Lipidomics: Techniques, Applications, and Outcomes Related to Biomedical Sciences

Lipidomics of Environmental Microbial Communities. II: Characterization Using Molecular Networking and Information Theory

Structurally diverse, specialized lipids are crucial components of microbial membranes and other organelles and play essential roles in ecological functioning. The detection of such lipids in the environment can reveal not only the occurrence of specific microbes but also the physicochemical conditions to which they are adapted to. Traditionally, liquid chromatography coupled with mass spectrometry allowed for the detection of lipids based on chromatographic separation and individual peak identification, resulting in a limited data acquisition and targeting of certain lipid groups. Here, we explored a comprehensive profiling of microbial lipids throughout the water column of a marine euxinic basin (Black Sea) using ultra high-pressure liquid chromatography coupled with high-resolution tandem mass spectrometry (UHPLC-HRMS/MS). An information theory framework combined with molecular networking based on the similarity of the mass spectra of lipids enabled us to capture lipidomic diversity and specificity in the environment, identify novel lipids, differentiate microbial sources within a lipid group, and discover potential biomarkers for biogeochemical processes. The workflow presented here allows microbial ecologists and biogeochemists to process quickly and efficiently vast amounts of lipidome data to understand microbial lipids characteristics in ecosystems.

Pharmacodynamic substances in Salvia miltiorrhiza for prevention and treatment of hyperlipidemia and coronary heart disease based on lipidomics technology and network pharmacology analysis

In this study, untargeted lipidomics based on UPLC-Q/TOF-MS, network pharmacology and atomic force microscopy were used to explore the common biomarkers of hyperlipidemia and coronary heart disease, the therapeutic mechanism of the main components of Salvia miltiorrhiza as well as the action mechanism of key lipids. Firstly, the serum samples of 30 healthy people, 30 patients with coronary heart disease and 30 patients with hyperlipidemia were analyzed by using lipidomics technology to obtain biomarkers which can be used to link hyperlipidemia and coronary heart disease and to find potential targets; then, the key components and core targets of Salvia miltiorrhiza intervention in hyperlipidemia and coronary heart disease were analyzed by network pharmacology, the results were verified by atomic force microscopy. It showed that SMS2 might be the key target. And through network pharmacology and atomic force microscope analysis, it can be inferred that salvianolic acid A can combine with SMS2 to play a therapeutic role.

A generalized kernel machine approach to identify higher-order composite effects in multi-view datasets, with application to adolescent brain development and osteoporosis

In recent years, a comprehensive study of complex disease with multi-view datasets (e.g., multi-omics and imaging scans) has been a focus and forefront in biomedical research. State-of-the-art biomedical technologies are enabling us to collect multi-view biomedical datasets for the study of complex diseases. While all the views of data tend to explore complementary information of disease, analysis of multi-view data with complex interactions is challenging for a deeper and holistic understanding of biological systems. In this paper, we propose a novel generalized kernel machine approach to identify higher-order composite effects in multi-view biomedical datasets (GKMAHCE). This generalized semi-parametric (a mixed-effect linear model) approach includes the marginal and joint Hadamard product of features from different views of data. The proposed kernel machine approach considers multi-view data as predictor variables to allow a more thorough and comprehensive modeling of a complex trait. We applied GKMAHCE approach to both synthesized datasets and real multi-view datasets from adolescent brain development and osteoporosis study. Our experiments demonstrate that the proposed method can effectively identify higher-order composite effects and suggest that corresponding features (genes, region of interests, and chemical taxonomies) function in a concerted effort. We show that the proposed method is more generalizable than existing ones. To promote reproducible research, the source code of the proposed method is available at.

Using machine learning approaches for multi-omics data analysis: A review

With the development of modern high-throughput omic measurement platforms, it has become essential for biomedical studies to undertake an integrative (combined) approach to fully utilise these data to gain insights into biological systems. Data from various omics sources such as genetics, proteomics, and metabolomics can be integrated to unravel the intricate working of systems biology using machine learning-based predictive algorithms. Machine learning methods offer novel techniques to integrate and analyse the various omics data enabling the discovery of new biomarkers. These biomarkers have the potential to help in accurate disease prediction, patient stratification and delivery of precision medicine. This review paper explores different integrative machine learning methods which have been used to provide an in-depth understanding of biological systems during normal physiological functioning and in the presence of a disease. It provides insight and recommendations for interdisciplinary professionals who envisage employing machine learning skills in multi-omics studies.

Isomer Selective Comprehensive Lipidomics Analysis of Phosphoinositides in Biological Samples by Liquid Chromatography with Data Independent Acquisition Tandem Mass Spectrometry

Phosphoinositides (PIPx) play central roles in membrane dynamics and signal transduction of key functions like cellular growth, proliferation, differentiation, migration, and adhesion. They are highly regulated through a network of distinct phosphatidylinositol phosphates consisting of seven groups and three regioisomers in two groups (PIP and PIP2), which arise from phosphorylation at 3', 4', and 5' positions of the inositol ring. Numerous studies have revealed the importance of both fatty acyl chains, degree of phosphorylation, and phosphorylation positions under physiological and pathological states. However, a comprehensive analytical method that allows differentiation of all regioisomeric forms with different acyl side chains and degrees of phosphorylation is still lacking. Here, we present an integrated comprehensive workflow of PIPx analysis utilizing a chiral polysaccharide stationary phase coupled with electrospray ionization high-resolution mass spectrometry with a data independent acquisition technique using the SWATH technology. Correspondingly, a targeted data mining strategy in the untargeted comprehensively acquired MS and MS/MS data was developed. This powerful highly selective method gives a full picture of PIPx profiles in biological samples. Herein, we present for the first time the full PIPx profiles of NIST SRM1950 plasma, Pichia pastoris lipid extract, and HeLa cell extract, including profile changes upon treatment with potential PI3K inhibitor wortmannin. We also illustrate using this inhibitor that measurements of the PIPx profile averaged over the distinct regioisomers by analytical procedures, which cannot differentiate between the individual PIPx isomers, can easily lead to biased conclusions.

An overview of lipidomics utilizing cadaver derived biological samples

INTRODUCTION

We present lipidomic studies that have utilized cadaveric biological samples, including tissues and bodily fluids (excluding blood or serum). Analyses of lipids from cadaveric-derived tissues play vital roles in many different fields, such as in anthropogeny to understand food habits of ancient people, in forensics for postmortem analyses, and in biomedical research to study human diseases.

AREAS COVERED

The goal of the review is to demonstrate how cadavers can be utilized for study of lipidome to get biological insight in different fields. Several important considerations need to be made when analyzing lipids from cadaver samples. For example, what important postmortem changes occur due to environmental or other intrinsic factors that introduce deviations in the observed differences versus true differences? Do these factors affect distinct classes of lipids differently? How do we arrive at a reasonable level of certainty that the observed differences are truly biological rather than artifacts of sample collection, changes during transportation, or variations in analytical procedures? These are pressing questions that need to be addressed when performing lipidomics investigations utilizing postmortem tissues, which inherently presents hurdles and unknowns beginning with harvesting methods, transportation logistics, and at analytical techniques. In our review, we have purposefully omitted blood and serum studies since they pose greater challenges in this regard. Several studies have been carried out with cadaveric tissues and fluids that support the successful use of cases of these samples; however, many control studies are still necessary to provide insight into full potential of the cadaveric tissue and fluid resources. Most importantly, additional control studies will allow us to gain important insights into the opportunities lipidomics presents for biomedical studies of complex human disease and disorders. Another goal of the review is to generate awareness about limitations and pitfalls of use of cadaver materials for study of lipidome.

EXPERT OPINION

We comment on the current state of lipidomics studies that utilize cadaveric tissues, provide a few pertinent examples, and discuss perspectives on both future technological directions and the applications they will enable.

Complex Alterations of Fatty Acid Metabolism and Phospholipidome Uncovered in Isolated Colon Cancer Epithelial Cells

The development of colon cancer, one of the most common malignancies, is accompanied with numerous lipid alterations. However, analyses of whole tumor samples may not always provide an accurate description of specific changes occurring directly in tumor epithelial cells. Here, we analyzed in detail the phospholipid (PL), lysophospholipid (lysoPL), and fatty acid (FA) profiles of purified EpCAM⁺ cells, isolated from tumor and adjacent non-tumor tissues of colon cancer patients. We found that a number of FAs increased significantly in isolated tumor cells, which also included a number of long polyunsaturated FAs. Higher levels of FAs were associated with increased expression of FA synthesis genes, as well as with altered expression of enzymes involved in FA elongation and desaturation, including particularly fatty acid synthase, stearoyl-CoA desaturase, fatty acid desaturase 2 and ELOVL5 fatty acid elongase 5 We identified significant changes in ratios of specific lysoPLs and corresponding PLs. A number of lysophosphatidylcholine and lysophosphatidylethanolamine species, containing long-chain and very-long chain FAs, often with high numbers of double bonds, were significantly upregulated in tumor cells. Increased de novo synthesis of very long-chain FAs, or, altered uptake or incorporation of these FAs into specific lysoPLs in tumor cells, may thus contribute to reprogramming of cellular phospholipidome and membrane alterations observed in colon cancer.

Mapping the distribution of double bond location isomers in lipids across mouse tissues

Lipids are highly diverse and essential biomolecules in all living systems. As lipid homeostasis is often perturbed in metabolic diseases, these molecules can serve as both biomarkers and drug targets. The development of modern mass spectrometry (MS) provided the platform for large-scale lipidomic studies at the level of molecular species. Traditionally, more detailed structural information, such as the C[double bond, length as m-dash]C location, was mostly assumed instead of properly measured, though the specific isomers were indicated as potential biomarkers of cancers or cardiovascular diseases. Recent C[double bond, length as m-dash]C localization methods, including the Paternò-Büchi (PB) reaction, have shown the prevalent and heterogeneous distribution of C[double bond, length as m-dash]C location in lipids across tissues. Mapping the lipidome of model animals at the level of C[double bond, length as m-dash]C position would increase the understanding of the metabolism and function of lipid isomers, facilitating clinical research. In this study, we employed an online PB reaction on a liquid chromatography-high resolution MS platform to map C[double bond, length as m-dash]C location isomers in five different murine tissues. We analyzed phosphatidylcholines, phosphatidylethanolamines, and sphingomyelins; we relatively quantified and mapped the distribution of ∼30 groups of co-existing isomers, characterized by different chain lengths and degrees of unsaturation. More specifically, we performed relative quantitation of four isomers of the C16:1 fatty acyl, which included rarely reported n-10 and n-5 species besides n-9 and n-7 isomers. We showed a small variation of the isomers' relative composition among individual animals (<20%) but significant differences across different lipid species and mouse tissues. Our results provided an initial database to map alternative lipid metabolic pathways at the tissue level.

Untargeted Lipidomics for Determining Cellular and Subcellular Responses in Zebrafish (Danio rerio) Liver Cells Following Exposure to Complex Mixtures in U.S. Streams

Surface waters often contain a variety of chemical contaminants potentially capable of producing adverse outcomes in both humans and wildlife due to impacts from industrial, urban, and agricultural activity. Here, we report the results of a zebrafish liver (ZFL) cell-based lipidomics approach to assess the potential ecotoxicological effects of complex contaminant mixtures using water collected from eight impacted streams across the United States mainland and Puerto Rico. We initially characterized the ZFL lipidome using high resolution mass spectrometry, resulting in the annotation of 508 lipid species covering 27 classes. We then identified lipid changes induced by all streamwater samples (nonspecific stress indicators) as well as those unique to water samples taken from specific streams. Subcellular impacts were classified based on organelle-specific lipid changes, including increased lipid saturation (endoplasmic reticulum stress), elevated bis(monoacylglycero)phosphate (lysosomal overload), decreased ubiquinone (mitochondrial dysfunction), and elevated ether lipids (peroxisomal stress). Finally, we demonstrate how these results can uniquely inform environmental monitoring and risk assessments of surface waters.

Extending the Lipidome Coverage by Combining Different Mass Spectrometric Platforms: An Innovative Strategy to Answer Chemical Food Safety Issues

From a general public health perspective, a strategy combining non-targeted and targeted lipidomics MS-based approaches is proposed to identify disrupted patterns in serum lipidome upon growth promoter treatment in pigs. Evaluating the relative contributions of the platforms involved, the study aims at investigating the potential of innovative analytical approaches to highlight potential chemical food safety threats. Serum samples collected during an animal experiment involving control and treated pigs, whose food had been supplemented with ractopamine, were extracted and characterised using three MS strategies: Non-targeted RP LC-HRMS; the targeted Lipidyzer™ platform (differential ion mobility associated with shotgun lipidomics) and a homemade LC-HRMS triglyceride platform. The strategy enabled highlighting specific lipid profile patterns involving various lipid classes, mainly in relation to cholesterol esters, sphingomyelins, lactosylceramide, phosphatidylcholines and triglycerides. Thanks to the combination of non-targeted and targeted MS approaches, various compartments of the pig serum lipidome could be explored, including commonly characterised lipids (Lipidyzer™), triglyceride isomers (Triglyceride platform) and unique lipid features (non-targeted LC-HRMS). Thanks to their respective characteristics, the complementarity of the three tools could be demonstrated for public health purposes, with enhanced coverage, level of characterization and applicability.

Multi-Omics Model Applied to Cancer Genetics

In this review, we focus on bioinformatic oncology as an integrative discipline that incorporates knowledge from the mathematical, physical, and computational fields to further the biomedical understanding of cancer. Before providing a deeper insight into the bioinformatics approach and utilities involved in oncology, we must understand what is a system biology framework and the genetic connection, because of the high heterogenicity of the backgrounds of people approaching precision medicine. In fact, it is essential to providing general theoretical information on genomics, epigenomics, and transcriptomics to understand the phases of multi-omics approach. We consider how to create a multi-omics model. In the last section, we describe the new frontiers and future perspectives of this field.

The Heterogeneity of Lipid Metabolism in Cancer

The study of cancer cell metabolism has traditionally focused on glycolysis and glutaminolysis. However, lipidomic technologies have matured considerably over the last decade and broadened our understanding of how lipid metabolism is relevant to cancer biology [1-3]. Studies now suggest that the reprogramming of cellular lipid metabolism contributes directly to malignant transformation and progression [4, 5]. For example, de novo lipid synthesis can supply proliferating tumor cells with phospholipid components that comprise the plasma and organelle membranes of new daughter cells [6, 7]. Moreover, the upregulation of mitochondrial β-oxidation can support tumor cell energetics and redox homeostasis [8], while lipid-derived messengers can regulate major signaling pathways or coordinate immunosuppressive mechanisms [9-11]. Lipid metabolism has, therefore, become implicated in a variety of oncogenic processes, including metastatic colonization, drug resistance, and cell differentiation [10, 12-16]. However, whether we can safely and effectively modulate the underlying mechanisms of lipid metabolism for cancer therapy is still an open question.

In vitro generation of oxidized standards for lipidomics. Application to major membrane lipid components

Membrane lipids (sphingolipids, glycerophospholipids, cardiolipins, and cholesteryl esters) are critical in cellular functions. Alterations in the levels of oxidized counterparts of some of these lipids have been linked to the onset and development of many pathologies. Unfortunately, the scarce commercial availability of chemically defined oxidized lipids is a limitation for accurate quantitative analysis, characterization of oxidized composition, or testing their biological effects in lipidomic studies. To address this dearth of standards, several approaches rely on in-house prepared mixtures of oxidized species generated under in vitro conditions from different sources - non-oxidized commercial standards, liposomes, micelles, cells, yeasts, and human preparations - and using different oxidant systems - UVA radiation, air exposure, enzymatic or chemical oxidant systems, among others. Moreover, high-throughput analytical techniques such as liquid chromatography coupled to mass spectrometry (LC-MS) have provided evidence of their capabilities to study oxidized lipids both in in vitro models and complex biological samples. In this review, we describe the commercial resources currently available, the in vitro strategies carried out for obtaining oxidized lipids as standards for LC-MS analysis, and their applications in lipidomics studies, specifically for lipids found in cell and mitochondria membranes.

Mass spectrometry in the lipid study of cancer

Introduction: Cancer is a heterogeneous disease that exploits various metabolic pathways to meet the demand for increased energy and structural components. Lipids are biomolecules that play essential roles as high energy sources, mediators, and structural components of biological membranes. Accumulating evidence has established that altered lipid metabolism is a hallmark of cancer.Areas covered: Mass spectrometry (MS) is a label-free analytical tool that can simultaneously identify and quantify hundreds of analytes. To date, comprehensive lipid studies exclusively rely on this technique. Here, we reviewed the use of MS in the study of lipids in various cancers and discuss its instrumental limitations and challenges.Expert opinion: MS and MS imaging have significantly contributed to revealing altered lipid metabolism in a variety of cancers. Currently, a single MS approach cannot profile the entire lipidome because of its lack of sensitivity and specificity for all lipid classes. For the metabolic pathway investigation, lipid study requires the integration of MS with other molecular approaches. Future developments regarding the high spatial resolution, mass resolution, and sensitivity of MS instruments are warranted.

Lipidomics reveals that acupuncture modulates the lipid metabolism and inflammatory interaction in a mouse model of depression

Depression is a serious disease that has considerable impact on lipid metabolism and inflammatory responses. Recent studies have shown that leptin, which is well known as a mediator of energy homeostasis and is a cytokine in inflammatory response, plays an important role in depression. Acupuncture is widely used to treat depression; however, the underlying mechanisms and the effect of acupuncture on depression remain poorly understood. In this study, we utilized the chronic restraint stress (CRS) induced depression model and acupuncture treatment was performed at KI10, LR8, LU8, LR4 (AP) or non-acupoint (NP). Then, lipidomics was applied to investigate the effects of acupuncture on lipid metabolism and analyze leptin signals in the brain and changes of immune markers. Acupuncture treatment at AP improved depression-like behavior in an open-field test, forced swimming test, and marble burying test. Concurrently, CRS mice treated with AP acupuncture (CRS + AP) had significantly lower levels of aspartate aminotransaminase (AST, liver injury markers) and exhibited different lipid patterns in liver lipidomic profiles. In particular, triglycerides (TGs) contributed the change of lipid patterns. Compared to the CRS mice, TGs with relatively high degrees of unsaturated fatty acids increased in the CRS + AP mice, but did not change in CRS mice treated with NP acupuncture (CRS + NP). The levels of leptin in plasma and leptin receptor positive cells in the brain (hypothalamus and hippocampus) decreased and increased, respectively, in the CRS + AP mice, while opposite patterns were exhibited in the CRS and CRS + NP mice. These results indicated that acupuncture treatment at AP attenuated leptin insensitivity in CRS mice. Additionally, expression of pro-inflammatory cytokines such as interleukin-1 beta and tumor necrosis factor-alpha were decreased in the spleen, plasma, and liver of CRS + AP mice, which was one of results of alleviation of leptin resistance. In conclusion, these results show that AP acupuncture treatment effectively alleviated the depression-like behavior, affected immune responses, and altered hepatic lipid metabolism through the attenuation of leptin insensitivity.

Metabolic View on Human Healthspan: A Lipidome-Wide Association Study

As ageing is a major risk factor for the development of non-communicable diseases, extending healthspan has become a medical and societal necessity. Precise lipid phenotyping that captures metabolic individuality could support healthspan extension strategies. This study applied ‘omic-scale lipid profiling to characterise sex-specific age-related differences in the serum lipidome composition of healthy humans. A subset of the COmPLETE-Health study, composed of 73 young (25.2 ± 2.6 years, 43% female) and 77 aged (73.5 ± 2.3 years, 48% female) clinically healthy individuals, was investigated, using an untargeted liquid chromatography high-resolution mass spectrometry approach. Compared to their younger counterparts, aged females and males exhibited significant higher levels in 138 and 107 lipid species representing 15 and 13 distinct subclasses, respectively. Percentage of difference ranged from 5.8% to 61.7% (females) and from 5.3% to 46.0% (males), with sphingolipid and glycerophophospholipid species displaying the greatest amplitudes. Remarkably, specific sphingolipid and glycerophospholipid species, previously described as cardiometabolically favourable, were found elevated in aged individuals. Furthermore, specific ether-glycerophospholipid and lyso-glycerophosphocholine species displayed higher levels in aged females only, revealing a more favourable lipidome evolution in females. Altogether, age determined the circulating lipidome composition, while lipid species analysis revealed additional findings that were not observed at the subclass level.

Untargeted metabolomics and lipidomics uncovering the cardioprotective effects of Huanglian Jiedu Decoction on pathological cardiac hypertrophy and remodeling

ETHNOPHARMACOLOGICAL RELEVANCE

As a classic herbal prescription, Huanglian Jiedu Decoction (HLJDD) exhibits positive effects against cardiac dysfunction. However, its cardioprotective effects and potential mechanism(s) of action still need to be systematically investigated.

AIM OF THE STUDY

This study aimed to reveal the underlying therapeutic mechanism of HLJDD on transverse aortic constriction (TAC)-induced pathological cardiac hypertrophy and remodeling.

MATERIALS AND METHODS

TAC-induced cardiac hypertrophy and remodeling mice model was established to evaluate the therapeutic effects of HLJDD. Serum untargeted metabolomics and lipidomic profiling were performed using ultra-performance liquid chromatography quadrupole-time-of-flight mass spectrometry coupled with multivariate statistical analyses.

RESULTS

Oral administration of HLJDD (2.5 g/kg/day, 5.0 g/kg/day) significantly improved the heart morphology, enhanced the heart function, and alleviated the accumulation of fibrosis in the interstitial space and the infiltration of inflammatory cells in TAC-stimulated mice. Serum untargeted metabolomics analysis showed that significant alterations were observed in metabolic signatures between the TAC-model and sham group. Principal component analysis and orthogonal partial least-squares discriminant analysis screened 59 differential metabolic features and 13 metabolites were identified. The disturbed metabolic pathways in TAC group mainly related to lipid metabolism. Further serum lipidomic profiling showed that most lipids including cholesterol esters, ceramides, glycerides, fatty acids and phospholipids were decreased in TAC group and these alterations were reversed after HLJDD intervention.

CONCLUSION

HLJDD alleviates TAC-induced pathological cardiac hypertrophy and remodeling, and its potential therapeutic mechanism involves the regulation of lipid metabolism.

UPLC-Q-TOF/MS based Untargeted Metabolite and Lipid Analysis on Premature Ovarian Insufficiency Plasma Samples

Background:

Metabolomics is one of the main areas to understand cellular process at molecular level by analyzing metabolites. In recent years metabolomics has emerged as a key tool to understand molecular basis of diseases, to find diagnostic and prognostic biomarkers and develop new treatment opportunities and drug molecules.

Objective:

In this study, untargeted metabolite and lipid analysis were performed to identify potential biomarkers on premature ovarian insufficiency plasma samples. 43 POI subject plasma samples were compared with 32 healthy subject plasma samples.

Methods:

Plasma samples were pooled and extracted using chloroform:methanol:water (3:3:1 v/v/v) mixture. Agilent 6530 LC/MS Q-TOF instrument equipped with ESI source was used for analysis. A C18 column (Agilent Zorbax 1.8 μM, 50 x 2.1 mm) was used for separation of the metabolites and lipids. XCMS, an “R software” based freeware program, was used for peak picking, grouping and comparing the findings. Isotopologue Parameter Optimization (IPO) software was used to optimize XCMS parameters. The analytical methodology and data mining process were validated according to the literature.

Results:

83 metabolite peaks and 213 lipid peaks were found to be in semi-quantitatively and statistically different (fold change >1.5, p <0.05) between the POI plasma samples and control subjects.

Conclusion:

According to the results, two groups were successfully separated through principal component analysis. Among the peaks, phenyl alanine, decanoyl-L-carnitine, 1-palmitoyl lysophosphatidylcholine and PC(O-16:0/2:0) were identified through auto MS/MS and matched with human metabolome database and proposed as plasma biomarker for POI and monitoring the patients in treatment period.

Brain lipidomics as a rising field in neurodegenerative contexts: Perspectives with Machine Learning approaches

Lipids are essential for cellular functioning considering their role in membrane composition, signaling, and energy metabolism. The brain is the second most abundant organ in terms of lipid concentration and diversity only after adipose tissue. However, in the central system (CNS) lipid dysregulation has been linked to the etiology, progression, and severity of neurodegenerative diseases such as Alzheimeŕs, Parkinson, and Multiple Sclerosis. Advances in the human genome and subsequent sequencing technologies allowed us the study of lipidomics as a promising approach to diagnosis and treatment of neurodegeneration. Lipidomics advances rapidly increased the amount and quality of data allowing the integration with other omic types as well as implementing novel bioinformatic and quantitative tools such as machine learning (ML). Integration of lipidomics data with ML, as a powerful quantitative predictive approach, led to improvements in diagnostic biomarker prediction, clinical data integration, network, and systems approaches for neural behavior, novel etiology markers for inflammation, and neurodegeneration progression and even Mass Spectrometry image analysis. In this sense, by exploiting lipidomics data with ML is possible to improve the identification of new biomarkers or unveil new molecular mechanisms associated with lipid impairment across neurodegeneration. In this review, we present the lipidomic neurobiology state-of-the-art highlighting its potential applications to study neurodegenerative conditions. Also, we present theoretical background, applications, and advances in the integration of lipidomics with ML. This review opens the door to new approaches in this rising field.

Changes in the lipidome in type 1 diabetes following low carbohydrate diet: Post-hoc analysis of a randomized crossover trial

Aims

Lipid metabolism might be compromised in type 1 diabetes, and the understanding of lipid physiology is critically important. This study aimed to compare the change in plasma lipid concentrations during carbohydrate dietary changes in individuals with type 1 diabetes and identify links to early-stage dyslipidaemia. We hypothesized that (1) the lipidomic profiles after ingesting low or high carbohydrate diet for 12 weeks would be different; and (2) specific annotated lipid species could have significant associations with metabolic outcomes.

Methods

Ten adults with type 1 diabetes (mean ± SD: age 43.6 ± 13.8 years, diabetes duration 24.5 ± 13.4 years, BMI 24.9 ± 2.1 kg/m2, HbA1c 57.6 ± 2.6 mmol/mol) using insulin pumps participated in a randomized 2-period crossover study with a 12-week intervention period of low carbohydrate diet (< 100 g carbohydrates/day) or high carbohydrate diet (> 250 g carbohydrates/day), respectively, separated by a 12-week washout period. A large-scale non-targeted lipidomics was performed with mass spectrometry in fasting plasma samples obtained before and after each diet intervention. Longitudinal lipid levels were analysed using linear mixed-effects models.

Results

In total, 289 lipid species were identified from 14 major lipid classes. Comparing the two diets, 11 lipid species belonging to sphingomyelins, phosphatidylcholines and LPC(O-16:0) were changed. All the 11 lipid species were significantly elevated during low carbohydrate diet. Two lipid species were most differentiated between diets, namely SM(d36:1) (β ± SE: 1.44 ± 0.28, FDR = 0.010) and PC(P-36:4)/PC(O-36:5) (β ± SE: 1.34 ± 0.25, FDR = 0.009) species. Polyunsaturated PC(35:4) was inversely associated with BMI and positively associated with HDL cholesterol (p < .001).

Conclusion

Lipidome-wide outcome analysis of a randomized crossover trial of individuals with type 1 diabetes following a low carbohydrate diet showed an increase in sphingomyelins and phosphatidylcholines which are thought to reduce dyslipidaemia. The polyunsaturated phosphatidylcholine 35:4 was inversely associated with BMI and positively associated with HDL cholesterol (p < .001). Results from this study warrant for more investigation on the long-term effect of single lipid species in type 1 diabetes.

Application of omics technologies in dermatological research and skin management

BACKGROUND

"Omics" are usually based on the use of high-throughput analysis methods for global analysis of biological samples and the discovery of biomarkers, and may provide new insights into biological phenomena. Over the last few years, the development of omics technologies has considerably accelerated the pace of dermatological research.

AIMS

The purpose of this article was to review the development of omics in recent decades and their application in dermatological research.

METHODS

An extensive literature search was conducted on omics technologies since the first research on omics.

RESULTS

This article summarizes the history and main research methods of the six omics technologies, including genomics, transcriptomics, proteomics, metabolomics, lipidomics, and microbiomics. Their application in certain skin diseases and cosmetics research and development are also summarized.

CONCLUSIONS

This information will help to understand the mechanism of some skin diseases and the discovery of potential biomarkers, and provide new insights for skin health management and cosmetics research and development.

Bioactive potential of natural biomaterials: identification, retention and assessment of biological properties

Biomaterials have had an increasingly important role in recent decades, in biomedical device design and the development of tissue engineering solutions for cell delivery, drug delivery, device integration, tissue replacement, and more. There is an increasing trend in tissue engineering to use natural substrates, such as macromolecules native to plants and animals to improve the biocompatibility and biodegradability of delivered materials. At the same time, these materials have favourable mechanical properties and often considered to be biologically inert. More importantly, these macromolecules possess innate functions and properties due to their unique chemical composition and structure, which increase their bioactivity and therapeutic potential in a wide range of applications. While much focus has been on integrating these materials into these devices via a spectrum of cross-linking mechanisms, little attention is drawn to residual bioactivity that is often hampered during isolation, purification, and production processes. Herein, we discuss methods of initial material characterisation to determine innate bioactivity, means of material processing including cross-linking, decellularisation, and purification techniques and finally, a biological assessment of retained bioactivity of a final product. This review aims to address considerations for biomaterials design from natural polymers, through the optimisation and preservation of bioactive components that maximise the inherent bioactive potency of the substrate to promote tissue regeneration.

Advances and Perspectives in Prostate Cancer Biomarker Discovery in the Last 5 Years through Tissue and Urine Metabolomics

Prostate cancer (PCa) is the second most diagnosed cancer in men worldwide. For its screening, serum prostate specific antigen (PSA) test has been largely performed over the past decade, despite its lack of accuracy and inability to distinguish indolent from aggressive disease. Metabolomics has been widely applied in cancer biomarker discovery due to the well-known metabolic reprogramming characteristic of cancer cells. Most of the metabolomic studies have reported alterations in urine of PCa patients due its noninvasive collection, but the analysis of prostate tissue metabolome is an ideal approach to disclose specific modifications in PCa development. This review aims to summarize and discuss the most recent findings from tissue and urine metabolomic studies applied to PCa biomarker discovery. Eighteen metabolites were found consistently altered in PCa tissue among different studies, including alanine, arginine, uracil, glutamate, fumarate, and citrate. Urine metabolomic studies also showed consistency in the dysregulation of 15 metabolites and, interestingly, alterations in the levels of valine, taurine, leucine and citrate were found in common between urine and tissue studies. These findings unveil that the impact of PCa development in human metabolome may offer a promising strategy to find novel biomarkers for PCa diagnosis.

Untargeted lipidomic approach in studying pinot noir wine lipids and predicting wine origin

An untargeted lipidomic profiling approach based on ultra - performance liquid chromatography - time-of-flight tandem mass spectrometry (UPLC-TOF-MS/MS) was successfully used to study the origin of commercial Pinot noir wines. The total wine lipids were extracted using a modified Bligh-Dyer method. In all wine samples, the total lipids were less than 0.1% (w/w) of wine. The wines analyzed consisted of 222 lipids from 11 different classes. 48 commercial Pinot noir wine samples were collected from producers in Burgundy, California, Oregon, and New Zealand. Lipidomic data was studied using advanced multivariate analysis methods, random forest, k-nearest neighbor (k-NN), and linear discriminant analysis. The overall classification accuracy was 97.5% for random forest and 90% for k-NN. Wine lipids showed a strong potential for classifying wines by origin, with the top 58 lipids contributing to the discrimination. This information could potentially be used for further study of the impacts of lipids on wine characteristics and authenticity.

Untargeted lipidomics reveals specific lipid abnormalities in Sjögren's syndrome

OBJECTIVE

The relationship between serum lipid variations in SS and healthy controls was investigated to identify potential predictive lipid biomarkers.

METHODS

Serum samples from 230 SS patients and 240 healthy controls were collected. The samples were analysed by ultrahigh-performance liquid chromatography coupled with Q Exactive™ spectrometry. Potential lipid biomarkers were screened through orthogonal projection to latent structures discriminant analysis and further evaluated by receiver operating characteristic analysis.

RESULTS

A panel of three metabolites [phosphatidylcholine (18:0/22:5), triglyceride (16:0/18:0/18:1) and acylcarnitine (12:0)] was identified as a specific biomarker of SS. The receiver operating characteristic analysis showed that the panel had a sensitivity of 84.3% with a specificity of 74.8% in discriminating patients with SS from healthy controls.

CONCLUSION

Our approach successfully identified serum biomarkers associated with SS patients. The potential lipid biomarkers indicated that SS metabolic disturbance might be associated with oxidized lipids, fatty acid oxidation and energy metabolism.

Accurate quantification of lipid species affected by isobaric overlap in Fourier-transform mass spectrometry

Lipidomics data require consideration of ions with near-identical masses, which comprises among others the Type-II isotopic overlap. This overlap occurs in series of lipid species differing only by number of double bonds (DBs) mainly because of the natural abundance of 13C-atoms. High-resolution mass spectrometry, such as Fourier-transform mass spectrometry (FTMS), is capable of resolving Type-II overlap depending on mass resolving power. In this work, we evaluated FTMS quantification accuracy of lipid species affected by Type-II overlap. Spike experiments with lipid species pairs of various lipid classes were analyzed by flow injection analysis-FTMS. Accuracy of quantification was evaluated without and with Type-II correction (using relative isotope abundance) as well as utilizing the first isotopic peak (M+1). Isobaric peaks, which were sufficiently resolved, were most accurate without Type-II correction. In cases of partially resolved peaks, we observed peak interference causing distortions in mass and intensity, which is a well-described phenomenon in FTMS. Concentrations of respective species were more accurate when calculated from M+1. Moreover, some minor species, affected by considerable Type-II overlap, could only be quantified by M+1. Unexpectedly, even completely unresolved peaks were substantially overcorrected by Type-II correction because of peak interference. The described method was validated including intraday and interday precisions for human serum and fibroblast samples. Taken together, our results show that accurate quantification of lipid species by FTMS requires resolution-depended data analysis.

The use of molecular markers in the verification of fish and seafood authenticity and the detection of adulteration

The verification of authenticity and detection of food mislabeling are elements that have been of high importance for centuries. During the last few decades there has been an increasing consumer demand for the verification of food identity and the implementation of stricter controls around these matters. Fish and seafood are among the most easily adulterated foodstuffs mainly due to the significant alterations of the species' morphological characteristics that occur during the different types of processing, which render the visual identification of the animals impossible. Even simple processes, such as filleting remove very important morphological elements and suffice to prevent the visual identification of species in marketed products. Novel techniques have therefore been developed that allow identification of species, the differentiation between species and also the differentiation of individuals that belong to the same species but grow in different populations and regions. Molecular markers have been used during the last few decades to fulfill this purpose and several improvements have been implemented rendering their use applicable to a commercial scale. The reliability, accuracy, reproducibility, and time-and cost-effectiveness of these techniques allowed them to be established as routine methods in the industry and research institutes. This review article aims at presenting the most important molecular markers used for the authentication of fish and seafood. The most important techniques are described, and the results of numerous studies are outlined and discussed, allowing interested parties to easily access and compare information about several techniques and fish/seafood species.

Dissecting lipid metabolism alterations in SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the COVID-19 pandemic that has infected over a hundred million people globally. There have been more than two million deaths recorded worldwide, with no end in sight until a widespread vaccination will be achieved. Current research has centred on different aspects of the virus interaction with cell surface receptors, but more needs to be done to further understand its mechanism of action in order to develop a targeted therapy and a method to control the spread of the virus. Lipids play a crucial role throughout the viral life cycle, and viruses are known to exploit lipid signalling and synthesis to affect host cell lipidome. Emerging studies using untargeted metabolomic and lipidomic approaches are providing new insight into the host response to COVID-19 infection. Indeed, metabolomic and lipidomic approaches have identified numerous circulating lipids that directly correlate to the severity of the disease, making lipid metabolism a potential therapeutic target. Circulating lipids play a key function in the pathogenesis of the virus and exert an inflammatory response. A better knowledge of lipid metabolism in the host-pathogen interaction will provide valuable insights into viral pathogenesis and to the development of novel therapeutic targets.

Bioactive Lipids in MSCs Biology: State of the Art and Role in Inflammation

Lipidomics is a lipid-targeted metabolomics approach that aims to the comprehensive analysis of lipids in biological systems in order to highlight the specific functions of lipid species in health and disease. Lipids play pivotal roles as they are major structural components of the cellular membranes and energy storage molecules but also, as most recently shown, they act as functional and regulatory components of intra- and intercellular signaling. Herein, emphasis is given to the recently highlighted roles of specific bioactive lipids species, as polyunsaturated fatty acids (PUFA)-derived mediators (generally known as eicosanoids), endocannabinoids (eCBs), and lysophospholipids (LPLs), and their involvement in the mesenchymal stem cells (MSCs)-related inflammatory scenario. Indeed, MSCs are a heterogenous population of multipotent cells that have attracted much attention for their potential in regulating inflammation, immunomodulatory capabilities, and reparative roles. The lipidomics of the inflammatory disease osteoarthritis (OA) and the influence of MSCs-derived lipids have also been addressed.

Metabolomic/lipidomic profiling of COVID-19 and individual response to tocilizumab

The current pandemic emergence of novel coronavirus disease (COVID-19) poses a relevant threat to global health. SARS-CoV-2 infection is characterized by a wide range of clinical manifestations, ranging from absence of symptoms to severe forms that need intensive care treatment. Here, plasma-EDTA samples of 30 patients compared with age- and sex-matched controls were analyzed via untargeted nuclear magnetic resonance (NMR)-based metabolomics and lipidomics. With the same approach, the effect of tocilizumab administration was evaluated in a subset of patients. Despite the heterogeneity of the clinical symptoms, COVID-19 patients are characterized by common plasma metabolomic and lipidomic signatures (91.7% and 87.5% accuracy, respectively, when compared to controls). Tocilizumab treatment resulted in at least partial reversion of the metabolic alterations due to SARS-CoV-2 infection. In conclusion, NMR-based metabolomic and lipidomic profiling provides novel insights into the pathophysiological mechanism of human response to SARS-CoV-2 infection and to monitor treatment outcomes.

The current COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is markedly affecting the world population. Here we report about the small-molecule profile of patients hospitalized during the first wave of the COVID-19 pandemic in Florence (Italy). Using magnetic resonance spectroscopy, we showed that the infection induces profound changes in the metabolome. The analysis of the specific metabolite changes and correlations with clinical data enabled the identification of potential biochemical determinants of the disease fingerprint. We also followed how metabolic alterations revert towards those of the control group upon treatment with tocilizumab, a recombinant humanized monoclonal antibody against the interleukin-6 receptor. These results open up possibilities for the monitoring of novel patients and their individual response to treatment.

The Role of Lipidomics in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a complex neurodevelopmental syndrome commonly diagnosed in early childhood; it is usually characterized by impairment in reciprocal communication and speech, repetitive behaviors, and social withdrawal with loss in communication skills. Its development may be affected by a variety of environmental and genetic factors. Trained physicians diagnose and evaluate the severity of ASD based on clinical evaluations of observed behaviors. As such, this approach is inevitably dependent on the expertise and subjective assessment of those administering the clinical evaluations. There is a need to identify objective biological markers associated with diagnosis or clinical severity of the disorder. Several important issues and concerns exist regarding the diagnostic competence of the many abnormal plasma metabolites produced in the different biochemical pathways evaluated in individuals with ASD. The search for high-performing bio-analytes to diagnose and follow-up ASD development is still a major target in medicine. Dysregulation in the oxidative stress response and proinflammatory processes are major etiological causes of ASD pathogenesis. Furthermore, dicarboxylic acid metabolites, cholesterol-related metabolites, phospholipid-related metabolites, and lipid transporters and mediators are impaired in different pathological conditions that have a role in the ASD etiology. A mechanism may exist by which pro-oxidant environmental stressors and abnormal metabolites regulate clinical manifestations and development of ASD.

The effects of meldonium on the acute ischemia/reperfusion liver injury in rats

Acute ischemia/reperfusion (I/R) liver injury is a clinical condition challenging to treat. Meldonium is an anti-ischemic agent that shifts energy production from fatty acid oxidation to less oxygen-consuming glycolysis. Thus, we investigated the effects of a 4-week meldonium pre-treatment (300 mg/kg b.m./day) on the acute I/R liver injury in Wistar strain male rats. Our results showed that meldonium ameliorates I/R-induced liver inflammation and injury, as confirmed by liver histology, and by attenuation of serum alanine- and aspartate aminotransferase activity, serum and liver high mobility group box 1 protein expression, and liver expression of Bax/Bcl2, haptoglobin, and the phosphorylated nuclear factor kappa-light-chain-enhancer of activated B cells. Through the increased hepatic activation of the nuclear factor erythroid 2-related factor 2, meldonium improves the antioxidative defence in the liver of animals subjected to I/R, as proved by an increase in serum and liver ascorbic/dehydroascorbic acid ratio, hepatic haem oxygenase 1 expression, glutathione and free thiol groups content, and hepatic copper-zinc superoxide dismutase, manganese superoxide dismutase, catalase, glutathione peroxidase, and glutathione reductase activity. Based on our results, it can be concluded that meldonium represent a protective agent against I/R-induced liver injury, with a clinical significance in surgical procedures.

Spatial Lipidomics Reveals Anticancer Mechanisms of Bufalin in Combination with Cinobufagin in Tumor-Bearing Mice

Bufalin (BFL) and cinobufagin (CBF) are the principal bioactive constituents of Chansu, a widely used traditional Chinese medicine (TCM). The synergistic effects of potential active components are responsible for the bioactivities of TCM. Our results showed that the cotreatment with BFL and CBF confers superior anticancer efficacy compared to monotreatment. To reveal the underlying mechanisms of their cotreatment, an integrated method composed of mass spectrometry-based lipidomics and matrix-assisted laser desorption/ionization mass spectrometry imaging was used to delineate the responses of tumor-bearing mice treated with BFL and CBF individually or in combination. The cotreatment with BFL and CBF modulated the sphingolipid metabolism and glycerophospholipid metabolism, and subsequently led to mitochondria-driven apoptosis and systemic disruption of biomembranes in tumor cells. Furthermore, we found that the disturbed lipid markers were mainly located in the non-necrotic tumor areas, the essential parts for the formation of solid tumor framework. Together, our findings revealed what occurred in tumor in response to the treatment of BFL and CBF, from lipids to enzymes, and thus provide insights into the critical role of lipid reprogramming in the satisfactory anticancer effect of BFL in combination with CBF.

Mass Spectrometry-Based Shotgun Lipidomics for Cancer Research

Shotgun lipidomics is an analytical approach for large-scale and systematic analysis of the composition, structure, and quantity of cellular lipids directly from lipid extracts of biological samples by mass spectrometry. This approach possesses advantages of high throughput and quantitative accuracy, especially in absolute quantification. As cancer research deepens at the level of quantitative biology and metabolomics, the demand for lipidomics approaches such as shotgun lipidomics is becoming greater. In this chapter, the principles, approaches, and some applications of shotgun lipidomics for cancer research are overviewed.

Applications of Lipidomics in Tumor Diagnosis and Therapy

Lipids have many critical biological functions in cancer. There are characteristic changes of lipid metabolism and metabolites in different physiological and pathological processes. Lipidomics is an emerging discipline of metabolomics for systematic analysis of lipids in organisms, tissues, or cells and the molecules that interact with them. With the development of new analytical techniques, especially the application and development of mass spectrometry techniques, the determination of lipids can be carried out quickly and accurately and has a high throughput. A large number of studies have shown that abnormal lipid metabolism is closely related to the occurrence and development of tumors. The application of lipidomics technology can reveal changes in lipids and relative abnormal metabolic pathways associated with tumors. Moreover, it shows a wide range of application prospects in the identification of tumor lipid biomarkers, early tumor diagnosis, and the discovery of antitumor drug targets. This chapter mainly introduces the application and development direction of lipidomics in the diagnosis and therapy of different tumors.

Dooming Phagocyte Responses: Inflammatory Effects of Endogenous Oxidized Phospholipids

Endogenous oxidized phospholipids are produced during tissue stress and are responsible for sustaining inflammatory responses in immune as well as non-immune cells. Their local and systemic production and accumulation is associated with the etiology and progression of several inflammatory diseases, but the molecular mechanisms that underlie the biological activities of these oxidized phospholipids remain elusive. Increasing evidence highlights the ability of these stress mediators to modulate cellular metabolism and pro-inflammatory signaling in phagocytes, such as macrophages and dendritic cells, and to alter the activation and polarization of these cells. Because these immune cells serve a key role in maintaining tissue homeostasis and organ function, understanding how endogenous oxidized lipids reshape phagocyte biology and function is vital for designing clinical tools and interventions for preventing, slowing down, or resolving chronic inflammatory disorders that are driven by phagocyte dysfunction. Here, we discuss the metabolic and signaling processes elicited by endogenous oxidized lipids and outline new hypotheses and models to elucidate the impact of these lipids on phagocytes and inflammation.

Rapid Peak Alignment for MALDI-TOF Lipid Analysis

The ability to measure structural and functional alterations in cellular and tissue lipids with small footprint, accessible instrumentation has sparked interest in their role in disease pathology. However, various lipidomic analytical tools tend to be cumbersome and time-consuming. A rapid, accurate, and straight forward peak alignment software routine would greatly facilitate the analysis of large datasets, such as those produced by matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Herein, we describe a novel Rapid Peak Alignment Method (RPAM) which allows untargeted analysis of lipids expressed in brain white matter following chronic ethanol exposure in an established experimental model. The RPAM outputs data comparable to manual peak alignments but the processing time requires only 90 minutes instead of 8-10 hours. This method is readily adapted to a broad range of models, tissue types, and human diseases.

Lipid Metabolism and Lipidomics Applications in Cancer Research

Lipids are the critical components of cellular and plasma membrane, which constitute an impermeable barrier of cellular compartments, and play important roles on numerous cellular processes including cell growth, proliferation, differentiation, and signaling. Alterations in lipid metabolism have been implicated in the development and progression of cancers. However, unlike other biomolecules, the diversity in the structures and characteristics of lipid species results in the limited understanding of their metabolic alterations in cancers. Lipidomics is an emerging discipline that studies lipids in a large scale based on analytical chemistry principles and technological tools. Multidimensional mass spectrometry-based shotgun lipidomics (MDMS-SL) uses direct infusion to avoid difficulties from alterations in concentration, chromatographic anomalies, and ion-pairing alterations to improve resolution and achieve rapid and accurate qualitative and quantitative analysis. In this chapter, lipids and lipid metabolism relevant to cancer research are introduced, followed by a brief description of MDMS-SL and other shotgun lipidomics techniques and some applications for cancer research.

Targeted Analysis of the Plant Lipidome by UPLC-NanoESI-MS/MS

The plant lipidome is highly complex and changes dynamically under the influence of various biotic and abiotic stresses. Targeted analyses based on mass spectrometry enable the detection and characterization of the plant lipidome. It can be analyzed in plant tissues of different developmental stages and from isolated cellular organelles and membranes. Here, we describe a sensitive method to establish the relative abundance of molecular lipid species belonging to three lipid categories: glycerolipids, sphingolipids, and sterol lipids. The method is based on a monophasic lipid extraction and includes the derivatization of a few rare and low-abundant lipid classes. The molecular lipid species are resolved by lipid class-specific reverse-phase liquid chromatography and detected by nanoelectrospray ionization coupled with tandem mass spectrometry. The triple quadrupole analyzer is used for detection with multiple reaction monitoring (MRM). Mass transition lists are constructed based on the knowledge of organism-specific lipid building blocks. They are initially determined by classical lipid analytical methods and then used for combinative assembly of all possible lipid structures. The targeted analysis enables detailed and comprehensive profiling of the entire lipid content and composition of plants.

Impact of sphingosine and acetylsphingosines on the aggregation and toxicity of metal-free and metal-treated amyloid-β

Pathophysiological shifts in the cerebral levels of sphingolipids in Alzheimer's disease (AD) patients suggest a link between sphingolipid metabolism and the disease pathology. Sphingosine (SP), a structural backbone of sphingolipids, is an amphiphilic molecule that is able to undergo aggregation into micelles and micellar aggregates. Considering its structural properties and cellular localization, we hypothesized that SP potentially interacts with amyloid-β (Aβ) and metal ions that are found as pathological components in AD-affected brains, with manifesting its reactivity towards metal-free Aβ and metal-bound Aβ (metal–Aβ). Herein, we report, for the first time, that SP is capable of interacting with both Aβ and metal ions and consequently affects the aggregation of metal-free Aβ and metal–Aβ. Moreover, incubation of SP with Aβ in the absence and presence of metal ions results in the aggravation of toxicity induced by metal-free Aβ and metal–Aβ in living cells. As the simplest acyl derivatives of SP, N-acetylsphingosine and 3-O-acetylsphingosine also influence metal-free Aβ and metal–Aβ aggregation to different degrees, compared to SP. Such slight structural modifications of SP neutralize its ability to exacerbate the cytotoxicity triggered by metal-free Aβ and metal–Aβ. Notably, the reactivity of SP and the acetylsphingosines towards metal-free Aβ and metal–Aβ is determined to be dependent on their formation of micelles and micellar aggregates. Our overall studies demonstrate that SP and its derivatives could directly interact with pathological factors in AD and modify their pathogenic properties at concentrations below and above critical aggregation concentrations.

The reactivity of sphingosine and acetylsphingosines towards both metal-free and metal-treated amyloid-β is demonstrated showing a correlation of their micellization properties.

Lipidomic profiling reveals triacylglycerol accumulation in the liver during pregnane X receptor activation-induced hepatomegaly

Pregnane X receptor (PXR) is highly expressed in the liver and plays an integral role in the control of xenobiotic and endobiotic metabolism to maintain homeostasis. We previously reported that activation of PXR significantly induced liver enlargement. But the lipid profiling during PXR-induced hepatomegaly remains unclear. This study aimed to characterize the effect of PXR activation on hepatic lipid homeostasis by lipidomics analysis. Mice were intraperitoneally administered with the typical mPXR agonist, pregnenolone 16α-carbonitrile (PCN, 100 mg/kg/d), for 5 days. Liver and serum were collected for further analysis. The results confirmed that PXR activation can significantly induce liver enlargement. An obvious hepatic lipid accumulation was observed in PCN-treated mice, as determined by H&E and Oil Red O staining. Ultra-high performance liquid chromatography-Q Exactive Orbitrap high-resolution mass spectrometer (UHPLC-Q Exactive Orbitrap HRMS)-based lipidomics was performed to characterize the change in lipid species. A total of 20 potential lipid biomarkers were significantly perturbed. The most significant change was found in the triacylglycerol (TG), which constituted with the lower number of carbon atoms and double bonds. Moreover, the mRNA expression levels showed that PCN-induced PXR activation significantly regulated the expression of genes involved in the uptake, synthesis and metabolism of TG, which was consistent with increased TG levels. Collectively, these findings demonstrated that lipids such as TG were significantly accumulated during PXR-induced hepatomegaly.

Antihypertensive activity of oleanolic acid is mediated via downregulation of secretory phospholipase A2 and fatty acid synthase in spontaneously hypertensive rats

Oleanolic acid (OA) is reported to possess antihypertensive activity via the regulation of lipid metabolism; however, the mechanisms underlying lipid regulation by OA are yet to be fully elucidated. The aim of the present study was to evaluate the mechanisms via which OA regulates lipid metabolism in spontaneously hypertensive rats (SHRs) via ultra‑performance liquid chromatography‑quadrupole/Orbitrap‑mass spectrometry (MS)‑based lipidomics analysis. SHRs were treated with OA (1.08 mg/kg) for 4 weeks. The liver tissues were excised, homogenized in dichloromethane and centrifuged, and subsequently the supernatant layer was collected and concentrated under vacuum to dryness. The dichloromethane extract was subjected to MS analysis and database searching, and comparison of standards was performed to identify potential biomarkers. Partial least squares‑discriminant analysis performed on the liver lipidome revealed a total of 14 endogenous metabolites that were significantly changed in the SHR model group (SH group) compared with Wistar Kyoto rats [normal control (NC group)], including glycerophospholipids, sphingolipids and glycerides. Heatmaps revealed that the liver lipid profiles in the OA group were clustered more closely compared with those observed in the NC group, indicating that the antihypertensive effect of OA was mediated via regulation of liver lipid metabolites. It was observed that the protein levels of secretory phospholipase A2 (sPLA2) and fatty acid synthase (FAS) were increased in the SH group compared with the NC group. In addition, the levels of lysophosphatidylcholine and triglycerides in the liver were elevated, whereas the levels of low‑density lipoprotein cholesterol and high‑density lipoprotein cholesterol were reduced in the SH group. Upon treatment with OA, the mRNA and protein levels of PLA2 and FAS were observed to be downregulated. Collectively, the present study indicated that the antihypertensive activity of OA was mediated via downregulation of sPLA2 and FAS in SHRs, and that treatment with OA resulted in significant improvements in blood pressure and associated abnormalities in the lipid metabolites.

Proteomics and Lipidomics Investigations to Decipher the Behavior of Willaertia magna C2c Maky According to Different Culture Modes

Willaertia magna C2c Maky is a free-living amoeba that has demonstrated its ability to inhibit the intracellular multiplication of some Legionella pneumophila strains, which are pathogenic bacteria inhabiting the aquatic environment. The Amoeba, an industry involved in the treatment of microbiological risk in the water and plant protection sectors, has developed a natural biocide based on the property of W. magna to manage the proliferation of the pathogen in cooling towers. In axenic liquid medium, amoebas are usually cultivated in adhesion on culture flask. However, we implemented a liquid culture in suspension using bioreactors in order to produce large quantities of W. magna. In order to investigate the culture condition effects on W. magna, we conducted a study based on microscopic, proteomics and lipidomics analyzes. According to the culture condition, amoeba exhibited two different phenotypes. The differential proteomics study showed that amoebas seemed to promote the lipid metabolism pathway in suspension culture, whereas we observed an upregulation of the carbohydrate pathway in adherent culture. Furthermore, we observed an over-regulation of proteins related to the cytoskeleton for W. magna cells grown in adhesion. Regarding the lipid analysis, suspension and adhesion cell growth showed comparable lipid class compositions. However, the differential lipid analysis revealed differences that confirmed cell phenotype differences observed by microscopy and predicted by proteomics. Overall, this study provides us with a better insight into the biology and molecular processes of W. magna in different culture lifestyles.

Metabolomic and lipidomic approaches to identify biomarkers for bladder cancer and interstitial cystitis (Review)

The discovery, introduction and clinical use of prognostic and diagnostic biomarkers has significantly improved outcomes for patients with various illnesses, including bladder cancer (BC) and other bladder-related diseases, such as benign bladder dysfunction and interstitial cystitis (IC). Several sensitive and noninvasive clinically relevant biomarkers for BC and IC have been identified. Metabolomic- and lipidomic-based biomarkers have notable clinical potential in improving treatment outcomes for patients with cancer; however, there are also some noted limitations. This review article provides a short and concise summary of the literature on metabolomic and lipidomic biomarkers for BC and IC, focusing on the possible clinical utility of profiling metabolic alterations in BC and IC.

Preferential Protein Partitioning in Biological Membrane with Coexisting Liquid Ordered and Liquid Disordered Phase Behavior: Underlying Design Principles

Several studies now show that certain proteins exhibit selective preference toward liquid ordered (L[Formula: see text]) or toward liquid disordered (L[Formula: see text]) regions of the heterogeneous membrane and some of them have preference for the L[Formula: see text]-L[Formula: see text] interface. Spatially heterogenous organization of lipids, enriched in specific protein molecules, function as platforms for signaling and are involved in several other physiologically critical functions. In this review, we collate together some of the experimental observations of cases where proteins preferentially segregate into different phases and highlight the importance of these preferential localization in terms of underlying functions. We also try to understand the structural features and chemical makeup of the membrane-interacting motifs of these proteins. Finally, we put forth some preliminary analysis on class I viral fusion proteins, some of which are known to partition at the L[Formula: see text]-L[Formula: see text] interface, and through them we try to understand the evolutionary design principles of phase segregating proteins. Put together, this review summarizes the existing studies on preferential partitioning of proteins into different membrane phases while emphasizing the need to understand the molecular design-level features that can help us "engineer" functionally rich peptides and proteins with a programmed membrane partitioning.

Multifunctional Reactive MALDI Matrix Enabling High-Lateral Resolution Dual Polarity MS Imaging and Lipid C═C Position-Resolved MS2 Imaging

Local lipid variations in tissues are readily revealed with mass spectrometry imaging (MSI) methods, and the resulting lipid distributions serve as bioanalytical signatures to reveal cell- or tissue-specific lipids. Comprehensive MSI lipid mapping requires measurements in both ion polarities. Additionally, structural lipid characterization is necessary to link the lipid structure to lipid function. Whereas some structural elements of lipids are readily derived from high-resolution mass spectrometry (MS) and tandem-MS (MSⁿ), the localization of C═C double bonds (DBs) requires specialized fragmentation and/or functionalization methods. In this work, we identify a multifunctional matrix-assisted laser desorption/ionization (MALDI) matrix for spatially resolved lipidomics investigations that reacts with lipids in Paternò-Büchi (PB) reactions during laser irradiation facilitating DB-position assignment and allows dual-polarity high-resolution MALDI-MSI and MALDI MS²I studies. By screening 12 compounds for improved ionization efficiency in positive-/negative-ion mode and the functionalization yield compared to the previously introduced reactive MALDI matrix benzophenone, 2-benzoylpyridine (BzPy) is identified as the best candidate. The new matrix enables DB localization of authentic standards belonging to 12 lipid classes and helps to assign 133/58 lipid features in positive-/negative-ion mode from mouse cerebellum tissue. The analytical capabilities of BzPy as a multifunctional MALDI-MSI matrix are demonstrated by imaging endogenous and PB-functionalized lipids in mouse kidney sections with 7 μm lateral resolution in both ion modes. Tracking diagnostic lipid DB-position fragment ions in mouse pancreatic tissue with down to 10 μm pixel size allows us to identify the islets of Langerhans associated with lipid isomer upregulation and depletion.