negative bacteria, and yeast. Time-to-results for FLAT MS, Sepsityper, and BioFire BCID2 were all approximately one hour. Hands-on times for FLAT MS, Sepsityper, and BioFire BCID2 were 10 (±1.3), 40 (±2.8), and 5 (±0.25) minutes, respectively. BED-FRAME demonstrated that each RDT had utility at different pathogen prevalence and relative importance. BED-FRAME is a useful tool that can used to determine which RDT is best for a healthcare center.

Lipidomic analysis of facial skin surface lipids in acne in young women.

Alterations in the secretion and composition of skin surface lipids (SSL) are closely associated with the development of acne. Lipidomics is a useful tool to analyse the SSL of different types of acne. Our previous study found that phosphatidylserine and triacylglycerols dominate SSL changes in male acne and infantile acne, respectively. However, skin surface lipids as well as specific lipids in female acne patients remain to be investigated. To analyse and compare the SSL profile of acne women and healthy women and to discuss the involvement of differential lipids in acne development. Systematic lipidomics approach (high-throughput UPLC-QTOF-MS technology in combination with multivariate data analysis methods) was used to analyse the variations of SSL between acne and healthy groups. Analysis revealed significant differences in lipid content and composition between the two groups. Further analysis showed that levels of 13 individual lipids were significantly different and followed the same trend as the main class and subclasses. The largest individual contributor to the subgroup was triglycerides (TG) and phosphatidylinositol (PI). In addition, female acne patients exhibited reduced ceramide chain length (CCL) and increased levels of unsaturated fatty acids (UFAs), The changes of CCL in female acne are identical to male acne. There was a significantly higher level of TG and PI in the SSL of female acne patients. A reduction in CCL and an increase in UFAs content might contribute to the reduced skin barrier function in acne patients. The results suggest that female acne may have different pathogenesis than male acne.

Nitro Indole Derivatives as Novel Dual-Polarity Matrices for MALDI Mass Spectrometry and Imaging with Broad Applications.

A new matrix framework is presented in this study for the improved ionization efficiency of complex mixtures by matrix-assisted laser desorption ionization (MALDI) mass spectrometry/imaging. Five nitro indole (NI) derivatives [3-methyl-4-nitro-1H-indole (3,4-MNI), 3-methyl-6-nitro-1H-indole (3,6-MNI), 2,3-dimethyl-4-nitro-1H-indole (2,3,4-DMNI), 2,3-dimethyl-6-nitro-1H-indole (2,3,6-DMNI), and 4-nitro-1H-indole (4-NI)] were synthesized and shown to produce both positive and negative ions with a broad class of analytes as MALDI matrices. NI matrices were compared to several common matrices, such as 2,5-dihydroxybenzoic acid (DHB), alpha-cyano-4-hydroxylcinnamic acid (CHCA), sinapinic acid (SA), 1,5-diaminonaphthelene (1,5-DAN), and 9-aminoacridine (9-AA), for the analysis of lipid, peptide, protein, glycan, and perfluorooctanesulfonic acid (PFOS) compounds. 3,4-MNI demonstrated the best performance among the NI matrices. This matrix resulted in reduced ion suppression and better detection sensitivity for complex mixtures, for example, egg lipids/milk proteins/PFOS in tap water, while 2,3,6-DMNI was the best matrix for blueberry tissue imaging. Several important aspects of this work are reported: (1) dual-polarity ion production with NI matrices and complex mixtures; (2) quantitative analysis of PFOS with a LOQ of 0.5 ppb in tap water and 0.05 ppb in MQ water (without solid phase extraction enrichment), with accuracy and precision within 5%; (3) MALDI imaging with 2,3,6-DMNI as a matrix for plant metabolite/lipid identification with ionization enhancement in the negative ion mode m/z 600-900 region; and (4) development of a thin film deposition under/above tissue method for MALDI imaging with a vacuum sublimation matrix on a high-vacuum MALDI instrument.

Faire gras à Molène: dairy products and ruminant fats detected by lipid and isotopic analysis of pottery dating to the Final Neolithic-Early Bronze Age from the island site of Beg ar Loued (Molène, western Brittany, France)

The subsistence strategies of early farming communities have been highlighted since the beginning of the Neolithic, thanks to numerous studies on lipid residues from ceramic vessels conducted in various parts of continental Europe. However, after the Early Neolithic, evidence of subsistence strategies along the northern Atlantic coast are still lacking, especially for island contexts. This paper presents the results of lipid residue analysis of 129 potsherds from Beg ar Loued (Molène, France), an island site dating primarily to the Early Bronze Age (c. 2700-2600 to 1800 BCE). Aiming to understand the use of vessels, vessel treatment and culinary practices on the settlement, analyses of visible charred residues, sherds and ceramic surfaces/coating layers were carried out using chromatographic (n = 174) and isotopic techniques (n = 24) after lipid extraction by solvent (n = 174) or acid methanolysis (n = 31). The results demonstrate the extensive use of terrestrial products (ruminant carcass and dairy) in pottery, including occasional plant products (with possible mixtures of different waxes), while the detection of aquatic products is limited. Thus, combined with evidence from faunal remains at the site, the results indicate that terrestrial resources like ruminant meat and dairy products were preferentially processed in vessels, and aquatic products mostly without the use of ceramics. These findings demonstrate the significance of lipid residue analysis for studying the role of pottery in food production and consumption at sites along the Atlantic coast.

Advances in Mass Spectrometry-Based Blood Metabolomics Profiling for Non-Cancer Diseases: A Comprehensive Review.

Blood metabolomics profiling using mass spectrometry has emerged as a powerful approach for investigating non-cancer diseases and understanding their underlying metabolic alterations. Blood, as a readily accessible physiological fluid, contains a diverse repertoire of metabolites derived from various physiological systems. Mass spectrometry offers a universal and precise analytical platform for the comprehensive analysis of blood metabolites, encompassing proteins, lipids, peptides, glycans, and immunoglobulins. In this comprehensive review, we present an overview of the research landscape in mass spectrometry-based blood metabolomics profiling. While the field of metabolomics research is primarily focused on cancer, this review specifically highlights studies related to non-cancer diseases, aiming to bring attention to valuable research that often remains overshadowed. Employing natural language processing methods, we processed 507 articles to provide insights into the application of metabolomic studies for specific diseases and physiological systems. The review encompasses a wide range of non-cancer diseases, with emphasis on cardiovascular disease, reproductive disease, diabetes, inflammation, and immunodeficiency states. By analyzing blood samples, researchers gain valuable insights into the metabolic perturbations associated with these diseases, potentially leading to the identification of novel biomarkers and the development of personalized therapeutic approaches. Furthermore, we provide a comprehensive overview of various mass spectrometry approaches utilized in blood metabolomics research, including GC-MS, LC-MS, and others discussing their advantages and limitations. To enhance the scope, we propose including recent review articles supporting the applicability of GC×GC-MS for metabolomics-based studies. This addition will contribute to a more exhaustive understanding of the available analytical techniques. The Integration of mass spectrometry-based blood profiling into clinical practice holds promise for improving disease diagnosis, treatment monitoring, and patient outcomes. By unraveling the complex metabolic alterations associated with non-cancer diseases, researchers and healthcare professionals can pave the way for precision medicine and personalized therapeutic interventions. Continuous advancements in mass spectrometry technology and data analysis methods will further enhance the potential of blood metabolomics profiling in non-cancer diseases, facilitating its translation from the laboratory to routine clinical application.

Comprehensive Single-Platform Lipidomic/Metabolomic Analysis Using Supercritical Fluid Chromatography-Mass Spectrometry.

Supercritical fluid chromatography (SFC) is a rapidly expanding technique in the analysis of nonpolar to moderately polar substances and, more recently, also in the analysis of compounds with higher polarity. Herein, we demonstrate a proof of concept for the application of a commercial SFC instrument with electrospray ionization-mass spectrometry (MS) detection as a platform for the comprehensive analysis of metabolites with the full range of polarities, from nonpolar lipids up to highly polar metabolites. The developed single-platform SFC-MS lipidomic/metabolomic method is based on two consecutive injections of lipid and polar metabolite extracts from biphase methyl tert-butyl ether extraction using a diol column and two different gradient programs of methanol-water-ammonium formate modifier. Detailed development of the method focused mainly on the pressure limits of the system, the long-term repeatability of results, and the chromatographic performance, including optimization of the flow rate program, modifier composition and gradient, and injection solvent selection. The developed method enabled fast and comprehensive analysis of lipids and polar metabolites from plasma within a 24 min cycle with two injections using a simple analytical platform based on a single instrument, column, and mobile phase. Finally, the results from SFC-MS analysis of polar metabolites were compared with widely established liquid chromatography MS analysis in metabolomics. The comparison showed different separation selectivity of metabolites using both methods and overall lower sensitivity of the SFC-MS due to the higher flow rate and worse chromatographic performance.

Comparison between ammonium formate and ammonium fluoride in the analysis of stratum corneum lipids by reversed phase chromatography coupled with high resolution mass spectrometry

Lipids are key constituents of the barrier function in the human stratum corneum (SC), which is the outermost layer of the epidermis and amenable to non-invasive sampling by tape stripping. The three major lipid classes in the SC, i.e., ceramides, fatty acids, and cholesterol, present equimolar concentration. Liquid chromatography coupled with mass spectrometry (LCMS) is elective in profiling lipids in the SC in both positive and negative ion modes. Nevertheless, the latter one allows for the simultaneous detection of the three major epidermal components of the SC. Determination of ceramides in the SC poses analytical challenges due to their wide range of structures and concentrations especially in the case of limited sample amounts. Ammonium formate is a commonly used modifier added to the mobile phase to assist ionization. However, it introduces uncertainty in the identification of ceramides when operating in negative ion mode, even with high resolution MS. We tested the advantages of using fluoride in the lipid profiling of SC and unambiguous identification of ceramides subclasses. The use of fluoride enhanced the ionization of ceramides, regardless the specific substructure, solved misidentification issues, and was successfully applied to the simultaneous detection of all three lipid classes in the human SC.

ER Membrane Lipid Composition and Metabolism: Lipidomic Analysis.

Plant ER membranes are the major site of biosynthesis of several lipid families (phospholipids, sphingolipids, neutral lipids such as sterols and triacylglycerols). The structural diversity of lipids presents considerable challenges to comprehensive lipid analysis. This chapter will briefly review the various biosynthetic pathways and will detail several aspects of the lipid analysis: lipid extraction, handling, separation, detection, identification, and data presentation. The different tools/approaches used for lipid analysis will also be discussed in relation to the studies to be carried out on lipid metabolism and function.

Analysis of Lipids (Ⅱ)

Analysis of Lipids (Ⅱ)

Analysis of Lipids (Ⅲ)

Analysis of Lipids (Ⅲ)

Distribution, screening and biochemical characterization of indigenous microalgae for bio-mass and bio-energy production potential from three districts of Pakistan.

Trend of biofuel production from microalgal triacylglycerols is enhancing, because this substrate is a good sustainable and advantageous alternative to oil and gas fuel. In the present study, indigenous micro algal isolates were screened from water (n=30) and soil (n=30) samples collected from three districts of Punjab, Pakistan to evaluate their biofuel production potential. The samples were inoculated on BG - 11 agar medium plates by incubating at room temperature of 25°C providing 1000 lux for 16h light cycle followed by 8h of dark cycle for 15 d. Water samples were found to be rich in microalgae and 65.33% microalgae (49 isolates) were isolated from Faisalabad district. On the basis of microscopic morphology microalgal isolates (n=180) were selected and subjected to lipid detection by Nile red staining assay. Nile red positive isolates (n=23) were processed for biochemical (lipid, protein and carbohydrates) characterization. AIN63 isolate showed higher lipids (17.4%) content as detected by micro vanillin assay. Algal isolate AIN128 showed best protein contents (42.91%) detected by Bradford assay and AIN172 isolate showed higher carbohydrate contents (73.83%) as detected by anthrone assay. The selected algal isolates were also analyzed by Fourier transform infrared (FTIR) spectroscopy for confirmation of carbohydrate, protein and lipid analysis. These indigenous algae have the potential for in-vitro biofuel production from agricultural waste.

Липидный анализ слезной жидкости в диагностике дисфункции мейбомиевых желез

The tear film lipid layer plays a crucial role in maintaining ocular surface homeostasis by preventing excessive evaporation of the aqueous layer and reducing heat transfer from the corneal and conjunctival surface. The lipid composition of the tear film is unique and consists of two main layers: the outer (nonpolar lipids) and the inner (polar lipids). The thick outer layer of the tear film is composed of non-polar lipids that lack internal distributed charge, while the thin inner layer is formed by polar lipids with positive and negative charges at the ends of the molecule. Both types of lipids are synthesized in the meibomian glands (MG) and contribute to tear film stability. Meibomian gland dysfunction (MGD) alters the composition and physical properties of lipids, leading to pathological changes in both the MG and tear film. In meibomian gland dysfunction (MGD), the meibum thickens and acquires a higher melting point than normal. This leads to a decrease in the amount of nonpolar and amphiphilic lipids in the meibomian gland secretion and tear film. Consequently, the protective effect of the tear lipid layer is impaired, and its stability is compromised. Lipid mapping analyzes the lipid composition of biological samples, such as tear fluid, to study the mechanisms of the development and progression of various ocular surface diseases, including dry eye syndrome, MGD, and recurrent blepharoconjunctivitis. This method provides fundamental data on the properties of the tear film in various ocular surface diseases. It has the potential to establish hallmarks of disease course and develop personalized treatment approaches for specific clinical cases. KEYWORDS: tear, tear film lipids, ocular surface, meibomian gland dysfunction, lipid analysis. FOR CITATION: Takhauova L.R., Guseva A.A., Krylova A.A., Krivosheina O.I. Lipid analysis of tear fluid as a diagnostic tool for meibomian gland dysfunction. Russian Journal of Clinical Ophthalmology. 2024;24(2):83–87 (in Russ.). DOI: 10.32364/2311-7729-2024-24-2-7.

Analysis and Quantification of the Mitochondrial-ER Lipidome.

Mitochondria are vital organelles essential for cellular functions, but their lipid composition and response to stressors are not fully understood. Recent advancements in lipidomics reveal insights into lipid functions, especially their roles in metabolic perturbations and diseases. Previous methods have focused on the protein composition of mitochondria and mitochondrial-associated membranes. The advantage of our technique is that it combines organelle isolation with targeted lipidomics, offering new insights into the composition and dynamics of these organelles in pathological conditions. We developed a mitochondria isolation protocol for L6 myotubes, enabling lipidomics analysis of specific organelles without interference from other cellular compartments. This approach offers a unique opportunity to dissect lipid dynamics within mitochondria and their associated ER compartments under cellular stress. Key features • Analysis and quantification of lipids in mitochondria-ER fraction through liquid chromatography-tandem mass spectrometry-based lipidomics (LC-MS/MS lipidomics). • LC-MS/MS lipidomics provide precise and unbiased information on the lipid composition in in vitro systems. • LC-MS/MS lipidomics facilitates the identification of lipid signatures in mammalian cells.

Quantitative analysis of protein lipidation and acyl-CoAs reveals substrate preferences of the S-acylation machinery.

Protein palmitoylation or S-acylation has emerged as a key regulator of cellular processes. Increasing evidence shows that this modification is not restricted to palmitate but it can include additional fatty acids, raising the possibility that differential S-acylation contributes to the fine-tuning of protein activity. However, methods to profile the acyl moieties attached to proteins are scarce. Herein, we report a method for the identification and quantification of lipids bound to proteins that relies on hydroxylamine treatment and mass spectrometry analysis of fatty acid hydroxamates. This method has enabled unprecedented and extensive profiling of the S-acylome in different cell lines and tissues and has shed light on the substrate specificity of some S-acylating enzymes. Moreover, we could extend it to quantify also the acyl-CoAs, which are thioesters formed between a fatty acid and a coenzyme A, overcoming many of the previously described challenges for the detection of such species. Importantly, the simultaneous analysis of the lipid fraction and the proteome allowed us to establish, for the first time, a direct correlation between the endogenous levels of acyl-CoAs and the S-acylation profile of its proteome.

Deciphering biomolecular complexities: the indispensable role of surface-enhanced Raman spectroscopy in modern bioanalytical research.

Surface-enhanced Raman spectroscopy (SERS) has emerged as an indispensable analytical tool in biomolecular research, providing unmatched sensitivity critical for the elucidation of biomolecular structures. This review presents a thorough examination of SERS, outlining its fundamental principles, cataloging its varied applications within the biomolecular sphere, and contemplating its future developmental trajectories. We begin with a detailed analysis of SERS's mechanistic principles, emphasizing both the phenomena of surface enhancement and the complexities inherent in Raman scattering spectroscopy. Subsequently, we delve into the pivotal role of SERS in the structural analysis of diverse biomolecules, including proteins, nucleic acids, lipids, carbohydrates, and biochromes. The remarkable capabilities of SERS extend beyond mere detection, offering profound insights into biomolecular configurations and interactions, thereby enriching our comprehension of intricate biological processes. This review also sheds light on the application of SERS in real-time monitoring of various bio-relevant compounds, from enzymes and coenzymes to metal ion-chelate complexes and cellular organelles, thereby providing a holistic view and empowering researchers to unravel the complexities of biological systems. We also address the current challenges faced by SERS, such as enhancing sensitivity and resolution, developing stable and reproducible substrates, and conducting thorough analyses in complex biological matrices. Nonetheless, the continual advancements in nanotechnology and spectroscopy solidify the standing of SERS as a formidable force in biomolecular research. In conclusion, the versatility and robustness of SERS not only deepen our understanding of biomolecular intricacies but also pave the way for significant developments in medical research, therapeutic innovation, and diagnostic approaches.

Targeted Analysis of Permethylated N-Glycans Using MRM/PRM Approaches.

Targeted mass spectrometric analysis is widely employed across various omics fields as a validation strategy due to its high sensitivity and accuracy. The approach has been successfully employed for the structural analysis of proteins, glycans, lipids, and metabolites. Multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) have been the methods of choice for targeted structural studies of biomolecules. These target analyses simplify the analytical workflow, reduce background interference, and increase selectivity/specificity, allowing for a reliable quantification of permethylated N-glycans in complex biological matrices.