Development of a NanoLC-MS workflow for high-sensitivity global lipidomic analysis

Impact of Exposure to a Mixture of Organophosphate Esters on Adrenal Cell Phenotype, Lipidome, and Function

Organophosphate esters (OPEs) are used primarily as flame retardants and plasticizers. Previously, we reported that adrenal cells are important targets of individual OPEs. However, real-life exposures are to complex mixtures of these chemicals. To address this, we exposed H295R human adrenal cells to varying dilutions (1/1000K to 1/3K) of a Canadian household dust-based OPE mixture for 48 hours and evaluated effects on phenotypic, lipidomic, and functional parameters. Using a high-content screening approach, we assessed phenotypic markers at mixture concentrations at which there was greater than 70% cell survival; the most striking effect of the OPE mixture was a 2.5-fold increase in the total area of lipid droplets. We then determined the response of specific lipid species to OPE exposures with novel, nontargeted lipidomic analysis of isolated lipid droplets. These data revealed that house dust OPEs induced concentration-dependent alterations in the composition of lipid droplets, particularly affecting the triglyceride, diglyceride, phosphatidylcholine, and cholesterol ester subclasses. The steroid-producing function of adrenal cells in the presence or absence of a steroidogenic stimulus, forskolin, was determined. While the production of 17β-estradiol remained unaffected, a slight decrease in testosterone production was observed after stimulation. Conversely, a 2-fold increase in both basal and stimulated cortisol and aldosterone production was observed. Thus, exposure to a house dust-based mixture of OPEs exerts endocrine-disrupting effects on adrenal cells, highlighting the importance of assessing the effects of environmentally relevant mixtures.

Development of a single mobile phase for LC-IM-MS-based discovery lipidomics and metabolic phenotyping: Application to methapyrilene hepatotoxicity in the rat

The untargeted global profiling of endogenous metabolites and lipids has the potential to increase knowledge and understanding in many areas of biology. LC-MS/MS is a key technology for such analyses however, several different LC methodologies, using different mobile phase compositions, are required to cover the diversity in polarity and analyte structure encountered in biological samples. Most notably many lipid screening methods make use of isopropanol (IPA) as a major component of mobile phases employed for comprehensive lipidomic profiling. In order to increase laboratory efficiency, and minimize opportunities for errors, a suite of methods, based on a single acetonitrile (ACN)-aqueous buffer mobile phase combination, has been developed. This mobile phase can be used for hydrophobic interaction liquid chromatography on an amide stationary phase (for polar analytes), reversed-phase (RP) LC analysis on a C8 stationary phase (for moderately polar-non-polar compounds) and RPLC using a CSH phenyl-hexyl bonded column (for lipids). All of these sub 10 minute separations had good throughput and reproducibility with CV's of analyte response <25 % whilst eliminating the need for complex mobile phase preparation and the use of IPA as an organic modifier for lipidomics. Advantages of removing IPA and replacing it with the ACN-based method were a 58 % increase in peak capacity for lipids, with improved resolution for the di- and triglycerides and cholesterol esters compared to current methods. Compared to the IPA-containing solvent system the ACN-based mobile phase also resulted in a 61 % increase in lipid feature detection. The utility of this "universal" mobile phase approach was demonstrated by its application to a rat toxicology study investigating the consequences of methapyrilene administration through on the endogenous metabolite profiles of plasma and urine. Methapyrilene and its metabolites were also profiled in these samples.

High-Throughput Microbore LC-MS Lipidomics to Investigate APOE Phenotypes

Microflow liquid chromatography interfaced with mass spectrometry (μLC-MS/MS) is increasingly applied for high-throughput profiling of biological samples and has been proven to have an acceptable trade-off between sensitivity and reproducibility. However, lipidomics applications are scarce. We optimized a μLC-MS/MS system utilizing a 1 mm inner diameter × 100 mm column coupled to a triple quadrupole mass spectrometer to establish a sensitive, high-throughput, and robust single-shot lipidomics workflow. Compared to conventional lipidomics methods, we achieve a ∼4-fold increase in response, facilitating quantification of 351 lipid species from a single iPSC-derived cerebral organoid during a 15 min LC-MS analysis. Consecutively, we injected 303 samples over ∼75 h to prove the robustness and reproducibility of the microflow separation. As a proof of concept, μLC-MS/MS analysis of Alzheimer's disease patient-derived iPSC cerebral organoid reveals differential lipid metabolism depending on APOE phenotype (E3/3 vs E4/4). Microflow separation proves to be an environmentally friendly and cost-effective method as it reduces the consumption of harmful solvents. Also, the data demonstrate robust, in-depth, high-throughput performance to enable routine clinical or biomedical applications.

A highly sensitive method for determination of tacrolimus in peripheral blood mononuclear cells by nano liquid chromatography-high resolution accurate mass spectrometry

The determination of intracellular tacrolimus concentration in peripheral blood mononuclear cells (PBMCs) is crucial for assessing the effect-site concentration of tacrolimus. Analytical methods previously reported required a minimum of 3 mL of whole blood sample for measuring the tacrolimus concentration. In this study, we developed a highly sensitive method using EASY nLC 1200 combined with Q Exactive orbitrap mass spectrometer for detecting tacrolimus in PBMCs, requiring only 0.5-2 mL of sample. Furthermore, we compared two primary normalization methods for PBMCs tacrolimus concentration using Passing-Bablok regression, Bland-Altman analysis, Spearman's rank correlation, and Mountain plot. The newly established method was employed to compare tacrolimus concentrations in whole blood and PBMCs among 194 lung transplant recipients. The developed method exhibited high sensitivity with a lower limit of quantitation at 5 pg/mL, and excellent intra- and inter-days accuracy and precision. The comparison between different normalization methods for PBMCs tacrolimus concentration revealed a strong correlation between PBMCs count and intracellular protein amount within these cells. This finding suggests that both PBMCs count and intracellular protein amount can be used for normalizing intracellular tacrolimus levels and can be mutually converted. However, a weaker correlation was observed between PBMCs and whole-blood tacrolimus concentrations in lung transplant recipients, warranting further investigation. The method reported herein enables the quantification of PBMCs tacrolimus concentration using smaller volumes of whole blood samples, which has significant implications for both patients and laboratory personnel.

Performance comparison of narrow-bore and capillary liquid-chromatography for non-targeted metabolomics profiling by HILIC-QTOF-MS

Clinical metabolomics studies often have to cope with limited sample amounts, thus miniaturized liquid chromatography (LC) systems are a promising alternative. Their applicability has already been demonstrated in various fields, including a few metabolomics studies that mainly used reversed-phase chromatography. However, hydrophilic interaction chromatography (HILIC), which is widely used in metabolomics due to its particular suitability for the analysis of polar molecules, has rarely been tested for miniaturized LC-MS analysis of small molecules. In the present work, the suitability of a capillary HILIC (CapHILIC)-QTOF-MS system for non-targeted metabolomics was evaluated based on extracts of porcine formalin-fixed, paraffin-embedded (FFPE) tissue samples. The performance was assessed with respect to the number and retention time span of metabolic features as well as the analytical repeatability, the signal-to-noise ratio and the signal intensity of 16 annotated metabolites from different compound classes. The results were compared with a well established narrow-bore HILIC-QTOF-MS system. Both platforms have detected a similar number of features and performed excellent with respect to retention time stability (median RT span <0.05 min) and analytical repeatability (>75% of features with CV < 20%). The signal areas of all metabolites assessed were increased up to 18-fold by the use of CapHILIC, although the signal-to-noise ratio was only improved for 50% of the metabolites. An even better reproducibility (median CV = 5.2%) and up to 80-fold increase in signal intensity were observed after optimization of CapHILIC conditions for analysis of bile acid standard solutions. Even though the observed improvement for specific bile acids (e.g. taurocholic acid) in biological matrix needs to be evaluated, the platform comparison indicates, that the tested CapHILIC system is particularly suitable for analyses of a less broad metabolite spectrum, and specifically optimized chromatography.

The metabolic and lipidomic profiling of the effects of tracheal occlusion in a rabbit model of congenital diaphragmatic hernia

PURPOSE

Fetal tracheal occlusion (TO) reverses the pulmonary hypoplasia associated with congenital diaphragmatic hernia (CDH), but its mechanism of action remains poorly understood. 'Omic' readouts capture metabolic and lipid processing function, which aid in understanding CDH and TO metabolic mechanisms.

METHODS

CDH was created in fetal rabbits at 23 days, TO at 28 days and lung collection at 31 days (Term ∼32 days). Lung-body weight ratio (LBWR) and mean terminal bronchiole density (MTBD) were determined. In a cohort, left and right lungs were collected, weighed, and samples homogenized, and extracts collected for non-targeted metabolomic and lipidomic profiling via LC-MS and LC-MS/MS, respectively.

RESULTS

LBWR was significantly lower in CDH while CDH + TO was similar to controls (p = 0.003). MTBD was significantly higher in CDH fetuses and restored to control and sham levels in CDH + TO (p < 0.001). CDH and CDH + TO resulted in significant differences in metabolome and lipidome profiles compared to sham controls. A significant number of altered metabolites and lipids between the controls and CDH groups and the CDH and CDH + TO fetuses were identified. Significant changes in the ubiquinone and other terpenoid-quinone biosynthesis pathway and the tyrosine metabolism pathway were observed in CDH + TO.

CONCLUSION

CDH + TO reverses pulmonary hypoplasia in the CDH rabbit, in association with a specific metabolic and lipid signature. A synergistic untargeted 'omics' approach provides a global signature for CDH and CDH + TO, highlighting cellular mechanisms among lipids and other metabolites, enabling comprehensive network analysis to identify critical metabolic drivers in disease pathology and recovery.

TYPE OF STUDY

Basic Science, Prospective.

LEVEL OF EVIDENCE

II.

Vascular lipidomics analysis reveales increased levels of phosphocholine and lysophosphocholine in atherosclerotic mice

OBJECTIVE

Atherosclerosis (AS) is the major cause of cardiovascular disease, and dyslipidemia is a principal determinant of the initiation and progression of AS. Numerous works have analyzed the lipid signature of blood, but scarce information on the lipidome of vascular tissue is available. This study investigated the lipid profile in the aorta of ApoE^-/- mice.

METHOD

ApoE^-/- mice were randomly divided into two groups: (1) the normal diet (ND) group and (2) the high-fat diet (HFD) group. After feeding for 8 weeks, the plasma low-density lipoprotein (LDL), total cholesterol (TC), and triglyceride (TGs) levels were measured. UHPLC-Q Exactive plus MS was used to assess the lipid profile using both positive and negative ionization modes.

RESULTS

LDL and TC levels were significantly increased in HFD mice, and lipid deposition, plaque area and collagen fiber levels were increased in HFD group. In addition, a total of 131 differential lipids were characterized, including 57 lipids with levels that were increased in the HFD group and 74 with levels that were decreased. Further analysis revealed that the levels of several differentially expressed phosphocholines (PCs) and lysophosphocholines (LPCs) were significantly increased. These PCs included PC (38:3), PC (36:4), PC (36:3), PC (36:2), PC (36:1), PC (34:1e), PC (34:1), PC (32:1), PC (18:0/18:1), and PC (38:5), and the LPCs included LPC (18:1), LPC (18:0) and LPC (16:0).

CONCLUSION

Our findings indicate the presence of a comprehensive lipid profile in the vascular tissue of atherosclerotic mice, particularly involving PC and LPC, which exhibited significantly increased levels in AS.

Two-dimensional liquid chromatography-mass spectrometry for lipidomics using off-line coupling of hydrophilic interaction liquid chromatography with 50 cm long reversed phase capillary columns

Comprehensive characterization of the lipidome remains a challenge requiring development of new analytical approaches to expand lipid coverage in complex samples. In this work, offline two-dimensional liquid chromatography-mass spectrometry was investigated for lipidomics from human plasma. Hydrophilic interaction liquid chromatography was implemented in the first dimension to fractionate lipid classes. Nine fractions were collected and subjected to a second-dimension separation utilizing 50 cm capillary columns packed with 1.7 µm C18 particles operated on custom-built instrumentation at 35 kpsi. Online coupling with time-of-flight mass spectrometry allowed putative lipid identification from precursor-mass based library searching. The method had good orthogonality (fractional coverage of ∼40%), achieved a peak capacity of approximately 1900 in 600 min, and detected over 1000 lipids from a 5 µL injection of a human plasma extract while consuming less than 3 mL of solvent. The results demonstrate the expected gains in peak capacity when employing long columns and two-dimensional separations and illustrate practical approaches for improving lipidome coverage from complex biological samples.

A multi-species direct-fed microbial supplement alters the milk lipidome of dairy cows

The study evaluated the effects of supplementing a multi-species direct-fed microbial (DFM) on the milk lipidome of lactating dairy cows. Twenty-four multiparous Holstein cows (41 ± 7 d in milk) were used in a randomized complete block design with experimental duration of 91 d. Cows were blocked based on energy-corrected milk yield from a 14-d pretreatment period, and were assigned randomly within each block to the following treatments: (1) control (CON): corn silage-based total mixed ration without DFM; or (2) BOV+: basal diet top-dressed with a DFM containing a mixture of Lactobacillus animalis (LA-51), Propionibacterium freudenreichii (PF-24), Bacillus subtilis (CH201), and Bacillus licheniformis (CH200) at 11.8 × 109 cfu/d. Milk samples were taken from morning and evening milkings on 2 consecutive days of each week of the pretreatment and treatment periods. Separate composites of pretreatment period and treatment period samples were prepared for individual cows and used for lipidome analysis. Lipidome analysis of the milk samples was performed using an ultra-high-performance liquid chromatograph linked to a quadrupole time-of-flight mass spectrometer in both positive and negative ionizations. The relative concentrations of 14 lipid species, including long-chain polyunsaturated fatty acids (LC-PUFA) such as FA 20:8 and FA 28:7 and triacylglycerides (TG) such as TG 40:3 and TG 54:2, were increased [false discovery rate (FDR) ≤0.05], whereas 13 lipid species, including saturated FA 24:0 and TG 40:0 were decreased (FDR ≤0.05) by supplemental BOV+. The relative concentration of de novo FA in milk was greater, whereas that of preformed FA was lower in dairy cows supplemented with BOV+. Results from this study demonstrate the potential of a DFM containing L. animalis, P. freudenreichii, Bacillus subtilis, and B. licheniformis to alter the milk lipidome in lactating dairy cows toward increased relative concentration of LC-PUFA, which might offer a healthier profile of FA to consumers with its associated health benefits.

Systematic Investigation of LC Miniaturization to Increase Sensitivity in Wide-Target LC-MS-Based Trace Bioanalysis of Small Molecules

Covering a wide spectrum of molecules is essential for global metabolome assessment. While metabolomics assays are most frequently carried out in microbore LC-MS analysis, reducing the size of the analytical platform has proven its ability to boost sensitivity for specific -omics applications. In this study, we elaborate the impact of LC miniaturization on exploratory small-molecule LC-MS analysis, focusing on chromatographic properties with critical impact on peak picking and statistical analysis. We have assessed a panel of small molecules comprising endogenous metabolites and environmental contaminants covering three flow regimes—analytical, micro-, and nano-flow. Miniaturization to the micro-flow regime yields moderately increased sensitivity as compared to the nano setup, where median sensitivity gains around 80-fold are observed in protein-precipitated blood plasma extract. This gain resulting in higher coverage at low µg/L concentrations is compound dependent. At the same time, the nano-LC-high-resolution mass spectrometry (HRMS) approach reduces the investigated chemical space as a consequence of the trap-and-elute nano-LC platform. Finally, while all three setups show excellent retention time stabilities, rapid gradients jeopardize the peak area repeatability of the nano-LC setup. Micro-LC offers the best compromise between improving signal intensity and metabolome coverage, despite the fact that only incremental gains can be achieved. Hence, we recommend using micro-LC for wide-target small-molecule trace bioanalysis and global metabolomics of abundant samples.

Maximizing MS/MS Acquisition for Lipidomics Using Capillary Separation and Orbitrap Tribrid Mass Spectrometer

Liquid chromatography-mass spectrometry (LC-MS) is a typical strategy for lipidomics analysis. Although capillary LC-MS is a common analytical technique for proteomics analysis, its application to lipidomics has been limited. In this study, we aim at improving lipid identifications achieved in a single LC-MS analysis by a 3-fold approach: capillary LC and nanoelectrospray for enhanced ionization, ion trap for higher sensitivity tandem MS, and parallelization of mass analyzers for increased speed of acquisition on an Orbitrap hybrid system. By applying the methods to a complex lipid mixture of human plasma, we identified and performed relative quantification on over 1500 lipids within a 60 min capillary LC-MS analysis.

Recent advances in microscale separation techniques for lipidome analysis

This review paper highlights the recent research on liquid-phase microscale separation techniques for lipidome analysis over the last 10 years, mainly focusing on capillary liquid chromatography (LC) and capillary electrophoresis (CE) coupled with mass spectrometry (MS). Lipids are one of the most important classes of biomolecules which are involved in the cell membrane, energy storage, signal transduction, and so on. Since lipids include a variety of hydrophobic compounds including numerous structural isomers, lipidomes are a challenging target in bioanalytical chemistry. MS is the key technology that comprehensively identifies lipids; however, separation techniques like LC and CE are necessary prior to MS detection in order to avoid ionization suppression and resolve structural isomers. Separation techniques using μm-scale columns, such as a fused silica capillary and microfluidic device, are effective at realizing high-resolution separation. Microscale separation usually employs a nL-scale flow, which is also compatible with nanoelectrospray ionization-MS that achieves high sensitivity. Owing to such analytical advantages, microscale separation techniques like capillary/microchip LC and CE have been employed for more than 100 lipidome studies. Such techniques are still being evolved and achieving further higher resolution and wider coverage of lipidomes. Therefore, microscale separation techniques are promising as the fundamental technology in next-generation lipidome analysis.

Opti-nQL: An Optimized, Versatile and Sensitive Nano-LC Method for MS-Based Lipidomics Analysis

Lipidomics is the comprehensive analysis of lipids in a given biological system. This investigation is often limited by the low amount and high complexity of biological samples, therefore highly sensitive lipidomics methods are required. Nanoflow-LC/MS offers extremely high sensitivity; however, it is challenging as a more demanding maintenance is often needed compared to conventional microflow-LC approaches. Here, we developed a sensitive and reproducible lipidomics LC method, termed Opti-nQL, which can be applied to any biological system. Opti-nQL has been validated with cellular lipid extracts of human and mouse origin and with different lipid extraction methods. Among the resulting 4000 detected features, 700 and even more unique lipid molecular species have been identified covering 16 lipid sub-classes, while 400 lipids were uniquely structure defined by MS/MS. These results were obtained by analyzing an amount of lipids extract equivalent to 40 ng of proteins, being highly suitable for low abundant samples. MS analysis showed that theOpti-nQL method increases the number of identified lipids, which is evidenced by injecting 20 times less material than in microflow based chromatography, being more reproducible and accurate thus enhancing robustness of lipidomics analysis.

A Distinctive Human Metabolomics Alteration Associated with Osteopenic and Osteoporotic Patients

Osteoporosis is a common progressive metabolic bone disease resulting in decreased bone mineral density (BMD) and a subsequent increase in fracture risk. The known bone markers are not sensitive and specific enough to reflect the balance in the bone metabolism. Finding a metabolomics-based biomarker specific for bone desorption or lack of bone formation is crucial for predicting bone health earlier. This study aimed to investigate patients' metabolomic profiles with low BMD (LBMD), including those with osteopenia (ON) and osteoporosis (OP), compared to healthy controls. An untargeted mass spectrometry (MS)-based metabolomics approach was used to analyze serum samples. Results showed a clear separation between patients with LBMD and control (Q² = 0.986, R² = 0.994), reflecting a significant difference in the dynamic of metabolic processes between the study groups. A total of 116 putatively identified metabolites were significantly associated with LBMD. Ninety-four metabolites were dysregulated, with 52 up- and 42 downregulated in patients with LBMD compared to controls. Histidine metabolism, aminoacyl-tRNA biosynthesis, glyoxylate, dicarboxylate metabolism, and biosynthesis of unsaturated fatty acids were the most common metabolic pathways dysregulated in LBMD. Furthermore, 35 metabolites were significantly dysregulated between ON and OP groups, with 11 up- and 24 downregulated in ON compared to OP. Among the upregulated metabolites were 3-carboxy-4-methyl-5-propyl-2-2furanopropionic acid (CMPF) and carnitine derivatives (i.e., 3-hydroxy-11-octadecenoylcarnitine, and l-acetylcarnitine), whereas phosphatidylcholine (PC), sphingomyelin (SM), and palmitic acid (PA) were among the downregulated metabolites in ON compared to OP. This study would add a layer to understanding the possible metabolic alterations associated with ON and OP. Additionally, this identified metabolic panel would help develop a prediction model for bone health and OP progression.

Comprehensive Serum Lipidomics for Detecting Incipient Dementia in Parkinson's Disease

While a number of methods are available for analyzing lipids, unbiased untargeted lipidomics with high coverage remains a challenge. In this work, we report a study of isotope-standard-assisted liquid chromatography mass spectrometry lipidomics of serum for biomarker discovery. We focus on Parkinson's disease (PD), a neurodegenerative disorder that often progresses to dementia. Currently, the diagnosis of PD is purely clinical and there is limited ability to predict which PD patients will transition to dementia, hampering early interventions. We studied serum samples from healthy controls and PD patients with no clinical signs of dementia. A follow-up 3 years later revealed that a subset of PD patients had transitioned to dementia. Using the baseline samples, we constructed two biomarker panels to differentiate (1) PD patients from healthy controls and (2) PD patients that remained cognitively stable from PD patients with incipient dementia (diagnosed 3 years after sample collection). The proposed biomarker panels displayed excellent performance and may be useful for detecting prodromal PD dementia, allowing early interventions and prevention efforts. The biochemistry of significantly changed lipids is also discussed within the current knowledge of neurological pathologies. Our results are promising and future work using a larger cohort of samples is warranted.

Tissue Lipidomic Alterations Induced by Prolonged Dexamethasone Treatment

Dexamethasone is a synthetic glucocorticoid medication vastly used to treat abnormal immune responses and inflammation. Although the medication is well-established in the medical community, the prolonged treatment with high dosages of dexamethasone may lead to severe adverse effects through mechanisms that are not yet well-known. Lipids are a large class of hydrophobic molecules involved in energy storage, signaling, modulation of gene expression, and membranes. Hence, untargeted lipidomics may help unravel the biochemical alterations following prolonged treatment with high dosages of dexamethasone. We performed comprehensive lipidomic analyses of brain, heart, kidney, liver, and muscle samples obtained from rats that were treated with intramuscular injections of dexamethasone for 14 weeks compared to healthy controls. The employed methodology and statistical analysis showed that phosphatidic acids, glycerophospholipids, plasmalogens, and fatty acids are deeply affected by prolonged use of the medication. Brain tissue was only mildly affected, but skeletal muscle showed a strong accumulation of lipids that may be correlated with alterations in the energy metabolism, myopathy, and oxidative processes. This work provides new insights into the mechanisms of action and adverse effects for one of the most commonly prescribed class of drugs in the world.

Lipidome Alterations Induced by Cystic Fibrosis, CFTR Mutation, and Lung Function

Cystic fibrosis is a genetic pathology characterized by abnormal accumulation of mucus in the respiratory, gastrointestinal, and reproductive tracts, caused by mutations in the CFTR gene. Although the classical presentation of the condition is well known, there is still a need for a better characterization of metabolic alterations related to cystic fibrosis and different genotypic mutations. We employed untargeted, comprehensive lipidomics of blood serum samples to investigate alterations in the lipid metabolism related to the pathology, mutation classes, and lung function decline. Six unique biomarker candidates were able to independently differentiate diseased individuals from healthy controls with excellent performance. Cystic fibrosis patients showed dyslipidemia for most lipid subclasses, with significantly elevated odd-chain and polyunsaturated fatty acyl lipids. Phosphatidic acids and diacylglycerols were particularly affected by different genotypic mutation classes. We selected a biomarker panel composed of four lipids, including two ceramides, one sphingomyelin, and one fatty acid, which correctly classified all validation samples from classes III and IV. A biomarker panel of five oxidized lipids was further selected to differentiate patients with reduced lung function, measured as predicted FEV1%. Our results indicate that cystic fibrosis is deeply related to lipid metabolism and provide new clues for the investigation of the disease mechanisms and therapeutic targets.