Selection of internal standards for accurate quantification of complex lipid species in biological extracts by electrospray ionization mass spectrometry-What, how and why?

Development of a targeted method for DNA adductome and its application as sensitive biomarkers of ambient air pollution exposure

DNA adducts are widely recognized as biomarkers of exposure to environmental carcinogens and associated health effects in toxicological and epidemiological studies. This study presents a targeted and sensitive method for comprehensive DNA adductome analysis using ultra-high-performance liquid chromatography coupled with triple-quadrupole tandem mass spectrometry (UHPLC-QqQ-MS/MS). The method was developed using calf thymus DNA, with careful optimization of mass spectrometric parameters, chromatographic separation conditions, and pretreatment methods. Ultimately, a targeted method was established for 41 DNA adducts, which showed good linearity (R2 ≥0.992), recovery (80.1-119.4 %), accuracy (81.3-117.8 %), and precision (relative standard deviation <14.2 %). The established method was employed to analyze DNA adducts in peripheral blood cells from pregnant women in Shanxi and Beijing. Up to 23 DNA adducts were successfully detected in samples of varying sizes. From 2 μg of maternal DNA samples, seven specific adducts were identified: 5-methyl-2'-deoxycytidine (5-MedC), 5-hydroxymethyl-2'-deoxycytidine (5-HmdC), N6-methyl-2'-deoxyadenosine (N6-MedA), 8-hydroxy-2'-deoxyguanosine (8-OHdG), 5-hydroxy-2'-deoxycytidine (5-OHdC), 1,N6-etheno-2'-deoxyadenosine (1,N6-εdA), and N2-methyl-2'-deoxyguanosine (N2-MedG). This study reveals that exposure to higher concentrations of ambient air pollutants may elevate the levels of DNA methylation and oxidative damage at different base sites, highlighting the application potential of DNA adducts as sensitive biomarkers of air pollution exposure.

Isotope dilution with isotopically labeled biomass: An effective alternative for quantitative metabolomics

BACKGROUND

State-of-the-art quantitative metabolomics relies on isotope dilution using internal standards (IS) derived from fully 13C labeled biomass. By spiking samples and external standards with known amounts of IS, the spike characterization demands are kept to a minimum. In fact, it is sufficient to experimentally assess the isotopic enrichment of the IS. This study develops the yeast derived IS toolbox further, (1) by characterizing the concentration levels of hydrophilic metabolites in a yeast fermentation batch and (2) by exploring the analytical figures of merit of one-point IS versus multipoint external calibration using IS, the established gold-standard for quantitative metabolomics.

RESULTS

Independent reverse isotope dilution experiments using different chromatographic methods over a period of several months, delivered a list of 83 13C-labeled metabolites with fully characterized concentration and their uncertainty, covering 5 orders of magnitude, from the nanomolar to the low millimolar range. The 13C-labeled yeast-derived IS showed excellent intermediate stability with 92 % of molecules showing inter-method RSDs ≤30 % (75 % of molecules showed RSDs ≤15 %) over a timeframe of five months. One-point internal standardization with the characterized labeled biomass achieved figures of merit equivalent to multipoint calibrations for the majority of metabolites.

SIGNIFICANCE

The proposed calibration workflow rationalizes time and standard expenditure and is particularly beneficial for laboratories dealing with wide-target assays and small analysis batches. The present assessment serves as a seminal study for further developments of the concept towards absolute quantification from archive high-resolution MS data of U13C-biomass-spiked samples and the implementation of quick biomass recalibration with each experiment, promising seamless transition between internal standards derived from different fermentation batches.

Plant and algal lipidomes: Analysis, composition, and their societal significance

Plants and algae play a crucial role in the earth's ecosystems. Through photosynthesis they convert light energy into chemical energy, capture CO2 and produce oxygen and energy-rich organic compounds. Photosynthetic organisms are primary producers and synthesize the essential omega 3 and omega 6 fatty acids. They have also unique and highly diverse complex lipids, such as glycolipids, phospholipids, triglycerides, sphingolipids and phytosterols, with nutritional and health benefits. Plant and algal lipids are useful in food, feed, nutraceutical, cosmeceutical and pharmaceutical industries but also for green chemistry and bioenergy. The analysis of plant and algal lipidomes represents a significant challenge due to the intricate and diverse nature of their composition, as well as their plasticity under changing environmental conditions. Optimization of analytical tools is crucial for an in-depth exploration of the lipidome of plants and algae. This review highlights how lipidomics analytical tools can be used to establish a complete mapping of plant and algal lipidomes. Acquiring this knowledge will pave the way for the use of plants and algae as sources of tailored lipids for both industrial and environmental applications. This aligns with the main challenges for society, upholding the natural resources of our planet and respecting their limits.

Ultrafast, Selective, and Highly Sensitive Nonchromatographic Analysis of Fourteen Cannabinoids in Cannabis Extracts, Δ8-Tetrahydrocannabinol Synthetic Mixtures, and Edibles by Cyclic Ion Mobility Spectrometry-Mass Spectrometry

The diversity of cannabinoid isomers and complexity of Cannabis products pose significant challenges for analytical methodologies. In this study, we developed a method to analyze 14 different cannabinoid isomers in diverse samples within milliseconds by leveraging the unique adduct-forming behavior of silver ions in advanced cyclic ion mobility spectrometry-mass spectrometry. The developed method achieved the separation of isomers from four groups of cannabinoids: Δ3-tetrahydrocannabinol (THC) (1), Δ8-THC (2), Δ9-THC (3), cannabidiol (CBD) (4), Δ8-iso-THC (5), and Δ(4)8-iso-THC (6) (all MW = 314); 9α-hydroxyhexahydrocannabinol (7), 9β-hydroxyhexahydrocannabinol (8), and 8-hydroxy-iso-THC (9) (all MW = 332); tetrahydrocannabinolic acid (THCA) (10) and cannabidiolic acid (CBDA) (11) (both MW = 358); Δ8-tetrahydrocannabivarin (THCV) (12), Δ8-iso-THCV (13), and Δ9-THCV (14) (all MW = 286). Moreover, experimental and theoretical traveling wave collision cross section values in nitrogen (TWCCSN2) of cannabinoid-Ag(I) species were obtained for the first time with an average error between experimental and theoretical values of 2.6%. Furthermore, a workflow for the identification of cannabinoid isomers in Cannabis and Cannabis-derived samples was established based on three identification steps (m/z and isotope pattern of Ag(I) adducts, TWCCSN2, and MS/MS fragments). Afterward, calibration curves of three major cannabinoids were established with a linear range of 1-250 ng·ml-1 for Δ8-THC (2) (R2 = 0.9999), 0.1-25 ng·ml-1 for Δ9-THC (3) (R2 = 0.9987), and 0.04-10 ng·ml-1 for CBD (4) (R2 = 0.9986) as well as very low limits of detection (0.008-0.2 ng·ml-1). Finally, relative quantification of Δ8-THC (2), Δ9-THC (3), and CBD (4) in eight complex acid-treated CBD mixtures was achieved without chromatographic separation. The results showed good correspondence (R2 = 0.999) with those obtained by gas chromatography-flame ionization detection/mass spectrometry.

Phospholipidomics in Clinical Trials for Brain Disorders: Advancing our Understanding and Therapeutic Potentials

Phospholipidomics is a specialized branch of lipidomics that focuses on the characterization and quantification of phospholipids. By using sensitive analytical techniques, phospholipidomics enables researchers to better understand the metabolism and activities of phospholipids in brain disorders such as Alzheimer's and Parkinson's diseases. In the brain, identifying specific phospholipid biomarkers can offer valuable insights into the underlying molecular features and biochemistry of these diseases through a variety of sensitive analytical techniques. Phospholipidomics has emerged as a promising tool in clinical studies, with immense potential to advance our knowledge of neurological diseases and enhance diagnosis and treatment options for patients. In the present review paper, we discussed numerous applications of phospholipidomics tools in clinical studies, with a particular focus on the neurological field. By exploring phospholipids' functions in neurological diseases and the potential of phospholipidomics in clinical research, we provided valuable insights that could aid researchers and clinicians in harnessing the full prospective of this innovative practice and improve patient outcomes by providing more potent treatments for neurological diseases.

Comprehensive studies on the development of HPLC-MS/MS and HPLC-FL based methods for routine determination of homocysteine thiolactone in human urine

The report presents a new, robust, and reproducible liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) and HPLC-fluorescence (FL) based methods for the determination of urinary homocysteine thiolactone (HTL). In particular, a versatile sample preparation procedure was designed to purify urine samples, involving chloroform liquid-liquid extraction (LLE) of HTL and its re-extraction (re-LLE) with formic acid, prior to chromatographic analysis. In relation to HPLC-FL assay, the quantification of HTL additionally uses o-phthaldialdehyde (OPA) as the on-column derivatization agent, while HPLC-MS/MS assay employs homoserine lactone (HSL) as an internal standard (IS). The baseline separation of the analyte and IS (if applicable) is accomplished under hydrophilic interactions chromatography (HILIC) and reverse phase (RP)-HPLC conditions in the case of HPLC-MS/MS and HPLC-FL based method, respectively. The assays linearity was observed within 20-400 nmol/L for HTL in urine, covering the expected unknown analyte's concentration in study samples. The value of 20 nmol/L in urine was recognized as the limit of quantification (LOQ) for both methods. The assays were successfully applied to urine samples delivered by fifteen apparently healthy volunteers showing that they are suitable for screening of human urine.

Lipid Isobaric Mass Tagging for Enhanced Relative Quantification of Unsaturated sn-Positional Isomers

Changes in the levels of lipid sn-positional isomers are associated with perturbation of the physiological environment within the biological system. Consequently, knowing the concentrations of these lipids holds significant importance for unraveling their involvement in disease diagnosis and pathological mechanisms. However, existing methods for lipid quantification often fall short in accuracy due to the structural diversity and isomeric forms of lipids. To address this challenge, we have developed an aziridine-based isobaric tag labeling strategy that allows (i) differentiation and (ii) enhanced relative quantification of lipid sn-positional isomers from distinct samples in a single run. The methodology enabled by aziridination, isobaric tag labeling, and lithiation has been applied to various phospholipids, enabling the determination of the sn-positions of fatty acyl chains and enhanced relative quantification. The analysis of Escherichia coli lipid extracts demonstrated the enhanced determination of the concentration ratios of lipid isomers by measuring the intensity ratios of mass reporters released from sn-positional diagnostic ions. Moreover, we applied the method to the analysis of human colon cancer plasma. Intriguingly, 17 PC lipid sn-positional isomers were identified and quantified simultaneously, and among them, 7 showed significant abundance changes in the colon cancer plasma, which can be used as potential plasma markers for diagnosis of human colon cancer.

Cholesterol 25-hydroxylase mediates neuroinflammation and neurodegeneration in a mouse model of tauopathy

Alzheimer's disease (AD) is characterized by amyloid plaques and neurofibrillary tangles, in addition to neuroinflammation and changes in brain lipid metabolism. 25-Hydroxycholesterol (25-HC), a known modulator of both inflammation and lipid metabolism, is produced by cholesterol 25-hydroxylase encoded by Ch25h expressed as a "disease-associated microglia" signature gene. However, whether Ch25h influences tau-mediated neuroinflammation and neurodegeneration is unknown. Here, we show that in the absence of Ch25h and the resultant reduction in 25-HC, there is strikingly reduced age-dependent neurodegeneration and neuroinflammation in the hippocampus and entorhinal/piriform cortex of PS19 mice, which express the P301S mutant human tau transgene. Transcriptomic analyses of bulk hippocampal tissue and single nuclei revealed that Ch25h deficiency in PS19 mice strongly suppressed proinflammatory signaling in microglia. Our results suggest a key role for Ch25h/25-HC in potentiating proinflammatory signaling to promote tau-mediated neurodegeneration. Ch25h may represent a novel therapeutic target for primary tauopathies, AD, and other neuroinflammatory diseases.

Evaluation of Exploratory Fluid Biomarker Results from a Phase 1 Senolytic Trial in Mild Alzheimer's Disease

Senescent cell accumulation contributes to the progression of age-related disorders including Alzheimer's disease (AD). Clinical trials evaluating senolytics, drugs that clear senescent cells, are underway, but lack standardized outcome measures. Our team recently published data from the first open-label trial to evaluate senolytics (dasatinib plus quercetin) in AD. After 12-weeks of intermittent treatment, we reported brain exposure to dasatinib, favorable safety and tolerability, and modest post-treatment changes in cerebrospinal fluid (CSF) inflammatory and AD biomarkers using commercially available assays. Herein, we present more comprehensive exploratory analyses of senolytic associated changes in AD relevant proteins, metabolites, lipids, and transcripts measured across blood, CSF, and urine. These analyses included mass spectrometry for precise quantification of amyloid beta (Aß) and tau in CSF; immunoassays to assess senescence associated secretory factors in plasma, CSF, and urine; mass spectrometry analysis of urinary metabolites and lipids in blood and CSF; and transcriptomic analyses relevant to chronic stress measured in peripheral blood cells. Levels of Aß and tau species remained stable. Targeted cytokine and chemokine analyses revealed treatment-associated increases in inflammatory plasma fractalkine and MMP-7 and CSF IL-6. Urinary metabolites remained unchanged. Modest treatment-associated lipid profile changes suggestive of decreased inflammation were observed both peripherally and centrally. Blood transcriptomic analysis indicated downregulation of inflammatory genes including FOS, FOSB, IL1β, IL8, JUN, JUNB, PTGS2. These data provide a foundation for developing standardized outcome measures across senolytic studies and indicate distinct biofluid-specific signatures that will require validation in future studies. ClinicalTrials.gov: NCT04063124.

Clinical advances in analytical profiling of signature lipids: implications for severe non-communicable and neurodegenerative diseases

BACKGROUND

Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts.

AIM OF THE REVIEW

The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.

Toward a More Comprehensive Approach for Dissolved Organic Matter Chemical Characterization Using an Orbitrap Fusion Tribrid Mass Spectrometer Coupled with Ion and Liquid Chromatography Techniques

Dissolved organic matter (DOM) represents one of the largest active organic carbon pools in the global carbon cycle. Although extensively studied, only <10% of DOM has been chemically characterized into individual dissolved compounds due to its molecular complexity. This study introduced a more comprehensive DOM characterization method by coupling both ion chromatography (IC) and liquid chromatography (LC) with high mass accuracy and resolution mass spectrometry. We presented a new on-the-fly mass calibration of the Orbitrap technique by utilizing the "lock mass" function in the Orbitrap Fusion Tribrid mass spectrometer (OT-FTMS), which assures high mass accuracy at every scan by a postcolumn introduction of internal labeled standards. With both IC and LC, tested unlabeled standards of amino acids, small peptides, and organic acids were consistently below 1.0 ppm mass error, giving the OT-FTMS the potential of reaching mass accuracy of the Fourier-transform ion cyclotron resonance mass spectrometer. In addition to mass accuracy, a pooled quality control sample (QC) was used to increase reproducibility by applying systematic error removal using random forest (SERRF). Using an untargeted mass spectrometry approach, estuarine DOM samples were analyzed by OT-FTMS coupled to IC in negative mode and LC in positive mode detection to cover a wide range of highly cationic to highly anionic molecules. As a proof of concept, we focused on elucidating the structures of three distinct DOM compound classes with varied acidities and basicities. In UPLC-OT-FTMS, a total of 915 compounds were detected. We putatively elucidated 44 small peptides and 33 deaminated peptides of these compounds. With IC-OT-FTMS, a total of 1432 compounds were detected. We putatively elucidated 20 peptides, 268 deaminated peptides, and 188 organic acids. Except for five compounds, all putatively elucidated compounds were uniquely detected in their corresponding chromatography technique. These results highlight the need for combining these two techniques to provide a more comprehensive method for DOM characterization. Application of the combined IC and LC techniques is not limited to DOM chemical characterization. It can analyze other complex compound mixtures, such as metabolites, and anthropogenic pollutants, such as pesticides and endocrine-disrupting chemicals, in environmental and biological samples.

Effects of dietary forage-to-concentrate ratio and forage type on milk phospholipids and fatty acid composition of polar lipids

The effects of grass silage and red clover silage on milk fatty acid (FA) composition are extensively studied, but little is known of their effects on minor lipid constituents of milk fat globule membrane. We investigated the effects of forage:concentrate (FC) ratio in grass silage-based diets and forage type (grass silage vs. red clover silage) on selected molecular species of milk phospholipids (PL) and the FA composition of PL. Ten multiparous Nordic Red cows were offered following dietary treatments: grass silage-based diets containing 70:30 (HG) or 30:70 (LG) FC ratio or a red clover silage-based diet (RC) comprising 50:50 FC ratio on a dry matter basis. The most abundant molecular species within the phosphatidylcholines was 16:0-18:1 phosphatidylcholine that was increased by 18% in HG compared with LG milk. Dietary treatments did not affect the relative proportion of 18:1-18:1+18:0-18:2 phosphatidylethanolamine that was the most prevalent species (ca. 44%-45%) in that class. We identified the d18:1-22:0 sphingomyelin as the most abundant sphingomyelin species that tended to increase in HG milk compared with LG. The FC ratio did not affect the relative proportions of saturated FA nor monounsaturated FA in PL, but the proportion of cis-9 18:1 was elevated in HG versus LG milk, whereas the proportion of 18:2n-6 was 50% higher in LG versus HG milk. The RC diet increased monounsaturated FA and 18:3n-3 levels in PL compared with grass silage-based diets and decreased the relative proportion of saturated FA. However, the RC diet did not affect the relative proportion of polyunsaturated FA in PL, although red clover silage typically increases the proportion of polyunsaturated FA in milk fat. This study provides valuable knowledge of the minor lipid components in milk on species level in relation to common feeding strategies in high-forage systems.

Accurate Clinical Detection of Vitamin D by Mass Spectrometry: A Review

Vitamin D deficiency is thought to be associated with a wide range of diseases, including diabetes, cancer, depression, neurodegenerative diseases, and cardiovascular and cerebrovascular diseases. This vitamin D deficiency is a global epidemic affecting both developing and developed countries and therefore qualitative and quantitative analysis of vitamin D in a clinical context is essential. Mass spectrometry has played an increasingly important role in the clinical analysis of vitamin D because of its accuracy, sensitivity, specificity, and the ability to detect multiple substances at the same time. Despite their many advantages, mass spectrometry-based methods are not without analytical challenges. Front-end and back-end challenges such as protein precipitation, analyte extraction, derivatization, mass spectrometer functionality, must be carefully considered to provide accurate and robust analysis of vitamin D through a well-designed approach with continuous control by internal and external quality control. Therefore, the aim of this review is to provide a comprehensive overview of the development of mass spectrometry methods for vitamin D accurate analysis, including emphasis on status markers, deleterious effects of biological matrices, derivatization reactions, effects of ionization sources, contribution of epimers, standardization of assays between laboratories.

Advances in identifying and managing emerging contaminants in aquatic ecosystems: Analytical approaches, toxicity assessment, transformation pathways, environmental fate, and remediation strategies

Emerging contaminants (ECs) are increasingly recognized as threats to human health and ecosystems. This review evaluates advanced analytical methods, particularly mass spectrometry, for detecting ECs and understanding their toxicity, transformation pathways, and environmental distribution. Our findings underscore the reliability of current techniques and the potential of upcoming methods. The adverse effects of ECs on aquatic life necessitate both in vitro and in vivo toxicity assessments. Evaluating the distribution and degradation of ECs reveals that they undergo physical, chemical, and biological transformations. Remediation strategies such as advanced oxidation, adsorption, and membrane bioreactors effectively treat EC-contaminated waters, with combinations of these techniques showing the highest efficacy. To minimize the impact of ECs, a proactive approach involving monitoring, regulations, and public education is vital. Future research should prioritize the refining of detection methods and formulation of robust policies for EC management.

Toward Omics-Scale Quantitative Mass Spectrometry Imaging of Lipids in Brain Tissue Using a Multiclass Internal Standard Mixture

Mass spectrometry imaging (MSI) has accelerated our understanding of lipid metabolism and spatial distribution in tissues and cells. However, few MSI studies have approached lipid imaging quantitatively and those that have focused on a single lipid class. We overcome this limitation by using a multiclass internal standard (IS) mixture sprayed homogeneously over the tissue surface with concentrations that reflect those of endogenous lipids. This enabled quantitative MSI (Q-MSI) of 13 lipid classes and subclasses representing almost 200 sum-composition lipid species using both MALDI (negative ion mode) and MALDI-2 (positive ion mode) and pixel-wise normalization of each lipid species in a manner analogous to that widely used in shotgun lipidomics. The Q-MSI approach covered 3 orders of magnitude in dynamic range (lipid concentrations reported in pmol/mm2) and revealed subtle changes in distribution compared to data without normalization. The robustness of the method was evaluated by repeating experiments in two laboratories using both timsTOF and Orbitrap mass spectrometers with an ∼4-fold difference in mass resolution power. There was a strong overall correlation in the Q-MSI results obtained by using the two approaches. Outliers were mostly rationalized by isobaric interferences or the higher sensitivity of one instrument for a particular lipid species. These data provide insight into how the mass resolving power can affect Q-MSI data. This approach opens up the possibility of performing large-scale Q-MSI studies across numerous lipid classes and subclasses and revealing how absolute lipid concentrations vary throughout and between biological tissues.

Lipids as Emerging Biomarkers in Neurodegenerative Diseases

Biomarkers are molecules that can be used to observe changes in an individual's biochemical or medical status and provide information to aid diagnosis or treatment decisions. Dysregulation in lipid metabolism in the brain is a major risk factor for many neurodegenerative disorders, including frontotemporal dementia, Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. Thus, there is a growing interest in using lipids as biomarkers in neurodegenerative diseases, with the anionic phospholipid bis(monoacylglycerol)phosphate and (glyco-)sphingolipids being the most promising lipid classes thus far. In this review, we provide a general overview of lipid biology, provide examples of abnormal lysosomal lipid metabolism in neurodegenerative diseases, and discuss how these insights might offer novel and promising opportunities in biomarker development and therapeutic discovery. Finally, we discuss the challenges and opportunities of lipid biomarkers and biomarker panels in diagnosis, prognosis, and/or treatment response in the clinic.

Multi-omics analyses reveal novel effects of PLCγ2 deficiency in the mouse brain

Phospholipase C gamma-2 (PLCγ2) catalyzes the hydrolysis of the membrane phosphatidylinositol-4,5-bisphosphate (PIP2) to form diacylglycerol (DAG) and inositol trisphosphate (IP3), which subsequently feed into numerous downstream signaling pathways. PLCG2 polymorphisms are associated with both reduced and increased risk of Alzheimer's disease (AD) and with longevity. In the brain, PLCG2 is highly expressed in microglia, where it is proposed to regulate phagocytosis, secretion of cytokines/chemokines, cell survival and proliferation. We analyzed the brains of three-month-old PLCγ2 knockout (KO), heterozygous (HET), and wild-type (WT) mice using multiomics approaches, including shotgun lipidomics, proteomics, and gene expression profiling, and immunofluorescence. Lipidomic analyses revealed sex-specific losses of total cerebrum PIP2 and decreasing trends of DAG content in KOs. In addition, PLCγ2 depletion led to significant losses of myelin-specific lipids and decreasing trends of myelin-enriched lipids. Consistent with our lipidomics results, RNA profiling revealed sex-specific changes in the expression levels of several myelin-related genes. Further, consistent with the available literature, gene expression profiling revealed subtle changes on microglia phenotype in mature adult KOs under baseline conditions, suggestive of reduced microglia reactivity. Immunohistochemistry confirmed subtle differences in density of microglia and oligodendrocytes in KOs. Exploratory proteomic pathway analyses revealed changes in KO and HET females compared to WTs, with over-abundant proteins pointing to mTOR signaling, and under-abundant proteins to oligodendrocytes. Overall, our data indicate that loss of PLCγ2 has subtle effects on brain homeostasis that may underlie enhanced vulnerability to AD pathology and aging via novel mechanisms in addition to regulation of microglia function.

An In Silico Database for Automated Feature Identification of High-Resolution Tandem Mass Spectrometry 13C-Trimethylation Enhancement Using Diazomethane (13C-TrEnDi)-Modified Lipid Data

13C-Trimethylation enhancement using diazomethane (13C-TrEnDi) is a chemical derivatization technique that uses 13C-labeled diazomethane to increase mass spectrometry (MS) signal intensities for phosphatidylcholine (PC) and phosphatidylethanolamine (PE) lipid classes, both of which are of major interest in biochemistry. In silico mass spectrometry databases have become mainstays in lipidomics experiments; however, 13C-TrEnDi-modified PC and PE species have altered m/z and fragmentation patterns from their native counterparts. To build a database of 13C-TrEnDi-modified PC and PE species, a lipid extract from nutritional yeast was derivatized and fragmentation spectra of modified PC and PE species were mined using diagnostic fragmentation filtering by searching 13C-TrEnDi-modified headgroups with m/z 199 (PC) and 202 (PE). Identities of 25 PC and 10 PE species were assigned after comparing to predicted masses from the Lipid Maps Structure Database with no false positive identifications observed; neutral lipids could still be annotated after derivatization. Collision energies from 16 to 52 eV were examined, resulting in three additional class-specific fragment ions emerging, as well as a combined sn-1/sn-2 fragment ion, allowing sum-composition level annotations to be assigned. Using the Lipid Blast templates, a NIST-compatible 13C-TrEnDi database was produced based on fragmentation spectra observed at 36 eV and tested on HEK 293T cell lipid extracts, identifying 47 PC and 24 PE species, representing a 1.8-fold and 2.2-fold increase in annotations, respectively. The 13C-TrEnDi database is freely available, MS vendor-independent, and widely compatible with MS data processing pipelines, increasing the throughput and accessibility of TrEnDi for lipidomics applications.

Total Lipid Extracts of Honeybee Drone Larvae Are Modulated by Extraction Temperature and Display Consistent Anti-Inflammatory Potential

Honeybee drone larvae are male bees that develop from unfertilized eggs and play a role in colony reproduction. The nutritional value of honeybee drone larvae is due to their high protein, lipid, and other nutrient contents, making them a profitable food source for humans in some cultures. Drone larvae lipids (DLLs) contribute to drone development; however, few studies have explored their substantial compositions and bioactive functions. In this study, we carried out DLL lipidomics analysis using UPLC-Q-Exactive-Orbitrap-MS prior to in vitro anti-inflammatory activity analysis. The results highlighted the importance of the extraction temperature on the DLL composition. A total of 21 lipids were found in the DLL extract, mostly categorized into five groups: nine phospholipids, three sphingolipids, two neutral lipids, one plant glycoglycerolipid, four lipid acyl, and others. Drying extraction at -20 °C produced more sphingolipids, phospholipids, and unsaturated fatty acids. Of 37 fatty acids, 18 were displayed at -20 °C degrees, as shown by GC-MS quantitative analysis. Myristic (246.99 ± 13.19 μg/g), palmitic (1707.87 ± 60.53 μg/g), stearic (852.32 ± 24.17 μg/g), and oleic (2463.03 ± 149.61 μg/g) acids were the predominant fatty acids. Furthermore, we examined the significant in vitro anti-inflammatory effects of DLL (-20 °C) using lipopolysaccharide (LPS)-challenged RAW264.7 cells. Nitric oxide (NO) and reactive oxygen (ROS) production and mRNA expression of IL-6, IL-10, COX-2, and iNOS were significantly decreased, demonstrating the anti-inflammatory function of DLL. Overall, this study provided insight into the lipid composition of DLL, revealed the influence of temperature, and explored the functionality of DLL (-20 °C), allowing for further application of DLLs as functional foods.

Nano-Structural Superwetting Surfaces for Highly Reliable On-Site Detection of Bisphenol A

In the domain of big data geographic screening for environmental pollutants, the expeditious dissemination of testing results to environmental investigation professionals is pivotal in facilitating comprehensive analysis and the implementation of more efficacious strategies for managing environmental issues. However, this endeavor can prove to be particularly arduous when conducting examinations in remote, resource-scarce rural areas and field environments, where deficient infrastructure often emerges as the principal impediment to unimpeded environmental monitoring. Therefore, the development of a reliable and portable monitoring strategy with the ability to analyze large amounts of data is highly required. Here, a deep-learning (DL)-assisted portable sensing strategy was developed based on thermal and pH dual-responsive nano-structural superwetting surfaces, for highly reliable, quick, and field monitoring of environmental pollutants. In our experiment, bisphenol A (BPA) was selected as the representative pollute. The achieved limit of detection, attaining a remarkably low value of 1.05 μM, unequivocally adhered to stringent international testing standards for evaluating the migration of BPA in thermal paper. Based on a DL image classification algorithm, highly precise predictions regarding the migration of BPA concentration were achieved, with an accuracy rate exceeding 99%. Furthermore, it successfully facilitated automated and exceedingly reliable monitoring of the migration of BPA from thermal paper within the principal provinces of thermal paper production in China. This strategy engenders the potential to establish correlations between environmental pollutant concentrations in specific regions and the prevalence of certain human ailments.

Lipocalin 2 regulates mitochondrial phospholipidome remodeling, dynamics, and function in brown adipose tissue in male mice

Mitochondrial function is vital for energy metabolism in thermogenic adipocytes. Impaired mitochondrial bioenergetics in brown adipocytes are linked to disrupted thermogenesis and energy balance in obesity and aging. Phospholipid cardiolipin (CL) and phosphatidic acid (PA) jointly regulate mitochondrial membrane architecture and dynamics, with mitochondria-associated endoplasmic reticulum membranes (MAMs) serving as the platform for phospholipid biosynthesis and metabolism. However, little is known about the regulators of MAM phospholipid metabolism and their connection to mitochondrial function. We discover that LCN2 is a PA binding protein recruited to the MAM during inflammation and metabolic stimulation. Lcn2 deficiency disrupts mitochondrial fusion-fission balance and alters the acyl-chain composition of mitochondrial phospholipids in brown adipose tissue (BAT) of male mice. Lcn2 KO male mice exhibit an increase in the levels of CLs containing long-chain polyunsaturated fatty acids (LC-PUFA), a decrease in CLs containing monounsaturated fatty acids, resulting in mitochondrial dysfunction. This dysfunction triggers compensatory activation of peroxisomal function and the biosynthesis of LC-PUFA-containing plasmalogens in BAT. Additionally, Lcn2 deficiency alters PA production, correlating with changes in PA-regulated phospholipid-metabolizing enzymes and the mTOR signaling pathway. In conclusion, LCN2 plays a critical role in the acyl-chain remodeling of phospholipids and mitochondrial bioenergetics by regulating PA production and its function in activating signaling pathways.

Simultaneous determination of tramadol and paracetamol in human plasma using LC-MS/MS and application in bioequivalence study of -fixed-dose combination

The study aimed to develop a sensitive and high-throughput liquid chromatography coupled with tandem mass spectrometry method to quantify concentrations of tramadol and paracetamol simultaneously in human plasma. Sample preparation involved single-step protein precipitation using methanol and two deuterated internal standards, tramadol D6 and paracetamol D4. Agilent Poroshell 120 EC-C18 (100 × 2.1 mm, 2.1 µm) analytical column was employed to achieve chromatographic separation. Detection was in positive ion multiple reaction monitoring mode. A tailing factor (Tf) of <1.2, separation factor (K prime) of >1.5 from the column dead time and signal-to-noise (S/N) ratio >10, were obtained for analytes and internal standards. The standard curve was linear over the concentration range of 2.5-500.00 ng/mL for tramadol and 0.025-20.00 μg/mL for paracetamol. A small injection volume of 1 µL, low flow rate of 440 µL/min and short analysis time of 3.5 min reduced the solvent consumption, analysis cost and system contamination. The results of method validation parameters fulfilled the acceptance criteria of bioanalytical guidelines. The method was successfully applied to a bioequivalence study of fixed-dose combination products of tramadol and paracetamol in Malaysian healthy subjects.

Accurate Sphingolipid Quantification Reducing Fragmentation Bias by Nonlinear Models

Quantitative sphingolipid analysis is crucial for understanding the roles of these bioactive molecules in various physiological and pathological contexts. Molecular sphingolipid species are typically quantified using sphingoid base-derived fragments relative to a class-specific internal standard. However, the commonly employed "one standard per class" strategy fails to account for fragmentation differences presented by the structural diversity of sphingolipids. To address this limitation, we developed a novel approach for quantitative sphingolipid analysis. This approach utilizes fragmentation models to correct for structural differences and thus overcomes the limitations associated with using a limited number of standards for quantification. Importantly, our method is independent of the internal standard, instrumental setup, and collision energy. Furthermore, we integrated this method into a user-friendly KNIME workflow. The validation results illustrate the effectiveness of our approach in accurately quantifying ceramide subclasses from various biological matrices. This breakthrough opens up new avenues for exploring sphingolipid metabolism and gaining insights into its implications.

Improving Quantitative Accuracy in Nontargeted Lipidomics by Evaluating Adduct Formation

For large-scale lipidomic analyses, accurate and reproducible quantification of endogenous lipids is crucial for comparing results within and across studies. Many lipids present in liquid chromatography-electrospray ionization-mass spectrometry form various adducts with buffer components. The mechanisms and conditions that dictate adduct formation are still poorly understood. In a positive mode, neutral lipids like mono-, di-, and triacylglycerides and cholesteryl esters typically generate [M + NH4]+ adduct ions, although [M + Na]+, [M + K]+, and other (more complex) species can also be significantly abundant in MS1 precursor ion spectra. Variations in the ratios of these adducts (within and between matrices) can lead to dramatic inaccuracies during quantification. Here, we examine 48 unique diacylglycerol (DAG) species across 2366 mouse samples for eight matrix-specific data sets of plasma, liver, kidney, brain, heart muscle, gastrocnemius muscle, gonadal, and inguinal fat. Typically, no single adduct ion species accounted for more than 60% of the total observed abundance across each data set. Even within a single matrix, DAGs showed a high variability of adduct ratios. The ratio of [M + NH4]+ adduct ions was increased for longer-chain DAGs and for polyunsaturated DAGs, at the expense of reduced ratios of [M + Na]+ adducts. When using three deuterated internal DAG standards, we found that absolute concentrations were estimated with up to 70% error when only one adduct ion was used instead of all adducts combined. Importantly, when combining [M + NH4]+ and [M + Na]+ adduct ions, quantification results were within 5% accuracy compared to all adduct ions combined. Additional variance can be caused by other factors, such as instrument conditions or matrix effects.

The expanding organelle lipidomes: current knowledge and challenges

Lipids in cell membranes and subcellular compartments play essential roles in numerous cellular processes, such as energy production, cell signaling and inflammation. A specific organelle lipidome is characterized by lipid synthesis and metabolism, intracellular trafficking, and lipid homeostasis in the organelle. Over the years, considerable effort has been directed to the identification of the lipid fingerprints of cellular organelles. However, these fingerprints are not fully characterized due to the large variety and structural complexity of lipids and the great variability in the abundance of different lipid species. The process becomes even more challenging when considering that the lipidome differs in health and disease contexts. This review summarizes the information available on the lipid composition of mammalian cell organelles, particularly the lipidome of the nucleus, mitochondrion, endoplasmic reticulum, Golgi apparatus, plasma membrane and organelles in the endocytic pathway. The lipid compositions of extracellular vesicles and lamellar bodies are also described. In addition, several examples of subcellular lipidome dynamics under physiological and pathological conditions are presented. Finally, challenges in mapping organelle lipidomes are discussed.

Lipids in Extracellular Vesicles: What Can Be Learned about Membrane Structure and Function?

Extracellular vesicles, such as exosomes, can be used as interesting models to study the structure and function of biological membranes as these vesicles contain only one membrane (i.e., one lipid bilayer). In addition to lipids, they contain proteins, nucleic acids, and various other molecules. The lipid composition of exosomes is here compared to HIV particles and detergent-resistant membranes, which also have a high content of sphingolipids, cholesterol, and phosphatidylserine (PS). We discuss interactions between the lipids in the two bilayers, and especially those between PS 18:0/18:1 in the inner leaflet and the very-long-chain sphingolipids in the outer leaflet, and the importance of cholesterol for these interactions. We also briefly discuss the involvement of ether-linked phospholipids (PLs) in such lipid raft-like structures, and the possible involvement of these and other lipid classes in the formation of exosomes. The urgent need to improve the quality of quantitative lipidomic studies is highlighted.

Chemical QuantArray: A Quantitative Tool for Mass Spectrometry Imaging

Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) is a powerful analytical technique that provides spatially preserved detection and quantification of analytes in tissue specimens. However, clinical translation still requires improved throughput, precision, and accuracy. To accomplish this, we created "Chemical QuantArray", a gelatin tissue microarray (TMA) mold filled with serial dilutions of isotopically labeled endogenous metabolite standards. The mold is then cryo-sectioned onto a tissue homogenate to produce calibration curves. To improve precision and accuracy, we automatically remove pixels outside of each TMA well and investigated several intensity normalizations, including the utilization of a second stable isotope internal standard (IS). Chemical QuantArray enables the quantification of several endogenous metabolites over a wide dynamic range and significantly improve over current approaches. The technique reduces the space needed on the MALDI slides for calibration standards by approximately 80%. Furthermore, removal of empty pixels and normalization to an internal standard or matrix peak provided precision (<20% RSD) and accuracy (<20% DEV). Finally, we demonstrate the applicability of Chemical QuantArray by quantifying multiple purine metabolites in 14 clinical tumor specimens using a single MALDI slide. Chemical QuantArray improves the analytical characteristics and practical feasibility of MALDI-MSI metabolite quantification in clinical and translational applications.

Scrutinizing different ionization responses of polar lipids in a reversed-phase gradient by implementing a counter-gradient

Lipidomics studies strive for a comprehensive identification and quantification of lipids. While reversed phase (RP) liquid chromatography (LC) coupled to high resolution mass spectrometry (MS) offers unrivalled selectivity and thus is the preferred method for lipid identification, accurate lipid quantification remains challenging. The widely adopted one-point lipid class specific quantification (one internal standard per lipid class) suffers from the fact that ionization of internal standard and target lipid occurs under different solvent composition as a consequence of chromatographic separation. To address this issue, we established a dual flow injection and chromatography setup that allows to control solvent conditions during ionization enabling isocratic ionization while running a RP gradient through the use of a counter-gradient. Using this dual LC pump platform, we investigated the impact of solvent conditions within a RP gradient on ionization response and arising quantification biases. Our results confirmed that changing solvent composition significantly influences ionization response. Quantification of human plasma (SRM 1950) lipids under gradient and isocratic ionization conditions further confirmed these findings as significant differences between the two conditions were found for the majority of lipids. While the quantity of sphingomyelins with >40 C atoms was consistently overestimated under gradient ionization, isocratic ionization improved their recovery compared to consensus values. However, the limitation of consensus values was demonstrated as overall only small changes in z-score were observed because of high uncertainties of the consensus values. Furthermore, we observed a trueness bias between gradient and isocratic ionization when quantifying a panel of lipid species standards which is highly dependent on lipid class and ionization mode. Uncertainty calculations under consideration of the trueness bias as RP gradient uncertainty revealed that especially ceramides with >40 C atoms had a high bias leading to total combined uncertainties of up to 54%. The assumption of isocratic ionization significantly decreases total measurement uncertainty and highlights the importance of studying the trueness bias introduced by a RP gradient to reduce quantification uncertainty.

Deep-profiling of phospholipidome via rapid orthogonal separations and isomer-resolved mass spectrometry

A lipidome comprises thousands of lipid species, many of which are isomers and isobars. Liquid chromatography-tandem mass spectrometry (LC-MS/MS), although widely used for lipidomic profiling, faces challenges in differentiating lipid isomers. Herein, we address this issue by leveraging the orthogonal separation capabilities of hydrophilic interaction liquid chromatography (HILIC) and trapped ion mobility spectrometry (TIMS). We further integrate isomer-resolved MS/MS methods onto HILIC-TIMS, which enable pinpointing double bond locations in phospholipids and sn-positions in phosphatidylcholine. This system profiles phospholipids at multiple structural levels with short analysis time (<10 min per LC run), high sensitivity (nM detection limit), and wide coverage, while data analysis is streamlined using a home-developed software, LipidNovelist. Notably, compared to our previous report, the system doubles the coverage of phospholipids in bovine liver and reveals uncanonical desaturation pathways in RAW 264.7 macrophages. Relative quantitation of the double bond location isomers of phospholipids and the sn-position isomers of phosphatidylcholine enables the phenotyping of human bladder cancer tissue relative to normal control, which would be otherwise indistinguishable by traditional profiling methods. Our research offers a comprehensive solution for lipidomic profiling and highlights the critical role of isomer analysis in studying lipid metabolism in both healthy and diseased states.

Lipidomics Workflow for Analyzing Lipid Profiles Using Multiple Reaction Monitoring (MRM) in Liver Homogenate of Mice with Non-alcoholic Steatohepatitis (NASH)

Non-alcoholic steatohepatitis (NASH) is a condition characterized by inflammation and hepatic injury/fibrosis caused by the accumulation of ectopic fats in the liver. Recent advances in lipidomics have allowed the identification and characterization of lipid species and have revealed signature patterns of various diseases. Here, we describe a lipidomics workflow to assess the lipid profiles of liver homogenates taken from a NASH mouse model. The protocol described below was used to extract and analyze the metabolites from the livers of mice with NASH by liquid chromatography-mass spectrometry (LC-MS); however, it can be applied to other tissue homogenate samples. Using this method, over 1,000 species of lipids from five classes can be analyzed in a single run on the LC-MS. Also, partial elucidation of the identity of neutral lipid (triacylglycerides and diacylglycerides) aliphatic chains can be performed with this simple LC-MS setup. Key features Over 1,000 lipid species (sphingolipids, cholesteryl esters, neutral lipids, phospholipids, fatty acids) are analyzed in one run. Analysis of liver lipids in non-alcoholic steatohepatitis (NASH) mouse model. Normal-phase chromatography coupled to a triple quadrupole mass spectrometer.

Central nervous system sulfatide deficiency as a causal factor for bladder disorder in Alzheimer's disease

BACKGROUND

Despite being a brain disorder, Alzheimer's disease (AD) is often accompanied by peripheral organ dysregulations (e.g., loss of bladder control in late-stage AD), which highly rely on spinal cord coordination. However, the causal factor(s) for peripheral organ dysregulation in AD remain elusive.

METHODS

The central nervous system (CNS) is enriched in lipids. We applied quantitative shotgun lipidomics to determine lipid profiles of human AD spinal cord tissues. Additionally, a CNS sulfatide (ST)-deficient mouse model was used to study the lipidome, transcriptome and peripheral organ phenotypes of ST loss.

RESULTS

We observed marked myelin lipid reduction in the spinal cord of AD subjects versus cognitively normal individuals. Among which, levels of ST, a myelin-enriched lipid class, were strongly and negatively associated with the severity of AD. A CNS myelin-specific ST-deficient mouse model was used to further identify the causes and consequences of spinal cord lipidome changes. Interestingly, ST deficiency led to spinal cord lipidome and transcriptome profiles highly resembling those observed in AD, characterized by decline of multiple myelin-enriched lipid classes and enhanced inflammatory responses, respectively. These changes significantly disrupted spinal cord function and led to substantial enlargement of urinary bladder in ST-deficient mice.

CONCLUSIONS

Our study identified CNS ST deficiency as a causal factor for AD-like lipid dysregulation, inflammation response and ultimately the development of bladder disorders. Targeting to maintain ST levels may serve as a promising strategy for the prevention and treatment of AD-related peripheral disorders.

Regulation of astrocyte lipid metabolism and ApoE secretionby the microglial oxysterol, 25-hydroxycholesterol

Neuroinflammation, a major hallmark of Alzheimer's disease and several other neurological and psychiatric disorders, is often associated with dysregulated cholesterol metabolism. Relative to homeostatic microglia, activated microglia express higher levels of Ch25h, an enzyme that hydroxylates cholesterol to produce 25-hydroxycholesterol (25HC). 25HC is an oxysterol with interesting immune roles stemming from its ability to regulate cholesterol metabolism. Since astrocytes synthesize cholesterol in the brain and transport it to other cells via ApoE-containing lipoproteins, we hypothesized that secreted 25HC from microglia may influence lipid metabolism as well as extracellular ApoE derived from astrocytes. Here, we show that astrocytes take up externally added 25HC and respond with altered lipid metabolism. Extracellular levels of ApoE lipoprotein particles increased after treatment of astrocytes with 25HC without an increase in Apoe mRNA expression. In mouse astrocytes-expressing human ApoE3 or ApoE4, 25HC promoted extracellular ApoE3 better than ApoE4. Increased extracellular ApoE was due to elevated efflux from increased Abca1 expression via LXRs as well as decreased lipoprotein reuptake from suppressed Ldlr expression via inhibition of SREBP. 25HC also suppressed expression of Srebf2, but not Srebf1, leading to reduced cholesterol synthesis in astrocytes without affecting fatty acid levels. We further show that 25HC promoted the activity of sterol-o-acyl transferase that led to a doubling of the amount of cholesteryl esters and their concomitant storage in lipid droplets. Our results demonstrate an important role for 25HC in regulating astrocyte lipid metabolism.

Accurate quantification of TAGs to identify adulteration of edible oils by ultra-high performance liquid chromatography-quadrupole-time of flight-tandem mass spectrometry

Edible oils play important roles in biological functions, and triacylglycerols (TAGs) in edible oils are complex mixtures. This makes accurate TAGs quantitation quite difficult that bring economically motivated food adulteration. Herein, we demonstrated a strategy for accurate quantification of TAGs in edible oils, which could be applied in identification of olive oil adulteration. The results showed that the proposed strategy could significantly improve the accuracy of TAG content determination, reduce the relative error of fatty acids (FAs) content determination, and present a wider accurate quantitative range than that of gas chromatography-flame ionization detection. Most important, this strategy coupled with principal component analysis could be used to identify adulteration of high-priced olive oil with cheaper soybean oils, rapeseed oils or camellia oils at a lower concentration of 2%. These findings indicated that the proposed strategy could be regarded as a potential method for edible oils quality and authenticity analysis.

qShot MALDI analysis: A rapid, simple, convenient, and reliable quantitative phospholipidomics approach using MALDI-TOF/MS

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI/MS) has potential applications in the qualitative analysis of phospholipids (PLs). However, its capability for quantitative analysis is limited by the unavailability and/or high cost of isotope-labeled internal standards (interSTDs, e.g., 1-oleoyl (d7)-2-hydroxy-sn-glycero-3-phosphocholine, 1-pentadecanoyl-2-oleoyl (d7)-sn-glycero-3-phosphocholine). This study investigated and validated whether only two PL interSTDs could be used to normalize the entire PL species in a complex bio-lipid background (i.e., urinary lipid extracts). The normalized intensities of PL ionization standards (ionSTDs) were found to have better linear regressions (R² > 0.984 for all PL subcategories) than those of traditional methods, such as total ion current and matrix-peak normalization methods. Furthermore, the intra-day precision of all the analyte concentrations after normalizing using our ionSTD method was superior to those of traditional methods. The inter-day precision of all the negatively charged analytes also differed statistically between our ionSTD and the two traditional methods. Meanwhile, a comparison of the three normalization methods revealed that the precision of all the positive analytes using the ionSTD method was comparable. Consequently, a cost-effective, fast, simple, convenient, and reliable quantitative method, defined as "qShot MALDI analysis," was developed to analyze PLs that could potentially be applied in clinical biomarker screening, especially in a negative mode.

Omic-Scale High-Throughput Quantitative LC-MS/MS Approach for Circulatory Lipid Phenotyping in Clinical Research

Lipid analysis at the molecular species level represents a valuable opportunity for clinical applications due to the essential roles that lipids play in metabolic health. However, a comprehensive and high-throughput lipid profiling remains challenging given the lipid structural complexity and exceptional diversity. Herein, we present an 'omic-scale targeted LC-MS/MS approach for the straightforward and high-throughput quantification of a broad panel of complex lipid species across 26 lipid (sub)classes. The workflow involves an automated single-step extraction with 2-propanol, followed by lipid analysis using hydrophilic interaction liquid chromatography in a dual-column setup coupled to tandem mass spectrometry with data acquisition in the timed-selective reaction monitoring mode (12 min total run time). The analysis pipeline consists of an initial screen of 1903 lipid species, followed by high-throughput quantification of robustly detected species. Lipid quantification is achieved by a single-point calibration with 75 isotopically labeled standards representative of different lipid classes, covering lipid species with diverse acyl/alkyl chain lengths and unsaturation degrees. When applied to human plasma, 795 lipid species were measured with median intra- and inter-day precisions of 8.5 and 10.9%, respectively, evaluated within a single and across multiple batches. The concentration ranges measured in NIST plasma were in accordance with the consensus intervals determined in previous ring-trials. Finally, to benchmark our workflow, we characterized NIST plasma materials with different clinical and ethnic backgrounds and analyzed a sub-set of sera (n = 81) from a clinically healthy elderly population. Our quantitative lipidomic platform allowed for a clear distinction between different NIST materials and revealed the sex-specificity of the serum lipidome, highlighting numerous statistically significant sex differences.

Guiding the choice of informatics software and tools for lipidomics research applications

Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.

From fundamentals in calibration to modern methodologies: A tutorial for small molecules quantification in liquid chromatography-mass spectrometry bioanalysis

Over the last two decades, liquid chromatography coupled to mass-spectrometry (LC‒MS) has become the gold standard to perform qualitative and quantitative analyses of small molecules. When quantitative analysis is developed, an analyst usually refers to international guidelines for analytical method validation. In this context, the design of calibration curves plays a key role in providing accurate results. During recent years and along with instrumental advances, strategies to build calibration curves have dramatically evolved, introducing innovative approaches to improve quantitative precision and throughput. For example, when a labeled standard is available to be spiked directly into the study sample, the concentration of the unlabeled analog can be easily determined using the isotopic pattern deconvolution or the internal calibration approach, eliminating the need for multipoint calibration curves. This tutorial aims to synthetize the advances in LC‒MS quantitative analysis for small molecules in complex matrices, going from fundamental aspects in calibration to modern methodologies and applications. Different work schemes for calibration depending on the sample characteristics (analyte and matrix nature) are distinguished and discussed. Finally, this tutorial outlines the importance of having international guidelines for analytical method validation that agree with the advances in calibration strategies and analytical instrumentation.

Recent Advances in Gas-phase Ion/Ion Chemistry for Lipid Analysis

Gas-phase ion/ion reactions can be used to alter analyte ion-types for subsequent dissociation both quickly and efficiently without the need for altering analyte ionization conditions. This capability can be particularly useful when the ion-type that is most efficiently generated by the ionization method at hand does not provide the structural information of interest using available dissociation methods. This situation often arises in the analysis of lipids, which constitute a diverse array of chemical species with many possibilities for isomers. Gas-phase ion/ion reactions have been demonstrated to be capable of enhancing the ability of tandem mass spectrometry to characterize the structures of various lipid classes. This review summarizes progress to date in the application of gas-phase ion/ion reactions to lipid structural characterization.

Positive Correlation of Triacylglycerols with Increased Chain Length and Unsaturation with ω-O-Acylceramide and Ceramide-NP as Well as Acidic pH in the Skin Surface of Healthy Korean Adults

Triacylglycerols (TG) play an important role in skin homeostasis including the synthesis of ω-O-acylceramides (acylCER) required for skin barrier formation by providing linoleic acid (C18:2n6). However, the overall relationships of TG species with various ceramides (CER) including CER-NP, the most abundant CER, ω-O-acylCER, and another acylCER, 1-O-acylCER in human SC, remain unclear. Therefore, we investigated these relationships and their influence on skin health status in healthy Korean adults. Twelve CER subclasses including two ω-O-acylCER and two 1-O-acylCER were identified with CER-NP consisting of approximately half of the total CER. The ω-O-acylCER species exhibited positive relationships with TG 52:4 and TG 54:2 containing C18:2, while interestingly, 1-O-acylCER containing ester-linked C14:0 and C16:0 demonstrated positive relationships with TG 46-50 including C14:0 and C16:0, respectively. In addition, CER-NP and CER-NH showed positive correlations with TG 52-54 containing C18:2 or C18:3. A lipid pattern with higher levels of CER including CER-NP and ω-O-acylCER with TG 54 and TG with 5-6 double bonds was related to good skin health status, especially with acidic skin pH. Collectively, TG with increased chain length and unsaturation seemed to improve CER content, and profiles such as higher acylCER and CER-NP improved skin health status by fortifying skin barrier structure.

Sulfatide Deficiency, an Early Alzheimer's Lipidomic Signature, Causes Brain Ventricular Enlargement in the Absence of Classical Neuropathological Hallmarks

Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive memory loss and a decline in activities of daily life. Ventricular enlargement has been associated with worse performance on global cognitive tests and AD. Our previous studies demonstrated that brain sulfatides, myelin-enriched lipids, are dramatically reduced in subjects at the earliest clinically recognizable AD stages via an apolipoprotein E (APOE)-dependent and isoform-specific process. Herein, we provided pre-clinical evidence that sulfatide deficiency is causally associated with brain ventricular enlargement. Specifically, taking advantage of genetic mouse models of global and adult-onset sulfatide deficiency, we demonstrated that sulfatide losses cause ventricular enlargement without significantly affecting hippocampal or whole brain volumes using histological and magnetic resonance imaging approaches. Mild decreases in sulfatide content and mild increases in ventricular areas were also observed in human APOE4 compared to APOE2 knock-in mice. Finally, we provided Western blot and immunofluorescence evidence that aquaporin-4, the most prevalent aquaporin channel in the central nervous system (CNS) that provides fast water transportation and regulates cerebrospinal fluid in the ventricles, is significantly increased under sulfatide-deficient conditions, while other major brain aquaporins (e.g., aquaporin-1) are not altered. In short, we unraveled a novel and causal association between sulfatide deficiency and ventricular enlargement. Finally, we propose putative mechanisms by which sulfatide deficiency may induce ventricular enlargement.

Phospholipid imbalance impairs autophagosome completion

Autophagy, a conserved eukaryotic intracellular catabolic pathway, maintains cell homeostasis by lysosomal degradation of cytosolic material engulfed in double membrane vesicles termed autophagosomes, which form upon sealing of single-membrane cisternae called phagophores. While the role of phosphatidylinositol 3-phosphate (PI3P) and phosphatidylethanolamine (PE) in autophagosome biogenesis is well-studied, the roles of other phospholipids in autophagy remain rather obscure. Here we utilized budding yeast to study the contribution of phosphatidylcholine (PC) to autophagy. We reveal for the first time that genetic loss of PC biosynthesis via the CDP-DAG pathway leads to changes in lipid composition of autophagic membranes, specifically replacement of PC by phosphatidylserine (PS). This impairs closure of the autophagic membrane and autophagic flux. Consequently, we show that choline-dependent recovery of de novo PC biosynthesis via the CDP-choline pathway restores autophagosome formation and autophagic flux in PC-deficient cells. Our findings therefore implicate phospholipid metabolism in autophagosome biogenesis.

High Throughput LC-MS Platform for Large Scale Screening of Bioactive Polar Lipids in Human Plasma and Serum

Lipids play a key role in many biological processes, and their accurate measurement is critical to unraveling the biology of diseases and human health. A high throughput HILIC-based (LC-MS) method for the semiquantitative screening of over 2000 lipids, based on over 4000 MRM transitions, was devised to produce an accessible and robust lipidomic screen for phospholipids in human plasma/serum. This methodology integrates many of the advantages of global lipid analysis with those of targeted approaches. Having used the method as an initial "wide class" screen, it can then be easily adapted for a more targeted analysis and quantification of key, dysregulated lipids. Robustness was assessed using 1550 continuous injections of plasma extracts onto a single column and via the evaluation of columns from 5 different batches of stationary phase. Initial screens in positive (239 lipids, 431 MRM transitions) and negative electrospray ionization (ESI) mode (232 lipids, 446 MRM transitions) were assessed for reproducibility, sensitivity, and dynamic range using analysis times of 8 min. The total number of lipids monitored using these screening methods was 433 with an overlap of 38 lipids in both modes. A polarity switching method for accurate quantification, using the same LC conditions, was assessed for intra- and interday reproducibility, accuracy, dynamic range, stability, carryover, dilution integrity, and matrix interferences and found to be acceptable. This polarity switching method was then applied to lipids important in the stratification of human prostate cancer samples.

Measurement of lipid flux to advance translational research: evolution of classic methods to the future of precision health

Over the past 70 years, the study of lipid metabolism has led to important discoveries in identifying the underlying mechanisms of chronic diseases. Advances in the use of stable isotopes and mass spectrometry in humans have expanded our knowledge of target molecules that contribute to pathologies and lipid metabolic pathways. These advances have been leveraged within two research paths, leading to the ability (1) to quantitate lipid flux to understand the fundamentals of human physiology and pathology and (2) to perform untargeted analyses of human blood and tissues derived from a single timepoint to identify lipidomic patterns that predict disease. This review describes the physiological and analytical parameters that influence these measurements and how these issues will propel the coming together of the two fields of metabolic tracing and lipidomics. The potential of data science to advance these fields is also discussed. Future developments are needed to increase the precision of lipid measurements in human samples, leading to discoveries in how individuals vary in their production, storage, and use of lipids. New techniques are critical to support clinical strategies to prevent disease and to identify mechanisms by which treatments confer health benefits with the overall goal of reducing the burden of human disease.

Personalized tracking of how lipid (fat) metabolism changes over time could lead to improvements in the diagnosis and treatment of several diseases. Elizabeth Parks and colleagues from the University of Missouri, Columbia, USA, discuss the ways in which researchers use stable isotope labeling to monitor the kinetics of fatty acids and other lipids in the body. Usually, lipid quantities are measured only at a single timepoint, however the tracking of lipid turnover over time provides further diagnostic information. Aided by new techniques such as high-throughput mass spectrometry and machine learning, researchers are now able to continuously map total lipid contents in individual patients. The transition of measurements of lipid flux from the research laboratory to the doctor’s office will likely play a role in a new era of precision medicine.

Lipidomics-Assisted GWAS (lGWAS) Approach for Improving High-Temperature Stress Tolerance of Crops

High-temperature stress (HT) over crop productivity is an important environmental factor demanding more attention as recent global warming trends are alarming and pose a potential threat to crop production. According to the Sixth IPCC report, future years will have longer warm seasons and frequent heat waves. Thus, the need arises to develop HT-tolerant genotypes that can be used to breed high-yielding crops. Several physiological, biochemical, and molecular alterations are orchestrated in providing HT tolerance to a genotype. One mechanism to counter HT is overcoming high-temperature-induced membrane superfluidity and structural disorganizations. Several HT lipidomic studies on different genotypes have indicated the potential involvement of membrane lipid remodelling in providing HT tolerance. Advances in high-throughput analytical techniques such as tandem mass spectrometry have paved the way for large-scale identification and quantification of the enormously diverse lipid molecules in a single run. Physiological trait-based breeding has been employed so far to identify and select HT tolerant genotypes but has several disadvantages, such as the genotype-phenotype gap affecting the efficiency of identifying the underlying genetic association. Tolerant genotypes maintain a high photosynthetic rate, stable membranes, and membrane-associated mechanisms. In this context, studying the HT-induced membrane lipid remodelling, resultant of several up-/down-regulations of genes and post-translational modifications, will aid in identifying potential lipid biomarkers for HT tolerance/susceptibility. The identified lipid biomarkers (LIPIDOTYPE) can thus be considered an intermediate phenotype, bridging the gap between genotype–phenotype (genotype–LIPIDOTYPE–phenotype). Recent works integrating metabolomics with quantitative genetic studies such as GWAS (mGWAS) have provided close associations between genotype, metabolites, and stress-tolerant phenotypes. This review has been sculpted to provide a potential workflow that combines MS-based lipidomics and the robust GWAS (lipidomics assisted GWAS-lGWAS) to identify membrane lipid remodelling related genes and associations which can be used to develop HS tolerant genotypes with enhanced membrane thermostability (MTS) and heat stable photosynthesis (HP).

MAVEN2: An Updated Open-Source Mass Spectrometry Exploration Platform

MAVEN, an open-source software program for analysis of LC-MS metabolomics data, was originally released in 2010. As mass spectrometry has advanced in the intervening years, MAVEN has been periodically updated to reflect this advancement. This manuscript describes a major update to the program, MAVEN2, which supports LC-MS/MS analysis of metabolomics and lipidomics samples. We have developed algorithms to support MS/MS spectral matching and efficient search of large-scale fragmentation libraries. We explore the ability of our approach to separate authentic from spurious metabolite identifications using a set of standards spiked into water and yeast backgrounds. To support our improved lipid identification workflow, we introduce a novel in-silico lipidomics library covering major lipid classes and compare searches using our novel library to searches with existing in-silico lipidomics libraries. MAVEN2 source code and cross-platform application installers are freely available for download from GitHub under a GNU permissive license [ver 3], as are the in silico lipidomics libraries and corresponding code repository.

Challenges and opportunities for prevention and removal of unwanted variation in lipidomic studies

Large 'omics studies are of particular interest to population and clinical research as they allow elucidation of biological pathways that are often out of reach of other methodologies. Typically, these information rich datasets are produced from multiple coordinated profiling studies that may include lipidomics, metabolomics, proteomics or other strategies to generate high dimensional data. In lipidomics, the generation of such data presents a series of unique technological and logistical challenges; to maximize the power (number of samples) and coverage (number of analytes) of the dataset while minimizing the sources of unwanted variation. Technological advances in analytical platforms, as well as computational approaches, have led to improvement of data quality - especially with regard to instrumental variation. In the small scale, it is possible to control systematic bias from beginning to end. However, as the size and complexity of datasets grow, it is inevitable that unwanted variation arises from multiple sources, some potentially unknown and out of the investigators control. Increases in cohort sizes and complexity has led to new challenges in sample collection, handling, storage, and preparation stages. If not considered and dealt with appropriately, this unwanted variation may undermine the quality of the data and reliability of any subsequent analysis. Here we review the various experimental phases where unwanted variation may be introduced and review general strategies and approaches to handle this variation, specifically addressing issues relevant to lipidomics studies.

Online monitoring of small volume reactions using compact liquid chromatography instrumentation

A wide variety of analytical techniques have been employed for monitoring chemical reactions, with online instrumentation providing additional benefits compared to offline analysis. A challenge in the past for online monitoring has been placement of the monitoring instrumentation as close as possible to the reaction vessel to maximize sampling temporal resolution and preserve sample composition integrity. Furthermore, the ability to sample very small volumes from bench-scale reactions allows the use of small reaction vessels and conservation of expensive reagents. In this study, a compact capillary LC instrument was used for online monitoring of as small as 1 mL total volume of a chemical reaction mixture, with automated sampling of nL-scale volumes directly from the reaction vessel used for analysis. Analyses to demonstrate short term (~2 h) and long term (~ 50 h) reactions were conducted using tandem on-capillary ultraviolet absorbance followed by in-line MS detection or ultraviolet absorbance detection alone, respectively. For both short term and long term reactions (10 and 250 injections, respectively), sampling approaches using syringe pumps minimized the overall sample loss to ~0.2% of the total reaction volume.