Development of a targeted hydrophilic interaction liquid chromatography-tandem mass spectrometry based lipidomics platform applied to a coronavirus disease severity study

Lipidomic profiling of triple-negative breast cancer cells reveals distinct metabolic signatures associated with EpCAM expression

Lipid metabolism is essential at all stages of cancer progression, particularly for triple-negative breast cancer (TNBC) the deadliest cancer subtype for women patients. TNBC cells exhibit significant metabolic heterogeneity, which contributes to their aggressive behavior. Epithelial-to-mesenchymal transition (EMT), a key step in metastasis, is associated with distinct lipid profiles, where the epithelial cell adhesion molecule (EpCAM) was found to be decreased along the transition. To understand this link, we employed lipidomic profiling of the TNBC cell line SUM149PT, which exhibits high variability in EpCAM, an epithelial marker. Using EpCAM levels to categorize cells with high and low EpCAM expression using fluorescence-activated cell sorter, we performed targeted mass spectrometry analysis of various lipid classes (glycerophospholipids, glycerolipids, lysophospholipids, and sphingolipids) by a hydrophilic interaction liquid chromatography-tandem mass spectrometry (HILIC-MS/MS)-based screening method. After correcting for cell size, we identified a unique lipid profile associated with each EpCAM expression level. Notably, cells with higher EpCAM expression displayed lower levels of lysophosphatidylethanolamine (LPE). This finding suggests a potential role for LPE in the regulation of EMT in TNBC.

From Complexity to Clarity: Expanding Metabolome Coverage With Innovative Analytical Strategies

Metabolomics, a powerful discipline within systems biology, aims at comprehensive profiling of small molecules in biological samples. The challenges of biological sample complexity are addressed through innovative sample preparation methods, including solid-phase extraction and microextraction techniques, enhancing the detection and quantification of low-abundance metabolites. Advances in chromatographic separation, particularly liquid chromatography (LC) and gas chromatography (GC), coupled with high-resolution (HR) mass spectrometry (MS), have significantly improved the sensitivity, selectivity, and throughput of metabolomic studies. Cutting-edge techniques, such as ion-mobility mass spectrometry (IM-MS) and tandem MS (MS/MS), further expand the capacity for comprehensive metabolite profiling. These advanced analytical platforms each offer unique advantages for metabolomics, with continued technological improvements driving deeper insights into metabolic pathways and biomarker discovery. By providing a detailed overview of current trends and techniques, this review aims to offer valuable insights into the future of metabolomics in human health research and its translational potential in clinical settings. Toward the end, this review also highlights the biomedical applications of metabolomics, emphasizing its role in biomarker discovery, disease diagnostics, personalized medicine, and drug development.

Development of a High-Throughput Platform for Quantitation of Histone Modifications on a New QTOF Instrument

Histone post-translational modifications (PTMs) regulate gene expression patterns through epigenetic mechanisms. The five histone proteins (H1, H2A, H2B, H3, and H4) are extensively modified, with over 75 distinct modification types spanning more than 200 sites. Despite strong advances in mass spectrometry (MS)-based approaches, identification and quantification of modified histone peptides remains challenging because of factors, such as isobaric peptides, pseudo-isobaric PTMs, and low stoichiometry of certain marks. Here, we describe the development of a new high-throughput method to identify and quantify over 150 modified histone peptides by LC-MS. Fast gradient microflow liquid chromatography and variable window sequential windows acquisition of all theoretical spectra data-independent acquisition on a new quadrupole time-of-flight platform is compared to a previous method using nanoflow LC-MS on an Orbitrap hybrid. Histones extracted from cells treated with either a histone deacetylase inhibitor or transforming growth factor-beta 1 were analyzed by data-independent acquisition on two mass spectrometers: an Orbitrap Exploris 240 with a 55-min nanoflow LC gradient and the SCIEX ZenoTOF 7600 with a 10-min microflow gradient. To demonstrate the reproducibility and speed advantage of the method, 100 consecutive injections of one sample were performed in less than 2 days on the quadrupole time-of-flight platform. The result is the comprehensive characterization of histone PTMs achieved in less than 20 min of total run time using only 200 ng of sample. Results for drug-treated histone samples are comparable to those produced by the previous method and can be achieved using less than one-third of the instrument time.

UHPLC-TIMS-PASEF®-MS for Lipidomics: From Theory to Practice

Trapped ion mobility spectrometry (TIMS) using parallel accumulation serial fragmentation (PASEF®) is an advanced analytical technique that offers several advantages in mass spectrometry (MS)-based lipidomics. TIMS provides an additional dimension of separation to mass spectrometry and accurate collision cross-section (CCS) measurements for ions, aiding in the structural characterization of molecules. This is especially valuable in lipidomics for identifying and distinguishing isomeric or structurally similar compounds. On the other hand, PASEF technology allows for fast and efficient data acquisition by accumulating ions in parallel and then serially fragmenting them. This accelerates the analysis process and improves throughput, making it suitable for high-throughput applications. Moreover, the combination of TIMS and PASEF reduces co-elution and ion coalescence issues, leading to cleaner and more interpretable mass spectra. This results in higher data quality and more confident identifications. In this chapter, a data-dependent TIMS-PASEF® workflow for lipidomics analysis is presented.

Advancements in Mass Spectrometry-Based Targeted Metabolomics and Lipidomics: Implications for Clinical Research

Targeted metabolomics and lipidomics are increasingly utilized in clinical research, providing quantitative and comprehensive assessments of metabolic profiles that underlie physiological and pathological mechanisms. These approaches enable the identification of critical metabolites and metabolic alterations essential for accurate diagnosis and precision treatment. Mass spectrometry, in combination with various separation techniques, offers a highly sensitive and specific platform for implementing targeted metabolomics and lipidomics in clinical settings. Nevertheless, challenges persist in areas such as sample collection, quantification, quality control, and data interpretation. This review summarizes recent advances in targeted metabolomics and lipidomics, emphasizing their applications in clinical research. Advancements, including microsampling, dynamic multiple reaction monitoring, and integration of ion mobility mass spectrometry, are highlighted. Additionally, the review discusses the critical importance of data standardization and harmonization for successful clinical implementation.

Detailed lipid investigation of edible seaweeds by photochemical derivatization and untargeted lipidomics

Seaweeds are macrophytic algae that have been gaining interest as alternative healthy foods, renewable drug sources, and climate change mitigation agents. In terms of their nutritional value, seaweeds are renowned for their high content of biologically active polyunsaturated fatty acids. However, little is known about the regiochemistry-the geometry and position of carbon-carbon double bonds-of free and conjugated fatty acids in seaweeds. In the present work, a detailed characterization of the seaweed lipidome was achieved based on untargeted HRMS-based analysis and lipid derivatization with a photochemical aza-Paternò-Büchi reaction. A triple-data processing strategy was carried out to achieve high structural detail on the seaweed lipidome, i.e., (i) a first data processing workflow with all samples for aligning peak and statistical analysis that led to the definition of lipid sum compositions (e.g., phosphatidylglycerol (PG) 34:1), (ii) a second data processing workflow in which the samples of each seaweed were processed separately to annotate molecular lipids with known fatty acyl isomerism (e.g., PG 16:0_18:1), and (iii) the annotation of lipid regioisomers following MS/MS annotation of the lipid derivatives obtained following the aza-Paternò-Büchi reaction (e.g., PG 16:0_18:1 ω-9). Once the platform was set up, the lipid extracts from 8 seaweed species from different seaweed families were characterized, describing over 900 different lipid species, and information on the regiochemistry of carbon-carbon double bonds uncovered unknown peculiarities of seaweeds belonging to different families. The overall analytical approach helped to fill a gap in the knowledge of the nutritional composition of seaweeds.

A comparison between different human hepatocyte models reveals profound differences in net glucose production, lipid composition and metabolism in vitro

Hepatocytes are responsible for maintaining a stable blood glucose concentration during periods of nutrient scarcity. The breakdown of glycogen and de novo synthesis of glucose are crucial metabolic pathways deeply interlinked with lipid metabolism. Alterations in these pathways are often associated with metabolic diseases with serious clinical implications. Studying energy metabolism in human cells is challenging. Primary hepatocytes are still considered the golden standard for in vitro studies and have been instrumental in elucidating key aspects of energy metabolism found in vivo. As a result of several limitations posed by using primary cells, a multitude of alternative hepatocyte cellular models emerged as potential substitutes. Yet, there remains a lack of clarity regarding the precise applications for which these models accurately reflect the metabolic competence of primary hepatocytes. In this study, we compared primary hepatocytes, stem cell-derived hepatocytes, adult donor-derived liver organoids, immortalized Upcyte-hepatocytes and the hepatoma cell line HepG2s in their response to a glucose production challenge. We observed the highest net glucose production in primary hepatocytes, followed by organoids, stem-cell derived hepatocytes, Upcyte-hepatocytes and HepG2s. Glucogenic gene induction was observed in all tested models, as indicated by an increase in G6PC and PCK1 expression. Lipidomic analysis revealed considerable differences across the models, with organoids showing the closest similarity to primary hepatocytes in the common lipidome, comprising 347 lipid species across 19 classes. Changes in lipid profiles as a result of the glucose production challenge showed a variety of, and in some cases opposite, trends when compared to primary hepatocytes.

Comprehensive analysis of phospholipid in milk and their biological roles as nutrients and biomarkers

Phospholipids (PL) have garnered significant attention due to their physiological activities. Milk and other dairy products are important dietary sources for humans and have been extensively used to analyze the presence of PL by various analytical techniques. In this paper, the analysis techniques of PL were reviewed with the eight trigrams of phospholipidomics and a comprehensive fingerprint of 1295 PLs covering 8 subclasses in milk and other dairy products, especially. Technology is the primary productive force. Based on phospholipidomics technology, we further review the relationship between the composition of PL and factors that may be involved in processing and experimental operation, and emphasized the significance of the biological role played by PL in dietary supplements and biomarkers (production, processing and clinical research), and providing the future research directions.

The potential role of dyslipidemia in COVID-19 severity among Iraqi patients

BACKGROUND

The correlation between dyslipidemia and the severity of coronavirus disease 2019 has been widely categorized. Dyslipidemia is one of the most dominant disorders among these patients. Systemic inflammation accompanied by cytokine storm hemostasis modifications and severe vasculitis have all been reported to occur among COVID-19 patients, and these may contribute to some severe complications.

OBJECTIVE

The aim of this study is to assess the possible relationship between dyslipidemia and the severity of coronavirus disease 2019.

METHODS

This work encompassed 200 patients with coronavirus disease 2019 (100 dyslipidemic and 100 normolipidemic) who were hospitalized at Baghdad Teaching Hospital/ Medical City-Baghdad, Iraq, from October 2021 to October 2022; their ages ranged between 40 and 55. Eligible individuals had a positive nasal swab polymerase chain reaction for severe acute respiratory syndrome coronavirus 2 infection. Every participant's anthropometric and clinical features were measured. The study includes the measurements of glycemic, lipid profile, renal function test, D-dimer, C-reactive protein, serum ferritin, and interleukin-6 in dyslipidemic and normolipidemic groups.

RESULTS

Considerable increase (p= 0.001) in glycemic and lipid levels in the dyslipidemic group compared to normolipidemic. Moreover, dyslipidemic patients have higher lipid indices (ratios) than the normolipidemic group. Significant increases (p= 0.001) in serum urea and creatinine levels were found among the dyslipidemic group compared to normolipidemic. There was a non-considerable decrease (p= 0.062) in serum total protein in the dyslipidemic group concerning the normolipidemic. In contrast, a considerable decrease (p= 0.045) in serum albumin was detected in the dyslipidemic group compared to normolipidemic. D-dimer, serum C-reactive protein, ferritin, and interleukin-6 were significantly increased (p= 0.001) in the dyslipidemic group compared to normolipidemic.

CONCLUSION

Dyslipidemia potentially raises the severity of coronavirus disease 2019. There was a significant disturbance in renal function tests among coronavirus disease 2019 patients. The study found a significant and statistical difference in kidney functions between dyslipidemic and normolipidemic groups. The patients, especially the dyslipidemic ones, have experienced protein abnormalities and a significant inflammation rate reflected by higher C-reactive protein and interleukin-6, which is due to the severity of coronavirus disease 2019. It is possible to conduct more research with a larger sample size. The majority of people who have dyslipidemia need to be enlightened.